OBJECTIVE: Mechanisms underlying the role of non-human leukocyte antigen (HLA) genetic risk variants in type 1 diabetes (T1D) are poorly understood. We aimed to test the association between methylation and non-HLA genetic risk. METHODS: We conducted a methylation quantitative trait loci (mQTL) analysis in a nested case-control study from the Dietary Autoimmunity Study in the Young. Controls (n = 83) were frequency-matched to T1D cases (n = 83) based on age, race/ethnicity, and sample availability. We evaluated 13 non-HLA genetic markers known be associated with T1D. Genome-wide methylation profiling was performed on peripheral blood samples collected prior to T1D using the Illumina 450 K (discovery set) and infinium methylation EPIC beadchip (EPIC validation) platforms. Linear regression models, adjusting for age and sex, were used to test to each single nucleotide polymorphism (SNP) -probe combination. Logistic regression models were used to test the association between T1D and methylation levels among probes with a significant mQTL. A meta-analysis was used to combine odds ratios from the two platforms. RESULTS: We identified 10 SNP-methylation probe pairs (false discovery rate (FDR) adjusted P < .05 and validation P < .05). Probes were associated with the GSDMB, C1QTNF6, IL27, and INS genes. The cg03366382 (OR: 1.9, meta-P = .0495), cg21574853 (OR: 2.5, meta-P = .0232), and cg25336198 (odds ratio: 6.6, meta-P = .0081) probes were significantly associated with T1D. The three probes were located upstream from the INS transcription start site. CONCLUSIONS: We confirmed an association between DNA methylation and rs689 that has been identified in related studies. Measurements in our study preceded the onset of T1D suggesting methylation may have a role in the relationship between INS variation and T1D development.
OBJECTIVE: Mechanisms underlying the role of non-human leukocyte antigen (HLA) genetic risk variants in type 1 diabetes (T1D) are poorly understood. We aimed to test the association between methylation and non-HLA genetic risk. METHODS: We conducted a methylation quantitative trait loci (mQTL) analysis in a nested case-control study from the Dietary Autoimmunity Study in the Young. Controls (n = 83) were frequency-matched to T1D cases (n = 83) based on age, race/ethnicity, and sample availability. We evaluated 13 non-HLA genetic markers known be associated with T1D. Genome-wide methylation profiling was performed on peripheral blood samples collected prior to T1D using the Illumina 450 K (discovery set) and infinium methylation EPIC beadchip (EPIC validation) platforms. Linear regression models, adjusting for age and sex, were used to test to each single nucleotide polymorphism (SNP) -probe combination. Logistic regression models were used to test the association between T1D and methylation levels among probes with a significant mQTL. A meta-analysis was used to combine odds ratios from the two platforms. RESULTS: We identified 10 SNP-methylation probe pairs (false discovery rate (FDR) adjusted P < .05 and validation P < .05). Probes were associated with the GSDMB, C1QTNF6, IL27, and INS genes. The cg03366382 (OR: 1.9, meta-P = .0495), cg21574853 (OR: 2.5, meta-P = .0232), and cg25336198 (odds ratio: 6.6, meta-P = .0081) probes were significantly associated with T1D. The three probes were located upstream from the INS transcription start site. CONCLUSIONS: We confirmed an association between DNA methylation and rs689 that has been identified in related studies. Measurements in our study preceded the onset of T1D suggesting methylation may have a role in the relationship between INS variation and T1D development.
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