Application of a Genetic Risk Score to Racially Diverse Type 1 Diabetes Populations Demonstrates the Need for Diversity in Risk-Modeling

Scientific Reports

Volumn 8, Issue 1, 2018, Pages

  Perry, Daniel J ^a   Wasserfall, Clive H ^a   Oram, Richard A ^b,c   Williams, Mackenzie D ^a   Posgai, Amanda ^a   Muir, Andrew B ^d   Haller, Michael J ^e   Schatz, Desmond A ^e   Wallet, Mark A ^a   Mathews, Clayton E ^a   Atkinson, Mark A ^a,e   Brusko, Todd M ^a  

^a Hepatology and Nutrition   (United States)

^b UNIVERSITY OF EXETER MEDICAL SCHOOL   (United Kingdom)

^c The National Institute for Health Research Health Protection Research Unit in Blood Borne and Sexually Transmitted Infections at University College London in partnership with UK Health Security Agency   (United Kingdom)

^d EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e NONE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOANTIBODY; HLA DQ ANTIGEN; HLA DR3 ANTIGEN; HLA DR4 ANTIGEN;

ADOLESCENT; ADULT; BLOOD; CASE CONTROL STUDY; CHILD; ETHNOLOGY; FEMALE; FLORIDA; GENETIC PREDISPOSITION; GENETICS; HUMAN; IMMUNOLOGY; INSULIN DEPENDENT DIABETES MELLITUS; MALE; POPULATION GENETICS; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT; THEORETICAL MODEL; YOUNG ADULT;

ADOLESCENT; ADULT; AUTOANTIBODIES; CASE-CONTROL STUDIES; CHILD; DIABETES MELLITUS, TYPE 1; FEMALE; FLORIDA; GENETIC PREDISPOSITION TO DISEASE; GENETICS, POPULATION; HLA-DQ ANTIGENS; HLA-DR3 ANTIGEN; HLA-DR4 ANTIGEN; HUMANS; MALE; MODELS, THEORETICAL; RISK ASSESSMENT; ROC CURVE; YOUNG ADULT;

EID: 85044216503     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-018-22574-5     Document Type: Article

References (49)

1. Noble, J. A. Immunogenetics of type 1 diabetes: A comprehensive review. J Autoimmun 64, 101-112, https://doi.org/10.1016/j.jaut.2015.07.014 (2015).
2. Pociot, F. et al. Genetics of type 1 diabetes: what's next? Diabetes 59, 1561-1571, https://doi.org/10.2337/db10-0076 (2010).
3. Noble, J. A. et al. The role of HLA class II genes in insulin-dependent diabetes mellitus: molecular analysis of 180 Caucasian, multiplex families. Am J Hum Genet 59, 1134-1148 (1996).
4. Risch, N. Assessing the role of HLA-linked and unlinked determinants of disease. Am J Hum Genet 40, 1-14 (1987).
5. Lambert, A. P. et al. Absolute risk of childhood-onset type 1 diabetes defined by human leukocyte antigen class II genotype: a population-based study in the United Kingdom. J Clin Endocrinol Metab 89, 4037-4043, https://doi.org/10.1210/jc.2003-032084 (2004).
6. Leslie, R. D., Palmer, J., Schloot, N. C. & Lernmark, A. Diabetes at the crossroads: relevance of disease classification to pathophysiology and treatment. Diabetologia 59, 13-20, https://doi.org/10.1007/s00125-015-3789-z (2016).
7. Buzzetti, R., Zampetti, S. & Maddaloni, E. Adult-onset autoimmune diabetes: current knowledge and implications for management. Nat Rev Endocrinol 13, 674-686, https://doi.org/10.1038/nrendo.2017.99 (2017).
8. Nathan, B. M. et al. Dysglycemia and Index60 as Prediagnostic End Points for Type 1 Diabetes Prevention Trials. Diabetes Care 40, 1494-1499, https://doi.org/10.2337/dc17-0916 (2017).
9. Battaglia, M. et al. Understanding and preventing type 1 diabetes through the unique working model of TrialNet. Diabetologia 60, 2139-2147, https://doi.org/10.1007/s00125-017-4384-2 (2017).
10. Ziegler, A. G., Bonifacio, E. & Group, B.-B. S. Age-related islet autoantibody incidence in offspring of patients with type 1 diabetes. Diabetologia 55, 1937-1943, https://doi.org/10.1007/s00125-012-2472-x (2012).
11. Giannopoulou, E. Z. et al. Islet autoantibody phenotypes and incidence in children at increased risk for type 1 diabetes. Diabetologia 58, 2317-2323, https://doi.org/10.1007/s00125-015-3672-y (2015).
12. Redondo, M. J., Oram, R. A. & Steck, A. K. Genetic Risk Scores for Type 1 Diabetes Prediction and Diagnosis. Curr Diab Rep 17, 129, https://doi.org/10.1007/s11892-017-0961-5 (2017).
13. Winkler, C. et al. A strategy for combining minor genetic susceptibility genes to improve prediction of disease in type 1 diabetes. Genes Immun 13, 549-555, https://doi.org/10.1038/gene.2012.36 (2012).
14. Steck, A. K. et al. Improving prediction of type 1 diabetes by testing non-HLA genetic variants in addition to HLA markers. Pediatr Diabetes 15, 355-362 (2014).
15. Winkler, C. et al. Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes. Diabetologia 57, 2521-2529, https://doi.org/10.1007/s00125-014-3362-1 (2014).
16. Oram, R. A. et al. A Type 1 Diabetes Genetic Risk Score Can Aid Discrimination Between Type 1 and Type 2 Diabetes in Young Adults. Diabetes Care 39, 337-344, https://doi.org/10.2337/dc15-1111 (2016).
17. Patel, K. A. et al. Type 1 Diabetes Genetic Risk Score: A Novel Tool to Discriminate Monogenic and Type 1 Diabetes. Diabetes 65, 2094-2099, https://doi.org/10.2337/db15-1690 (2016).
18. Evans, D. M., Visscher, P. M. & Wray, N. R. Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. Hum Mol Genet 18, 3525-3531, https://doi.org/10.1093/hmg/ddp295 (2009).
19. Mayer-Davis, E. J. et al. Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med 376, 1419-1429, https://doi.org/10.1056/NEJMoa1610187 (2017).
20. Erlich, H. et al. HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families. Diabetes 57, 1084-1092, https://doi.org/10.2337/db07-1331 (2008).
21. Ziegler, A. G. et al. Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. Jama 309, 2473-2479, https://doi.org/10.1001/jama.2013.6285 (2013).
22. Auton, A. et al. A global reference for human genetic variation. Nature 526, 68-74, https://doi.org/10.1038/nature15393 (2015).
23. Bryc, K., Durand, E. Y., Macpherson, J. M., Reich, D. & Mountain, J. L. The genetic ancestry of African Americans, Latinos, and European Americans across the United States. Am J Hum Genet 96, 37-53, https://doi.org/10.1016/j.ajhg.2014.11.010 (2015).
24. Consortium, W. T. C. C. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661-678, https://doi.org/10.1038/nature05911 (2007).
25. Komulainen, J. et al. Clinical, autoimmune, and genetic characteristics of very young children with type 1 diabetes. Childhood Diabetes in Finland (DiMe) Study Group. Diabetes Care 22, 1950-1955 (1999).
26. Gillespie, K. M., Gale, E. A. & Bingley, P. J. High familial risk and genetic susceptibility in early onset childhood diabetes. Diabetes 51, 210-214 (2002).
27. Valdes, A. M. et al. Use of class I and class II HLA loci for predicting age at onset of type 1 diabetes in multiple populations. Diabetologia 55, 2394-2401, https://doi.org/10.1007/s00125-012-2608-z (2012).
28. Awa, W. L. et al. HLA-DR genotypes influence age at disease onset in children and juveniles with type 1 diabetes mellitus. Eur J Endocrinol 163, 97-104, https://doi.org/10.1530/EJE-09-0921 (2010).
29. Noble, J. A., Johnson, J., Lane, J. A. & Valdes, A. M. HLA class II genotyping of African American type 1 diabetic patients reveals associations unique to African haplotypes. Diabetes 62, 3292-3299, https://doi.org/10.2337/db13-0094 (2013).
30. Abecasis, G. R. et al. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56-65, https://doi.org/10.1038/nature11632 (2012).
31. Winkler, C. et al. Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1diabetes. Diabetologia 57, 2521-2529, https://doi.org/10.1007/s00125-014-3362-1 (2014).
32. Törn, C. et al. Role of Type 1 Diabetes-Associated SNPs on Risk of Autoantibody Positivity in the TEDDY Study. Diabetes 64, 1818-1829, https://doi.org/10.2337/db14-1497 (2015).
33. Inshaw, J. R. J., Walker, N. M., Wallace, C., Bottolo, L. & Todd, J. A. The chromosome 6q22.33 region is associated with age at diagnosis of type 1 diabetes and disease risk in those diagnosed under 5 years of age. Diabetologia. https://doi.org/10.1007/s00125-017-4440-y (2017).
34. Dabelea, D. et al. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA 311, 1778-1786, https://doi.org/10.1001/jama.2014.3201 (2014).
35. Pettitt, D. J. et al. Prevalence of diabetes in U.S. youth in 2009: the SEARCH for diabetes in youth study. Diabetes Care 37, 402-408, https://doi.org/10.2337/dc13-1838 (2014).
36. Erlich, H. et al. HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families. Diabetes 57, 1084-1092, https://doi.org/10.2337/db07-1331 (2008).
37. Bersenev, A. et al. Lnk constrains myeloproliferative diseases in mice. J Clin Invest 120, 2058-2069, https://doi.org/10.1172/JCI42032 (2010).
38. Gery, S. et al. Lnk inhibits myeloproliferative disorder-associated JAK2 mutant, JAK2V617F. J Leukoc Biol 85, 957-965, https://doi.org/10.1189/jlb.0908575 (2009).
39. Yoshida, K. et al. The landscape of somatic mutations in Down syndrome-related myeloid disorders. Nat Genet 45, 1293-1299, https://doi.org/10.1038/ng.2759 (2013).
40. Gonzales, A. J. et al. Oclacitinib (APOQUEL(®)) is a novel Janus kinase inhibitor with activity against cytokines involved in allergy. J Vet Pharmacol Ther 37, 317-324, https://doi.org/10.1111/jvp.12101 (2014).
41. Waters, M. J. & Brooks, A. J. JAK2 activation by growth hormone and other cytokines. Biochem J 466, 1-11, https://doi.org/10.1042/BJ20141293 (2015).
42. Westra, H. J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet 45, 1238-1243, https://doi.org/10.1038/ng.2756 (2013).
43. Wolf, I. et al. Gab3, a new DOS/Gab family member, facilitates macrophage differentiation. Mol Cell Biol 22, 231-244 (2002).
44. Mayer-Davis, E. J. et al. Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med 376, 1419-1429, https://doi.org/10.1056/NEJMoa1610187 (2017).
45. Abraham, G., Kowalczyk, A., Zobel, J. & Inouye, M. Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease. Genet Epidemiol 37, 184-195, https://doi.org/10.1002/gepi.21698 (2013).
46. Steck, A. K., Armstrong, T. K., Babu, S. R. & Eisenbarth, G. S. & Consortium, T. D. G. Stepwise or linear decrease in penetrance of type 1 diabetes with lower-risk HLA genotypes over the past 40 years. Diabetes 60, 1045-1049, https://doi.org/10.2337/db10-1419 (2011).
47. Atkinson, M. A., Eisenbarth, G. S. & Michels, A. W. Type 1diabetes. Lancet 383, 69-82, https://doi.org/10.1016/S0140-6736(13)60591-7 (2014).
48. Wasserfall, C. et al. Validation of a Rapid Type 1 Diabetes Autoantibody Screening Assay for Community Based Screening of Organ Donors to Identify Subjects at Increased Risk for the Disease. Clin Exp Immunol, Epub ahead of print, https://doi.org/10.1111/cei.12797 (2016).
49. Noble, J. A. et al. HLA class I and genetic susceptibility to type 1 diabetes: results from the Type 1Diabetes Genetics Consortium. Diabetes 59, 2972-2979, https://doi.org/10.2337/db10-0699 (2010).