1
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He J, Li L, Hu H. Causal associations between circulating metabolites and chronic kidney disease: a Mendelian randomization study. Ren Fail 2025; 47:2498090. [PMID: 40302304 PMCID: PMC12044913 DOI: 10.1080/0886022x.2025.2498090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2024] [Revised: 03/30/2025] [Accepted: 04/13/2025] [Indexed: 05/02/2025] Open
Abstract
BACKGROUND Circulating metabolites have been associated with cross-sectional renal function in population-based research. Nevertheless, there is currently little proof to support the idea that metabolites either cause or prevent renal function. New treatment targets and ways to screen individuals with impaired renal function will be made possible via an in-depth analysis of the causal relationship between blood metabolites and renal function. METHODS We assessed the causal relationship between 452 serum metabolites and six renal phenotypes (CKD, rapid progression to CKD [CKDi25], rapid eGFR decline [CKD rapid3], dialysis, estimated glomerular filtration rate, and blood urea nitrogen) using univariate Mendelian randomization, primarily employing the inverse variance weighted method with robust sensitivity analyses. Heterogeneity and pleiotropy were examined via Cochrane's Q test and MR-Egger regression, and statistical significance was adjusted using Bonferroni correction. To assess potential adverse effects of metabolite modulation, we conducted a phenome-wide Mendelian randomization analysis, followed by multivariate Mendelian randomization to adjust for confounders. RESULTS We identified glycine and N-acetylornithine as potential causal mediators of CKD and renal dysfunction. Notably, lowering glycine levels may increase the risk of cholelithiasis and cholecystitis, while reducing N-acetylornithine could have unintended effects on tinnitus. CONCLUSION Glycine and N-acetylornithine represent promising therapeutic targets for CKD and renal function preservation, but their modulation requires careful risk-benefit assessment to avoid adverse effects.
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Affiliation(s)
- Jie He
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P.R. China
| | - Lin Li
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P.R. China
| | - Hongjie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P.R. China
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2
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Su T, Xia Y. A quantitative comparison of the deleteriousness of missense and nonsense mutations using the structurally resolved human protein interactome. Protein Sci 2025; 34:e70155. [PMID: 40384578 PMCID: PMC12086521 DOI: 10.1002/pro.70155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2025] [Revised: 04/02/2025] [Accepted: 04/22/2025] [Indexed: 05/20/2025]
Abstract
The complex genotype-to-phenotype relationships in Mendelian diseases can be elucidated by mutation-induced disturbances to the networks of molecular interactions (interactomes) in human cells. Missense and nonsense mutations cause distinct perturbations within the human protein interactome, leading to functional and phenotypic effects with varying degrees of severity. Here, we structurally resolve the human protein interactome at atomic-level resolutions and perform structural and thermodynamic calculations to assess the biophysical implications of these mutations. We focus on a specific type of missense mutation, known as "quasi-null" mutations, which destabilize proteins and cause similar functional consequences (node removal) to nonsense mutations. We propose a "fold difference" quantification of deleteriousness, which measures the ratio between the fractions of node-removal mutations in datasets of Mendelian disease-causing and non-pathogenic mutations. We estimate the fold differences of node-removal mutations to range from 3 (for quasi-null mutations with folding ΔΔG ≥2 kcal/mol) to 20 (for nonsense mutations). We observe a strong positive correlation between biophysical destabilization and phenotypic deleteriousness, demonstrating that the deleteriousness of quasi-null mutations spans a continuous spectrum, with nonsense mutations at the extreme (highly deleterious) end. Our findings substantiate the disparity in phenotypic severity between missense and nonsense mutations and suggest that mutation-induced protein destabilization is indicative of the phenotypic outcomes of missense mutations. Our analyses of node-removal mutations allow for the potential identification of proteins whose removal or destabilization lead to harmful phenotypes, enabling the development of targeted therapeutic approaches, and enhancing comprehension of the intricate mechanisms governing genotype-to-phenotype relationships in clinically relevant diseases.
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Affiliation(s)
- Ting‐Yi Su
- Graduate Program in Quantitative Life SciencesMcGill UniversityMontréalQuébecCanada
| | - Yu Xia
- Graduate Program in Quantitative Life SciencesMcGill UniversityMontréalQuébecCanada
- Department of BioengineeringMcGill UniversityMontréalQuébecCanada
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3
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Gao S, Xiao AY, Zou S, Li T, Deng H, Wang Y. Exploring causal links in the gut-brain axis: a Mendelian randomization study of gut microbiota, metabolites, and cognition. Food Funct 2025. [PMID: 40423497 DOI: 10.1039/d4fo04366a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2025]
Abstract
The causal mediation effects of metabolites between gut microbiota and cognitive phenotypes remain unclear. Guided by the gut-brain axis mechanism, this study employed systematic Mendelian randomization (MR) to investigate these mediation pathways and their implications for functional food development. Univariate MR analysis was performed to estimate the causality of 211 gut microbial taxa (n = 18 340) and 452 serum metabolites (n = 7824) on general cognitive (n = 257 700), non-cognitive (n = 510 795), and specific cognitive phenotypes (n ≈ 2500) using genome-wide association study data. Inverse-variance weighted estimation was adopted as the primary method, with MR sensitivity analyses performed to complement the results. Metabolic pathway analysis was employed to enrich metabolic profiles, while two-step MR was used to screen mediation pathways. We revealed seven causal associations between microbiotas or metabolites and cognitive phenotypes (FDR < 0.05). Increased abundance of the order Clostridiales id.1863 was associated with better cognitive traits (OR = 1.14, 95%CI = 1.06-1.22, P = 2.06 × 10-4), while 1-linoleoylglycerophosphoethanolamine was also positively associated with cognitive traits (OR = 1.61, 95%CI = 1.33-1.95, P = 8.17 × 10-7). Seven significant metabolic pathways were enriched, including alpha-linolenic acid and linoleic acid metabolism, highlighting the potential role of omega-3 and omega-6 fatty acids in cognitive health. We further identified two significant mediation pathways linking the gut microbiota to cognitive phenotypes through metabolites. Notably, homostachydrine (39.1%) was found to mediate a proportion of the impact of the genus Turicibacter on emotion recognition (indirect effect: β = 0.105, 95%CI = 0.006-0.259, p = 2.60 × 10-2). This study provides evidence for causal relationships between gut microbiota, serum metabolites, and cognitive function, supporting the gut-brain axis mechanism. Our findings suggest potential targets for the development of functional food and personalized nutrition to improve cognitive health.
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Affiliation(s)
- Sunan Gao
- School of Statistics, Renmin University of China, Beijing, China
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Angela Y Xiao
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Siyu Zou
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
- School of Public Health, Peking University, Beijing, China
| | - Tongxu Li
- School of Statistics, Renmin University of China, Beijing, China
| | - Heming Deng
- School of Statistics, Renmin University of China, Beijing, China
| | - Yu Wang
- Center for Applied Statistics, Renmin University of China, Beijing, China.
- School of Statistics, Renmin University of China, Beijing, China
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4
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MULTI consortium, Anagnostakis F, Ko S, Saadatinia M, Wang J, Davatzikos C, Wen J. Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk. Nat Commun 2025; 16:4871. [PMID: 40419465 DOI: 10.1038/s41467-025-59964-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Collaborators] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2025] [Accepted: 05/06/2025] [Indexed: 05/28/2025] Open
Abstract
Multi-organ biological aging clocks across different organ systems have been shown to predict human disease and mortality. Here, we extend this multi-organ framework to plasma metabolomics, developing five organ-specific metabolome-based biological age gaps (MetBAGs) using 107 plasma non-derivatized metabolites from 274,247 UK Biobank participants. Our age prediction models achieve a mean absolute error of approximately 6 years (0.25
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Affiliation(s)
| | - Filippos Anagnostakis
- Laboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA
| | - Sarah Ko
- Laboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA
| | - Mehrshad Saadatinia
- Laboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA
| | - Jingyue Wang
- Laboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
- Department of Radiology, Columbia University, New York, NY, USA.
- New York Genome Center (NYGC), New York, NY, USA.
- Department of Biomedical Engineering (BME), Columbia University, New York, NY, USA.
- Data Science Institute (DSI), Columbia University, New York, NY, USA.
- Zuckerman Institute, Columbia University, New York, NY, USA.
- Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID), Department of Radiology, Columbia University, New York, NY, USA.
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Collaborators
Andrew Zalesky, Ye Ella Tian, Luigi Ferrucci, Keenan A Walker, Wenjia Bai, Michael S Rafii, Paul Aisen,
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5
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Pang ZY, Zhu YB, Hu JX, Li XX, Gao YJ, Wang YY, Zhou Q, Li P. The impact of lipidome on intervertebral disk degeneration, low back pain, and sciatica: a Mendelian randomization study. Sci Rep 2025; 15:18045. [PMID: 40410311 PMCID: PMC12102376 DOI: 10.1038/s41598-025-99914-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2024] [Accepted: 04/23/2025] [Indexed: 05/25/2025] Open
Abstract
Degeneration of intervertebral discs is a significant factor in chronic lower back pain, impacting millions annually. Existing studies propose a potential link between lipids and disc disease, though causal relationships remain unclear. The objective of this study is to explore the causal connections between lipids, lower back pain, disc degeneration, and the risk of sciatica In this research, we utilized a comprehensive GWAS dataset encompassing 179 lipid traits to explore the causal connections between lipids and the susceptibility to conditions such as lower back pain (LBP), intervertebral disc degeneration (IVDD), and sciatica. To establish causality, we employed two-sample Mendelian randomization, supplemented by Bayesian model averaging for verification. Our assessment of diversity and mutual influence involved Cochran's Q test, MR-Egger intercept assessment, and MR-PRESSO. Additionally, we performed a sensitivity analysis by systematically excluding individual elements to gauge their impact on outcomes in Mendelian randomization. Lastly, bidirectional Mendelian randomization was conducted to explore potential inverse associations between lipids and IVDD. Analyzing 179 lipidomic features as exposures and IVDD, LBP, and sciatica as outcomes, this study reveals significant causal relationships of glycerophospholipids, sterols, and glycerolipids with the risk of IVDD, LBP, and sciatica. Phosphatidylcholine, triglycerides, and sterols consistently exerted risk influences on IVDD, while phosphatidylethanolamine (O-16:1_18:2) among glycerophospholipids exhibited a protective effect (OR: 0.927-0.998, P < 0.05). Regarding LBP, sphingomyelin (d38:2) in sphingolipids demonstrated a protective effect (OR: 0.925-0.997, P < 0.05). For sciatica, triglycerides exhibited a risk influence, with varying effects observed for phosphatidylcholine and sterols with different molecular structures. Notably, sterol ester (27:1/16:1) consistently showed a risk effect across all three conditions. Our research provides valuable insights into how certain lipids are linked to the risks of LBP, IVDD, and sciatica. Our findings indicate that phosphatidylcholine and triglycerides may increase the incidence of IVDD, LBP, and sciatica, suggesting potential adverse effects. In contrast, sphingomyelin appears to reduce the occurrence of LBP and sciatica, indicating a protective role. Sterol esters also show a protective effect against sciatica; however, the sterol ester (27:1/16:1) consistently demonstrates a detrimental impact on IVDD, LBP, and sciatica. Additionally, our study underscores the intricate nature of lipid metabolism concerning IVDD, LBP, and sciatica. It uncovers a range of structural variations among lipids and explores how these variations may lead to different effects across various molecular subtypes.
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Affiliation(s)
- Ze-Yu Pang
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China
| | - Yi-Bo Zhu
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China
| | - Jun-Xian Hu
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China
| | - Xiao-Xiao Li
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China
| | - Yong-Jian Gao
- Tissue Repairing and Biotechnology Research Center, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China
| | - Yi-Yang Wang
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China.
| | - Qiang Zhou
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China.
| | - Pei Li
- Department of Orthopedics, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China.
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6
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Zhang X, Zhu Z, Shen C, Tang G. The causal effects of systemic antioxidant capacity on male infertility: A two-sample mendelian randomization analysis. Sci Rep 2025; 15:17009. [PMID: 40379801 PMCID: PMC12084361 DOI: 10.1038/s41598-025-02243-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Accepted: 05/12/2025] [Indexed: 05/19/2025] Open
Abstract
The present research aimed to assess the potential causal relationship between systemic antioxidant capacity and male infertility using a two-sample Mendelian randomization approach. The primary MR analysis utilized the inverse variance weighted (IVW)method, supplemented by complementary analyses including MR-Egger, weighted mode, simple mode, and weighted median methods. For male infertility, the available summarized data were gained from the open database (IEU OPEN GWAS PROJECT), which includes a total of 680 male patients with infertility and 72,799 controls of European population.10 biomarkers related to systemic antioxidant capacity were examined to investigate their potential association with male infertility, including glutathione S-transferase (GST), superoxide dismutase(SOD), glutathione peroxidase(GPX), catalase (CAT), total bilirubin, albumin, α-tocopherol, ascorbate, retinol, and uric acid. MR analyses using IVW mode revealed that genetically determined systemic antioxidant capacity biomarkers had no causal effects on male infertility risk, including GST(OR = 1.08, 95%CI: 0.91-1.29, P = 0.35), SOD(OR = 0.83, 95%CI: 0.66-1.04, P = 0.11), GPX(OR = 1.12, 95%CI: 0.92-1.36,P = 0.26), CAT(OR = 1.04, 95%CI: 0.83-1.29, P = 0.75), total bilirubin(OR = 0.98, 95%CI: 0.94-1.01, P = 0.18), albumin(OR = 1.14, 95%CI: 0.73-1.76, P = 0.57), α-tocopherol(OR = 0.56, 95%CI: 0.03-9.38, P = 0.69), ascorbate(OR = 1.06, 95%CI: 0.24-4.60, P = 0.94), retinol(OR = 1.29, 95%CI: 0.34-4.96, P = 0.71), and uric acid (OR = 0.88, 95% CI : 0.67-1.17, P = 0.39). The current study found no significantly causal link between systemic antioxidant capacity and male infertility. Further research with larger sample sizes and data from different ethnicities is needed.
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Affiliation(s)
- Xiaolong Zhang
- Department of Urology, Shaoxing People's Hospital(The First Affiliated Hospital, Shaoxing University), 568 Zhongxing North Road, 312000, Shaoxing, Zhejiang, China
| | - Zhirong Zhu
- Department of Urology, Shaoxing People's Hospital(The First Affiliated Hospital, Shaoxing University), 568 Zhongxing North Road, 312000, Shaoxing, Zhejiang, China
| | - Chaodong Shen
- Department of Urology, Shaoxing People's Hospital(The First Affiliated Hospital, Shaoxing University), 568 Zhongxing North Road, 312000, Shaoxing, Zhejiang, China
| | - Guiliang Tang
- Department of Urology, Shaoxing People's Hospital(The First Affiliated Hospital, Shaoxing University), 568 Zhongxing North Road, 312000, Shaoxing, Zhejiang, China.
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7
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Lin S, Zhou D, Zhu H, Huang G, Yu M, Chen S, Wang J, Xia W. Genetic association between coffee consumption and multiple myeloma mediated by plasma metabolites: a Mendelian randomization study. Food Funct 2025. [PMID: 40375831 DOI: 10.1039/d4fo05696e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2025]
Abstract
Background: Multiple myeloma (MM) is a hematologic malignancy closely associated with diets and metabolic disorders, showing an increasing incidence trend. Genome-wide association studies (GWAS) contribute to exploring the causal relationships between diets, metabolites, and MM, thereby revealing biological mechanisms underlying cancer progression. Methods: This study included large-scale GWAS data for two diets, four metabolomics, and MM. The two-sample Mendelian randomization (MR) analysis was conducted to assess causalities between these dietary patterns, metabolites, and MM. The MR analysis primarily employed the inverse variance weighted (IVW) method, supported by multiple sensitivity analysis and reverse MR analysis to validate significant associations. Mediation analysis identified specific metabolites mediating the causal relationships between diets and MM. Results: Univariate MR analysis suggested that coffee consumption (ORIVW = 2.72; 95% CI: 1.21-6.10; PIVW = 0.015, P_fdr = 0.022), decaffeinated coffee consumption (ORIVW = 7.10; 95% CI: 1.33-37.87; PIVW = 0.022, P_fdr = 0.022), ground coffee consumption (ORIVW = 4.04; 95% CI: 1.25-13.02; PIVW = 0.019, P_fdr = 0.022), instant coffee consumption (ORIVW = 6.13; 95% CI: 1.95-19.34; PIVW = 0.002, P_fdr = 0.008), and coffee max liking (ORIVW = 2.94; 95% CI: 1.23-7.03; PIVW = 0.015, P_fdr = 0.035) were associated with increased MM risk. Metabolomic MR analysis identified 19 plasma metabolites, 1 blood and urine biomarker, and 4 plasma lipids with significant association with MM. Mediation analysis indicated that hippurate and cinnamoylglycine mediated 35.55% (P < 0.001) and 21.85% (P = 0.002) of the genetically predicted effect of coffee consumption on MM risk, respectively. Cinnamoylglycine contributed 12.63% (P = 0.042) to the total causal effect of ground coffee consumption on MM. Hippurate (21.43%, P < 0.001), 3-hydroxyhippurate (4.39%, P = 0.031), and cinnamoylglycine (8.79%, P = 0.010) mediated the genetically predicted impact of instant coffee consumption on MM risk. Metabolic pathway analysis suggested that glutathione metabolism significantly contributes to MM pathogenesis (P = 0.002, FDR < 0.05). Conclusions: Our findings support the adverse causal effects of various coffee consumption on MM risk, identifying hippurate, 3-hydroxyhippurate, and cinnamoylglycine as key mediators, driving the relationship potentially through the glutathione metabolism pathway.
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Affiliation(s)
- Shichong Lin
- School of Smart Health Care (School of Health & Medical), Zhejiang Dongfang Polytechnic, Zhejiang, China
- The First Affiliated Hospital, Wenzhou Medical University, Wenzhou 325000, People's Republic of China
| | - Dan Zhou
- School of Smart Health Care (School of Health & Medical), Zhejiang Dongfang Polytechnic, Zhejiang, China
| | - Hua Zhu
- School of Smart Health Care (School of Health & Medical), Zhejiang Dongfang Polytechnic, Zhejiang, China
| | - Gaoxiang Huang
- School of Smart Health Care (School of Health & Medical), Zhejiang Dongfang Polytechnic, Zhejiang, China
| | - Menglu Yu
- Department of Pediatric Surgery, Jinhua Central Hospital, Jinhua, China
| | - Shaomin Chen
- School of Smart Health Care (School of Health & Medical), Zhejiang Dongfang Polytechnic, Zhejiang, China
| | - Junjie Wang
- Department of Cardiovascular Medicine, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Wenzhou, China
| | - Weiqiang Xia
- Department of Gastroenterology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou 325200, China.
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8
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Yu K, Estonian Biobank Research Team, Estrada K, Esko T, Kals M, Nikopensius T, Kronberg J, Võsa U, Wuster A, Bomba L. Plasma Metabolic Outliers Identified in Estonian Human Knockouts. Metabolites 2025; 15:323. [PMID: 40422899 DOI: 10.3390/metabo15050323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2025] [Revised: 05/02/2025] [Accepted: 05/07/2025] [Indexed: 05/28/2025] Open
Abstract
Background/Objectives: Metabolomics, in combination with genetic data, is a powerful approach to study the biochemical consequences of genetic variation. We assessed the impact of human gene knockouts (KOs) on the metabolite levels of Estonia Biobank (EstBB) participants and integrated the results with electronic health record data. Methods: In 150,000 EstBB genotyped participants, we identified 723 KOs with 152 different predicted loss of function (pLoF) variants in 115 genes. For those KOs and 258 controls, 1387 metabolites were profiled using ultra-high-performance liquid chromatography-tandem mass spectrometry. Results: We identified 48 associations linking rare pLoF variants in 22 genes to 43 metabolites. Out of 48 associations, 27 (56%) were found in genes that cause inborn errors of metabolism. The top associations identified in our analysis included genes and metabolites involved in the degradation pathway of the pyrimidine bases uracil and thymine (DPYD and UPB1). We found DPYD gene KOs to be associated with elevated levels of Uracil, confirming that DPD-deficiency is a leading cause of severe 5-Fluorouracil toxicity. Overall, 54% of reported associations are gene targets of approved drugs or bioactive drug-like compounds. Conclusions: Our findings contribute to assessing the impact of human KOs on metabolite levels and offer insights into gene functions, disease mechanism, and drug target validation.
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Affiliation(s)
- Ketian Yu
- Genomics, BioMarin Pharmaceutical, Novato, CA 94949, USA
| | | | - Karol Estrada
- Genomics, BioMarin Pharmaceutical, Novato, CA 94949, USA
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Tiit Nikopensius
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Jaanika Kronberg
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Arthur Wuster
- Genomics, BioMarin Pharmaceutical, Novato, CA 94949, USA
| | - Lorenzo Bomba
- Genomics, BioMarin Pharmaceutical, Novato, CA 94949, USA
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9
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Liu Q, Shi R, Gu Y, Zhang J, Wang S, Xu T, Zhang Z, Tian J. The role of immune cell phenotypes and metabolites in the risk of ischemic stroke: a Mendelian randomization-based mediation analysis. BMC Neurol 2025; 25:196. [PMID: 40329249 PMCID: PMC12054204 DOI: 10.1186/s12883-025-04205-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 04/23/2025] [Indexed: 05/08/2025] Open
Abstract
BACKGROUND Ischemic stroke (IS) occurs when a blood clot obstructs a blood vessel supplying blood to the brain, leading to brain tissue damage due to insufficient oxygen and nutrients. The roles of immune cells and metabolites in IS are increasingly recognized, yet their specific mechanisms remain unclear. METHODS This study conducted a comprehensive statistical analysis to explore the relationships between immune cell phenotypes, metabolite levels, and IS. We utilized methods such as inverse variance weighted (IVW), weighted median, and MR Egger to ensure robust results. Sensitivity analyses were performed to confirm the absence of significant heterogeneity or pleiotropy. RESULTS We identified several immune cell phenotypes significantly associated with IS. Notably, IgD + CD24 + AC showed a positive association with IS (OR = 1.045601, p = 0.011562), while CD62L- HLA DR + + monocyte AC demonstrated a negative association (OR = 0.948673, p = 0.005415). Among metabolites, adenosine 5'-monophosphate (AMP) to cysteine ratio was positively associated with IS (OR = 1.083144, p = 0.000310), whereas xanthurenate levels were negatively associated (OR = 0.926100, p = 0.001614). Mediation analysis revealed a significant mediating effect of acetylcarnitine levels on the relationship between IgD + CD24 + AC and IS, with an estimated mediation effect of 0.00606 (p = 0.036834077). CONCLUSION Our study highlights the crucial roles of specific immune cell phenotypes and metabolites in IS, suggesting their potential as novel therapeutic targets or biomarkers. The mediation analysis underscores the complex interactions between immune cells and metabolites in IS, providing valuable insights for future research. These findings pave the way for further exploration of the pathophysiological mechanisms and therapeutic strategies for IS.
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Affiliation(s)
- Qiming Liu
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, 050091, China
| | - Rui Shi
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, 050091, China
| | - Yiting Gu
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, 050091, China
| | - Jiayun Zhang
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, 050091, China
| | - Shiduo Wang
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, 050091, China
| | - Tiantian Xu
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, 050091, China
| | - Zhe Zhang
- Department of Neurology, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, 050011, China
| | - Junbiao Tian
- Department of Neurology, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, 050011, China.
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10
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Cheng Y, Ruan X, Lu X, Yang Y, Wang Y, Yan S, Sun Y, Yan F, Jiang L, Liu T. Accounting for the impact of rare variants on causal inference with RARE: a novel multivariable Mendelian randomization method. Brief Bioinform 2025; 26:bbaf214. [PMID: 40370099 PMCID: PMC12078940 DOI: 10.1093/bib/bbaf214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Revised: 04/10/2025] [Accepted: 04/20/2025] [Indexed: 05/16/2025] Open
Abstract
Mendelian randomization (MR) method utilizes genetic variants as instrumental variables to infer the causal effect of an exposure on an outcome. However, the impact of rare variants on traits is often neglected, and traditional MR assumptions can be violated by correlated horizontal pleiotropy (CHP) and uncorrelated horizontal pleiotropy (UHP). To address these issues, we propose a multivariable MR approach, an extension of the standard MR framework: MVMR incorporating Rare variants Accounting for multiple Risk factors and shared horizontal plEiotropy (RARE). In the simulation studies, we demonstrate that RARE effectively detects the causal effects of exposures on outcome with accounting for the impact of rare variants on causal inference. Additionally, we apply RARE to study the effects of high density lipoprotein and low density lipoprotein on type 2 diabetes and coronary atherosclerosis, respectively, thereby illustrating its robustness and effectiveness in real data analysis.
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Affiliation(s)
- Yu Cheng
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
- Department of Bioinformatics and Computational Biology, The University of Texas, M.D. Anderson Cancer Center, #7007 Bertner Ave, Texas Medical Center, Houston 77030, TX, United States
| | - Xinjia Ruan
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
| | - Xiaofan Lu
- Department of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology, CNRS/INSERM/UNISTRA, #10142 BP, Illkirch 67400, Bas-Rhin, France
| | - Yuqing Yang
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
| | - Yuhang Wang
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
| | - Shangjin Yan
- High School Affiliated to Nanjing Normal University, #37 Chahar Road, Gulou District, Nanjing 210003, Jiangsu, China
| | - Yuzhe Sun
- Department of Biochemistry, Vassar college, Poughkeepsie, NY 12604, United States
| | - Fangrong Yan
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
| | - Liyun Jiang
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
| | - Tiantian Liu
- Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, #639 Longmian Ave, Jiangning District, Nanjing 211100, Jiangsu, China
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11
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Chen B, Pu B, Lin S, Li S, Dong H. Investigating the association between polyunsaturated fatty acids and osteomyelitis by Mendelian randomization. Sci Rep 2025; 15:14760. [PMID: 40295609 PMCID: PMC12037996 DOI: 10.1038/s41598-025-98502-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Accepted: 04/11/2025] [Indexed: 04/30/2025] Open
Abstract
Osteomyelitis, characterized by bone inflammation and infection, poses a significant global health burden. This Mendelian randomization (MR) study investigates the causal relationship between polyunsaturated fatty acids (PUFAs) and osteomyelitis risk. By using GWAS data from 114,999 individuals, we explore specific PUFAs and their genetic variations using Inverse variance weighted (IVW), MR-Egger and weighted median methods. The results reveal a suggestive association between genetically predicted higher docosahexaenoic acid (DHA) and omega-6 levels with increased osteomyelitis risk. Conversely, a negative association is found for the omega-6:3 ratio. Linoleic acid, omega-3, and omega-6 show no significant associations. Heterogeneity and pleiotropy analyses support result robustness, indicating minimal confounding effects. Sensitivity analyses confirm the stability of findings. Our MR analysis challenges the presumed protective role of omega-3 in osteomyelitis, suggesting a nuanced relationship where DHA may pose an increased risk. The study underscores the complexity of fatty acid interactions influenced by genetic variability and dietary nuances. Further research is essential to unravel underlying mechanisms and translate these findings into actionable strategies for osteomyelitis prevention and treatment.
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Affiliation(s)
- Baixing Chen
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Bin Pu
- Department of Orthopedics, Suining Traditional Chinese Medicine Hospital Affiliated to North Sichuan Medical College, Suining, Sichuan Province, China
| | - Shi Lin
- Shenzhen Pingle Orthopedic Hospital, Shenzhen, China
| | - Shaoshuo Li
- Wuxi Affiliated Hospital of Nanjing University of Traditional Chinese Medicine, Wuxi, China
| | - Hang Dong
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, China.
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12
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Yuan W, Liu Y, Liu C, Qiu Y. Serum metabolites and risk of sudden sensorineural hearing loss: A Mendelian randomization study. Braz J Otorhinolaryngol 2025; 91:101596. [PMID: 40288303 PMCID: PMC12056394 DOI: 10.1016/j.bjorl.2025.101596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Revised: 02/05/2025] [Accepted: 03/10/2025] [Indexed: 04/29/2025] Open
Abstract
OBJECTIVE Observational studies found that Sudden Sensorineural Hearing Loss (SSNHL) is associated with metabolic disorders, but the causal relationship remains unclear. Here we performed a two-sample Mendelian Randomization (MR) analysis to systematically assess the causation between blood metabolites and SSNHL. METHODS Summary statistics for blood metabolites were extracted from GWAS data of 7824 European participants on metabolite levels. GWAS data for SSNHL were collected from the FinnGen Consortium R10 release data, which consisted of 3128 cases and 362,353 controls in European populations. The inverse variance weighted method was the primary method for causality analysis while MR-Egger, weighted median and MR-RAPS served as complementary approaches. Cochran'sQ test, MR-Egger intercept test, MR-PRESSO, Radial MR, leave-one-out and Steiger test were used for sensitivity analyses. Additionally, we performed metabolic pathway analysis to further explore the potential pathogenesis of SSNHL. RESULTS We found that genetically predicted cholesterol, citrate, myristoleate (14:1n5) and tryptophan betaine may increase the risk of SSNHL, while stearate (18:0), pantothenate and glycerol 2-phosphate may act as protective factors for SSNHL. Nevertheless, these metabolites did not reach statistical significance after Bonferroni correction. Sensitivity analyses revealed no evidence of heterogeneity or horizontal pleiotropy. Metabolic pathway analysis revealed the pantothenate and CoA biosynthesis pathway and the citrate cycle pathway potentially related to the pathogenesis of SSNHL. CONCLUSION The findings of our study offer new insights into the role of blood metabolites in the development and pathogenesis of SSNHL and provide potential inspiration for further advancements in clinical settings. LEVEL OF EVIDENCE Level 3.
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Affiliation(s)
- Wenhui Yuan
- Central South University, Xiangya Hospital, Department of Otolaryngology Head and Neck Surgery, Changsha, China; Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, China; Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, China
| | - Yong Liu
- Central South University, Xiangya Hospital, Department of Otolaryngology Head and Neck Surgery, Changsha, China; Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, China; Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
| | - Chao Liu
- Central South University, Xiangya Hospital, Department of Otolaryngology Head and Neck Surgery, Changsha, China; Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, China; Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China.
| | - Yuanzheng Qiu
- Central South University, Xiangya Hospital, Department of Otolaryngology Head and Neck Surgery, Changsha, China; Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, China; Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China
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13
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Cheng C, Liu Y, Sun L, Fan J, Sun X, Zheng JS, Zheng L, Zhu Y, Zhou D. Integrative metabolomics and genomics reveal molecular signatures for type 2 diabetes and its cardiovascular complications. Cardiovasc Diabetol 2025; 24:166. [PMID: 40241080 PMCID: PMC12004867 DOI: 10.1186/s12933-025-02718-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2025] [Accepted: 03/29/2025] [Indexed: 04/18/2025] Open
Abstract
BACKGROUND Metabolites are pivotal in the biological process underlying type 2 diabetes (T2D) and its cardiovascular complications. Nevertheless, their contributions to these diseases have not been comprehensively evaluated, particularly in East Asian ancestry. This study aims to elucidate the metabolic underpinnings of T2D and its cardiovascular complications and leverage multi-omics integration to uncover the molecular pathways involved. METHOD This study included 1180 Chinese participants from the Zhejiang Metabolic Syndrome Cohort (ZMSC). A total of 1912 metabolites were profiled using high-coverage widely targeted and non-targeted metabolic techniques. Multivariable logistic regression models and orthogonal partial least squares discriminant analysis were used to identify T2D-related metabolites. A metabolome-wide genome-wide association study (GWAS) in ZMSC, followed by two-sample Mendelian randomization (MR) analyses, was conducted to explore potential causal metabolite-T2D associations. To enhance cross-ancestry generalizability, MR analyses were conducted in European ancestry to explore the potential causal effects of serum metabolites on T2D and its cardiovascular complications. Furthermore, multi-omics evidence was integrated to explore the underlying molecular mechanisms. RESULTS We identified six metabolites associated with T2D in Chinese, supported by metabolome analysis and genetic-informed causal inference. These included two potential protective factors (PC [O-16:0/0:0] and its derivative LPC [O-16:0]) and four potential risk factors ([R]-2-hydroxybutyric acid, 2-methyllactic acid, eplerenone, and rauwolscine). Cross-ancestry metabolome-wide analysis further revealed four shared potential causal metabolites, highlighting the potential protective role of creatine for T2D. Through multi-omics integration, we revealed a potential regulatory path initialized by a genetic variant near CPS1 (coding for a urea cycle-related mitochondrial enzyme) influencing serum creatine levels and subsequently modulating the risk of T2D. MR analyses further demonstrated that nine urea cycle-related metabolites significantly influence cardiovascular complications of T2D. CONCLUSION Our study provides novel insights into the metabolic underpinnings of T2D and its cardiovascular complications, emphasizing the role of urea cycle-related metabolites in disease risk and progression. These findings advance our understanding of circulating metabolites in the etiology of T2D, offering potential biomarkers and therapeutic targets for future research. RESEARCH INSIGHTS WHAT IS CURRENTLY KNOWN ABOUT THIS TOPIC?: Metabolites are crucial for understanding diabetes biology.Multi-omics integration aids in revealing complex mechanisms. WHAT IS THE KEY RESEARCH QUESTION?: How do serum metabolites affect diabetes and its cardiovascular outcomes? WHAT IS NEW?: Novel diabetes-related metabolites identified in Chinese populations.Consistent metabolites associated with diabetes and glycemic traits in East Asians and Europeans.Emphasizing the role of urea cycle pathway in cardiometabolic disease. HOW MIGHT THIS STUDY INFLUENCE CLINICAL PRACTICE?: Findings could guide diabetes prevention and personalized management strategies.
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Affiliation(s)
- Chunxiao Cheng
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, Zhejiang, China
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China
| | - Yuanjiao Liu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Lingyun Sun
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, Zhejiang, China
| | - Jiayao Fan
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, Zhejiang, China
| | - Xiaohui Sun
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Ju-Sheng Zheng
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou, 310024, China
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, 310024, China
- Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou, 310024, China
- Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China
| | - Lin Zheng
- Hangzhou Xihu District Health Supervision Institute, Hangzhou, 310030, Zhejiang, China.
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Dan Zhou
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, Zhejiang, China.
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, China.
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14
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Beer SA, Went M, Mills C, Wood C, Sud A, Allan JM, Houlston R, Kaiser MF. Mendelian randomization of immune cell phenotypes to discover potential drug targets for B-cell malignancy. Blood Cancer J 2025; 15:62. [PMID: 40199857 PMCID: PMC11979003 DOI: 10.1038/s41408-025-01277-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2024] [Revised: 03/28/2025] [Accepted: 04/01/2025] [Indexed: 04/10/2025] Open
Abstract
Although treatment options for B-cell malignancies have expanded, many patients continue to face limited response rates, highlighting an urgent need for new therapeutic targets. To prioritize candidate drug targets for B-cell malignancies, we employed Mendelian Randomization to estimate potentially causal relationships between 445 immune cell traits and six B-cell cancers: follicular lymphoma (FL), diffuse large B-cell lymphoma (DLBCL), Hodgkin lymphoma (HL), marginal zone lymphoma (MZL), chronic lymphocytic leukemia (CLL), and multiple myeloma (MM), totaling 22,922 cases and 394,204 controls. 163 traits showed a suggestive association with at least one B-cell malignancy (P < 0.05), with 34 traits being significant after correction for multiple testing (P < 2 × 10-4). By integrating findings with observational data and clinical trial evidence to support drug target candidacy, 24 cell surface markers were identified as druggable targets. In addition to established therapeutic targets such as CD3, CD20 and CD38, our analysis highlights BAFF-R and CD39 in HL, CD25 in MM, CD27 in CLL, CD80/86 in DLBCL, and CCR2 in FL and MZL as promising candidates for therapeutic inhibition. Our findings provide further support for the potential of human genetics to guide the identification of drug targets and address a productivity-limiting step.
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Affiliation(s)
- Sina A Beer
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.
| | - Molly Went
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Charlie Mills
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Codie Wood
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Amit Sud
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - James M Allan
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Richard Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Martin F Kaiser
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
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15
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Lin C, Xia M, Dai Y, Huang Q, Sun Z, Zhang G, Luo R, Peng Q, Li J, Wang X, Lin H, Gao X, Tang H, Shen X, Wang S, Jin L, Hao X, Zheng Y. Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites. CELL GENOMICS 2025; 5:100810. [PMID: 40118068 PMCID: PMC12008806 DOI: 10.1016/j.xgen.2025.100810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 01/22/2025] [Accepted: 02/17/2025] [Indexed: 03/23/2025]
Abstract
Differential susceptibilities to various diseases and corresponding metabolite variations have been documented across diverse ethnic populations, but the genetic determinants of these disparities remain unclear. Here, we performed large-scale genome-wide association studies of 171 directly quantifiable metabolites from a nuclear magnetic resonance-based metabolomics platform in 10,792 Han Chinese individuals. We identified 15 variant-metabolite associations, eight of which were successfully replicated in an independent Chinese population (n = 4,480). By cross-ancestry meta-analysis integrating 213,397 European individuals from the UK Biobank, we identified 228 additional variant-metabolite associations and improved fine-mapping precision. Moreover, two-sample Mendelian randomization analyses revealed evidence that genetically predicted levels of triglycerides in high-density lipoprotein were associated with a higher risk of coronary artery disease and that of glycine with a lower risk of heart failure in both ancestries. These findings enhance our understanding of the shared and specific genetic architecture of metabolites as well as their roles in complex diseases across populations.
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Affiliation(s)
- Chenhao Lin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; College of Food Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China
| | - Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yuxiang Dai
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Zhonghan Sun
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Guoqing Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; National Genomics Data Center& Bio-Med Big Data Center, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai 200031, China
| | - Ruijin Luo
- Shanghai Southgene Technology Co., Ltd., Shanghai 201203, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jinxi Li
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Xiaofeng Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; Fudan University-the People's Hospital of Rugao Joint Research Institute of Longevity and Aging, Rugao, Jiangsu 226500, China
| | - Huandong Lin
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Xia Shen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, Guangdong 511400, China
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Xingjie Hao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
| | - Yan Zheng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
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16
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Wang Z, Zhao C, Wang Z, Li M, Zhang L, Diao J, Chen J, Zhang L, Wang Y, Li M, Zhou Y, Xu H. Elucidating Causal Relationships Among Gut Microbiota, Human Blood Metabolites, and Knee Osteoarthritis: Evidence from a Two-Stage Mendelian Randomization Analysis. Rejuvenation Res 2025. [PMID: 40193247 DOI: 10.1089/rej.2024.0079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2025] Open
Abstract
Background: Although previous observational studies suggest a potential association between gut microbiota (GM) and knee osteoarthritis (KOA), the causal relationships remain unclear, particularly concerning the role of blood metabolites (BMs) as potential mediators. Elucidating these interactions is crucial for understanding the mechanisms underlying KOA progression and may inform the development of novel therapeutic strategies. Objective: This study aimed to determine the causal relationship between GM and KOA and to quantify the potential mediating role of BMs. Methods: Instrumental variables (IVs) for GM and BMs were retrieved from the MiBioGen consortium and metabolomics genome-wide association studies (GWAS) databases. KOA-associated single-nucleotide polymorphisms were sourced from the FinnGen consortium. Inverse-variance weighted approach was utilized as the main analytical method for Mendelian randomization (MR) analysis, complemented by MR-Egger, simple mode, weighted mode, and weighted median methods. The causal relationships between GM, BMs, and KOA were sequentially analyzed by multivariate MR. False discovery rate correction was applied to account for multiple comparisons in the MR results. Sensitivity analyses and reverse MR analysis were also conducted to verify the reliability of the findings. Finally, a two-step approach was employed to determine the proportion of BMs mediating the effects of GM on KOA. Results: MR analysis identified seven gut microbial species that are causally associated with KOA. Additionally, MR analysis of 1091 BMs and 309 metabolite ratios revealed 13 metabolites that influence the risk of KOA. Through two-step analysis, three BMs were identified as mediators of the effects of two GMs on KOA. Among them, 6-hydroxyindole sulfate exhibited the highest mediation percentage (10.26%), followed by N-formylanthranilic acid (6.55%). Sensitivity and reverse causality analyses further supported the robustness of these findings. Conclusion: This research identified specific GMs and BMs that have a causal association with KOA. These findings provide critical insights into how GM may influence KOA risk by modulating specific metabolites, which could be valuable for the targeted treatment and prevention of KOA.
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Affiliation(s)
- Zhen Wang
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
| | - Chi Zhao
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
- Tuina Department, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Zheng Wang
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
| | - Mengmeng Li
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
- Tuina Department, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Lili Zhang
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
| | - Jieyao Diao
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
| | - Juntao Chen
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
| | - Lijuan Zhang
- Rehabilitation Department, Jiaozuo Coal Industry (Group) Co. Ltd., Central Hospital, Jiaozuo, China
| | - Yu Wang
- College of Computer Science, Xidian University, Xian, China
| | - Miaoxiu Li
- College of Acupuncture and Massage, Shanghai University of Chinese Medicine, Shanghai, China
| | - Yunfeng Zhou
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
| | - Hui Xu
- College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, China
- Tuina Department, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
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17
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Zhao Y, Zheng R, Luo K, Zhao H, Xiang W. Association between erythritol and lung cancer: a two-sample Mendelian randomization study. Nutr Metab (Lond) 2025; 22:28. [PMID: 40197329 PMCID: PMC11978034 DOI: 10.1186/s12986-025-00916-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 03/14/2025] [Indexed: 04/10/2025] Open
Abstract
BACKGROUND Sweeteners have been widely added to food and beverages due to their low-calorie and sweetening properties. However, the role of sweeteners in cancer risk has been a subject of extensive debate over the past few decades. OBJECTIVE We aimed to elucidate the causation between the commonly used natural sweetener erythritol and the risk of lung cancer (LC) using Mendelian randomization (MR). METHODS Data on erythritol and its metabolites were obtained from publicly available genome-wide association studies data. Summary data on LC and its subtypes were obtained from a large-scale genetic study conducted by the Transdisciplinary Research of Cancer in Lung of the International Lung Cancer Consortium and the Lung Cancer Cohort Consortium. We conducted independent two-sample MR analyses to assess the causation between erythritol and LC and its subtypes. RESULTS The inverse variance weighted method of MR analysis showed no evidence supporting causation between erythritol and LC or its histological subtypes. Sensitivity analysis further supported the results. CONCLUSION Our study findings do not support genetic association between erythritol and LC or its subtypes.
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Affiliation(s)
- Yongsheng Zhao
- Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College, No. 1, South Maoyuan Road, Shunqing District, Nanchong City, 637000, Sichuan Province, China.
| | - Renyan Zheng
- Department of Integrated Western and Chinese Colorectal and Anal Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Kexin Luo
- Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College, No. 1, South Maoyuan Road, Shunqing District, Nanchong City, 637000, Sichuan Province, China
| | - Haiyang Zhao
- Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College, No. 1, South Maoyuan Road, Shunqing District, Nanchong City, 637000, Sichuan Province, China
| | - Wanping Xiang
- Department of Thoracic Surgery, Affiliated Hospital of North Sichuan Medical College, No. 1, South Maoyuan Road, Shunqing District, Nanchong City, 637000, Sichuan Province, China
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18
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Yu X, Chen Y, Lei L, Li P, Lin D, Shen Y, Hou C, Chen J, Fan Y, Jin Y, Lu H, Wu D, Xu Y. Mendelian randomization analysis of blood metabolites and immune cell mediators in relation to GVHD and relapse. BMC Med 2025; 23:201. [PMID: 40189523 PMCID: PMC11974087 DOI: 10.1186/s12916-025-04026-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Accepted: 03/19/2025] [Indexed: 04/09/2025] Open
Abstract
BACKGROUND Graft-versus-host disease (GVHD) and relapse are major complications following allogeneic hematopoietic stem cell transplantation (allo-HSCT). Metabolites play crucial roles in immune regulation, but their causal relationships with GVHD and relapse remain unclear. METHODS We utilized genetic variants from genome-wide association studies (GWAS) of 309 known metabolites as instrumental variables to evaluate their causal effects on acute GVHD (aGVHD), gut GVHD, chronic GVHD (cGVHD), and relapse in different populations. Multiple causal inference methods, heterogeneity assessments, and pleiotropy tests were conducted to ensure result robustness. Multivariable MR analysis was performed to adjust for potential confounders, and validation MR analysis further confirmed key findings. Mediation MR analysis was employed to explore indirect causal pathways. RESULTS After correction for multiple testing, we identified elevated pyridoxate and proline levels as protective factors against grade 3-4 aGVHD (aGVHD3) and relapse, respectively. Conversely, glycochenodeoxycholate increased the risk of aGVHD3, whereas 1-stearoylglycerophosphoethanolamine had a protective effect. The robustness and stability of these findings were confirmed by multiple causal inference approaches, heterogeneity, and horizontal pleiotropy analyses. Multivariable MR analysis further excluded potential confounding pleiotropic effects. Validation MR analyses supported the causal roles of pyridoxate and 1-stearoylglycerophosphoethanolamine, while mediation MR revealed that pyridoxate influences GVHD directly and indirectly via CD39 + Tregs. Pathway analyses highlighted critical biochemical alterations, including disruptions in bile acid metabolism and the regulatory roles of vitamin B6 derivatives. Finally, clinical metabolic analyses, including direct fecal metabolite measurements, confirmed the protective role of pyridoxate against aGVHD. CONCLUSIONS Our findings provide novel insights into the metabolic mechanisms underlying GVHD and relapse after allo-HSCT. Identified metabolites, particularly pyridoxate, may serve as potential therapeutic targets for GVHD prevention and management.
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Affiliation(s)
- Xinghao Yu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Yiyin Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Lei Lei
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Pengfei Li
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Dandan Lin
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Ying Shen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Chang Hou
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China
| | - Jia Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yi Fan
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yi Jin
- Department of Pharmacy, Wujin Hospital Affiliated with Jiangsu University, Changzhou, 213000, China
| | - Huimin Lu
- Department of Outpatient and Emergency, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Depei Wu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China.
| | - Yang Xu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, China.
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Zheng Z, Sun H, Zhang P, Cao F, Xiao X, Zhao T. Causal relationship between gut microbiota, metabolites, and short stature: a Mendelian randomization study. Pediatr Res 2025:10.1038/s41390-025-03985-3. [PMID: 40181144 DOI: 10.1038/s41390-025-03985-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2024] [Revised: 01/22/2025] [Accepted: 02/02/2025] [Indexed: 04/05/2025]
Abstract
BACKGROUND Previous evidence suggests close relationships between the gut microbiota and short stature, but the causal relationship between them remains unclear. Our study performed Mendelian randomization (MR) analysis to investigate the causal relationships between gut microbiota, blood metabolites, and short stature, and to identify the potential role of blood metabolites as mediators. METHODS We extracted summary-level data for 119 genera gut microbiota, 309 blood metabolites, and short stature from published genome-wide association studies (GWASs). We applied two-sample MR to infer the causal links, and a two-step MR was employed to quantify the proportion of the effect of gut microbiota on short stature mediated by blood metabolites. RESULTS Increased Prevotella9, Alloprevotella, FamilyXIIIAD3011group, 3-(4-hydroxyphenyl) lactate, and cyclo (leu-pro) were potentially associated with higher short stature risk while Parasutterella, Clostridium sensu stricto 1, Roseburia, caffeine, laurate (12:0), and 4-hydroxyhippurate were related to lower short stature risk. Mediation analysis indicated that 4-hydroxyhippurate levels acted as a mediator between Clostridium sensu stricto 1 and short stature, with an indirect effect proportion of 43.03%. CONCLUSION Our study demonstrates the causal relationships among gut microbiota, blood metabolites, and short stature, and computes the proportion of the effect mediated by blood metabolites, provides new insights for studying the gut-bone axis theory in short stature. IMPACT Our study used Mendelian randomization to demonstrate a causal relationship between gut microbiota, blood metabolites and short stature and identified a mediating role for metabolites. Current studies on the relationship between gut microbiota and short stature are observational and cannot infer causality, our research provides new evidence for this problem. This is the first Mendelian randomization study of gut microbiota, blood metabolites and short stature, providing new insights into the gut-skeletal axis theory of short stature.
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Affiliation(s)
- Zhimin Zheng
- Department of Graduate School, Dalian Medical University, Dalian, Liaoning, China
| | - Hao Sun
- Department of Pediatric, Dalian Women and Children's Medical Center (Group), Dalian, Liaoning, China
| | - Panpan Zhang
- Department of Graduate School, Dalian Medical University, Dalian, Liaoning, China
| | - Fan Cao
- Department of Graduate School, Dalian Medical University, Dalian, Liaoning, China
| | - Xuwu Xiao
- Department of Pediatric, Dalian Women and Children's Medical Center (Group), Dalian, Liaoning, China.
| | - Tingting Zhao
- Department of Pediatric, Dalian Women and Children's Medical Center (Group), Dalian, Liaoning, China.
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20
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Zhao Q, Baranova A, Liu D, Cao H, Zhang F. Bidirectional causal associations between plasma metabolites and bipolar disorder. Mol Psychiatry 2025:10.1038/s41380-025-02977-3. [PMID: 40169804 DOI: 10.1038/s41380-025-02977-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2024] [Revised: 03/03/2025] [Accepted: 03/21/2025] [Indexed: 04/03/2025]
Abstract
Altered levels of human plasma metabolites have been implicated in the etiology of bipolar disorder (BD). However, the causality between metabolites and the disease was not well described. We performed a bidirectional metabolome-wide Mendelian randomization (MR) analysis to evaluate the potential causal relationships between 871 plasma metabolites and BD. We used DrugBank and ChEMBL to evaluate whether related metabolites are potential therapeutic targets. Finally, Bayesian colocalization analysis was performed to identify shared genomic loci BD and identified metabolites. Our MR results showed that six metabolites were significantly associated with a reduced risk of BD, including arachidonate (20:4n6) (OR: 0.90, 95% CI: 0.84-0.95) and sphingomyelin (d18:2/24:1, d18:1/24:2) (OR: 0.92, 95% CI: 0.87-0.96), while five metabolites were significantly associated with an increased risk of BD, including 1-palmitoyl-2-linoleoyl-GPE (16:0/18:2) (OR: 1.09, 95% CI: 1.05-1.13). However, our reverse MR analysis showed that BD was not associated with the levels of any metabolite. Additionally, the leave-one-out analysis revealed SNPs within chromosome 11 loci harboring MYRF, FADS1, and FADS2 as ones with the potential to influence partial causal effects. Druggability evaluation showed that 10 of the BD-related metabolites, such as sphingomyelin and cytidine, have been targeted by pharmacologic intervention. Colocalization analysis highlighted one colocalized region (chromosome 11q12) shared by 11 metabolites and BD and pointed to some genes as possible players, including FADS1, FADS2, FADS3, and SYT7. Our study supported a causal role of plasma metabolites in the susceptibility to BD, and the identified metabolites may provide a new avenue for the prevention and treatment of BD.
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Affiliation(s)
- Qian Zhao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Ancha Baranova
- School of Systems Biology, George Mason University, Fairfax, 22030, USA
- Research Centre for Medical Genetics, Moscow, 115478, Russia
| | - Dongming Liu
- Department of Radiology, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, 210008, China
| | - Hongbao Cao
- School of Systems Biology, George Mason University, Fairfax, 22030, USA
| | - Fuquan Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.
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Hu W, Hu Y, Li J, Men Y, Xia J, Zheng W, Zhao Y. Effect of L-Carnitine Level on the Risk of Neuromyelitis Optica Spectrum Disorders: A Two-Sample Mendelian Randomization Study. Mol Neurobiol 2025; 62:5133-5142. [PMID: 39514170 DOI: 10.1007/s12035-024-04607-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 10/29/2024] [Indexed: 11/16/2024]
Abstract
Previous research has often focused on studying the CNS damage in neuromyelitis optica spectrum disorders (NMOSD), while the role of the peripheral blood in the development of NMOSD is also of significant importance. The relationship between metabolites in blood and cerebrospinal fluid (CSF) with neuroimmune is receiving increasing attention. L-carnitine, whose astrocytic accumulation is associated with neuroinflammation and demyelination, may participate in the pathogenesis of NMOSD. However, whether circulating L-carnitine level has a causal effect on NMOSD risk needs elucidation. With large data sets now available, we used two-sample Mendelian randomization (MR) to determine whether circulating L-carnitine level is causally associated with the risk of NMOSD. Genetic variants associated with circulating L-carnitine levels were derived from a genome-wide association study (GWAS) of 7797 individuals from TwinsUK and KORA F4 cohorts. NMOSD summary statistics, including 215 cases and 1244 controls, were obtained from a separate GWAS. Subgroup analyses included aquaporin-4 (AQP4)-IgG-seropositive NMOSD (132 cases) and AQP4-IgG-seronegative NMOSD (83 cases). We used two-sample MR to explore associations between circulating L-carnitine levels and NMOSD risk, as well as its seropositive and seronegative subtypes. 16 SNPs (single nucleotide polymorphisms) were significantly associated with circulating L-carnitine level (P < 5 × 10-8), all of which were independent and available in the NMOSD dataset, after 1 SNP removed for being palindromic with intermediate allele frequencies in harmonization. Finally, a high circulating L-carnitine level conferred a protective effect against combined NMOSD (OR = 2.216 × 10-4, 95% confidence interval [CI] = 2.335 × 10-7-2.104 × 10-1, P = 0.0161) as well as AQP4-IgG-seronegative NMOSD (OR = 7.678 × 10-7, 95% CI = 2.233 × 10-11-2.640 × 10-2, P = 0.0082). There is no causal effect on AQP4-IgG-seropositive NMOSD risk (OR = 5.471 × 10-3, CI = 1.090 × 10-6-27.465, P = 0.2798) by circulating L-carnitine. Results remained positive and robust after the horizontal pleiotropy test, heterogeneity test, and Bonferroni test. In the reverse MR analysis, there was no causal effect of NMOSD and its subtypes on circulating L-carnitine levels. Our findings suggest that higher circulating L-carnitine levels may reduce the risk of NMOSD, particularly in AQP4-IgG-seronegative patients. L-carnitine could serve as a valuable biomarker and potential therapeutic target for NMOSD, especially in cases without AQP4-IgG. The genetic evidence from this study supports further exploration of L-carnitine's role in managing NMOSD.
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Affiliation(s)
- Wenyu Hu
- Department of Cardiology, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China
| | - Yue Hu
- Department of Neurology, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China
| | - Jiahong Li
- Department of Neurology, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China
| | - Yi Men
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Jiangwei Xia
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Wenxu Zheng
- Department of Geriatric, Dalian Friendship Hospital, Dalian, Liaoning, 116100, China.
| | - Yinan Zhao
- Department of Neurology, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, China.
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China.
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22
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Zhan C, Quan Z, Huang X, Bu J, Li S. Causal relationships of circulating amino acids with sarcopenia-related traits: A bidirectional Mendelian randomization study. Clin Nutr 2025; 47:258-264. [PMID: 40073510 DOI: 10.1016/j.clnu.2025.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2024] [Revised: 01/26/2025] [Accepted: 02/16/2025] [Indexed: 03/14/2025]
Abstract
BACKGROUND AND AIM Recent studies have indicated a correlation between certain Amino acids (AAs) and sarcopenia. However, the exact causal relationship among these associations is still unclear. This study aims to elucidate the causal relationships between 20 types of AAs and the phenotypic characteristics associated with sarcopenia through Mendelian randomization (MR) analysis. METHODS AND RESULTS This MR study employed single nucleotide polymorphisms (SNPs) that were significantly associated with both AAs and the traits of sarcopenia as instrumental variables (IVs). The main method for estimating causal effects was the inverse-variance weighted (IVW) approach. To ensure the robustness of the findings, additional methods such as weighted median, weighted mode, and MR Egger regression were used. Sensitivity analyses included heterogeneity and pleiotropy tests. In this research, we discovered potential causal relationships between AAs and traits associated with sarcopenia. We not only found that AAs previously studied, such as Glutamine, Tyrosine, Glycine, and branched-chain amino acids, play positive roles in muscle metabolism. Additionally, our study identified the role of AAs previously neglected or not considered in earlier research, such as Alanine, Lysine, Cysteine, and Methionine, which exert potential effects on muscle metabolism and offer considerable research potential and value. CONCLUSIONS This MR study clarified the reciprocal effects between circulating levels of AAs and sarcopenia-related traits. These results indicate that AAs may be used as biomarkers for diagnosing sarcopenia or as intervention targets for its treatment in clinical practice.
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Affiliation(s)
- Chenyang Zhan
- Department of General Surgery, Chengdu Second People's Hospital, Chengdu 610041, China; School of Clinical Medicine, Chengdu Medical College, Chengdu, 610500, China.
| | - Zongjie Quan
- Department of General Surgery, Chengdu Second People's Hospital, Chengdu 610041, China; School of Clinical Medicine, North Sichuan Medical College, Nanchong, 637000, China.
| | - Xiujin Huang
- Department of General Surgery, Chengdu Second People's Hospital, Chengdu 610041, China; School of Clinical Medicine, North Sichuan Medical College, Nanchong, 637000, China.
| | - Jun Bu
- Department of General Surgery, Chengdu Second People's Hospital, Chengdu 610041, China.
| | - Sheng Li
- Department of General Surgery, Chengdu Second People's Hospital, Chengdu 610041, China; School of Clinical Medicine, Chengdu Medical College, Chengdu, 610500, China.
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23
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Zhang R, Han L, Pu L, Jiang G, Guan Q, Fan W, Liu H. Investigating causal associations of gut microbiota and blood metabolites on stroke and its subtypes: A Mendelian randomization study. J Stroke Cerebrovasc Dis 2025; 34:108233. [PMID: 39798630 DOI: 10.1016/j.jstrokecerebrovasdis.2025.108233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 01/07/2025] [Accepted: 01/08/2025] [Indexed: 01/15/2025] Open
Abstract
BACKGROUND The causal relationships between gut microbiota, blood metabolites, and stroke and its subtypes remain unclear. This study aims to uncover the causal associations using Mendelian randomization. METHODS We initially identify Single-Nucleotide Polymorphisms (SNPs) correlated with gut microbiota and blood metabolites as instrumental variables (IVs) from the summary statistics in Genome-Wide Association Study (GWAS) to evaluate their potential causal associations with stroke and its subtypes. We proceed with a two-step Mendelian randomization analysis aiming to determine whether blood metabolites mediate the relationships between gut microbiota and stroke or its subtypes. RESULTS We identified the genetic predictions of 12, 11, and 10 particular gut microbiota were associated with stroke, ischemic stroke, and intracerebral hemorrhage respectively. Inverse variance weighted (IVW) analysis disclosed Alistipes (OR [95%CI]: 1.11[1.00,1.23]), Streptococcus (OR [95%CI]: 1.17[1.05,1.30]), and Porphyromonadaceae (OR [95%CI]: 2.41[1.09,5.31]) as the primary causal effects on stroke, ischemic stroke, and ICH, respectively. We determined that 8, 11, and 1 blood metabolites were causally related to stroke, ischemic stroke, and ICH, respectively. Among these metabolites, Citrate (OR [95%CI]: 2.39[1.32,4.34]) and Beta-hydroxyisovalerate (OR [95%CI]: 2.54[1.62,3.97]) had the foremost causal effect on stroke and ischemic stroke, respectively, whereas Glutaroyl carnitine evidenced a causal effect on ICH. Furthermore, our study revealed that Tetradecanedioate marginally mediated the causal effects of Paraprevotella on stroke and ischemic stroke. CONCLUSIONS This study established a causal link between gut microbiota, plasma metabolites, and stroke. It revealed a marginal pathway, shedding new light on the intricate interactions among gut microbes, blood metabolites, stroke, and their underlying mechanisms.
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Affiliation(s)
- Ruijie Zhang
- School of Public Health, Southeast University, Nanjing, Jiangsu, China; Department of Clinical Epidemiology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, Zhejiang, China
| | - Liyuan Han
- Department of Clinical Epidemiology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, Zhejiang, China
| | - Liyuan Pu
- Department of Clinical Epidemiology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, Zhejiang, China
| | - Guozhi Jiang
- School of Public Health, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Qiongfeng Guan
- Department of Neurology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China
| | - Weinv Fan
- Department of Neurology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China
| | - Huina Liu
- Department of Clinical Epidemiology, Ningbo No.2 Hospital, Ningbo, Zhejiang, China; Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, Zhejiang, China.
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24
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Ottensmann L, Tabassum R, Ruotsalainen SE, Gerl MJ, Klose C, McCartney DL, Widén E, Simons K, Ripatti S, Vitart V, Hayward C, Pirinen M. Examining the link between 179 lipid species and 7 diseases using genetic predictors. EBioMedicine 2025; 114:105671. [PMID: 40157129 PMCID: PMC11995710 DOI: 10.1016/j.ebiom.2025.105671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2024] [Revised: 03/12/2025] [Accepted: 03/13/2025] [Indexed: 04/01/2025] Open
Abstract
BACKGROUND Genome-wide association studies of lipid species have identified several loci shared with various diseases, however, the relationship between lipid species and disease risk remains poorly understood. Here we investigated whether the plasma levels of lipid species are causally linked to disease risk. METHODS We built genetic predictors of 179 lipid species, measured in 7174 Finnish individuals, by utilising either 11 high-impact genomic loci or genome-wide polygenic scores (PGS). We assessed the impact of the lipid species on seven diseases by performing disease association across FinnGen (n = 500,348), UK Biobank (n = 420,531), and Generation Scotland (n = 20,032). We performed univariable Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to examine whether lipid species impact disease risk independently of standard lipids. FINDINGS PGS explained >4% of the variance for 34 lipid species but variants outside the high-impact loci had only a marginal contribution. Variants within the high-impact loci showed association with all seven diseases. MVMR supported a causal role of ApoB in ischaemic heart disease after accounting for lipid species. Phosphatidylethanolamine-increasing LIPC variants seemed to lower age-related macular degeneration risk independently of HDL-cholesterol. MVMR suggested a protective effect of four lipid species containing arachidonic acid on cholelithiasis risk independently of Total Cholesterol. INTERPRETATION Our study demonstrates how genetic predictors of lipid species can be utilised to gain insights into disease risk. We report potential links between lipid species and age-related macular degeneration and cholelithiasis risk, which can be explored for their utility in disease risk prediction and therapy. FUNDING The funders had no role in the study design, data analyses, interpretation, or writing of this article.
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Affiliation(s)
- Linda Ottensmann
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom.
| | - Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | | | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Samuli Ripatti
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
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25
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Xu Q, Liu S, Ran X, Li Y, Shen J, Tang H, Liu JK, Pan G, Zhang Q. Robust Sensory Information Reconstruction and Classification With Augmented Spikes. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2025; 36:7462-7471. [PMID: 38833393 DOI: 10.1109/tnnls.2024.3404021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Sensory information recognition is primarily processed through the ventral and dorsal visual pathways in the primate brain visual system, which exhibits layered feature representations bearing a strong resemblance to convolutional neural networks (CNNs), encompassing reconstruction and classification. However, existing studies often treat these pathways as distinct entities, focusing individually on pattern reconstruction or classification tasks, overlooking a key feature of biological neurons, the fundamental units for neural computation of visual sensory information. Addressing these limitations, we introduce a unified framework for sensory information recognition with augmented spikes. By integrating pattern reconstruction and classification within a single framework, our approach not only accurately reconstructs multimodal sensory information but also provides precise classification through definitive labeling. Experimental evaluations conducted on various datasets including video scenes, static images, dynamic auditory scenes, and functional magnetic resonance imaging (fMRI) brain activities demonstrate that our framework delivers state-of-the-art pattern reconstruction quality and classification accuracy. The proposed framework enhances the biological realism of multimodal pattern recognition models, offering insights into how the primate brain visual system effectively accomplishes the reconstruction and classification tasks through the integration of ventral and dorsal pathways.
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26
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Peng P, Shen F, Peng B, Chen Z, Zhou L, Hao X, Liu Y. Genetic Evidence Supporting the Repurposing of mTOR Inhibitors for Reducing BMI. Biomedicines 2025; 13:839. [PMID: 40299431 PMCID: PMC12025023 DOI: 10.3390/biomedicines13040839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2025] [Revised: 03/26/2025] [Accepted: 03/28/2025] [Indexed: 04/30/2025] Open
Abstract
Background: Although mTOR has long been regarded as a promising target for cancer treatment, the efficacy of mTOR inhibitors in most clinical trials has been rather limited. Nevertheless, their favorable safety profile has opened up opportunities for drug repurposing, even as their potential applications across various diseases remain largely unexplored. Methods: We performed an MR-PheWAS analysis across 1431 phenotypes to explore drug repurposing opportunities. We analyzed GWAS data of 452 plasma metabolites, 731 immune traits, and 412 gut microbiota to uncover potential mechanisms for the causal link between the mTOR gene and body mass index (BMI). Results: A causal link between mTOR gene expression and BMI has been established. Additionally, mTOR-related vulnerabilities associated with BMI, including alterations in metabolites, immune traits, and gut microbiota, were identified. Conclusions: The identified causal relationship between mTOR and BMI suggests novel potential non-cancer applications for mTOR inhibitors.
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Affiliation(s)
- Ping Peng
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (B.P.); (Z.C.); (L.Z.)
| | - Fan Shen
- Nursing Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China;
| | - Bi Peng
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (B.P.); (Z.C.); (L.Z.)
| | - Ziqi Chen
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (B.P.); (Z.C.); (L.Z.)
| | - Lei Zhou
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (B.P.); (Z.C.); (L.Z.)
| | - Xingjie Hao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China;
| | - Yuanhui Liu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (B.P.); (Z.C.); (L.Z.)
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27
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Yin X, Li J, Bose D, Okamoto J, Kwon A, Jackson AU, Fernandes Silva L, Oravilahti A, Chu X, Stringham HM, Liu L, Peng R, Xia Z, Ripatti S, Daly M, Palotie A, Scott LJ, Burant CF, Fauman EB, Wen X, Boehnke M, Laakso M, Morrison J. Assessing the potential causal effects of 1099 plasma metabolites on 2099 binary disease endpoints. Nat Commun 2025; 16:3039. [PMID: 40155430 PMCID: PMC11953310 DOI: 10.1038/s41467-025-58129-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 03/10/2025] [Indexed: 04/01/2025] Open
Abstract
Metabolites are small molecules that are useful for estimating disease risk and elucidating disease biology. Here, we perform two-sample Mendelian randomization to systematically infer the potential causal effects of 1099 plasma metabolites measured in 6136 Finnish men from the METSIM study on risk of 2099 binary disease endpoints measured in 309,154 Finnish individuals from FinnGen. We find evidence for 282 putative causal effects of 70 metabolites on 183 disease endpoints. We also identify 25 metabolites with potential causal effects across multiple disease domains, including ascorbic acid 2-sulfate affecting 26 disease endpoints in 12 disease domains. Our study suggests that N-acetyl-2-aminooctanoate and glycocholenate sulfate affect risk of atrial fibrillation through two distinct metabolic pathways and that N-methylpipecolate may mediate the putative causal effect of N6,N6-dimethyllysine on anxious personality disorder.
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Affiliation(s)
- Xianyong Yin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Jack Li
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Debraj Bose
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jeffrey Okamoto
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Annie Kwon
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Anniina Oravilahti
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Xiaomeng Chu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Lei Liu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ruyi Peng
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhijie Xia
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - Mark Daly
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology, and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology, and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Eric B Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA
| | - Xiaoquan Wen
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.
| | - Jean Morrison
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA.
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28
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Yang R, Lv M, Yang X, Zhai S. A Mendelian randomized study of circulating antioxidants in the diet and risk of cardiovascular disease. Sci Rep 2025; 15:10341. [PMID: 40133449 PMCID: PMC11937293 DOI: 10.1038/s41598-025-94369-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2024] [Accepted: 03/13/2025] [Indexed: 03/27/2025] Open
Abstract
Cardiovascular diseases (CVD) are a major global mortality cause, heavily impacted by diet and oxidative stress. This study investigates the causal effects of five circulatory antioxidants on various cardiovascular diseases using Mendelian randomization (MR) to mitigate confounding biases.We conducted a two-sample Mendelian Randomization (MR) analysis utilizing summary-level genome-wide association study (GWAS) data from both the UK Biobank and FinnGen. Genetic instrumental variables for antioxidants, including vitamin A, beta-carotene, vitamin C, α-tocopherol, and lycopene, were identified based on rigorous criteria. The outcomes included arrhythmia, cardiomyopathy, heart failure, myocardial infarction, pericarditis, angina pectoris and coronary atherosclerosis.Higher genetically determined levels of α-tocopherol were associated with an increased risk of myocardial infarction (OR 5.10, 95% CI 2.92-8.91, P < 0.001) and cardiac arrhythmias (OR 1.94, 95% CI 1.34-2.83, P = 0.001). Retinol was linked to heightened risks of cardiomyopathy (OR 6.38, 95% CI 1.23-33.20, P = 0.028) and heart failure (OR 2.26, 95% CI 1.01-5.07, P = 0.047). A meta-analysis corroborated the pathogenic effects of α-carotene on arrhythmias (OR, 2.00; 95% CI, 1.39-2.86; P < 0.001) and myocardial infarction (OR, 4.81; 95% CI, 2.84-8.15; P < 0.001), α-tocopherol on angina pectoris (OR: 4.33; 95% CI: 2.07-9.09; P < 0.001) and coronary atherosclerosis (OR: 5.34; 95% CI: 2.81-10.12; P < 0.001).Our study indicates that elevated levels of specific antioxidants, particularly α-tocopherol and retinol, may increase the risk of certain cardiovascular diseases. Further research is necessary to clarify the impact of these antioxidants on cardiovascular health and to explore potential gene-environment interactions.
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Affiliation(s)
- Ruonan Yang
- Department of Medical Quality Control, Chengdu Seventh People's Hospital, Chengdu, Sichuan, China.
| | - Mingyue Lv
- The Sixth Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Xiujuan Yang
- Department of Medical Quality Control, Chengdu Seventh People's Hospital, Chengdu, Sichuan, China
| | - Siwei Zhai
- Department of Medical Quality Control, Chengdu Seventh People's Hospital, Chengdu, Sichuan, China.
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29
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Qi L, Zhang C, Liu Y, Li W, Ren J, Zhao M. Plasma proteomes and metabolism with genome-wide association data for causal effect identification in ovarian cancer. Discov Oncol 2025; 16:388. [PMID: 40131661 PMCID: PMC11936866 DOI: 10.1007/s12672-025-02087-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2024] [Accepted: 03/06/2025] [Indexed: 03/27/2025] Open
Abstract
BACKGROUND This study seeks to investigate the relationship between plasma metabolites or proteins and the risk of ovarian cancer through Mendelian randomization analysis and construct, while also developing a predictive model for resistance to chemotherapy. METHODOLOGY/PRINCIPAL FINDINGS Appropriate SNPs from GWAS data were selected as instrumental variables. Multiple methods, such as IVW, MR-Egger regression, and WME, were employed to investigate the causal relationship. A predictive model was established utilizing binary logistic regression based on the identified plasma protein genes. Four plasma metabolites and four plasma proteins were recognized as risk factors for ovarian cancer, whereas four plasma proteins were identified as protective factors. A predictive model for chemotherapy resistance was formulated with an AUC of 0.844 (p = 0.002). CONCLUSIONS Plasma metabolites and proteins may affect the risk of ovarian cancer and its resistance to chemotherapy. This study presents potential predictive factors and the underlying mechanisms influencing the onset, progression, and resistance of the disease.
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Affiliation(s)
- Lin Qi
- Department of Gynecology and Obstetrics, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, People's Republic of China
| | - Cheng Zhang
- Department of Gynecology and Obstetrics, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, People's Republic of China
| | - Yinuo Liu
- Qingdao Medical College of Qingdao University, Qingdao, Shandong, People's Republic of China
| | - Wenshu Li
- Department of Gynecology and Obstetrics, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, People's Republic of China
| | - Jingjing Ren
- Department of Gynecology, The Women and Children's Hospital of Qingdao University, Qingdao, Shandong, People's Republic of China.
| | - Manyin Zhao
- Department of Gynecology and Obstetrics, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, People's Republic of China.
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30
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Meng XY, Zhu YQ, Zhang YJ, Sun W, Li SA. Causal relationships between serum metabolites and coronary heart disease risk: a mendelian randomization study. Front Genet 2025; 16:1440364. [PMID: 40182922 PMCID: PMC11965349 DOI: 10.3389/fgene.2025.1440364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 02/21/2025] [Indexed: 04/05/2025] Open
Abstract
Background Coronary heart disease (CHD) represents a substantial global burden in terms of morbidity and mortality. Understanding the causal relationships between serum metabolites and CHD can provide a crucial understanding of disease mechanisms and potential therapeutic targets. Methods We conducted a Mendelian randomization (MR) approach to explore the potential causal associations between serum metabolites and CHD risk. The primary analysis employed the inverse variance weighted (IVW) method, supplemented by additional analyses, including MR-Egger, weighted median, weighted mode, and sample mode. To bolster the robustness and reliability of our findings, we performed sensitivity analyses, which included evaluating, horizontal pleiotropy and leave-one-out analysis. Additionally, pathway enrichment analysis was conducted. Results We identified 15 known and 11 unknown metabolites with potential associations to CHD. Among the known, six displayed protective effects, while nine were identified as risk factors. Notably, many of these metabolites are closely related to mitochondrial function, which was further supported by pathways and enrichment analysis. Using multiple statistical models to ensure robust results, we unveiled a significant association between hexadecanedioate, a palmitoyl lipid metabolized in mitochondria, and a ∼18% reduced risk of CHD (OR = 0.82, 95%CI: 0.72-0.93). Conclusion MR analysis revealed 6 protective molecules, 9 hazardous metabolites associated with CHD. Many of these known metabolites are closely link to mitochondrial function, suggesting a critical role of mitochondria in CHD development. In particular, hexadecanedioate, an essential component for mitochondrial energy production, was inversely associated with CHD risk. This suggests that mitochondrial function, and specifically the role of hexadecanedioate, may be pivotal in the development and progression of CHD.
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Affiliation(s)
- Xiao-Yan Meng
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Yong-Qing Zhu
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Ying-Jie Zhang
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Wei Sun
- Department of Burn and Repair Reconstruction, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shu-Ang Li
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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31
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Zhang L, Li Y, Pu Y, Dang T, Shi Q, Wu W. Exploring clinical and genetic evidence in association between unsaturated fatty acids and acne. Eur J Nutr 2025; 64:130. [PMID: 40106045 DOI: 10.1007/s00394-025-03647-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 03/05/2025] [Indexed: 03/22/2025]
Abstract
PURPOSE This study aims to comprehensively analyze the intricate relationship between unsaturated fatty acids (UFAs, particularly omega-3 and omega-6 UFAs) and acne, from their clinical therapeutic effects to their underlying genetic regulatory mechanisms, to elucidate the role of UFAs in acne pathogenesis. METHODS Clinical evidence synthesis: we systematically reviewed randomized controlled trials (RCTs) to evaluate the impact of UFA supplementation on acne treatment outcomes. Genetic analysis: two-sample Mendelian randomization (MR) analysis we used to investigate causal relationships between serum UFA metabolites and acne, identifying potential key regulatory enzymes. RESULTS The synthesis of these RCT studies confirmed that UFA supplementation improved acne conditions. MR analysis revealed causal links between three serum UFA metabolites and acne, with dihomo-gamma-linolenic acid (DGLA) (OR = 8.457; 95% CI: 2.367-30.214; P-value = 0.001) as a risk factor and arachidonic acid (AA) (OR = 0.209; 95% CI: 0.071-0.618; P-value = 0.005) and eicosapentaenoic acid (EPA) (OR = 0.318; 95% CI: 0.102-0.991; P-value = 0.048) as protective factors. Functional annotation suggested enzymes such as Δ5 desaturase (FADS1) and Δ6 desaturase (FADS2) may play a role in acne regulation. CONCLUSION This study offers evidence that supports a connection between UFAs and acne, examining this relationship from both clinical and genetic angles. These findings highlight the role of specific UFAs and their associated metabolic enzymes in the development of acne. Omega-3 UFAs seem to have a protective effect against acne, whereas certain types and ratios of omega-6 UFAs might contribute to acne formation. The varied impacts of UFAs on acne could be attributed to disease processes mediated by specific enzymes. However, the study's limitations include its genetic analysis being primarily based on European populations, which limits the applicability of the findings to other groups. Future research should aim to include a more diverse range of participants to improve the generalizability of the results.
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Affiliation(s)
- Li Zhang
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, China
- Department of Dermatology, Kunming Children's Hospital (Children's Hospital Affiliated of Kunming Medical University), Kunming, Yunnan, 650118, China
| | - Yadong Li
- Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, Yunnan, 650018, China
| | - Yunjing Pu
- Department of Dermatology, Kunming Children's Hospital (Children's Hospital Affiliated of Kunming Medical University), Kunming, Yunnan, 650118, China
| | - Tianyuan Dang
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, China
| | - Qian Shi
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, China
| | - Wenjuan Wu
- Department of Dermatology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, China.
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32
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Mori Y, van Dijk EHC, Miyake M, Hosoda Y, den Hollander AI, Yzer S, Miki A, Chen LJ, Ahn J, Takahashi A, Morino K, Nakao SY, Hoyng CB, Ng DSC, Cen LP, Chen H, Ng TK, Pang CP, Joo K, Sato T, Sakata Y, Tajima A, Tabara Y, Park KH, Matsuda F, Yamashiro K, Honda S, Nagasaki M, Boon CJF, Tsujikawa A. Genome-wide association and multi-omics analyses provide insights into the disease mechanisms of central serous chorioretinopathy. Sci Rep 2025; 15:9158. [PMID: 40097481 PMCID: PMC11914043 DOI: 10.1038/s41598-025-92210-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 02/26/2025] [Indexed: 03/19/2025] Open
Abstract
Central serous chorioretinopathy (CSC) is a major cause of vision loss, especially in middle-aged men, and its chronic subtype can lead to legal blindness. Despite its clinical importance, the underlying mechanisms of CSC need further clarification. In this study, we conducted a meta-analysis of three genome-wide association studies (GWASs) for CSC consisting of 8811 Asians and Caucasians, followed by replication in an additional 4338 Asians. We identified four genome-wide hits, including a novel hit (rs12960630 at LINC01924-CDH7, Pmeta = 2.97 × 10-9). A phenome-wide association study for rs12960630 showed a positive correlation between its CSC risk allele with plasma cortisol concentration. Expression/splicing quantitative trait loci (QTL) analyses showed an association of all these hits with the expression and/or splicing of genes in genital organs, which may explain the sex differences in CSC. Protein QTL also suggested the protein-level contribution of the complement factor H pathway to CSC pathogenesis.
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Affiliation(s)
- Yuki Mori
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Elon H C van Dijk
- Department of Ophthalmology, Leiden University Medical Center, Leiden, The Netherlands
| | - Masahiro Miyake
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan.
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
| | | | | | - Suzanne Yzer
- Department of Ophthalmology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Akiko Miki
- Division of Ophthalmology, Department of Surgery, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Li Jia Chen
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Jeeyun Ahn
- Seoul National University, College of Medicine, Seoul, Korea
- SMG-SNU Boramae Medical Center, Seoul, Korea
| | - Ayako Takahashi
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
| | - Kazuya Morino
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shin-Ya Nakao
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Carel B Hoyng
- Department of Ophthalmology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Danny S C Ng
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Ling-Ping Cen
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Haoyu Chen
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Tsz Kin Ng
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Chi Pui Pang
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Kwangsic Joo
- Seoul National University, College of Medicine, Seoul, Korea
- Seoul National University Bundang Hospital, Seongnam, Korea
| | - Takehiro Sato
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Yasuhiko Sakata
- Department of Clinical Medicine and Development, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Atsushi Tajima
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Graduate School of Public Health, Shizuoka Graduate University of Public Health, Shizuoka, Japan
| | - Kyu Hyung Park
- Seoul National University, College of Medicine, Seoul, Korea
- Seoul National University Hospital, Seoul, Korea
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kenji Yamashiro
- Department of Ophthalmology and Visual Science, Kochi Medical School, Kochi University, Nankoku, Japan
| | - Shigeru Honda
- Department of Ophthalmology and Visual Sciences, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Masao Nagasaki
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Camiel J F Boon
- Department of Ophthalmology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Ophthalmology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Akitaka Tsujikawa
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
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33
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Eissman JM, Qiao M, Kalia V, Zerlin-Esteves M, Reyes-Dumeyer D, Piriz A, Dubey S, Nandakumar R, Lee AJ, Lantigua RA, Medrano M, Mejia DR, Honig LS, Dalgard CL, Miller GW, Mayeux R, Vardarajan BN. Genetic Regulation of the Metabolome Differs by Sex, Alzheimer's Disease Stage, and Plasma Biomarker Status. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.02.26.25322932. [PMID: 40061336 PMCID: PMC11888523 DOI: 10.1101/2025.02.26.25322932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/18/2025]
Abstract
We investigated genetic regulators of circulating plasma metabolites to identify pathways underlying biochemical changes in clinical and biomarker-assisted diagnosis of Alzheimer's disease (AD). We computed metabolite quantitative trait loci by using whole genome sequencing and small molecule plasma metabolites from 229 older adults with clinical AD and 322 age-matched healthy controls. Unbiased associations between 6,881 metabolites and 332,772 common genetic variants were tested, adjusted for age, sex, and both metabolomic and genomic principal components. We identified 72 novel and known SNP-metabolite associations spanning 66 genes and 12 metabolite classes, including PYROXD2 and N6-methyllysine, FAAH and myristoylglycine, as well as FADS2 and arachidonic acid. In addition, we found differences in genetic regulation of metabolites among individuals with clinically defined AD compared to AD defined by a published plasma P-tau181 level cut-off. We also found more SNP-metabolite associations among males compared to females. In summary, we identified sex- and disease-specific genetic regulators of plasma metabolites and unique biological mechanisms of genetic perturbations in AD.
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Affiliation(s)
- Jaclyn M. Eissman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
| | - Min Qiao
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
| | - Vrinda Kalia
- Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | | | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
| | - Angel Piriz
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
| | - Saurabh Dubey
- Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | - Renu Nandakumar
- Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | - Annie J. Lee
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
| | - Rafael A. Lantigua
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
| | - Martin Medrano
- Pontificia Universidad Católica Madre y Maestra, Santiago, Dominican Republic
| | - Diones Rivera Mejia
- CEDIMAT, Plaza de la Salud, Santo Domingo, Dominican Republic
- Universidad Nacional Pedro Henriquez Ureña, Santo Domingo, Dominican Republic
| | - Lawrence S. Honig
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
| | - Clifton L. Dalgard
- Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
- The American Genome Center, Center for Military Precision Health, Uniformed Services University of the Health Sciences, Bethesda, MD, 20894, USA
| | - Gary W Miller
- Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
| | - Badri N. Vardarajan
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, 10032, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, 10032, USA
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
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Li Y, Chen Z, Huang Z, Wang J, Wang J, Lin L, Lin R, Lai J, Zhang L, Qiu S. Causal association between blood metabolites and head and neck cancer: butyrylcarnitine identified as an associated trait for cancer risk and progression. Hereditas 2025; 162:36. [PMID: 40087718 PMCID: PMC11907814 DOI: 10.1186/s41065-025-00408-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2024] [Accepted: 03/05/2025] [Indexed: 03/17/2025] Open
Abstract
BACKGROUND Blood metabolites play an important role in predicting or influencing the occurrence and development of cancers. We aimed to evaluate the relationship between blood metabolites and the occurrence of head and neck cancer (HNC). METHODS We employed a Mendelian randomization (MR) approach to investigate the role of blood metabolites in HNC predisposition. The HNC cell line HN30 was treated with butyrylcarnitine, the metabolite identified through MR analysis, and subjected to a series of cellular assays to assess its potential carcinogenic effects. RESULTS Among the 258 blood metabolites analyzed, butyrylcarnitine emerged as the only metabolite demonstrating a potential causal association with HNC risk following Bonferroni correction (inverse-variance-weighted MR method: β = 0.904, P < 0.001). Genetically predicted higher levels of butyrylcarnitine (log-transformed) were causally linked to an increased risk of HNC (OR: 2.470, 95% CI: 1.530-3.987). Sensitivity analyses, including MR-Egger regression, leave-one-out analysis, and funnel plots, confirmed the robustness of the findings, with no evidence of directional pleiotropy. In vitro experiments further demonstrated that butyrylcarnitine promoted the proliferation, migration and invasion of HN30 cells. CONCLUSIONS By employing a genetic epidemiological framework, our research assessed the impact of metabolite butyrylcarnitine on HNC susceptibility. These findings offer valuable insights into potential therapeutic targets and highlight the promise of targeted metabolic strategies for reducing HNC risk. Nevertheless, further research is required to elucidate the precise biological mechanisms underlying these findings.
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Affiliation(s)
- Ying Li
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Zihan Chen
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Zongwei Huang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Jing Wang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Jue Wang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Lanxin Lin
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Ruyu Lin
- Fujian Medical University, Fujian, China
| | - Jinghua Lai
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Libin Zhang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
| | - Sufang Qiu
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
- Fujian Key Laboratory of Translational Cancer Medicine, Fujian, China.
- Fujian Provincial Key Laboratory of Tumor Biotherapy, Fujian, China.
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Bovo S, Ribani A, Fanelli F, Galimberti G, Martelli PL, Trevisi P, Bertolini F, Bolner M, Casadio R, Dall'Olio S, Gallo M, Luise D, Mazzoni G, Schiavo G, Taurisano V, Zambonelli P, Bosi P, Pagotto U, Fontanesi L. Merging metabolomics and genomics provides a catalog of genetic factors that influence molecular phenotypes in pigs linking relevant metabolic pathways. Genet Sel Evol 2025; 57:11. [PMID: 40050712 PMCID: PMC11887101 DOI: 10.1186/s12711-025-00960-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Accepted: 02/18/2025] [Indexed: 03/09/2025] Open
Abstract
BACKGROUND Metabolomics opens novel avenues to study the basic biological mechanisms underlying complex traits, starting from characterization of metabolites. Metabolites and their levels in a biofluid represent simple molecular phenotypes (metabotypes) that are direct products of enzyme activities and relate to all metabolic pathways, including catabolism and anabolism of nutrients. In this study, we demonstrated the utility of merging metabolomics and genomics in pigs to uncover a large list of genetic factors that influence mammalian metabolism. RESULTS We obtained targeted characterization of the plasma metabolome of more than 1300 pigs from two populations of Large White and Duroc pig breeds. The metabolomic profiles of these pigs were used to identify genetically influenced metabolites by estimating the heritability of the level of 188 metabolites. Then, combining breed-specific genome-wide association studies of single metabolites and their ratios and across breed meta-analyses, we identified a total of 97 metabolite quantitative trait loci (mQTL), associated with 126 metabolites. Using these results, we constructed a human-pig comparative catalog of genetic factors influencing the metabolomic profile. Whole genome resequencing data identified several putative causative mutations for these mQTL. Additionally, based on a major mQTL for kynurenine level, we designed a nutrigenetic study feeding piglets that carried different genotypes at the candidate gene kynurenine 3-monooxygenase (KMO) varying levels of tryptophan and demonstrated the effect of this genetic factor on the kynurenine pathway. Furthermore, we used metabolomic profiles of Large White and Duroc pigs to reconstruct metabolic pathways using Gaussian Graphical Models, which included perturbation of the identified mQTL. CONCLUSIONS This study has provided the first catalog of genetic factors affecting molecular phenotypes that describe the pig blood metabolome, with links to important metabolic pathways, opening novel avenues to merge genetics and nutrition in this livestock species. The obtained results are relevant for basic and applied biology and to evaluate the pig as a biomedical model. Genetically influenced metabolites can be further exploited in nutrigenetic approaches in pigs. The described molecular phenotypes can be useful to dissect complex traits and design novel feeding, breeding and selection programs in pigs.
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Affiliation(s)
- Samuele Bovo
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy.
| | - Anisa Ribani
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Flaminia Fanelli
- Endocrinology Research Group, Center for Applied Biomedical Research, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
- Division of Endocrinology and Prevention and Care of Diabetes, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico di Sant'Orsola, Bologna, Italy
| | - Giuliano Galimberti
- Department of Statistical Sciences "Paolo Fortunati", University of Bologna, Bologna, Italy
| | - Pier Luigi Martelli
- Biocomputing Group, Department of Pharmacology and Biotechnology, University of Bologna, Bologna, Italy
| | - Paolo Trevisi
- Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Francesca Bertolini
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Matteo Bolner
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, Department of Pharmacology and Biotechnology, University of Bologna, Bologna, Italy
| | - Stefania Dall'Olio
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | | | - Diana Luise
- Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Gianluca Mazzoni
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Giuseppina Schiavo
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Valeria Taurisano
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Paolo Zambonelli
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Paolo Bosi
- Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Uberto Pagotto
- Endocrinology Research Group, Center for Applied Biomedical Research, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
- Division of Endocrinology and Prevention and Care of Diabetes, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico di Sant'Orsola, Bologna, Italy
| | - Luca Fontanesi
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy.
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Wei P, Gao S, Han G. Evidence for Genetic Causal Association Between the Gut Microbiome, Derived Metabolites, and Age-Related Macular Degeneration: A Mediation Mendelian Randomization Analysis. Biomedicines 2025; 13:639. [PMID: 40149615 PMCID: PMC11940807 DOI: 10.3390/biomedicines13030639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2025] [Revised: 02/25/2025] [Accepted: 03/03/2025] [Indexed: 03/29/2025] Open
Abstract
Background/Objectives: Despite substantial research, the causal relationships between gut microbiota (GM) and age-related macular degeneration (AMD) remain unclear. We aimed to explore these causal associations using Mendelian randomization (MR) and elucidate the potential mechanisms mediated by blood metabolites. Methods: We utilized the 211 GM dataset (n = 18,340) provided by the MiBioGen consortium. AMD outcome data were sourced from the MRC Integrated Epidemiology Unit (IEU) OpenGWAS Project. We performed bidirectional MR, two mediation analyses, and two-step MR to assess the causal links between GM and different stages of AMD (early, dry, and wet). Results: Our findings indicate that the Bacteroidales S24.7 group and genus Dorea are associated with an increased risk of early AMD, while Ruminococcaceae UCG011 and Parasutterella are linked to a higher risk of dry AMD. Conversely, Lachnospiraceae UCG004 and Anaerotruncus are protective against dry AMD. In the case of wet AMD, Intestinimonas and Sellimonas increase risk, whereas Anaerotruncus and Rikenellaceae RC9 reduce it. Additionally, various blood metabolites were implicated: valine, arabinose, creatine, lysine, alanine, and apolipoprotein A1 were associated with early AMD; glutamine and hyodeoxycholate-with a reduced risk of dry AMD; and androsterone sulfate, epiandrosterone sulfate, and lipopolysaccharide-with a reduced risk of wet AMD. Notably, the association between family Oxalobacteraceae and early AMD was mediated by valine, accounting for 19.1% of the association. Conclusions: This study establishes causal links between specific gut microbiota and AMD, mediated by blood metabolites, thereby enhancing our understanding of the gut-retina axis in AMD pathophysiology.
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Affiliation(s)
- Pinghui Wei
- Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin 300020, China; (P.W.); (S.G.)
- Nankai University Eye Institute, Nankai University Affiliated Eye Hospital, Nankai University, Tianjin 300071, China
- Clinical College of Ophthalmology, Tianjin Medical University, Tianjin 300020, China
| | - Shan Gao
- Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin 300020, China; (P.W.); (S.G.)
- School of Medicine, Nankai University, Tianjin 300071, China
| | - Guoge Han
- Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin 300020, China; (P.W.); (S.G.)
- Nankai University Eye Institute, Nankai University Affiliated Eye Hospital, Nankai University, Tianjin 300071, China
- Clinical College of Ophthalmology, Tianjin Medical University, Tianjin 300020, China
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Hector EC, Zhang D, Tian L, Feng J, Yin X, Xu T, Laakso M, Bai Y, Xiao J, Kang J, Yu T. Dissecting genetic regulation of metabolic coordination. Brief Bioinform 2025; 26:bbaf095. [PMID: 40067114 PMCID: PMC11894804 DOI: 10.1093/bib/bbaf095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 12/24/2024] [Accepted: 02/19/2025] [Indexed: 03/15/2025] Open
Abstract
Understanding genetic regulation of metabolism is critical for gaining insights into the causes of metabolic diseases. Traditional metabolome-based genome-wide association studies (mGWAS) focus on static associations between single nucleotide polymorphisms (SNPs) and metabolite levels, overlooking the changing relationships caused by genotypes within the metabolic network. Notably, some metabolites exhibit changes in correlation patterns with other metabolites under certain physiological conditions while maintaining their overall abundance level. In this manuscript, we develop Metabolic Differential-coordination GWAS (mdGWAS), an innovative framework that detects SNPs associated with the changing correlation patterns between metabolites and metabolic pathways. This approach transcends and complements conventional mean-based analyses by identifying latent regulatory factors that govern the system-level metabolic coordination. Through comprehensive simulation studies, mdGWAS demonstrated robust performance in detecting SNP-metabolite-metabolite associations. Applying mdGWAS to genotyping and mass spectrometry (MS)-based metabolomics data of the METabolic Syndrome In Men (METSIM) Study revealed novel SNPs and genes potentially involved in the regulation of the coordination between metabolic pathways.
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Affiliation(s)
- Emily C Hector
- Department of Statistics, North Carolina State University, Raleigh, NC 27695, United States
| | - Daiwei Zhang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States
- Department of Biostatistics and Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, United States
| | - Leqi Tian
- School of Data Science, the Chinese University of Hong Kong, Shenzhen, Guangdong 518172, P.R.China
| | - Junning Feng
- School of Data Science, the Chinese University of Hong Kong, Shenzhen, Guangdong 518172, P.R.China
| | - Xianyong Yin
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States
| | - Tianyi Xu
- School of Data Science, the Chinese University of Hong Kong, Shenzhen, Guangdong 518172, P.R.China
| | - Markku Laakso
- School of Medicine, University of Eastern Finland, FI-70211 Kuopio, Finland
| | - Yun Bai
- School of Medicine, the Chinese University of Hong Kong, Shenzhen, Guangdong 518172, P.R.China
| | - Jiashun Xiao
- Shenzhen Research Institute of Big Data, Shenzhen, Guangdong 518172, P.R.China
| | - Jian Kang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States
| | - Tianwei Yu
- School of Data Science, the Chinese University of Hong Kong, Shenzhen, Guangdong 518172, P.R.China
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Shen J, Guo Y, Cao R. The relationship between amino acids and gastroesophageal reflux disease: evidence from a mendelian randomization analysis combined with a meta-analysis. Front Immunol 2025; 16:1420132. [PMID: 40103821 PMCID: PMC11914792 DOI: 10.3389/fimmu.2025.1420132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 02/06/2025] [Indexed: 03/20/2025] Open
Abstract
Background Gastroesophageal Reflux Disease (GERD), a prevalent gastrointestinal disorder globally, exhibits variable prevalence across regions, with higher frequencies observed in Western nations and lower in Asian countries. Key contributing factors encompass unhealthy eating patterns, tobacco use, consumption of alcohol, excess weight, and obesity, along with health conditions such as gestation and diabetes. Common manifestations include heartburn and a burning discomfort behind the breastbone, which, without appropriate management, can progress to more severe issues like esophagitis and Barrett's esophagus. Approaches to management and prevention primarily involve modifications in lifestyle, pharmacotherapy, and surgical interventions when deemed necessary. Utilizing Omics Mendelian Randomization (OMR) to investigate the causative links between genetic variants and diseases provides insights into the biological underpinnings of gastroesophageal reflux diseasec. It aids in pinpointing novel targets for therapy. The influence of amino acids in gastroesophageal reflux disease demonstrates the complexity, having the potential to both mitigate and intensify symptoms, underscoring the significance of personalized nutrition and therapeutic strategies. Methods This study is based on the omics mendelian randomization method, coupled with meta-analysis techniques, to enhance the precision of the research findings. Furthermore, a reverse validation procedure was implemented to validate the association between the positive findings and disease outcomes further. Throughout the study, multiple correction measures were employed to ensure the accuracy and reliability of the results. Results Based on our research methodology, we have ultimately discovered that glutamate exacerbates gastroesophageal reflux disease, increasing its risk. The data supporting this includes analysis of 20 amino acids and outcomes from the Finnish database, which showed that glutamate had an odds ratio (OR) for gastroesophageal reflux disease risk of 1.175(95% confidence interval (CI): 1.000 ~ 1.380, P = 0.05), and a beta value of 0.161. Analysis with outcomes from the UK database indicated that glutamate had an OR for gastroesophageal reflux disease risk of 1.399(95% CI: 1.060 ~ 1.847, P = 0.018) and a beta value of 0.336. After conducting a meta-analysis of the MR results and applying multiple corrections, the combined OR of glutamate for gastroesophageal reflux disease risk was 1.227 (95% CI: 1.068 ~ 1.411 P = 0.043); the beta values of the three primary MR outcomes were consistent in direction. Building on the positive results, reverse validation with outcome data from two different database sources for glutamate showed: in the Finngen database, with gastroesophageal reflux disease as the exposure, the Inverse Variance Weighted (IVW) method resulted in a P-value of 0.059; in the IEU database under the same condition, the IVW P-value was 1.433. Conclusions Glutamate may increase the risk and exacerbate the progression of gastroesophageal reflux disease through mechanisms such as impacting the nervous system and promoting inflammatory responses. Delving into the role of glutamate in gastroesophageal reflux disease enriches our understanding of the disease's biological mechanisms and may offer new strategies for clinical treatment and nutritional management. This insight can aid in developing healthier dietary plans, thereby benefiting patients.
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Affiliation(s)
- Jianjun Shen
- Jiamusi College, Heilongjiang University of Chinese Medicine,
Jiamusi, China
| | - Yongqing Guo
- Capital University of Physical Education and Sports, Beijing, China
| | - Rui Cao
- Jiamusi College, Heilongjiang University of Chinese Medicine,
Jiamusi, China
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Ning L, Gao Z, Chen D, Han J, Xie G, Sun J. Causality of blood metabolites on hepatocellular carcinoma and cholangiocarcinoma: a metabolome-wide mendelian randomization study. BMC Cancer 2025; 25:389. [PMID: 40038628 PMCID: PMC11877886 DOI: 10.1186/s12885-025-13690-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/07/2025] [Indexed: 03/06/2025] Open
Abstract
BACKGROUND Reportedly, there is an association between body metabolites and the risk of Hepatocellular Carcinoma (HCC) & Cholangiocarcinoma (CCA), possibly due to disrupted metabolic pathways leading to oxidative stress and an imbalance in cell proliferation and apoptosis, thereby increasing the risk of cancer. However, whether metabolites play a role in the onset of HCC or CCA remains inconclusive. OBJECTIVE The aim of our study is to explore the potential causal relationship between metabolites and the risk of HCC&CCA. METHODS Our study investigated the causal relationship between 1400 metabolites and HCC&CCA using publicly available genome-wide association study data. Single nucleotide polymorphisms (SNPs) associated with both metabolites and HCC&CCA were chosen as instrumental variables (IVs). The main approaches employed include inverse variance weighted (IVW), MR-Egger regression, and weighted median estimator (WME), with odds ratios (OR) used as the assessment criterion. Heterogeneity testing and sensitivity analyses were conducted to validate the results. We also conducted a reverse MR analysis to further validate the relationship between exposure and disease outcomes. RESULTS This Mendelian Randomization (MR) study indicates a significant causal relationship between 19 metabolites and the risk of HCC&CCA. Among them, the risk factors include "Bilirubin (E, Z or Z, E) levels," "Bilirubin (Z, Z) to taurocholate ratio," "Dimethylarginine (sdma + adma) levels," "N-methyltaurine levels," "4-vinylguaiacol sulfate levels," "Cholate to adenosine 3',5'-cyclic monophosphate (cAMP) ratio," "Glycohyocholate levels," "Cholesterol levels," and "4-methylguaiacol sulfate levels." The incidence risk of HCC and CCA increases with the elevation of these metabolites. Protective factors include "Ursodeoxycholate levels," "3-hydroxybutyroylglycine levels," "Linoleoylcholine levels," "Nonanoylcarnitine (C9) levels," "Pristanate levels," "Heptenedioate (C7:1-DC) levels," "Mannonate levels," "N-acetyl-L-glutamine levels," "Sphinganine levels," and "N-lactoyl isoleucine levels." The incidence risk of HCC and CCA potentially decreases as the levels of these metabolites increase. Heterogeneity tests show that most instrumental variables do not exhibit inter-gene heterogeneity, and the possibility of pleiotropy in the analysis is very low according to the sensitivity analysis. The reverse MR analysis did not yield positive results. CONCLUSION Our study has unveiled the intricate causal relationships between metabolites and the risk of HCC&CCA. Through our analysis, we identified nine metabolites, including "Bilirubin (E, Z or Z, E) levels," "Dimethylarginine (sdma + adma) levels," "Cholesterol levels,"ect, as risk factors for HCC&CCA. The incidence risk of HCC and CCA increases with their elevation. On the other hand, ten metabolites, such as "Ursodeoxycholate levels," "Linoleoylcholine levels," "Pristanate levels," ect, were identified as protective factors for HCC&CCA. The risk of developing HCC and CCA decreases with an increase in these metabolites. In conclusion, these findings further explore the physiological metabolic pathways underlying the pathogenesis of HCC and CCA, emphasizing future research directions. They pave the way for researchers to delve into the biological mechanisms of these diseases, facilitating early intervention and treatment strategies for these conditions.
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Affiliation(s)
- Lin Ning
- Department of Traditional Chinese medicine, The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhanhua Gao
- Department of Hepatobiliary Medicine, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Di Chen
- Department of Hepatobiliary Medicine, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jie Han
- Department of Hepatobiliary Medicine, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Guanyue Xie
- Department of Hepatobiliary Medicine, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jianguang Sun
- Department of Traditional Chinese medicine, The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China.
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Du Z, Liu X, Xie Z, Wang Q, Lv Z, Li L, Wang H, Xue D, Zhang Y. The relationship between a high-fat diet, gut microbiome, and systemic chronic inflammation: insights from integrated multiomics analysis. Am J Clin Nutr 2025; 121:643-653. [PMID: 39746397 DOI: 10.1016/j.ajcnut.2024.12.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 10/29/2024] [Accepted: 12/26/2024] [Indexed: 01/04/2025] Open
Abstract
BACKGROUND The detrimental effects of a high-fat diet (HFD) extend beyond metabolic consequences and include systemic chronic inflammation (SCI), immune dysregulation, and gut health disruption. OBJECTIVES In this study, we used Mendelian randomization (MR) to investigate the relationship between HFD, gut microbiota, and SCI. METHODS Genetic variants associated with dietary fat were utilized to explore causal relationships. Genome-wide association study data for the analyses of the gut microbiota, inflammatory cytokines, immune cell characteristics, and serum metabolites were obtained from European individuals. Mediation analysis was used to reveal potential mediating factors. The GMrepo database was used to analyze the bacterial composition in different groups. Transcriptomic and single-cell sequencing analyses explored inflammation and barrier function in colonic tissue. RESULTS HFD consumption was linked to changes in the abundance of 3 bacterial families and 11 bacterial genera. Combined with the GMrepo database, the increased abundance of the genus Lachnospiraceae_FCS020group and the decreased abundance of genus Bacteroides and genus Barnesiella are consistent with the MR results. Transcriptomic and single-cell sequencing analyses revealed intestinal inflammation and mucosal barrier dysfunction in HFD-fed mice. MR revealed a link between HFD consumption and increased levels of interleukin (IL)-18 [odds ratio (OR): 3.64, 95%CI: 1.24, 10.69, P = 0.02], MIG (OR = 3.14, 95%CI: 1.17, 8.47, P = 0.02), IL-13 [OR = 3.21, 95% confidence interval (CI): 1.08, -9.52, P = 0.04], and IL-2RA (OR = 2.93, 95%CI: 1.01, 8.53, P = 0.049). Twenty-nine immune cell signatures, including altered monocyte and T-cell subsets, were affected by HFD consumption. Twenty-six serum metabolites that are linked to HFD consumption, particularly lipid and amino acid metabolites, were identified. The positive gut microbiota exhibit extensive associations with inflammatory cytokines. In particular, Lachnospiraceae_FCS020 group (OR: 1.93, 95% CI: 1.11, 3.37, P = 0.02) may play a mediating role in HFD-induced increases in IL-2RA concentrations. CONCLUSIONS Microbial dysbiosis appears to be an important mechanism for HFD-induced SCI. The Lachnospiraceae_FCS020 group may act as a key genus in HFD-mediated elevation of IL-2RA.
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Affiliation(s)
- Zhiwei Du
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xuxu Liu
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhihong Xie
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qiang Wang
- Department of General Surgery, Qilu Hospital of Shandong University, Shandong, China
| | - Zhenyi Lv
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Lianghao Li
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Heming Wang
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Dongbo Xue
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yingmei Zhang
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
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Geng W, Wen X, Jin R, Yuan X. 1,400 genetically predicted plasma metabolites in relation to risk of primary biliary cholangitis: a bi-directional, two-sample Mendelian randomization analysis. Clin Exp Hepatol 2025; 11:61-70. [PMID: 40303583 PMCID: PMC12035705 DOI: 10.5114/ceh.2025.148221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Accepted: 11/01/2024] [Indexed: 05/02/2025] Open
Abstract
Aim of the study Primary biliary cholangitis (PBC) is a complex, chronic, cholestatic liver disease with an autoimmune etiology. While plasma metabolites are crucial indicators of physiological and pathological states, their involvement in PBC pathogenesis remains unclear. To address this knowledge gap, we performed a rigorous two-sample Mendelian randomization (MR) analysis to assess the causal associations of 1,400 plasma metabolites with PBC. Material and methods Genome-wide association data for 1,400 plasma metabolites and PBC were obtained from established public databases. The inverse-variance weighted (IVW) method was the primary method used for MR analysis. Sensitivity analyses and heterogeneity tests were conducted to assess the stability of the MR results. A reverse MR analysis was performed to investigate the possibility of reverse causality. Results Four plasma metabolites were identified as potential predictors for the occurrence of PBC. Specifically, sphingosine 1-phosphate (OR = 0.65, 95% CI: 0.42-0.98, p = 0.04) and docosadienoate (22:2n6) (OR = 0.57, 95% CI: 0.36-0.90, p = 0.01) were implicated in conferring a protective effect against PBC. Conversely, homoarginine (OR = 1.34, 95% CI: 1.04-1.72, p = 0.02) and campesterol (OR = 1.19, 95% CI: 1.01-1.40, p = 0.03) were associated with an increased risk of PBC. There was no evidence of reverse causality between PBC and the identified plasma metabolites. Conclusions This study utilized a two-sample Mendelian randomization approach to explore the causal relationship between 1,400 plasma metabolites and PBC. We identified four plasma metabolites that may have a causal relationship with the development of PBC. The metabolites identified hold promise as prognostic indicators and could illuminate novel pathways for therapeutic intervention in PBC.
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Affiliation(s)
- Wenqian Geng
- Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 100015, China
| | - Xiajie Wen
- Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 100015, China
| | - Ronghua Jin
- Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 100015, China
| | - Xiaoxue Yuan
- Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 100015, China
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Mi Y, Lin S, Chen K, Shu Z. The causal association between plasma caffeine and frailty: A two-sample mendelian randomization study. Arch Gerontol Geriatr 2025; 130:105706. [PMID: 39616874 DOI: 10.1016/j.archger.2024.105706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 10/24/2024] [Accepted: 11/25/2024] [Indexed: 01/11/2025]
Abstract
BACKGROUND Frailty is one of the most common and challenging consequences of aging, which negatively affects older adults, their families, and society. Caffeine has been shown to be associated with a reduced risk of frailty by observational studies, yet its causal relationship with frailty remains to be tested using more robust methods. AIMS This study aimed to explore the causal association between plasma caffeine and frailty using a two-sample Mendelian Randomization (MR) analysis. METHODS Single nucleotide polymorphisms related to plasma caffeine concentrations were selected as instrumental variables. Data on the Frailty Index (FI) were sourced from the UK Biobank and TwinGen meta-analysis (n = 175,226), while data on the Fried Frailty Score (FFS) were obtained from the UK Biobank (n = 386,565). The causal association between plasma caffeine levels and frailty was tested using five MR methods, with the inverse-variance weighted method as the primary approach. RESULTS Our results consistently showed significantly negative associations between genetically predicted plasma caffeine with FI (β = -0.050, 95 % CI:0.077 to -0.023, P < 0.001) and FFS (β = -0.049, 95 % CI:0.064 to -0.034, P < 0.001). These results remained robust in further sensitivity analyses using a leave-one-out approach. CONCLUSION Our findings confirm a causal relationship between plasma caffeine and frailty and suggest that increasing plasma caffeine levels may help prevent and reduce the risk of frailty.
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Affiliation(s)
- Yuze Mi
- Rehabilitation Medicine Center, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, , PR China; State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, PR China
| | - Shaokai Lin
- Rehabilitation Medicine Center, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, , PR China; State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, PR China
| | - Ke Chen
- Rehabilitation Medicine Center, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, , PR China; State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, PR China
| | - Zhendi Shu
- Rehabilitation Medicine Center, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, , PR China; School of Rehabilitation Medicine, Wenzhou Medical University, Wenzhou, PR China.
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Colenso‐Semple LM, McKendry J, Lim C, Atherton PJ, Wilkinson DJ, Smith K, Phillips SM. Menstrual cycle phase does not influence muscle protein synthesis or whole-body myofibrillar proteolysis in response to resistance exercise. J Physiol 2025; 603:1109-1121. [PMID: 39630025 PMCID: PMC11870050 DOI: 10.1113/jp287342] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 10/24/2024] [Indexed: 03/01/2025] Open
Abstract
It has been hypothesised that skeletal muscle protein turnover is affected by menstrual cycle phase with a more anabolic environment during the follicular vs. the luteal phase. We assessed the influence of menstrual cycle phase on muscle protein synthesis and myofibrillar protein breakdown in response to 6 days of controlled resistance exercise in young females during peak oestrogen and peak progesterone, using stable isotopes, unbiased metabolomics and muscle biopsies. We used comprehensive menstrual cycle phase-detection methods, including cycle tracking, blood samples and urinary test kits, to classify menstrual phases. Participants (n = 12) completed two 6 day study phases in a randomised order: late follicular phase and mid-luteal phase. Participants performed unilateral resistance exercise in each menstrual cycle phase, exercising the contralateral leg in each phase in a counterbalanced manner. Follicular phase myofibrillar protein synthesis (MPS) rates were 1.33 ± 0.27% d-1 in the control leg and 1.52 ± 0.27% d-1 in the exercise leg. Luteal phase MPS was 1.28 ± 0.27% d-1 in the control leg and 1.46 ± 0.25% d-1 in the exercise leg. We observed a significant effect of exercise (P < 0.001) but no effect of cycle phase or interaction. There was no significant effect of menstrual cycle phase on whole-body myofibrillar protein breakdown (P = 0.24). Using unbiased metabolomics, we observed no notable phase-specific changes in circulating blood metabolites associated with any particular menstrual cycle phase. Fluctuations in endogenous ovarian hormones influenced neither MPS, nor MPB in response to resistance exercise. Skeletal muscle is not more anabolically responsive to resistance exercise in a particular menstrual cycle phase. KEY POINTS: It has been hypothesised that the follicular (peak oestrogen) vs. the luteal (peak progesterone) phase of the menstrual cycle is more advantageous for skeletal muscle anabolism in response to resistance exercise. Using best practice methods to assess menstrual cycle status, we measured integrated (over 6 days) muscle protein synthesis (MPS) and myofibrillar protein breakdown (MPB) following resistance exercise in females (n = 12) in their follicular and luteal phases. We observed the expected differences in oestrogen and progesterone concentrations that confirmed our participants' menstrual cycle phase; however, there were no notable metabolic pathway differences, as measured using metabolomics, between cycle phases. We observed that resistance exercise stimulated MPS, but there was no effect of menstrual cycle phase on either resting or exercise-stimulated MPS or MPB. Our data show no greater anabolic effect of resistance exercise in the follicular vs. the luteal phase of the menstrual cycle.
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Affiliation(s)
- Lauren M. Colenso‐Semple
- Exercise Metabolism Research Group, Department of KinesiologyMcMaster UniversityHamiltonONCanada
| | - James McKendry
- Exercise Metabolism Research Group, Department of KinesiologyMcMaster UniversityHamiltonONCanada
- Food, Nutrition and Health, Faculty of Land and Food SystemsThe University of British ColumbiaVancouverBCCanada
| | - Changhyun Lim
- Exercise Metabolism Research Group, Department of KinesiologyMcMaster UniversityHamiltonONCanada
- Population Health. Sciences InstituteFaculty of Medical SciencesNewcastle UniversityNewcastleUK
| | - Philip J. Atherton
- MRC/ARUK Centre for Musculoskeletal Ageing Research and National Institute of Health Research, Biomedical Research CentreSchool of MedicineUniversity of NottinghamNottinghamUK
- Ritsumeikan UniversityRitsumeikan Advanced Research Academy (RARA) Fellow and Visiting ProfessorFaculty of Sport and Health ScienceKyotoJapan
| | - Daniel J. Wilkinson
- MRC/ARUK Centre for Musculoskeletal Ageing Research and National Institute of Health Research, Biomedical Research CentreSchool of MedicineUniversity of NottinghamNottinghamUK
| | - K. Smith
- MRC/ARUK Centre for Musculoskeletal Ageing Research and National Institute of Health Research, Biomedical Research CentreSchool of MedicineUniversity of NottinghamNottinghamUK
| | - Stuart M. Phillips
- Exercise Metabolism Research Group, Department of KinesiologyMcMaster UniversityHamiltonONCanada
- Department of Sport and Exercise ScienceManchester Metropolitan University Institute of SportManchesterUK
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Wei Y, Huang L, Sui J, Liu C, Qi M. Human blood metabolites and risk of post-traumatic stress disorder: A Mendelian randomization study. J Affect Disord 2025; 372:227-233. [PMID: 39643216 DOI: 10.1016/j.jad.2024.12.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 11/30/2024] [Accepted: 12/03/2024] [Indexed: 12/09/2024]
Abstract
BACKGROUND Post-traumatic stress disorder (PTSD) is a debilitating chronic mental disorder that leads to reduced quality of life and increased economic burden. Observational studies have found an association between human blood metabolites and PTSD. Nonetheless, these studies have limitations and are subject to confounding factors as well as reverse causation. Herein, we employed a two-sample Mendelian randomization (MR) approach for the systematic analysis of the blood metabolites and PTSD causal link. METHODS Data for the human blood metabolome, cerebrospinal fluid (CSF) metabolome, and PTSD were obtained from publicly available summary-level genome-wide association studies (GWAS), respectively. The inverse variance weighted (IVW) approach represented the main analytic method for assessing exposure-outcome causal associations, employing multiple sensitivity analyses to verify the results' stability. In addition, replication and meta-analysis, steiger test and reverse MR analysis methods were performed to clarify further that these metabolites have independent causal effects on PTSD. Finally, the results of blood and CSF metabolomics analyses were synthesized to obtain biological markers with a causal link to PTSD. RESULTS Conclusively, we identified potential causal associations between six blood metabolites and PTSD. The sensitivity analyses elucidated the absence of pleiotropy or heterogeneity in the MR results. The Steiger test and reverse MR analysis did not reveal reverse causal associations, proving the robustness of our results. Combined blood and CSF metabolome analyses showed the same trend for theophylline. CONCLUSION This study reveals a strong causal link between metabolites and PTSD, which can be used as a biomarker for clinical PTSD disease screening and prevention. This study also provides a new perspective on the mechanism of metabolite-mediated PTSD development by combining genomics and metabolomics.
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Affiliation(s)
- Yi Wei
- Nanjing University of Chinese Medicine, Nanjing 21023, China
| | - Liyu Huang
- Department of Medical Imaging, Qingdao Traditional Chinese Medicine Hospital (Qingdao Hiser Hospital), Qingdao 266014, China
| | - Jie Sui
- Department of Health Care, People's Liberation Army Navy No 971 Hospital, Qingdao 266071, China
| | - Chao Liu
- Department of Medical Imaging, Qingdao Traditional Chinese Medicine Hospital (Qingdao Hiser Hospital), Qingdao 266014, China.
| | - Ming Qi
- Department of Primary Care, Qingdao Traditional Chinese Medicine Hospital (Qingdao Hiser Hospital), Qingdao 266014, China.
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Reus LM, Boltz T, Francia M, Bot M, Ramesh N, Koromina M, Pijnenburg YAL, den Braber A, van der Flier WM, Visser PJ, van der Lee SJ, Tijms BM, Teunissen CE, Loohuis LO, Ophoff RA. Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes. Mol Psychiatry 2025:10.1038/s41380-025-02934-0. [PMID: 40021830 DOI: 10.1038/s41380-025-02934-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/16/2024] [Accepted: 02/12/2025] [Indexed: 03/03/2025]
Abstract
Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanisms in vivo, measuring 5543 CSF metabolites, the largest panel in CSF to date, in 977 individuals of European ancestry. Individuals originated from two separate cohorts including cognitively healthy subjects (n = 490) and a well-characterized memory clinic sample, the Amsterdam Dementia Cohort (ADC, n = 487). We performed metabolite quantitative trait loci (mQTL) mapping on CSF metabolomics and found 126 significant mQTLs, representing 65 unique CSF metabolites across 51 independent loci. To better understand the role of CSF mQTLs in brain-related disorders we integrated our CSF mQTL results with pre-existing summary statistics on brain traits, identifying 34 genetic associations between CSF metabolites and brain traits. Over 90% of significant mQTLs demonstrated colocalized associations with brain-specific gene expression, unveiling potential neurobiological pathways.
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Affiliation(s)
- Lianne M Reus
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
| | - Toni Boltz
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
| | - Marcelo Francia
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Merel Bot
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Naren Ramesh
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Maria Koromina
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, NY, USA
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Department of Psychiatry, Maastricht University, Maastricht, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Neurodegeneration, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Loes Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, CA, USA
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Psychiatry, Erasmus University Medical Center, Rotterdam, The Netherlands.
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Arnold M, Buyukozkan M, Doraiswamy PM, Nho K, Wu T, Gudnason V, Launer LJ, Wang-Sattler R, Adamski J, De Jager PL, Ertekin-Taner N, Bennett DA, Saykin AJ, Peters A, Suhre K, Kaddurah-Daouk R, Kastenmüller G, Krumsiek J. Individual bioenergetic capacity as a potential source of resilience to Alzheimer's disease. Nat Commun 2025; 16:1910. [PMID: 39994231 PMCID: PMC11850607 DOI: 10.1038/s41467-025-57032-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/04/2025] [Indexed: 02/26/2025] Open
Abstract
Impaired glucose uptake in the brain is an early presymptomatic manifestation of Alzheimer's disease (AD), with symptom-free periods of varying duration that likely reflect individual differences in metabolic resilience. We propose a systemic "bioenergetic capacity", the individual ability to maintain energy homeostasis under pathological conditions. Using fasting serum acylcarnitine profiles from the AD Neuroimaging Initiative as a blood-based readout for this capacity, we identified subgroups with distinct clinical and biomarker presentations of AD. Our data suggests that improving beta-oxidation efficiency can decelerate bioenergetic aging and disease progression. The estimated treatment effects of targeting the bioenergetic capacity were comparable to those of recently approved anti-amyloid therapies, particularly in individuals with specific mitochondrial genotypes linked to succinylcarnitine metabolism. Taken together, our findings provide evidence that therapeutically enhancing bioenergetic health may reduce the risk of symptomatic AD. Furthermore, monitoring the bioenergetic capacity via blood acylcarnitine measurements can be achieved using existing clinical assays.
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Affiliation(s)
- Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Mustafa Buyukozkan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - P Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tong Wu
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, MD, USA
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Philip L De Jager
- Department of Neurology, Center for Translational & Computational Neuroimmunology, Taub Institute, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | | | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Medical Faculty, Ludwig-Maximilians-Universität, Munich, Germany
- German Center for Diabetes Research (DZD e.V.), Munich, Germany
- German Center for Cardiovascular Disease (DZHK e.V.), Munich Heart Alliance, Munich, Germany
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
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Bender A, Ranea-Robles P, Williams EG, Mirzaian M, Heimel JA, Levelt CN, Wanders RJ, Aerts JM, Zhu J, Auwerx J, Houten SM, Argmann CA. A multiomic network approach uncovers disease modifying mechanisms of inborn errors of metabolism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.19.639093. [PMID: 40027804 PMCID: PMC11870498 DOI: 10.1101/2025.02.19.639093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
For many inborn errors of metabolism (IEM) the understanding of disease mechanisms remains limited in part explaining their unmet medical needs. We hypothesize that the expressivity of IEM disease phenotypes is affected by the activity of specific modifier pathways, which is controlled by rare and common polygenic variation. To identify these modulating pathways, we used RNA sequencing to generate molecular signatures of IEM in disease relevant tissues. We then integrated these disease signatures with multiomic data and gene regulatory networks generated from animal and human populations without overt IEM. We identified and subsequently validated glucocorticoid signaling as a candidate modifier of mitochondrial fatty acid oxidation disorders, and we re-capitulated complement signaling as a modifier of inflammation in Gaucher disease. Our work describes a novel approach that can overcome the rare disease-rare data dilemma, and reveal new IEM pathophysiology and potential drug targets using multiomics data in seemingly healthy populations.
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Affiliation(s)
- Aaron Bender
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pablo Ranea-Robles
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Evan G. Williams
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4367, Esch-sur-Alzette, Luxembourg
| | - Mina Mirzaian
- Department of Clinical Chemistry, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - J. Alexander Heimel
- Circuits Structure and Function Group, Netherlands Institute for Neuroscience, Netherlands
| | - Christiaan N. Levelt
- Molecular Visual Plasticity Group, Netherlands Institute for Neuroscience, Netherlands
| | - Ronald J. Wanders
- Department of Clinical Chemistry and Pediatrics, Laboratory Genetic Metabolic Diseases, Emma Children’s Hospital, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Inborn Errors of Metabolism, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, The Netherlands
| | - Johannes M. Aerts
- Department of Medical Biochemistry, Leiden Institute of Chemistry, Leiden University, Netherlands
| | - Jun Zhu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan Auwerx
- Laboratory of Integrative and Systems Physiology, Interfaculty Institute of Bioengineering, École Polytechnique Fédérale de Lausanne CH-1015, Switzerland
| | - Sander M. Houten
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carmen A. Argmann
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Huang M, Xing F, Hu Y, Sun F, Zhang C, Xv Z, Yang Y, Deng Q, Shi R, Li L, Zhu J, Xu F, Li D, Wang J. Causal inference study of plasma proteins and blood metabolites mediating the effect of obesity-related indicators on osteoporosis. Front Endocrinol (Lausanne) 2025; 16:1435295. [PMID: 40041284 PMCID: PMC11876022 DOI: 10.3389/fendo.2025.1435295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 01/21/2025] [Indexed: 03/06/2025] Open
Abstract
Background Osteoporosis and obesity are both major global public health problems. Observational studies have found that osteoporosis might be related to obesity. Mendelian randomization (MR) analysis could overcome the limitations of observational studies in assessing causal relationships. Objective This study aims to evaluate the causal potential relationship between obesity-related indicators and osteoporosis by using a two-sample MR analysis and to identify potential mediators. Method A total of 53 obesity-related indicators, 3,282 plasma protein lists, and 452 blood metabolite lists were downloaded from the public data set as instrumental variables, and the osteoporosis GWAS data of the MRC IEU Open GWAS database was used as the outcome indicators. Using two-sample univariate MR, multivariate MR, and intermediate MR, the causal relationship and mediating factors between obesity-related indicators and osteoporosis were identified. Results The IVW model results show that 31 obesity-related indicators may have a significant causal relationship with osteoporosis (P < 0.05), except for waist circumference (id: Ieu-a-71, OR = 1.00566); the remaining 30 indicators could reduce the risk of osteoporosis (OR: 0.983-0.996). A total of 25 plasma protein indicators may have a significant causal relationship with osteoporosis (P < 0.05), and 10 of them, such as ANKED46, KLRF1, and LPO, CA9 may have a protective effect on osteoporosis (OR: 0.996-0.999), while the other 15 such as ATP1B1, zinc finger protein 175, could increase the risk of osteoporosis (OR: 1.001-1.004). For blood metabolite indicators, except for alanine (id: Met a-469, OR: 1.071), the other six blood metabolite indicators including uridine and 1-linoleoylglycerophosphoethanolaminecan may have a protective effect on osteoporosis (P < 0.05, OR: 0.961-0.992). The direction of causal relationship of MR is all correct; the heterogeneity is all not significant and not affected by horizontal pleiotropy. Using multivariate and mediated MR analysis, it was found that the protective effect of obesity-related indicators against osteoporosis may be mediated by histone-lysine N-methyltransferase in plasma proteins and alanine in blood metabolites. Conclusion Obesity may confer a protective effect against osteoporosis, potentially mediated by EHMT2 in plasma proteins and alanine in blood metabolites. Further empirical research is required to fully elucidate the mechanisms behind the influence of obesity on osteoporosis. Interventions on obesity-related factors to reduce the risk of osteoporosis while controlling other adverse effects associated with obesity may require further research.
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Affiliation(s)
- Maomao Huang
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
- Department of Rehabilitation Medicine, Southwest Medical University, Luzhou, China
- Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou Science and Technology Bureau, Luzhou, China
| | - Fei Xing
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
- Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou Science and Technology Bureau, Luzhou, China
| | - Yue Hu
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Fuhua Sun
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
- Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou Science and Technology Bureau, Luzhou, China
| | - Chi Zhang
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
- Department of Rehabilitation Medicine, Southwest Medical University, Luzhou, China
- Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou Science and Technology Bureau, Luzhou, China
| | - Zhangyu Xv
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Yue Yang
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Qi Deng
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Ronglan Shi
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Lei Li
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Jiayi Zhu
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Fangyuan Xu
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
| | - Dan Li
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
- Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou Science and Technology Bureau, Luzhou, China
| | - Jianxiong Wang
- Rehabilitation Medicine Department, The Affiliated Hospital Of Southwest Medical University, Luzhou, China
- Department of Rehabilitation Medicine, Southwest Medical University, Luzhou, China
- Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou Science and Technology Bureau, Luzhou, China
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Sheng Q, Ma Y, Geng B, Chen J, Cheng J, Liu S, Li R, Li X, Wang J, Lu H, Gao F, Gao F. Serum amino acid alterations in hyperuricemia: potential targets for renal disease prevention. Amino Acids 2025; 57:16. [PMID: 39966264 PMCID: PMC11836093 DOI: 10.1007/s00726-025-03444-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2024] [Accepted: 01/30/2025] [Indexed: 02/20/2025]
Abstract
Observational studies have linked uric acid (UA) levels and kidney disease to amino acid homeostasis, but the causal relationship is unclear. This study aims to determine if elevated UA affects amino acid levels and whether amino acids mediate this relationship, focusing on the causal links between UA, circulating amino acids, and kidney disease. METHODS This study utilized Uox-KO mice as a hyperuricemia model, assessed renal injury through blood biochemistry and pathology, analyzed serum amino acid changes via targeted amino acidomics, and employed Mendelian randomization to investigate the causal links between uric acid, amino acids, and renal disease. RESULTS Hyperuricemia Uox-KO mice have significantly higher serum UA and renal impairment markers, with histopathological analysis showing extensive renal tissue damage. Changes in amino acid balance were found in the mice's serum, with key metabolites like alanine, isoleucine, leucine, aspartic acid, cysteine, glutamate, and glycine potentially influencing UA pathophysiology. Genetically predicted UA was positively correlated with chronic renal failure (CRF) and blood urea nitrogen(BUN) levels and negatively with serum cystatin C (eGFRcys) and serum creatinine (eGFRcrea). Alanine (Ala) mediated the effect of UA on elevated CRF and BUN risk, accounting for 4.5% of the UA-CRF relationship and 14.4% of the UA-BUN association. CONCLUSION In hyperuricemia mice, serum amino acids undergo metabolic changes. Genetically predicted UA levels are positively linked to CRF and BUN, but negatively linked to eGFRcys and eGFRcrea. Ala mediates UA's effect on CRF and BUN risk, indicating Ala could be a target for preventing renal diseases caused by hyperuricemia.
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Affiliation(s)
- Qinglin Sheng
- University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Yuqing Ma
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Bingjie Geng
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Jiahui Chen
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Junfei Cheng
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Su Liu
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Rui Li
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Xiangtong Li
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Jing Wang
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Hongtao Lu
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Fangyuan Gao
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China
| | - Fu Gao
- University of Shanghai for Science and Technology, Shanghai, 200093, China.
- Department of Naval Medicine, Naval Medical University, Shanghai, 200093, China.
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50
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Cheng C, Xu F, Pan XF, Wang C, Fan J, Yang Y, Liu Y, Sun L, Liu X, Xu Y, Zhou Y, Xiao C, Gou W, Miao Z, Yuan J, Shen L, Fu Y, Sun X, Zhu Y, Chen Y, Pan A, Zhou D, Zheng JS. Genetic mapping of serum metabolome to chronic diseases among Han Chinese. CELL GENOMICS 2025; 5:100743. [PMID: 39837327 PMCID: PMC11872534 DOI: 10.1016/j.xgen.2024.100743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 10/31/2024] [Accepted: 12/24/2024] [Indexed: 01/23/2025]
Abstract
Serum metabolites are potential regulators for chronic diseases. To explore the genetic regulation of metabolites and their roles in chronic diseases, we quantified 2,759 serum metabolites and performed genome-wide association studies (GWASs) among Han Chinese individuals. We identified 184 study-wide significant (p < 1.81 × 10-11) metabolite quantitative trait loci (metaboQTLs), 88.59% (163) of which were novel. Notably, we identified Asian-ancestry-specific metaboQTLs, including the SNP rs2296651 for taurocholic acid and taurochenodesoxycholic acid. Leveraging the GWAS for 37 clinical traits from East Asians, Mendelian randomization analyses identified 906 potential causal relationships between metabolites and clinical traits, including 27 for type 2 diabetes and 38 for coronary artery disease. Integrating genetic regulation of the transcriptome and proteome revealed putative regulators of several metabolites. In summary, we depict a landscape of the genetic architecture of the serum metabolome among Han Chinese and provide insights into the role of serum metabolites in chronic diseases.
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Affiliation(s)
- Chunxiao Cheng
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Fengzhe Xu
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
| | - Xiong-Fei Pan
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China; West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Cheng Wang
- Department of Clinical Nutrition, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510012, China
| | - Jiayao Fan
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Yunhaonan Yang
- Section of Epidemiology and Population Health & Department of Gynecology and Obstetrics, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children & National Medical Products Administration Key Laboratory for Technical Research on Drug Products In Vitro and In Vivo Correlation, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yuanjiao Liu
- Department of Epidemiology & Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Lingyun Sun
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Xiaojuan Liu
- Department of Laboratory Medicine, Ministry of Education Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yue Xu
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Yuan Zhou
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China
| | - Congmei Xiao
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
| | - Wanglong Gou
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
| | - Zelei Miao
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
| | - Jiaying Yuan
- Department of Science and Education & Shuangliu Institute of Women's and Children's Health, Shuangliu Maternal and Child Health Hospital, Chengdu, Sichuan 610200, China
| | - Luqi Shen
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
| | - Yuanqing Fu
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
| | - Xiaohui Sun
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Yimin Zhu
- Department of Epidemiology & Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yuming Chen
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
| | - Dan Zhou
- The Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou 310058, Zhejiang, China.
| | - Ju-Sheng Zheng
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, China; Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China; Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou 310024, China; Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
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