Nature GeneticsGeneticsPeer-reviewed journal article
Fine-mapping identifies causal variants for RA and T1D in DNASE1L3, SIRPG, MEG3, TNFAIP3 and CD28/CTLA4 loci
Harm-Jan WestraiD, Marta Martínez‐BonetiD, Suna Önengüt-GümüşcüiD, Annette LeeiD, Yang LuoiD, Nikola C. TeslovichiD, Jane WorthingtoniD, Javier J. MartiniD, Tom W. J. HuizingaiD, Lars KlareskogiD, Solbritt Rantapää‐DahlqvistiD, Wei‐Min CheniD, Aaron R. QuinlaniD, John A. ToddiD, Stephen EyreiD, Peter Andrija NigroviciD, Peter K. GregerseniD, Stephen S. RichiD, Soumya RaychaudhuriiD
Abstract
We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to [≤]5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- approach: statistical model
- Citations
- 148
- FWCI
- 11.65
- Field percentile
- top 1%
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