Type 1 and 2 diabetes (T1/2D) are complex metabolic diseases caused by absolute or relative loss of functional β-cell mass, respectively. Both diseases are influenced by multiple genetic loci that alter disease risk. For many of the disease-associated loci, the causal candidate genes remain to be identified. Remarkably, despite the partially shared phenotype of the two diabetes forms, the associated loci for T1D and T2D are almost completely separated. We hypothesized that some of the genes located in risk loci for T1D and T2D interact in common pancreatic islet networks to mutually regulate important islet functions which are disturbed by disease-associated variants leading to β-cell dysfunction. To address this, we took a dual systems genetics approach. All genes located in 57 T1D and 243 T2D established genome-wide association studies (GWAS) loci were extracted and filtered for genes expressed in human islets using RNA sequencing data, and then integrated with; (1) human islet expression quantitative trait locus (eQTL) signals in linkage disequilibrium (LD) with T1D- and T2D-associated variants; or (2) with genes transcriptionally regulated in human islets by pro-inflammatory cytokines or palmitate as in vitro models of T1D and T2D, respectively. Our in silico systems genetics approaches created two interaction networks consisting of densely-connected T1D and T2D loci genes. The "T1D-T2D islet eQTL interaction network" identified 9 genes (GSDMB, CARD9, DNLZ, ERAP1, PPIP5K2, TMEM69, SDCCAG3, PLEKHA1, and HEMK1) in common T1D and T2D loci that harbor islet eQTLs in LD with disease-associated variants. The "cytokine and palmitate islet interaction network" identified 4 genes (ASCC2, HIBADH, RASGRP1, and SRGAP2) in common T1D and T2D loci whose expression is mutually regulated by cytokines and palmitate. Functional annotation analyses of the islet networks revealed a number of significantly enriched pathways and molecular functions including cell cycle regulation, inositol phosphate metabolism, lipid metabolism, and cell death and survival. In summary, our study has identified a number of new plausible common candidate genes and pathways for T1D and T2D.
Keywords: genetics; human islets; network analysis; type 1 diabetes; type 2 diabetes.
Copyright © 2021 Kaur, Mirza, Overgaard, Pociot and Størling.