Frequency and phenotype of type 1 diabetes in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank

Nicholas J Thomas, Samuel E Jones, Michael N Weedon, Beverley M Shields, Richard A Oram, Andrew T Hattersley, Nicholas J Thomas, Samuel E Jones, Michael N Weedon, Beverley M Shields, Richard A Oram, Andrew T Hattersley

Abstract

Background: Type 1 diabetes is typically considered a disease of children and young adults. Genetic susceptibility to young-onset type 1 diabetes is well defined and does not predispose to type 2 diabetes. It is not known how frequently genetic susceptibility to type 1 diabetes leads to a diagnosis of diabetes after age 30 years. We aimed to investigate the frequency and phenotype of type 1 diabetes resulting from high genetic susceptibility in the first six decades of life.

Methods: In this cross-sectional analysis, we used a type 1 diabetes genetic risk score based on 29 common variants to identify individuals of white European descent in UK Biobank in the half of the population with high or low genetic susceptibility to type 1 diabetes. We used Kaplan-Meier analysis to evaluate the number of cases of diabetes in both groups in the first six decades of life. We genetically defined type 1 diabetes as the additional cases of diabetes that occurred in the high genetic susceptibility group compared with the low genetic susceptibility group. All remaining cases were defined as type 2 diabetes. We assessed the clinical characteristics of the groups with genetically defined type 1 or type 2 diabetes.

Findings: 13 250 (3·5%) of 379 511 white European individuals in UK Biobank had developed diabetes in the first six decades of life. 1286 more cases of diabetes were in the half of the population with high genetic susceptibility to type 1 diabetes than in the half of the population with low genetic susceptibility. These genetically defined cases of type 1 diabetes were distributed across all ages of diagnosis; 537 (42%) were in individuals diagnosed when aged 31-60 years, representing 4% (537/12 233) of all diabetes cases diagnosed after age 30 years. The clinical characteristics of the group diagnosed with type 1 diabetes when aged 31-60 years were similar to the clinical characteristics of the group diagnosed with type 1 diabetes when aged 30 years or younger. For individuals diagnosed with diabetes when aged 31-60 years, the clinical characteristics of type 1 diabetes differed from those of type 2 diabetes: they had a lower BMI (27·4 kg/m2 [95% CI 26·7-28·0] vs 32·4 kg/m2 [32·2-32·5]; p<0·0001), were more likely to use insulin in the first year after diagnosis (89% [476/537] vs 6% [648/11 696]; p<0·0001), and were more likely to have diabetic ketoacidosis (11% [61/537] vs 0·3% [30/11 696]; p<0·0001).

Interpretation: Genetic susceptibility to type 1 diabetes results in non-obesity-related, insulin-dependent diabetes, which presents throughout the first six decades of life. Our results highlight the difficulty of identifying type 1 diabetes after age 30 years because of the increasing background prevalence of type 2 diabetes. Failure to diagnose late-onset type 1 diabetes can have serious consequences because these patients rapidly develop insulin dependency.

Funding: Wellcome Trust and Diabetes UK.

Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1
Figure 1
Use of a type 1 diabetes genetic risk score to establish the proportion of population with genetically defined type 1 diabetes (A) Distribution of type 1 genetic risk score in the Wellcome Trust Case Control Consortium type 1 diabetes and type 2 diabetes cohorts. Type 1 diabetes is restricted to high type 1 diabetes genetic risk scores. Numbers of individuals with type 2 diabetes above and below the 50th centile (dotted line; fifth centile for type 1 diabetes) will be the same; thus, any excess in the top 50% will be cases of type 1 diabetes. In a population where the proportions of type 1 diabetes and type 2 diabetes are unknown, this method can be used to determine the proportion of type 1 diabetes cases. (B) Schematic showing that the high type 1 diabetes genetic risk group will have the same amount of type 2 diabetes as the low type 1 diabetes genetic risk group in addition to an excess of diabetes contributed by type 1 diabetes.
Figure 2
Figure 2
Kaplan-Meier curve of diabetes-free survival in the high and low genetic susceptibility groups Graph shows that diabetes was more likely in the high genetic susceptibility group. HR=hazard ratio.
Figure 3
Figure 3
Cumulative excess of genetically defined cases of type 1 diabetes occurring throughout the first six decades of life 58% (749/1286) of type 1 diabetes cases were diagnosed when individuals were aged 30 years or younger; 42% (537/1286) were diagnosed when individuals were aged 31–60 years.
Figure 4
Figure 4
Incidence of genetically defined type 1 and type 2 diabetes in the first six decades of life Cases of type 1 diabetes were distributed across all ages of diagnosis, whereas cases of type 2 diabetes increased substantially with increasing age.

References

    1. Maahs DM, West NA, Lawrence JM, Mayer-Davis EJ. Epidemiology of type 1 diabetes. Endocrinol Metab Clin North Am. 2010;39:481–497.
    1. Diaz-Valencia PA, Bougneres P, Valleron AJ. Global epidemiology of type 1 diabetes in young adults and adults: a systematic review. BMC Public Health. 2015;15:255.
    1. Scottish Diabetes Survey Monitoring Group Scottish Diabetes Survey 2015. 2015. (accessed June 15, 2017).
    1. Hope SV, Wienand-Barnett S, Shepherd M. Practical Classification Guidelines for Diabetes in patients treated with insulin: a cross-sectional study of the accuracy of diabetes diagnosis. Br J Gen Pract. 2016;66:E315–E322.
    1. Farmer A, Fox R. Diagnosis, classification, and treatment of diabetes. BMJ. 2011;342:d3319.
    1. Diabetes UK. Theresa May: “Type 1 doesn't change what you can do”. 2014. (accessed May 19, 2017).
    1. Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med. 2013;30:803–817.
    1. Sabbah E, Savola K, Ebeling T. Genetic, autoimmune, and clinical characteristics of childhood- and adult-onset type 1 diabetes. Diabetes Care. 2000;23:1326–1332.
    1. Bingley PJ. Clinical applications of diabetes antibody testing. J Clin Endocrinol Metab. 2010;95:25–33.
    1. Clayton DG. Prediction and interaction in complex disease genetics: experience in type 1 diabetes. PLoS Genet. 2009;5:e1000540.
    1. Husby S, Koletzko S, Korponay-Szabo IR. European Society for Pediatric Gastroenterology, Hepatology, and Nutrition guidelines for the diagnosis of coeliac disease. J Pediatr Gastroenterol Nutr. 2012;54:136–160.
    1. Kaukinen K, Partanen J, Maki M, Collin P. HLA-DQ typing in the diagnosis of celiac disease. Am J Gastroenterol. 2002;97:695–699.
    1. Taurog JD, Chhabra A, Colbert RA. Ankylosing spondylitis and axial spondyloarthritis. N Engl J Med. 2016;375:1303.
    1. Barrett JC, Clayton DG, Concannon P. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet. 2009;41:703–707.
    1. Morris AP, Voight BF, Teslovich TM. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–990.
    1. Oram RA, Patel K, Hill A. A type 1 diabetes genetic risk score can aid discrimination between type 1 and type 2 diabetes in young adults. Diabetes Care. 2016;39:337–344.
    1. Winkler C, Krumsiek J, Buettner F. Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes. Diabetologia. 2014;57:2521–2529.
    1. Patel KA, Oram RA, Flanagan SE. Type 1 diabetes genetic risk score: a novel tool to discriminate monogenic and type 1 diabetes. Diabetes. 2016;65:2094–2099.
    1. Allen NE, Sudlow C, Peakman T, Collins R. UK Biobank data: come and get it. Sci Transl Med. 2014;6:224.
    1. Tyrrell J, Jones SE, Beaumont R. Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank. BMJ. 2016;352:i582.
    1. Barker JM, Triolo TM, Aly TA. Two single nucleotide polymorphisms identify the highest-risk diabetes HLA genotype: potential for rapid screening. Diabetes. 2008;57:3152–3155.
    1. Eastwood SV, Mathur R, Atkinson M. Algorithms for the capture and adjudication of prevalent and incident diabetes in UK Biobank. PLoS One. 2016;11:e0162388.
    1. Wellcome Trust Case Control Consortium Genome-wide association study of 14 000 cases of seven common diseases and 3000 shared controls. Nature. 2007;447:661–678.
    1. Tuomi T, Santoro N, Caprio S, Cai M, Weng J, Groop L. The many faces of diabetes: a disease with increasing heterogeneity. Lancet. 2014;383:1084–1094.
    1. Davey Smith G, Davies NM. Can genetic evidence help us understand why height and weight relate to social position? BMJ. 2016;352:i1224.
    1. Mayer-Davis EJ, Bell RA, Dabelea D. The many faces of diabetes in American youth: type 1 and type 2 diabetes in five race and ethnic populations: the SEARCH for Diabetes in Youth Study. Diabetes Care. 2009;32(suppl 2):S99–S101.
    1. Gillespie KM, Bain SC, Barnett AH. The rising incidence of childhood type 1 diabetes and reduced contribution of high-risk HLA haplotypes. Lancet. 2004;364:1699–1700.
    1. Howson JMM, Rosinger S, Smyth DJ, Boehm BO, Todd JA, Grp A-ES. Genetic analysis of adult-onset autoimmune diabetes. Diabetes. 2011;60:2645–2653.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren