Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

Nat Genet. 2018 Nov;50(11):1505-1513. doi: 10.1038/s41588-018-0241-6. Epub 2018 Oct 8.

Abstract

We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Mass Index
  • Case-Control Studies
  • Chromosome Mapping / methods*
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / genetics*
  • Diabetes Mellitus, Type 2 / pathology
  • Epigenesis, Genetic*
  • Female
  • Gene Frequency
  • Genetic Loci / genetics
  • Genetic Predisposition to Disease
  • Genome, Human / genetics*
  • Genome-Wide Association Study
  • High-Throughput Screening Assays / methods
  • Humans
  • Islets of Langerhans / metabolism*
  • Islets of Langerhans / pathology
  • Linkage Disequilibrium
  • Male
  • Meta-Analysis as Topic
  • Polymorphism, Single Nucleotide*
  • Sex Factors
  • White People / genetics