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

Published version
Peer-reviewed

Type

Article

Change log

Authors

Taliun, Daniel 
Thurner, Matthias 
Robertson, Neil R 
Torres, Jason M 

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).

Description

Keywords

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

Journal Title

Nat Genet

Conference Name

Journal ISSN

1061-4036
1546-1718

Volume Title

50

Publisher

Springer Science and Business Media LLC
Sponsorship
Medical Research Council (MC_UU_12015/1)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0617-10149)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0512-10135)
MRC (MC_PC_13046)
MRC (MC_PC_13048)
European Commission (602068)
The InterAct project (LSHM-CT-2006-037197) is a European-Community funded project under Framework Programme 6. We thank all EPIC participants and staff for their contribution to the study. We thank Nicola Kerrison (MRC Epidemiology Unit, Cambridge) for managing the data for the InterAct Project and staff from the Laboratory Team, Field Epidemiology Team, and Data Functional Group of the MRC Epidemiology Unit in Cambridge, UK, for carrying out sample preparation, DNA provision and quality control, genotyping, and data-handling work.