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Yang J. Unveiling the multifaceted roles of long non-coding RNA CTBP1-DT in human diseases: Special attention to its microprotein-encoding potential. Pathol Res Pract 2025; 268:155870. [PMID: 40020329 DOI: 10.1016/j.prp.2025.155870] [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: 11/18/2024] [Revised: 01/30/2025] [Accepted: 02/25/2025] [Indexed: 03/03/2025]
Abstract
C-terminal binding protein 1 divergent transcript (CTBP1-DT) is a novel long non-coding RNA (lncRNA) located on human chromosome 4p16.3. Numerous studies have shown that CTBP1-DT plays a critical regulatory role in various human malignancies and non-malignant diseases. In several cancers, the expression of CTBP1-DT is upregulated, closely associated with the risk of 12 types of cancer, and strongly correlated with the clinical pathological features and poor prognosis of 10 of these cancers. Mechanistically, CTBP1-DT is stimulated by the transcription factors ETV5 and Sp1, or methylated by YTHDC1. By competitively inhibiting 12 microRNAs, it activates 3 signaling pathways that influence malignant behaviors of tumor cells, including proliferation, apoptosis, cell cycle arrest, migration, invasion, immune evasion, and chemoresistance. Importantly, it also encodes the microprotein DNA damage up-regulated protein (DDUP), which mediates cisplatin resistance through sustained response to DNA damage signals. Furthermore, CTBP1-DT has been implicated in the progression of non-malignant diseases such as diabetes and related conditions, cardiovascular diseases, and osteoarthritis. This review summarizes the latest research on the RNA and protein functions of CTBP1-DT in human diseases, outlines various molecular regulatory networks centered around CTBP1-DT, and discusses the opportunities and challenges of its clinical applications.
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Affiliation(s)
- Jingjie Yang
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China; Key Laboratory of Cancer Immunology and Biotherapy, Tianjin 300060, China.
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2
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Bae H, Jeon H, Lee C. Genetic regulation of B cell receptor signaling pathway: Insights from expression quantitative trait locus analysis using a mixed model. Comput Biol Chem 2024; 113:108188. [PMID: 39236423 DOI: 10.1016/j.compbiolchem.2024.108188] [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: 04/24/2024] [Revised: 08/23/2024] [Accepted: 08/24/2024] [Indexed: 09/07/2024]
Abstract
The B cell receptor (BCR) signaling pathway regulates non-immune cellular response through various pathways like MAPK, NF-kB, and PI3K-Akt. This study aimed to identify expression quantitative trait loci (eQTL) and their regulatory functions on BCR signaling pathway genes. A mixed model was employed to analyze eQTL using RNA expression levels in lymphoblastoid from 376 Europeans in the GEUVADIS dataset. In total, 266 SNPs, including 115 cis-acting SNPs, were found for association with transcription of 13 genes (P < 5 × 10-8), revealing 19 independent signals for five genes through linkage disequilibrium analysis. Functional analysis, aligning them with DNase sensitive sites, transcription factor binding sites, histone modification, promoters/enhancers, CpG islands, and ChIA-PET, identified regulatory variants targeting SYK, VAV2, and PLCG2. Notably, rs2562397 was validated as a SYK promoter variant, and rs694505, rs636667, and rs4889409 were confirmed as enhancer variants for VAV2 and PLCG2. Their allelic differences in gene expression were also confirmed using ENCODE ChIP-seq and Sei neural network prediction. Persistent differential expression of these genes by alleles might impact the adaptive immune system, vascular development, and/or relevant diseases that have been previously associated with other variants of the genes. Comprehensive genetic architecture studies of the BCR signaling pathway, along with experiments demonstrating related mechanisms, will greatly contribute to understanding the underlying mechanisms of relevant disease development and implementing precision medicine.
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Affiliation(s)
- Hojin Bae
- Department of Bioinformatics and Life Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Republic of Korea
| | - Hyowon Jeon
- Department of Bioinformatics and Life Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Republic of Korea
| | - Chaeyoung Lee
- Department of Bioinformatics and Life Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Republic of Korea.
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Collu R, Zarate YA, Xia W, Fish JL. Individuals with SATB2-associated syndrome have impaired vitamin and energy metabolism pathways. Metab Brain Dis 2024; 40:3. [PMID: 39541055 DOI: 10.1007/s11011-024-01465-x] [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: 02/20/2024] [Accepted: 09/12/2024] [Indexed: 11/16/2024]
Abstract
Special AT-rich sequence-binding protein 2 (SATB2) is a master regulator of gene expression. Mutations of the SATB2 gene results in the SATB2-associated syndrome (SAS), a genetic disorder characterized by neurodevelopmental disabilities and autism-related phenotype. The importance of plasma as an indicator of SAS phenotypes is unknown. We aim to investigate if pathogenic variants in SATB2 are associated with alteration to relevant pathways in the plasma of SAS patients and identify key differentially regulated proteins which may serve as biomarkers to improve diagnostic and future pharmacological approaches. We used well-validated proteomic technologies to determine the proteomic profile of plasma from SAS patients compared to healthy control subjects. Bioinformatical analysis was performed to identify significant proteins and functionally enriched pathways. We identified differentially expressed proteins in the plasma of SAS patients that are significantly involved in metabolism-related pathways. Energy metabolism, glucose metabolism and vitamin metabolism pathways are significantly enriched in SAS patients as compared to healthy controls. Our study linked SATB2 mutations to the impairment of plasma proteins involved in different metabolic pathways in SAS patients.
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Affiliation(s)
- Roberto Collu
- Geriatric Research Education and Clinical Center, Bedford VA Healthcare System, Bedford, MA, USA.
- Department of Pharmacology, Physiology and Biophysics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
| | - Yuri A Zarate
- Division of Genetics and Metabolism, University of Kentucky, Lexington, KY, USA
- Section of Genetics and Metabolism, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Weiming Xia
- Geriatric Research Education and Clinical Center, Bedford VA Healthcare System, Bedford, MA, USA
- Department of Pharmacology, Physiology and Biophysics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Jennifer L Fish
- Department of Biological Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
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Imamura M, Maeda S. Genetic studies of type 2 diabetes, and microvascular complications of diabetes. Diabetol Int 2024; 15:699-706. [PMID: 39469559 PMCID: PMC11512959 DOI: 10.1007/s13340-024-00727-4] [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: 01/16/2024] [Accepted: 04/24/2024] [Indexed: 10/30/2024]
Abstract
Genome-wide association studies (GWAS) have significantly advanced the identification of genetic susceptibility variants associated with complex diseases. As of 2023, approximately 800 variants predisposing individuals to the risk of type 2 diabetes (T2D) were identified through GWAS, and the majority of studies were predominantly conducted in European populations. Despite the shared nature of the majority of genetic susceptibility loci across diverse ethnic populations, GWAS in non-European populations, including Japanese and East Asian populations, have revealed population-specific T2D loci. Currently, polygenic risk scores (PRSs), encompassing millions of associated variants, can identify individuals with a higher T2D risk than the general population. However, GWAS focusing on microvascular complications of diabetes have identified a limited number of disease-susceptibility loci. Ongoing efforts are crucial to enhance the applicability of PRS for all ethnic groups and unravel the genetic architecture of microvascular complications of diabetes.
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Affiliation(s)
- Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Okinawa 903-0215 Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara-Cho, Okinawa 930-0215 Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Okinawa 903-0215 Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara-Cho, Okinawa 930-0215 Japan
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Imamura M, Maeda S. Perspectives on genetic studies of type 2 diabetes from the genome-wide association studies era to precision medicine. J Diabetes Investig 2024; 15:410-422. [PMID: 38259175 PMCID: PMC10981147 DOI: 10.1111/jdi.14149] [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: 11/23/2023] [Revised: 12/24/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
Genome-wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS until 2023. From 2018 to 2022, hundreds of type 2 diabetes susceptibility loci with smaller effect sizes were identified through large-scale GWAS with sample sizes of 200,000 to >1 million. The clinical translation of genetic information for type 2 diabetes includes the development of novel therapeutics and risk predictions. Although drug discovery based on loci identified in GWAS remains challenging owing to the difficulty of functional annotation, global efforts have been made to identify novel biological mechanisms and therapeutic targets by applying multi-omics approaches or searching for disease-associated coding variants in isolated founder populations. Polygenic risk scores (PRSs), comprising up to millions of associated variants, can identify individuals with higher disease risk than those in the general population. In populations of European descent, PRSs constructed from base GWAS data with a sample size of approximately 450,000 have predicted the onset of diseases well. However, European GWAS-derived PRSs have limited predictive performance in non-European populations. The predictive accuracy of a PRS largely depends on the sample size of the base GWAS data. The results of GWAS meta-analyses for multi-ethnic groups as base GWAS data and cross-population polygenic prediction methodology have been applied to establish a universal PRS applicable to small isolated ethnic populations.
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Affiliation(s)
- Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of MedicineUniversity of the RyukyusNishihara‐ChoJapan
- Division of Clinical Laboratory and Blood TransfusionUniversity of the Ryukyus HospitalNishihara‐ChoJapan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of MedicineUniversity of the RyukyusNishihara‐ChoJapan
- Division of Clinical Laboratory and Blood TransfusionUniversity of the Ryukyus HospitalNishihara‐ChoJapan
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Pierantozzi E, Raucci L, Buonocore S, Rubino EM, Ding Q, Laurino A, Fiore F, Soldaini M, Chen J, Rossi D, Vangheluwe P, Chen H, Sorrentino V. Skeletal muscle overexpression of sAnk1.5 in transgenic mice does not predispose to type 2 diabetes. Sci Rep 2023; 13:8195. [PMID: 37210436 PMCID: PMC10199891 DOI: 10.1038/s41598-023-35393-0] [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: 01/09/2023] [Accepted: 05/17/2023] [Indexed: 05/22/2023] Open
Abstract
Genome-wide association studies (GWAS) and cis-expression quantitative trait locus (cis-eQTL) analyses indicated an association of the rs508419 single nucleotide polymorphism (SNP) with type 2 diabetes (T2D). rs508419 is localized in the muscle-specific internal promoter (P2) of the ANK1 gene, which drives the expression of the sAnk1.5 isoform. Functional studies showed that the rs508419 C/C variant results in increased transcriptional activity of the P2 promoter, leading to higher levels of sAnk1.5 mRNA and protein in skeletal muscle biopsies of individuals carrying the C/C genotype. To investigate whether sAnk1.5 overexpression in skeletal muscle might predispose to T2D development, we generated transgenic mice (TgsAnk1.5/+) in which the sAnk1.5 coding sequence was selectively overexpressed in skeletal muscle tissue. TgsAnk1.5/+ mice expressed up to 50% as much sAnk1.5 protein as wild-type (WT) muscles, mirroring the difference reported between individuals with the C/C or T/T genotype at rs508419. However, fasting glucose levels, glucose tolerance, insulin levels and insulin response in TgsAnk1.5/+ mice did not differ from those of age-matched WT mice monitored over a 12-month period. Even when fed a high-fat diet, TgsAnk1.5/+ mice only presented increased caloric intake, but glucose disposal, insulin tolerance and weight gain were comparable to those of WT mice fed a similar diet. Altogether, these data indicate that sAnk1.5 overexpression in skeletal muscle does not predispose mice to T2D susceptibility.
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Affiliation(s)
- E Pierantozzi
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - L Raucci
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - S Buonocore
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - E M Rubino
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - Q Ding
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, 210008, Jiangsu, China
| | - A Laurino
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - F Fiore
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - M Soldaini
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
| | - J Chen
- Laboratory of Cellular Transport Systems, Department of Cellular and Molecular Medicine, Katholieke Universiteit Leuven (KU Leuven), 3000, Leuven, Belgium
| | - D Rossi
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy
- Interdepartmental Program of Molecular Diagnosis and Pathogenetic Mechanisms of Rare Genetic Diseases, Azienda Ospedaliera Universitaria Senese, 53100, Siena, Italy
| | - P Vangheluwe
- Laboratory of Cellular Transport Systems, Department of Cellular and Molecular Medicine, Katholieke Universiteit Leuven (KU Leuven), 3000, Leuven, Belgium
| | - H Chen
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, 210008, Jiangsu, China
- Programme in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore
| | - V Sorrentino
- Department of Molecular and Developmental Medicine, University of Siena, 53100, Siena, Italy.
- Interdepartmental Program of Molecular Diagnosis and Pathogenetic Mechanisms of Rare Genetic Diseases, Azienda Ospedaliera Universitaria Senese, 53100, Siena, Italy.
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Hill C, Duffy S, Kettyle LM, McGlynn L, Sandholm N, Salem RM, Thompson A, Swan EJ, Kilner J, Rossing P, Shiels PG, Lajer M, Groop PH, Maxwell AP, McKnight AJ. Differential Methylation of Telomere-Related Genes Is Associated with Kidney Disease in Individuals with Type 1 Diabetes. Genes (Basel) 2023; 14:genes14051029. [PMID: 37239390 DOI: 10.3390/genes14051029] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/21/2023] [Accepted: 04/23/2023] [Indexed: 05/28/2023] Open
Abstract
Diabetic kidney disease (DKD) represents a major global health problem. Accelerated ageing is a key feature of DKD and, therefore, characteristics of accelerated ageing may provide useful biomarkers or therapeutic targets. Harnessing multi-omics, features affecting telomere biology and any associated methylome dysregulation in DKD were explored. Genotype data for nuclear genome polymorphisms in telomere-related genes were extracted from genome-wide case-control association data (n = 823 DKD/903 controls; n = 247 end-stage kidney disease (ESKD)/1479 controls). Telomere length was established using quantitative polymerase chain reaction. Quantitative methylation values for 1091 CpG sites in telomere-related genes were extracted from epigenome-wide case-control association data (n = 150 DKD/100 controls). Telomere length was significantly shorter in older age groups (p = 7.6 × 10-6). Telomere length was also significantly reduced (p = 6.6 × 10-5) in DKD versus control individuals, with significance remaining after covariate adjustment (p = 0.028). DKD and ESKD were nominally associated with telomere-related genetic variation, with Mendelian randomisation highlighting no significant association between genetically predicted telomere length and kidney disease. A total of 496 CpG sites in 212 genes reached epigenome-wide significance (p ≤ 10-8) for DKD association, and 412 CpG sites in 193 genes for ESKD. Functional prediction revealed differentially methylated genes were enriched for Wnt signalling involvement. Harnessing previously published RNA-sequencing datasets, potential targets where epigenetic dysregulation may result in altered gene expression were revealed, useful as potential diagnostic and therapeutic targets for intervention.
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Affiliation(s)
- Claire Hill
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Seamus Duffy
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Laura M Kettyle
- Centre for Cancer Research and Cell Biology, Queen's University of Belfast, Belfast BT9 7AE, UK
| | - Liane McGlynn
- College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, 00290 Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, 00290 Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290 Helsinki, Finland
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Alex Thompson
- School of Medicine, The Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, UK
| | - Elizabeth J Swan
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Jill Kilner
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Peter Rossing
- Nordsjaellands Hospital, Hilleroed, Denmark and Health, Aarhus University, 8000 Aarhus, Denmark
- Steno Diabetes Center, 2730 Gentofte, Denmark
- Department of Clinical Medicine, University of Copenhagen, 1165 Copenhagen, Denmark
| | - Paul G Shiels
- School of Molecular Biosciences, Davidson Building, University of Glasgow, Glasgow G12 8QQ, UK
| | - Maria Lajer
- Steno Diabetes Center, 2730 Gentofte, Denmark
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, 00290 Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, 00290 Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290 Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC 3800, Australia
| | - Alexander Peter Maxwell
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast BT9 7AB, UK
| | - Amy Jayne McKnight
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
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Shojima N, Yamauchi T. Progress in genetics of type 2 diabetes and diabetic complications. J Diabetes Investig 2023; 14:503-515. [PMID: 36639962 PMCID: PMC10034958 DOI: 10.1111/jdi.13970] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/12/2022] [Accepted: 12/15/2022] [Indexed: 01/15/2023] Open
Abstract
Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
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Affiliation(s)
- Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Xue J, Li F, Dai P. The Potential of ANK1 to Predict Parkinson's Disease. Genes (Basel) 2023; 14:genes14010226. [PMID: 36672967 PMCID: PMC9859451 DOI: 10.3390/genes14010226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/10/2023] [Accepted: 01/12/2023] [Indexed: 01/18/2023] Open
Abstract
The main cause of Parkinson's disease (PD) remains unknown and the pathologic changes in the brain limit rapid diagnosis. Herein, differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) database (GSE8397 and GSE22491) were assessed using linear models for microarray analysis (limma). Ankyrin 1 (ANK1) was the only common gene differentially down-regulated in lateral substantia nigra (LSN), medial substantia nigra (MSN) and blood. Additionally, DEGs between high ANK1 and low ANK1 in GSE99039 were picked out and then uploaded to the Database for Annotation, Visualization and Integrated Discovery (DAVID) for gene ontology (GO) functional annotation analysis. GO analysis displayed that these DEGs were mainly enriched in oxygen transport, myeloid cell development and gas transport (biological process (BP)); hemoglobin complex, haptoglobin-hemoglobin complex and cortical cytoskeleton (cellular component (CC)); and oxygen transporter activity, haptoglobin binding and oxygen binding (molecular function (MF)). Receiver operating characteristic (ROC) curve analysis showed ANK1 had good diagnostic accuracy and increased the area under the curve (AUC) value when combined with other biomarkers. Consistently, intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropy-ridi-ne (MPTP) in C57BL/6J mice reduced ANK1 mRNA expression in both substantia nigra and blood compared to the control group. Thus, ANK1 may serve as a candidate biomarker for PD diagnosis.
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Blazev R, Carl CS, Ng YK, Molendijk J, Voldstedlund CT, Zhao Y, Xiao D, Kueh AJ, Miotto PM, Haynes VR, Hardee JP, Chung JD, McNamara JW, Qian H, Gregorevic P, Oakhill JS, Herold MJ, Jensen TE, Lisowski L, Lynch GS, Dodd GT, Watt MJ, Yang P, Kiens B, Richter EA, Parker BL. Phosphoproteomics of three exercise modalities identifies canonical signaling and C18ORF25 as an AMPK substrate regulating skeletal muscle function. Cell Metab 2022; 34:1561-1577.e9. [PMID: 35882232 DOI: 10.1016/j.cmet.2022.07.003] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/31/2022] [Accepted: 07/08/2022] [Indexed: 11/03/2022]
Abstract
Exercise induces signaling networks to improve muscle function and confer health benefits. To identify divergent and common signaling networks during and after different exercise modalities, we performed a phosphoproteomic analysis of human skeletal muscle from a cross-over intervention of endurance, sprint, and resistance exercise. This identified 5,486 phosphosites regulated during or after at least one type of exercise modality and only 420 core phosphosites common to all exercise. One of these core phosphosites was S67 on the uncharacterized protein C18ORF25, which we validated as an AMPK substrate. Mice lacking C18ORF25 have reduced skeletal muscle fiber size, exercise capacity, and muscle contractile function, and this was associated with reduced phosphorylation of contractile and Ca2+ handling proteins. Expression of C18ORF25 S66/67D phospho-mimetic reversed the decreased muscle force production. This work defines the divergent and canonical exercise phosphoproteome across different modalities and identifies C18ORF25 as a regulator of exercise signaling and muscle function.
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Affiliation(s)
- Ronnie Blazev
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - Christian S Carl
- August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark
| | - Yaan-Kit Ng
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - Jeffrey Molendijk
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - Christian T Voldstedlund
- August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark
| | - Yuanyuan Zhao
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia
| | - Di Xiao
- Children's Medical Research Institute, The University of Sydney, Camperdown, NSW, Australia; School of Mathematics and Statistics, The University of Sydney, Camperdown, NSW, Australia
| | - Andrew J Kueh
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Paula M Miotto
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia
| | - Vanessa R Haynes
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia
| | - Justin P Hardee
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - Jin D Chung
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - James W McNamara
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia; Murdoch Children's Research Institute and Melbourne Centre for Cardiovascular Genomics and Regenerative Medicine, The Royal Children's Hospital, Parkville, VIC, Australia
| | - Hongwei Qian
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - Paul Gregorevic
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | | | - Marco J Herold
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Thomas E Jensen
- August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark
| | - Leszek Lisowski
- Children's Medical Research Institute, The University of Sydney, Camperdown, NSW, Australia; Military Institute of Medicine, Warsaw, Poland
| | - Gordon S Lynch
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia
| | - Garron T Dodd
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia
| | - Matthew J Watt
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia
| | - Pengyi Yang
- Children's Medical Research Institute, The University of Sydney, Camperdown, NSW, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Bente Kiens
- August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark.
| | - Erik A Richter
- August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark.
| | - Benjamin L Parker
- Department of Anatomy & Physiology, The University of Melbourne, Parkville, VIC, Australia; Centre for Muscle Research, The University of Melbourne, Parkville, VIC, Australia.
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11
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Benny P, Ahn HJ, Burlingame J, Lee MJ, Miller C, Chen J, Urschitz J. Genetic risk factors associated with gestational diabetes in a multi-ethnic population. PLoS One 2021; 16:e0261137. [PMID: 34928995 PMCID: PMC8687569 DOI: 10.1371/journal.pone.0261137] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 11/24/2021] [Indexed: 11/19/2022] Open
Abstract
AIMS Genome-wide association studies have shown an increased risk of type-2-diabetes (T2DM) in patients who carry single nucleotide polymorphisms in several genes. We investigated whether the same gene loci confer a risk for gestational diabetes mellitus (GDM) in women from Hawaii, and in particular, Pacific Islander and Filipino populations. METHODS Blood was collected from 291 women with GDM and 734 matched non-diabetic controls (Pacific Islanders: 71 GDM, 197 non-diabetic controls; Filipinos: 162 GDM, 395 controls; Japanese: 58 GDM, 142 controls). Maternal DNA was used to genotype and show allele frequencies of 25 different SNPs mapped to 18 different loci. RESULTS After adjusting for age, BMI, parity and gravidity by multivariable logistic regression, several SNPs showed significant associations with GDM and were ethnicity specific. In particular, SNPs rs1113132 (EXT2), rs1111875 (HHEX), rs2237892 (KCNQ1), rs2237895 (KCNQ1), rs10830963 (MTNR1B) and rs13266634 (SLC30A8) showed significant associations with GDM in Filipinos. For Japanese, SNPs rs4402960 (IGFBP2) and rs2237892 (KCNQ1) were significantly associated with GDM. For Pacific Islanders, SNPs rs10830963 (MTNR1B) and rs13266634 (SLC30A8) showed significant associations with GDM. Individually, none of the SNPs showed a consistent association with GDM across all three investigated ethnicities. CONCLUSION Several SNPs associated with T2DM are found to confer increased risk for GDM in a multiethnic cohort in Hawaii.
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Affiliation(s)
- Paula Benny
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Hyeong Jun Ahn
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Janet Burlingame
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Men-Jean Lee
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Corrie Miller
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - John Chen
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Johann Urschitz
- Department of Anatomy, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
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12
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Liu C, Sun YV. Anticipation of Precision Diabetes and Promise of Integrative Multi-Omics. Endocrinol Metab Clin North Am 2021; 50:559-574. [PMID: 34399961 DOI: 10.1016/j.ecl.2021.05.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Precision diabetes is a concept of customizing delivery of health practices based on variability of diabetes. The authors reviewed recent research on type 2 diabetes heterogeneity and -omic biomarkers, including genomic, epigenomic, and metabolomic markers associated with type 2 diabetes. The emerging multiomics approach integrates complementary and interconnected molecular layers to provide systems level understanding of disease mechanisms and subtypes. Although the multiomic approach is not currently ready for routine clinical applications, future studies in the context of precision diabetes, particular in populations from diverse ethnic and demographic groups, may lead to improved diagnosis, treatment, and management of diabetes and diabetic complications.
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Affiliation(s)
- Chang Liu
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road Northeast, Atlanta, GA 30322, USA
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road Northeast, Atlanta, GA 30322, USA; Atlanta VA Healthcare System, 1670 Clairmont Road, Decatur, GA 30033, USA.
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13
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Arikoglu H, Erkoc-Kaya D, Ipekci SH, Gokturk F, Iscioglu F, Korez MK, Baldane S, Gonen MS. Type 2 diabetes is associated with the MTNR1B gene, a genetic bridge between circadian rhythm and glucose metabolism, in a Turkish population. Mol Biol Rep 2021; 48:4181-4189. [PMID: 34117605 DOI: 10.1007/s11033-021-06431-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 05/21/2021] [Indexed: 01/06/2023]
Abstract
Type 2 diabetes (T2D) is a complicated public health problem in Turkey as well as worldwide. Genome-wide approaches have been guiding in very challenging situations, such as the elucidation of genetic variations underlying complex diseases such as T2D. Despite intensive studies worldwide, few studies have determined the genetic susceptibility to T2D in Turkish populations. In this study, we investigated the effect of genes that are strongly associated with T2D in genome-wide association (GWA) studies, including MTNR1B, CDKAL1, THADA, ADAMTS9 and ENPP1, on T2D and its characteristic traits in a Turkish population. In 824 nonobese individuals (454 T2D patients and 370 healthy individuals), prominent variants of these GWA genes were genotyped by real-time PCR using the LightSNiP Genotyping Assay System. The SNP rs1387153 C/T, which is located 28 kb upstream of the MTNR1B gene, was significantly associated with T2D and fasting blood glucose levels (P < 0.05). The intronic SNP rs10830963 C/G in the MTNR1B gene was not associated with T2D, but it was associated with fasting blood glucose, HbA1C and LDL levels (P < 0.05). The other important GWA loci investigated in our study were not found to be associated with T2D or its traits. Only the SNP rs1044498 (A/C variation) in the ENPP1 gene was determined to be related to fasting blood glucose (P < 0.05). Our study suggests, consistent with the literature, that the MTNR1B locus, which has a prominent role in glucose regulation, is associated with T2D development by affecting blood glucose levels in our population.
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Affiliation(s)
- Hilal Arikoglu
- Department of Medical Biology, Faculty of Medicine, Selcuk University, Konya, Turkey.
| | - Dudu Erkoc-Kaya
- Department of Medical Biology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Suleyman Hilmi Ipekci
- Department of Endocrinology and Metabolic Diseases, Hisar Hospital Intercontinental, Istanbul, Turkey
| | - Fatma Gokturk
- Department of Medical Biology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Funda Iscioglu
- Department of Statistics, Faculty of Science, Ege University, Izmir, Turkey
| | - Muslu Kazim Korez
- Department of Biostatistics, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Suleyman Baldane
- Department of Endocrinology and Metabolic Diseases, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Mustafa Sait Gonen
- Department of Endocrinology and Metabolic Diseases, Faculty of Cerrahpasa Medicine, Istanbul University, Istanbul, Turkey
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14
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Jiang H, Lou P, Chen X, Wu C, Shao S. Deregulation of lncRNA HIST1H2AG-6 and AIM1-3 in peripheral blood mononuclear cells is associated with newly diagnosed type 2 diabetes. BMC Med Genomics 2021; 14:149. [PMID: 34092238 PMCID: PMC8182924 DOI: 10.1186/s12920-021-00994-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 05/31/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown. METHODS Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman's rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. RESULTS The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman's rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively). CONCLUSION The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.
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Affiliation(s)
- Hui Jiang
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, China
| | - Peian Lou
- Xuzhou Center for Disease Control Prevention, Xuzhou, 221000, China
| | - Xiaoluo Chen
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, China
| | - Chenguang Wu
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, China
| | - Shihe Shao
- School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, 212013, Jiangsu Province, China.
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15
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Heller S, Melzer MK, Azoitei N, Julier C, Kleger A. Human Pluripotent Stem Cells Go Diabetic: A Glimpse on Monogenic Variants. Front Endocrinol (Lausanne) 2021; 12:648284. [PMID: 34079523 PMCID: PMC8166226 DOI: 10.3389/fendo.2021.648284] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 04/13/2021] [Indexed: 12/17/2022] Open
Abstract
Diabetes, as one of the major diseases in industrial countries, affects over 350 million people worldwide. Type 1 (T1D) and type 2 diabetes (T2D) are the most common forms with both types having invariable genetic influence. It is accepted that a subset of all diabetes patients, generally estimated to account for 1-2% of all diabetic cases, is attributed to mutations in single genes. As only a subset of these genes has been identified and fully characterized, there is a dramatic need to understand the pathophysiological impact of genetic determinants on β-cell function and pancreatic development but also on cell replacement therapies. Pluripotent stem cells differentiated along the pancreatic lineage provide a valuable research platform to study such genes. This review summarizes current perspectives in applying this platform to study monogenic diabetes variants.
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Affiliation(s)
- Sandra Heller
- Department of Internal Medicine I, Ulm University Hospital, Ulm, Germany
| | - Michael Karl Melzer
- Department of Internal Medicine I, Ulm University Hospital, Ulm, Germany
- Department of Urology, Ulm University Hospital, Ulm, Germany
| | - Ninel Azoitei
- Department of Internal Medicine I, Ulm University Hospital, Ulm, Germany
| | - Cécile Julier
- Université de Paris, Institut Cochin, INSERM U1016, CNRS UMR-8104, Paris, France
| | - Alexander Kleger
- Department of Internal Medicine I, Ulm University Hospital, Ulm, Germany
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16
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Imamura M, Takahashi A, Matsunami M, Horikoshi M, Iwata M, Araki SI, Toyoda M, Susarla G, Ahn J, Park KH, Kong J, Moon S, Sobrin L, International Diabetic Retinopathy and Genetics CONsortium (iDRAGON), Yamauchi T, Tobe K, Maegawa H, Kadowaki T, Maeda S. Genome-wide association studies identify two novel loci conferring susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. Hum Mol Genet 2021; 30:716-726. [PMID: 33607655 PMCID: PMC9022108 DOI: 10.1093/hmg/ddab044] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 01/14/2021] [Accepted: 02/03/2021] [Indexed: 12/21/2022] Open
Abstract
Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (P < 1.0 × 10-4) in an independent case-control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stages 1 and 2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, P = 1.62 × 10-9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11-1.23, and rs140508424 within PALM2 on chromosome 9, P = 4.19 × 10-8, OR = 1.61, 95% CI 1.36-1.91. However, the association of these two loci was not replicated in Korean, European or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (P = 2.17 × 10-6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.
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Affiliation(s)
- Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa 903-0215, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa 903-0215, Japan
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
| | - Atsushi Takahashi
- Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Osaka 564-8565, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
| | - Masatoshi Matsunami
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa 903-0215, Japan
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
| | - Minoru Iwata
- First Department of Internal Medicine, University of Toyama, Toyama 930-0194, Japan
- Itoigawa Community Medical Unit, Toyama University Hospital, Toyama 930-0194, Japan
| | - Shin-ichi Araki
- Department of Medicine, Shiga University of Medical Science, Shiga 520-2192, Japan
| | - Masao Toyoda
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Tokai University School of Medicine, Kanagawa 259-1193, Japan
| | - Gayatri Susarla
- Massachusetts Eye and Ear Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | - Jeeyun Ahn
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul Municipal Government Seoul National University Boramae Medical Center, Seoul 07061, Korea
| | - Kyu Hyung Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam 13620, Korea
| | - Jinhwa Kong
- Division of Genome Research, Center for Genome Science, Korea National Institute of Health, Chungcheongbuk-do 28159, Korea
| | - Sanghoon Moon
- Division of Genome Research, Center for Genome Science, Korea National Institute of Health, Chungcheongbuk-do 28159, Korea
| | - Lucia Sobrin
- Massachusetts Eye and Ear Department of Ophthalmology, Harvard Medical School, Boston, MA 02114, USA
| | | | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Kazuyuki Tobe
- First Department of Internal Medicine, University of Toyama, Toyama 930-0194, Japan
| | - Hiroshi Maegawa
- Department of Medicine, Shiga University of Medical Science, Shiga 520-2192, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
- Toranomon Hospital, Tokyo 105-8470, Japan
- Okinaka Memorial Institute for Medical Research, Tokyo 105-8470, Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa 903-0215, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa 903-0215, Japan
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
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17
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Spracklen CN, Sim X. Progress in Defining the Genetic Contribution to Type 2 Diabetes in Individuals of East Asian Ancestry. Curr Diab Rep 2021; 21:17. [PMID: 33846905 DOI: 10.1007/s11892-021-01388-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/25/2021] [Indexed: 02/08/2023]
Abstract
PURPOSE OF REVIEW Prevalence of type 2 diabetes (T2D) and progression of complications differ between worldwide populations. While obesity is a major contributing risk factor, variations in physiological manifestations, e.g., developing T2D at lower body mass index in some populations, suggest other contributing factors. Early T2D genetic associations were mostly discovered in European ancestry populations. This review describes the progression of genetic discoveries associated with T2D in individuals of East Asian ancestry in the last 10 years and highlights the shared genetic susceptibility between the population groups and additional insights into genetic contributions to T2D. RECENT FINDINGS Through increased sample size and power, new genetic associations with T2D were discovered in East Asian ancestry populations, often with higher allele frequencies than European ancestry populations. As we continue to generate maps of T2D-associated variants across diverse populations, there will be a critical need to expand and diversify other omics resources to enable integration for clinical translation.
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Affiliation(s)
- Cassandra N Spracklen
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, 715 North Pleasant Street, 429 Arnold House, Amherst, MA, 01002, USA.
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore.
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18
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Iafusco F, Maione G, Rosanio FM, Mozzillo E, Franzese A, Tinto N. Cystic Fibrosis-Related Diabetes (CFRD): Overview of Associated Genetic Factors. Diagnostics (Basel) 2021; 11:diagnostics11030572. [PMID: 33810109 PMCID: PMC8005125 DOI: 10.3390/diagnostics11030572] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 03/19/2021] [Indexed: 12/21/2022] Open
Abstract
Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population and is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene that encodes for a chloride/bicarbonate channel expressed on the membrane of epithelial cells of the airways and of the intestine, as well as in cells with exocrine and endocrine functions. A common nonpulmonary complication of CF is cystic fibrosis-related diabetes (CFRD), a distinct form of diabetes due to insulin insufficiency or malfunction secondary to destruction/derangement of pancreatic betacells, as well as to other factors that affect their function. The prevalence of CFRD increases with age, and 40–50% of CF adults develop the disease. Several proposed hypotheses on how CFRD develops have emerged, including exocrine-driven fibrosis and destruction of the entire pancreas, as well as contrasting theories on the direct or indirect impact of CFTR mutation on islet function. Among contributors to the development of CFRD, in addition to CFTR genotype, there are other genetic factors related and not related to type 2 diabetes. This review presents an overview of the current understanding on genetic factors associated with glucose metabolism abnormalities in CF.
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Affiliation(s)
- Fernanda Iafusco
- Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; (F.I.); (G.M.)
- CEINGE Advanced Biotechnology, 80131 Naples, Italy
| | - Giovanna Maione
- Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; (F.I.); (G.M.)
- CEINGE Advanced Biotechnology, 80131 Naples, Italy
| | - Francesco Maria Rosanio
- Regional Center of Pediatric Diabetology, Department of Translational Medical Sciences, Section of Pediatrics, University of Naples “Federico II”, 80131 Naples, Italy; (F.M.R.); (E.M.); (A.F.)
| | - Enza Mozzillo
- Regional Center of Pediatric Diabetology, Department of Translational Medical Sciences, Section of Pediatrics, University of Naples “Federico II”, 80131 Naples, Italy; (F.M.R.); (E.M.); (A.F.)
| | - Adriana Franzese
- Regional Center of Pediatric Diabetology, Department of Translational Medical Sciences, Section of Pediatrics, University of Naples “Federico II”, 80131 Naples, Italy; (F.M.R.); (E.M.); (A.F.)
| | - Nadia Tinto
- Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, 80131 Naples, Italy; (F.I.); (G.M.)
- CEINGE Advanced Biotechnology, 80131 Naples, Italy
- Correspondence:
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19
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Samaha G, Wade CM, Beatty J, Lyons LA, Fleeman LM, Haase B. Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat (Felis catus). Sci Rep 2020; 10:19194. [PMID: 33154479 PMCID: PMC7644637 DOI: 10.1038/s41598-020-76166-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 10/22/2020] [Indexed: 12/30/2022] Open
Abstract
Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline SNV array and whole genome sequence data to undertake a genome wide-association study and runs of homozygosity analysis, of a case–control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, implicated in diabetes mellitus and lipid dysregulation. Mapping this condition in Burmese cats has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat.
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Affiliation(s)
- Georgina Samaha
- Faculty of Science, Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, Australia.
| | - Claire M Wade
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Julia Beatty
- Faculty of Science, Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, Australia.,Department of Infectious Diseases and Public Health, City University of Hong Kong, Kowloon, Hong Kong SAR, People's Republic of China
| | - Leslie A Lyons
- Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA
| | | | - Bianca Haase
- Faculty of Science, Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, Australia
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20
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Atashi H, Salavati M, De Koster J, Crowe MA, Opsomer G, Hostens M. Genome-wide association for metabolic clusters in early-lactation Holstein dairy cows. J Dairy Sci 2020; 103:6392-6406. [PMID: 32331880 DOI: 10.3168/jds.2019-17369] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 01/22/2020] [Indexed: 11/19/2022]
Abstract
The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and β-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starting from the first week until 50 DIM were used to determine Fourier-transform mid-infrared (FT-MIR) spectra and subsequently to classify the animals into the same metabolic clusters (BAL vs. OTR). Twenty-eight percent of the animals were categorized in the BAL group, and the remainder were classified in the OTR category. Although daily milk yield was lower in BAL cows, we found no difference in daily fat- and protein-corrected milk yield in cows from the BAL metabolic cluster compared with those in the OTR metabolic cluster. In the next step, a single-step genomic BLUP was used to identify the genomic region(s) associated with the predicted metabolic clusters. The results revealed that prediction of metabolic clusters is a highly polygenic trait regulated by many small-sized effects. The region of 36,258 to 36,295 kb on BTA27 was the highly associated region for the predicted metabolic clusters, with the closest genes to this region (ANK1 and miR-486) being related to hematopoiesis, erythropoiesis, and mammary gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows.
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Affiliation(s)
- H Atashi
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke 9820, Belgium; Department of Animal Science, Shiraz University, Shiraz 71441-65186, Iran
| | - M Salavati
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - J De Koster
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke 9820, Belgium
| | - M A Crowe
- University College Dublin, 4 Dublin, Ireland
| | - G Opsomer
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke 9820, Belgium
| | | | - M Hostens
- Department of Reproduction, Obstetrics and Herd Health, Ghent University, Merelbeke 9820, Belgium.
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A Replication Study Identified Seven SNPs Associated with Quantitative Traits of Type 2 Diabetes among Chinese Population in A Cross-Sectional Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17072439. [PMID: 32260174 PMCID: PMC7177704 DOI: 10.3390/ijerph17072439] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 03/31/2020] [Accepted: 04/01/2020] [Indexed: 12/17/2022]
Abstract
Genome-wide association studies (GWAS) have identified common variants for quantitative traits (insulin resistance and impaired insulin release) of type 2 diabetes (T2D) across different ethnics including China, but results were inconsistent. The study included 1654 subjects who were selected from the 2010–2012 China National Nutrition and Health Surveillance (CNNHS). Insulin resistance and impaired insulin release were assessed by homeostasis model assessment (HOMA). The study included 64 diabetes-related single nucleotide polymorphisms (SNPs), which were done using Mass ARRAY. A logistic regression model was employed to explore the associations of SNPs with insulin resistance and impaired insulin release by correcting for the confounders. The 5q11.2-rs4432842, RASGRP1-rs7403531, and SEC16B-rs574367 increased the risk of insulin resistance with OR = 1.23 (95% CI: 1.04–1.45, OR = 1.35 (95% CI: 1.13–1.62), OR = 1.34 (95% CI: 1.07–1.67), respectively, while MAEA-rs6815464 decreased the risk of insulin resistance (OR = 0.84, 95% CI: 0.71–1.00). CENTD2-rs1552224, TSPAN8-rs7961581 and ANK1-rs516946 was associated with increased risk of impaired insulin release with OR = 1.47 (95% CI: 1.09–1.99), OR = 1.25 (95% CI: 1.03–1.51), OR = 1.39 (95% CI: 1.07–1.81), respectively. Our findings would provide insight into the pathogenesis of individual SNPs and T2D.
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Abstract
PURPOSE OF REVIEW Genetic, socioeconomic and clinical features vary considerably among individuals with type 2 diabetes (T2D) influencing disease development, progression and response to therapy. Although a patient-centred approach to pharmacologic therapy of T2D is widely recommended, patients are often treated similarly, irrespective of the differences that may affect therapeutic response. Addressing the heterogeneity of T2D is a major task of diabetes research to lower the high rate of treatment failure as well as to reduce the risk of long-term complications. RECENT FINDINGS A pathophysiology-based clustering system seems the most promising to help in the stratification of diabetes in terms of complication risk and response to treatment. This urges for clinical studies looking at novel biomarkers related to the different metabolic pathways of T2D and able to inform about the therapeutic cluster of each patient. Here, we review the main settings of diabetes heterogeneity, to what extent it has been already addressed and the current gaps in knowledge towards a personalized therapeutic approach that considers the distinctive features of each patient.
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Affiliation(s)
- Pieralice Silvia
- Department of Medicine, Unit of Endocrinology and Diabetes, Campus Bio-Medico University of Rome, Via Alvaro del Portillo 21, 00128, Rome, Italy
| | - Zampetti Simona
- Department of Experimental Medicine, Sapienza University, Viale Regina Elena 324, 00161, Rome, Italy
| | - Maddaloni Ernesto
- Department of Experimental Medicine, Sapienza University, Viale Regina Elena 324, 00161, Rome, Italy.
| | - Buzzetti Raffaella
- Department of Experimental Medicine, Sapienza University, Viale Regina Elena 324, 00161, Rome, Italy
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Mohamadi M, Ghaedi H, Kazerouni F, Erfanian Omidvar M, Kalbasi S, Shanaki M, Miraalamy G, Rahimipour A. Deregulation of long noncoding RNA SNHG17 and TTC28-AS1 is associated with type 2 diabetes mellitus. Scandinavian Journal of Clinical and Laboratory Investigation 2019; 79:519-523. [PMID: 31509021 DOI: 10.1080/00365513.2019.1664760] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Long noncoding RNAs (lncRNAs) have emerged as key players in several biological processes and complex diseases including type 2 diabetes mellitus (T2DM). The purpose of this study was to investigate the expression levels of SNHG17 and TTC28-AS1 in T2DM patients. Quantitative real-time RT-PCR analysis was performed using peripheral blood mononuclear cells (PBMCs) samples from patients diagnosed with T2DM and healthy controls. Binary logistic regression analysis was carried out to determine the odds of development of T2DM based on expression levels of lncRNAs and clinical characteristic of the subjects. Spearman's correlation analysis was used to clarify the correlation between SNHG17 and TTC28-AS1 expressions to metabolic features. We found that SNHG17 and TTC28-AS1were down-regulated in the T2DM group compared to the healthy control group. The logistic regression revealed that body mass index (BMI), systolic blood pressure (SBP), fasting blood glucose (FBG) and TTC28-AS1 expression substantially affect T2DM susceptibility. Furthermore, expression of SNHG17 was negatively correlated with high-density lipoprotein cholesterol (HDL-C) and expression of TTC28-AS1 was positively correlated with low-density lipoprotein cholesterol (LDL-C). Decreased expressions of lncRNAs TTC28-AS1 and SNHG17 in T2DM are possibly associated with the development of T2DM.
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Affiliation(s)
- Mahroo Mohamadi
- Department of Medical Laboratory Sciences, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences , Tehran , Iran
| | - Hamid Ghaedi
- Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences , Tehran , Iran
| | - Faranak Kazerouni
- Department of Medical Laboratory Sciences, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences , Tehran , Iran
| | - Maryam Erfanian Omidvar
- Department of Clinical Biochemistry, Faculty of Medicine, Shahid Beheshti University of Medical Sciences , Tehran , Iran
| | - Saeid Kalbasi
- Department of Endocrinology, Loghman Hospital, Shahid Beheshti University of Medical Sciences , Tehran , Iran
| | - Mehrnoosh Shanaki
- Department of Medical Laboratory Sciences, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences , Tehran , Iran
| | - Ghasem Miraalamy
- Ali-Asghar Hospital, Iran University of Medical Sciences , Tehran , Iran
| | - Ali Rahimipour
- Department of Medical Laboratory Sciences, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences , Tehran , Iran.,Department of Clinical Biochemistry, Faculty of Medicine, Shahid Beheshti University of Medical Sciences , Tehran , Iran
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Che Y, Sugita N, Yoshihara A, Iwasaki M, Miyazaki H, Nakamura K, Yoshie H. A polymorphism rs6815464 in the macrophage erythroblast attacher gene is associated with low bone mineral density in postmenopausal Japanese women. Gene 2019; 700:1-6. [DOI: 10.1016/j.gene.2019.03.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Revised: 03/13/2019] [Accepted: 03/15/2019] [Indexed: 01/20/2023]
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Goto A, Yamaji T, Sawada N, Momozawa Y, Kamatani Y, Kubo M, Shimazu T, Inoue M, Noda M, Tsugane S, Iwasaki M. Diabetes and cancer risk: A Mendelian randomization study. Int J Cancer 2019; 146:712-719. [PMID: 30927373 PMCID: PMC6916579 DOI: 10.1002/ijc.32310] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 03/03/2019] [Accepted: 03/13/2019] [Indexed: 12/28/2022]
Abstract
Earlier cohort studies using conventional regression models have consistently shown an increased cancer risk among individuals with type 2 diabetes. However, reverse causality and residual confounding due to common risk factors could exist, and it remains unclear whether diabetes per se contributes to cancer development. Mendelian randomization analyses might clarify the true association between diabetes and cancer risk. We conducted a case-cohort study with 10,536 subcohort subjects and 3,541 newly diagnosed cancer cases derived from 32,949 eligible participants aged 40-69 years within the Japan Public Health Center-based Prospective Study. With 29 known type 2 diabetes susceptibility variants, we used an inverse variance-weighted method to estimate hazard ratios for the associations of diabetes with risks of total and site-specific cancers. The hazard ratios of cancer per doubling of the probability of diabetes were 1.03 (95% confidence interval [CI], 0.92-1.15) overall, 1.08 (95% CI: 0.73-1.59) for the pancreas, 0.80 (95% CI: 0.57-1.14) for the liver and 0.90 (95% CI: 0.74-1.10) for the colorectum. Additional analyses, using publicly available large-scale genome-wide association study data on colorectal cancer in Japan, resulted in a narrower CI (hazard ratio: 1.00; 95% CI: 0.93-1.07). In this prospective Mendelian randomization study with a large number of incident cancer cases, we found no strong evidence to support associations between diabetes and overall and site-specific cancer risks. Our findings suggest that there is little evidence to support the genetic role of type 2 diabetes in cancer development in the Japanese population.
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Affiliation(s)
- Atsushi Goto
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Taiki Yamaji
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Norie Sawada
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Yukihide Momozawa
- Laboratory for Genotyping DevelopmentRIKEN Center for Integrative Medical SciencesYokohamaJapan
| | - Yoichiro Kamatani
- Laboratory for Genotyping DevelopmentRIKEN Center for Integrative Medical SciencesYokohamaJapan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical SciencesYokohamaJapan
| | - Taichi Shimazu
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Manami Inoue
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Mitsuhiko Noda
- Department of Endocrinology and DiabetesSaitama Medical UniversitySaitamaJapan
| | - Shoichiro Tsugane
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
| | - Motoki Iwasaki
- Epidemiology and Prevention Group, Center for Public Health SciencesNational Cancer CenterTokyoJapan
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Che Y, Sugita N, Yoshihara A, Iwasaki M, Miyazaki H, Nakamura K, Yoshie H. MAEA rs6815464 polymorphism and periodontitis in postmenopausal Japanese females: A cross-sectional study. Arch Oral Biol 2019; 102:128-134. [PMID: 31005685 DOI: 10.1016/j.archoralbio.2019.04.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 04/11/2019] [Accepted: 04/12/2019] [Indexed: 12/23/2022]
Abstract
OBJECTIVES Macrophage erythroblast attacher (MAEA) is a membrane protein that regulates the development of mature macrophages by mediating attachment with erythroblasts. A polymorphism rs6815464 (C/G) in MAEA gene was reported to be associated with type II diabetes. Along with diabetes, osteoporosis shows an increased prevalence in postmenopausal females, and both diseases have been reported to be associated with periodontitis. Therefore, we explored the relevance of the MAEA polymorphism to periodontitis, bone mineral density (BMD) and haemoglobin A1c (HbA1c). DESIGN This was a cross-sectional study with the final sample comprised of 344 postmenopausal Japanese females. Probing pocket depth (PPD) and clinical attachment level (CAL) were measured. Genotype was determined by TaqMan assay. Blood biochemical parameters and BMD of the lumbar spine were evaluated. RESULTS No differences were found in age, body mass index, HbA1c, BMD, number of teeth, bone metabolism parameters between the genotypes. Mean CAL and percentage of sites with PPD or CAL ≥ 5 mm were higher in the G-allele carriers than in the non-carriers. Multiple logistic regression analyses revealed that G-allele carriage was associated with severe periodontitis (odds ratio = 3.73, 95% CI = 1.36-10.19). CONCLUSION Our results suggested that the MAEA gene polymorphism was independently associated with severe periodontitis.
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Affiliation(s)
- Yulan Che
- Division of Periodontology, Department of Oral Biological Science, Niigata University Graduate School of Medical and Dental Sciences, 2-5274 Gakkocho-dori, Niigata 951-8514, Japan; Department of Stomatology, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China.
| | - Noriko Sugita
- Division of Periodontology, Department of Oral Biological Science, Niigata University Graduate School of Medical and Dental Sciences, 2-5274 Gakkocho-dori, Niigata 951-8514, Japan.
| | - Akihiro Yoshihara
- Division of Oral Science for Health Promotion, Department of Oral Health and Welfare, Niigata University Graduate School of Medical and Dental Sciences, 2-5274 Gakkocho-dori, Niigata 951-8514, Japan.
| | - Masanori Iwasaki
- Division of Community Oral Health Development, Kyushu Dental University, 2-6-1, Manazuru, Kokura-kita, Kitakyushu, Fukuoka 803-8580, Japan.
| | - Hideo Miyazaki
- Division of Preventive Dentistry, Department of Oral Health Science, Niigata University Graduate School of Medical and Dental Sciences, 2-5274 Gakkocho-dori, Niigata 951-8514, Japan.
| | - Kazutoshi Nakamura
- Division of Social and Environmental Medicine, Department of Community Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata City 951-8510, Japan.
| | - Hiromasa Yoshie
- Division of Periodontology, Department of Oral Biological Science, Niigata University Graduate School of Medical and Dental Sciences, 2-5274 Gakkocho-dori, Niigata 951-8514, Japan.
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Genome-wide gene-based analyses of weight loss interventions identify a potential role for NKX6.3 in metabolism. Nat Commun 2019; 10:540. [PMID: 30710084 PMCID: PMC6358625 DOI: 10.1038/s41467-019-08492-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Accepted: 01/07/2019] [Indexed: 12/31/2022] Open
Abstract
Hundreds of genetic variants have been associated with Body Mass Index (BMI) through genome-wide association studies (GWAS) using observational cohorts. However, the genetic contribution to efficient weight loss in response to dietary intervention remains unknown. We perform a GWAS in two large low-caloric diet intervention cohorts of obese participants. Two loci close to NKX6.3/MIR486 and RBSG4 are identified in the Canadian discovery cohort (n = 1166) and replicated in the DiOGenes cohort (n = 789). Modulation of HGTX (NKX6.3 ortholog) levels in Drosophila melanogaster leads to significantly altered triglyceride levels. Additional tissue-specific experiments demonstrate an action through the oenocytes, fly hepatocyte-like cells that regulate lipid metabolism. Our results identify genetic variants associated with the efficacy of weight loss in obese subjects and identify a role for NKX6.3 in lipid metabolism, and thereby possibly weight control. Individuals show large variability in their capacity to lose weight and maintain this weight. Here, the authors perform GWAS in two weight loss intervention cohorts and identify two genetic loci associated with weight loss that are taken forward for Bayesian fine-mapping and functional assessment in flies.
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Erfanian Omidvar M, Ghaedi H, Kazerouni F, Kalbasi S, Shanaki M, Miraalamy G, Zare A, Rahimipour A. Clinical significance of long noncoding RNA VIM-AS1 and CTBP1-AS2 expression in type 2 diabetes. J Cell Biochem 2018; 120:9315-9323. [PMID: 30506719 DOI: 10.1002/jcb.28206] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 11/15/2018] [Indexed: 12/14/2022]
Abstract
BACKGROUND/AIMS The risk of type 2 diabetes (T2D) is determined by a combination of genetic and environmental factors. Multiple studies have proposed that long noncoding RNAs (lncRNAs) are crucial molecules in regulating several biological processes and complex diseases. The study was aimed at investigating the association between the expression levels of lncRNA VIM-AS1, lncRNA CTBP1-AS2, and T2D susceptibility. METHODS lncRNA VIM-AS1 and lncRNA CTBP1-AS2 in the peripheral blood mononuclear cell (PBMC) of 100 healthy individuals and 100 T2D patients were collected for Quantitative Real-Time RT-PCR analysis. A logistic regression was performed to understand whether the likelihood of T2D can be predicted based on the expression levels of lncRNA VIM-AS1 and lncRNA CTBP1-AS2. Receiver operating characteristic (ROC) analysis was also performed to determine the statistical analysis of VIM-AS1 and CTBP1-AS2 levels in 200 samples. RESULTS Our results display that decreased levels of VIM-AS1 and CTBP1-AS2 in PBMC were associated with diabetes in Iranian population. The logistic regression revealed that Systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), Fasting blood glucose (FBG) and CTBP1-AS2 are substantial predictors of T2D. The ROC analysis of CTBP1-AS2 revealed the area under the ROC curve (AUC) of 0.68 with a sensitivity of 58.7% and specificity of 75.3% in distinguishing nondiabetic from diabetic subjects. The ROC analysis of VIM-AS1 determined AUC of 0.63 with a sensitivity of 56.1% and specificity of 68.37% in distinguishing the two diagnostic groups. CONCLUSION lncRNA VIM-AS1 and lncRNA CTBP1-AS2 expression levels are associated with T2D susceptibility.
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Affiliation(s)
- Maryam Erfanian Omidvar
- Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hamid Ghaedi
- Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Faranak Kazerouni
- Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saeid Kalbasi
- Department of endocrinology, Loghman Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehrnoosh Shanaki
- Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ghasem Miraalamy
- Ali-Asghar Hospital, Iran University of Medical Sciences, Tehran, Iran
| | - Ali Zare
- Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ali Rahimipour
- Department of Medical Laboratory Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Kurochkina N, Bhaskar M, Yadav SP, Pant HC. Phosphorylation, Dephosphorylation, and Multiprotein Assemblies Regulate Dynamic Behavior of Neuronal Cytoskeleton: A Mini-Review. Front Mol Neurosci 2018; 11:373. [PMID: 30349458 PMCID: PMC6186834 DOI: 10.3389/fnmol.2018.00373] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2018] [Accepted: 09/20/2018] [Indexed: 12/28/2022] Open
Abstract
Cellular localization, assembly and abnormal aggregation of neurofilaments depend on phosphorylation. Pathological processes associated with neurodegeneration exhibit aberrant accumulation of microtubule associated aggregated forms of hyperphosphorylated neuronal protein tau in cell bodies. These processes are critical for the disease progression in patients suffering from Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis. In healthy cells, tau is localized in axons. Topographic regulation suggests that whereas the sites of synthesis of kinases and neurofilaments are the cell bodies, and sites of their functional assemblies are axons, phosphorylation/dephosphorylation are the key processes that arrange the molecules at their precise locations. Phosphorylation sites in the dynamic developmental and degenerative processes differ. Not all these processes are well understood. New advancements identify epigenetic factors involved in AD which account for the influence of age-related environment/genome interactions leading to the disease. Progress in proteomics highlights previously found major proteins and adds more to the list of those involved in AD. New key elements of specificity provide determinants of molecular recognition important for the assembly of macromolecular complexes. In this review, we discuss aberrant spatial distribution of neuronal polypeptides observed in neuropathies: aggregation, association with proteins of the neuronal cytoskeleton, and phosphorylation dependent dynamics. Particularly, we emphasize recent advancements in understanding the function and determinants of specific association of molecules involved in Alzheimer's disease with respect to the topographic regulation of phosphorylation in neuronal cytoskeleton and implications for the design of new therapies. Further, we address the role of various filament systems in maintenance of the shape, rigidity and dynamics of the cytoskeleton.
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Affiliation(s)
- Natalya Kurochkina
- Department of Biophysics, The School of Theoretical Modeling, Washington, DC, United States
| | - Manju Bhaskar
- Neuronal Cytoskeletal Protein Regulation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Sharda Prasad Yadav
- Neuronal Cytoskeletal Protein Regulation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Harish C. Pant
- Neuronal Cytoskeletal Protein Regulation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
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O’Beirne SL, Salit J, Rodriguez-Flores JL, Staudt MR, Abi Khalil C, Fakhro KA, Robay A, Ramstetter MD, Malek JA, Zirie M, Jayyousi A, Badii R, Al-Nabet Al-Marri A, Bener A, Mahmoud M, Chiuchiolo MJ, Al-Shakaki A, Chidiac O, Stadler D, Mezey JG, Crystal RG. Exome sequencing-based identification of novel type 2 diabetes risk allele loci in the Qatari population. PLoS One 2018; 13:e0199837. [PMID: 30212457 PMCID: PMC6136697 DOI: 10.1371/journal.pone.0199837] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Accepted: 06/14/2018] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Type 2 diabetes (T2D) susceptibility is influenced by genetic and lifestyle factors. To date, the majority of genetic studies of T2D have been in populations of European and Asian descent. The focus of this study is on genetic variations underlying T2D in Qataris, a population with one of the highest incidences of T2D worldwide. RESULTS Illumina HiSeq exome sequencing was performed on 864 Qatari subjects (574 T2D cases, 290 controls). Sequence kernel association test (SKAT) gene-based analysis identified an association for low frequency potentially deleterious variants in 6 genes. However, these findings were not replicated by SKAT analysis in an independent cohort of 12,699 exomes, primarly due to the absence of low frequency potentially deleterious variants in 5 of the 6 genes. Interestingly one of the genes identified, catenin beta 1 (CTNNB1, β-catenin), is the key effector of the Wnt pathway and interacts with the nuclear receptor transcription factor 7-like 2 (TCF7L2), variants which are the most strongly associated with risk of developing T2D worldwide. Single variant analysis did not identify any associated variants, suggesting the SKAT association signal was not driven by individual variants. None of the 6 associated genes were among 634 previously described T2D genes. CONCLUSIONS The observation that genes not previously linked to T2D in prior studies of European and Asian populations are associated with T2D in Qatar provides new insights into the complexity of T2D pathogenesis and emphasizes the importance of understudied populations when assessing genetic variation in the pathogenesis of common disorders.
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Affiliation(s)
- Sarah L. O’Beirne
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Jacqueline Salit
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Juan L. Rodriguez-Flores
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Michelle R. Staudt
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Charbel Abi Khalil
- Department of Genetic Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Khalid A. Fakhro
- Department of Genetic Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
- Division of Translational Medicine, Sidra Medical Research Centre, Doha, Qatar
| | - Amal Robay
- Department of Genetic Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Monica D. Ramstetter
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, United States of America
| | - Joel A. Malek
- Department of Genetic Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Mahmoud Zirie
- Department of Medicine, Hamad Medical Corporation, Doha, Qatar
| | - Amin Jayyousi
- Department of Medicine, Hamad Medical Corporation, Doha, Qatar
| | - Ramin Badii
- Laboratory Medicine and Pathology, Hamad Medical Corporation, Doha, Qatar
| | | | - Abdulbari Bener
- Department of Medicine, Hamad Medical Corporation, Doha, Qatar
| | - Mai Mahmoud
- Department of Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Maria J. Chiuchiolo
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Alya Al-Shakaki
- Department of Genetic Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Omar Chidiac
- Department of Genetic Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Dora Stadler
- Department of Medicine, Weill Cornell Medical College-Qatar, Doha, Qatar
| | - Jason G. Mezey
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, United States of America
| | - Ronald G. Crystal
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, United States of America
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America
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Yokoyama N, Ishimura T, Oda T, Ogawa S, Yamamoto K, Fujisawa M. Association of the PCK2 Gene Polymorphism With New-onset Glucose Intolerance in Japanese Kidney Transplant Recipients. Transplant Proc 2018; 50:1045-1049. [PMID: 29731064 DOI: 10.1016/j.transproceed.2018.01.042] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 01/22/2018] [Indexed: 01/18/2023]
Abstract
BACKGROUND New-onset diabetes mellitus after transplantation (NODAT) is a risk factor for both cardiovascular disease and poor graft survival after kidney transplantation (KTx). In this study, we identified single-nucleotide polymorphisms (SNPs) in genes involved in glucose metabolism and examined the correlation between these SNPs and glucose intolerance after KTx. METHODS Thirty-eight patients with normal glucose tolerance before KTx were included in this study. Patients with plasma glucose levels of >140 mg/dL at 120 minutes on the 75-g oral glucose tolerance test at 1 year after KTx were classified as having new-onset impaired glucose tolerance (NIGT). We identified 8 SNPs in 7 genes that are involved in glucose metabolism among the patients included in this study, and compared the prevalence rate of NIGT among SNPs in each gene. RESULTS Of the 38 patients, 11 (28.9%) were diagnosed with NIGT. For rs4982856 in the PCK2 gene, the distribution of genotypes among the total patient population was as follows: T/T, 12 (31.6%); T/C, 22 (57.9%); and C/C, 4 (10.5%). Seven of 11 patients with NIGT had the T/T genotype of rs4982856, whereas only 5 of 27 patients with normal glucose tolerance had this genotype. The T allele frequency of the rs4982856 was significantly higher in the NIGT group than in the normal group (81.8 vs 52.8%, respectively; P = .015). CONCLUSION Our study indicates that the T allele of the rs4982856 SNP in the PCK2 gene may be a risk factor for glucose intolerance after KTx.
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Affiliation(s)
- N Yokoyama
- Division of Urology, Department of Surgery Related, Faculty of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
| | - T Ishimura
- Division of Urology, Department of Surgery Related, Faculty of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.
| | - T Oda
- Division of Urology, Department of Surgery Related, Faculty of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
| | - S Ogawa
- Division of Urology, Department of Surgery Related, Faculty of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
| | - K Yamamoto
- Department of Pharmacy, Kobe University Hospital, Kobe, Japan
| | - M Fujisawa
- Division of Urology, Department of Surgery Related, Faculty of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
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Liu J, Yagi K, Nohara A, Chujo D, Ohbatake A, Fujimoto A, Miyamoto Y, Kobayashi J, Yamagishi M. High frequency of type 2 diabetes and impaired glucose tolerance in Japanese subjects with the angiopoietin-like protein 8 R59W variant. J Clin Lipidol 2018; 12:331-337. [PMID: 29397342 DOI: 10.1016/j.jacl.2017.12.011] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 11/30/2017] [Accepted: 12/19/2017] [Indexed: 10/18/2022]
Abstract
BACKGROUND Angiopoietin-like protein 8 (ANGPTL8) is considered to be metabolically multifunctional. One notable function still to be elucidated definitively is a betatrophic role in protecting and preserving pancreatic beta-cell function. There is, however, a paucity of data regarding the role of ANGPTL8 in the etiology of type 2 diabetes (T2D), but some findings of human research have suggested the potential for significant involvement. OBJECTIVE To examine the frequency of T2D and impaired glucose tolerance (IGT) in Japanese subjects with the ANGPTL8 R59W variant. METHODS ANGPTL8 R59W (Rs2278426, c.194C > T) was determined by polymerase chain reaction-restriction fragment length polymorphism using the restriction enzyme FokI in 797 consecutive Japanese individuals. Subjects with triglyceride levels greater than or equal to 150 mg/dL were considered to be hypertriglyceridemic. RESULTS Genotype frequencies of ANGPTL8 R59W were as follows: wild-type RR (C/C) 53.5%, RW (C/T) 36.6%, and WW (T/T) 9.9%. T2D and IGT were significantly prevalent in WW and RW subjects relative to RR among all 797 subjects (P = .0138) and also in hypertriglyceridemic subjects (P = .0015). In multiple logistic regression models for the existence of T2D and IGT in hypertriglyceridemic subjects, the odds ratio for heterozygote RW and homozygote WW genotypes to wild-type RR was 2.406 (P = .0017) after controlling the risk factors of age, gender, and body mass index as covariates. CONCLUSIONS The frequency of ANGPTL8 R59W is significantly higher in Japanese subjects than in other ethnic groups. The rates of T2D and IGT were greater in subjects with the R59W variant. These findings indicate that ANGPTL8 is a participant in diabetes and a potential therapeutic target for T2D prevention, especially in East Asians.
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Affiliation(s)
- Jianhui Liu
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan.
| | - Kunimasa Yagi
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan; First Department of Internal Medicine, Toyama University, Toyama, Japan
| | - Atsushi Nohara
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan
| | - Daisuke Chujo
- National Center for Global Health and Medicine, Tokyo, Japan
| | - Azusa Ohbatake
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan
| | - Aya Fujimoto
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan
| | - Yukiko Miyamoto
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan
| | - Junji Kobayashi
- Department of General Medicine, Kanazawa Medical University, Kahoku, Japan
| | - Masakazu Yamagishi
- Department of Internal Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Japan
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Sun W, Yao S, Tang J, Liu S, Chen J, Deng D, Zeng C. Integrative analysis of super enhancer SNPs for type 2 diabetes. PLoS One 2018; 13:e0192105. [PMID: 29385209 PMCID: PMC5792005 DOI: 10.1371/journal.pone.0192105] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 01/18/2018] [Indexed: 01/01/2023] Open
Abstract
Clinical studies in type 2 diabetes (T2D) primarily focused on the single nucleotide polymorphisms (SNPs) located in protein-coding regions. Recently, the SNPs located in noncoding regions have also been recognized to play an important role in disease susceptibility. The super enhancer is a cluster of transcriptional enhancers located in noncoding regions. It plays a critical role in cell-type specific gene expression. However, the exact mechanism of the super enhancer SNPs for T2D remains unclear. In this study, we integrated genome-wide association studies (GWASs) and T2D cell/tissue-specific histone modification ChIP-seq data to identify T2D-associated SNPs in super enhancer, followed by comprehensive bioinformatics analyses to further explore the functional importance of these SNPs. We identified several interesting T2D super enhancer SNPs. Interesting, most of them were clustered within the same or neighboring super enhancers. A number of SNPs are involved in chromatin interactive regulation and/or potentially influence the binding affinity of transcription factors. Gene Ontology (GO) analysis showed a significant enrichment in several well-known signaling pathways and regulatory process, e.g. WNT signaling pathway, which plays a key role in T2D metabolism. Our results highlighted the potential functional importance of T2D super enhancer SNPs, which may yield novel insights into the pathogenesis of T2D.
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Affiliation(s)
- Weiping Sun
- Department of Geriatrics, the First People's Hospital of Xiangtan City, Xiangtan, PR, China
| | - Sihong Yao
- Department of Clinical Medicine, Jishou University School of Medicine, Jishou, PR, China
| | - Jielong Tang
- Department of Endocrinology, the Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR, China
| | - Shuai Liu
- Department of Endocrinology, the Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR, China
| | - Juan Chen
- Department of Geriatrics, the First People's Hospital of Xiangtan City, Xiangtan, PR, China
| | - Daqing Deng
- Department of Geriatrics, the First People's Hospital of Xiangtan City, Xiangtan, PR, China
| | - Chunping Zeng
- Department of Endocrinology, the Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR, China
- * E-mail:
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Szabo M, Máté B, Csép K, Benedek T. Genetic Approaches to the Study of Gene Variants and Their Impact on the Pathophysiology of Type 2 Diabetes. Biochem Genet 2017; 56:22-55. [DOI: 10.1007/s10528-017-9827-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 10/06/2017] [Indexed: 12/18/2022]
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Sharp GC, Salas LA, Monnereau C, Allard C, Yousefi P, Everson TM, Bohlin J, Xu Z, Huang RC, Reese SE, Xu CJ, Baïz N, Hoyo C, Agha G, Roy R, Holloway JW, Ghantous A, Merid SK, Bakulski KM, Küpers LK, Zhang H, Richmond RC, Page CM, Duijts L, Lie RT, Melton PE, Vonk JM, Nohr EA, Williams-DeVane C, Huen K, Rifas-Shiman SL, Ruiz-Arenas C, Gonseth S, Rezwan FI, Herceg Z, Ekström S, Croen L, Falahi F, Perron P, Karagas MR, Quraishi BM, Suderman M, Magnus MC, Jaddoe VWV, Taylor JA, Anderson D, Zhao S, Smit HA, Josey MJ, Bradman A, Baccarelli AA, Bustamante M, Håberg SE, Pershagen G, Hertz-Picciotto I, Newschaffer C, Corpeleijn E, Bouchard L, Lawlor DA, Maguire RL, Barcellos LF, Davey Smith G, Eskenazi B, Karmaus W, Marsit CJ, Hivert MF, Snieder H, Fallin MD, Melén E, Munthe-Kaas MC, Arshad H, Wiemels JL, Annesi-Maesano I, Vrijheid M, Oken E, Holland N, Murphy SK, Sørensen TIA, Koppelman GH, Newnham JP, Wilcox AJ, Nystad W, London SJ, Felix JF, Relton CL. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium. Hum Mol Genet 2017; 26:4067-4085. [PMID: 29016858 PMCID: PMC5656174 DOI: 10.1093/hmg/ddx290] [Citation(s) in RCA: 172] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 06/23/2017] [Accepted: 07/17/2017] [Indexed: 12/16/2022] Open
Abstract
Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for acausal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology.
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Affiliation(s)
- Gemma C Sharp
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
| | - Lucas A Salas
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Claire Monnereau
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier, Université de Sherbrooke, QC, Canada
| | - Paul Yousefi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Todd M Everson
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jon Bohlin
- Department of Infection Epidemiology and Modeling, Norwegian Institute of Public Health, Oslo, Norway
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Crawley, WA 6009, Australia
| | - Sarah E Reese
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Cheng-Jian Xu
- Department of Pulmonology, GRIAC Research Institute
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Nour Baïz
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Sorbonne Université, UPMC Univ Paris 06, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Saint-Antoine Medical School, Paris, France
| | - Cathrine Hoyo
- Department of Biological Sciences
- Center for Human Health and the Environment, North Carolina State University, NC, USA
| | - Golareh Agha
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ritu Roy
- University of California San Francisco, CA, USA
- HDF Comprehensive Cancer Center, University of California, San Francisco, CA, USA
- Computational Biology Core
| | - John W Holloway
- Human Development & Health, Faculty of Medicine, University of Southampton, UK
| | - Akram Ghantous
- Epigenetics Group, International Agency for Research on Cancer, Lyon, France
| | - Simon K Merid
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, MI, USA
| | - Leanne K Küpers
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Christian M Page
- Department of Non-Communicable Disease, Norwegian Institute of Public Health, Oslo, Norway
| | - Liesbeth Duijts
- The Generation R Study Group
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Norway
- Medical Birth Registry of Norway, Norwegian Institute of Public Health, Bergen, Norway
| | - Phillip E Melton
- The Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University Health Sciences, Curtin University and Faculty of Medicine Dentistry & Health Sciences, The University of Western Australia, Perth, Australia
- Faculty of Medicine Dentistry & Health Sciences, The University of Western Australia, Perth, Australia
| | - Judith M Vonk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, GRIAC Research Institute Groningen, The Netherlands
| | - Ellen A Nohr
- Research Unit for Gynaecology and Obstetrics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | | | - Karen Huen
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Sheryl L Rifas-Shiman
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA
| | - Carlos Ruiz-Arenas
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Semira Gonseth
- Department of Epidemiology and Biostatistics, University of California San Francisco, CA, USA
- School of Public Health, University of California Berkeley, CA, USA
| | - Faisal I Rezwan
- Human Development & Health, Faculty of Medicine, University of Southampton, UK
| | - Zdenko Herceg
- Epigenetics Group, International Agency for Research on Cancer, Lyon, France
| | - Sandra Ekström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lisa Croen
- Division of Research, Kaiser Permanente Northern California, CA, UDA
| | - Fahimeh Falahi
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Patrice Perron
- Centre de Recherche du Centre Hospitalier, Université de Sherbrooke, QC, Canada
- Department of Medicine, Université de Sherbrooke, QC, Canada
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Children's Environmental Health & Disease Prevention Research Center at Dartmouth, Hanover, NH, USA
| | - Bilal M Quraishi
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Maria C Magnus
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
- Department of Non-Communicable Disease, Norwegian Institute of Public Health, Oslo, Norway
| | - Vincent W V Jaddoe
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
- Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Denise Anderson
- Telethon Kids Institute, University of Western Australia, Crawley, WA 6009, Australia
| | - Shanshan Zhao
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Henriette A Smit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Michele J Josey
- Department of Biological & Biomedical Sciences, North Carolina Central University, Durham, NC, USA
- Epidemiology and Biostatistics Department, University of South Carolina (Columbia), SC, USA
| | - Asa Bradman
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Mariona Bustamante
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Siri E Håberg
- Domain of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Center for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Irva Hertz-Picciotto
- Department of Public Health, School of Medicine, University of California, Davis, CA, USA
| | - Craig Newschaffer
- AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, USA
| | - Eva Corpeleijn
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Luigi Bouchard
- Department of Biochemistry, Université de Sherbrooke, QC, Canada
- ECOGENE-21 and Lipid Clinic, Chicoutimi Hospital, Saguenay, QC, Canada
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Rachel L Maguire
- Department of Biological Sciences
- Department of Community and Family Medicine, Duke University Medical Center, Durham, NC, USA
| | - Lisa F Barcellos
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - George Davey Smith
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Wilfried Karmaus
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Carmen J Marsit
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Marie-France Hivert
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA
- Department of Medicine, Université de Sherbrooke, QC, Canada
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M Daniele Fallin
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Erik Melén
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Center for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
- Sachs’ Children’s Hospital, South General Hospital, Stockholm, Sweden
| | - Monica C Munthe-Kaas
- Department of Pediatric and Adolescent Medicine, Oslo University Hospital, Norway
- Norwegian Institute of Public Health, Oslo Norway
| | - Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- NIHR Respiratory Biomedical Research Unit, University Hospital Southampton, Southampton, UK
- The David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
| | - Joseph L Wiemels
- Department of Epidemiology and Biostatistics, University of California San Francisco, CA, USA
| | - Isabella Annesi-Maesano
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Sorbonne Université, UPMC Univ Paris 06, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Saint-Antoine Medical School, Paris, France
| | - Martine Vrijheid
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Emily Oken
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA
| | - Nina Holland
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC, USA
| | - Thorkild I A Sørensen
- MRC Integrative Epidemiology Unit
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section on Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
| | - Gerard H Koppelman
- Department of Paediatric Pulmonology and Paediatric Allergy, University of Groningen, University Medical Center Groningen, Beatrix Children’s Hospital, GRIAC Research Institute, Groningen, the Netherlands
| | - John P Newnham
- School of Women's and Infants' Health, The University of Western Australia, Crawley, WA 6009, Australia
| | - Allen J Wilcox
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Wenche Nystad
- Department of Non-Communicable Disease, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Janine F Felix
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit
- School of Social and Community Medicine
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Roubroeks JAY, Smith RG, van den Hove DLA, Lunnon K. Epigenetics and DNA methylomic profiling in Alzheimer's disease and other neurodegenerative diseases. J Neurochem 2017; 143:158-170. [PMID: 28805248 DOI: 10.1111/jnc.14148] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 08/08/2017] [Accepted: 08/09/2017] [Indexed: 12/13/2022]
Abstract
Recent studies have suggested a role for epigenetic mechanisms in the complex etiology of various neurodegenerative diseases. In this review, we discuss advances that have been made toward understanding the role of epigenetic processes in neurodegenerative disorders, with a particular focus on Alzheimer's disease, where the most extensive studies have been undertaken to date. We provide a brief overview of DNA modifications, followed by a summarization of studies of DNA modifications in Alzheimer's disease and other neurodegenerative diseases.
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Affiliation(s)
| | - Rebecca G Smith
- University of Exeter Medical School, University of Exeter, Devon, UK
| | - Daniel L A van den Hove
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands.,Laboratory of Translational Neuroscience, Division of Molecular Psychiatry, Department of Psychiatry, Psychosomatics and Psychotherapy, University of Würzburg, Würzburg, Germany
| | - Katie Lunnon
- University of Exeter Medical School, University of Exeter, Devon, UK
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Sun L, Zhang X, Wang T, Chen M, Qiao H. Association of ANK1 variants with new-onset type 2 diabetes in a Han Chinese population from northeast China. Exp Ther Med 2017; 14:3184-3190. [PMID: 28912869 DOI: 10.3892/etm.2017.4866] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 06/08/2017] [Indexed: 12/30/2022] Open
Abstract
Previous studies have identified three loci (rs4737009, rs515071 and rs516946) in ankyrin 1 (ANK1) that are associated with type 2 diabetes mellitus (T2DM) in a number of ethnic groups. However, the impact of single nucleotide polymorphisms (SNPs) of ANK1 on T2DM in a Han Chinese population from northeast China has not yet been studied. The present study was undertaken to investigate the relationship between the ANK1 gene and new-onset T2DM in northeastern China. Three widely studied variants were genotyped and analyzed for T2DM susceptibility in 1,962 Chinese subjects (996 with T2DM and 966 healthy controls). Genotyping was performed using SNPscan™. The single-locus analysis, identified differences in the expression of rs515071 and rs516946 between cases and controls, with an odds ratio (OR) of 1.31 [95% confidence interval (CI), 1.10-1.55; P=0.002] and 1.32 (95% CI, 1.09-1.61; P=0.005) respectively, while there were no differences in the expression of rs4737009 between the groups. For the SNP of rs515071, the presence of AA or GA significantly reduced the risk of T2DM compared with GG (adjusted P=0.019, OR=0.78; 95% CI, 0.63-0.96). With respect to rs516946, individuals carrying TT or CT exhibited a decreased risk of T2DM compared with those with the CC allele (adjusted P=0.040, OR=0.79; 95% CI, 0.63-0.99). Furthermore, haplotype analysis indicated that the haplotype frequency of GC in T2DM cases was significantly higher than in controls (P=0.002, OR=1.31; 95% CI, 1.10-1.55). Furthermore, the rs516946-CC genotype was associated with a larger waist circumference (P=0.031). The present data indicated that ANK1 was a potential T2DM susceptibility gene in a Han Chinese population from northeastern China.
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Affiliation(s)
- Lulu Sun
- Department of Endocrinology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
| | - Xuelong Zhang
- Laboratory of Medical Genetics, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
| | - Tongtong Wang
- Department of Endocrinology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
| | - Meijun Chen
- Department of Endocrinology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
| | - Hong Qiao
- Department of Endocrinology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
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Yamada Y, Sakuma J, Takeuchi I, Yasukochi Y, Kato K, Oguri M, Fujimaki T, Horibe H, Muramatsu M, Sawabe M, Fujiwara Y, Taniguchi Y, Obuchi S, Kawai H, Shinkai S, Mori S, Arai T, Tanaka M. Identification of five genetic variants as novel determinants of type 2 diabetes mellitus in Japanese by exome-wide association studies. Oncotarget 2017; 8:80492-80505. [PMID: 29113320 PMCID: PMC5655215 DOI: 10.18632/oncotarget.19287] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 06/09/2017] [Indexed: 12/20/2022] Open
Abstract
We performed exome-wide association studies to identify single nucleotide polymorphisms that either influence fasting plasma glucose level or blood hemoglobin A1c content or confer susceptibility to type 2 diabetes mellitus in Japanese. Exome-wide association studies were performed with the use of Illumina Human Exome-12 DNA Analysis or Infinium Exome-24 BeadChip arrays and with 11,729 or 8635 subjects for fasting plasma glucose level or blood hemoglobin A1c content, respectively, or with 14,023 subjects for type 2 diabetes mellitus (3573 cases, 10,450 controls). The relation of genotypes of 41,265 polymorphisms to fasting plasma glucose level or blood hemoglobin A1c content was examined by linear regression analysis. After Bonferroni's correction, 41 and 17 polymorphisms were significantly (P < 1.21 × 10-6) associated with fasting plasma glucose level or blood hemoglobin A1c content, respectively, with two polymorphisms (rs139421991, rs189305583) being associated with both. Examination of the relation of allele frequencies to type 2 diabetes mellitus with Fisher's exact test revealed that 87 polymorphisms were significantly (P < 1.21 × 10-6) associated with type 2 diabetes mellitus. Subsequent multivariable logistic regression analysis with adjustment for age and sex showed that four polymorphisms (rs138313632, rs76974938, rs139012426, rs147317864) were significantly (P < 1.44 × 10-4) associated with type 2 diabetes mellitus, with rs138313632 and rs139012426 also being associated with fasting plasma glucose and rs76974938 with blood hemoglobin A1c. Five polymorphisms-rs139421991 of CAT, rs189305583 of PDCL2, rs138313632 of RUFY1, rs139012426 of LOC100505549, and rs76974938 of C21orf59-may be novel determinants of type 2 diabetes mellitus.
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Affiliation(s)
- Yoshiji Yamada
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Japan
| | - Jun Sakuma
- CREST, Japan Science and Technology Agency, Kawaguchi, Japan.,Computer Science Department, College of Information Science, University of Tsukuba, Tsukuba, Japan.,RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Ichiro Takeuchi
- CREST, Japan Science and Technology Agency, Kawaguchi, Japan.,RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.,Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan
| | - Yoshiki Yasukochi
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Japan
| | - Kimihiko Kato
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,Department of Internal Medicine, Meitoh Hospital, Nagoya, Japan
| | - Mitsutoshi Oguri
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,Department of Cardiology, Kasugai Municipal Hospital, Kasugai, Japan
| | - Tetsuo Fujimaki
- Department of Cardiovascular Medicine, Inabe General Hospital, Inabe, Japan
| | - Hideki Horibe
- Department of Cardiovascular Medicine, Gifu Prefectural Tajimi Hospital, Tajimi, Japan
| | - Masaaki Muramatsu
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Motoji Sawabe
- Section of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshinori Fujiwara
- Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Yu Taniguchi
- Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Shuichi Obuchi
- Research Team for Promoting Support System for Home Care, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Hisashi Kawai
- Research Team for Promoting Support System for Home Care, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Shoji Shinkai
- Research Team for Social Participation and Health Promotion, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Seijiro Mori
- Center for Promotion of Clinical Investigation, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
| | - Tomio Arai
- Department of Pathology, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
| | - Masashi Tanaka
- Department of Clinical Laboratory, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
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39
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Zarkoob H, Lewinsky S, Almgren P, Melander O, Fakhrai-Rad H. Utilization of genetic data can improve the prediction of type 2 diabetes incidence in a Swedish cohort. PLoS One 2017; 12:e0180180. [PMID: 28700623 PMCID: PMC5507496 DOI: 10.1371/journal.pone.0180180] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 06/12/2017] [Indexed: 01/21/2023] Open
Abstract
The aim of this study was to measure the impact of genetic data in improving the prediction of type 2 diabetes (T2D) in the Malmö Diet and Cancer Study cohort. The current study was performed in 3,426 Swedish individuals and utilizes of a set of genetic and environmental risk data. We first validated our environmental risk model by comparing it to both the Finnish Diabetes Risk Score and the T2D risk model derived from the Framingham Offspring Study. The area under the curve (AUC) for our environmental model was 0.72 [95% CI, 0.69–0.74], which was significantly better than both the Finnish (0.64 [95% CI, 0.61–0.66], p-value < 1 x 10−4) and Framingham (0.69 [95% CI, 0.66–0.71], p-value = 0.0017) risk scores. We then verified that the genetic data has a statistically significant positive correlation with incidence of T2D in the studied population. We also verified that adding genetic data slightly but statistically increased the AUC of a model based only on environmental risk factors (RFs, AUC shift +1.0% from 0.72 to 0.73, p-value = 0.042). To study the dependence of the results on the environmental RFs, we divided the population into two equally sized risk groups based only on their environmental risk and repeated the same analysis within each subpopulation. While there is a statistically significant positive correlation between the genetic data and incidence of T2D in both environmental risk categories, the positive shift in the AUC remains statistically significant only in the category with the lower environmental risk. These results demonstrate that genetic data can be used to increase the accuracy of T2D prediction. Also, the data suggests that genetic data is more valuable in improving T2D prediction in populations with lower environmental risk. This suggests that the impact of genetic data depends on the environmental risk of the studied population and thus genetic association studies should be performed in light of the underlying environmental risk of the population.
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Affiliation(s)
- Hadi Zarkoob
- BaseHealth Inc., Sunnyvale, California, United States of America
| | - Sarah Lewinsky
- BaseHealth Inc., Sunnyvale, California, United States of America
| | - Peter Almgren
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
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40
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Mastroeni D, Sekar S, Nolz J, Delvaux E, Lunnon K, Mill J, Liang WS, Coleman PD. ANK1 is up-regulated in laser captured microglia in Alzheimer's brain; the importance of addressing cellular heterogeneity. PLoS One 2017; 12:e0177814. [PMID: 28700589 PMCID: PMC5507536 DOI: 10.1371/journal.pone.0177814] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 05/03/2017] [Indexed: 01/19/2023] Open
Abstract
Recent epigenetic association studies have identified a new gene, ANK1, in the pathogenesis of Alzheimer’s disease (AD). Although strong associations were observed, brain homogenates were used to generate the data, introducing complications because of the range of cell types analyzed. In order to address the issue of cellular heterogeneity in homogenate samples we isolated microglial, astrocytes and neurons by laser capture microdissection from CA1 of hippocampus in the same individuals with a clinical and pathological diagnosis of AD and matched control cases. Using this unique RNAseq data set, we show that in the hippocampus, ANK1 is significantly (p<0.0001) up-regulated 4-fold in AD microglia, but not in neurons or astrocytes from the same individuals. These data provide evidence that microglia are the source of ANK1 differential expression previously identified in homogenate samples in AD.
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Affiliation(s)
- Diego Mastroeni
- Biodesign, ASU-Banner Biodesign Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
- Banner Sun Health Research Institute, 10515 West Santa Fe Drive, Sun City, AZ, United States of America
- * E-mail:
| | - Shobana Sekar
- Translational Genomics Institute, 445 North Fifth Street, Phoenix, AZ, United States of America
| | - Jennifer Nolz
- Biodesign, ASU-Banner Biodesign Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
| | - Elaine Delvaux
- Biodesign, ASU-Banner Biodesign Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
| | - Katie Lunnon
- University of Exeter Medical School, RILD, University of Exeter, Devon, United Kingdom
| | - Jonathan Mill
- University of Exeter Medical School, RILD, University of Exeter, Devon, United Kingdom
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, United Kingdom
| | - Winnie S. Liang
- Translational Genomics Institute, 445 North Fifth Street, Phoenix, AZ, United States of America
| | - Paul D. Coleman
- Biodesign, ASU-Banner Biodesign Neurodegenerative Disease Research Center, and School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
- Banner Sun Health Research Institute, 10515 West Santa Fe Drive, Sun City, AZ, United States of America
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41
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Kasuga Y, Hata K, Tajima A, Ochiai D, Saisho Y, Matsumoto T, Arata N, Miyakoshi K, Tanaka M. Association of common polymorphisms with gestational diabetes mellitus in Japanese women: A case-control study. Endocr J 2017; 64:463-475. [PMID: 28202837 DOI: 10.1507/endocrj.ej16-0431] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Gestational diabetes (GDM) and type 2 diabetes (T2DM) share part of pathomechanism and several T2DM susceptibility genes are demonstrated to be associated with GDM. No information on the genetics of GDM, however, was available in Japanese women. In this study, T2DM risk variants (45 single nucleotide polymorphisms [SNPs] from 36 genes) identified in previous studies were genotyped using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in a cohort of 171 Japanese women with GDM and 128 normal glucose tolerance (NGT) diagnosed by the new International Association of Diabetes in Pregnancy Study Group criteria. Of 45 SNPs, three genetic variants were nominally associated with the development of GDM: rs266729 (p = 0.013, odds ratio [OR]: 1.56, 95% confidence interval [CI]: 1.10-2.23) in ADIPOQ, rs10811661 (p = 0.035, OR: 1.46, 95% CI: 1.03-2.08) in CDKN2A/2B, and rs9505118 (p = 0.046, OR: 1.41, 95% CI: 1.01-1.97) in SSR1-RREB1. There was a significant difference in the number of risk alleles of three variants between women with GDM and NGT (3.79 ± 1.33 vs. 3.05 ± 1.41, p = 6.0 × 10-6). In combined analysis of three genetic variants, women with five or more risk alleles had a 7.32-fold increased risk of GDM (p = 5.6 × 10-5, 95% CI: 4.54-11.96), compared with those having no more than one risk allele. Our results suggest several risk variants of T2DM had cumulative effects on the development of GDM in Japanese women.
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Affiliation(s)
- Yoshifumi Kasuga
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo 157-8583, Japan
| | - Kenichiro Hata
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo 157-8583, Japan
| | - Atsushi Tajima
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa 920-8640, Japan
| | - Daigo Ochiai
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Yoshifumi Saisho
- Department of Internal Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Tadashi Matsumoto
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Naoko Arata
- Department of Women's Health, National Center for Child Health and Development, Tokyo 157-8583, Japan
| | - Kei Miyakoshi
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Mamoru Tanaka
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160-8582, Japan
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42
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Shimizu K, Okamoto M, Terada T, Sakurai F, Mizuguchi H, Tomita K, Nishinaka T. Adenovirus vector-mediated macrophage erythroblast attacher (MAEA) overexpression in primary mouse hepatocytes attenuates hepatic gluconeogenesis. Biochem Biophys Rep 2017; 10:192-197. [PMID: 28955747 PMCID: PMC5614675 DOI: 10.1016/j.bbrep.2017.04.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Revised: 12/27/2016] [Accepted: 04/18/2017] [Indexed: 11/30/2022] Open
Abstract
Japanese patients with type 2 diabetes mellitus present a different responsiveness in terms of insulin secretion to glucose and body mass index (BMI) from other populations. The genetic background that predisposes Japanese individuals to type 2 diabetes mellitus is under study. Recent genetic studies demonstrated that the locus mapped in macrophage erythroblast attacher (MAEA) increases the susceptibility to type 2 diabetes mellitus in East Asians, including Japanese individuals. MAEA encodes a protein that plays a role in erythroblast enucleation and in the normal differentiation of erythroid cells and macrophages. However, the contribution of MAEA to type 2 diabetes mellitus remains unknown. In this study, to overexpress MAEA in the mouse liver and primary mouse hepatocytes, we generated a MAEA-expressing adenovirus (Ad) vector using a novel Ad vector exhibiting significantly lower hepatotoxicity (Ad-MAEA). Blood glucose and insulin levels in Ad-MAEA-treated mice were comparable to those in control Ad-treated mice. Primary mouse hepatocytes transduced with Ad-MAEA showed lower levels of expression of gluconeogenesis genes than those transduced with the control Ad vector. Hepatocyte nuclear factor-4α (HNF-4α) mRNA expression in primary mouse hepatocytes was also suppressed by MAEA overexpression. These results suggest that MAEA overexpression attenuates hepatic gluconeogenesis, which could potentially lead to improvement of type 2 diabetes mellitus.
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Affiliation(s)
- Kahori Shimizu
- Laboratory of Biochemistry, Faculty of Pharmacy, Osaka Ohtani University, Osaka 584-8540, Japan
| | - Minako Okamoto
- Laboratory of Biochemistry, Faculty of Pharmacy, Osaka Ohtani University, Osaka 584-8540, Japan
| | - Tomoyuki Terada
- Laboratory of Biochemistry, Faculty of Pharmacy, Osaka Ohtani University, Osaka 584-8540, Japan
| | - Fuminori Sakurai
- Laboratory of Biochemistry and Molecular Biology, Graduate School of Pharmaceutical Sciences, Osaka University, Osaka 565-0871, Japan.,Laboratory of Regulatory Sciences for Oligonucleotide Therapeutics, Clinical Drug Development Unit, Graduate School of Pharmaceutical Sciences, Osaka University, Osaka 565-0871, Japan
| | - Hiroyuki Mizuguchi
- Laboratory of Biochemistry and Molecular Biology, Graduate School of Pharmaceutical Sciences, Osaka University, Osaka 565-0871, Japan.,Global Center for Medical Engineering and Informatics, Osaka University, Osaka 565-0871, Japan.,Laboratory of Hepatocyte Differentiation, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka 567-0085, Japan.,iPS Cell-Based Research Project on Hepatic Toxicity and Metabolism, Graduate School of Pharmaceutical Sciences, Osaka University, Osaka 565-0871, Japan
| | - Koji Tomita
- Laboratory of Molecular Biology, Faculty of Pharmacy, Osaka Ohtani University, Osaka 584-8540, Japan
| | - Toru Nishinaka
- Laboratory of Biochemistry, Faculty of Pharmacy, Osaka Ohtani University, Osaka 584-8540, Japan
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43
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Chen G, Zhang Z, Adebamowo SN, Liu G, Adeyemo A, Zhou Y, Doumatey AP, Wang C, Zhou J, Yan W, Shriner D, Tekola-Ayele F, Bentley AR, Jiang C, Rotimi CN. Common and rare exonic MUC5B variants associated with type 2 diabetes in Han Chinese. PLoS One 2017; 12:e0173784. [PMID: 28346466 PMCID: PMC5367689 DOI: 10.1371/journal.pone.0173784] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 02/27/2017] [Indexed: 12/17/2022] Open
Abstract
Genome-wide association studies have identified over one hundred common genetic risk variants associated with type 2 diabetes (T2D). However, most of the heritability of T2D has not been accounted for. In this study, we investigated the contribution of rare and common variants to T2D susceptibility by analyzing exome array data in 1,908 Han Chinese genotyped with Affymetrix Axiom® Exome Genotyping Arrays. Based on the joint common and rare variants analysis of 57,704 autosomal SNPs within 12,244 genes using Sequence Kernel Association Tests (SKAT), we identified significant associations between T2D and 25 variants (9 rare and 16 common) in MUC5B, p-value 1.01×10−14. This finding was replicated (p = 0.0463) in an independent sample that included 10,401 unrelated individuals. Sixty-six of 1,553 possible haplotypes based on 25 SNPs within MUC5B showed significant association with T2D (Bonferroni corrected p values < 3.2×10−5). The expression level of MUC5B is significantly higher in pancreatic tissues of persons with T2D compared to those without T2D (p-value = 5×10−5). Our findings suggest that dysregulated MUC5B expression may be involved in the pathogenesis of T2D. As a strong candidate gene for T2D, MUC5B may play an important role in the mechanisms underlying T2D etiology and its complications.
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Affiliation(s)
- Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CNR); (GC)
| | | | - Sally N. Adebamowo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Yanxun Zhou
- Suizhou Central Hospital, Suizhou, Hubei, China
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CNR); (GC)
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44
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Two-stage association study to identify the genetic susceptibility of a novel common variant of rs2075290 in ZPR1 to type 2 diabetes. Sci Rep 2016; 6:29586. [PMID: 27411854 PMCID: PMC4944165 DOI: 10.1038/srep29586] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Accepted: 06/22/2016] [Indexed: 12/30/2022] Open
Abstract
The SNP of rs964184 in ZPR1 has recently been associated with type 2 diabetes mellitus (T2DM) in Japanese individuals. To comprehensively investigate the association of common variants in ZPR1 with T2DM in Han Chinese individuals, we designed a two-stage case-control study of 3,505 T2DM patients and 6,911 unrelated healthy Han Chinese individuals. A total of 24 single nucleotide polymorphisms (SNPs) were genotyped, and single-SNP association, imputation and gender-specific association analyses were performed. To increase the coverage of genetic markers, we implemented imputation techniques to extend the number of tested makers to 280. A novel SNP, rs2075290, and the previously reported SNP, rs964184, were significantly associated with T2DM in the two independent datasets, and individuals harboring the CC genotype of rs2075290 and GG genotype of rs964184 exhibited higher levels of fasting plasma glucose (FPG) and blood hemoglobin A1c (HbA1c) than individuals of other genotypes. Additionally, haplotype analyses indicated that two haplotype blocks containing rs2075290 or rs964184 were also significantly associated with T2DM. In summary, these results suggest that ZPR1 plays an important role in the etiology of T2DM, and this gene might be involved in abnormal glucose metabolism.
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45
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Gan W, Walters RG, Holmes MV, Bragg F, Millwood IY, Banasik K, Chen Y, Du H, Iona A, Mahajan A, Yang L, Bian Z, Guo Y, Clarke RJ, Li L, McCarthy MI, Chen Z. Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank. Diabetologia 2016; 59:1446-1457. [PMID: 27053236 PMCID: PMC4901105 DOI: 10.1007/s00125-016-3920-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2015] [Accepted: 02/22/2016] [Indexed: 01/19/2023]
Abstract
AIMS/HYPOTHESIS Genome-wide association studies (GWAS) have discovered many risk variants for type 2 diabetes. However, estimates of the contributions of risk variants to type 2 diabetes predisposition are often based on highly selected case-control samples, and reliable estimates of population-level effect sizes are missing, especially in non-European populations. METHODS The individual and cumulative effects of 59 established type 2 diabetes risk loci were measured in a population-based China Kadoorie Biobank (CKB) study of 93,000 Chinese adults, including >7,100 diabetes cases. RESULTS Association signals were directionally consistent between CKB and the original discovery GWAS: of 56 variants passing quality control, 48 showed the same direction of effect (binomial test, p = 2.3 × 10(-8)). We observed a consistent overall trend towards lower risk variant effect sizes in CKB than in case-control samples of GWAS meta-analyses (mean 19-22% decrease in log odds, p ≤ 0.0048), likely to reflect correction of both 'winner's curse' and spectrum bias effects. The association with risk of diabetes of a genetic risk score, based on lead variants at 25 loci considered to act through beta cell function, demonstrated significant interactions with several measures of adiposity (BMI, waist circumference [WC], WHR and percentage body fat [PBF]; all p interaction < 1 × 10(-4)), with a greater effect being observed in leaner adults. CONCLUSIONS/INTERPRETATION Our study provides further evidence of shared genetic architecture for type 2 diabetes between Europeans and East Asians. It also indicates that even very large GWAS meta-analyses may be vulnerable to substantial inflation of effect size estimates, compared with those observed in large-scale population-based cohort studies. ACCESS TO RESEARCH MATERIALS Details of how to access China Kadoorie Biobank data and details of the data release schedule are available from www.ckbiobank.org/site/Data+Access .
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Affiliation(s)
- Wei Gan
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital Campus, Old Road, Headington, Oxford, OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Michael V Holmes
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Fiona Bragg
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Karina Banasik
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital Campus, Old Road, Headington, Oxford, OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Copenhagen, Denmark
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Andri Iona
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Anubha Mahajan
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital Campus, Old Road, Headington, Oxford, OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Zheng Bian
- Chinese Academy of Medical Sciences, Dong Cheng District, Beijing, People's Republic of China
| | - Yu Guo
- Chinese Academy of Medical Sciences, Dong Cheng District, Beijing, People's Republic of China
| | - Robert J Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Liming Li
- Chinese Academy of Medical Sciences, Dong Cheng District, Beijing, People's Republic of China
- School of Public Health, Peking University Health Sciences Center, Beijing, People's Republic of China
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital Campus, Old Road, Headington, Oxford, OX3 7LJ, UK.
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
- National Institute of Health Research Oxford Biomedical Research Centre, Oxford, UK.
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK.
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46
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The genetic regulatory signature of type 2 diabetes in human skeletal muscle. Nat Commun 2016; 7:11764. [PMID: 27353450 PMCID: PMC4931250 DOI: 10.1038/ncomms11764] [Citation(s) in RCA: 96] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 04/27/2016] [Indexed: 12/11/2022] Open
Abstract
Type 2 diabetes (T2D) results from the combined effects of genetic and environmental factors on multiple tissues over time. Of the >100 variants associated with T2D and related traits in genome-wide association studies (GWAS), >90% occur in non-coding regions, suggesting a strong regulatory component to T2D risk. Here to understand how T2D status, metabolic traits and genetic variation influence gene expression, we analyse skeletal muscle biopsies from 271 well-phenotyped Finnish participants with glucose tolerance ranging from normal to newly diagnosed T2D. We perform high-depth strand-specific mRNA-sequencing and dense genotyping. Computational integration of these data with epigenome data, including ATAC-seq on skeletal muscle, and transcriptome data across diverse tissues reveals that the tissue-specific genetic regulatory architecture of skeletal muscle is highly enriched in muscle stretch/super enhancers, including some that overlap T2D GWAS variants. In one such example, T2D risk alleles residing in a muscle stretch/super enhancer are linked to increased expression and alternative splicing of muscle-specific isoforms of ANK1.
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Yan R, Lai S, Yang Y, Shi H, Cai Z, Sorrentino V, Du H, Chen H. A novel type 2 diabetes risk allele increases the promoter activity of the muscle-specific small ankyrin 1 gene. Sci Rep 2016; 6:25105. [PMID: 27121283 PMCID: PMC4848520 DOI: 10.1038/srep25105] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 04/08/2016] [Indexed: 11/09/2022] Open
Abstract
Genome-wide association studies have identified Ankyrin-1 (ANK1) as a common type 2 diabetes (T2D) susceptibility locus. However, the underlying causal variants and functional mechanisms remain unknown. We screened for 8 tag single nucleotide polymorphisms (SNPs) in ANK1 between 2 case-control studies. Genotype analysis revealed significant associations of 3 SNPs, rs508419 (first identified here), rs515071, and rs516946 with T2D (P < 0.001). These SNPs were in linkage disequilibrium (r2 > 0.80); subsequent analysis indicated that the CCC haplotype associated with increased T2D susceptibility (OR 1.447, P < 0.001). Further mapping showed that rs508419 resides in the muscle-specific ANK1 gene promoter. Allele-specific mRNA and protein level measurements confirmed association of the C allele with increased small ANK1 (sAnk1) expression in human skeletal muscle (P = 0.018 and P < 0.001, respectively). Luciferase assays showed increased rs508419-C allele transcriptional activity in murine skeletal muscle C2C12 myoblasts, and electrophoretic mobility-shift assays demonstrated altered rs508419 DNA-protein complex formation. Glucose uptake was decreased with excess sAnk1 expression upon insulin stimulation. Thus, the ANK1 rs508419-C T2D-risk allele alters DNA-protein complex binding leading to increased promoter activity and sAnk1 expression; thus, increased sAnk1 expression in skeletal muscle might contribute to T2D susceptibility.
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Affiliation(s)
- Rengna Yan
- School of Medicine, Nanjing University, Nanjing, 210093, China.,Department of Endocrinology, Jinling Hospital Affiliated to Nanjing University School of Medicine, Nanjing, 210002, China.,Department of Endocrinology, Nanjing First Hospital Affiliated to Nanjing Medical University, Nanjing, 210006, China
| | - Shanshan Lai
- School of Medicine, Nanjing University, Nanjing, 210093, China.,MOE Key Laboratory of Model Animals for Disease Study, Model Animal Research Center and the School of Medicine, Nanjing University, National Resource Center for Mutant Mice, Nanjing 210093, China.,Jiangsu Key Laboratory of Molecular Medicine, Nanjing, 210002, China
| | - Yang Yang
- School of Medicine, Nanjing University, Nanjing, 210093, China.,Jiangsu Key Laboratory of Molecular Medicine, Nanjing, 210002, China.,Department of Urology, Drum Tower Hospital Affiliated to Nanjing University School of Medicine, Nanjing, 210008, China
| | - Hongfei Shi
- School of Medicine, Nanjing University, Nanjing, 210093, China.,Jiangsu Key Laboratory of Molecular Medicine, Nanjing, 210002, China.,Department of Orthopedics, Drum Tower Hospital Affiliated to Nanjing University School of Medicine, Nanjing, 210008, China
| | - Zhenming Cai
- School of Medicine, Nanjing University, Nanjing, 210093, China.,Jiangsu Key Laboratory of Molecular Medicine, Nanjing, 210002, China
| | - Vincenzo Sorrentino
- Molecular Medicine Section, Department of Molecular and Developmental Medicine, University of Siena, Siena, 53100, Italy
| | - Hong Du
- School of Medicine, Nanjing University, Nanjing, 210093, China.,Department of Endocrinology, Jinling Hospital Affiliated to Nanjing University School of Medicine, Nanjing, 210002, China
| | - Huimei Chen
- School of Medicine, Nanjing University, Nanjing, 210093, China.,Jiangsu Key Laboratory of Molecular Medicine, Nanjing, 210002, China
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48
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Replication Study in a Japanese Population of Six Susceptibility Loci for Type 2 Diabetes Originally Identified by a Transethnic Meta-Analysis of Genome-Wide Association Studies. PLoS One 2016; 11:e0154093. [PMID: 27115357 PMCID: PMC4845992 DOI: 10.1371/journal.pone.0154093] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Accepted: 04/08/2016] [Indexed: 01/21/2023] Open
Abstract
AIM We performed a replication study in a Japanese population to evaluate the association between type 2 diabetes and six susceptibility loci (TMEM154, SSR1, FAF1, POU5F1, ARL15, and MPHOSPH9) originally identified by a transethnic meta-analysis of genome-wide association studies (GWAS) in 2014. METHODS We genotyped 7,620 Japanese participants (5,817 type 2 diabetes patients and 1,803 controls) for each of the single nucleotide polymorphisms (SNPs) using a multiplex polymerase chain reaction invader assay. The association of each SNP locus with the disease was evaluated using logistic regression analysis. RESULTS Of the six SNPs examined in this study, four (rs6813195 near TMEM154, rs17106184 in FAF1, rs3130501 in POU5F1 and rs4275659 near MPHOSPH9) had the same direction of effect as in the original reports, but two (rs9505118 in SSR1 and rs702634 in ARL15) had the opposite direction of effect. Among these loci, rs3130501 and rs4275659 were nominally associated with type 2 diabetes (rs3130501; p = 0.017, odds ratio [OR] = 1.113, 95% confidence interval [CI] 1.019-1.215, rs4275659; p = 0.012, OR = 1.127, 95% CI 1.026-1.238, adjusted for sex, age and body mass index), but we did not observe a significant association with type 2 diabetes for any of the six evaluated SNP loci in our Japanese population. CONCLUSIONS Our results indicate that effects of the six SNP loci identified in the transethnic GWAS meta-analysis are not major among the Japanese, although SNPs in POU5F1 and MPHOSPH9 loci may have some effect on susceptibility to type 2 diabetes in this population.
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49
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Imamura M, Takahashi A, Yamauchi T, Hara K, Yasuda K, Grarup N, Zhao W, Wang X, Huerta-Chagoya A, Hu C, Moon S, Long J, Kwak SH, Rasheed A, Saxena R, Ma RCW, Okada Y, Iwata M, Hosoe J, Shojima N, Iwasaki M, Fujita H, Suzuki K, Danesh J, Jørgensen T, Jørgensen ME, Witte DR, Brandslund I, Christensen C, Hansen T, Mercader JM, Flannick J, Moreno-Macías H, Burtt NP, Zhang R, Kim YJ, Zheng W, Singh JR, Tam CHT, Hirose H, Maegawa H, Ito C, Kaku K, Watada H, Tanaka Y, Tobe K, Kawamori R, Kubo M, Cho YS, Chan JCN, Sanghera D, Frossard P, Park KS, Shu XO, Kim BJ, Florez JC, Tusié-Luna T, Jia W, Tai ES, Pedersen O, Saleheen D, Maeda S, Kadowaki T. Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes. Nat Commun 2016; 7:10531. [PMID: 26818947 PMCID: PMC4738362 DOI: 10.1038/ncomms10531] [Citation(s) in RCA: 125] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 12/22/2015] [Indexed: 12/11/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P<5 × 10(-8)), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P<0.007). These results indicate that expansion of single ethnic GWAS is still useful to identify novel susceptibility loci to complex traits not only for ethnicity-specific loci but also for common loci across different ethnicities.
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Affiliation(s)
- Minako Imamura
- Laboratory for Endocrinology, Metabolism and Kidney Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Atsushi Takahashi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Laboratory for Omics Informatics, Omics Research Center, National Cerebral And Cardiovascular Center, Suita 565-8565, Japan
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
| | - Kazuo Hara
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan.,Department of Diabetes Endocrinology, Metabolism and Rheumatology, Tokyo Medical University, Tokyo 160-0023, Japan
| | - Kazuki Yasuda
- Department of Metabolic Disorder, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo 162-8655, Japan
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Wei Zhao
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021, USA
| | - Xu Wang
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 138672, Singapore
| | - Alicia Huerta-Chagoya
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City C.P.14000, Mexico
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Sanghoon Moon
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do 28159, Korea
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee 37203-1738, USA
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul 03080, Korea
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Richa Saxena
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Yukinori Okada
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Minoru Iwata
- First Department of Internal Medicine, University of Toyama, Toyama 930-0194, Japan.,Health Administration Center, University of Toyama, Toyama 930-0194, Japan
| | - Jun Hosoe
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
| | - Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
| | - Minaka Iwasaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
| | - Hayato Fujita
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
| | - Ken Suzuki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
| | - John Danesh
- Department of Public Health and Primary Care, University of Cambridge CB1 8RN, UK.,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1RQ, UK.,NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Torben Jørgensen
- Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup DK-2600, Denmark.,Faculty of Health and Medical Sciences, Department of Public Health, University of Copenhagen, Copenhagen 2200, Denmark.,Faculty of Medicine, University of Aalborg, Aalborg 9220, Denmark
| | | | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus 8000, Denmark.,Danish Diabetes Academy, Odense 5000, Denmark
| | - Ivan Brandslund
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle 7100, Denmark.,Institute of Regional Health Research, University of Southern Denmark, Odense 5230, Denmark
| | | | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Josep M Mercader
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.,Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona 08034, Spain.,Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Jason Flannick
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.,Department of Molecular Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | | | - Noël P Burtt
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Rong Zhang
- Department of Endocrinology and Metabolism, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Young Jin Kim
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do 28159, Korea
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee 37203-1738, USA
| | - Jai Rup Singh
- Central University of Punjab, Bathinda, Punjab 151001, India
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | | | - Hiroshi Maegawa
- Department of Medicine, Shiga University of Medical Science, Otsu 520-2192, Japan
| | - Chikako Ito
- Grand Tower Medical Court Life Care Clinic, Hiroshima 730-0012, Japan
| | - Kohei Kaku
- Department of Internal Medicine, Kawasaki Medical School, Kurashiki 701-0192, Japan
| | - Hirotaka Watada
- Department of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan.,Sportology Center, Juntendo University Graduate School of Medicine, Tokyo 113-0034, Japan
| | - Yasushi Tanaka
- Division of Metabolism and Endocrinology, Department of Internal Medicine, St Marianna University School of Medicine, Kawasaki 216-8511, Japan
| | - Kazuyuki Tobe
- First Department of Internal Medicine, University of Toyama, Toyama 930-0194, Japan
| | - Ryuzo Kawamori
- Sportology Center, Juntendo University Graduate School of Medicine, Tokyo 113-0034, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chunchon, Gangwon-do 24252, Republic of Korea
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Dharambir Sanghera
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma 73104, USA.,Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma 73104, n
| | | | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul 03080, Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul 03080, Korea.,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 03080, Korea
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee 37203-1738, USA
| | - Bong-Jo Kim
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do 28159, Korea
| | - Jose C Florez
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.,Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City C.P.14000, Mexico
| | - Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 138672, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.,Duke-National University of Singapore Graduate School, Singapore 169857, Singapore
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Danish Saleheen
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021, USA.,Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Shiro Maeda
- Laboratory for Endocrinology, Metabolism and Kidney Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara 903-0215, Japan.,Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara 903-0215, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan
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Wang X, Strizich G, Hu Y, Wang T, Kaplan RC, Qi Q. Genetic markers of type 2 diabetes: Progress in genome-wide association studies and clinical application for risk prediction. J Diabetes 2016; 8:24-35. [PMID: 26119161 DOI: 10.1111/1753-0407.12323] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Revised: 05/22/2015] [Accepted: 06/16/2015] [Indexed: 12/18/2022] Open
Abstract
Type 2 diabetes (T2D) has become a leading public health challenge worldwide. To date, a total of 83 susceptibility loci for T2D have been identified by genome-wide association studies (GWAS). Application of meta-analysis and modern genotype imputation approaches to GWAS data from diverse ethnic populations has been key in the effort to discover T2D loci. Genetic information is expected to play a vital role in the prediction of T2D, and many efforts have been made to develop T2D risk models that include both conventional and genetic risk factors. Yet, because most T2D genetic variants identified have small effect size individually (10%-20% increased risk of T2D per risk allele), their clinical utility remains unclear. Most studies report that a genetic risk score combining multiple T2D genetic variants does not substantially improve T2D risk prediction beyond conventional risk factors. In this article, we summarize the recent progress of T2D GWAS and further review the incremental predictive performance of genetic markers for T2D.
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Affiliation(s)
- Xueyin Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Garrett Strizich
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
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