Triglyceride-Increasing Alleles Associated with Protection against Type-2 Diabetes
An elevated triglyceride level is generally considered a risk factor for the development of type-2 diabetes. However, recent studies suggest, somewhat paradoxically, that genetic risk for elevated triglycerides may protect against type-2 diabetes. In this study, we test the relationship of triglyceride-associated genetic variants, collectively and individually, with incident type-2 diabetes across three prospective cohort studies comprised of European- and African-American participants. Our findings across studies, racial groups, and statistical models consistently demonstrate that triglyceride-increasing alleles are associated with decreased type-2 diabetes incidence. These genes therefore appear to both increase triglyceride levels and decrease type-2 diabetes risk. More work is needed to understand the physiological mechanism underlying these findings, and to determine the causal relationship between triglycerides and type-2 diabetes.
Vyšlo v časopise:
Triglyceride-Increasing Alleles Associated with Protection against Type-2 Diabetes. PLoS Genet 11(5): e32767. doi:10.1371/journal.pgen.1005204
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pgen.1005204
Souhrn
An elevated triglyceride level is generally considered a risk factor for the development of type-2 diabetes. However, recent studies suggest, somewhat paradoxically, that genetic risk for elevated triglycerides may protect against type-2 diabetes. In this study, we test the relationship of triglyceride-associated genetic variants, collectively and individually, with incident type-2 diabetes across three prospective cohort studies comprised of European- and African-American participants. Our findings across studies, racial groups, and statistical models consistently demonstrate that triglyceride-increasing alleles are associated with decreased type-2 diabetes incidence. These genes therefore appear to both increase triglyceride levels and decrease type-2 diabetes risk. More work is needed to understand the physiological mechanism underlying these findings, and to determine the causal relationship between triglycerides and type-2 diabetes.
Zdroje
1. Noble D, Mathur R, Dent T, Meads C, Greenhalgh T (2011) Risk models and scores for type 2 diabetes: systematic review. Bmj Clinical Research Ed 343: d7163–d7163. doi: 10.1136/bmj.d7163 22123912
2. Li N, Fu J, Koonen DP, Kuivenhoven JA, Snieder H, et al. (2014) Are hypertriglyceridemia and low HDL causal factors in the development of insulin resistance? Atherosclerosis 233: 130–138. doi: 10.1016/j.atherosclerosis.2013.12.013 24529133
3. Teslovich TM, Musunuru K, Smith A V, Edmondson AC, Stylianou IM, et al. (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466: 707–713. doi: 10.1038/nature09270 20686565
4. Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, et al. (2013) Discovery and refinement of loci associated with lipid levels. Nature genetics 45: 1274–1283. doi: 10.1038/ng.2797 24097068
5. Klimentidis YC, Wineinger NE, Vazquez AI, De los Campos G (2014) Multiple Metabolic Genetic Risk Scores and Type 2 Diabetes Risk in Three Racial/Ethnic Groups. Journal of Clinical Endocrinology & Metabolism 99: E1814–E1818.
6. Li N, Van der Sijde MR, Study LC, Bakker SJL, Dullaart RPF, et al. (2014) Pleiotropic Effects of Lipid Genes on Plasma Glucose, HbA1c, and HOMA-IR Levels. Diabetes 63: 3149–3158. doi: 10.2337/db13-1800 24722249
7. Orho-Melander M, Melander O, Guiducci C, Perez-Martinez P, Corella D, et al. (2008) Common Missense Variant in the Glucokinase Regulatory Protein Gene Is Associated With Increased Plasma Triglyceride and C-Reactive Protein but Lower Fasting Glucose Concentrations. Diabetes 57: 3112–3121. doi: 10.2337/db08-0516 18678614
8. Sparsø T, Andersen G, Nielsen T, Burgdorf KS, Gjesing AP, et al. (2008) The GCKR rs780094 polymorphism is associated with elevated fasting serum triacylglycerol, reduced fasting and OGTT-related insulinaemia, and reduced risk of type 2 diabetes. Diabetologia 51: 70–75. 18008060
9. Sanders FWB, Griffin JL (2015) De novo lipogenesis in the liver in health and disease: more than just a shunting yard for glucose. Biological Reviews: n/a–n/a.
10. Beer NL, Tribble ND, McCulloch LJ, Roos C, Johnson PR V, et al. (2009) The P446L variant in GCKR associated with fasting plasma glucose and triglyceride levels exerts its effect through increased glucokinase activity in liver. Human Molecular Genetics 18: 4081–4088. doi: 10.1093/hmg/ddp357 19643913
11. De Silva NMG, Freathy RM, Palmer TM, Donnelly LA, Luan J, et al. (2011) Mendelian randomization studies do not support a role for raised circulating triglyceride levels influencing type 2 diabetes, glucose levels, or insulin resistance. Diabetes 60: 1008–1018. doi: 10.2337/db10-1317 21282362
12. Qi Q, Liang L, Doria A, Hu FB, Qi L (2012) Genetic Predisposition to Dyslipidemia and Type 2 Diabetes Risk in Two Prospective Cohorts. Diabetes 61: 745–752. doi: 10.2337/db11-1254 22315312
13. Scott R, Lagou V, Welch RP, Wheeler E, Montasser ME, et al. (2012) Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nature genetics 44: 991–1005. doi: 10.1038/ng.2385 22885924
14. Souverein OW, Jukema JW, Boekholdt SM, Zwinderman AH, Tanck MWT (2005) Polymorphisms in APOA1 and LPL genes are statistically independently associated with fasting TG in men with CAD. European journal of human genetics : EJHG 13: 445–451. 15657615
15. Yamamoto M, Morita SY, Kumon M, Kawabe M, Nishitsuji K, et al. (2003) Effects of plasma apolipoproteins on lipoprotein lipase-mediated lipolysis of small and large lipid emulsions. Biochimica et Biophysica Acta—Molecular and Cell Biology of Lipids 1632: 31–39.
16. Morris AP, Voight BF, Teslovich TM, Ferreira T, Segrè A V, et al. (2012) Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nature genetics 44: 981–990. doi: 10.1038/ng.2383 22885922
17. Onuma H, Tabara Y, Kawamoto R, Shimizu I, Kawamura R, et al. (2010) The GCKR rs780094 polymorphism is associated with susceptibility of type 2 diabetes, reduced fasting plasma glucose levels, increased triglycerides levels and lower HOMA-IR in Japanese population. Journal of human genetics 55: 600–604. doi: 10.1038/jhg.2010.75 20574426
18. Saxena R, Voight BF, Lyssenko V, Burtt NP, De Bakker PI, et al. (2007) Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316: 1331–1336. 17463246
19. Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, et al. (2010) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 42: 105–116. doi: 10.1038/ng.520 20081858
20. Matschinsky FM, Magnuson MA, Zelent D, Jetton TL, Doliba N, et al. (2006) The network of glucokinase-expressing cells in glucose homeostasis and the potential of glucokinase activators for diabetes therapy. Diabetes 55: 1–12. 16380470
21. Saxena R, Elbers C, Guo Y, Peter I, Gaunt T, et al. (2012) Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci. The American Journal of Human Genetics 90: 1–16.
22. Scott RA, Fall T, Pasko D, Barker A, Sharp SJ, et al. (2014) Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independently of obesity. Diabetes: 1–37.
23. The Aric Investigators (1989) The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. American Journal of Epidemiology 129: 687–702. 2646917
24. DAWBER TR, MEADORS GF, MOORE FE Jr. (1951) Epidemiological approaches to heart disease: the Framingham Study. AmJ Public HealthNationsHealth 41: 279–281. 14819398
25. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux A V, et al. (2002) Multi-ethnic study of atherosclerosis: objectives and design. AmJ Epidemiol 156: 871–881. 12397006
26. Sharrett AR, Ballantyne CM, Coady SA, Heiss G, Sorlie PD, et al. (2001) Coronary heart disease prediction from lipoprotein cholesterol levels, triglycerides, lipoprotein(a), apolipoproteins A-I and B, and HDL density subfractions: The Atherosclerosis Risk in Communities (ARIC) Study. Circulation 104: 1108–1113. 11535564
27. Cromwell WC, Otvos JD, Keyes MJ, Pencina MJ, Sullivan L, et al. (2007) LDL particle number and risk of future cardiovascular disease in the Framingham Offspring Study-Implications for LDL management. Journal of Clinical Lipidology 1: 583–592. doi: 10.1016/j.jacl.2007.10.001 19657464
28. Holvoet P, Jenny NS, Schreiner PJ, Tracy RP, Jacobs DR (2007) The relationship between oxidized LDL and other cardiovascular risk factors and subclinical CVD in different ethnic groups: The Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis 194: 245–252. 16982059
29. Duncan BB, Schmidt MI, Pankow JS, Ballantyne CM, Couper D, et al. (2003) Low-grade systemic inflammation and the development of type 2 diabetes: the atherosclerosis risk in communities study. Diabetes 52: 1799–1805. 12829649
30. Howie B, Marchini J, Stephens M, Chakravarti A (2011) Genotype Imputation with Thousands of Genomes. G3 GenesGenomesGenetics 1: 457–470. doi: 10.1534/g3.111.001198 22384356
31. Keller MC (2014) Gene × environment interaction studies have not properly controlled for potential confounders: The problem and the (simple) solution. Biological Psychiatry 75: 18–24. doi: 10.1016/j.biopsych.2013.09.006 24135711
32. R Development Core Team (2011) R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.Rproject.org.
Štítky
Genetika Reprodukčná medicínaČlánok vyšiel v časopise
PLOS Genetics
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