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Del Bosque-Plata L, Martínez-Martínez E, Espinoza-Camacho MÁ, Gragnoli C. The Role of TCF7L2 in Type 2 Diabetes. Diabetes 2021; 70:1220-1228. [PMID: 34016596 PMCID: PMC8275893 DOI: 10.2337/db20-0573] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 03/19/2021] [Indexed: 12/16/2022]
Abstract
TCF7L2 is the most potent locus for type 2 diabetes (T2D) risk and the first locus to have been robustly reported by genomic linkage studies. TCF7L2 is a transcription factor that forms a basic part of the Wnt signaling pathway. This gene has highly conserved sequence regions that correspond to functional domains. The association of TCF7L2 with T2D is one of the most powerful genetically discovered in studies of complex diseases, as it has been consistently replicated in multiple populations with diverse genetic origins. The mechanisms over which TCF7L2 exerts its effect on T2D are still not well understood. In this article, we describe the main molecular mechanisms of how TCF7L2 is related to T2D. TCF7L2 variants associated with T2D risk exert an influence on the initial therapeutic success of the hypoglycemic oral agent sulfonylurea. Thus, it is important to know whether there are other TCF7L2 variants associated with T2D that can influence treatment with oral hypoglycemic agents. Resequencing of the TCF7L2 gene in diverse ethnic groups is required to reveal common and rare variations and their role in different pathologies and in adverse reactions to drugs. Identification of TCF7L2-susceptibility disease variants will permit, at a given moment, offering of therapies to patients according to their genotype.
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Affiliation(s)
- Laura Del Bosque-Plata
- Laboratory of Nutrigenetics and Nutrigenomics, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Eduardo Martínez-Martínez
- Laboratory of Cell Communication and Extracellular Vesicles, National Institute of Genomic Medicine, Mexico City, Mexico
| | | | - Claudia Gragnoli
- Division of Endocrinology, Department of Medicine, School of Medicine, Creighton University, Omaha, NE
- Division of Endocrinology, Diabetes, and Metabolic Disease, Department of Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA
- Molecular Biology Laboratory, Bios Biotech Multi-Diagnostic Health Center, Rome, Italy
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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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Fernández-Rhodes L, Howard AG, Graff M, Isasi CR, Highland HM, Young KL, Parra E, Below JE, Qi Q, Kaplan RC, Justice AE, Papanicolaou G, Laurie CC, Grant SFA, Haiman C, Loos RJF, North KE. Complex patterns of direct and indirect association between the transcription Factor-7 like 2 gene, body mass index and type 2 diabetes diagnosis in adulthood in the Hispanic Community Health Study/Study of Latinos. BMC OBESITY 2018; 5:26. [PMID: 30305909 PMCID: PMC6167893 DOI: 10.1186/s40608-018-0200-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 05/23/2018] [Indexed: 01/10/2023]
Abstract
Background Genome-wide association studies have implicated the transcription factor 7-like 2 (TCF7L2) gene in type 2 diabetes risk, and more recently, in decreased body mass index. Given the contrary direction of genetic effects on these two traits, it has been suggested that the observed association with body mass index may reflect either selection bias or a complex underlying biology at TCF7L2. Methods Using 9031 Hispanic/Latino adults (21–76 years) with complete weight history and genetic data from the community-based Hispanic Community Health Study/Study of Latinos (HCHS/SOL, Baseline 2008–2011), we estimated the multivariable association between the additive number of type 2 diabetes increasing-alleles at TCF7L2 (rs7903146-T) and body mass index. We then used structural equation models to simultaneously model the genetic association on changes in body mass index across the life course and estimate the odds of type 2 diabetes per TCF7L2 risk allele. Results We observed both significant increases in type 2 diabetes prevalence at examination (independent of body mass index) and decreases in mean body mass index and waist circumference across genotypes at rs7903146. We observed a significant multivariable association between the additive number of type 2 diabetes-risk alleles and lower body mass index at examination. In our structured modeling, we observed non-significant inverse direct associations between rs7903146-T and body mass index at ages 21 and 45 years, and a significant positive association between rs7903146-T and type 2 diabetes onset in both middle and late adulthood. Conclusions Herein, we replicated the protective effect of rs7930146-T on body mass index at multiple time points in the life course, and observed that these effects were not explained by past type 2 diabetes status in our structured modeling. The robust replication of the negative effects of TCF7L2 on body mass index in multiple samples, including in our diverse Hispanic/Latino community-based sample, supports a growing body of literature on the complex biologic mechanism underlying the functional consequences of TCF7L2 on obesity and type 2 diabetes across the life course. Electronic supplementary material The online version of this article (10.1186/s40608-018-0200-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- 1Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA.,2Carolina Population Center, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA
| | - Annie Green Howard
- 2Carolina Population Center, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA.,3Department of Biostatistics, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Mariaelisa Graff
- 1Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA
| | - Carmen R Isasi
- 4Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY USA
| | - Heather M Highland
- 1Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA
| | - Kristin L Young
- 1Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA
| | - Esteban Parra
- 5Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON Canada
| | - Jennifer E Below
- 6Department of Medicine, Vanderbilt University Medical Center, Nashville, TN USA
| | - Qibin Qi
- 4Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY USA
| | - Robert C Kaplan
- 4Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY USA
| | - Anne E Justice
- 7Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA USA
| | - George Papanicolaou
- 8Epidemiology Branch, National Heart Lung and Blood Institute, Bethesda, MD USA
| | - Cathy C Laurie
- 9Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA USA
| | - Struan F A Grant
- 10Divisions of Human Genetics and Endocrinology, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA USA
| | - Christopher Haiman
- 11Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Ruth J F Loos
- 12Charles R. Bronfman Instituted for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Kari E North
- 1Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 123 W Franklin St, Building C, Chapel Hill, NC USA
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