Meta-analyses of genome-wide association studies (GWAS) have improved our understanding of the genetic foundations of a number of diseases, including diabetes. However, single nucleotide polymorphisms (SNPs) that are identified by GWAS, especially those that fall outside of gene regions, do not always clearly link to the underlying biology. Despite this, these SNPs have often been validated through re-sequencing efforts as not just tag SNPs, but as causative SNPs, and so must play a role in disease development or progression. In this study, we show how the 3D genome (spatial connections) and trans-expression Quantitative Trait Loci connect diabetes loci from different GWAS meta-analyses, informing the backbone of regulatory networks. Our findings include a three-way functional-spatial connection between the TM6SF2, CTRB1-BCAR1, and CELSR2-PSRC1 loci (rs201189528, rs7202844, and rs7202844, respectively) connected through the KCNIP3 and BCAR1/BCAR3 loci, respectively. These spatial hubs serve as an example of how loci in genes with little biological connection to disease come together to contribute to the diabetes phenotype.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2015.
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