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 colocalises 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 genomewide 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 (7,467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate
Highlights
There is a genetic component to both type 1 and type 2 diabetes, with approximately 60 chromosome regions associated with type 1 diabetes [1] and over 200 associated with type 2 diabetes [2] at genome-wide significance
Summary statistics for type 2 diabetes were from 74,124 cases and 824,006 controls of European ancestry, imputed using the Haplotype Reference Consortium reference panel [2]
Regions associated with both diseases were identified by selecting all variants with type 1 diabetes and a type 2 diabetes association with an false discovery rate (FDR)
Summary
There is a genetic component to both type 1 and type 2 diabetes, with approximately 60 chromosome regions associated with type 1 diabetes [1] and over 200 associated with type 2 diabetes [2] at genome-wide significance. Examination of regions associated with both diseases could uncover signals that simultaneously alter disease risk for both diseases, termed colocalisation. A recent analysis suggested that the same genetic variant alters risk of both type 1 and type 2 diabetes in five regions, near CENPW, CTRB1/BCAR1, GLIS3, BCL11A and THADA [3]. We identified all regions across the genome that showed evidence of association with both type 1 and type 2 diseases at a false discovery rate (FDR)
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