Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D

Ana Viñuela, Arushi Varshney, Martijn van de Bunt, Rashmi B Prasad, Olof Asplund, Amanda Bennett, Michael Boehnke, Andrew A Brown, Michael R Erdos, João Fadista, Ola Hansson, Gad Hatem, Cédric Howald, Apoorva K Iyengar, Paul Johnson, Ulrika Krus, Patrick E MacDonald, Anubha Mahajan, Jocelyn E Manning Fox, Narisu Narisu, Vibe Nylander, Peter Orchard, Nikolay Oskolkov, Nikolaos I Panousis, Anthony Payne, Michael L Stitzel, Swarooparani Vadlamudi, Ryan Welch, Francis S Collins, Karen L Mohlke, Anna L Gloyn, Laura J Scott, Emmanouil T Dermitzakis, Leif Groop, Stephen C J Parker, Mark I McCarthy.
Nat Commun. 2020-09-30;11(1):4912.
Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.
Consortium data used in this publication
All relevant data supporting the key findings of this study are available within the article and its Supplementary Information files or from the corresponding author upon reasonable request. Genotype, technical and biological covariates, and sequence data have been deposited at the European Genome-phenome Archive (EGA; under the following accession numbers: EGAD00001006149; EGAS00001004042; EGAS00001004056. Complete summary statistics for eQTL associations are accessible in the following link: In addition, Source data are provided with this paper.