#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes: The EPIC-InterAct case-cohort study


Fumiaki Imamura and colleagues reveal profiles of plasma phospholipid fatty acids that are associated with risk of type 2 diabetes using data from the EPIC cohort.


Vyšlo v časopise: A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes: The EPIC-InterAct case-cohort study. PLoS Med 14(10): e32767. doi:10.1371/journal.pmed.1002409
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1002409

Souhrn

Fumiaki Imamura and colleagues reveal profiles of plasma phospholipid fatty acids that are associated with risk of type 2 diabetes using data from the EPIC cohort.


Zdroje

1. Fessler MB, Rudel LL, Brown JM. Toll-like receptor signaling links dietary fatty acids to the metabolic syndrome. Curr Opin Lipidol. 2009;20(5):379–85. doi: 10.1097/MOL.0b013e32832fa5c4 19625959

2. Jump DB, Tripathy S, Depner CM. fatty acid–regulated transcription factors in the liver. Annu Rev Nutr. 2013;33(1):249–69. doi: 10.1146/annurev-nutr-071812-161139 23528177

3. Hodson L, Skeaff CM, Fielding BA. Fatty acid composition of adipose tissue and blood in humans and its use as a biomarker of dietary intake. Prog Lipid Res. 2008;47(5):348–80. doi: 10.1016/j.plipres.2008.03.003 18435934

4. Baylin A, Campos H. The use of fatty acid biomarkers to reflect dietary intake. Curr Opin Lipidol. 2006;17(1):22–7. 16407712

5. Wahli W, Michalik L. PPARs at the crossroads of lipid signaling and inflammation. Trends Endocrinol Metab. 2012;23(7):351–63. doi: 10.1016/j.tem.2012.05.001 22704720

6. Mozaffarian D, Wu JHY. Omega-3 fatty acids and cardiovascular disease: effects on risk factors, molecular pathways, and clinical events. J Am Coll Cardiol. 2011;58(20):2047–67. doi: 10.1016/j.jacc.2011.06.063 22051327

7. Borkman M, Storlien LH, Pan DA, Jenkins AB, Chisholm DJ, Campbell L V. The relation between insulin sensitivity and the fatty-acid composition of skeletal-muscle phospholipids. N Engl J Med. 1993;328(4):238–44. doi: 10.1056/NEJM199301283280404 8418404

8. Poitout V, Robertson RP. Glucolipotoxicity: fuel excess and β-cell dysfunction. Endocr Rev. 2008;29(3):351–66. doi: 10.1210/er.2007-0023 18048763

9. Rhee EP, Cheng S, Larson MG, Walford GA, Lewis GD, McCabe E, et al. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans. J Clin Invest. 2011;121(4):1402–11. doi: 10.1172/JCI44442 21403394

10. Vessby B, Lithell H. Interruption of long-term lipid-lowering treatment with bezafibrate in hypertriglyceridaemic patients. Effects on lipoprotein composition, lipase activities and the plasma lipid fatty acid spectrum. Atherosclerosis. 1990;82(1–2):137–43. doi: 10.1016/0021-9150(90)90152-9 2360915

11. King IB, Lemaitre RN, Kestin M. Effect of a low-fat diet on fatty acid composition in red cells, plasma phospholipids, and cholesterol esters: investigation of a biomarker of total fat intake. Am J Clin Nutr. 2006;83(2):227–36. 16469979

12. Warensjö E, Sundström J, Lind L, Vessby B, Warensjo E, Sundstrom J. Factor analysis of fatty acids in serum lipids as a measure of dietary fat quality in relation to the metabolic syndrome in men. Am J Clin Nutr. 2006;84(2):442–8. 16895896

13. Anderson SG, Sanders TAB, Cruickshank JK. Plasma fatty acid composition as a predictor of arterial stiffness and mortality. Hypertension. 2009;53(5):839–45. doi: 10.1161/HYPERTENSIONAHA.108.123885 19307467

14. Dahm CC, Gorst-Rasmussen A, Jakobsen MU, Schmidt EB, Tjønneland A, Sørensen TIA, et al. Adipose tissue fatty acid patterns and changes in anthropometry: a cohort study. PLoS ONE. 2011;6(7):e22587. doi: 10.1371/journal.pone.0022587 21811635

15. Imamura F, Lemaitre RN, King IB, Song X, Lichtenstein AH, Matthan NR, et al. Novel circulating fatty acid patterns and risk of cardiovascular disease: the Cardiovascular Health Study. Am J Clin Nutr. 2012;96(6):1252–61. doi: 10.3945/ajcn.112.039990 23097270

16. Forouhi NG, Koulman A, Sharp SJ, Imamura F, Kröger J, Schulze MB, et al. Differences in the prospective association between individual plasma phospholipid saturated fatty acids and incident type 2 diabetes: the EPIC-InterAct case-cohort study. Lancet Diab Endocrinol. 2014;2(10):810–8. doi: 10.1016/S2213-8587(14)70146-9 25107467

17. Forouhi NG, Imamura F, Sharp SJ, Koulman A, Schulze MB, Zheng J, et al. Association of plasma phospholipid n-3 and n-6 polyunsaturated fatty acids with type 2 diabetes: the EPIC-InterAct case-cohort study. PLoS Med. 2016;13(7):e1002094. doi: 10.1371/journal.pmed.1002094 27434045

18. InterAct Consortium. 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. 2011;54(9):2272–82. doi: 10.1007/s00125-011-2182-9 21717116

19. Prentice RL. A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika. 1986;73(1):1–11.

20. Wang L, Summerhill K, Rodriguez-Canas C, Mather I, Patel P, Eiden M, et al. Development and validation of a robust automated analysis of plasma phospholipid fatty acids for metabolic phenotyping of large epidemiological studies. Genome Med. 2013;5(4):39. doi: 10.1186/gm443 23618465

21. Wareham NJ, Jakes RW, Rennie KL, Schuit J, Mitchell J, Hennings S, et al. 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. 2003;6(4):407–13. doi: 10.1079/PHN2002439 12795830

22. Margetts BM, Pietinen P. European Prospective Investigation into Cancer and Nutrition: validity studies on dietary assessment methods. Int J Epidemiol. 1997;26(Suppl 1):S1–5.

23. Slimani N, Deharveng G, Unwin I, Southgate DAT, Vignat J, Skeie G, et al. 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. 2007;61(9):1037–56. doi: 10.1038/sj.ejcn.1602679 17375121

24. Scott RA, Fall T, Pasko D, Barker A, Sharp SJ, Arriola L, et al. Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity. Diabetes. 2014;63(12):4378–87. doi: 10.2337/db14-0319 24947364

25. Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197–206. doi: 10.1038/nature14177 25673413

26. Ehrenberg ASC. Some questions about factor analysis. Statistician. 1962;12(3):191–208.

27. Vigneau E, Qannari EM. Clustering of variables around latent components. Commun Stat Simul Comput. 2003;32(4):1131–50. doi: 10.1081/SAC-120023882

28. Riley RD, Higgins JPT, Deeks JJ. Interpretation of random effects meta-analyses. BMJ. 2011;342:d549. doi: 10.1136/bmj.d549 21310794

29. Durrleman S, Simon R. Flexible regression models with cubic splines. Stat Med. 1989;8(5):551–61. 2657958

30. Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. doi: 10.1136/bmj.b2393 19564179

31. Efron B, Tibshirani RJ. Cross-validation and other estimates of prediction error. In: Efron B, Tibshirani RJ, editors. An introduction to the bootstrap. Boca Raton (Florida): Chapman & Hall/CRC, Taylor & Francix Group; 1994. pp. 237–57.

32. Spiegelman D, Hertzmark E. Easy SAS calculations for risk or prevalence ratios and differences. Am J Epidemiol. 2005;162(3):199–200. doi: 10.1093/aje/kwi188 15987728

33. Prati D, Taioli E, Zanella A, Della Torre E, Butelli S, Del Vecchio E, et al. Updated definitions of healthy ranges for serum alanine aminotransferase levels. Ann Intern Med. 2002;137(1):1–10. doi: 10.7326/0003-4819-137-1-200207020-00006 12093239

34. Maldonado G, Greenland S. simulation study of confounder-selection strategies. Am J Epidemiol. 1993;138(11):923–36. 8256780

35. Jakobsson A, Jörgensen JA, Jacobsson A. Differential regulation of fatty acid elongation enzymes in brown adipocytes implies a unique role for Elovl3 during increased fatty acid oxidation. Am J Physiol Endocrinol Metab. 2005;289(4):E517–26. doi: 10.1152/ajpendo.00045.2005 15855229

36. Brown JM, Chung S, Sawyer JK, Degirolamo C, Alger HM, Nguyen T, et al. Inhibition of stearoyl-coenzyme A desaturase 1 dissociates insulin resistance and obesity from atherosclerosis. Circulation. 2008;118(14):1467–75. doi: 10.1161/CIRCULATIONAHA.108.793182 18794388

37. Kersten S, Seydoux J, Peters JM, Gonzalez FJ, Desvergne B, Wahli W. Peroxisome proliferator-activated receptor alpha mediates the adaptive response to fasting. J Clin Invest. 1999;103(11):1489–98. doi: 10.1172/JCI6223 10359558

38. Fu S, Watkins SM, Hotamisligil GS. The role of endoplasmic reticulum in hepatic lipid homeostasis and stress signaling. Cell Metab. 2012;15(5):623–34. doi: 10.1016/j.cmet.2012.03.007 22560215

39. Sevastianova K, Santos A, Kotronen A, Hakkarainen A, Makkonen J, Silander K, et al. Effect of short-term carbohydrate overfeeding and long-term weight loss on liver fat in overweight humans. Am J Clin Nutr. 2012;96(4):727–34. doi: 10.3945/ajcn.112.038695 22952180

40. Lotta LA, Sharp SJ, Burgess S, Perry JRB, Stewart ID, Willems SM, et al. Association between low-density lipoprotein cholesterol–lowering genetic variants and risk of type 2 diabetes. JAMA. 2016;316(13):1383. doi: 10.1001/jama.2016.14568 27701660

41. Lemaitre RN, King IB, Rice K, McKnight B, Sotoodehnia N, Rea TD, et al. Erythrocyte very long-chain saturated fatty acids associated with lower risk of incident sudden cardiac arrest. Prostaglandins Leukot Essent Fatty Acids. 2014;91(4):149–53. doi: 10.1016/j.plefa.2014.07.010 25107579

42. Krachler B, Norberg M, Eriksson JW, Hallmans G, Johansson I, Vessby B, et al. Fatty acid profile of the erythrocyte membrane preceding development of type 2 diabetes mellitus. Nutr Metab Cardiovasc Dis. 2008;18(7):503–10. doi: 10.1016/j.numecd.2007.04.005 18042359

43. Grösch S, Schiffmann S, Geisslinger G. Chain length-specific properties of ceramides. Prog Lipid Res. 2012;51(1):50–62. doi: 10.1016/j.plipres.2011.11.001 22133871

44. Abdullah MMH, Cyr A, Lépine M-C, Labonté M-È, Couture P, Jones PJH, et al. Recommended dairy product intake modulates circulating fatty acid profile in healthy adults: a multi-centre cross-over study. Br J Nutr. 2015;113(3):435–44. doi: 10.1017/S0007114514003894 25609231

45. Weitkunat K, Schumann S, Nickel D, Hornemann S, Petzke KJ, Schulze MB, et al. Odd-chain fatty acids as a biomarker for dietary fiber intake: a novel pathway for endogenous production from propionate. Am J Clin Nutr. 2017;105(6):1544–51. doi: 10.3945/ajcn.117.152702 28424190

46. Jenkins BJ, Seyssel K, Chiu S, Pan P-H, Lin S-Y, Stanley E, et al. Odd chain fatty acids; new insights of the relationship between the gut microbiota, dietary intake, biosynthesis and glucose intolerance. Sci Rep. 2017;7:44845. doi: 10.1038/srep44845 28332596

47. Corrao G, Bagnardi V, Zambon A, La Vecchia C. A meta-analysis of alcohol consumption and the risk of 15 diseases. Prev Med. 2004;38(5):613–9. doi: 10.1016/j.ypmed.2003.11.027 15066364

48. Murase T, Misawa K, Minegishi Y, Aoki M, Ominami H, Suzuki Y, et al. Coffee polyphenols suppress diet-induced body fat accumulation by downregulating SREBP-1c and related molecules in C57BL/6J mice. Am J Physiol Endocrinol Metab. 2011;300(1):E122–33. doi: 10.1152/ajpendo.00441.2010 20943752

49. Ding M, Bhupathiraju SN, Chen M, van Dam RM, Hu FB. Caffeinated and decaffeinated coffee consumption and risk of type 2 diabetes: a systematic review and a dose-response meta-analysis. Diabetes Care. 2014;37(2):569–86. doi: 10.2337/dc13-1203 24459154

50. Jacobs S, Kroger J, Floegel A, Boeing H, Drogan D, Pischon T, et al. Evaluation of various biomarkers as potential mediators of the association between coffee consumption and incident type 2 diabetes in the EPIC-Potsdam Study. Am J Clin Nutr. 2014;100(3):891–900. doi: 10.3945/ajcn.113.080317 25057154

51. Vinknes KJ, Elshorbagy AK, Nurk E, Drevon CA, Gjesdal CG, Tell GS, et al. Plasma stearoyl-CoA desaturase indices: association with lifestyle, diet, and body composition. Obesity. 2013;21(3):E294–302. doi: 10.1002/oby.20011 23404690

52. Imamura F, Micha R, Wu JHY, de Oliveira Otto MC, Otite FO, Abioye AI, et al. Effects of saturated fat, polyunsaturated fat, monounsaturated fat, and carbohydrate on glucose-insulin homeostasis: a systematic review and meta-analysis of randomised controlled feeding trials. PLoS Med. 2016;13(7):e1002087. doi: 10.1371/journal.pmed.1002087 27434027

53. Barclay AW, Petocz P, McMillan-Price J, Flood VM, Prvan T, Mitchell P, et al. Glycemic index, glycemic load, and chronic disease risk—a meta-analysis of observational studies. Am J Clin Nutr. 2008;87(3):627–37. 18326601

Štítky
Interné lekárstvo

Článok vyšiel v časopise

PLOS Medicine


2017 Číslo 10
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Získaná hemofilie - Povědomí o nemoci a její diagnostika
nový kurz

Eozinofilní granulomatóza s polyangiitidou
Autori: doc. MUDr. Martina Doubková, Ph.D.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#