4.7 Article

Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals

Journal

DIABETOLOGIA
Volume 56, Issue 10, Pages 2134-2146

Publisher

SPRINGER
DOI: 10.1007/s00125-013-2985-y

Keywords

BMI; Genetic; Meta-analysis; Metabolic traits; SNP; Obesity susceptibility; Pleiotropy; WHR

Funding

  1. Cancer Research UK
  2. MRC [MC_U106179471, G1000143, U120063239, U123092720]
  3. Netherlands Organization of Scientific Research NWO [175.010.2007.006]
  4. Economic Structure Enhancing Fund (FES) of the Dutch government
  5. Ministry of Economic Affairs
  6. Ministry of Education, Culture and Science
  7. Ministry for Health, Welfare and Sports
  8. Northern Netherlands Collaboration of Provinces (SNN)
  9. Province of Groningen, University Medical Center Groningen
  10. University of Groningen
  11. Dutch Kidney Foundation
  12. Dutch Diabetes Research Foundation
  13. Netherlands Scientific Organization [NWO 480-05-003]
  14. Dutch Brain Foundation
  15. VU University Amsterdam
  16. Wellcome Trust [MC_U106179471]
  17. Support for Science Funding programme
  18. CamStrad [MC_U106179471]
  19. Netherlands Organization for Scientific Research (NWO) [825.10.035]
  20. Netherlands Consortium for Healthy Ageing (NCHA) (NCHA NGI) [050-060-810]
  21. European Union [261433]
  22. MRC [MC_U106179472, MC_U106188470, MC_U123092720, MC_UU_12015/1, MC_UU_12015/2] Funding Source: UKRI
  23. Cancer Research UK [14136] Funding Source: researchfish
  24. Medical Research Council [MC_U123092720, MC_UU_12015/2, MC_UU_12015/1, MC_U106179472, G0401527, MC_U106188470, MC_U106179471, G1000143] Funding Source: researchfish

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Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies. We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR. We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (RBJ [also known as DNAJC27], QPTCL: effect sizes -0.068 and -0.107 SD, respectively), HDL-cholesterol (SLC39A8: -0.065 SD, MTCH2: -0.039 SD), and diastolic BP (SLC39A8: -0.069 SD), and higher and lower levels of LDL- and total cholesterol (QPTCL: 0.041 and 0.042 SDs, respectively, FLJ35779 [also known as POC5]: -0.042 and -0.041 SDs, respectively) (all p < 2.4 x 10(-4)), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (GRB14: 0.069 SD) and lower fasting glucose levels (CPEB4: -0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (-0.005 SD), diastolic BP (-0.006 SD) and 2 h glucose (-0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (-0.015 SD) and higher triacylglycerol levels (0.014 SD) (all p < 2.9 x 10(-3)), independent of BMI and/or WHR. These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities.

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