The PTPN22 C1858T gene variant is associated with proinsulin in new-onset type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>The protein tyrosine phosphatase nonreceptor type 2 (<it>PTPN22</it>) has been established as a type 1 diabetes susceptibility gene. A recent study found the C1858T variant of this gene to be associated with lower residual fasting C-peptide levels and poorer glycemic control in patients with type 1 diabetes. We investigated the association of the C1858T variant with residual beta-cell function (as assessed by stimulated C-peptide, proinsulin and insulin dose-adjusted HbA_1c), glycemic control, daily insulin requirements, diabetic ketoacidosis (DKA) and diabetes-related autoantibodies (IA-2A, GADA, ICA, ZnT8Ab) in children during the first year after diagnosis of type 1 diabetes.</p> <p>Methods</p> <p>The C1858T variant was genotyped in an international cohort of children (n = 257 patients) with newly diagnosed type 1 diabetes during 12 months after onset. We investigated the association of this variant with liquid-meal stimulated beta-cell function (proinsulin and C-peptide) and antibody status 1, 6 and 12 months after onset. In addition HbA_1cand daily insulin requirements were determined 1, 3, 6, 9 and 12 months after diagnosis. DKA was defined at disease onset.</p> <p>Results</p> <p>A repeated measurement model of all time points showed the stimulated proinsulin level is significantly higher (22%, p = 0.03) for the T allele carriers the first year after onset. We also found a significant positive association between proinsulin and IA levels (est.: 1.12, p = 0.002), which did not influence the association between <it>PTPN22 </it>and proinsulin (est.: 1.28, p = 0.03).</p> <p>Conclusions</p> <p>The T allele of the C1858T variant is positively associated with proinsulin levels during the first 12 months in newly diagnosed type 1 diabetes children.</p

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling