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Zhu X, Ventura EF, Bansal S, Wijeyesekera A, Vimaleswaran KS. Integrating genetics, metabolites, and clinical characteristics in predicting cardiometabolic health outcomes using machine learning algorithms - A systematic review. Comput Biol Med 2025; 186:109661. [PMID: 39799831 DOI: 10.1016/j.compbiomed.2025.109661] [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: 04/14/2024] [Revised: 01/02/2025] [Accepted: 01/06/2025] [Indexed: 01/15/2025]
Abstract
BACKGROUND Machine learning (ML) integration of clinical, metabolite, and genetic data reveals variable results in predicting cardiometabolic health (CMH) outcomes. Therefore, we aim to (1) evaluate whether a multi-modal approach incorporating all three data types using ML algorithms can improve CMH outcome prediction compared to single-modal or paired-modal models, and (2) compare the methodologies used in existing prediction models. METHODS We systematically searched five databases from 1998 to 2024 for ML predictive modelling studies using the multi-modal approach for CMH outcomes. Risk-of-bias assessment tools were used to assess methodological quality. Study characteristics, ML algorithms, data preprocessing, evaluation methods and metrics, feature selections, and feature importance parameters were synthesized narratively to show methodological heterogeneity. RESULTS Of the four included studies (3 ML algorithms), three were at low risk of bias, and one was at high risk. The multi-modal approach consistently improved T2D and BP prediction compared to single-modal or paired-modal models. Genetics showed the lowest predictive performance in three studies. Logistic regression (n = 2 studies) and random forest (n = 1) were used in T2D studies, while XGBoost was used in one BP study. One study with missing data and variations in feature selection across all studies hindered a comprehensive comparison of feature importance. CONCLUSIONS Our review emphasizes the potential improvement in T2D and BP prediction using ML algorithms with the multi-modal approach. However, further studies using diverse ML algorithms with optimized methodologies on single-modal, paired-modal, and multi-modal models are needed to gain insights into biomarker selection for predicting CMH outcomes.
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Affiliation(s)
- Xianyu Zhu
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK
| | - Eduard F Ventura
- Institute of Agrochemistry and Food Technology-National Research Council (IATA-CSIC), Department of Biotechnology, Av. Agustin Escardino 7, 46980, Valencia, Spain
| | - Sakshi Bansal
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK
| | - Anisha Wijeyesekera
- Food Microbial Sciences Unit, Department of Food and Nutritional Sciences, School of Chemistry, Food and Pharmacy, University of Reading, Reading, RG6 6DZ, UK
| | - Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK; Institute for Food, Nutrition and Health (IFNH), University of Reading, Reading, RG6 6AH, UK.
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Benitez MBM, Navarro YP, Azuara-Liceaga E, Cruz AT, Flores JV, Lopez-Canovas L. Circular RNAs and the regulation of gene expression in diabetic nephropathy (Review). Int J Mol Med 2024; 53:44. [PMID: 38516776 PMCID: PMC10998718 DOI: 10.3892/ijmm.2024.5368] [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: 10/06/2023] [Accepted: 02/14/2024] [Indexed: 03/23/2024] Open
Abstract
Circular RNAs (circRNAs) are non‑coding single‑stranded covalently closed RNA molecules that are considered important as regulators of gene expression at the transcriptional and post‑transcriptional levels. These molecules have been implicated in the initiation and progression of multiple human diseases, ranging from cancer to inflammatory and metabolic diseases, including diabetes mellitus and its vascular complications. The present article aimed to review the current knowledge on the biogenesis and functions of circRNAs, as well as their role in cell processes associated with diabetic nephropathy. In addition, novel potential interactions between circRNAs expressed in renal cells exposed to high‑glucose concentrations and the transcription factors c‑Jun and c‑Fos are reported.
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Affiliation(s)
- Maximo Berto Martinez Benitez
- Postgraduate Program in Genomic Sciences, Science and Technology School, Autonomous University of Mexico City, Mexico City, CP 03100, Mexico
| | - Yussel Pérez Navarro
- Postgraduate Program in Genomic Sciences, Science and Technology School, Autonomous University of Mexico City, Mexico City, CP 03100, Mexico
| | - Elisa Azuara-Liceaga
- Postgraduate Program in Genomic Sciences, Science and Technology School, Autonomous University of Mexico City, Mexico City, CP 03100, Mexico
| | - Angeles Tecalco Cruz
- Postgraduate Program in Genomic Sciences, Science and Technology School, Autonomous University of Mexico City, Mexico City, CP 03100, Mexico
| | - Jesús Valdés Flores
- Biochemistry Department, Center for Research and Advanced Studies, National Polytechnic Institute of Mexico, Mexico City, CP 07360, Mexico
| | - Lilia Lopez-Canovas
- Postgraduate Program in Genomic Sciences, Science and Technology School, Autonomous University of Mexico City, Mexico City, CP 03100, Mexico
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Chaudhary N, Alawadhi F, Al-Serri A, Al-Temaimi R. TCF7L2 and FTO Polymorphisms Are Associated with Type 2 Diabetes Mellitus Risk in Kuwait. Med Princ Pract 2024; 33:157-163. [PMID: 38228106 PMCID: PMC11045214 DOI: 10.1159/000536229] [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: 09/14/2023] [Accepted: 01/10/2024] [Indexed: 01/18/2024] Open
Abstract
OBJECTIVE Despite the high prevalence of type 2 diabetes mellitus (T2DM) and obesity in the region, reports are limited on genetic risk factors associated with T2DM risk in Kuwait. Our aim was to investigate the association of reported FTO and TCF7L2 T2DM genetic risk variants in Kuwaiti T2DM patients. SUBJECTS AND METHODS FTO rs9939609 and TCF7L2 rs7903146 variants were genotyped in 203 T2DM patients and 162 healthy controls. Data analysis included Fisher's exact test, χ2 test, and linear and logistic regression analyses. RESULTS FTO rs9939609 (AA) and TCF7L2 rs7903146 (TT) genotypes associated with T2DM risk among Kuwaitis (p = 0.0016 and p < 0.0001; respectively). Both variants had the strongest association with T2DM risk in an autosomal recessive inheritance model (FTO rs9939609A: odds ratio (OR) 2.136, 95% confidence interval (CI): 1.21-3.67, p = 0.0075; TCF7L2 rs7903146T: OR 3.283, 95% CI: 1.92-5.76, p < 0.0001). Moreover, rs7903146T associated with risk of peripheral neuropathy (β = 0.735, 95% CI: 0.514-0.96, p < 0.001) and risk of myocardial infarction (β = 0.36, 95% CI: 0.024-0.7, p = 0.036) in T2DM patients. CONCLUSION The increased susceptibility of Kuwaitis to T2DM is influenced by the same common genetic factors found in other T2DM populations. Further investigations of other T2DM genetic risk factors in Kuwait should refine and further support the clinical utility of a genetic risk score in predicting T2DM risk in a high-risk population such as Kuwait.
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Affiliation(s)
- Nawal Chaudhary
- Undergraduate Medical Program, Department of Pathology, College of Medicine, Kuwait University, Jabriya, Kuwait
| | - Faye Alawadhi
- Undergraduate Medical Program, Department of Pathology, College of Medicine, Kuwait University, Jabriya, Kuwait
| | - Ahmad Al-Serri
- Human Genetics Unit, Department of Pathology, College of Medicine, Kuwait University, Jabriya, Kuwait
| | - Rabeah Al-Temaimi
- Human Genetics Unit, Department of Pathology, College of Medicine, Kuwait University, Jabriya, Kuwait
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Vejrazkova D, Vankova M, Lukasova P, Hill M, Vcelak J, Tura A, Chocholova D, Bendlova B. The Glycemic Curve during the Oral Glucose Tolerance Test: Is It Only Indicative of Glycoregulation? Biomedicines 2023; 11:biomedicines11051278. [PMID: 37238949 DOI: 10.3390/biomedicines11051278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/17/2023] [Accepted: 04/22/2023] [Indexed: 05/28/2023] Open
Abstract
The shape of the glycemic curve during the oral glucose tolerance test (OGTT), interpreted in the correct context, can predict impaired glucose homeostasis. Our aim was to reveal information inherent in the 3 h glycemic trajectory that is of physiological relevance concerning the disruption of glycoregulation and complications beyond, such as components of metabolic syndrome (MS). METHODS In 1262 subjects (1035 women, 227 men) with a wide range of glucose tolerance, glycemic curves were categorized into four groups: monophasic, biphasic, triphasic, and multiphasic. The groups were then monitored in terms of anthropometry, biochemistry, and timing of the glycemic peak. RESULTS Most curves were monophasic (50%), then triphasic (28%), biphasic (17.5%), and multiphasic (4.5%). Men had more biphasic curves than women (33 vs. 14%, respectively), while women had more triphasic curves than men (30 vs. 19%, respectively) (p < 0.01). Monophasic curves were more frequent in people with impaired glucose regulation and MS compared to bi-, tri-, and multiphasic ones. Peak delay was the most common in monophasic curves, in which it was also most strongly associated with the deterioration of glucose tolerance and other components of MS. CONCLUSION The shape of the glycemic curve is gender dependent. A monophasic curve is associated with an unfavorable metabolic profile, especially when combined with a delayed peak.
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Affiliation(s)
| | | | - Petra Lukasova
- Institute of Endocrinology, 110 00 Prague, Czech Republic
| | - Martin Hill
- Institute of Endocrinology, 110 00 Prague, Czech Republic
| | - Josef Vcelak
- Institute of Endocrinology, 110 00 Prague, Czech Republic
| | - Andrea Tura
- Institute of Neuroscience, National Research Council (CNR), 351 22 Padova, Italy
| | - Denisa Chocholova
- Faculty of Science, Charles University, 128 00 Prague, Czech Republic
| | - Bela Bendlova
- Institute of Endocrinology, 110 00 Prague, Czech Republic
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Early Prediction for Prediabetes and Type 2 Diabetes Using the Genetic Risk Score and Oxidative Stress Score. Antioxidants (Basel) 2022; 11:antiox11061196. [PMID: 35740093 PMCID: PMC9231325 DOI: 10.3390/antiox11061196] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/14/2022] [Accepted: 06/15/2022] [Indexed: 11/17/2022] Open
Abstract
We aimed to use a genetic risk score (GRS) constructed with prediabetes and type 2 diabetes-related single nucleotide polymorphisms (SNPs) and an oxidative stress score (OSS) to construct an early-prediction model for prediabetes and type 2 diabetes (T2DM) incidence in a Korean population. The study population included 549 prediabetes and T2DM patients and 1036 normal subjects. The GRS was constructed using six prediabetes and T2DM-related SNPs, and the OSS was composed of three recognized oxidative stress biomarkers. Among the nine SNPs, six showed significant associations with the incidence of prediabetes and T2DM. The GRS was profoundly associated with increased prediabetes and T2DM (OR = 1.946) compared with individual SNPs after adjusting for age, sex, and BMI. Each of the three oxidative stress biomarkers was markedly higher in the prediabetes and T2DM group than in the normal group, and the OSS was significantly associated with increased prediabetes and T2DM (OR = 2.270). When BMI was introduced to the model with the OSS and GRS, the area under the ROC curve improved (from 69.3% to 70.5%). We found that the prediction model composed of the OSS, GRS, and BMI showed a significant prediction ability for the incidence of prediabetes and T2DM.
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Smith CJ, McNaughton DA, Meyer SB. Implications for clients when nurses view weight as main cause of Type 2 diabetes in primary care. Aust J Prim Health 2021; 27:404-408. [PMID: 34229828 DOI: 10.1071/py20245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 04/28/2021] [Indexed: 11/23/2022]
Abstract
Type 2 diabetes (T2D) is often seen as primarily caused by weight, and its amelioration associated with individual behaviour change, which has the potential for negative consequences for people living with the disease. The aims of this study were to explore how weight was framed by diabetes resource nurses and to determine the implications of that framing for nurse practice in a primary care setting in Australia. The research was a qualitative empirical case study using semistructured interviews with nurses focusing on meanings and interpretations. The findings were interpreted using a constructivist epistemology of both inductive and deductive inference. The study found that nurses viewed overweight and obesity as unhealthy and the primary causes of T2D, and that weight was frequently discussed in the health care encounter. Nurses emphasised individual responsibility through behaviour change to manage T2D, downplaying other known causes such as age and family history and important social inequalities. Studies show that nurses have negative attitudes towards overweight and obese patients. The implications of this research are that the nurses' views could potentially negatively affect clients' management of T2D, which has the potential for poor health outcomes.
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Affiliation(s)
- Cynthia J Smith
- School of Health and Human Services, Camosun College, 4461 Interurban Road, Victoria, BC V9E2C1, Canada; and Corresponding author.
| | - Darlene A McNaughton
- Anthropology - Faculty of Humanities, Arts, Social Sciences and Education, School of Humanities, Arts, and Social Sciences, University of New England, Madgwick Drive, Armidale, NSW 2351, Australia
| | - Samantha B Meyer
- University of Waterloo, 200 University Avenue, Waterloo, ON N2L3G1, Canada
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7
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Cho SB, Jang JH, Chung MG, Kim SC. Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus. Diabetes Metab J 2021; 45:231-240. [PMID: 32794382 PMCID: PMC8024163 DOI: 10.4093/dmj.2019.0163] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 02/10/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Most loci associated with type 2 diabetes mellitus (T2DM) discovered to date are within noncoding regions of unknown functional significance. By contrast, exonic regions have advantages for biological interpretation. METHODS We analyzed the association of exome array data from 14,026 Koreans to identify susceptible exonic loci for T2DM. We used genotype information of 50,543 variants using the Illumina exome array platform. RESULTS In total, 7 loci were significant with a Bonferroni adjusted P=1.03×10-6. rs2233580 in paired box gene 4 (PAX4) showed the highest odds ratio of 1.48 (P=1.60×10-10). rs11960799 in membrane associated ring-CH-type finger 3 (MARCH3) and rs75680863 in transcobalamin 2 (TCN2) were newly identified loci. When we built a model to predict the incidence of diabetes with the 7 loci and clinical variables, area under the curve (AUC) of the model improved significantly (AUC=0.72, P<0.05), but marginally in its magnitude, compared with the model using clinical variables (AUC=0.71, P<0.05). When we divided the entire population into three groups-normal body mass index (BMI; <25 kg/m2), overweight (25≤ BMI <30 kg/m2), and obese (BMI ≥30 kg/m2) individuals-the predictive performance of the 7 loci was greatest in the group of obese individuals, where the net reclassification improvement was highly significant (0.51; P=8.00×10-5). CONCLUSION We found exonic loci having a susceptibility for T2DM. We found that such genetic information is advantageous for predicting T2DM in a subgroup of obese individuals.
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Affiliation(s)
- Seong Beom Cho
- Division of Biomedical Informatics, Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Cheongju, Korea
| | - Jin Hwa Jang
- Division of Biomedical Informatics, Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Cheongju, Korea
| | - Myung Guen Chung
- Division of Biomedical Informatics, Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Cheongju, Korea
| | - Sang Cheol Kim
- Division of Biomedical Informatics, Center for Genome Science, National Institute of Health, Korea Center for Disease Control and Prevention, Cheongju, Korea
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Sayed S, Nabi AHMN. Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1307:457-498. [PMID: 32314317 DOI: 10.1007/5584_2020_518] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.
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Affiliation(s)
- Shomoita Sayed
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh.
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Boecker M, Lai AG. Could personalised risk prediction for type 2 diabetes using polygenic risk scores direct prevention, enhance diagnostics, or improve treatment? Wellcome Open Res 2020. [DOI: 10.12688/wellcomeopenres.16251.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Over the past three decades, the number of people globally with diabetes mellitus has more than doubled. It is estimated that by 2030, 439 million people will be suffering from the disease, 90-95% of whom will have type 2 diabetes (T2D). In 2017, 5 million deaths globally were attributable to T2D, placing it in the top 10 global causes of death. Because T2D is a result of both genetic and environmental factors, identification of individuals with high genetic risk can help direct early interventions to prevent progression to more serious complications. Genome-wide association studies have identified ~400 variants associated with T2D that can be used to calculate polygenic risk scores (PRS). Although PRSs are not currently more accurate than clinical predictors and do not yet predict risk with equal accuracy across all ethnic populations, they have several potential clinical uses. Here, we discuss potential usages of PRS for predicting T2D and for informing and optimising interventions. We also touch on possible health inequality risks of PRS and the feasibility of large-scale implementation of PRS in clinical practice. Before PRSs can be used as a therapeutic tool, it is important that further polygenic risk models are derived using non-European genome-wide association studies to ensure that risk prediction is accurate for all ethnic groups. Furthermore, it is essential that the ethical, social and legal implications of PRS are considered before their implementation in any context.
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Ingelsson E, McCarthy MI. Human Genetics of Obesity and Type 2 Diabetes Mellitus: Past, Present, and Future. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2019; 11:e002090. [PMID: 29899044 DOI: 10.1161/circgen.118.002090] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.
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Affiliation(s)
- Erik Ingelsson
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (E.I.) .,Stanford Cardiovascular Institute, Stanford University, CA (E.I.)
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics (M.I.M.).,Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, United Kingdom (M.I.M.).,Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, United Kingdom (M.I.M.)
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Nasykhova YA, Barbitoff YA, Serebryakova EA, Katserov DS, Glotov AS. Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes. World J Diabetes 2019; 10:376-395. [PMID: 31363385 PMCID: PMC6656706 DOI: 10.4239/wjd.v10.i7.376] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 05/23/2019] [Accepted: 06/11/2019] [Indexed: 02/05/2023] Open
Abstract
Type 2 diabetes (T2D) mellitus is a common complex disease that currently affects more than 400 million people worldwide and has become a global health problem. High-throughput sequencing technologies such as whole-genome and whole-exome sequencing approaches have provided numerous new insights into the molecular bases of T2D. Recent advances in the application of sequencing technologies to T2D research include, but are not limited to: (1) Fine mapping of causal rare and common genetic variants; (2) Identification of confident gene-level associations; (3) Identification of novel candidate genes by specific scoring approaches; (4) Interrogation of disease-relevant genes and pathways by transcriptional profiling and epigenome mapping techniques; and (5) Investigation of microbial community alterations in patients with T2D. In this work we review these advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis, as well as progress and challenges in implementation of this new knowledge about T2D genetics in diagnosis, prevention, and treatment of the disease.
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Affiliation(s)
- Yulia A Nasykhova
- Laboratory of Biobanking and Genomic Medicine of Institute of Translation Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia
- Department of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology and Reproductology, St. Petersburg 199034, Russia
| | - Yury A Barbitoff
- Laboratory of Biobanking and Genomic Medicine of Institute of Translation Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia
- Bioinformatics Institute, St. Petersburg 194021, Russia
- Department of Genetics and Biotechnology, St. Petersburg State University, St. Petersburg 199034, Russia
| | - Elena A Serebryakova
- Department of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology and Reproductology, St. Petersburg 199034, Russia
- Department of Genetics, City Hospital No. 40, St. Petersburg 197706, Russia
| | - Dmitry S Katserov
- Institute of Living Systems, Immanuel Kant Baltic Federal University, Kaliningrad 236016, Russia
| | - Andrey S Glotov
- Laboratory of Biobanking and Genomic Medicine of Institute of Translation Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia
- Department of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology and Reproductology, St. Petersburg 199034, Russia
- Department of Genetics, City Hospital No. 40, St. Petersburg 197706, Russia
- Institute of Living Systems, Immanuel Kant Baltic Federal University, Kaliningrad 236016, Russia
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12
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Bell HS, Odumosu F, Martinez-Hume AC, Howard HA, Hunt LM. Racialized Risk in Clinical Care: Clinician Vigilance and Patient Responsibility. Med Anthropol 2019; 38:224-238. [PMID: 29912575 PMCID: PMC6298860 DOI: 10.1080/01459740.2018.1476508] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Racial/ethnic identity is contingent and arbitrary, yet it is commonly used to evaluate disease risk and treatment response. Drawing on open-ended interviews with patients and clinicians in two US clinics, we explore how racialized risk is conceptualized and how it impacts patient care and experience. We found that racial/ethnic risk was a common but poorly defined construct for both patients and clinicians, who intermingled concepts of genetics, biology, behavior, and culture, while disregarding historical or structural context. We argue that racializing risk embodies social power in marked and unmarked bodies, reinforcing inequality along racial lines and undermining equitable health care.
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Affiliation(s)
- Hannah S Bell
- a Department of Anthropology , Michigan State University , East Lansing , Michigan , USA
| | - Funmi Odumosu
- a Department of Anthropology , Michigan State University , East Lansing , Michigan , USA
| | - Anna C Martinez-Hume
- a Department of Anthropology , Michigan State University , East Lansing , Michigan , USA
| | - Heather A Howard
- a Department of Anthropology , Michigan State University , East Lansing , Michigan , USA
| | - Linda M Hunt
- a Department of Anthropology , Michigan State University , East Lansing , Michigan , USA
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13
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Genetic risk score of common genetic variants for impaired fasting glucose and newly diagnosed type 2 diabetes influences oxidative stress. Sci Rep 2018; 8:7828. [PMID: 29777116 PMCID: PMC5959868 DOI: 10.1038/s41598-018-26106-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 05/02/2018] [Indexed: 12/11/2022] Open
Abstract
We tested the hypothesis that the cumulative effects of common genetic variants related to elevated fasting glucose are collectively associated with oxidative stress. Using 25 single nucleotide polymorphisms (SNPs), a weighted genetic risk score (wGRS) was constructed by summing nine risk alleles based on nominal significance and a consistent effect direction in 1,395 controls and 718 patients with impaired fasting glucose (IFG) or newly diagnosed type 2 diabetes. All the participants were divided into the following three groups: low-wGRS, middle-wGRS, and high-wGRS groups. Among the nine SNPs, five SNPs were significantly associated with IFG and type 2 diabetes in this Korean population. wGRS was significantly associated with increased IFG and newly diagnosed type 2 diabetes (p = 6.83 × 10−14, odds ratio = 1.839) after adjusting for confounding factors. Among the IFG and type 2 diabetes patients, the fasting serum glucose and HbA1c levels were significantly higher in the high-wGRS group than in the other groups. The urinary 8-epi-PGF2α and malondialdehyde concentrations were significantly higher in the high-wGRS group than in the other groups. Moreover, general population-level instrumental variable estimation (using wGRS as an instrument) strengthened the causal effect regarding the largely adverse influence of high levels of fasting serum glucose on markers of oxidative stress in the Korean population. Thus, the combination of common genetic variants with small effects on IFG and newly diagnosed type 2 diabetes are significantly associated with oxidative stress.
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Lei X, Huang S. Enrichment of minor allele of SNPs and genetic prediction of type 2 diabetes risk in British population. PLoS One 2017; 12:e0187644. [PMID: 29099854 PMCID: PMC5669465 DOI: 10.1371/journal.pone.0187644] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Accepted: 10/23/2017] [Indexed: 01/09/2023] Open
Abstract
Type 2 diabetes (T2D) is a complex disorder characterized by high blood sugar, insulin resistance, and relative lack of insulin. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in T2D using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 357 SNPs was found to have the best predictive accuracy in a British population. A weighted risk score calculated by using this set produced an area under the curve (AUC) score of 0.86, which is comparable to risk models built by phenotypic markers. These results identify a novel genetic risk element in T2D susceptibility and provide a potentially useful genetic method to identify individuals with high risk of T2D.
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Affiliation(s)
- Xiaoyun Lei
- Laboratory of Medical Genetics, School of Life Sciences, Xiangya Medical School, Central South University, Changsha, Hunan, China
| | - Shi Huang
- Laboratory of Medical Genetics, School of Life Sciences, Xiangya Medical School, Central South University, Changsha, Hunan, China
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15
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Pitkänen N, Juonala M, Rönnemaa T, Sabin MA, Hutri-Kähönen N, Kähönen M, Lehtimäki T, Viikari JSA, Raitakari OT. Role of Conventional Childhood Risk Factors Versus Genetic Risk in the Development of Type 2 Diabetes and Impaired Fasting Glucose in Adulthood: The Cardiovascular Risk in Young Finns Study. Diabetes Care 2016; 39:1393-9. [PMID: 27298332 DOI: 10.2337/dc16-0167] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Accepted: 05/06/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We examined whether the addition of novel genetic risk variant data to conventional childhood risk factors improves risk assessment of impaired fasting glucose (IFG) and type 2 diabetes in adulthood. RESEARCH DESIGN AND METHODS An association of a weighted genetic risk score (wGRS) based on 73 risk variants with IFG and type 2 diabetes was analyzed in 2,298 participants of the Cardiovascular Risk in Young Finns Study who were followed for 24-31 years from childhood to adulthood. In addition, the value of the wGRS in pediatric prediction of type 2 diabetes was examined. RESULTS Of the 2,298 participants, 484 (21.8%) and 79 (3.4%) had IFG or type 2 diabetes in adulthood, respectively. Adjusting for age, sex, baseline BMI, parental diabetes, mother's BMI, fasting insulin concentration, systolic blood pressure, and smoking status, wGRS was associated with an increased risk of IFG (odds ratio 1.64 [95% CI 1.33-2.01] per unit increase in the wGRS) and type 2 diabetes (2.22 [1.43-3.44]). Incorporating wGRS into pediatric risk models improved model discrimination and reclassification properties. Area under the receiver operating curve improved for IFG (from 0.678 to 0.691, P = 0.015), combined IFG and type 2 diabetes outcome (from 0.678 to 0.692, P = 0.007), and type 2 diabetes (from 0.728 to 0.749, P = 0.158). The net reclassification improvement and integrated discrimination improvement were significant for all outcomes. CONCLUSIONS A multifactorial approach combining genetic and clinical risk factors may be useful in identifying children at high risk for adult IFG and type 2 diabetes.
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Affiliation(s)
- Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Markus Juonala
- Division of Medicine, Turku University Hospital, Turku, Finland Department of Medicine, University of Turku, Turku, Finland
| | - Tapani Rönnemaa
- Division of Medicine, Turku University Hospital, Turku, Finland Department of Medicine, University of Turku, Turku, Finland
| | - Matthew A Sabin
- Murdoch Childrens Research Institute, Royal Children's Hospital, Australia, and Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Nina Hutri-Kähönen
- Department of Pediatrics, University of Tampere, and Tampere University Hospital, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere, and Tampere University Hospital, Tampere, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and School of Medicine, University of Tampere, Tampere, Finland
| | - Jorma S A Viikari
- Division of Medicine, Turku University Hospital, Turku, Finland Department of Medicine, University of Turku, Turku, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
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16
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Genetic-risk assessment of GWAS-derived susceptibility loci for type 2 diabetes in a 10 year follow-up of a population-based cohort study. J Hum Genet 2016; 61:1009-1012. [DOI: 10.1038/jhg.2016.93] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Revised: 06/02/2016] [Accepted: 06/09/2016] [Indexed: 12/22/2022]
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17
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Blood-based biomarkers of age-associated epigenetic changes in human islets associate with insulin secretion and diabetes. Nat Commun 2016; 7:11089. [PMID: 27029739 PMCID: PMC4821875 DOI: 10.1038/ncomms11089] [Citation(s) in RCA: 169] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Accepted: 02/19/2016] [Indexed: 12/18/2022] Open
Abstract
Aging associates with impaired pancreatic islet function and increased type 2 diabetes (T2D) risk. Here we examine whether age-related epigenetic changes affect human islet function and if blood-based epigenetic biomarkers reflect these changes and associate with future T2D. We analyse DNA methylation genome-wide in islets from 87 non-diabetic donors, aged 26-74 years. Aging associates with increased DNA methylation of 241 sites. These sites cover loci previously associated with T2D, for example, KLF14. Blood-based epigenetic biomarkers reflect age-related methylation changes in 83 genes identified in human islets (for example, KLF14, FHL2, ZNF518B and FAM123C) and some associate with insulin secretion and T2D. DNA methylation correlates with islet expression of multiple genes, including FHL2, ZNF518B, GNPNAT1 and HLTF. Silencing these genes in β-cells alter insulin secretion. Together, we demonstrate that blood-based epigenetic biomarkers reflect age-related DNA methylation changes in human islets, and associate with insulin secretion in vivo and T2D.
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18
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Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives. Hum Genet 2016; 135:259-72. [PMID: 26839113 PMCID: PMC4759222 DOI: 10.1007/s00439-016-1636-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Accepted: 01/15/2016] [Indexed: 02/07/2023]
Abstract
Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.
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19
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Park HY, Choi HJ, Hong YC. Utilizing Genetic Predisposition Score in Predicting Risk of Type 2 Diabetes Mellitus Incidence: A Community-based Cohort Study on Middle-aged Koreans. J Korean Med Sci 2015; 30:1101-9. [PMID: 26240488 PMCID: PMC4520941 DOI: 10.3346/jkms.2015.30.8.1101] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Accepted: 04/09/2015] [Indexed: 01/16/2023] Open
Abstract
Contribution of genetic predisposition to risk prediction of type 2 diabetes mellitus (T2DM) was investigated using a prospective study in middle-aged adults in Korea. From a community cohort of 6,257 subjects with 8 yr' follow-up, genetic predisposition score with subsets of 3, 18, 36 selected single nucleotide polymorphisms (SNPs) (genetic predisposition score; GPS-3, GPS-18, GPS-36) in association with T2DM were determined, and their effect was evaluated using risk prediction models. Rs5215, rs10811661, and rs2237892 were in significant association with T2DM, and hazard ratios per risk allele score increase were 1.11 (95% confidence intervals: 1.06-1.17), 1.09 (1.01-1.05), 1.04 (1.02-1.07) with GPS-3, GPS-18, GPS-36, respectively. Changes in AUC upon addition of GPS were significant in simple and clinical models, but the significance disappeared in full clinical models with glycated hemoglobin (HbA1c). For net reclassification index (NRI), significant improvement observed in simple (range 5.1%-8.6%) and clinical (3.1%-4.4%) models were no longer significant in the full models. Influence of genetic predisposition in prediction ability of T2DM incidence was no longer significant when HbA1c was added in the models, confirming HbA1c as a strong predictor for T2DM risk. Also, the significant SNPs verified in our subjects warrant further research, e.g. gene-environmental interaction and epigenetic studies.
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Affiliation(s)
- Hye Yin Park
- Center for Clinical Preventive Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Hyung Jin Choi
- Department of Internal Medicine, Chungbuk National University Hospital, Cheongju, Korea
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Korea
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20
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Mousel MR, Reynolds JO, White SN. Genome-Wide Association Identifies SLC2A9 and NLN Gene Regions as Associated with Entropion in Domestic Sheep. PLoS One 2015; 10:e0128909. [PMID: 26098909 PMCID: PMC4476619 DOI: 10.1371/journal.pone.0128909] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Accepted: 05/01/2015] [Indexed: 12/22/2022] Open
Abstract
Entropion is an inward rolling of the eyelid allowing contact between the eyelashes and cornea that may lead to blindness if not corrected. Although many mammalian species, including humans and dogs, are afflicted by congenital entropion, no specific genes or gene regions related to development of entropion have been reported in any mammalian species to date. Entropion in domestic sheep is known to have a genetic component therefore, we used domestic sheep as a model system to identify genomic regions containing genes associated with entropion. A genome-wide association was conducted with congenital entropion in 998 Columbia, Polypay, and Rambouillet sheep genotyped with 50,000 SNP markers. Prevalence of entropion was 6.01%, with all breeds represented. Logistic regression was performed in PLINK with additive allelic, recessive, dominant, and genotypic inheritance models. Two genome-wide significant (empirical P<0.05) SNP were identified, specifically markers in SLC2A9 (empirical P = 0.007; genotypic model) and near NLN (empirical P = 0.026; dominance model). Six additional genome-wide suggestive SNP (nominal P<1x10-5) were identified including markers in or near PIK3CB (P = 2.22x10-6; additive model), KCNB1 (P = 2.93x10-6; dominance model), ZC3H12C (P = 3.25x10-6; genotypic model), JPH1 (P = 4.68x20-6; genotypic model), and MYO3B (P = 5.74x10-6; recessive model). This is the first report of specific gene regions associated with congenital entropion in any mammalian species, to our knowledge. Further, none of these genes have previously been associated with any eyelid traits. These results represent the first genome-wide analysis of gene regions associated with entropion and provide target regions for the development of sheep genetic markers for marker-assisted selection.
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Affiliation(s)
- Michelle R. Mousel
- Range Sheep Production Efficiency Research Unit, Agricultural Research Service, Department of Agriculture, Dubois, ID, United States of America
- * E-mail:
| | - James O. Reynolds
- Animal Disease Research Unit, Agricultural Research Service, Department of Agriculture, Pullman, WA, United States of America
| | - Stephen N. White
- Animal Disease Research Unit, Agricultural Research Service, Department of Agriculture, Pullman, WA, United States of America
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, United States of America
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21
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Prattichizzo F, Giuliani A, Ceka A, Rippo MR, Bonfigli AR, Testa R, Procopio AD, Olivieri F. Epigenetic mechanisms of endothelial dysfunction in type 2 diabetes. Clin Epigenetics 2015; 7:56. [PMID: 26015812 PMCID: PMC4443613 DOI: 10.1186/s13148-015-0090-4] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Accepted: 05/12/2015] [Indexed: 02/08/2023] Open
Abstract
The development of type-2 diabetes mellitus (T2DM) and its complications is largely due to the complex interaction between genetic factors and environmental influences, mainly dietary habits and lifestyle, which can either accelerate or slow down disease progression. Recent findings suggest the potential involvement of epigenetic mechanisms as a crucial interface between the effects of genetic predisposition and environmental factors. The common denominator of environmental factors promoting T2DM development and progression is that they trigger an inflammatory response, promoting inflammation-mediated insulin resistance and endothelial dysfunction. Proinflammatory stimuli, including hyperglycemia, oxidative stress, and other inflammatory mediators, can affect epigenetic mechanisms, altering the expression of specific genes in target cells without changes in underlying DNA sequences. DNA methylation and post-translational histone modifications (PTHMs) are the most extensively investigated epigenetic mechanisms. Over the past few years, non-coding RNA, including microRNAs (miRNAs), have also emerged as key players in gene expression modulation. MiRNAs can be actively released or shed by cells in the bloodstream and taken up in active form by receiving cells, acting as efficient systemic communication tools. The miRNAs involved in modulation of inflammatory pathways (inflammamiRs), such as miR-146a, and those highly expressed in endothelial lineages and hematopoietic progenitor cells (angiomiRs), such as miR-126, are the most extensively studied circulating miRNAs in T2DM. However, data on circulating miRNA signatures associated with specific diabetic complications are still lacking. Since immune cells and endothelial cells are primarily involved in the vascular complications of T2DM, their relative contribution to circulating miRNA signatures needs to be elucidated. An integrated approach encompassing different epigenetic mechanisms would have the potential to provide new mechanistic insights into the genesis of diabetes and its severe vascular complications and identify a panel of epigenetic markers with diagnostic/prognostic and therapeutic relevance.
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Affiliation(s)
- Francesco Prattichizzo
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Via Tronto 10/A, 60020 Ancona, Italy
| | - Angelica Giuliani
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Via Tronto 10/A, 60020 Ancona, Italy
| | - Artan Ceka
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Via Tronto 10/A, 60020 Ancona, Italy
| | - Maria Rita Rippo
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Via Tronto 10/A, 60020 Ancona, Italy
| | | | - Roberto Testa
- Experimental Models in Clinical Pathology, National Institute INRCA-IRCCS, Ancona, Italy
| | - Antonio Domenico Procopio
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Via Tronto 10/A, 60020 Ancona, Italy ; Center of Clinical Pathology and Innovative Therapy, National Institute INRCA-IRCCS, Ancona, Italy
| | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Via Tronto 10/A, 60020 Ancona, Italy ; Center of Clinical Pathology and Innovative Therapy, National Institute INRCA-IRCCS, Ancona, Italy
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22
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Feng W, Zhao T, Mao G, Wang W, Feng Y, Li F, Zheng D, Wu H, Jin D, Yang L, Wu X. Type 2 diabetic rats on diet supplemented with chromium malate show improved glycometabolism, glycometabolism-related enzyme levels and lipid metabolism. PLoS One 2015; 10:e0125952. [PMID: 25942313 PMCID: PMC4420285 DOI: 10.1371/journal.pone.0125952] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2014] [Accepted: 03/28/2015] [Indexed: 01/04/2023] Open
Abstract
Our previous study showed that chromium malate improved the regulation of blood glucose in mice with alloxan-induced diabetes. The present study was designed to evaluate the effect of chromium malate on glycometabolism, glycometabolism-related enzymes and lipid metabolism in type 2 diabetic rats. Our results showed that fasting blood glucose, serum insulin level, insulin resistance index and C-peptide level in the high dose group had a significant downward trend when compared with the model group, chromium picolinate group and chromium trichloride group. The hepatic glycogen, glucose-6-phosphate dehydrogenase, glucokinase, Glut4, phosphor-AMPKβ1 and Akt levels in the high dose group were significantly higher than those of the model, chromium picolinate and chromium trichloride groups. Chromium malate in a high dose group can significantly increase high density lipoprotein cholesterol level while decreasing the total cholesterol, low density lipoprotein cholesterol and triglyceride levels when compared with chromium picolinate and chromium trichloride. The serum chromium content in chromium malate and chromium picolinate group is significantly higher than that of the chromium trichloride group. The results indicated that the curative effects of chromium malate on glycometabolism, glycometabolism-related enzymes and lipid metabolism changes are better than those of chromium picolinate and chromium trichloride. Chromium malate contributes to glucose uptake and transport in order to improved glycometabolism and glycometabolism-related enzymes.
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Affiliation(s)
- Weiwei Feng
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Ting Zhao
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Guanghua Mao
- School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Wei Wang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Yun Feng
- School of Medical Science and Laboratory Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Fang Li
- School of Medical Science and Laboratory Medicine, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Daheng Zheng
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Huiyu Wu
- School of Pharmacy, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Dun Jin
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Liuqing Yang
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Xiangyang Wu
- School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
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Guénard F, Lamontagne M, Bossé Y, Deshaies Y, Cianflone K, Kral JG, Marceau P, Vohl MC. Influences of gestational obesity on associations between genotypes and gene expression levels in offspring following maternal gastrointestinal bypass surgery for obesity. PLoS One 2015; 10:e0117011. [PMID: 25603303 PMCID: PMC4300091 DOI: 10.1371/journal.pone.0117011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2014] [Accepted: 12/17/2014] [Indexed: 12/17/2022] Open
Abstract
METHODS Whole-genome genotyping and gene expression analyses in blood of 22 BMS and 23 AMS offspring from 19 mothers were conducted using Illumina HumanOmni-5-Quad and HumanHT-12 v4 Expression BeadChips, respectively. Using PLINK we analyzed interactions between offspring gene variations and maternal surgical status on offspring gene expression levels. Altered biological functions and pathways were identified and visualized using DAVID and Ingenuity Pathway Analysis. RESULTS Significant interactions (p ≤ 1.22 x 10(-12)) were found for 525 among the 16,060 expressed transcripts: 1.9% of tested SNPs were involved. Gene function and pathway analysis demonstrated enrichment of transcription and of cellular metabolism functions and overrepresentation of cellular stress and signaling, immune response, inflammation, growth, proliferation and development pathways. CONCLUSION We suggest that impaired maternal gestational metabolic fitness interacts with offspring gene variations modulating gene expression levels, providing potential mechanisms explaining improved cardiometabolic risk profiles of AMS offspring related to ameliorated maternal lipid and carbohydrate metabolism.
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Affiliation(s)
- Frédéric Guénard
- Institute of Nutrition and Functional Foods (INAF) and Department of Food Science and Nutrition, Laval University, Quebec, Canada
- Endocrinology and Nephrology, CHU de Quebec Research Center, Quebec, Canada
| | | | - Yohan Bossé
- Quebec Heart and Lung Institute, Quebec, Canada
- Department of Molecular Medicine, Laval University, Quebec, Canada
| | - Yves Deshaies
- Quebec Heart and Lung Institute, Quebec, Canada
- Department of Medicine, Laval University, Quebec, Canada
| | - Katherine Cianflone
- Quebec Heart and Lung Institute, Quebec, Canada
- Department of Medicine, Laval University, Quebec, Canada
| | - John G. Kral
- Department of Surgery, SUNY Downstate Medical Center, Brooklyn, New York, United States of America
| | - Picard Marceau
- Quebec Heart and Lung Institute, Quebec, Canada
- Department of Surgery, Laval University, Quebec, Canada
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods (INAF) and Department of Food Science and Nutrition, Laval University, Quebec, Canada
- Endocrinology and Nephrology, CHU de Quebec Research Center, Quebec, Canada
- * E-mail:
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24
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Rulifson IC, Majeti JZ, Xiong Y, Hamburger A, Lee KJ, Miao L, Lu M, Gardner J, Gong Y, Wu H, Case R, Yeh WC, Richards WG, Baribault H, Li Y. Inhibition of secreted frizzled-related protein 5 improves glucose metabolism. Am J Physiol Endocrinol Metab 2014; 307:E1144-52. [PMID: 25370851 DOI: 10.1152/ajpendo.00283.2014] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Elucidating the role of secreted frizzled-related protein 5 (SFRP5) in metabolism and obesity has been complicated by contradictory findings when knockout mice were used to determine metabolic phenotypes. By overexpressing SFRP5 in obese, prediabetic mice we consistently observed elevated hyperglycemia and glucose intolerance, supporting SFRP5 as a negative regulator of glucose metabolism. Accordingly, Sfrp5 mRNA expression analysis of both epididymal and subcutaneous adipose depots of mice indicated a correlation with obesity. Thus, we generated a monoclonal antibody (mAb) against SFRP5 to ascertain the effect of SFRP5 inhibition in vivo. Congruent with SFRP5 overexpression worsening blood glucose levels and glucose intolerance, anti-SFRP5 mAb therapy improved these phenotypes in vivo. The results from both the overexpression and mAb inhibition studies suggest a role for SFRP5 in glucose metabolism and pancreatic β-cell function and thus establish the use of an anti-SFRP5 mAb as a potential approach to treat type 2 diabetes.
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Affiliation(s)
| | | | - Yumei Xiong
- Amgen Incorporated, South San Francisco, California; and
| | | | | | - Li Miao
- Amgen Incorporated, South San Francisco, California; and
| | - Mei Lu
- Amgen Incorporated, South San Francisco, California; and
| | | | - Yan Gong
- Amgen Incorporated, South San Francisco, California; and
| | - Hai Wu
- Amgen Incorporated, South San Francisco, California; and
| | - Ryan Case
- Amgen Incorporated, South San Francisco, California; and
| | - Wen-Chen Yeh
- Amgen Incorporated, South San Francisco, California; and
| | | | | | - Yang Li
- Amgen Incorporated, South San Francisco, California; and
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25
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Fernández M, Fabregat M, Javiel G, Mimbacas A. HLA alleles may serve as a tool to discriminate atypical type 2 diabetic patients. World J Diabetes 2014; 5:711-716. [PMID: 25317248 PMCID: PMC4138594 DOI: 10.4239/wjd.v5.i5.711] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2014] [Revised: 05/01/2014] [Accepted: 07/18/2014] [Indexed: 02/05/2023] Open
Abstract
AIM: To investigate whether the presence of human leukocyte antigen (HLA) marker could add new information to discriminated atypical diabetic type 2 patients.
METHODS: We analyzed 199 patients initially diagnosed as type 2 diabetes who are treated in special care diabetes clinics (3rd level). This population was classified in “atypical” (sample A) and “classic” (sample B) according to HLA typing. We consider “classic patient” when has absence of type 1 diabetes associated HLA alleles and no difficulties in their diagnosis and treatments. By the other hand, we considered “atypical patient” when show type 1 diabetes associated HLA alleles and difficulties in their diagnosis and treatments. The standard protocol Asociacion Latinoamericana de Diabetes 2006 was used for patients follow up. To analyze differences between both populations in paraclinical parameters we used unpaired t tests and contingence tables. Bivariate and multivariate analyses were carried out using the SPSS software program. In all studies we assume differences statistically significant, with a P-value < 0.05 corrected and 95%CI.
RESULTS: The typing HLA in the “atypical” populations show that 92.47% patients presented at list one type 1 diabetes associated HLA alleles (DQB1*0201-0302 and DR 3-4) and 7.53% had two of its. The results showed for categorical variables (family history, presence or absence of hypertension and/or dyslipidemia, reason for initial consultation) the only difference found was at dyslipidemia (OR = 0.45, 0.243 < OD < 0.822 (P < 0.001). In relation to continuous variables we found significant differences between atypical vs classic only in cholesterol (5.07 ± 1.1 vs 5.56 ± 1.5, P < 0.05), high density lipoproteins (1.23 ± 0.3 vs 1.33 ± 0.3, P < 0.05) and low density lipoproteins (2.86 ± 0.9 vs 3.38 ± 1.7, P < 0.01). None of the variables had discriminating power when logistic regression was done.
CONCLUSION: We propose an algorithm including HLA genotyping as a tool to discriminate atypical patients, complementing international treatment guidelines for complex patients.
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26
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Vaxillaire M, Yengo L, Lobbens S, Rocheleau G, Eury E, Lantieri O, Marre M, Balkau B, Bonnefond A, Froguel P. Type 2 diabetes-related genetic risk scores associated with variations in fasting plasma glucose and development of impaired glucose homeostasis in the prospective DESIR study. Diabetologia 2014; 57:1601-10. [PMID: 24893864 DOI: 10.1007/s00125-014-3277-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2014] [Accepted: 05/02/2014] [Indexed: 02/06/2023]
Abstract
AIMS/HYPOTHESIS Genome-wide association studies have firmly established 65 independent European-derived loci associated with type 2 diabetes and 36 loci contributing to variations in fasting plasma glucose (FPG). Using individual data from the Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR) prospective study, we evaluated the contribution of three genetic risk scores (GRS) to variations in metabolic traits, and to the incidence and prevalence of impaired fasting glycaemia (IFG) and type 2 diabetes. METHODS Three GRS (GRS-1, 65 type 2 diabetes-associated single nucleotide polymorphisms [SNPs]; GRS-2, GRS-1 combined with 24 FPG-raising SNPs; and GRS-3, FPG-raising SNPs alone) were analysed in 4,075 DESIR study participants. GRS-mediated effects on longitudinal variations in quantitative traits were assessed in 3,927 nondiabetic individuals using multivariate linear mixed models, and on the incidence and prevalence of hyperglycaemia at 9 years using Cox and logistic regression models. The contribution of each GRS to risk prediction was evaluated using the C-statistic and net reclassification improvement (NRI) analysis. RESULTS The two most inclusive GRS were significantly associated with increased FPG (β = 0.0011 mmol/l per year per risk allele, p GRS-1 = 8.2 × 10(-5) and p GRS-2 = 6.0 × 10(-6)), increased incidence of IFG and type 2 diabetes (per allele: HR GRS-1 1.03, p = 4.3 × 10(-9) and HR GRS-2 1.04, p = 1.0 × 10(-16)), and the 9 year prevalence (OR GRS-1 1.13 [95% CI 1.10, 1.17], p = 1.9 × 10(-14) for type 2 diabetes only; OR GRS-2 1.07 [95% CI 1.05, 1.08], p = 7.8 × 10(-25), for IFG and type 2 diabetes). No significant interaction was found between GRS-1 or GRS-2 and potential confounding factors. Each GRS yielded a modest, but significant, improvement in overall reclassification rates (NRI GRS-1 17.3%, p = 6.6 × 10(-7); NRI GRS-2 17.6%, p = 4.2 × 10(-7); NRI GRS-3 13.1%, p = 1.7 × 10(-4)). CONCLUSIONS/INTERPRETATION Polygenic scores based on combined genetic information from type 2 diabetes risk and FPG variation contribute to discriminating middle-aged individuals at risk of developing type 2 diabetes in a general population.
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Abstract
Knowledge of the genetics of type 2 diabetes mellitus (T2DM) has evolved tremendously over the past few years. Following advances in technology and analytical approaches, collaborative case-control genome-wide association studies have revealed up to 65 loci credibly associated with T2DM. Prospective population studies have demonstrated that aggregated genetic risk scores, so-called because they sum the genetic risk attributed to each locus, can predict incident T2DM among individuals of various age ranges and diverse ethnic backgrounds. With each set of T2DM loci discovered, increasing the number of loci in these scores has improved their predictive ability, although a prediction plateau may already have been reached. The current literature shows that intensive lifestyle interventions are effective for preventing T2DM at any level of genetic risk and might be particularly efficacious among individuals with high genetic susceptibility. By contrast, counselling to inform patients about their personal T2DM genetic risk profiles does not seem to improve motivation or attitudes that lead to positive lifestyle behaviour changes. Future studies should investigate the role of genetics for both T2DM prediction and prevention in young populations in the hope of reducing disease burden for future generations.
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Affiliation(s)
- Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, 50 Staniford Street, 9th floor, Boston, MA 02114, USA
| | - Jason L Vassy
- Section of General Internal Medicine, VA Boston Healthcare System, Harvard Medical School, 50 Staniford Street, 9th floor, Boston, MA 02114, USA
| | - James B Meigs
- General Medicine Division, Massachusetts General Hospital, Harvard Medical School, 50 Staniford Street, 9th floor, Boston, MA 02114, USA
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Predicting the metabolic condition after gestational diabetes mellitus from oral glucose tolerance test curves shape. Ann Biomed Eng 2014; 42:1112-20. [PMID: 24473701 DOI: 10.1007/s10439-014-0979-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2013] [Accepted: 01/17/2014] [Indexed: 02/01/2023]
Abstract
The objective of this feasibility study is to predict the metabolic condition in women with a history of gestational diabetes mellitus (GDM) from the shape of oral glucose tolerance test (OGTT) data. The rationale for this approach is that the evolution to a metabolic condition could be traceable in the shape of OGTT curves. 3-h OGTT data of 136 women with follow up, for a total of 401 OGTTs were analyzed. Subjects were classified as having normal (NGT) or non-normal glucose tolerance (NON-NGT), according to the American Diabetes Association criteria. The measured glucose, insulin, C-peptide data and combination of them were used to build up NGT and NON-NGT reference curves. Similarity between reference and individual OGTT-based curves was calculated using the Kullback-Leibler divergence. Our findings suggest that the shape of OGTT curves (1) contains information on the evolution to disease and (2) could be a reliable indicator to predict with high sensitivity (75%) and high specificity (69%) the metabolic condition of women with a history of GDM. In the future, the proposed shape-based prediction could be easily translated to the clinical practice, because it does not require the intervention of an operator specifically trained, thus facilitating its application in a clinical setting and ultimately empowering risk estimation, by improving/complementing the information which is currently adopted for risk stratification after pregnancy with GDM.
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Fry CH, Sahai A, Vahabi B, Kanai AJ, Birder LA. What is the role for biomarkers for lower urinary tract disorders? ICI-RS 2013. Neurourol Urodyn 2014; 33:602-5. [PMID: 24436105 DOI: 10.1002/nau.22558] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2013] [Accepted: 12/17/2013] [Indexed: 12/12/2022]
Abstract
AIMS A biomarker is an entity that measures a normal or pathological process, or the response to an intervention. A biomarker must measure exclusively and be sufficiently sensitive to the process of interest. Alternatively, a biomarker may give clues regarding the underlying pathology of the condition and be a useful research or specialist tool. If a biomarker is to be of practical benefit then it must also be economical and practical to use. This article will consider chemical moieties as biomarkers, although in principle physical markers (e.g., bladder wall thickness) could also be defined as such. RESULTS AND CONCLUSIONS The validation of a biomarker for detrusor overactivity (DO) must appreciate the fact that the condition is likely to multifactorial and thus no single entity may be sufficiently selective and sensitive. However, more specific conditions, such as bladder pain associated with DO, may make the biomarker search easier. Several prospective agents including antiproliferative factor (APF) and epidermal growth factors (EGF) are discussed. Several urinary biomarkers, including neurotrophins (NGF, BDNF) and cytokines, and a serum marker, C-reactive protein, are considered as reaching the above criteria. All suffer from relatively poor lack of discrimination, as they all change in response to other, often inflammatory, conditions; BDNF may offer the highest expectations. Urinary ATP has also been proposed as a DO/OAB biomarker but requires further evaluation. Finally genetic markers offer potential to understand more about the pathophysiology of DO/OAB. The increasing availability of genome-wide association studies and micro-RNA assays offer genetic markers as a new generation of biomarkers. Neurourol. Urodynam. 33:602-605, 2014. © 2014 Wiley Periodicals, Inc.
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Affiliation(s)
- Christopher H Fry
- Department of Biochemistry and Physiology, University of Surrey, Guildford, Surrey, United Kingdom
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The effect of genetic counseling for adult offspring of patients with type 2 diabetes on attitudes toward diabetes and its heredity: a randomized controlled trial. J Genet Couns 2014; 23:762-9. [PMID: 24399094 DOI: 10.1007/s10897-013-9680-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2012] [Accepted: 12/04/2013] [Indexed: 01/23/2023]
Abstract
The aim of this study is to investigate the effect of diabetes genetic counseling on attitudes toward diabetes and its heredity in relatives of type 2 diabetes patients. This study was an unmasked, randomized controlled trial at a medical check-up center in Japan. Subjects in this study are healthy adults between 30 and 60 years of age who have a family history of type 2 diabetes in their first degree relatives. Participants in the intervention group received a brief genetic counseling session for approximately 10 min. Genetic counseling was structured based on the Health Belief Model. Both intervention and control groups received a booklet for general diabetes prevention. Risk perception and recognition of diabetes, and attitude towards its prevention were measured at baseline, 1 week and 1 year after genetic counseling. Participants who received genetic counseling showed significantly higher recognition about their sense of control over diabetes onset than control group both at 1 week and 1 year after the session. On the other hand, anxiety about diabetes did not change significantly. The findings show that genetic counseling for diabetes at a medical check center helped adults with diabetes family history understand they are able to exert control over the onset of their disease through lifestyle modification.
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Herder C, Kowall B, Tabak AG, Rathmann W. The potential of novel biomarkers to improve risk prediction of type 2 diabetes. Diabetologia 2014; 57:16-29. [PMID: 24078135 DOI: 10.1007/s00125-013-3061-3] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2013] [Accepted: 08/24/2013] [Indexed: 01/05/2023]
Abstract
The incidence of type 2 diabetes can be reduced substantially by implementing preventive measures in high-risk individuals, but this requires prior knowledge of disease risk in the individual. Various diabetes risk models have been designed, and these have all included a similar combination of factors, such as age, sex, obesity, hypertension, lifestyle factors, family history of diabetes and metabolic traits. The accuracy of prediction models is often assessed by the area under the receiver operating characteristic curve (AROC) as a measure of discrimination, but AROCs should be complemented by measures of calibration and reclassification to estimate the incremental value of novel biomarkers. This review discusses the potential of novel biomarkers to improve model accuracy. The range of molecules that serve as potential predictors of type 2 diabetes includes genetic variants, RNA transcripts, peptides and proteins, lipids and small metabolites. Some of these biomarkers lead to a statistically significant increase of model accuracy, but their incremental value currently seems too small for routine clinical use. However, only a fraction of potentially relevant biomarkers have been assessed with regard to their predictive value. Moreover, serial measurements of biomarkers may help determine individual risk. In conclusion, current risk models provide valuable tools of risk estimation, but perform suboptimally in the prediction of individual diabetes risk. Novel biomarkers still fail to have a clinically applicable impact. However, more efficient use of biomarker data and technological advances in their measurement in clinical settings may allow the development of more accurate predictive models in the future.
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Kwak SH, Choi SH, Kim K, Jung HS, Cho YM, Lim S, Cho NH, Kim SY, Park KS, Jang HC. Prediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score. Diabetologia 2013; 56:2556-63. [PMID: 24057154 DOI: 10.1007/s00125-013-3059-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2013] [Accepted: 09/04/2013] [Indexed: 12/25/2022]
Abstract
AIMS/HYPOTHESIS Women with a history of gestational diabetes mellitus (GDM) are at increased risk of future development of type 2 diabetes. Recently, over 65 genetic variants have been confirmed to be associated with diabetes. We investigated whether this genetic information could improve the prediction of future diabetes in women with GDM. METHODS This was a prospective cohort study consisting of 395 women with GDM who were followed annually with an OGTT. A weighted genetic risk score (wGRS), consisting of 48 variants, was assessed for improving discrimination (C statistic) and risk reclassification (continuous net reclassification improvement [NRI] index) when added to clinical risk factors. RESULTS Among the 395 women with GDM, 116 (29.4%) developed diabetes during a median follow-up period of 45 months. Women with GDM who went on to develop diabetes had a significantly higher wGRS than those who did not (9.36 ± 0.92 vs 8.78 ± 1.07; p < 1.56 × 10(-7)). In a complex clinical model adjusted for age, prepregnancy BMI, family history of diabetes, blood pressure, fasting glucose and fasting insulin concentration, the C statistic marginally improved from 0.741 without the wGRS to 0.775 with the wGRS (p = 0.015). The addition of the wGRS to the clinical model resulted in a modest improvement in reclassification (continuous NRI 0.430 [95% CI 0.218, 0.642]; p = 7.0 × 10(-5)). CONCLUSIONS/INTERPRETATION In women with GDM, who are at high risk of diabetes, the wGRS was significantly associated with the future development of diabetes. Furthermore, it improved prediction over clinical risk factors.
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Affiliation(s)
- Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-Ro, Chongno-Gu, Seoul, 110-744, South Korea
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Collins J, Ryan L, Truby H. A systematic review of the factors associated with interest in predictive genetic testing for obesity, type II diabetes and heart disease. J Hum Nutr Diet 2013; 27:479-88. [DOI: 10.1111/jhn.12179] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- J. Collins
- Department of Nutrition and Dietetics; Monash University; Notting Hill VIC Australia
| | - L. Ryan
- Department of Nutrition and Dietetics; Monash University; Notting Hill VIC Australia
| | - H. Truby
- Department of Nutrition and Dietetics; Monash University; Notting Hill VIC Australia
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Xu M, Bi Y, Cui B, Hong J, Wang W, Ning G. The new perspectives on genetic studies of type 2 diabetes and thyroid diseases. Curr Genomics 2013; 14:33-48. [PMID: 23997649 PMCID: PMC3580778 DOI: 10.2174/138920213804999138] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2012] [Revised: 11/16/2012] [Accepted: 11/19/2012] [Indexed: 12/18/2022] Open
Abstract
Recently, genome-wide association studies (GWAS) have led to the discovery of hundreds of susceptibility loci that are associated with complex metabolic diseases, such as type 2 diabetes and hyperthyroidism. The majority of the susceptibility loci are common across different races or populations; while some of them show ethnicity-specific distribution. Though the abundant novel susceptibility loci identified by GWAS have provided insight into biology through the discovery of new genes or pathways that were previously not known, most of them are in introns and the associated variants cumulatively explain only a small fraction of total heritability. Here we reviewed the genetic studies on the metabolic disorders, mainly type 2 diabetes and hyperthyroidism, including candidate genes-based findings and more recently the GWAS discovery; we also included the clinical relevance of these novel loci and the gene-environmental interactions. Finally, we discussed the future direction about the genetic study on the exploring of the pathogenesis of the metabolic diseases.
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Affiliation(s)
- Min Xu
- Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, E-Institute of Shanghai Universities, Shanghai, China
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Affiliation(s)
- Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden.
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Expanding possibilities for intervention against small ruminant lentiviruses through genetic marker-assisted selective breeding. Viruses 2013; 5:1466-99. [PMID: 23771240 PMCID: PMC3717717 DOI: 10.3390/v5061466] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2013] [Revised: 06/01/2013] [Accepted: 06/07/2013] [Indexed: 12/25/2022] Open
Abstract
Small ruminant lentiviruses include members that infect sheep (ovine lentivirus [OvLV]; also known as ovine progressive pneumonia virus/maedi-visna virus) and goats (caprine arthritis encephalitis virus [CAEV]). Breed differences in seroprevalence and proviral concentration of OvLV had suggested a strong genetic component in susceptibility to infection by OvLV in sheep. A genetic marker test for susceptibility to OvLV has been developed recently based on the TMEM154 gene with validation data from over 2,800 sheep representing nine cohorts. While no single genotype has been shown to have complete resistance to OvLV, consistent association in thousands of sheep from multiple breeds and management conditions highlight a new strategy for intervention by selective breeding. This genetic marker-assisted selection (MAS) has the potential to be a useful addition to existing viral control measures. Further, the discovery of multiple additional genomic regions associated with susceptibility to or control of OvLV suggests that additional genetic marker tests may be developed to extend the reach of MAS in the future. This review will cover the strengths and limitations of existing data from host genetics as an intervention and outline additional questions for future genetic research in sheep, goats, small ruminant lentiviruses, and their host-pathogen interactions.
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McNaughton D. 'Diabesity' down under: overweight and obesity as cultural signifiers for type 2 diabetes mellitus. CRITICAL PUBLIC HEALTH 2013; 23:274-288. [PMID: 23914074 PMCID: PMC3725668 DOI: 10.1080/09581596.2013.766671] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2012] [Revised: 01/10/2013] [Indexed: 12/24/2022]
Abstract
Although overweight and obesity are increasingly seen as the key ‘risk factors’ for Type 2 diabetes mellitus (T2DM), the relationship between them is complex and not well understood. There are many ‘risk factors’ for T2DM, including ageing, genetics, previous gestational diabetes, a family history of the disease, etc. the interplay of which is not entirely clear. While weight gain is a common symptom of T2DM and the disease appears to be more prevalent among ‘obese’ people, individuals from a broad range of weights (including those considered ‘healthy’) can develop the disease. However, in recent years, the idea that fatness is the risk factor and/or central cause of T2DM has become increasingly prevalent and naturalized in popular, academic, and public health discourses in Australia. In these convergences, the complex etiology of the disease and limitations in current knowledge are blurred or reconstituted. To date, the potency of overweight and obesity as cultural signifiers for T2DM and its consequences has received little attention. Drawing on an analysis of government reports, journal articles, and media coverage published since 1998, this article sets out to trace and unpack some of the contours of these convergences, while recognizing their entanglement in earlier moralizing discourses, which continue to have considerable salience.
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Ruan HL, Qin HD, Shugart YY, Bei JX, Luo FT, Zeng YX, Jia WH. Developing genetic epidemiological models to predict risk for nasopharyngeal carcinoma in high-risk population of China. PLoS One 2013; 8:e56128. [PMID: 23457511 PMCID: PMC3574061 DOI: 10.1371/journal.pone.0056128] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2012] [Accepted: 01/04/2013] [Indexed: 01/12/2023] Open
Abstract
To date, the only established model for assessing risk for nasopharyngeal carcinoma (NPC) relies on the sero-status of the Epstein-Barr virus (EBV). By contrast, the risk assessment models proposed here include environmental risk factors, family history of NPC, and information on genetic variants. The models were developed using epidemiological and genetic data from a large case-control study, which included 1,387 subjects with NPC and 1,459 controls of Cantonese origin. The predictive accuracy of the models were then assessed by calculating the area under the receiver-operating characteristic curves (AUC). To compare the discriminatory improvement of models with and without genetic information, we estimated the net reclassification improvement (NRI) and integrated discrimination index (IDI). Well-established environmental risk factors for NPC include consumption of salted fish and preserved vegetables and cigarette smoking (in pack years). The environmental model alone shows modest discriminatory ability (AUC = 0.68; 95% CI: 0.66, 0.70), which is only slightly increased by the addition of data on family history of NPC (AUC = 0.70; 95% CI: 0.68, 0.72). With the addition of data on genetic variants, however, our model’s discriminatory ability rises to 0.74 (95% CI: 0.72, 0.76). The improvements in NRI and IDI also suggest the potential usefulness of considering genetic variants when screening for NPC in endemic areas. If these findings are confirmed in larger cohort and population-based case-control studies, use of the new models to analyse data from NPC-endemic areas could well lead to earlier detection of NPC.
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Affiliation(s)
- Hong-Lian Ruan
- State Key Laboratory of Oncology in Southern China, Guangzhou, China
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Hai-De Qin
- Unit of Statistical Genomics, Division of Intramural Research Program, National Institute of Mental Health (NIMH)/National Institutes of Health (NIH), Bethesda, Maryland, United States of America
| | - Yin Yao Shugart
- Unit of Statistical Genomics, Division of Intramural Research Program, National Institute of Mental Health (NIMH)/National Institutes of Health (NIH), Bethesda, Maryland, United States of America
| | - Jin-Xin Bei
- State Key Laboratory of Oncology in Southern China, Guangzhou, China
| | - Fu-Tian Luo
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Yi-Xin Zeng
- State Key Laboratory of Oncology in Southern China, Guangzhou, China
- * E-mail: (Y-XZ); (W-HJ)
| | - Wei-Hua Jia
- State Key Laboratory of Oncology in Southern China, Guangzhou, China
- * E-mail: (Y-XZ); (W-HJ)
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Jensen RA, Sim X, Li X, Cotch MF, Ikram MK, Holliday EG, Eiriksdottir G, Harris TB, Jonasson F, Klein BEK, Launer LJ, Smith AV, Boerwinkle E, Cheung N, Hewitt AW, Liew G, Mitchell P, Wang JJ, Attia J, Scott R, Glazer NL, Lumley T, McKnight B, Psaty BM, Taylor K, Hofman A, de Jong PTVM, Rivadeneira F, Uitterlinden AG, Tay WT, Teo YY, Seielstad M, Liu J, Cheng CY, Saw SM, Aung T, Ganesh SK, O'Donnell CJ, Nalls MA, Wiggins KL, Kuo JZ, van Duijn CM, Gudnason V, Klein R, Siscovick DS, Rotter JI, Tai ES, Vingerling J, Wong TY. Genome-wide association study of retinopathy in individuals without diabetes. PLoS One 2013; 8:e54232. [PMID: 23393555 PMCID: PMC3564946 DOI: 10.1371/journal.pone.0054232] [Citation(s) in RCA: 11] [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: 08/08/2012] [Accepted: 12/11/2012] [Indexed: 01/11/2023] Open
Abstract
Background Mild retinopathy (microaneurysms or dot-blot hemorrhages) is observed in persons without diabetes or hypertension and may reflect microvascular disease in other organs. We conducted a genome-wide association study (GWAS) of mild retinopathy in persons without diabetes. Methods A working group agreed on phenotype harmonization, covariate selection and analytic plans for within-cohort GWAS. An inverse-variance weighted fixed effects meta-analysis was performed with GWAS results from six cohorts of 19,411 Caucasians. The primary analysis included individuals without diabetes and secondary analyses were stratified by hypertension status. We also singled out the results from single nucleotide polymorphisms (SNPs) previously shown to be associated with diabetes and hypertension, the two most common causes of retinopathy. Results No SNPs reached genome-wide significance in the primary analysis or the secondary analysis of participants with hypertension. SNP, rs12155400, in the histone deacetylase 9 gene (HDAC9) on chromosome 7, was associated with retinopathy in analysis of participants without hypertension, −1.3±0.23 (beta ± standard error), p = 6.6×10−9. Evidence suggests this was a false positive finding. The minor allele frequency was low (∼2%), the quality of the imputation was moderate (r2 ∼0.7), and no other common variants in the HDAC9 gene were associated with the outcome. SNPs found to be associated with diabetes and hypertension in other GWAS were not associated with retinopathy in persons without diabetes or in subgroups with or without hypertension. Conclusions This GWAS of retinopathy in individuals without diabetes showed little evidence of genetic associations. Further studies are needed to identify genes associated with these signs in order to help unravel novel pathways and determinants of microvascular diseases.
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Affiliation(s)
- Richard A Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America.
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Kwak SH, Park KS. Genetics of type 2 diabetes and potential clinical implications. Arch Pharm Res 2013; 36:167-77. [PMID: 23377708 DOI: 10.1007/s12272-013-0021-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2012] [Accepted: 12/24/2012] [Indexed: 12/30/2022]
Abstract
Type 2 diabetes (T2DM) is a common complex metabolic disorder that has a strong genetic component. Recent advances in genome-wide association studies have revolutionized our knowledge regarding the genetics of T2DM. There are at least 64 common genetic variants that are strongly associated with T2DM. However, the pathophysiologic roles of these variants are mostly unknown and require further functional characterization. The variants identified so far have a small effect size and their added effect explains less than 10 % of the T2DM heritability. The current ongoing whole exome and whole genome studies of T2DM are focused on identifying functionally important rare variants that have a stronger effect. Through these efforts, we will have a better understanding of the genetic architecture of T2DM and its pathophysiology. The potential clinical applications of genetic studies of T2DM include risk prediction, identification of novel therapeutic targets, genetic prediction of efficacy and toxicity of anti-diabetic medications, and eventually optimization of patient care through personalized genomic medicine. We hope further research in genetics of T2DM could aid patient care and improve outcomes of T2DM patients.
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Affiliation(s)
- Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
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