#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Childhood adiposity and risk of type 1 diabetes: A Mendelian randomization study


Tove Fall and colleagues, using a Mendelian randomization study, show support for the link between childhood adiposity and increased risk of type 1 diabetes.


Vyšlo v časopise: Childhood adiposity and risk of type 1 diabetes: A Mendelian randomization study. PLoS Med 14(8): e32767. doi:10.1371/journal.pmed.1002362
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1002362

Souhrn

Tove Fall and colleagues, using a Mendelian randomization study, show support for the link between childhood adiposity and increased risk of type 1 diabetes.


Zdroje

1. The Diamond Project Group. Incidence and trends of childhood Type 1 diabetes worldwide 1990–1999. Diabetic Medicine. 2006;23(8):857–66. doi: 10.1111/j.1464-5491.2006.01925.x 16911623

2. Patterson CC, Gyürüs E, Rosenbauer J, Cinek O, Neu A, Schober E, et al. Trends in childhood type 1 diabetes incidence in Europe during 1989–2008: evidence of non-uniformity over time in rates of increase. Diabetologia. 2012;55(8):2142–7. doi: 10.1007/s00125-012-2571-8 22638547

3. Christoffersson G, Rodriguez-Calvo T, von Herrath M. Recent advances in understanding Type 1 Diabetes. F1000Research. 2016;5:F1000 Faculty Rev-110. doi: 10.12688/f1000research.7356.1 26918165

4. Ziegler AG, Rewers M, Simell O, Simell T, Lempainen J, Steck A, et al. Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. JAMA. 2013;309(23):2473–9. doi: 10.1001/jama.2013.6285 23780460.

5. Insel RA, Dunne JL, Atkinson MA, Chiang JL, Dabelea D, Gottlieb PA, et al. Staging Presymptomatic Type 1 Diabetes: A Scientific Statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care. 2015;38(10):1964–74. doi: 10.2337/dc15-1419 26404926

6. Nerup J, Andersen OO, Bendixen G, Egeberg J, Gunnarsson R, Kromann H, et al. Cell-mediated Immunity in Diabetes Mellitus. Proceedings of the Royal Society of Medicine. 1974;67(6 Pt 1):506–13. 4604192

7. Lieberman SM, DiLorenzo TP. A comprehensive guide to antibody and T-cell responses in type 1 diabetes. Tissue Antigens. 2003;62(5):359–77. doi: 10.1034/j.1399-0039.2003.00152.x 14617043

8. Atkinson MA, von Herrath M, Powers AC, Clare-Salzler M. Current concepts on the pathogenesis of type 1 diabetes—considerations for attempts to prevent and reverse the disease. Diabetes Care. 2015;38(6):979–88. doi: 10.2337/dc15-0144 25998290.

9. Skog O, Korsgren S, Melhus A, Korsgren O. Revisiting the notion of type 1 diabetes being a T-cell-mediated autoimmune disease. Curr Opin Endocrinol Diabetes Obes. 2013;20(2):118–23. doi: 10.1097/MED.0b013e32835edb89 23422243.

10. Condon JJ. A study of diabetes mellitus within a large sample of Australian twins. Twin research and human genetics. 11(1):28–40. doi: 10.1375/twin.11.1.28 18251672

11. Baum J, Ounsted M, Smith M. Letter: Weight gain in infancy and subsequent development of diabetes mellitus in childhood. The Lancet (British edition). 2(7940):866.

12. Wilkin TJ. The accelerator hypothesis: weight gain as the missing link between Type I and Type II diabetes. Diabetologia. 2001;44(7):914–22. doi: 10.1007/s001250100548 11508279

13. Dahlquist G. Can we slow the rising incidence of childhood-onset autoimmune diabetes? The overload hypothesis. Diabetologia. 2006;49(1):20–4. doi: 10.1007/s00125-005-0076-4 16362279

14. Raj SM, Howson JM, Walker NM, Cooper JD, Smyth DJ, Field SF, et al. No association of multiple type 2 diabetes loci with type 1 diabetes. Diabetologia. 2009;52(10):2109–16. doi: 10.1007/s00125-009-1391-y 19455305.

15. Lobstein T, Baur L, Uauy R. Obesity in children and young people: a crisis in public health. Obesity Reviews. 2004;5:4–85. doi: 10.1111/j.1467-789X.2004.00133.x 15096099

16. United Nations Children’s Fund, World Health Organization, The World Bank. UNICEF-WHO-World Bank Joint Child Malnutrition Estimates. UNICEF, New York; WHO, Geneva; The World Bank, Washington, DC. 2012.

17. Liston A, Todd JA, Lagou V. Beta-Cell Fragility As a Common Underlying Risk Factor in Type 1 and Type 2 Diabetes. Trends Mol Med. 2017;23(2):181–94. doi: 10.1016/j.molmed.2016.12.005 28117227.

18. Copley VR, Bray C. Changes in children’s body mass index in England between 2006/7 and 2014/15: National Child Measurement Programme. London: Public Health England. October 2016

19. Lamb MM, Yin X, Zerbe GO, Klingensmith GJ, Dabelea D, Fingerlin TE, et al. Height growth velocity, islet autoimmunity and type 1 diabetes development: the Diabetes Autoimmunity Study in the Young. Diabetologia. 2009;52(10):2064–71. doi: 10.1007/s00125-009-1428-2 19547949

20. O’Connell MA, Donath S, Cameron FJ. Major increase in Type 1 diabetes—no support for the Accelerator Hypothesis. Diabetic Medicine. 2007;24(8):920–3. doi: 10.1111/j.1464-5491.2007.02203.x 17535289

21. Giménez M, Aguilera E, Castell C, de Lara N, Nicolau J, Conget I. Relationship Between BMI and Age at Diagnosis of Type 1 Diabetes in a Mediterranean Area in the Period of 1990–2004. Diabetes Care. 2007;30(6):1593–5. doi: 10.2337/dc06-2578 17372154

22. Porter JR, Barrett TG. Braking the Accelerator Hypothesis? Diabetologia. 2004;47(2):352–3. doi: 10.1007/s00125-003-1291-5 14666370

23. Verbeeten KC, Elks CE, Daneman D, Ong KK. Association between childhood obesity and subsequent Type 1 diabetes: a systematic review and meta-analysis. Diabetic Medicine. 2011;28(1):10–8. doi: 10.1111/j.1464-5491.2010.03160.x 21166841

24. Harder T, Roepke K, Diller N, Stechling Y, Dudenhausen JW, Plagemann A. Birth Weight, Early Weight Gain, and Subsequent Risk of Type 1 Diabetes: Systematic Review and Meta-Analysis. American Journal of Epidemiology. 2009;169(12):1428–36. doi: 10.1093/aje/kwp065 19363100

25. Ferrara CT, Geyer SM, Liu YF, Evans-Molina C, Libman IM, Besser R, et al. Excess BMI in Childhood: A Modifiable Risk Factor for Type 1 Diabetes Development. Diabetes Care. 2017. doi: 10.2337/dc16-2331 28202550.

26. Burgess S, Scott RA, Timpson NJ, Davey Smith G, Thompson SG, Epic- InterAct Consortium. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. European Journal of Epidemiology. 2015;30(7):543–52. doi: 10.1007/s10654-015-0011-z 25773750

27. Ference BA, Robinson JG, Brook RD, Catapano AL, Chapman MJ, Neff DR, et al. Variation in PCSK9 and HMGCR and Risk of Cardiovascular Disease and Diabetes. New England Journal of Medicine. 2016;375(22):2144–53. doi: 10.1056/NEJMoa1604304 27959767.

28. Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet. 2012;380(9841):572–80. Epub 2012/05/23. doi: 10.1016/S0140-6736(12)60312-2 22607825.

29. Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG. Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants. Epidemiology. Published Online: September 26, 2016; Published Ahead of Print. doi: 10.1097/ede.0000000000000559 27749700

30. Felix JF, Bradfield JP, Monnereau C, van der Valk RJP, Stergiakouli E, Chesi A, et al. Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index. Human Molecular Genetics. 2016;25(2):389–403. doi: 10.1093/hmg/ddv472 26604143

31. 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.

32. Horikoshi M, Beaumont RN, Day FR, Warrington NM, Kooijman MN, Fernandez-Tajes J, et al. Genome-wide associations for birth weight and correlations with adult disease. Nature. 2016;538(7624):248–52. doi: 10.1038/nature19806 27680694.

33. The Tobacco and Genetics Consortium. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nature genetics. 2010;42(5):441–7. doi: 10.1038/ng.571 20418890

34. Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533(7604):539–42. doi: 10.1038/nature17671 27225129.

35. Cooper NJ, Wallace C, Burren OS, Cutler A, Walker N, Todd JA. Type 1 diabetes genome-wide association analysis with imputation identifies five new risk regions. bioRxiv. 2017. doi: 10.1101/120022

36. Barrett JC, Clayton DG, Concannon P, Akolkar B, Cooper JD, Erlich HA, et al. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature genetics. 2009;41(6):703–7. doi: 10.1038/ng.381 19430480

37. Barrett JC, Clayton D, Concannon P, Akolkar B, Cooper JD, Erlich HA, et al. Genome-wide association study and meta-analysis finds over 40 loci affect risk of type 1 diabetes. Nature genetics. 2009;41(6):703–7. doi: 10.1038/ng.381 19430480

38. The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447(7145):661–78. doi: 10.1038/nature05911 17554300

39. Cooper N. Data from Type 1 diabetes genome-wide association analysis with imputation identifies five new risk regions. (2017) Dryad Digital Repository. Openly available via http://dx.doi.org/10.5061/dryad.ns8q3.

40. Wellcome Trust Case Control C. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447(7145):661–78. doi: 10.1038/nature05911 17554300.

41. Felix JF, Bradfield JP, Monnereau C, van der Valk RJ, Stergiakouli E, Chesi A, et al. Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index. Hum Mol Genet. 2016;25(2):389–403. doi: 10.1093/hmg/ddv472 26604143.

42. Burgess S, Scott RA, Timpson NJ, Davey Smith G, Thompson SG, Consortium E-I. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015;30(7):543–52. doi: 10.1007/s10654-015-0011-z 25773750.

43. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International Journal of Epidemiology. 2015;44(2):512–25. doi: 10.1093/ije/dyv080 26050253

44. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria. 2015. https://www.R-project.org/.

45. Soetaert K. Shape: Functions for Plotting Graphical Shapes, Colors. R package version 1.4.2. 2014. https://CRAN.R-project.org/package=shape.

46. Schwarzer G. Meta: General Package for Meta-Analysis. R package version 4.3–2. 2015.https://CRAN.R-project.org/package=meta.

47. Harrell F, with contributions from Dupont C and many others. Hmisc: Harrell Miscellaneous. R package version 4.0–0. 2016. https://CRAN.R-project.org/package=Hmisc.

48. Burgess S, Dudbridge F, Thompson SG. Re: "Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects". Am J Epidemiol. 2015;181(4):290–1. doi: 10.1093/aje/kwv017 25660081.

49. Staley JR, Blackshaw J, Kamat MA, Ellis S, Surendran P, Sun BB, et al. PhenoScanner: a database of human genotype-phenotype associations. Bioinformatics. 2016;32(20):3207–9. doi: 10.1093/bioinformatics/btw373 27318201.

50. Group ESS. Rapid early growth is associated with increased risk of childhood type 1 diabetes in various European populations. Diabetes Care. 2002;25(10):1755–60. 12351473.

51. Ljungkrantz M, Ludvigsson J, Samuelsson U. Type 1 diabetes: increased height and weight gains in early childhood. Pediatr Diabetes. 2008;9(3 Pt 2):50–6. doi: 10.1111/j.1399-5448.2007.00360.x 18540867.

52. Yeste D, Vendrell J, Tomasini R, Broch M, Gussinye M, Megia A, et al. Interleukin-6 in obese children and adolescents with and without glucose intolerance. Diabetes Care. 2007;30(7):1892–4. doi: 10.2337/dc06-2289 17416792.

53. Hotamisligil GS, Arner P, Caro JF, Atkinson RL, Spiegelman BM. Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. Journal of Clinical Investigation. 1995;95(5):2409–15. doi: 10.1172/JCI117936 7738205

54. Versini M, Jeandel P-Y, Rosenthal E, Shoenfeld Y. Obesity in autoimmune diseases: Not a passive bystander. Autoimmunity Reviews. 2014;13(9):981–1000. doi: 10.1016/j.autrev.2014.07.001 25092612

55. Maffei M, Halaas J, Ravussin E, Pratley RE, Lee GH, Zhang Y, et al. Leptin levels in human and rodent: measurement of plasma leptin and ob RNA in obese and weight-reduced subjects. Nat Med. 1995;1(11):1155–61. 7584987.

56. Matarese G, Sanna V, Lechler RI, Sarvetnick N, Fontana S, Zappacosta S, et al. Leptin Accelerates Autoimmune Diabetes in Female NOD Mice. Diabetes. 2002;51(5):1356. 11978630

57. Wijesekara N, Krishnamurthy M, Bhattacharjee A, Suhail A, Sweeney G, Wheeler MB. Adiponectin-induced ERK and Akt Phosphorylation Protects against Pancreatic Beta Cell Apoptosis and Increases Insulin Gene Expression and Secretion. The Journal of Biological Chemistry. 2010;285(44):33623–31. doi: 10.1074/jbc.M109.085084 20709750

58. Pang TTL, Chimen M, Goble E, Dixon N, Benbow A, Eldershaw SE, et al. Inhibition of Islet Immunoreactivity by Adiponectin Is Attenuated in Human Type 1 Diabetes. The Journal of Clinical Endocrinology & Metabolism. 2013;98(3):E418–E28. doi: 10.1210/jc.2012-3516 23386639.

59. The Diabetes Control Complications Trial Research Group. The Effect of Intensive Treatment of Diabetes on the Development and Progression of Long-Term Complications in Insulin-Dependent Diabetes Mellitus. New England Journal of Medicine. 1993;329(14):977–86. doi: 10.1056/NEJM199309303291401 8366922.

60. Khashan AS, Kenny LC, Lundholm C, Kearney PM, Gong T, McNamee R, et al. Gestational Age and Birth Weight and the Risk of Childhood Type 1 Diabetes: A Population-Based Cohort and Sibling Design Study. Diabetes Care. 2015;38(12):2308–15. doi: 10.2337/dc15-0897 26519334.

61. Calixto O-J, Anaya J-M. Socioeconomic status. The relationship with health and autoimmune diseases. Autoimmunity Reviews. 2014;13(6):641–54. doi: 10.1016/j.autrev.2013.12.002 24418307

62. Behl M, Rao D, Aagaard K, Davidson TL, Levin ED, Slotkin TA, et al. Evaluation of the Association between Maternal Smoking, Childhood Obesity, and Metabolic Disorders: A National Toxicology Program Workshop Review. Environmental Health Perspectives. 2013;121(2):170–80. doi: 10.1289/ehp.1205404 23232494

63. Oikari S, Makkonen K, Deen AJ, Tyni I, Kärnä R, Tammi RH, et al. Hexosamine biosynthesis in keratinocytes: roles of GFAT and GNPDA enzymes in the maintenance of UDP-GlcNAc content and hyaluronan synthesis. Glycobiology. 2016;26(7):710–22. doi: 10.1093/glycob/cww019 26887390

64. Wiemerslage L, Gohel PA, Maestri G, Hilmarsson TG, Mickael M, Fredriksson R, et al. The Drosophila ortholog of TMEM18 regulates insulin and glucagon-like signaling. Journal of Endocrinology. 2016;229(3):233–43. doi: 10.1530/JOE-16-0040 27029472

65. Wu L, Shen C, Seed Ahmed M, Östenson CG, Gu HF. Adenylate cyclase 3: a new target for anti-obesity drug development. Obesity Reviews. 2016;17(9):907–14. doi: 10.1111/obr.12430 27256589

66. Wang Z, Li V, Chan GCK, Phan T, Nudelman AS, Xia Z, et al. Adult Type 3 Adenylyl Cyclase–Deficient Mice Are Obese. PLoS ONE. 2009;4(9):e6979. doi: 10.1371/journal.pone.0006979 19750222

Štítky
Interné lekárstvo

Článok vyšiel v časopise

PLOS Medicine


2017 Číslo 8
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#