The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis
Background:
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings:
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions:
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Vyšlo v časopise:
The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis. PLoS Med 10(6): e32767. doi:10.1371/journal.pmed.1001474
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pmed.1001474
Souhrn
Background:
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings:
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions:
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Zdroje
1. GershBJ, SliwaK, MayosiBM, YusufS (2010) Novel therapeutic concepts: the epidemic of cardiovascular disease in the developing world: global implications. Eur Heart J 31: 642–648.
2. WhitlockG, LewingtonS, SherlikerP, ClarkeR, EmbersonJ, et al. (2009) Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet 373: 1083–1096.
3. Davey SmithG, SterneJA, FraserA, TyneliusP, LawlorDA, et al. (2009) The association between BMI and mortality using offspring BMI as an indicator of own BMI: large intergenerational mortality study. BMJ 339: b5043.
4. KnowlerWC, Barrett-ConnorE, FowlerSE, HammanRF, LachinJM, et al. (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346: 393–403.
5. TuomilehtoJ, LindstromJ, ErikssonJG, ValleTT, HamalainenH, et al. (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344: 1343–1350.
6. PanXR, LiGW, HuYH, WangJX, YangWY, et al. (1997) Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 20: 537–544.
7. LiG, ZhangP, WangJ, GreggEW, YangW, et al. (2008) The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study. Lancet 371: 1783–1789.
8. UusitupaM, PeltonenM, LindstromJ, AunolaS, Ilanne-ParikkaP, et al. (2009) Ten-year mortality and cardiovascular morbidity in the Finnish Diabetes Prevention Study—secondary analysis of the randomized trial. PLoS ONE 4: e5656 doi:10.1371/journal.pone.0005656
9. Davey SmithG, EbrahimS (2003) ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 32: 1–22.
10. DidelezV, SheehanN (2007) Mendelian randomization as an instrumental variable approach to causal inference. Stat Methods Med Res 16: 309–330.
11. Sheehan NA, Meng S, Didelez V (2011) Mendelian randomisation: a tool for assessing causality in observational epidemiology. In: Teare MD, editor. Genetic epidemiology. New York City: Humana Press.
12. DayFR, LoosRJ (2011) Developments in obesity genetics in the era of genome-wide association studies. J Nutrigenet Nutrigenomics 4: 222–238.
13. SpeliotesEK, WillerCJ, BerndtSI, MondaKL, ThorleifssonG, et al. (2010) Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 42: 937–948.
14. TimpsonNJ, NordestgaardBG, HarbordRM, ZachoJ, FraylingTM, et al. (2011) C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization. Int J Obes (Lond) 35: 300–308.
15. FreathyRM, TimpsonNJ, LawlorDA, PoutaA, Ben-ShlomoY, et al. (2008) Common variation in the FTO gene alters diabetes-related metabolic traits to the extent expected given its effect on BMI. Diabetes 57: 1419–1426.
16. NordestgaardBG, PalmerTM, BennM, ZachoJ, Tybjaerg-HansenA, et al. (2012) The effect of elevated body mass index on ischemic heart disease risk: causal estimates from a mendelian randomisation approach. PLoS Med 9: e1001212 doi:10.1371/journal.pmed.1001212
17. KivimakiM, SmithGD, TimpsonNJ, LawlorDA, BattyGD, et al. (2008) Lifetime body mass index and later atherosclerosis risk in young adults: examining causal links using Mendelian randomization in the Cardiovascular Risk in Young Finns study. Eur Heart J 29: 2552–2560.
18. TimpsonNJ, HarbordR, Davey SmithG, ZachoJ, Tybjaerg-HansenA, et al. (2009) Does greater adiposity increase blood pressure and hypertension risk?: Mendelian randomization using the FTO/MC4R genotype. Hypertension 54: 84–90.
19. WelshP, PoliseckiE, RobertsonM, JahnS, BuckleyBM, et al. (2010) Unraveling the directional link between adiposity and inflammation: a bidirectional Mendelian randomization approach. J Clin Endocrinol Metab 95: 93–99.
20. GrundySM, CleemanJI, DanielsSR, DonatoKA, EckelRH, et al. (2005) Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 112: 2735–2752.
21. CoxD (1972) Regression models and life-tables (with discussion). J R Stat Soc Series B Stat Methodol 34: 187–220.
22. RossI, RobertG (1996) R: A language for data analysis and graphics. J Comput Graph Stat 5: 299–314.
23. MagiR, MorrisAP (2010) GWAMA: software for genome-wide association meta-analysis. BMC Bioinformatics 11: 288.
24. WaldA (1940) The fitting of straight lines if both variables are subject to error. Ann Math Stat 11: 284–300.
25. PalmerTM, SterneJA, HarbordRM, LawlorDA, SheehanNA, et al. (2011) Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization analyses. Am J Epidemiol 173: 1392–1403.
26. LiH, KilpelainenTO, LiuC, ZhuJ, LiuY, et al. (2012) Association of genetic variation in FTO with risk of obesity and type 2 diabetes with data from 96,551 East and South Asians. Diabetologia 55: 981–995.
27. MeyreD (2012) Is FTO a type 2 diabetes susceptibility gene? Diabetologia 55: 873–876.
28. KenchaiahS, EvansJC, LevyD, WilsonPW, BenjaminEJ, et al. (2002) Obesity and the risk of heart failure. N Engl J Med 347: 305–313.
29. IngelssonE, SundstromJ, ArnlovJ, ZetheliusB, LindL (2005) Insulin resistance and risk of congestive heart failure. JAMA 294: 334–341.
30. WilhelmsenL, RosengrenA, ErikssonH, LappasG (2001) Heart failure in the general population of men—morbidity, risk factors and prognosis. J Intern Med 249: 253–261.
31. MansonJE, ColditzGA, StampferMJ, WillettWC, RosnerB, et al. (1990) A prospective study of obesity and risk of coronary heart disease in women. N Engl J Med 322: 882–889.
32. LauerMS, AndersonKM, KannelWB, LevyD (1991) The impact of obesity on left ventricular mass and geometry. The Framingham Heart Study. JAMA 266: 231–236.
33. VincentHK, PowersSK, StewartDJ, ShanelyRA, DemirelH, et al. (1999) Obesity is associated with increased myocardial oxidative stress. Int J Obes Relat Metab Disord 23: 67–74.
34. ZhouYT, GrayburnP, KarimA, ShimabukuroM, HigaM, et al. (2000) Lipotoxic heart disease in obese rats: implications for human obesity. Proc Natl Acad Sci U S A 97: 1784–1789.
35. World Health Organization (2008) The global burden of disease: 2004 update. Geneva: World Health Organization.
36. RogerVL, GoAS, Lloyd-JonesDM, AdamsRJ, BerryJD, et al. (2011) Heart disease and stroke statistics—2011 update: a report from the American Heart Association. Circulation 123: e18–e209.
37. FuS, YangL, LiP, HofmannO, DickerL, et al. (2011) Aberrant lipid metabolism disrupts calcium homeostasis causing liver endoplasmic reticulum stress in obesity. Nature 473: 528–531.
38. SheehanNA, DidelezV, BurtonPR, TobinMD (2008) Mendelian randomisation and causal inference in observational epidemiology. PLoS Med 5: e177 doi:10.1371/journal.pmed.0050177
39. SmithGD, LawlorDA, HarbordR, TimpsonN, DayI, et al. (2007) Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology. PLoS Med 4: e352 doi:10.1371/journal.pmed.0040352
40. ChurchC, MoirL, McMurrayF, GirardC, BanksGT, et al. (2010) Overexpression of Fto leads to increased food intake and results in obesity. Nat Genet 42: 1086–1092.
41. CecilJE, TavendaleR, WattP, HetheringtonMM, PalmerCN (2008) An obesity-associated FTO gene variant and increased energy intake in children. N Engl J Med 359: 2558–2566.
42. PalmerTM, LawlorDA, HarbordRM, SheehanNA, TobiasJH, et al. (2011) Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 21: 223–242.
43. WillerCJ, SpeliotesEK, LoosRJ, LiS, LindgrenCM, et al. (2009) Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet 41: 25–34.
44. FraylingTM, TimpsonNJ, WeedonMN, ZegginiE, FreathyRM, et al. (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316: 889–894.
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