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Use of a Multiethnic Approach to Identify Rheumatoid- Arthritis-Susceptibility Loci, 1p36 and 17q12
Author(s) -
Fina Kurreeman,
Eli A. Stahl,
Yukinori Okada,
Katherine P. Liao,
Dorothée Diogo,
Soumya Raychaudhuri,
Jan Freudenberg,
Yuta Kochi,
Nikolaos A. Patsopoulos,
Namrata Gupta,
Cynthia Sandor,
SoYoung Bang,
HyeSoon Lee,
Leonid Padyukov,
Akari Suzuki,
Kathy Siminovitch,
Jane Worthington,
Peter K. Gregersen,
Laura B. Hughes,
Richard J. Reynolds,
S. Louis Bridges,
SangCheol Bae,
Kazuhiko Yamamoto,
Robert M. Plenge
Publication year - 2012
Publication title -
the american journal of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.661
H-Index - 302
eISSN - 1537-6605
pISSN - 0002-9297
DOI - 10.1016/j.ajhg.2012.01.010
Subject(s) - genome wide association study , locus (genetics) , single nucleotide polymorphism , allele , genetics , biology , bonferroni correction , genetic association , gene , genotype , statistics , mathematics
We have previously shown that rheumatoid arthritis (RA) risk alleles overlap between different ethnic groups. Here, we utilize a multiethnic approach to show that we can effectively discover RA risk alleles. Thirteen putatively associated SNPs that had not yet exceeded genome-wide significance (p < 5 × 10(-8)) in our previous RA genome-wide association study (GWAS) were analyzed in independent sample sets consisting of 4,366 cases and 17,765 controls of European, African American, and East Asian ancestry. Additionally, we conducted an overall association test across all 65,833 samples (a GWAS meta-analysis plus the replication samples). Of the 13 SNPs investigated, four were significantly below the study-wide Bonferroni corrected p value threshold (p < 0.0038) in the replication samples. Two SNPs (rs3890745 at the 1p36 locus [p = 2.3 × 10(-12)] and rs2872507 at the 17q12 locus [p = 1.7 × 10(-9)]) surpassed genome-wide significance in all 16,659 RA cases and 49,174 controls combined. We used available GWAS data to fine map these two loci in Europeans and East Asians, and we found that the same allele conferred risk in both ethnic groups. A series of bioinformatic analyses identified TNFRSF14-MMEL1 at the 1p36 locus and IKZF3-ORMDL3-GSDMB at the 17q12 locus as the genes most likely associated with RA. These findings demonstrate empirically that a multiethnic approach is an effective strategy for discovering RA risk loci, and they suggest that combining GWASs across ethnic groups represents an efficient strategy for gaining statistical power.

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