Analysis of overlapping genetic association in type 1 and type 2 diabetes

Abstract

Aims/hypothesis Given the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal co-localises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. Methods Using publicly available type 2 diabetes summary statistics from a genome-wide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate <0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined co-localisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a co-localisation posterior probability of ≥0.9 was considered a genuine shared association with both diseases. Results Of the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals co-localised between both diseases (posterior probability ≥0.9): (1) chromosome 16q23.1, near CTRB1/BCAR1, which has been previously identified; (2) chromosome 11p15.5, near the INS gene; (3) chromosome 4p16.3, near TMEM129 and (4) chromosome 1p31.3, near PGM1. In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified co-localisation on chromosome 9p24.2, near the GLIS3 gene, in this case with a concordant direction of effect. Conclusions/interpretation Four of five association signals that co-localise between type 1 diabetes and type 2 diabetes are in opposite directions, suggesting a complex genetic relationship between the two diseases. Graphical abstract

Obesity in late adolescence and incident type 1 diabetes in young adulthood

“…There is increasing evidence for a shared and complex genetic basis for type 1 diabetes, type 2 diabetes and obesity [35]. For example, the SNP in TCF7L2 is considered to be a strong risk factor for type 2 diabetes and was recently also linked to increased risk for type 1 diabetes, primarily in adolescents aged 12 years or older [36].…”

Rs864745 in JAZF1, an Islet Function Associated Variant, Correlates With Plasma Lipid Levels in Both Type 1 and Type 2 Diabetes Status, but Not Healthy Subjects

“…Previous studies have found a shared genetic risk factor underlying T1D and T2D etiology (25,26), with approximately 60 chromosome regions associated with T1D ( 27) and over 200 associated with T2D ( 28), reaching genome-wide significance. Therefore, uncovering co-localizing signals could provide biological insights into overlapping disease mechanisms, and potentially reveal therapeutic targets effective for both diseases.…”

Genetic regulation of RNA splicing in human pancreatic islets

“…For example, islet sQTLs can also be considered to understand genetic variants that modify autoimmune T1D risk. The genetic risk for T1D is largely mediated through effects on immune cells 51,52 , although recent studies have highlighted a role of genes expressed pancreatic exocrine and endocrine cells in T1D pathophysiology [53][54][55][56] . We identified examples of islet splicing QTLs at MEG3 lncRNA and ESYT1 that co-localize with T1D association signals 55 (Supplementary Figure 8a,b) and thereby expose new candidate biological mediators for T1D.…”