Literature DB >> 15593091

Characterization of linkage disequilibrium structure, mutation history, and tagging SNPs, and their use in association analyses: ELAC2 and familial early-onset prostate cancer.

Nicola J Camp1, Jeff Swensen, Benjamin D Horne, James M Farnham, Alun Thomas, Lisa A Cannon-Albright, Sean V Tavtigian.   

Abstract

In association analyses, it is critical that informative single-nucleotide polymorphisms (SNPs) be selected for study and utilized appropriately. We sequenced 38 kb, including exons of ELAC2, promoter region and conserved upstream intergenic sequences. A comprehensive characterization of linkage disequilibrium (LD) structure and mutation history was performed using our principal components analysis (PCA) method and a phylogenetic analysis. We identified a complex pattern of LD structure consistent with the occurrence of both recombination and mutation events within ELAC2. Four overlapping and noncontiguous LD groups were defined. Eight tagging SNPs (tSNPs) were identified, accounting for over 90% of the genetic variation of the 19 total variants. We tested associations between familial early-onset prostate cancer (PRCA) and each variant independently and in haplotypes. We performed these tests using all 19 variants and the 8 tSNPs; the results using tSNP haplotypes accurately represent the association evidence for the full haplotypes. We observed increased evidence for association when SNPs were analyzed in haplotypes. The phylogenetic analysis indicated three haplotypes, clustered farthest from the root-node, all of which were found more often in cases than controls. These three haplotypes together showed the best evidence of association with familial, early-onset PRCA (P=0.0024; odds ratio=2.23; 95% CI, 1.33-3.74), indicating possible allelic heterogeneity. Our results suggest that 8 tSNPs are required to comprehensively assess associations in ELAC2, and that haplotypes should be considered for analysis, and that a knowledge of mutation history may be helpful in parsing allelic heterogeneity and suggesting combinations of haplotypes to be tested. (c) 2005 Wiley-Liss, Inc.

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Year:  2005        PMID: 15593091     DOI: 10.1002/gepi.20054

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  7 in total

1.  Association of HPC2/ELAC2 and RNASEL non-synonymous variants with prostate cancer risk in African American familial and sporadic cases.

Authors:  Christiane M Robbins; Wenndy Hernandez; Chiledum Ahaghotu; James Bennett; Gerald Hoke; Terry Mason; Curtis A Pettaway; Srinivasan Vijayakumar; Sally Weinrich; Paulette Furbert-Harris; Georgia Dunston; Isaac J Powell; John D Carpten; Rick A Kittles
Journal:  Prostate       Date:  2008-12-01       Impact factor: 4.104

2.  Sequence variants of elaC homolog 2 (Escherichia coli) (ELAC2) gene and susceptibility to prostate cancer in the Health Professionals Follow-Up Study.

Authors:  Yen-Ching Chen; Edward Giovannucci; Peter Kraft; David J Hunter
Journal:  Carcinogenesis       Date:  2008-03-28       Impact factor: 4.944

3.  Assessment of SNP streak statistics using gene drop simulation with linkage disequilibrium.

Authors:  Alun Thomas
Journal:  Genet Epidemiol       Date:  2010-02       Impact factor: 2.135

4.  Polymorphisms of HPC2/ELAC2 and SRD5A2 (5α-Reductase Type II) Genes in Prostate Cancer.

Authors:  M Izmirli; B Arikan; Y Bayazit; D Alptekin
Journal:  Balkan J Med Genet       Date:  2011-06       Impact factor: 0.519

5.  Characterization of the linkage disequilibrium structure and identification of tagging-SNPs in five DNA repair genes.

Authors:  Kristina Allen-Brady; Nicola J Camp
Journal:  BMC Cancer       Date:  2005-08-09       Impact factor: 4.430

6.  hapConstructor: automatic construction and testing of haplotypes in a Monte Carlo framework.

Authors:  Ryan Abo; Stacey Knight; Jathine Wong; Angela Cox; Nicola J Camp
Journal:  Bioinformatics       Date:  2008-07-23       Impact factor: 6.937

7.  Analysis of high-density single-nucleotide polymorphism data: three novel methods that control for linkage disequilibrium between markers in a linkage analysis.

Authors:  Kristina Allen-Brady; Benjamin D Horne; Alka Malhotra; Craig Teerlink; Nicola J Camp; Alun Thomas
Journal:  BMC Proc       Date:  2007-12-18
  7 in total

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