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Rout M, Tung GK, Singh JR, Mehra NK, Wander GS, Ralhan S, Sanghera DK. Polygenic Risk Score Assessment for Coronary Artery Disease in Asian Indians. J Cardiovasc Transl Res 2024:10.1007/s12265-024-10511-z. [PMID: 38658478 DOI: 10.1007/s12265-024-10511-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/11/2024] [Indexed: 04/26/2024]
Abstract
We evaluated the performance of various polygenic risk score (PRS) models derived from European (EU), South Asian (SA), and Punjabi Asian Indians (AI) studies on 13,974 subjects from AI ancestry. While all models successfully predicted Coronary artery disease (CAD) risk, the AI, SA, and EU + AI were superior predictors and more transportable than the EU model; the predictive performance in training and test sets was 18% and 22% higher in AI and EU + AI models, respectively than in EU. Comparing individuals with extreme PRS quartiles, the AI and EU + AI captured individuals with high CAD risk showed 2.6 to 4.6 times higher efficiency than the EU. Interestingly, including the clinical risk score did not significantly change the performance of any genetic model. The enrichment of diversity variants in EU PRS improves risk prediction and transportability. Establishing population-specific normative and risk factors and inclusion into genetic models would refine the risk stratification and improve the clinical utility of CAD PRS.
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Affiliation(s)
- Madhusmita Rout
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | - Gurleen Kaur Tung
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | | | | | | | - Sarju Ralhan
- Hero DMC Heart Institute, Ludhiana, Punjab, India
| | - Dharambir K Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA.
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Priyadarshini A, Madan R, Das S. Genetics and epigenetics of diabetes and its complications in India. Hum Genet 2024; 143:1-17. [PMID: 37999799 DOI: 10.1007/s00439-023-02616-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 10/17/2023] [Indexed: 11/25/2023]
Abstract
Diabetes mellitus (DM) has become a significant health concern with an increasing rate of morbidity and mortality worldwide. India ranks second in the number of diabetes cases in the world. The increasing burden of DM can be explained by genetic predisposition of Indians to type 2 diabetes mellitus (T2DM) coupled with rapid urbanization and socio-economic development in the last 3 decades leading to drastic changes in lifestyle. Environment and lifestyle changes contribute to T2DM development by altering epigenetic processes such as DNA methylation, histone post-translational modifications, and long non-coding RNAs, all of which regulate chromatin structure and gene expression. Although the genetic predisposition of Indians to T2DM is well established, how environmental and genetic factors interact and lead to T2DM is not well understood. In this review, we discuss the prevalence of diabetes and its complications across different states in India and how various risk factors contribute to its pathogenesis. The review also highlights the role of genetic predisposition among the Indian population and epigenetic factors involved in the etiology of diabetes. Lastly, we review current treatments and emphasize the knowledge gap with respect to genetic and epigenetic factors in the Indian context. Further understanding of the genetic and epigenetic determinants will help in risk prediction and prevention as well as therapeutic interventions, which will improve the clinical management of diabetes and associated macro- and micro-vascular complications.
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Affiliation(s)
- Ankita Priyadarshini
- Diabetic Vascular Complications Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Mohali, Punjab, 140306, India
| | - Riya Madan
- Diabetic Vascular Complications Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Mohali, Punjab, 140306, India
| | - Sadhan Das
- Diabetic Vascular Complications Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Mohali, Punjab, 140306, India.
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Rout M, Wander GS, Ralhan S, Singh JR, Aston CE, Blackett PR, Chernausek S, Sanghera DK. Assessing the prediction of type 2 diabetes risk using polygenic and clinical risk scores in South Asian study populations. Ther Adv Endocrinol Metab 2023; 14:20420188231220120. [PMID: 38152657 PMCID: PMC10752110 DOI: 10.1177/20420188231220120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 11/11/2023] [Indexed: 12/29/2023] Open
Abstract
Background Genome-wide polygenic risk scores (PRS) have shown high specificity and sensitivity in predicting type 2 diabetes (T2D) risk in Europeans. However, the PRS-driven information and its clinical significance in non-Europeans are underrepresented. We examined the predictive efficacy and transferability of PRS models using variant information derived from genome-wide studies of Asian Indians (AIs) (PRSAI) and Europeans (PRSEU) using 13,974 AI individuals. Methods Weighted PRS models were constructed and analyzed on 4602 individuals from the Asian Indian Diabetes Heart Study/Sikh Diabetes Study (AIDHS/SDS) as discovery/training and test/validation datasets. The results were further replicated in 9372 South Asian individuals from UK Biobank (UKBB). We also assessed the performance of each PRS model by combining data of the clinical risk score (CRS). Results Both genetic models (PRSAI and PRSEU) successfully predicted the T2D risk. However, the PRSAI revealed 13.2% odds ratio (OR) 1.80 [95% confidence interval (CI) 1.63-1.97; p = 1.6 × 10-152] and 12.2% OR 1.38 (95% CI 1.30-1.46; p = 7.1 × 10-237) superior performance in AIDHS/SDS and UKBB validation sets, respectively. Comparing individuals of extreme PRS (ninth decile) with the average PRS (fifth decile), PRSAI showed about two-fold OR 20.73 (95% CI 10.27-41.83; p = 2.7 × 10-17) and 1.4-fold OR 3.19 (95% CI 2.51-4.06; p = 4.8 × 10-21) higher predictability to identify subgroups with higher genetic risk than the PRSEU. Combining PRS and CRS improved the area under the curve from 0.74 to 0.79 in PRSAI and 0.72 to 0.75 in PRSEU. Conclusion Our data suggest the need for extending genetic and clinical studies in varied ethnic groups to exploit the full clinical potential of PRS as a risk prediction tool in diverse study populations.
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Affiliation(s)
- Madhusmita Rout
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Sarju Ralhan
- Hero DMC Heart Institute, Ludhiana, Punjab, India
| | - Jai Rup Singh
- Central University of Punjab, Bathinda, Punjab, India
| | - Christopher E. Aston
- Section of Developmental and Behavioral Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Piers R. Blackett
- Department of Pediatrics, Section of Endocrinology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Steven Chernausek
- Department of Pediatrics, Section of Endocrinology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Dharambir K. Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK 73104, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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Rabby MG, Rahman MH, Islam MN, Kamal MM, Biswas M, Bonny M, Hasan MM. In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes. PLoS One 2023; 18:e0294399. [PMID: 38096208 PMCID: PMC10721103 DOI: 10.1371/journal.pone.0294399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023] Open
Abstract
Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.
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Affiliation(s)
- Md. Golam Rabby
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Hafizur Rahman
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
- Faculty of Food Sciences and Safety, Department of Quality Control and Safety Management, Khulna Agricultural University, Khulna, Bangladesh
| | - Md. Numan Islam
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mostafa Kamal
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mrityunjoy Biswas
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mantasa Bonny
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mahmudul Hasan
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
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Shelake G, Baviskar S, Panda AK, Solankure S, Pandey K, Chauthe S, Behera SK. Exploring the rare variants associated with Type 2 Diabetes Mellitus in Indian population and its disease-drug association studies: an in-silico approach. J Biomol Struct Dyn 2023:1-16. [PMID: 37440426 DOI: 10.1080/07391102.2023.2233634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 07/01/2023] [Indexed: 07/15/2023]
Abstract
The diversified eating habits and religious culture of Indian population may be one of the reasons they largely contribute to the global diabetes burden. In the present investigation, an in-silico approach was carried out to explore hub genes in the Indian population with Type 2 Diabetes Mellitus (T2DM) that are scantily reported in the GWAS catalogue and probable potential anti-diabetic drugs from plants. This computational approach unwrapped LEP (leptin) as the hub gene among 170 genes analyzed with 14 non-synonymous single nucleotide polymorphisms (nsSNPs) with MAF < 0.01. The mutation of the LEP gene leads to a decrease in leptin concentration, which increases the risk of obesity and T2DM. According to the DUET webserver, 11 of 14 mutations examined were found to destabilize the LEP protein. Among 14, four barely reported LEP variants rs781301976 (I45N), rs776443424 (S52F), rs200915360 (D76Y), and rs1191666811 (D162N) were unzipped to be associated with T2DM, which may be the probable potential drug targets. The virtual screening revealed Vescalagin as having the highest binding energy among 336 natural compounds. Molecular docking of Vescalagin depicted higher binding energy (-9.0 kcal/mol) against mutated LEP [rs200915360 (D76Y)] compared to wild (-8.9 kcal/mol) and LEP-Metformin complexes. The trajectory analysis of MD simulations revealed that Vescalagin was more effective than Metformin in stabilizing the system. The present study suggests that the associations of the investigated nsSNPs in LEP [rs200915360 (D76Y)] and others can be key factors in the predominant role of T2DM morbidity in the Indian population that can be used as potential markers and drug targets for T2DM therapeutics.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ganesh Shelake
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research, Ahmedabad, Gandhinagar, Gujarat, India
| | - Shraddha Baviskar
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research, Ahmedabad, Gandhinagar, Gujarat, India
| | - Amrita Kumari Panda
- Department of Biotechnology, Sant Gahira Guru Vishwavidyalaya, Sarguja, Ambikapur, Chhattisgarh, India
| | - Sunetra Solankure
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research, Ahmedabad, Gandhinagar, Gujarat, India
| | - Komal Pandey
- Department of Natural Products, National Institute of Pharmaceutical Education and Research, Ahmedabad, Gandhinagar, Gujarat, India
| | - Siddheshwar Chauthe
- Department of Natural Products, National Institute of Pharmaceutical Education and Research, Ahmedabad, Gandhinagar, Gujarat, India
| | - Santosh Kumar Behera
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research, Ahmedabad, Gandhinagar, Gujarat, India
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Yajnik CS, Wagh R, Kunte P, Asplund O, Ahlqvist E, Bhat D, Shukla SR, Prasad RB. Polygenic scores of diabetes-related traits in subgroups of type 2 diabetes in India: a cohort study. THE LANCET REGIONAL HEALTH. SOUTHEAST ASIA 2023; 14:100182. [PMID: 37492423 PMCID: PMC10363502 DOI: 10.1016/j.lansea.2023.100182] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/08/2022] [Accepted: 03/09/2023] [Indexed: 07/27/2023]
Abstract
Background A machine-learning approach identified five subgroups of diabetes in Europeans which included severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD) with partially distinct genetic aetiologies. We previously validated four of the non-autoimmune subgroups in people with young-onset type 2 diabetes (T2D) from the Indian WellGen study. Here, we aimed to apply European-derived centroids and genetic risk scores (GRSs) to the unselected (for age) WellGen to test their applicability and investigate the genetic aetiology of the Indian T2D subgroups. Methods We applied European derived centroids and GRSs to T2D participants of Indian ancestry (WellGen, n = 2217, 821 genotyped) and compared them with normal glucose tolerant controls (Pune Maternal Nutrition Study, n = 461). Findings SIDD was the predominant subgroup followed by MOD, whereas SIRD and MARD were less frequent. Weighted-GRS for T2D, obesity and lipid-related traits associated with T2D. We replicated some of the previous associations of GRS for T2D, insulin secretion, and BMI with SIDD and MOD. Unique to Indian subgroups was the association of GRS for (a) proinsulin with MOD and MARD, (b) liver-lipids with SIDD, SIRD and MOD, and (c) opposite effect of beta-cell GRS with SIDD and MARD, obesity GRS with MARD compared to Europeans. Genetic variants of fucosyltransferases were associated with T2D and MOD in Indians but not Europeans. Interpretation The similarities emphasise the applicability of some of the European-derived GRSs to T2D and its subgroups in India while the differences highlight the need for large-scale studies to identify aetiologies in diverse ancestries. The data provide robust evidence for genetically distinct aetiologies for the T2D subgroups and at least partly mirror those seen in Europeans. Funding Vetenskapsrådet, Diabetes Wellness, and Hjärt-Lungfonden (Sweden), DST (India), Wellcome Trust, Crafoord Foundation and Albert Påhlsson Foundation.
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Affiliation(s)
- Chittaranjan S. Yajnik
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, 411011, India
| | - Rucha Wagh
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, 411011, India
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed) University, Pune, 411021, India
| | - Pooja Kunte
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, 411011, India
- Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Campbelltown Campus, Sydney, 2560, NSW, Australia
| | - Olof Asplund
- Department of Clinical Sciences, Diabetes and Endocrinology, CRC, Lund University, Malmö SE-205 02, Sweden
| | - Emma Ahlqvist
- Department of Clinical Sciences, Diabetes and Endocrinology, CRC, Lund University, Malmö SE-205 02, Sweden
| | - Dattatrey Bhat
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, 411011, India
| | - Sharvari R. Shukla
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, 411011, India
- Symbiosis Statistical Institute, Symbiosis International University, Pune, 411005, India
| | - Rashmi B. Prasad
- Department of Clinical Sciences, Diabetes and Endocrinology, CRC, Lund University, Malmö SE-205 02, Sweden
- Institute for Molecular Medicine Finland FIMM, Helsinki University, 00290, Helsinki, Finland
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Shojima N, Yamauchi T. Progress in genetics of type 2 diabetes and diabetic complications. J Diabetes Investig 2023; 14:503-515. [PMID: 36639962 PMCID: PMC10034958 DOI: 10.1111/jdi.13970] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/12/2022] [Accepted: 12/15/2022] [Indexed: 01/15/2023] Open
Abstract
Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
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Affiliation(s)
- Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Narayan KMV, Varghese JS, Beyh YS, Bhattacharyya S, Khandelwal S, Krishnan GS, Siegel KR, Thomas T, Kurpad AV. A Strategic Research Framework for Defeating Diabetes in India: A 21st-Century Agenda. J Indian Inst Sci 2023; 103:1-22. [PMID: 37362852 PMCID: PMC10029804 DOI: 10.1007/s41745-022-00354-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/14/2022] [Indexed: 03/24/2023]
Abstract
Indian people are at high risk for type 2 diabetes (T2DM) even at younger ages and lower body weights. Already 74 million people in India have the disease, and the proportion of those with T2DM is increasing across all strata of society. Unique aspects, related to lower insulin secretion or function, and higher hepatic fat deposition, accompanied by the rise in overweight (related to lifestyle changes) may all be responsible for this unrelenting epidemic of T2DM. Yet, research to understand the causes, pathophysiology, phenotypes, prevention, treatment, and healthcare delivery of T2DM in India seriously lags behind. There are major opportunities for scientific discovery and technological innovation, which if tapped can generate solutions for T2DM relevant to the country's context and make leading contributions to global science. We analyze the situation of T2DM in India, and present a four-pillar (etiology, precision medicine, implementation research, and health policy) strategic research framework to tackle the challenge. We offer key research questions for each pillar, and identify infrastructure needs. India offers a fertile environment for shifting the paradigm from imprecise late-stage diabetes treatment toward early-stage precision prevention and care. Investing in and leveraging academic and technological infrastructures, across the disciplines of science, engineering, and medicine, can accelerate progress toward a diabetes-free nation.
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Affiliation(s)
- K. M. Venkat Narayan
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322 USA
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, GA 30322 USA
| | - Jithin Sam Varghese
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322 USA
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, GA 30322 USA
| | - Yara S. Beyh
- Laney Graduate School, Nutrition and Health Sciences Doctoral Program, Emory University, Atlanta, USA
| | | | | | - Gokul S. Krishnan
- Robert Bosch Centre for Data Science and Artificial Intelligence, Indian Institute of Technology Madras, Chennai, India
| | - Karen R. Siegel
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322 USA
- Emory Global Diabetes Research Center, Woodruff Health Sciences Center, Emory University, Atlanta, GA 30322 USA
| | - Tinku Thomas
- Department of Biostatistics, St. John’s Medical College, Bengaluru, India
| | - Anura V. Kurpad
- Department of Physiology, St. John’s Medical College, Bengaluru, India
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Azarova I, Polonikov A, Klyosova E. Molecular Genetics of Abnormal Redox Homeostasis in Type 2 Diabetes Mellitus. Int J Mol Sci 2023; 24:ijms24054738. [PMID: 36902173 PMCID: PMC10003739 DOI: 10.3390/ijms24054738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
Numerous studies have shown that oxidative stress resulting from an imbalance between the production of free radicals and their neutralization by antioxidant enzymes is one of the major pathological disorders underlying the development and progression of type 2 diabetes (T2D). The present review summarizes the current state of the art advances in understanding the role of abnormal redox homeostasis in the molecular mechanisms of T2D and provides comprehensive information on the characteristics and biological functions of antioxidant and oxidative enzymes, as well as discusses genetic studies conducted so far in order to investigate the contribution of polymorphisms in genes encoding redox state-regulating enzymes to the disease pathogenesis.
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Affiliation(s)
- Iuliia Azarova
- Department of Biological Chemistry, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
| | - Alexey Polonikov
- Laboratory of Statistical Genetics and Bioinformatics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
- Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, 305041 Kursk, Russia
- Correspondence:
| | - Elena Klyosova
- Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya Street, 305041 Kursk, Russia
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Timasheva Y, Balkhiyarova Z, Avzaletdinova D, Rassoleeva I, Morugova TV, Korytina G, Prokopenko I, Kochetova O. Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes. Int J Mol Sci 2023; 24:ijms24020984. [PMID: 36674502 PMCID: PMC9866792 DOI: 10.3390/ijms24020984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/12/2022] [Accepted: 12/22/2022] [Indexed: 01/07/2023] Open
Abstract
We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, PFDR = 3.40 × 10-5), CCR5 rs333 (OR = 1.99, PFDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, PFDR = 2.64 × 10-4), TCF7L2 rs114758349 (OR = 1.77, PFDR = 9.37 × 10-5), and CCL2 rs1024611 (OR = 1.38, PFDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.
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Affiliation(s)
- Yanina Timasheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, 450008 Ufa, Russia
- Correspondence:
| | - Zhanna Balkhiyarova
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Diana Avzaletdinova
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Irina Rassoleeva
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Tatiana V. Morugova
- Department of Endocrinology, Bashkir State Medical University, 450008 Ufa, Russia
| | - Gulnaz Korytina
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia
| | - Inga Prokopenko
- Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Olga Kochetova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia
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11
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Nadiger N, Anantharamu S, Priyanka CN, Vidal-Puig A, Mukhopadhyay A. Unique attributes of obesity in India: A narrative review. OBESITY MEDICINE 2022; 35:100454. [PMID: 38572212 PMCID: PMC7615800 DOI: 10.1016/j.obmed.2022.100454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
Obesity has become a burgeoning epidemic in India, even though the country is still dealing with undernutrition. As a significant determinant of the Metabolic Syndrome (MetS) and non-communicable diseases (NCDs) such as type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD), understanding the Indian context of the problem and learning how to deal with the obesity epidemic in this country has gained paramount importance. This narrative review points to the unique features of the obesity epidemic in India and its associated contributing factors, including the evolving nature of the Indian diet, the peculiarity of the increased adiposity at lower BMIs, unique obesity-associated genetic variants in Indians, the contribution of the gut microbiome, the impact of chronic inflammation and the role of ambient air pollution, and the contribution of decreased physical activity levels concerning the rapid urbanisation and the built environment. We believe that disseminating our insights into these unique features influencing the development of obesity in India will help increase global awareness and pave the way for better control and management of this obesity epidemic.
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Affiliation(s)
- Nikhil Nadiger
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, Koramangala, Bangalore, India
| | - Sahana Anantharamu
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, Koramangala, Bangalore, India
| | - CN Priyanka
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, Koramangala, Bangalore, India
| | - Antonio Vidal-Puig
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, MDU MRC, Addenbrooke's Hospital, Cambridge, UK
| | - Arpita Mukhopadhyay
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, Koramangala, Bangalore, India
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12
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Joseph A, Thirupathamma M, Mathews E, Alagu M. Genetics of type 2 diabetes mellitus in Indian and Global Population: A Review. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2022; 23:135. [PMID: 37192883 PMCID: PMC9438889 DOI: 10.1186/s43042-022-00346-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 08/21/2022] [Indexed: 11/10/2022] Open
Abstract
Background Non-communicable diseases such as cardiovascular diseases, respiratory diseases and diabetes contribute to the majority of deaths in India. Public health programmes on non-communicable diseases (NCD) prevention primarily target the behavioural risk factors of the population. Hereditary is known as a risk factor for most NCDs, specifically, type 2 diabetes mellitus (T2DM), and hence, understanding of the genetic markers of T2DM may facilitate prevention, early case detection and management. Main body We reviewed the studies that explored marker-trait association with type 2 diabetes mellitus globally, with emphasis on India. Globally, single nucleotide polymorphisms (SNPs) rs7903146 of Transcription Factor 7-like 2 (TCF7L2) gene was common, though there were alleles that were unique to specific populations. Within India, the state-wise data were also taken to foresee the distribution of risk/susceptible alleles. The findings from India showcased the common and unique alleles for each region. Conclusion Exploring the known and unknown genetic determinants might assist in risk prediction before the onset of behavioural risk factors and deploy prevention measures. Most studies were conducted in non-representative groups with inherent limitations such as smaller sample size or looking into only specific marker-trait associations. Genome-wide association studies using data from extensive prospective studies are required in highly prevalent regions worldwide. Further research is required to understand the singular effect and the interaction of genes in predicting diabetes mellitus and other comorbidities.
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Affiliation(s)
- Anjaly Joseph
- Department of Public Health and Community Medicine, Central University of Kerala, Kasaragod, Kerala 671320 India
| | - Maradana Thirupathamma
- Department of Genomic Science, Central University of Kerala, Kasaragod, Kerala 671320 India
| | - Elezebeth Mathews
- Department of Public Health and Community Medicine, Central University of Kerala, Kasaragod, Kerala 671320 India
| | - Manickavelu Alagu
- Department of Genomic Science, Central University of Kerala, Kasaragod, Kerala 671320 India
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13
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Pipal KV, Mamtani M, Patel AA, Jaiswal SG, Jaisinghani MT, Kulkarni H. Susceptibility Loci for Type 2 Diabetes in the Ethnically Endogamous Indian Sindhi Population: A Pooled Blood Genome-Wide Association Study. Genes (Basel) 2022; 13:genes13081298. [PMID: 35893037 PMCID: PMC9331904 DOI: 10.3390/genes13081298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/15/2022] [Accepted: 07/19/2022] [Indexed: 12/10/2022] Open
Abstract
Type 2 diabetes (T2D) is a complex metabolic derangement that has a strong genetic basis. There is substantial population-specificity in the association of genetic variants with T2D. The Indian urban Sindhi population is at a high risk of T2D. The genetic basis of T2D in this population is unknown. We interrogated 28 pooled whole blood genomes of 1402 participants from the Diabetes In Sindhi Families In Nagpur (DISFIN) study using Illumina’s Global Screening Array. From a total of 608,550 biallelic variants, 140 were significantly associated with T2D after adjusting for comorbidities, batch effects, pooling error, kinship status and pooling variation in a random effects multivariable logistic regression framework. Of the 102 well-characterized genes that these variants mapped onto, 70 genes have been previously reported to be associated with T2D to varying degrees with known functional relevance. Excluding open reading frames, intergenic non-coding elements and pseudogenes, our study identified 22 novel candidate genes in the Sindhi population studied. Our study thus points to the potential, interesting candidate genes associated with T2D in an ethnically endogamous population. These candidate genes need to be fully investigated in future studies.
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Affiliation(s)
- Kanchan V. Pipal
- Lata Medical Research Foundation, Nagpur 440002, India; (K.V.P.); (M.M.); (A.A.P.); (S.G.J.); (M.T.J.)
| | - Manju Mamtani
- Lata Medical Research Foundation, Nagpur 440002, India; (K.V.P.); (M.M.); (A.A.P.); (S.G.J.); (M.T.J.)
- M&H Research, LLC, San Antonio, TX 78249, USA
| | - Ashwini A. Patel
- Lata Medical Research Foundation, Nagpur 440002, India; (K.V.P.); (M.M.); (A.A.P.); (S.G.J.); (M.T.J.)
| | - Sujeet G. Jaiswal
- Lata Medical Research Foundation, Nagpur 440002, India; (K.V.P.); (M.M.); (A.A.P.); (S.G.J.); (M.T.J.)
| | - Manisha T. Jaisinghani
- Lata Medical Research Foundation, Nagpur 440002, India; (K.V.P.); (M.M.); (A.A.P.); (S.G.J.); (M.T.J.)
| | - Hemant Kulkarni
- Lata Medical Research Foundation, Nagpur 440002, India; (K.V.P.); (M.M.); (A.A.P.); (S.G.J.); (M.T.J.)
- M&H Research, LLC, San Antonio, TX 78249, USA
- Correspondence:
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14
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Kuhn T, Kaiser K, Lebek S, Altenhofen D, Knebel B, Herwig R, Rasche A, Pelligra A, Görigk S, Khuong JMA, Vogel H, Schürmann A, Blüher M, Chadt A, Al-Hasani H. Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene. Hum Mol Genet 2022; 31:4019-4033. [PMID: 35796564 DOI: 10.1093/hmg/ddac150] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 05/10/2022] [Accepted: 07/01/2022] [Indexed: 11/14/2022] Open
Abstract
To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue (gWAT), defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3 T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with BMI and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will shine light on the mechanism by which Sgcg may protect from the development of obesity.
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Affiliation(s)
- Tanja Kuhn
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Katharina Kaiser
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Sandra Lebek
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Delsi Altenhofen
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Birgit Knebel
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Ralf Herwig
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, D-14195, Germany
| | - Axel Rasche
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, D-14195, Germany
| | - Angela Pelligra
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Sarah Görigk
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Jenny Minh-An Khuong
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Heike Vogel
- German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany.,Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, D-14558, Germany
| | - Annette Schürmann
- German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany.,Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, D-14558, Germany
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, D-04103, Germany
| | - Alexandra Chadt
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Hadi Al-Hasani
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
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15
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Ke C, Narayan KMV, Chan JCN, Jha P, Shah BR. Pathophysiology, phenotypes and management of type 2 diabetes mellitus in Indian and Chinese populations. Nat Rev Endocrinol 2022; 18:413-432. [PMID: 35508700 PMCID: PMC9067000 DOI: 10.1038/s41574-022-00669-4] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/24/2022] [Indexed: 02/08/2023]
Abstract
Nearly half of all adults with type 2 diabetes mellitus (T2DM) live in India and China. These populations have an underlying predisposition to deficient insulin secretion, which has a key role in the pathogenesis of T2DM. Indian and Chinese people might be more susceptible to hepatic or skeletal muscle insulin resistance, respectively, than other populations, resulting in specific forms of insulin deficiency. Cluster-based phenotypic analyses demonstrate a higher frequency of severe insulin-deficient diabetes mellitus and younger ages at diagnosis, lower β-cell function, lower insulin resistance and lower BMI among Indian and Chinese people compared with European people. Individuals diagnosed earliest in life have the most aggressive course of disease and the highest risk of complications. These characteristics might contribute to distinctive responses to glucose-lowering medications. Incretin-based agents are particularly effective for lowering glucose levels in these populations; they enhance incretin-augmented insulin secretion and suppress glucagon secretion. Sodium-glucose cotransporter 2 inhibitors might also lower blood levels of glucose especially effectively among Asian people, while α-glucosidase inhibitors are better tolerated in east Asian populations versus other populations. Further research is needed to better characterize and address the pathophysiology and phenotypes of T2DM in Indian and Chinese populations, and to further develop individualized treatment strategies.
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Affiliation(s)
- Calvin Ke
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Department of Medicine, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada.
- Centre for Global Health Research, Unity Health Toronto, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China.
| | - K M Venkat Narayan
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Nutrition and Health Sciences Program, Graduate Division of Biological and Biomedical Sciences, Laney Graduate School, Emory University, Atlanta, GA, USA
- Department of Medicine, School of Medicine, Emory University, Atlanta, GA, USA
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- Asia Diabetes Foundation, Shatin, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Prabhat Jha
- Centre for Global Health Research, Unity Health Toronto, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Baiju R Shah
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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16
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Rout M, Lerner M, Blackett PR, Peyton MD, Stavrakis S, Sidorov E, Sanghera DK. Ethnic differences in ApoC-III concentration and the risk of cardiovascular disease: No evidence for the cardioprotective role of rare/loss of function APOC3 variants in non-Europeans. AMERICAN HEART JOURNAL PLUS : CARDIOLOGY RESEARCH AND PRACTICE 2022; 13:100128. [PMID: 35528316 PMCID: PMC9075110 DOI: 10.1016/j.ahjo.2022.100128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
BACKGROUND Hypertriglyceridemia is as an independent risk factor for cardiovascular disease (CVD). Apolipoprotein C-III (ApoC-III) is known to regulate triglyceride (TG) metabolism. However, the causal association between ApoC-III and CVD development is unclear. The objectives were to examine the impact of ApoC-III concentration on TG and lipoproteins and investigate the role of known rare loss-of-function APOC3 variants for modulating ApoC-III, TG concentrations and CVD risk in different ethnic groups. METHODS Plasma ApoC-III levels were measured in a multiethnic sample of 518 individuals comprising 271 Asian Indians (Sikhs), 87 Caucasians, 80 African Americans, and 80 Hispanics. RESULTS ApoC-III levels showed a robust association with TG in Asian Indians (r = 0.5, p = 1.1 × 10-23), Caucasians (r = 0.4, p = 7.2 × 10-4), and Hispanics (r = 0.9, p = 2.7x × 10-28). African Americans had lowest ApoC-III and TG concentrations and highest (44%) prevalence of coronary artery disease (CAD). ApoC-III levels correlated with fasting blood glucose (r = 0.25, p = 6.1 × 10-5) in Asian Indians and central adiposity in Hispanics (waist: r = 0.22, p = 0.05; waist-hip ratio: r = 0.24, p = 0.04). The carriers of rare variants IVS1-2G-A (rs373975305); A43T (rs147210663) and IVS3 + 1G-T (rs140621530) showed high TG but not low ApoC-III levels in Asian Indians and Caucasians. CONCLUSION These results highlight the challenges of generalizing antisense ApoC-III inhibition for treating atherosclerotic disease in dyslipidemia that may benefit only specific sub-populations. The observed ethnic differences in ApoC-III concentrations and CAD risk factors, emphasize in-depth genetic and metabolomics evaluations on diverse ancestries.
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Affiliation(s)
- Madhusmita Rout
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Megan Lerner
- Department of Surgery, Oklahoma University of Health Sciences Center, Oklahoma City, OK, USA
| | - Piers R. Blackett
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Marvin D. Peyton
- Department of Surgery, Oklahoma University of Health Sciences Center, Oklahoma City, OK, USA
| | - Stavros Stavrakis
- Department of Cardiology, Oklahoma University of Health Sciences Center, Oklahoma City, OK, USA
| | - Evgeny Sidorov
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S.L Young Blvd #2040, 73104 Oklahoma City, OK, USA
| | - Dharambir K. Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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17
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Venkatesan V, Lopez-Alvarenga JC, Arya R, Ramu D, Koshy T, Ravichandran U, Ponnala AR, Sharma SK, Lodha S, Sharma KK, Shaik MV, Resendez RG, Venugopal P, R P, Saju N, Ezeilo JA, Bejar C, Wander GS, Ralhan S, Singh JR, Mehra NK, Vadlamudi RR, Almeida M, Mummidi S, Natesan C, Blangero J, Medicherla KM, Thanikachalam S, Panchatcharam TS, Kandregula DK, Gupta R, Sanghera DK, Duggirala R, Paul SFD. Burden of Type 2 Diabetes and Associated Cardiometabolic Traits and Their Heritability Estimates in Endogamous Ethnic Groups of India: Findings From the INDIGENIUS Consortium. Front Endocrinol (Lausanne) 2022; 13:847692. [PMID: 35498404 PMCID: PMC9048207 DOI: 10.3389/fendo.2022.847692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 02/21/2022] [Indexed: 01/14/2023] Open
Abstract
To assess the burden of type 2 diabetes (T2D) and its genetic profile in endogamous populations of India given the paucity of data, we aimed to determine the prevalence of T2D and estimate its heritability using family-based cohorts from three distinct Endogamous Ethnic Groups (EEGs) representing Northern (Rajasthan [Agarwals: AG]) and Southern (Tamil Nadu [Chettiars: CH] and Andhra Pradesh [Reddys: RE]) states of India. For comparison, family-based data collected previously from another North Indian Punjabi Sikh (SI) EEG was used. In addition, we examined various T2D-related cardiometabolic traits and determined their heritabilities. These studies were conducted as part of the Indian Diabetes Genetic Studies in collaboration with US (INDIGENIUS) Consortium. The pedigree, demographic, phenotypic, covariate data and samples were collected from the CH, AG, and RE EEGs. The status of T2D was defined by ADA guidelines (fasting glucose ≥ 126 mg/dl or HbA1c ≥ 6.5% and/or use of diabetes medication/history). The prevalence of T2D in CH (N = 517, families = 21, mean age = 47y, mean BMI = 27), AG (N = 530, Families = 25, mean age = 43y, mean BMI = 27), and RE (N = 500, Families = 22, mean age = 46y, mean BMI = 27) was found to be 33%, 37%, and 36%, respectively, Also, the study participants from these EEGs were found to be at increased cardiometabolic risk (e.g., obesity and prediabetes). Similar characteristics for the SI EEG (N = 1,260, Families = 324, Age = 51y, BMI = 27, T2D = 75%) were obtained previously. We used the variance components approach to carry out genetic analyses after adjusting for covariate effects. The heritability (h2) estimates of T2D in the CH, RE, SI, and AG were found to be 30%, 46%, 54%, and 82% respectively, and statistically significant (P ≤ 0.05). Other T2D related traits (e.g., BMI, lipids, blood pressure) in AG, CH, and RE EEGs exhibited strong additive genetic influences (h2 range: 17% [triglycerides/AG and hs-CRP/RE] - 86% [glucose/non-T2D/AG]). Our findings highlight the high burden of T2D in Indian EEGs with significant and differential additive genetic influences on T2D and related traits.
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Affiliation(s)
- Vettriselvi Venkatesan
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | - Juan Carlos Lopez-Alvarenga
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Rector Arya
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Deepika Ramu
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | - Teena Koshy
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | - Umarani Ravichandran
- Department of Medicine, Rajah Muthiah Medical College Hospital, Annamalai University, Chidambaram, India
| | - Amaresh Reddy Ponnala
- Department of Endocrinology, Krishna Institute of Medical Sciences (KIMS) Hospital, Nellore, India
| | | | - Sailesh Lodha
- Departments of Preventive Cardiology, Internal Medicine and Endocrinology, Eternal Heart Care Centre and Research Institute, Mount Sinai New York Affiliate, Jaipur, India
| | - Krishna K. Sharma
- Department of Pharmacology, Lal Bahadur Shastri College of Pharmacy, Rajasthan University of Health Sciences, Jaipur, India
| | - Mahaboob Vali Shaik
- Department of Endocrinology, Narayana Medical College and Hospital, Nellore, India
| | - Roy G. Resendez
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Priyanka Venugopal
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | - Parthasarathy R
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | - Noelta Saju
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | - Juliet A. Ezeilo
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Cynthia Bejar
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Gurpreet S. Wander
- Hero Dayanand Medical College (DMC) Heart Institute, Dayanand Medical College and Hospital, Ludhaina, India
| | - Sarju Ralhan
- Hero Dayanand Medical College (DMC) Heart Institute, Dayanand Medical College and Hospital, Ludhaina, India
| | - Jai Rup Singh
- Honorary or Emeritus Faculty, Central University of Punjab, Bathinda, India
| | - Narinder K. Mehra
- Honorary or Emeritus Faculty, All India Institute of Medical Sciences and Research, New Delhi, India
| | | | - Marcio Almeida
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Srinivas Mummidi
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Chidambaram Natesan
- Department of Medicine, Rajah Muthiah Medical College Hospital, Annamalai University, Chidambaram, India
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | | | - Sadagopan Thanikachalam
- Department of Cardiology, Sri Ramachandra Medical College and Research Institute, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
| | | | | | - Rajeev Gupta
- Departments of Preventive Cardiology, Internal Medicine and Endocrinology, Eternal Heart Care Centre and Research Institute, Mount Sinai New York Affiliate, Jaipur, India
| | - Dharambir K. Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Solomon F. D. Paul
- Department of Human Genetics, Faculty of Biomedical Sciences and Technology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India
- *Correspondence: Solomon F. D. Paul,
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18
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Liu T, Li H, Conley YP, Primack BA, Wang J, Lo WJ, Li C. A Genome-Wide Association Study of Prediabetes Status Change. Front Endocrinol (Lausanne) 2022; 13:881633. [PMID: 35769078 PMCID: PMC9234217 DOI: 10.3389/fendo.2022.881633] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 04/29/2022] [Indexed: 11/13/2022] Open
Abstract
We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher's method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including SGCZ (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, HPSE2 (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, ADGRA1 (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, GLB1L3 (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and PCSK6 (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted.
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Affiliation(s)
- Tingting Liu
- College of Nursing, Florida State University, Tallahassee, FL, United States
| | - Hongjin Li
- College of Nursing, University of Illinois at Chicago, Chicago, IL, United States
| | - Yvette P. Conley
- School of Nursing, University of Pittsburgh, Pittsburgh, PA, United States
| | - Brian A. Primack
- College of Education and Health Professions, University of Arkansas, Fayetteville, AR, United States
| | - Jing Wang
- College of Nursing, Florida State University, Tallahassee, FL, United States
| | - Wen-Juo Lo
- College of Education and Health Professions, University of Arkansas, Fayetteville, AR, United States
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Tropical Medicine and Public Health, New Orleans, LA, United States
- *Correspondence: Changwei Li,
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19
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Benny P, Ahn HJ, Burlingame J, Lee MJ, Miller C, Chen J, Urschitz J. Genetic risk factors associated with gestational diabetes in a multi-ethnic population. PLoS One 2021; 16:e0261137. [PMID: 34928995 PMCID: PMC8687569 DOI: 10.1371/journal.pone.0261137] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 11/24/2021] [Indexed: 11/19/2022] Open
Abstract
AIMS Genome-wide association studies have shown an increased risk of type-2-diabetes (T2DM) in patients who carry single nucleotide polymorphisms in several genes. We investigated whether the same gene loci confer a risk for gestational diabetes mellitus (GDM) in women from Hawaii, and in particular, Pacific Islander and Filipino populations. METHODS Blood was collected from 291 women with GDM and 734 matched non-diabetic controls (Pacific Islanders: 71 GDM, 197 non-diabetic controls; Filipinos: 162 GDM, 395 controls; Japanese: 58 GDM, 142 controls). Maternal DNA was used to genotype and show allele frequencies of 25 different SNPs mapped to 18 different loci. RESULTS After adjusting for age, BMI, parity and gravidity by multivariable logistic regression, several SNPs showed significant associations with GDM and were ethnicity specific. In particular, SNPs rs1113132 (EXT2), rs1111875 (HHEX), rs2237892 (KCNQ1), rs2237895 (KCNQ1), rs10830963 (MTNR1B) and rs13266634 (SLC30A8) showed significant associations with GDM in Filipinos. For Japanese, SNPs rs4402960 (IGFBP2) and rs2237892 (KCNQ1) were significantly associated with GDM. For Pacific Islanders, SNPs rs10830963 (MTNR1B) and rs13266634 (SLC30A8) showed significant associations with GDM. Individually, none of the SNPs showed a consistent association with GDM across all three investigated ethnicities. CONCLUSION Several SNPs associated with T2DM are found to confer increased risk for GDM in a multiethnic cohort in Hawaii.
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Affiliation(s)
- Paula Benny
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Hyeong Jun Ahn
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Janet Burlingame
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Men-Jean Lee
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Corrie Miller
- Department of Obstetrics, Gynecology, and Women’s Health, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - John Chen
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
| | - Johann Urschitz
- Department of Anatomy, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, United States of America
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20
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Irgam K, Reddy BS, Hari SG, Banapuram S, Reddy BM. The genetic susceptibility profile of type 2 diabetes and reflection of its possible role related to reproductive dysfunctions in the southern Indian population of Hyderabad. BMC Med Genomics 2021; 14:272. [PMID: 34784930 PMCID: PMC8597259 DOI: 10.1186/s12920-021-01129-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 11/12/2021] [Indexed: 12/25/2022] Open
Abstract
Background The genetic association studies of type 2 diabetes mellitus (T2DM) hitherto undertaken among the Indian populations are grossly inadequate representation of the ethnic and geographic heterogeneity of the country. In view of this and due to the inconsistent nature of the results of genetic association studies, it would be prudent to undertake large scale studies in different regions of India considering wide spectrum of variants from the relevant pathophysiological pathways. Given the reproductive dysfunctions associated with T2DM, it would be also interesting to explore if some of the reproductive pathway genes are associated with T2DM. The present study is an attempt to examine these aspects in the southern Indian population of Hyderabad. Methods A prioritized panel of 92 SNPs from a large number of metabolic and reproductive pathway genes was genotyped on 500 cases and 500 controls, matched for ethnicity, age and BMI, using AGENA MassARRAYiPLEX™ platform. Results The allelic association results suggested 14 SNPs to be significantly associated with T2DM at P ≤ 0.05 and seven of those—rs2241766-G (ADIPOQ), rs6494730-T (FEM1B), rs1799817-A and rs2059806-T (INSR), rs11745088-C (FST), rs9939609-A and rs9940128-A (FTO)—remained highly significant even after correction for multiple testing. A great majority of the significant SNPs were risk in nature. The ROC analysis of the risk scores of the significant SNPs yielded an area under curve of 0.787, suggesting substantial power of our study to confer these genetic variants as predictors of risk for T2DM. Conclusions The associated SNPs of this study are known to be specifically related to insulin signaling, fatty acid metabolism and reproductive pathway genes and possibly suggesting the role of overlapping phenotypic features of insulin resistance, obesity and reproductive dysfunctions inherent in the development of diabetes. Large scale studies involving gender specific approach may be required in order to identify the precise nature of population and gender specific risk profiles for different populations, which might be somewhat distinct. Supplementary Information The online version contains supplementary material available at 10.1186/s12920-021-01129-0.
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Affiliation(s)
- Kumuda Irgam
- Department of Genetics and Biotechnology, Osmania University, Amberpet, Hyderabad, Telangana, 500007, India
| | - Battini Sriteja Reddy
- Dr Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Vijayawada, Andhra Pradesh, 521286, India
| | - Sai Gayathri Hari
- Department of Genetics and Biotechnology, Osmania University, Amberpet, Hyderabad, Telangana, 500007, India
| | - Swathi Banapuram
- Department of Genetics and Biotechnology, Osmania University, Amberpet, Hyderabad, Telangana, 500007, India
| | - Battini Mohan Reddy
- Department of Genetics and Biotechnology, Osmania University, Amberpet, Hyderabad, Telangana, 500007, India. .,Molecular Anthropology Laboratory, Indian Statistical Institute, Street No. 8, Habsiguda, Hyderabad, Telangana, 500007, India.
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21
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Goyal S, Tanigawa Y, Zhang W, Chai JF, Almeida M, Sim X, Lerner M, Chainakul J, Ramiu JG, Seraphin C, Apple B, Vaughan A, Muniu J, Peralta J, Lehman DM, Ralhan S, Wander GS, Singh JR, Mehra NK, Sidorov E, Peyton MD, Blackett PR, Curran JE, Tai ES, van Dam R, Cheng CY, Duggirala R, Blangero J, Chambers JC, Sabanayagam C, Kooner JS, Rivas MA, Aston CE, Sanghera DK. APOC3 genetic variation, serum triglycerides, and risk of coronary artery disease in Asian Indians, Europeans, and other ethnic groups. Lipids Health Dis 2021; 20:113. [PMID: 34548093 PMCID: PMC8456544 DOI: 10.1186/s12944-021-01531-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 08/25/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Hypertriglyceridemia has emerged as a critical coronary artery disease (CAD) risk factor. Rare loss-of-function (LoF) variants in apolipoprotein C-III have been reported to reduce triglycerides (TG) and are cardioprotective in American Indians and Europeans. However, there is a lack of data in other Europeans and non-Europeans. Also, whether genetically increased plasma TG due to ApoC-III is causally associated with increased CAD risk is still unclear and inconsistent. The objectives of this study were to verify the cardioprotective role of earlier reported six LoF variants of APOC3 in South Asians and other multi-ethnic cohorts and to evaluate the causal association of TG raising common variants for increasing CAD risk. METHODS We performed gene-centric and Mendelian randomization analyses and evaluated the role of genetic variation encompassing APOC3 for affecting circulating TG and the risk for developing CAD. RESULTS One rare LoF variant (rs138326449) with a 37% reduction in TG was associated with lowered risk for CAD in Europeans (p = 0.007), but we could not confirm this association in Asian Indians (p = 0.641). Our data could not validate the cardioprotective role of other five LoF variants analysed. A common variant rs5128 in the APOC3 was strongly associated with elevated TG levels showing a p-value 2.8 × 10- 424. Measures of plasma ApoC-III in a small subset of Sikhs revealed a 37% increase in ApoC-III concentrations among homozygous mutant carriers than the wild-type carriers of rs5128. A genetically instrumented per 1SD increment of plasma TG level of 15 mg/dL would cause a mild increase (3%) in the risk for CAD (p = 0.042). CONCLUSIONS Our results highlight the challenges of inclusion of rare variant information in clinical risk assessment and the generalizability of implementation of ApoC-III inhibition for treating atherosclerotic disease. More studies would be needed to confirm whether genetically raised TG and ApoC-III concentrations would increase CAD risk.
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Affiliation(s)
- Shiwali Goyal
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | - Yosuke Tanigawa
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UB1 3HW, UK
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore , 117549, Singapore
| | - Marcio Almeida
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore , 117549, Singapore
| | - Megan Lerner
- Department of Surgery, Oklahoma University of Health Sciences Center, Oklahoma City, OK, USA
| | - Juliane Chainakul
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S. L Young Blvd #2040, Oklahoma City, OK, 73104, USA
| | - Jonathan Garcia Ramiu
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S. L Young Blvd #2040, Oklahoma City, OK, 73104, USA
| | - Chanel Seraphin
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S. L Young Blvd #2040, Oklahoma City, OK, 73104, USA
| | - Blair Apple
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S. L Young Blvd #2040, Oklahoma City, OK, 73104, USA
| | - April Vaughan
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S. L Young Blvd #2040, Oklahoma City, OK, 73104, USA
| | - James Muniu
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | - Juan Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Donna M Lehman
- Departments of Medicine and Epidemiology and Biostatistics, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Sarju Ralhan
- Hero DMC Heart Institute, Ludhiana, Punjab, India
| | | | - Jai Rup Singh
- Central University of Punjab, Bathinda, Punjab, India
| | - Narinder K Mehra
- All India Institute of Medical Sciences and Research, New Delhi, India
| | - Evgeny Sidorov
- Department of Neurology, University of Oklahoma Health Sciences Center, 920 S. L Young Blvd #2040, Oklahoma City, OK, 73104, USA
| | - Marvin D Peyton
- Department of Surgery, Oklahoma University of Health Sciences Center, Oklahoma City, OK, USA
| | - Piers R Blackett
- Department of Pediatrics, Section of Endocrinology, Oklahoma University of Health Sciences Center, Oklahoma City, OK, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore , 117549, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University Health System, Singapore , 119228, Singapore
- Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Rob van Dam
- Department of Cardiology, Ealing Hospital, Middlesex, UB1 3HW, UK
- Department of Medicine, Yong Loo Lin School of Medicine, National University Health System, Singapore , 119228, Singapore
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ching-Yu Cheng
- Duke-NUS Medical School, Singapore, 169857, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
- National University of Singapore, Singapore, 119077, Singapore
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UB1 3HW, UK
- Lee Kong Chan School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - Charumathi Sabanayagam
- Duke-NUS Medical School, Singapore, 169857, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751, Singapore
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, Middlesex, UB1 3HW, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Manuel A Rivas
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA
| | - Christopher E Aston
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | - Dharambir K Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA.
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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22
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Bejar CA, Goyal S, Afzal S, Mangino M, Zhou A, van der Most PJ, Bao Y, Gupta V, Smart MC, Walia GK, Verweij N, Power C, Prabhakaran D, Singh JR, Mehra NK, Wander GS, Ralhan S, Kinra S, Kumari M, de Borst MH, Hyppönen E, Spector TD, Nordestgaard BG, Blackett PR, Sanghera DK. A Bidirectional Mendelian Randomization Study to evaluate the causal role of reduced blood vitamin D levels with type 2 diabetes risk in South Asians and Europeans. Nutr J 2021; 20:71. [PMID: 34315477 PMCID: PMC8314596 DOI: 10.1186/s12937-021-00725-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/28/2021] [Indexed: 12/24/2022] Open
Abstract
Context Multiple observational studies have reported an
inverse relationship between 25-hydroxyvitamin
D concentrations (25(OH)D) and type 2 diabetes (T2D). However, the results of
short- and long-term interventional trials concerning the relationship between 25(OH)D and T2D risk have been
inconsistent. Objectives and methods To evaluate the causal role of reduced blood
25(OH)D in T2D, here we have performed a bidirectional Mendelian randomization
study using 59,890 individuals (5,862 T2D cases and 54,028 controls) from
European and Asian Indian ancestries. We used six known SNPs, including three
T2D SNPs and three vitamin D pathway SNPs, as a genetic instrument to evaluate
the causality and direction of the association between T2D and circulating
25(OH)D concentration. Results Results of the combined meta-analysis of eight
participating studies showed that a composite score of three T2D SNPs would
significantly increase T2D risk by an odds ratio (OR) of 1.24, p = 1.82 × 10–32; Z score 11.86, which, however, had
no significant association with 25(OH)D status (Beta -0.02nmol/L ± SE
0.01nmol/L; p = 0.83; Z score -0.21). Likewise, the genetically
instrumented composite score of 25(OH)D lowering alleles significantly
decreased 25(OH)D concentrations (-2.1nmol/L ± SE 0.1nmol/L,
p = 7.92 × 10–78; Z score -18.68) but was not
associated with increased risk for T2D (OR 1.00, p = 0.12;
Z score 1.54). However, using 25(OH)D synthesis SNP (DHCR7; rs12785878) as an
individual genetic instrument, a per allele reduction of 25(OH)D concentration
(-4.2nmol/L ± SE 0.3nmol/L)
was predicted to increase T2D risk by 5%, p = 0.004;
Z score 2.84. This effect, however, was not seen in other 25(OH)D SNPs (GC
rs2282679, CYP2R1 rs12794714) when used as an individual instrument. Conclusion Our new data on this bidirectional Mendelian
randomization study suggests that genetically instrumented T2D risk does not
cause changes in 25(OH)D levels. However, genetically regulated 25(OH)D
deficiency due to vitamin D synthesis gene (DHCR7) may influence the risk of
T2D. Supplementary Information The online version contains supplementary material available at 10.1186/s12937-021-00725-1.
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Affiliation(s)
- Cynthia A Bejar
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, OK, 73104, OK City, USA
| | - Shiwali Goyal
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, OK, 73104, OK City, USA
| | - Shoaib Afzal
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK.,NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, SE1 9RT, London, UK
| | - Ang Zhou
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, NL, The Netherlands
| | - Yanchun Bao
- Department of Mathematical Sciences, University of Essex, Colchester, UK
| | - Vipin Gupta
- Department of Anthropology, University of Delhi, New Delhi, India
| | - Melissa C Smart
- Department of Mathematical Sciences, University of Essex, Colchester, UK
| | | | - Niek Verweij
- Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Christine Power
- Population, Policy and Practice, Institute of Child Health, University College London, London, WC1N 1EH, UK
| | | | - Jai Rup Singh
- Department of Human Genetics, Central University of Punjab, Bathinda, Punjab, India
| | - Narinder K Mehra
- Department of Transplant Immunology and Immunogenetics, All India Institute of Medical Sciences and Research, New Delhi, India
| | | | - Sarju Ralhan
- Department of Cardiology, Hero DMC Heart Institute, Ludhiana, India
| | - Sanjay Kinra
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Meena Kumari
- Department of Mathematical Sciences, University of Essex, Colchester, UK
| | - Martin H de Borst
- Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Elina Hyppönen
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia.,Population, Policy and Practice, Institute of Child Health, University College London, London, WC1N 1EH, UK.,Australian Centre for Precision Health, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Piers R Blackett
- Department of Pediatrics, Section of Pediatric Endocrinology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.,Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Dharambir K Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, OK, 73104, OK City, USA. .,Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. .,Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. .,Department of Physiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. .,Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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23
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Sabiha B, Bhatti A, Fan KH, John P, Aslam MM, Ali J, Feingold E, Demirci FY, Kamboh MI. Assessment of genetic risk of type 2 diabetes among Pakistanis based on GWAS-implicated loci. Gene 2021; 783:145563. [PMID: 33705809 DOI: 10.1016/j.gene.2021.145563] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 02/28/2021] [Accepted: 03/02/2021] [Indexed: 12/12/2022]
Abstract
Genome-wide association studies (GWAS) have identified multiple type 2 diabetes (T2D) loci, mostly among populations of European descent. There is a high prevalence of T2D among Pakistanis. Both genetic and environmental factors may be responsible for this high prevalence. In order to understand the shared genetic basis of T2D among Pakistanis and Europeans, we examined 77 genome-wide significant variants previously implicated among European populations. We genotyped 77 single-nucleotide polymorphisms (SNPs) by iPLEX® Gold or TaqMan® assays in a case-control sample of 1,683 individuals. Association analysis was performed using logistic regression. A total of 16 SNPs (TCF7L2/rs7903146, GLIS3/rs7041847, CHCHD9/rs13292136, PLEKHA1/rs2292626, FTO/rs9936385, CDKAL1/rs7756992, KCNJ11/rs5215, LOC105372155/rs12970134, KCNQ1/rs163182, CTRB1/rs7202877, ST6GAL1/rs16861329, ADAMTS9-AS2/rs6795735, LOC105370275/rs1359790, C5orf67/rs459193, ZBED3-AS1/rs6878122 and UBE2E2/rs7612463) showed statistically significant associations after controlling for the false discovery rate. While KCNQ1/rs163182 and ZBED3-AS1/rs6878122 showed opposite allelic effects, the remaining significant SNPs had the same allelic effects as reported previously. Our data indicate that a selected number of T2D loci previously identified among populations of European descent also affect the risk of T2D in the Pakistani population.
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Affiliation(s)
- Bibi Sabiha
- Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan
| | - Attya Bhatti
- Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan.
| | - Kang-Hsien Fan
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
| | - Peter John
- Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan
| | - Muhammad Muaaz Aslam
- Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
| | - Johar Ali
- Center for Genome Sciences, Rehman Medical College, Phase-V, Hayatabad, Peshawar, Khyber Pakhtunkhwa, Pakistan
| | - Eleanor Feingold
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
| | - F Yesim Demirci
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
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24
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Shahvazian E, Mahmoudi MB, Farashahi Yazd E, Gharibi S, Moghimi B, HosseinNia P, Mirzaei M. The KLF14 Variant is Associated with Type 2 Diabetes and HbA 1C Level. Biochem Genet 2021; 59:574-588. [PMID: 33389382 DOI: 10.1007/s10528-020-10015-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 10/30/2020] [Indexed: 12/20/2022]
Abstract
The purpose of this study was to scan variants in coding region of Krȕppel like factor14 (KLF14) locus and assess association related to type 2 diabetes (T2D) in Iranian population. We sequenced the coding region of KLF14 to scan variants in case-sibling study (92 individuals with T2D and 92 healthy older siblings). To confirm, we analyzed rs76603546 association with T2D in a larger unrelated case-control study by PCR-RFLP (475 cases and 512 controls). We analyzed the association of rs76603546 with HbA1C, BMI, fat mass, waist circumference, fasting glucose, cholesterol and HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) using one-way ANOVA analysis. Also, association of genotypes with T2D adjusted for confounding variables was analyzed using logistic regression. HaploReg v 4.1 was used to predict rs76603546 possible function. Sequencing results analysis revealed the association of C allele of rs76603546, synonymous variant C>T, [OR 2.10 (1.38-3.20), P value < 0.001] and CC genotype of rs76603546 [OR 4.3 (1.79-10.23), P value = 0.001] with susceptibility to T2D. PCR-Restriction Fragment Length Polymorphism (RFLP) results analysis confirmed the association of rs76603546 with T2D [C allele, OR 1.91 (1.59-2.29), P value = 0.002, CC genotype, OR 3.27 (2.26-4.73), P value = 0.002 and TC genotype, OR 1.74 (1.31-2.31), P value = 0.001]. The CC genotype of rs76603546 is associated with HbA1C level (P value < 0.001) and BMI (P value = 0.02). After adjustment with confounding variables, we observed association of CC genotype with T2D [OR 2.542 (1.25-3.77), P value = 0.03]. Among over 220 SNPs, rs76603546 was associated with T2D, HbA1C and BMI in our study.
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Affiliation(s)
- Ensieh Shahvazian
- Department of Genetics, Faculty of Medicine, International Campus, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Mohammad Bagher Mahmoudi
- Department of Genetics, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Ehsan Farashahi Yazd
- Department of Genetics, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. .,Stem Cell Biology Research Center, Yazd Reproductive Sciences Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. .,Yazd Reproductive Sciences Institute, Bu-Ali Ave., Timsar Fallahi St., Safaeieh, Yazd, Iran.
| | - Saba Gharibi
- Department of Genetics, Faculty of Medicine, International Campus, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Bahram Moghimi
- Department of Genetics, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | | | - Masoud Mirzaei
- Yazd Cardiovascular Research Centre, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
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25
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Goyal S, Sanghera DK. Genetic and Non-genetic Determinants of Cardiovascular Disease in South Asians. Curr Diabetes Rev 2021; 17:e011721190373. [PMID: 33461471 PMCID: PMC10370262 DOI: 10.2174/1573399817666210118103022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 11/18/2020] [Accepted: 11/20/2020] [Indexed: 01/09/2023]
Abstract
South Asians (SAs), people from the Indian subcontinent (e.g., India, Pakistan, Bangladesh, Sri Lanka, and Nepal) have a higher prevalence of cardiovascular disease (CVD) and suffer from a greater risk of CVD-associated mortality compared to other global populations. These problems are compounded by the alterations in lifestyles due to urbanization and changing cultural, social, economic, and political environments. Current methods of CV risk prediction are based on white populations that under-estimate the CVD risk in SAs. Prospective studies are required to obtain actual CVD morbidity/mortality rates so that comparisons between predicted CVD risk can be made with actual events. Overwhelming data support a strong influence of genetic factors. Genome-Wide Association Studies (GWAS) serve as a starting point for future genetic and functional studies since the mechanisms of action by which these associated loci influence CVD is still unclear. It is difficult to predict the potential implication of these findings in clinical settings. This review provides a systematic assessment of the risk factors, genetics, and environmental causes of CV health disparity in SAs, and highlights progress made in clinical and genomics discoveries in the rapidly evolving field, which has the potential to show clinical relevance in the near future.
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Affiliation(s)
- Shiwali Goyal
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Dharambir K Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
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26
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Cheng CF, Lin YJ, Lin MC, Liang WM, Chen CC, Chen CH, Wu JY, Lin TH, Liao CC, Huang SM, Hsieh AR, Tsai FJ. Genetic risk score constructed from common genetic variants is associated with cardiovascular disease risk in type 2 diabetes mellitus. J Gene Med 2020; 23:e3305. [PMID: 33350037 DOI: 10.1002/jgm.3305] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/21/2020] [Accepted: 12/08/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Patients with type 2 diabetes mellitus (T2DM) experience a two-fold increased risk of cardiovascular diseases. Genome-wide association studies (GWAS) have identified T2DM susceptibility genetic variants. Interestingly, the genetic variants associated with cardiovascular disease risk in T2DM Han Chinese remain to be elucidated. The present study aimed to investigate the genetic variants associated with cardiovascular disease risk in T2DM. METHODS We performed bootstrapping, GWAS and an investigation of genetic variants associated with cardiovascular disease risk in a discovery T2DM cohort and in a replication cohort. The discovery cohort included 326 cardiovascular disease patients and 1209 noncardiovascular disease patients. The replication cohort included 68 cardiovascular disease patients and 317 noncardiovascular disease patients. The main outcome measures were genetic variants for genetic risk score (GRS) in cardiovascular disease risk in T2DM. RESULTS In total, 35 genetic variants were associated with cardiovascular disease risk. A GRS was generated by combining risk alleles from these variants weighted by their estimated effect sizes (log odds ratio [OR]). T2DM patients with weighted GRS ≥ 12.63 had an approximately 15-fold increase in cardiovascular disease risk (odds ratio = 15.67, 95% confidence interval [CI] = 10.33-24.00) compared to patients with weighted GRS < 10.39. With the addition of weighted GRS, receiver-operating characteristic curves showed that area under the curve with conventional risk factors was improved from 0.719 (95% CI = 0.689-0.750) to 0.888 (95% CI = 0.866-0.910). CONCLUSIONS These 35 genetic variants are associated with cardiovascular disease risk in T2DM, alone and cumulatively. T2DM patients with higher levels of weighted genetic risk score have higher cardiovascular disease risks.
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Affiliation(s)
- Chi-Fung Cheng
- Graduate Institute of Biostatistics, School of Public Health, China Medical University, Taichung, Taiwan.,Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Ying-Ju Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.,School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Mei-Chen Lin
- Graduate Institute of Biostatistics, School of Public Health, China Medical University, Taichung, Taiwan
| | - Wen-Miin Liang
- Graduate Institute of Biostatistics, School of Public Health, China Medical University, Taichung, Taiwan
| | - Ching-Chu Chen
- Division of Endocrinology and Metabolism, Department of Medicine, China Medical University Hospital, Taichung, Taiwan
| | - Chien-Hsiun Chen
- School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Institute of Biomedical Sciences, Taipei, Taiwan
| | - Jer-Yuarn Wu
- School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Institute of Biomedical Sciences, Taipei, Taiwan
| | - Ting-Hsu Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chiu-Chu Liao
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Shao-Mei Huang
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Ai-Ru Hsieh
- Department of Statistics, Tamkang University, New Taipei, Taiwan
| | - Fuu-Jen Tsai
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.,School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan
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27
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Song C, Ding C, Yuan F, Feng G, Ma Y, Liu A. Ten SNPs May Affect Type 2 Diabetes Risk in Interaction with Prenatal Exposure to Chinese Famine. Nutrients 2020; 12:E3880. [PMID: 33353041 PMCID: PMC7766924 DOI: 10.3390/nu12123880] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/03/2020] [Accepted: 12/14/2020] [Indexed: 12/01/2022] Open
Abstract
Increasing studies have demonstrated that gene and famine may interact on type 2 diabetes risk. The data derived from the cross-sectional 2010-2012 China National Nutrition and Health Survey (CNNHS) was examined to explore whether gene and famine interacted to influence type 2 diabetes risk. In total, 2216 subjects were involved. The subjects born in 1960 and 1961 were selected as the famine-exposed group, whereas subjects born in 1963 were selected as the unexposed group. A Mass Array system was used to detect the genotypes of 50 related single-nucleotide polymorphisms (SNPs). Interactions were found between prenatal exposure to famine and ten SNPs (rs10401969, rs10886471, rs10946398, rs1470579, rs2796441, rs340874, rs3794991, rs5015480, rs7961581, and rs9470794) on type 2 diabetes risk after adjustments. The stratified results showed that famine exposure exacerbated the effect of CILP2-rs10401969 to fasting serum insulin (FINS), GRK5-rs10886471 to fasting plasma glucose (FPG) and FINS, IGF2BP2-rs1470579 to FINS, TLE1-rs2796441 to impaired fasting glucose (IFG), PROX1-rs340874 to impaired glucose tolerance (IGT), GATAD2A-rs3794991 to FINS, TSPAN8/LGR5-rs7961581 to FPG, and ZFAND3-rs9470794 to IGT and FINS. Famine exposure weakened the effect of CDKAL1-rs10946398 to type 2 diabetes. Famine exposure weakened the effect of HHEX-rs5015480 to IFG, but exacerbated the effect of HHEX-rs5015480 to FINS. The present study suggests that ten SNPs may affect type 2 diabetes risk in interaction with prenatal exposure to Chinese famine.
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Affiliation(s)
| | | | | | | | | | - Ailing Liu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China; (C.S.); (C.D.); (F.Y.); (G.F.); (Y.M.)
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28
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El Bitar F, Al Sudairy N, Qadi N, Al Rajeh S, Alghamdi F, Al Amari H, Al Dawsari G, Alsubaie S, Al Sudairi M, Abdulaziz S, Al Tassan N. A Comprehensive Analysis of Unique and Recurrent Copy Number Variations in Alzheimer's Disease and its Related Disorders. Curr Alzheimer Res 2020; 17:926-938. [PMID: 33256577 DOI: 10.2174/1567205017666201130111424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 08/20/2020] [Accepted: 10/29/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Copy number variations (CNVs) play an important role in the genetic etiology of various neurological disorders, including Alzheimer's disease (AD). Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) were shown to have share mechanisms and signaling pathways with AD. OBJECTIVE We aimed to assess CNVs regions that may harbor genes contributing to AD, T2DM, and MDD in 67 Saudi familial and sporadic AD patients, with no alterations in the known genes of AD and genotyped previously for APOE. METHODS DNA was analyzed using the CytoScan-HD array. Two layers of filtering criteria were applied. All the identified CNVs were checked in the Database of Genomic Variants (DGV). RESULTS A total of 1086 CNVs (565 gains and 521 losses) were identified in our study. We found 73 CNVs harboring genes that may be associated with AD, T2DM or MDD. Nineteen CNVs were novel. Most importantly, 42 CNVs were unique in our studied cohort existing only in one patient. Two large gains on chromosomes 1 and 13 harbored genes implicated in the studied disorders. We identified CNVs in genes that encode proteins involved in the metabolism of amyloid-β peptide (AGRN, APBA2, CR1, CR2, IGF2R, KIAA0125, MBP, RER1, RTN4R, VDR and WISPI) or Tau proteins (CACNAIC, CELF2, DUSP22, HTRA1 and SLC2A14). CONCLUSION The present work provided information on the presence of CNVs related to AD, T2DM, and MDD in Saudi Alzheimer's patients.
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Affiliation(s)
- Fadia El Bitar
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Nourah Al Sudairy
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Najeeb Qadi
- Department of Neurosciences, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | | | - Fatimah Alghamdi
- Institute of Biology and Environmental Research, National Center for Biotechnology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Hala Al Amari
- Institute of Biology and Environmental Research, National Center for Biotechnology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Ghadeer Al Dawsari
- Institute of Biology and Environmental Research, National Center for Genomics Technology, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Sahar Alsubaie
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Mishael Al Sudairi
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Sara Abdulaziz
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Nada Al Tassan
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
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29
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Identification of the potential type 2 diabetes susceptibility genetic elements in South Asian populations. Meta Gene 2020. [DOI: 10.1016/j.mgene.2020.100771] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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30
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Samaha G, Wade CM, Beatty J, Lyons LA, Fleeman LM, Haase B. Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat (Felis catus). Sci Rep 2020; 10:19194. [PMID: 33154479 PMCID: PMC7644637 DOI: 10.1038/s41598-020-76166-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 10/22/2020] [Indexed: 12/30/2022] Open
Abstract
Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline SNV array and whole genome sequence data to undertake a genome wide-association study and runs of homozygosity analysis, of a case–control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, implicated in diabetes mellitus and lipid dysregulation. Mapping this condition in Burmese cats has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat.
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Affiliation(s)
- Georgina Samaha
- Faculty of Science, Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, Australia.
| | - Claire M Wade
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Julia Beatty
- Faculty of Science, Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, Australia.,Department of Infectious Diseases and Public Health, City University of Hong Kong, Kowloon, Hong Kong SAR, People's Republic of China
| | - Leslie A Lyons
- Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA
| | | | - Bianca Haase
- Faculty of Science, Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, Australia
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31
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Identification of cardiovascular health gene variants related to longevity in a Chinese population. Aging (Albany NY) 2020; 12:16775-16802. [PMID: 32897244 PMCID: PMC7521493 DOI: 10.18632/aging.103396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Accepted: 05/25/2020] [Indexed: 01/24/2023]
Abstract
Cardiovascular disease (CVD) is one of the most important causes of human death, but no attention has been paid to cardiovascular health genes related to healthy longevity. Therefore, we developed a cohort study to explore such genes in healthy, long-lived Chinese subjects. A total of 13275 healthy elderly people were enrolled, including 5107 healthy long-lived individuals and 8168 age-matched control individuals with low CVD risk. Using a combination of whole-exome sequencing (WES) and genome-wide association studies (GWAS), we identified 2 genetic variants (TFPI rs7586970 T, p=0.013, OR=1.100. ADAMTS7 rs3825807 A, p=0.017, OR=1.198) associated with healthy lipid metabolism and longevity. Furthermore, we showed that an interaction among TFPI rs7586970, ADAMTS7 rs3825807 and APOE ɛ3 maintained normal blood lipid levels in centenarians by stratified analysis of CVD risk factors. Finally, through biological function analysis, we revealed clues regarding the mechanism of factor related to cardiovascular health (FCH) such as lipids and longevity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the two variants above may be associated with longevity via FCH lipid metabolism pathways. From a meta-analysis of venous thrombosis patients, we unexpectedly found that rs7586970 T is associated with both longevity and protection against vascular disease.
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32
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Nikpay M, Lau P, Soubeyrand S, Whytock KL, Beehler K, Pileggi C, Ghosh S, Harper ME, Dent R, McPherson R. SGCG rs679482 Associates With Weight Loss Success in Response to an Intensively Supervised Outpatient Program. Diabetes 2020; 69:2017-2026. [PMID: 32527767 DOI: 10.2337/db20-0219] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 06/07/2020] [Indexed: 02/07/2023]
Abstract
Weight loss in response to energy restriction is highly variable, and identification of genetic contributors can provide insights into underlying biology. Leveraging 1000 Genomes imputed genotypes, we carried out genome-wide association study (GWAS) analysis in 551 unrelated obese subjects of European ancestry who participated in an intensively supervised weight loss program with replication of promising signals in an independent sample of 1,331 obese subjects who completed the program at a later date. By single nucleotide polymorphism-based and sib-pair analysis, we show that that weight loss is a heritable trait, with estimated heritability (h 2 = 0.49) within the range reported for obesity. We find rs679482, intronic to SGCG (sarcoglycan γ), highly expressed in skeletal muscle, to concordantly associate with weight loss in discovery and replication samples reaching GWAS significance in the combined meta-analysis (β = -0.35, P = 1.7 × 10-12). Located in a region of open chromatin, rs679482 is predicted to bind DMRT2, and allele-specific transcription factor binding analysis indicates preferential binding of DMRT2 to rs679482-A. Concordantly, rs679482-A impairs native repressor activity and increases basal and DMRT2-mediated enhancer activity. These findings confirm that weight loss is a heritable trait and provide evidence by which a novel variant in SGCG, rs679482, leads to impaired diet response.
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Affiliation(s)
- Majid Nikpay
- Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Canada
| | - Paulina Lau
- Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, Canada
| | | | - Katey L Whytock
- Translational Research Institute for Metabolism and Diabetes, AdventHealth, Orlando, FL
| | - Kaitlyn Beehler
- Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, Canada
| | - Chantal Pileggi
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada
| | - Sujoy Ghosh
- Duke-NUS Medical School, Singapore, Singapore
| | - Mary-Ellen Harper
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada
| | - Robert Dent
- Weight Management Clinic, The Ottawa Hospital, Ottawa, Canada
| | - Ruth McPherson
- Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Canada
- Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, Canada
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Canada
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33
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Fu D, Zhong Z, Shi D, Peng Y, Li B, Wang D, Guo L, Li Z, Mao H, Yu X, Li M. ST6GAL1 polymorphisms influence susceptibility and progression of IgA nephropathy in a Chinese Han population. Immunobiology 2020; 225:151973. [PMID: 32747022 DOI: 10.1016/j.imbio.2020.151973] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 05/19/2020] [Accepted: 06/03/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND ST6GAL1 has been identified as a novel susceptibility gene for IgA nephropathy (IgAN) in a previous genome-wide association study. The present study is aimed at exploring whether the genetic polymorphisms of ST6GAL1 gene correlate with IgAN susceptibility, clinical phenotypes and progression in a Chinese Han population. METHODS Twenty-six single nucleotide polymorphisms (SNPs) of ST6GAL1 were genotyped in 1000 biopsy-proven IgAN patients and 1000 control subjects of Chinese Han population using Sequenom MassARRAY iPLEX. A logistic regression analysis with age and sex as covariates was performed to evaluate the effects of ST6GAL1 gene polymorphisms on IgAN susceptibility. Kaplan-Meier method and Cox proportional hazard models were applied to analyze the associations between genetic variants and renal survival. RESULTS We found that rs7634389 (OR = 1.24, 95 % CI = 1.02-1.50, pdominant = 0.034) and rs6784233 (OR = 1.23, 95 % CI = 1.05-1.45, padditive = 0.013; OR = 1.28, 95 % CI = 1.05-1.55, pdominant = 0.014) were associated with susceptibility of IgAN. In addition, rs7634389 was correlated with hyperuricemia (OR = 1.27, p = 0.012) and segmental glomerulosclerosis (OR = 1.21, p = 0.047) in IgAN patients. Furthermore, rs7634389 was independently associated with renal survival after adjustments for multiple confounders (hazard ratio [HR] = 0.51, 95 % CI = 0.33-0.78, p = 0.002). Haplotype analysis for ST6GAL1 polymorphisms confirmed their associations with the susceptibility to IgAN. CONCLUSIONS Our research suggested that ST6GAL1 gene polymorphisms were implicated in IgAN susceptibility and clinical outcome in a Chinese Han population.
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Affiliation(s)
- Dongying Fu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Zhong Zhong
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Dianchun Shi
- Department of Nephrology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510080, China
| | - Yuan Peng
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Bin Li
- Clinical Trials Unit, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Dan Wang
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Lin Guo
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Zhijian Li
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Haiping Mao
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China
| | - Xueqing Yu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China; Department of Nephrology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510080, China
| | - Ming Li
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China; Key Laboratory of Nephrology, National Health Commission and Guangdong Province, Guangzhou, Guangdong, 510080, China.
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34
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Sapkota BR, Sanghera DK. A rare missense variant in the milk fat globule-EGF factor 8 (MFGE8) increases T2DM susceptibility and cardiovascular disease risk with population-specific effects. Acta Diabetol 2020; 57:733-741. [PMID: 32025861 PMCID: PMC10502938 DOI: 10.1007/s00592-019-01463-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 11/28/2019] [Indexed: 12/26/2022]
Abstract
AIMS The milk fat globule-epidermal growth factor 8 (MFGE8), also called lactadherin, is an integrin ligand and a known mediator of inflammation and atherosclerosis in T2DM in studies using animal models. However, its role in the pathophysiology of human T2DM, obesity, and cardiovascular disease has been poorly explored. Aim of this study was to investigate the role of a missense variant (rs371227978 C/T: Arg148His) in the MFGE8 gene identified through exome sequencing for its association with T2DM and cardiometabolic traits. METHODS Exome-wide sequencing was performed using DNA samples from 68 Sikh individuals from multi-generation pedigrees affected with diabetes on Illumina's GAIIx using "SureSelect Human All Exon" panels. We further replicated this variant by de novo genotyping in a total of 4242 individuals of the Asian Indian Diabetic Heart Study/Sikh Diabetes Study using custom TaqMan genotyping assay. We also measured circulating concentrations of Mfge8 using frozen serum aliquots by enzyme-linked immunosorbent assay. RESULTS Overall, only 1.78% of 4242 individuals were carriers of this variant with MAF being 0.009. Except for the significant correlation of this variant with T2DM and triglycerides, no other quantitative risk phenotype was significant. The minor per allele-associated increased risk for T2DM showed odds ratio of 1.95 (95% CI 1.18-3.23; p = 0.008) in unadjusted model and was 1.73 (95% CI 1.02-2.93; p = 0.043) after adjusting for the age, gender, and BMI. However, there was a strong correlation between serum Mfge8 concentrations with T2DM, (r2 = 0.38; p = 0.001), fasting glucose (r2= 0.36; p = 0.002), and triglycerides (r2 = 0.33; p = 0.005). Our data revealed a significant dose-related increase in MFGE8 genotypes for affecting serum Mfge8 (p = 2.1 × 10-3) and triglyceride concentrations (p = 3.2 × 10-3). For a per risk allele-associated increase of 4.74 ng/ml ± SD of 1.62 ng/ml of the Mfge8 concentration was found to increase T2DM risk to 1.7 fold (95% CI from 1 to 3 fold). CONCLUSIONS Here, we report for the first time a novel population-specific rare variant in the MFGE8 gene linked with the increased Mfge8 concentrations and the risk for developing T2DM and cardiovascular risk factors in a population of Punjabi Sikhs from India. In view of a strong evidence from animal studies supporting the role of Mfge8 in obesity, insulin resistance, and the development of atherosclerosis in T2DM, our findings are important and timely. If validated in a large independent dataset, early screening of Mfge8 in blood levels may especially benefit those patients with genetically elevated Mfge8 levels to preventing or reducing the risk of T2DM and cardiovascular disease.
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Affiliation(s)
- Bishwa R Sapkota
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | - Dharambir K Sanghera
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA.
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Genome-wide meta-analysis associates GPSM1 with type 2 diabetes, a plausible gene involved in skeletal muscle function. J Hum Genet 2020; 65:411-420. [PMID: 31959871 DOI: 10.1038/s10038-019-0720-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 12/20/2019] [Accepted: 12/23/2019] [Indexed: 12/21/2022]
Abstract
Genome-wide association studies (GWASs) have identified many genetic variations associated with type 2 diabetes mellitus (T2DM) in Asians, but understanding the functional genetic variants that influence traits is often a complex process. In this study, fine mapping and other analytical strategies were performed to investigate the effects of G protein signaling modulator 1 (GPSM1) on insulin resistance in skeletal muscle. A total of 128 single-nucleotide polymorphisms (SNPs) within GPSM1 were analysed in 21,897 T2DM cases and 32,710 healthy controls from seven GWASs. The SNP rs28539249 in intron 9 of GPSM1 showed a nominally significant association with T2DM in Asians (OR = 1.07, 95% CI = 1.04-1.10, P < 10-4). The GPSM1 mRNA was increased in skeletal muscle and correlated with T2DM traits across obese mice model. An eQTL for the cis-acting regulation of GPSM1 expression in human skeletal muscle was identified for rs28539249, and the increased GPSM1 expression related with T2DM traits within GEO datasets. Another independent Asian cohort showed that rs28539249 is associated with the skeletal muscle expression of CACFD1, GTF3C5, SARDH, and FAM163B genes, which are functionally enriched for endoplasmic reticulum stress (ERS) and unfolded protein response (UPR) pathways. Moreover, rs28539249 locus was predicted to disrupt regulatory regions in human skeletal muscle with enriched epigenetic marks and binding affinity for CTCF. Supershift EMSA assays followed luciferase assays demonstrated the CTCF specifically binding to rs28539249-C allele leading to decreased transcriptional activity. Thus, the post-GWAS annotation confirmed the Asian-specific association of genetic variant in GPSM1 with T2DM, suggesting a role for the variant in the regulation in skeletal muscle.
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Yip L, Fuhlbrigge R, Alkhataybeh R, Fathman CG. Gene Expression Analysis of the Pre-Diabetic Pancreas to Identify Pathogenic Mechanisms and Biomarkers of Type 1 Diabetes. Front Endocrinol (Lausanne) 2020; 11:609271. [PMID: 33424774 PMCID: PMC7793767 DOI: 10.3389/fendo.2020.609271] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 11/16/2020] [Indexed: 12/28/2022] Open
Abstract
Type 1 Diabetes (T1D) occurs as a result of the autoimmune destruction of pancreatic β-cells by self-reactive T cells. The etiology of this disease is complex and difficult to study due to a lack of disease-relevant tissues from pre-diabetic individuals. In this study, we performed gene expression analysis on human pancreas tissues obtained from the Network of Pancreatic Organ Donors with Diabetes (nPOD), and showed that 155 genes were differentially expressed by ≥2-fold in the pancreata of autoantibody-positive (AA+) at-risk individuals compared to healthy controls. Only 48 of these genes remained changed by ≥2-fold in the pancreata of established T1D patients. Pathway analysis of these genes showed a significant association with various immune pathways. We were able to validate the differential expression of eight disease-relevant genes by QPCR analysis: A significant upregulation of CADM2, and downregulation of TRPM5, CRH, PDK4, ANGPL4, CLEC4D, RSG16, and FCGR2B was confirmed in the pancreata of AA+ individuals versus controls. Studies have already implicated FCGR2B in the pathogenesis of disease in non-obese diabetic (NOD) mice. Here we showed that CADM2, TRPM5, PDK4, and ANGPL4 were similarly changed in the pancreata of pre-diabetic 12-week-old NOD mice compared to NOD.B10 controls, suggesting a possible role for these genes in the pathogenesis of both T1D and NOD disease. The loss of the leukocyte-specific gene, FCGR2B, in the pancreata of AA+ individuals, is particularly interesting, as it may serve as a potential whole blood biomarker of disease progression. To test this, we quantified FCGR2B expression in peripheral blood samples of T1D patients, and AA+ and AA- first-degree relatives of T1D patients enrolled in the TrialNet Pathway to Prevention study. We showed that FCGR2B was significantly reduced in the peripheral blood of AA+ individuals compared to AA- controls. Together, these findings demonstrate that gene expression analysis of pancreatic tissue and peripheral blood samples can be used to identify disease-relevant genes and pathways and potential biomarkers of disease progression in T1D.
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37
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Sarkar P, Bhowmick A, Baruah MP, Bhattacharjee S, Subhadra P, Banu S. Determination of individual type 2 diabetes risk profile in the North East Indian population & its association with anthropometric parameters. Indian J Med Res 2019; 150:390-398. [PMID: 31823921 PMCID: PMC6902361 DOI: 10.4103/ijmr.ijmr_888_17] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Background & objectives: Diabetes genomics research has illuminated single nucleotide polymorphism (SNP) in several genes including, fat mass and obesity associated (FTO) (rs9939609 and rs9926289), potassium voltage-gated channel subfamily J member 11 (rs5219), SLC30A8 (rs13266634) and peroxisome proliferator-activated receptor gamma 2 (rs1805192). The present study was conducted to investigate the involvement of these polymorphisms in conferring susceptibility to type 2 diabetes (T2D) in the North East Indian population, and also to establish their association with anthropometric parameters. Methods: DNA was extracted from blood samples of 155 patients with T2D and 100 controls. Genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism and DNA sequencing. To confirm the association between the inheritance of SNP and T2D development, logistic regression analysis was performed. Results: For the rs9939609 variant (FTO), the dominant model AA/(AT+TT) revealed significant association with T2D [odds ratio (OR)=2.03, P=0.021], but was non-significant post correction for multiple testing (P=0.002). For the rs13266634 variant (SLC30A8), there was considerable but non-significant difference in the distribution pattern of genotypic polymorphisms between the patients and the controls (P=0.004). Significant association was observed in case of the recessive model (CC+CT)/TT (OR=4.56 P=0.001), after adjusting for age, gender and body mass index. In addition, a significant association (P=0.001) of low-density lipoprotein (mg/dl) could be established with the FTO (rs9926289) polymorphism assuming dominant model. Interpretation & conclusions: The current study demonstrated a modest but significant effect of SLC30A8 (rs13266634) polymorphisms on T2D predisposition. Considering the burgeoning prevalence of T2D in the Indian population, the contribution of these genetic variants studied, to the ever-increasing number of T2D cases, appears to be relatively low. This study may serve as a foundation for performing future genome-wide association studies (GWAS) involving larger populations.
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Affiliation(s)
- Purabi Sarkar
- Department of Bioengineering & Technology, Gauhati University, Guwahati, Assam, India
| | - Ananya Bhowmick
- Department of Bioengineering & Technology, Gauhati University, Guwahati, Assam, India
| | - Manash P Baruah
- Department of Endocrinology, Excelcare Hospitals, Guwahati, Assam, India
| | | | - Poornima Subhadra
- Department of Genetics & Molecular Medicine, Kamineni Academy of Medical Sciences & Research Center, Hyderabad, Telangana, India
| | - Sofia Banu
- Department of Bioengineering & Technology, Gauhati University, Guwahati, Assam, India
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Jamaleddine M, Harris MS, Liyanage L, Cook GA. Expression, purification, and structural analysis of the full-length human integral membrane protein γ-sarcoglycan. Protein Expr Purif 2019; 167:105525. [PMID: 31682967 DOI: 10.1016/j.pep.2019.105525] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 10/25/2019] [Accepted: 10/29/2019] [Indexed: 11/26/2022]
Abstract
Mutation of the gene encoding γ-sarcoglycan (SGCG), an integral membrane protein responsible for maintaining the integrity of the muscle cell sarcolemma, results in Limb-Girdle Muscular Dystrophy (LGMD), a congenital disease with no current treatment options. This member of the sarcoglycan glycoprotein family is a vital component of the Dystrophin Complex, which together facilitate normal muscle function. However, very little is known about the structure and dynamics of these proteins, and of membrane glycoproteins in general. This is due to a number of factors, including their complexity, heterogeneity and highly-specific native environments. The expression, purification, and structural study of membrane proteins is further impeded by their hydrophobic nature and consequent propensity to aggregate in aqueous solutions. Here, we report the first successful expression and purification of milligram quantities of full-length recombinant SGCG, utilizing fusion protein-guided overexpression to inclusion bodies in Escherichia coli. Purification of SGCG from the fusion protein, TrpΔLE, was facilitated using chemical cleavage. Cleavage products were then isolated by size-exclusion chromatography. Successful purification of the protein was confirmed using SDS-PAGE and mass spectroscopy. Finally, solution nuclear magnetic resonance spectroscopy of uniformly 15N-labeled SGCG in detergent environments was performed, yielding the first spectra of the full-length membrane glycoprotein, SGCG. These results represent the initial structural studies of SGCG, laying the foundation for further investigation on the interaction and dynamics of other integral membrane proteins. More specifically, this data allows for opportunities in the future for enhanced treatment modalities and cures for LGMD.
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Affiliation(s)
- Michael Jamaleddine
- Oklahoma State University, Department of Chemistry, 107 Physical Science, Stillwater, OK, 74074, USA
| | - Michael S Harris
- Oklahoma State University, Department of Chemistry, 107 Physical Science, Stillwater, OK, 74074, USA
| | - Leshani Liyanage
- Oklahoma State University, Department of Chemistry, 107 Physical Science, Stillwater, OK, 74074, USA
| | - Gabriel A Cook
- Oklahoma State University, Department of Chemistry, 107 Physical Science, Stillwater, OK, 74074, USA.
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Song C, Wang M, Fang H, Gong W, Mao D, Ding C, Fu Q, Feng G, Chen Z, Ma Y, Yao Y, Liu A. Effects of variants of 50 genes on diabetes risk among the Chinese population born in the early 1960s. J Diabetes 2019; 11:857-868. [PMID: 30907055 PMCID: PMC6850447 DOI: 10.1111/1753-0407.12922] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 03/06/2019] [Accepted: 03/21/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Genome-wide association studies have identified loci that significantly increase diabetes risk. This study explored the genetic susceptibility in relation to diabetes risk in adulthood among a Chinese population born in the early 1960s. METHODS In all, 2129 subjects (833 males, 1296 females) were selected from the cross-sectional 2010 to 2012 China National Nutrition and Health Survey. Fifty diabetes-related single nucleotide polymorphisms (SNPs) were detected. Two diabetes genetic risk scores (GRSs) based on the 50 diabetes-predisposing variants were developed to examine the association of these SNPs with diabetes risk. RESULTS Associations were found between diabetes risk and SNPs in the MTNR1B (rs10830963), KLHDC5 (rs10842994), GRK5 (rs10886471), cyclindependentkinase 5 regulatory subunit associated protein 1 (rs10946398), adaptorrelated protein complex 3 subunit sigma 2 (rs2028299), diacylglycerol kinase beta/transmembrane protein 195 (rs2191349), SREBF chaperone (rs4858889), ankyrin1 (rs516946), RAS guanyl releasing protein 1 (rs7403531), and zinc finger AN1-type containing 3 (rs9470794) genes. As a continuous variable, with a 1-point increase in the GRS or weighted (w) GRS, fasting plasma glucose (FPG) increased 0.045 and 0.044 mM, respectively (P < 0.001 for both), after adjusting for confounders. Both GRS and wGRS showed an association with diabetes, with a multivariable-adjusted odds ratio (95% confidence interval) of 1.09 (1.00-1.19) and 1.12 (1.03-1.22), respectively, among all subjects. No significant associations were found between the GRS or wGRS and impaired fasting glucose or impaired glucose tolerance. CONCLUSIONS The data suggest the association of 10 SNPs and the GRS or wGRS with diabetes risk. Genetic susceptibility to diabetes may synergistically affect the risk of diabetes in adulthood.
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Affiliation(s)
- Chao Song
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Meng Wang
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Hongyun Fang
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Weiyan Gong
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Deqian Mao
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Caicui Ding
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Qiqi Fu
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Ganyu Feng
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Zheng Chen
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Yanning Ma
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Yecheng Yao
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
| | - Ailing Liu
- Chinese Center for Disease Control and PreventionNational Institute for Nutrition and HealthBeijingChina
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Bärenwaldt A, Läubli H. The sialoglycan-Siglec glyco-immune checkpoint - a target for improving innate and adaptive anti-cancer immunity. Expert Opin Ther Targets 2019; 23:839-853. [PMID: 31524529 DOI: 10.1080/14728222.2019.1667977] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Introduction: During cancer progression, tumor cells develop several mechanisms to prevent killing and to shape the immune system into a tumor-promoting environment. One of such regulatory mechanism is the overexpression of sialic acid (Sia) on carbohydrates of proteins and lipids on tumor cells. Sia-containing glycans or sialoglycans were shown to inhibit immune effector functions of NK cells and T cells by engaging inhibitory Siglec receptors on the surface of these cells. They can also modulate the differentiation of myeloid cells into tumor-promoting M2 macrophages. Areas covered: We review the role of sialoglycans in cancer and introduce the Siglecs, their expression on different immune cells and their interaction with cancer-associated sialoglycans. The targeting of this sialoglycan-Siglec glyco-immune checkpoint is discussed along with potential therapeutic approaches. Pubmed was searched for publications on Siglecs, sialic acid, and cancer. Expert opinion: The targeting of sialoglycan-Siglec interactions has become a major focus in cancer research. New approaches have been developed that directly target sialic acids in tumor lesions. Targeted sialidases that cleave sialic acid specifically in the tumor, have already shown efficacy; efforts targeting the sialoglycan-Siglec pathway for improvement of CAR T cell therapy are ongoing. The sialoglycan-Siglec immune checkpoint is a promising new target for cancer immunotherapy.
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Affiliation(s)
- Anne Bärenwaldt
- Division of Medical Oncology, and Laboratory for Cancer Immunotherapy, Department of Biomedicine, University Hospital Basel , Basel , Switzerland
| | - Heinz Läubli
- Division of Medical Oncology, and Laboratory for Cancer Immunotherapy, Department of Biomedicine, University Hospital Basel , Basel , Switzerland
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41
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Sanghera DK, Hopkins R, Malone-Perez MW, Bejar C, Tan C, Mussa H, Whitby P, Fowler B, Rao CV, Fung KA, Lightfoot S, Frazer JK. Targeted sequencing of candidate genes of dyslipidemia in Punjabi Sikhs: Population-specific rare variants in GCKR promote ectopic fat deposition. PLoS One 2019; 14:e0211661. [PMID: 31369557 PMCID: PMC6675050 DOI: 10.1371/journal.pone.0211661] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 05/28/2019] [Indexed: 12/18/2022] Open
Abstract
Dyslipidemia is a well-established risk factor for cardiovascular diseases. Although, advances in genome-wide technologies have enabled the discovery of hundreds of genes associated with blood lipid phenotypes, most of the heritability remains unexplained. Here we performed targeted resequencing of 13 bona fide candidate genes of dyslipidemia to identify the underlying biological functions. We sequenced 940 Sikh subjects with extreme serum levels of hypertriglyceridemia (HTG) and 2,355 subjects were used for replication studies; all 3,295 participants were part of the Asian Indians Diabetic Heart Study. Gene-centric analysis revealed burden of variants for increasing HTG risk in GCKR (p = 2.1x10-5), LPL (p = 1.6x10-3) and MLXIPL (p = 1.6x10-2) genes. Of these, three missense and damaging variants within GCKR were further examined for functional consequences in vivo using a transgenic zebrafish model. All three mutations were South Asian population-specific and were largely absent in other multiethnic populations of Exome Aggregation Consortium. We built different transgenic models of human GCKR with and without mutations and analyzed the effects of dietary changes in vivo. Despite the short-term of feeding, profound phenotypic changes were apparent in hepatocyte histology and fat deposition associated with increased expression of GCKR in response to a high fat diet (HFD). Liver histology of the GCKRmut showed severe fatty metamorphosis which correlated with ~7 fold increase in the mRNA expression in the GCKRmut fish even in the absence of a high fat diet. These findings suggest that functionally disruptive GCKR variants not only increase the risk of HTG but may enhance ectopic lipid/fat storage defects in absence of obesity and HFD. To our knowledge, this is the first transgenic zebrafish model of a putative human disease gene built to accurately assess the influence of genetic changes and their phenotypic consequences in vivo.
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Affiliation(s)
- Dharambir K. Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Ruth Hopkins
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Megan W. Malone-Perez
- Department of Pediatrics, Section of Pediatric Hematology-Oncology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Cynthia Bejar
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Chengcheng Tan
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Huda Mussa
- Department of Pediatrics, Section of Infectious Diseases, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Paul Whitby
- Department of Pediatrics, Section of Infectious Diseases, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Ben Fowler
- Oklahoma Medical Research Foundation, Imaging Core Facility, Oklahoma City, Oklahoma, United States of America
| | - Chinthapally V. Rao
- Center for Cancer Prevention and Drug Development, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - KarMing A. Fung
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, Oklahoma, United States of America
| | - Stan Lightfoot
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, Oklahoma, United States of America
| | - J. Kimble Frazer
- Department of Pediatrics, Section of Pediatric Hematology-Oncology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
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42
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Arora GP, Åkerlund M, Brøns C, Moen GH, Wasenius NS, Sommer C, Jenum AK, Almgren P, Thaman RG, Orho-Melander M, Eriksson J, Qvigstad E, Birkeland K, Berntorp K, Vaag AA, Groop L, Prasad RB. Phenotypic and genotypic differences between Indian and Scandinavian women with gestational diabetes mellitus. J Intern Med 2019; 286:192-206. [PMID: 30919529 DOI: 10.1111/joim.12903] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Gestational diabetes mellitus (GDM) is a transient form of diabetes characterized by impaired insulin secretion and action during pregnancy. Population-based differences in prevalence exist which could be explained by phenotypic and genetic differences. The aim of this study was to examine these differences in pregnant women from Punjab, India and Scandinavia. METHODS Eighty-five GDM/T2D loci in European and/or Indian populations from previous studies were assessed for association with GDM based on Swedish GDM criteria in 4018 Punjabi Indian and 507 Swedish pregnant women. Selected loci were replicated in Scandinavian cohorts, Radiel (N = 398, Finnish) and STORK/STORK-G (N = 780, Norwegian). RESULTS Punjabi Indian women had higher GDM prevalence, lower insulin secretion and better insulin sensitivity than Swedish women. There were significant frequency differences of GDM/T2D risk alleles between both populations. rs7178572 at HMG20A, previously associated with GDM in South Indian and European women, was replicated in North Indian women. The T2D risk SNP rs11605924 in the CRY2 gene was associated with increased GDM risk in Scandinavian but decreased GDM risk in Punjabi Indian women. No other overlap was seen between GDM loci in both populations. CONCLUSIONS Gestational diabetes mellitus is more common in Indian than Swedish women, which partially can be attributed to differences in insulin secretion and action. There was marked heterogeneity in the GDM phenotypes between the populations which could only partially be explained by genetic differences.
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Affiliation(s)
- G P Arora
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden.,Deep Hospital, Ludhiana, Punjab, India
| | - M Åkerlund
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden
| | - C Brøns
- Department of Endocrinology (Diabetes and Metabolism), Rigshospitalet, Copenhagen, Denmark
| | - G-H Moen
- Department of Endocrinology Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway.,Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - N S Wasenius
- Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland.,Department of General Practice and Primary Health Care, Diabetes and Obesity Research Program Research Programs Unit, University of Helsinki, Helsinki, Finland
| | - C Sommer
- Department of Endocrinology Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - A K Jenum
- Department of General Practice, Institute of Health and Society, University of Oslo, Oslo, Norway
| | - P Almgren
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden
| | | | - M Orho-Melander
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden
| | - J Eriksson
- Department of General Practice and Primary Health Care, Diabetes and Obesity Research Program Research Programs Unit, University of Helsinki, Helsinki, Finland
| | - E Qvigstad
- Department of Endocrinology Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway.,Section of Specialized Endocrinology, Department of Endocrinology, Oslo University Hospital, Oslo, Norway
| | - K Birkeland
- Department of Endocrinology Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway.,Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - K Berntorp
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden.,Department of Endocrinology, Skåne University Hospital, Malmö, Sweden
| | - A A Vaag
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden.,Department of Endocrinology (Diabetes and Metabolism), Rigshospitalet, Copenhagen, Denmark.,Cardiovascular, Renal and Metabolism (CVRM) Translational Medicine Unit, Early Clinical development, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - L Groop
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden.,Finnish Institute of Molecular Medicine (FIMM), Helsinki University, Helsinki, Finland
| | - R B Prasad
- Department of Clinical Sciences, Clinical Research Centre, Lund University, Malmö, Sweden
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ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response. Nat Commun 2019; 10:3195. [PMID: 31324766 PMCID: PMC6642147 DOI: 10.1038/s41467-019-10967-7] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 06/11/2019] [Indexed: 12/13/2022] Open
Abstract
Genome analysis of diverse human populations has contributed to the identification of novel genomic loci for diseases of major clinical and public health impact. Here, we report a genome-wide analysis of type 2 diabetes (T2D) in sub-Saharan Africans, an understudied ancestral group. We analyze ~18 million autosomal SNPs in 5,231 individuals from Nigeria, Ghana and Kenya. We identify a previously-unreported genome-wide significant locus: ZRANB3 (Zinc Finger RANBP2-Type Containing 3, lead SNP p = 2.831 × 10−9). Knockdown or genomic knockout of the zebrafish ortholog results in reduction in pancreatic β-cell number which we demonstrate to be due to increased apoptosis in islets. siRNA transfection of murine Zranb3 in MIN6 β-cells results in impaired insulin secretion in response to high glucose, implicating Zranb3 in β-cell functional response to high glucose conditions. We also show transferability in our study of 32 established T2D loci. Our findings advance understanding of the genetics of T2D in non-European ancestry populations. Type 2 diabetes (T2D) is prevalent in populations worldwide, however, mostly studied in European and mixed-ancestry populations. Here, the authors perform a genome-wide association study for T2D in over 5,000 sub-Saharan Africans and identify a locus, ZRANB3, that is specific for this population.
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The pleiotropic effect of rs7903146 on type 2 diabetes and ischemic stroke: a family-based study in a Chinese population. J Thromb Thrombolysis 2019; 48:303-314. [PMID: 30980227 DOI: 10.1007/s11239-019-01855-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The rs7903146, an established genetic variant susceptible to type 2 diabetes (T2D), is also reported to be related to ischemic stroke (IS), though conflicting. Furthermore, it remained unknown whether the genetic association with stroke is independent of T2D. In the current study, 1603 individuals across 986 families were included. The genetic pleiotropic effect on each outcome diseases (T2D, overall IS, or each subtype) was assessed using multilevel logistic regression after adjustment for multiple covariates. Principal component of heritability (PCH) was also used to assess the pleiotropy by combining T2D and IS into one outcome for analysis. To identify the T2D-independent path out of the pleiotropic effect on IS, T2D status was additionally adjusted for the risk of IS or each subtype. The analyses of putative molecular pathways (dyslipidemia, hypertension, obesity and inflammation) and gene-lifestyle interactions were also performed. We found that rs7903146_T allele was associated with a 77% higher risk of T2D, 55% of IS, and 70% of large artery atherosclerosis (LAA) subtype respectively. Particularly, a T2D-independent genetic effect was identified to increase the risk of overall IS and LAA. No evidence on the molecular mechanisms and gene-lifestyle interaction behind the pleiotropic genetic effect was observed. In conclusion, our study provided evidence that a T2D-independent path was identified out of the pleiotropic effect of rs7903146 on IS. However, further studies were needed to validate the biological mechanisms behind the pleiotropic effect and the modification by lifestyle intervention.
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Justice AE, Karaderi T, Highland HM, Young KL, Graff M, Lu Y, Turcot V, Auer PL, Fine RS, Guo X, Schurmann C, Lempradl A, Marouli E, Mahajan A, Winkler TW, Locke AE, Medina-Gomez C, Esko T, Vedantam S, Giri A, Lo KS, Alfred T, Mudgal P, Ng MCY, Heard-Costa NL, Feitosa MF, Manning AK, Willems SM, Sivapalaratnam S, Abecasis G, Alam DS, Allison M, Amouyel P, Arzumanyan Z, Balkau B, Bastarache L, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bottinger EP, Bowden DW, Brandslund I, Broer L, Burt AA, Butterworth AS, Caulfield MJ, Cesana G, Chambers JC, Chasman DI, Chen YDI, Chowdhury R, Christensen C, Chu AY, Collins FS, Cook JP, Cox AJ, Crosslin DS, Danesh J, de Bakker PIW, Denus SD, Mutsert RD, Dedoussis G, Demerath EW, Dennis JG, Denny JC, Di Angelantonio E, Dörr M, Drenos F, Dubé MP, Dunning AM, Easton DF, Elliott P, Evangelou E, Farmaki AE, Feng S, Ferrannini E, Ferrieres J, Florez JC, Fornage M, Fox CS, Franks PW, Friedrich N, Gan W, Gandin I, Gasparini P, Giedraitis V, Girotto G, Gorski M, Grallert H, Grarup N, Grove ML, Gustafsson S, Haessler J, Hansen T, Hattersley AT, Hayward C, Heid IM, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Hung YJ, Hveem K, Ikram MA, Ingelsson E, Jackson AU, Jarvik GP, Jia Y, Jørgensen T, Jousilahti P, Justesen JM, Kahali B, Karaleftheri M, Kardia SLR, Karpe F, Kee F, Kitajima H, Komulainen P, Kooner JS, Kovacs P, Krämer BK, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange LA, Langenberg C, Larson EB, Lee NR, Lee WJ, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Luan J, Lyytikäinen LP, MacGregor S, Mägi R, Männistö S, Marenne G, Marten J, Masca NGD, McCarthy MI, Meidtner K, Mihailov E, Moilanen L, Moitry M, Mook-Kanamori DO, Morgan A, Morris AP, Müller-Nurasyid M, Munroe PB, Narisu N, Nelson CP, Neville M, Ntalla I, O'Connell JR, Owen KR, Pedersen O, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Ewing A, Polasek O, Raitakari OT, Rasheed A, Raulerson CK, Rauramaa R, Reilly DF, Reiner AP, Ridker PM, Rivas MA, Robertson NR, Robino A, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe M, Sim X, Slater AJ, Small KS, Smith BH, Smith JA, Southam L, Spector TD, Speliotes EK, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swart KMA, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Torres M, Tsafantakis E, Tuomilehto J, Uitterlinden AG, Uusitupa M, van Duijn CM, Vanhala M, Varma R, Vermeulen SH, Vestergaard H, Vitart V, Vogt TF, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Wood AR, Wu Y, Yaghootkar H, Yao J, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zheng H, Zhou W, Zillikens MC, Rivadeneira F, Borecki IB, Pospisilik JA, Deloukas P, Frayling TM, Lettre G, Mohlke KL, Rotter JI, Kutalik Z, Hirschhorn JN, Cupples LA, Loos RJF, North KE, Lindgren CM. Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution. Nat Genet 2019; 51:452-469. [PMID: 30778226 PMCID: PMC6560635 DOI: 10.1038/s41588-018-0334-2] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 12/17/2018] [Indexed: 02/02/2023]
Abstract
Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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Affiliation(s)
- Anne E Justice
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
- Weis Center for Research, Geisinger Health System, Danville, PA, USA
| | - Tugce Karaderi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Biological Sciences, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta, Cyprus
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Yingchang Lu
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Valérie Turcot
- Montreal Heart Institute, Universite de Montreal, Montreal, Quebec, Canada
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Rebecca S Fine
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Adelheid Lempradl
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Adam E Locke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO, USA
| | - Carolina Medina-Gomez
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Tõnu Esko
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Sailaja Vedantam
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
| | - Ayush Giri
- Department of Obstetrics and Gynecology, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Ken Sin Lo
- Montreal Heart Institute, Universite de Montreal, Montreal, Quebec, Canada
- Department of Obstetrics and Gynecology, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Tamuno Alfred
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Poorva Mudgal
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Maggie C Y Ng
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Nancy L Heard-Costa
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- NHLBI Framingham Heart Study, Framingham, MA, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Alisa K Manning
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard University Medical School, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Sara M Willems
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Suthesh Sivapalaratnam
- Massachusetts General Hospital, Boston, MA, USA
- Department of Vascular Medicine, AMC, Amsterdam, The Netherlands
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Goncalo Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Dewan S Alam
- School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Canada
| | - Matthew Allison
- Department of Family Medicine & Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Philippe Amouyel
- INSERM U1167, Lille, France
- Institut Pasteur de Lille, U1167, Lille, France
- U1167-RID-AGE, Universite de Lille - Risk factors and molecular determinants of aging-related diseases, Lille, France
| | - Zorayr Arzumanyan
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Beverley Balkau
- INSERM U1018, Centre de recherche en Épidemiologie et Sante des Populations (CESP), Villejuif, France
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Matthias Blüher
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Carsten A Böger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Jette Bork-Jensen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Donald W Bowden
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ivan Brandslund
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Linda Broer
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Amber A Burt
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Research Centre, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, UK
| | - Giancarlo Cesana
- Research Centre on Public Health, University of Milano-Bicocca, Monza, Italy
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Cardiology, London North West Healthcare NHS Trust, Ealing Hospital, Middlesex, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Daniel I Chasman
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Brigham and Women's and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Rajiv Chowdhury
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women's and Harvard Medical School, Boston, MA, USA
| | - Francis S Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Amanda J Cox
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
| | - David S Crosslin
- Department of Biomedical Infomatics and Medical Education, University of Washington, Seattle, WA, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Wellcome Trust Sanger Institute, Hinxton, UK
- British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Paul I W de Bakker
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Simon de Denus
- Montreal Heart Institute, Universite de Montreal, Montreal, Quebec, Canada
- Faculty of Pharmacy, Universite de Montreal, Montreal, Quebec, Canada
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Ellen W Demerath
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Joe G Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Josh C Denny
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Emanuele Di Angelantonio
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Fotios Drenos
- Institute of Cardiovascular Science, University College London, London, UK
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Department of Life Sciences, Brunel University London, Uxbridge, UK
| | - Marie-Pierre Dubé
- Montreal Heart Institute, Universite de Montreal, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Universite de Montreal, Montreal, Quebec, Canada
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Shuang Feng
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ele Ferrannini
- CNR Institute of Clinical Physiology, Pisa, Italy
- Department of Clinical & Experimental Medicine, University of Pisa, Pisa, Italy
| | - Jean Ferrieres
- Toulouse University School of Medicine, Toulouse, France
| | - Jose C Florez
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard University Medical School, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmo, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
- Department of Public Health and Clinical Medicine, Unit of Medicine, Umeå University, Umeå, Sweden
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Wei Gan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ilaria Gandin
- Ilaria Gandin, Research Unit, AREA Science Park, Trieste, Italy
| | - Paolo Gasparini
- Department of Medical Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | | | - Giorgia Girotto
- Department of Medical Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Harald Grallert
- German Center for Diabetes Research, München-Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle WA, USA
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Oddgeir L Holmen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - G Kees Hovingh
- Department of Vascular Medicine, AMC, Amsterdam, The Netherlands
| | - Joanna M M Howson
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Yao Hu
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yi-Jen Hung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health, Norwegian University of Science and Technology, Levanger, Norway
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Gail P Jarvik
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Yucheng Jia
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Torben Jørgensen
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Research Center for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
| | | | - Johanne M Justesen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bratati Kahali
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Frank Kee
- UKCRC Centre of Excellence for Public Health Research, Queens University Belfast, Belfast, UK
| | - Hidetoshi Kitajima
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Pirjo Komulainen
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Jaspal S Kooner
- Department of Cardiology, London North West Healthcare NHS Trust, Ealing Hospital, Middlesex, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Peter Kovacs
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Bernhard K Krämer
- University Medical Centre Mannheim, 5th Medical Department, University of Heidelberg, Mannheim, Germany
| | - Kari Kuulasmaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Timo A Lakka
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - David Lamparter
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Verge Genomics, San Fransico, CA, USA
| | - Leslie A Lange
- Division of Biomedical and Personalized Medicine, Department of Medicine, University of Colorado-Denver, Aurora, CO, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Eric B Larson
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Nanette R Lee
- Department of Anthropology, Sociology, and History, University of San Carlos, Cebu City, Philippines
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Social Work, Tunghai University, Taichung, Taiwan
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Cora E Lewis
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Huaixing Li
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jin Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Li-An Lin
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xu Lin
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | | | - Jaana Lindström
- National Institute for Health and Welfare, Helsinki, Finland
| | - Allan Linneberg
- Research Center for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Institute for Personalized Medicine, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, Finland
| | | | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Nicholas G D Masca
- Department of Cardiovascular Sciences, Univeristy of Leicester, Glenfield Hospital, Leicester, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Karina Meidtner
- German Center for Diabetes Research, München-Neuherberg, Germany
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany
| | | | - Leena Moilanen
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Marie Moitry
- Department of Epidemiology and Public Health, University of Strasbourg, Strasbourg, France
- Department of Public Health, University Hospital of Strasbourg, Strasbourg, France
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Anna Morgan
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Andrew P Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-Universitat, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Research Centre, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, UK
| | - Narisu Narisu
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, Univeristy of Leicester, Glenfield Hospital, Leicester, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Matt Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jeffrey R O'Connell
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Katharine R Owen
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Craig E Pennell
- Division of Obstetric and Gynaecology, School of Medicine, The University of Western Australia, Perth, Western Australia, Australia
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine (FIMM) and Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland
| | - James A Perry
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Tune H Pers
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Ailith Ewing
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ozren Polasek
- School of Medicine, University of Split, Split, Croatia
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Asif Rasheed
- Centre for Non-Communicable Diseases, Karachi, Pakistan
| | | | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
| | - Dermot F Reilly
- Genetics and Pharmacogenomics, Merck & Co., Inc., Boston, MA, USA
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Manuel A Rivas
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Neil R Robertson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Antonietta Robino
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Katherine S Ruth
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Danish Saleheen
- Centre for Non-Communicable Diseases, Karachi, Pakistan
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, Univeristy of Leicester, Glenfield Hospital, Leicester, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Pamela J Schreiner
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Matthias B Schulze
- German Center for Diabetes Research, München-Neuherberg, Germany
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Marcelo Segura-Lepe
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Xueling Sim
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Andrew J Slater
- Genetics, Target Sciences, GlaxoSmithKline, Research Triangle Park, NC, USA
- OmicSoft a QIAGEN Company, Cary, NC, USA
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Blair H Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lorraine Southam
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Wellcome Trust Sanger Institute, Hinxton, UK
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Elizabeth K Speliotes
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Kathleen E Stirrups
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Germany
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michael Stumvoll
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Liang Sun
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Karin M A Swart
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - Jean-Claude Tardif
- Montreal Heart Institute, Universite de Montreal, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Universite de Montreal, Montreal, Quebec, Canada
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Betina H Thuesen
- Research Center for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
| | - Anke Tönjes
- Center for Pediatric Research, Department for Women's and Child Health, University of Leipzig, Leipzig, Germany
| | - Mina Torres
- USC Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | | | - Jaakko Tuomilehto
- National Institute for Health and Welfare, Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
- Dasman Diabetes Institute, Dasman, Kuwait
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Matti Uusitupa
- Department of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | - Mauno Vanhala
- Central Finland Central Hospital, Jyvaskyla, Finland
- University of Eastern Finland, Kuopio, Finland
| | - Rohit Varma
- USC Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Sita H Vermeulen
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Henrik Vestergaard
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Thomas F Vogt
- Cardiometabolic Disease, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Dragana Vuckovic
- Department of Medical Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Mark Walker
- Institute of Cellular Medicine, The Medical School, Newcastle University, Newcastle, UK
| | - Lars Wallentin
- Department of Medical Sciences, Cardiology, Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
| | - Feijie Wang
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Carol A Wang
- Division of Obstetric and Gynaecology, School of Medicine, The University of Western Australia, Perth, Western Australia, Australia
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Shuai Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Research Centre, Barts and The London School of Medicine & Dentistry, Queen Mary University of London, London, UK
| | | | - Jennifer Wessel
- Departments of Epidemiology & Medicine, Diabetes Translational Research Center, Fairbanks School of Public Health & School of Medicine, Indiana University, Indiana, IN, USA
| | - Harvey D White
- Green Lane Cardiovascular Service, Auckland City Hospital and University of Auckland, Auckland, New Zealand
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Laura M Yerges-Armstrong
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- GlaxoSmithKline, King of Prussia, PA, USA
| | - Robin Young
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- University of Glasgow, Glasgow, UK
| | | | - Xiaowei Zhan
- Department of Clinical Sciences, Quantitative Biomedical Research Center, Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Weihua Zhang
- Department of Cardiology, London North West Healthcare NHS Trust, Ealing Hospital, Middlesex, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Wei Zhao
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - He Zheng
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - M Carola Zillikens
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ingrid B Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Guillaume Lettre
- Montreal Heart Institute, Universite de Montreal, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Universite de Montreal, Montreal, Quebec, Canada
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Joel N Hirschhorn
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Departments of Pediatrics and Genetics, Harvard Medical School, Boston, MA, USA
| | - L Adrienne Cupples
- NHLBI Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E North
- Department of Epidemiology and Carolina Center of Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Cecilia M Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
- Li Ka Shing Centre for Health Information and Discovery, The Big Data Institute, University of Oxford, Oxford, UK.
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Najafi A, Janghorbani S, Motahari SA, Fatemizadeh E. Statistical Association Mapping of Population-Structured Genetic Data. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019; 16:638-649. [PMID: 29990264 DOI: 10.1109/tcbb.2017.2786239] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability distribution of the model parameters. We have implemented our proposed framework on a software package whose performance is extensively evaluated on a number of synthetic datasets, and compared to some of the well-known existing methods such as STRUCTURE. It has been shown that in extreme scenarios, up to $10-15$10-15 percent of improvement in the inference accuracy is achieved with a moderate increase in computational complexity.
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Reddy BM, Pranavchand R, Latheef SAA. Overview of genomics and post-genomics research on type 2 diabetes mellitus: Future perspectives and a framework for further studies. J Biosci 2019; 44:21. [PMID: 30837372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
In this review, we briefly outlined salient features of pathophysiology and results of the genetic association studies hitherto conducted on type 2 diabetes. Primarily focusing on the current status of genomic research, we briefly discussed the limited progress made during the post-genomic era and tried to identify the limitations of the post-genomic research strategies. We suggested reanalysis of the existing genomic data through advanced statistical and computational methods and recommended integrated genomics-metabolomics approaches for future studies to facilitate understanding of the gene-environment interactions in the manifestation of the disease. We also propose a framework for research that may be apt for determining the effects of urbanization and changing lifestyles in the manifestation of complex genetic disorders like type 2 diabetes in the Indian populations and offset the confounding effects of both genetic and environmental factors in the natural way.
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Overview of genomics and post-genomics research on type 2 diabetes mellitus: Future perspectives and a framework for further studies. J Biosci 2019. [DOI: 10.1007/s12038-018-9818-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Lam YWF, Duggirala R, Jenkinson CP, Arya R. The Role of Pharmacogenomics in Diabetes. Pharmacogenomics 2019. [DOI: 10.1016/b978-0-12-812626-4.00009-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
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Elbere I, Silamikelis I, Ustinova M, Kalnina I, Zaharenko L, Peculis R, Konrade I, Ciuculete DM, Zhukovsky C, Gudra D, Radovica-Spalvina I, Fridmanis D, Pirags V, Schiöth HB, Klovins J. Significantly altered peripheral blood cell DNA methylation profile as a result of immediate effect of metformin use in healthy individuals. Clin Epigenetics 2018; 10:156. [PMID: 30545422 PMCID: PMC6293577 DOI: 10.1186/s13148-018-0593-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 11/29/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Metformin is a widely prescribed antihyperglycemic agent that has been also associated with multiple therapeutic effects in various diseases, including several types of malignancies. There is growing evidence regarding the contribution of the epigenetic mechanisms in reaching metformin's therapeutic goals; however, the effect of metformin on human cells in vivo is not comprehensively studied. The aim of our study was to examine metformin-induced alterations of DNA methylation profiles in white blood cells of healthy volunteers, employing a longitudinal study design. RESULTS Twelve healthy metformin-naïve individuals where enrolled in the study. Genome-wide DNA methylation pattern was estimated at baseline, 10 h and 7 days after the start of metformin administration. The whole-genome DNA methylation analysis in total revealed 125 differentially methylated CpGs, of which 11 CpGs and their associated genes with the most consistent changes in the DNA methylation profile were selected: POFUT2, CAMKK1, EML3, KIAA1614, UPF1, MUC4, LOC727982, SIX3, ADAM8, SNORD12B, VPS8, and several differentially methylated regions as novel potential epigenetic targets of metformin. The main functions of the majority of top-ranked differentially methylated loci and their representative cell signaling pathways were linked to the well-known metformin therapy targets: regulatory processes of energy homeostasis, inflammatory responses, tumorigenesis, and neurodegenerative diseases. CONCLUSIONS Here we demonstrate for the first time the immediate effect of short-term metformin administration at therapeutic doses on epigenetic regulation in human white blood cells. These findings suggest the DNA methylation process as one of the mechanisms involved in the action of metformin, thereby revealing novel targets and directions of the molecular mechanisms underlying the various beneficial effects of metformin. TRIAL REGISTRATION EU Clinical Trials Register, 2016-001092-74. Registered 23 March 2017, https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-001092-74/LV .
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Affiliation(s)
- Ilze Elbere
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Ivars Silamikelis
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Monta Ustinova
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Ineta Kalnina
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Linda Zaharenko
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Raitis Peculis
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Ilze Konrade
- Riga East Clinical University Hospital, 2 Hipokrata Street, Riga, LV-1038, Latvia
| | - Diana Maria Ciuculete
- Department of Neuroscience, Functional Pharmacology, Uppsala University, BMC, Box 593, 751 24, Uppsala, Sweden
| | - Christina Zhukovsky
- Department of Neuroscience, Functional Pharmacology, Uppsala University, BMC, Box 593, 751 24, Uppsala, Sweden
| | - Dita Gudra
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Ilze Radovica-Spalvina
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Davids Fridmanis
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Valdis Pirags
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia
| | - Helgi B Schiöth
- Department of Neuroscience, Functional Pharmacology, Uppsala University, BMC, Box 593, 751 24, Uppsala, Sweden
| | - Janis Klovins
- Latvian Biomedical Research and Study Centre, Ratsupites Str. 1 k-1, Riga, LV-1067, Latvia.
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