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Whole-Genome Detection of Disease-Associated Deletions or Excess Homozygosity in a Case-Control Study of Rheumatoid Arthritis.
MedLine Citation:
PMID:  23223014     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Unlike genome-wide association studies, few comprehensive studies have been performed of copy number variation's contribution to complex human disease susceptibility. Copy number variations are abundant in humans and represent one of the least well studied classes of genetic variants; in addition, known rheumatoid arthritis susceptibility loci explain only a portion of familial clustering. Therefore, we performed a genome-wide study of association between deletion or excess homozygosity and rheumatoid arthritis using high-density 550K SNP genotype data from a genome-wide association study. We used a genome-wide statistical method that we recently developed to test each contiguous SNP locus between the 868 cases and 1194 controls to detect deletion variants or excess homozygosity that influence susceptibility. Our method is designed to detect statistically significant evidence of deletions or homozygosity at individual SNPs for SNP-by-SNP analyses and to combine the information among neighboring SNPs for cluster analyses. In addition to successfully detecting the known deletion variants on MHC, we identified 4.3-kb and 28-kb clusters on chromosomes 10p and 13q, respectively, which were significant at a Bonferroni-type corrected 0.05 nominal significant level. Independently, we performed analyses using PennCNV, an algorithm for identifying and cataloging copy numbers for individuals based on a hidden Markov model, and identified cases and controls that had chromosomal segments with copy number < 2. Using Fisher's exact test for comparing the numbers of cases and controls with copy number < 2 per SNP, we identified 26 significant SNPs (protective; more controls than cases) aggregating on chromosome 14 with p-values < 10(-8).
Authors:
Chih-Chieh Wu; Sanjay Shete; Eun-Ji Jo; Yaji Xu; Yue E Lu; Wei V Chen; Christopher I Amos
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-12-6
Journal Detail:
Title:  Human molecular genetics     Volume:  -     ISSN:  1460-2083     ISO Abbreviation:  Hum. Mol. Genet.     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-12-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9208958     Medline TA:  Hum Mol Genet     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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