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Gene-Lifestyle Interaction and Type 2 Diabetes: The EPIC InterAct Case-Cohort Study


Background:
Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.

Methods and Findings:
The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10−4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10−3) and waist circumference (p for interaction  = 7.49×10−9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score.

Conclusions:
The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.

Please see later in the article for the Editors' Summary


Vyšlo v časopise: Gene-Lifestyle Interaction and Type 2 Diabetes: The EPIC InterAct Case-Cohort Study. PLoS Med 11(5): e32767. doi:10.1371/journal.pmed.1001647
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1001647

Souhrn

Background:
Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention.

Methods and Findings:
The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10−4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10−3) and waist circumference (p for interaction  = 7.49×10−9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score.

Conclusions:
The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.

Please see later in the article for the Editors' Summary


Zdroje

1. International Diabetes Federation (2013) IDF diabetes atlas, 6th ed. Brussels: International Diabetes Federation. Available: http://www.idf.org/diabetesatlas/download-book. Accessed 15 April 2014.

2. NeelJV (1962) Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am J Hum Genet 14: 353–362.

3. 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.

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. KnowlerWC, FowlerSE, HammanRF, ChristophiCA, HoffmanHJ, et al. (2009) 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 374: 1677–1686.

6. GilliesCL, AbramsKR, LambertPC, CooperNJ, SuttonAJ, et al. (2007) Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. BMJ 334: 299.

7. McCarthyMI (2010) Genomics, type 2 diabetes, and obesity. N Engl J Med 363: 2339–2350.

8. HivertMF, JablonskiKA, PerreaultL, SaxenaR, McAteerJB, et al. (2011) Updated genetic score based on 34 confirmed type 2 diabetes Loci is associated with diabetes incidence and regression to normoglycemia in the diabetes prevention program. Diabetes 60: 1340–1348.

9. LangenbergC, SharpS, ForouhiNG, FranksPW, SchulzeMB, et al. (2011) Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study. Diabetologia 54: 2272–2282.

10. HaftenbergerM, LahmannPH, PanicoS, GonzalezCA, SeidellJC, et al. (2002) Overweight, obesity and fat distribution in 50- to 64-year-old participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 5(6B): 1147–1162.

11. SpencerEA, RoddamAW, KeyTJ (2004) Accuracy of self-reported waist and hip measurements in 4492 EPIC-Oxford participants. Public Health Nutr 7: 723–727.

12. LangenbergC, SharpSJ, SchulzeMB, RolandssonO, OvervadK, et al. (2012) Long-term risk of incident type 2 diabetes and measures of overall and regional obesity: the EPIC-InterAct case-cohort study. PLoS Med 9: e1001230.

13. RiboliE, HuntKJ, SlimaniN, FerrariP, NoratT, et al. (2002) European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr 5: 1113–1124.

14. The InterAct Consortium (2013) The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors: the EPIC-InterAct study. Diabetologia 56: 60–69.

15. WarehamNJ, JakesRW, RennieKL, SchuitJ, MitchellJ, et al. (2003) Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutr 6: 407–413.

16. The InterActConsortium (2012) Validity of a short questionnaire to assess physical activity in 10 European countries. Eur J Epidemiol 27: 15–25.

17. SlimaniN, DeharvengG, UnwinI, SouthgateDA, VignatJ, et al. (2007) The EPIC nutrient database project (ENDB): a first attempt to standardize nutrient databases across the 10 European countries participating in the EPIC study. Eur J Clin Nutr 61: 1037–1056.

18. TrichopoulouA, Kouris-BlazosA, WahlqvistML, GnardellisC, LagiouP, et al. (1995) Diet and overall survival in elderly people. BMJ 311: 1457–1460.

19. TrichopoulouA, CostacouT, BamiaC, TrichopoulosD (2003) Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med 348: 2599–2608.

20. RomagueraD, GuevaraM, NoratT, LangenbergC, ForouhiNG, et al. (2011) Mediterranean diet and type 2 diabetes risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study: the InterAct project. Diabetes Care 34: 1913–1918.

21. BucklandG, AgudoA, LujanL, JakszynP, Bueno-de-MesquitaHB, et al. (2010) Adherence to a Mediterranean diet and risk of gastric adenocarcinoma within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort study. Am J Clin Nutr 91: 381–390.

22. MorrisAP, VoightBF, TeslovichTM, FerreiraT, SegreAV, et al. (2012) Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet 44: 981–990.

23. KongA, SteinthorsdottirV, MassonG, ThorleifssonG, SulemP, et al. (2009) Parental origin of sequence variants associated with complex diseases. Nature 462: 868–874.

24. NovembreJ, JohnsonT, BrycK, KutalikZ, BoykoAR, et al. (2008) Genes mirror geography within Europe. Nature 456: 98–101.

25. ManicaA, PrugnolleF, BallouxF (2005) Geography is a better determinant of human genetic differentiation than ethnicity. Hum Genet 118: 366–371.

26. The InterAct Consortium (2012) Physical activity reduces the risk of incident type 2 diabetes in general and in abdominally lean and obese men and women: the EPIC-InterAct Study. Diabetologia 55: 1944–1952.

27. de Miguel-YanesJM, ShraderP, PencinaMJ, FoxCS, ManningAK, et al. (2011) Genetic risk reclassification for type 2 diabetes by age below or above 50 years using 40 type 2 diabetes risk single nucleotide polymorphisms. Diabetes Care 34: 121–125.

28. BuijsseB, SimmonsRK, GriffinSJ, SchulzeMB (2011) Risk assessment tools for identifying individuals at risk of developing type 2 diabetes. Epidemiol Rev 33: 46–62.

29. LyssenkoV, JonssonA, AlmgrenP, PulizziN, IsomaaB, et al. (2008) Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med 359: 2220–2232.

30. MeigsJB, ShraderP, SullivanLM, McAteerJB, FoxCS, et al. (2008) Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 359: 2208–2219.

31. TalmudPJ, HingoraniAD, CooperJA, MarmotMG, BrunnerEJ, et al. (2010) Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ 340: b4838.

32. GloynAL, PearsonER, AntcliffJF, ProksP, BruiningGJ, et al. (2004) Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med 350: 1838–1849.

33. PearsonER, FlechtnerI, NjolstadPR, MaleckiMT, FlanaganSE, et al. (2006) Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med 355: 467–477.

34. FlorezJC, JablonskiKA, BayleyN, PollinTI, de BakkerPI, et al. (2006) TCF7L2 polymorphisms and progression to diabetes in the Diabetes Prevention Program. N Engl J Med 355: 241–250.

35. MooreAF, JablonskiKA, MasonCC, McAteerJB, ArakakiRF, et al. (2009) The association of ENPP1 K121Q with diabetes incidence is abolished by lifestyle modification in the diabetes prevention program. J Clin Endocrinol Metab 94: 449–455.

36. MooreAF, JablonskiKA, McAteerJB, SaxenaR, PollinTI, et al. (2008) Extension of type 2 diabetes genome-wide association scan results in the diabetes prevention program. Diabetes 57: 2503–2510.

37. OrozcoG, IoannidisJP, MorrisA, ZegginiE (2012) Sex-specific differences in effect size estimates at established complex trait loci. Int J Epidemiol 41: 1376–1382.

38. PerryJR, VoightBF, YengoL, AminN, DupuisJ, et al. (2012) Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases. PLoS Genet 8: e1002741.

39. BritoEC, LyssenkoV, RenstromF, BerglundG, NilssonPM, et al. (2009) Previously associated type 2 diabetes variants may interact with physical activity to modify the risk of impaired glucose regulation and type 2 diabetes: a study of 16,003 Swedish adults. Diabetes 58: 1411–1418.

40. QiL, CornelisMC, ZhangC, van DamRM, HuFB (2009) Genetic predisposition, Western dietary pattern, and the risk of type 2 diabetes in men. Am J Clin Nutr 89: 1453–1458.

41. SonestedtE, LyssenkoV, EricsonU, GullbergB, WirfaltE, et al. (2012) Genetic variation in the glucose-dependent insulinotropic polypeptide receptor modifies the association between carbohydrate and fat intake and risk of type 2 diabetes in the Malmo Diet and Cancer cohort. J Clin Endocrinol Metab 97: E810–E818.

42. HindyG, SonestedtE, EricsonU, JingXJ, ZhouY, et al. (2012) Role of TCF7L2 risk variant and dietary fibre intake on incident type 2 diabetes. Diabetologia 55: 2646–2654.

43. CornelisMC, QiL, KraftP, HuFB (2009) TCF7L2, dietary carbohydrate, and risk of type 2 diabetes in US women. Am J Clin Nutr 89: 1256–1262.

44. PallaL, HigginsJP, WarehamNJ, SharpSJ (2010) Challenges in the use of literature-based meta-analysis to examine gene-environment interactions. Am J Epidemiol 171: 1225–1232.

45. CornelisMC, TchetgenEJ, LIangL, QiL, ChatterjeeN, et al. (2012) Gene-environment interactions in genome-wide association studies: a comparative study of tests applied to empirical studies of type 2 diabetes. Am J Epidemiol 175: 191–202.

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