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. 2026 Jan 16;14(1):e003877.
doi: 10.1136/bmjdrc-2023-003877.

Association of genetic variation with age at diagnosis in type 1 diabetes

Collaborators, Affiliations

Association of genetic variation with age at diagnosis in type 1 diabetes

Charlotte E Vollenbrock et al. BMJ Open Diabetes Res Care. .

Abstract

Introduction: Type 1 diabetes is an autoimmune disease with a strong genetic basis. The aim of this study was to identify additional single-nucleotide polymorphisms (SNPs) for type 1 diabetes age at diagnosis and to replicate previously identified loci.

Research design and methods: Meta genome-wide association studies of age at diagnosis from eight cohorts (n=5910 in total) were performed in three models. Model 1 was age at diagnosis with no covariates. Model 2 was age at diagnosis adjusted for DR3/DR4 genotype categories. Model 3 was similar to model 2, including the most significant SNP from model 2 (coded additively). Models 1 and 2 were also performed for major histocompatibility complex (MHC) imputed data. In addition, we tested previously identified loci for age at diagnosis and type 1 diabetes risk for association with age at diagnosis in model 1.

Results: In model 1, we identified a genome-wide significant locus (rs2856721, p=3.3×10-11) in the MHC region whose effect was attenuated in model 2 (p=0.03). In model 2, we identified another locus in the MHC region, rs76730244, p=4.9×10-9, which was associated with age at diagnosis adjusted for DR3/DR4 genotypes. Model 3 and analysis of the MHC region did not reveal novel loci. Among 14 previously identified SNPs for age at diagnosis, 6 were confirmed; in addition, 11 out of 78 non-HLA loci for type 1 diabetes risk were associated with age at diagnosis.

Conclusions: We identified rs76730244 in the MHC region for age at diagnosis of type 1 diabetes, which was independent of the HLA-DR3/DR4 genotype categories. We also confirmed 6 previously identified SNPs and showed that 11 non-HLA loci for type 1 diabetes risk are associated with age at diagnosis.

Keywords: Diabetes Mellitus, Type 1; Genetic Markers; Histocompatibility Antigens Class II; Meta-Analysis.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1. Manhattan plot of age at diagnosis in meta-analysis with DR3/DR4 genotype categories included as covariate (model 2). λgc: 1.0108 (Q–Q plot visualized in online supplemental figure 3. Variants are plotted on the x-axis according to their position on each chromosome (Hg19) with the −log10(p value) of the association test on the y-axis. The red line indicates the threshold for genome-wide significance (p=5×10−8) and the blue line indicates the suggestive loci (p=1×10−5).
Figure 2
Figure 2. Minor allele frequency of the T allele of rs76730244 by age at diagnosis quartiles.
Figure 3
Figure 3. Association of 78 non-HLA single-nucleotide polymorphisms for type 1 diabetes risk with age at diagnosis (meta-analysis model 1, no covariates).

References

    1. Todd JA, Bell JI, McDevitt HO. HLA-DQ beta gene contributes to susceptibility and resistance to insulin-dependent diabetes mellitus. Nature New Biol. 1987;329:599–604. doi: 10.1038/329599a0. - DOI - PubMed
    1. Oram RA, Patel K, Hill 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. 2016;39:337–44. doi: 10.2337/dc15-1111. - DOI - PMC - PubMed
    1. Robertson CC, Inshaw JRJ, Onengut-Gumuscu S, et al. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes. Nat Genet. 2021;53:962–71. doi: 10.1038/s41588-021-00880-5. - DOI - PMC - PubMed
    1. Onengut-Gumuscu S, Chen W-M, Burren O, et al. Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers. Nat Genet. 2015;47:381–6. doi: 10.1038/ng.3245. - DOI - PMC - PubMed
    1. Harjutsalo V, Podar T, Tuomilehto J. Cumulative incidence of type 1 diabetes in 10,168 siblings of Finnish young-onset type 1 diabetic patients. Diabetes. 2005;54:563–9. doi: 10.2337/diabetes.54.2.563. - DOI - PubMed