Localization of cancer susceptibility genes by genome-wide single-nucleotide polymorphism linkage-disequilibrium mapping Journal Article


Authors: Mitra, N.; Ye, T. Z.; Smith, A.; Chuai, S.; Kirchhoff, T.; Peterlongo, P.; Nafa, K.; Phillips, M. S.; Offit, K.; Ellis, N. A.
Article Title: Localization of cancer susceptibility genes by genome-wide single-nucleotide polymorphism linkage-disequilibrium mapping
Abstract: With the large numbers of single nucleotide polymorphisms (SNPs) available and new technologies that permit high throughput genotyping, we have investigated the possibility of the localization of disease genes with genome-wide panels of SNP markers and taking advantage of the linkage-disequilibrium (LD) between the disease gene and closely linked markers. For this purpose, we selected cases from the Ashkenazi Jewish population, in which the mutant alleles are expected to be identical by descent from a common founder and the regions of LD encompassing these mutant alleles are large. As a validation of this approach for localization, we performed two trials: one in autosomal recessive Bloom syndrome, in which a unique mutation of the BLM gene is present at elevated frequencies in cases, and the other in autosomal dominant hereditary nonpolyposis colorectal cancer (HNPCC), in which a unique mutation of MSH2 is present at elevated frequencies. In the Bloom syndrome trial, we genotyped 3,258 SNPs in 10 Jewish Bloom syndrome cases and 31 non-Bloom syndrome Jewish persons as a comparison group. In the HNPCC trial, we genotyped 8,549 SNPS in 13 Jewish HNPCC cases whose colon cancers exhibited microsatellite instability and in 63 healthy Jews as a comparison group. To identify significant associations, we performed (a) Fisher's exact test comparing genotypes at each locus in cases versus controls and (b) a haplotype analysis by estimating the frequency of haplotypes with the expectation-maximization algorithm and comparing haplotype frequencies in cases versus controls by logistic regression and a maximum likelihood ratio method. In the Bloom syndrome trial, by Fisher's exact test, statistically significant association was detected at a single locus, TSC0754862, which is a locus 1.7 million bp from BLM. Two-locus, three-locus, and four-locus haplotypes that included TSC0754862 and flanked BLM were also statistically more frequent in cases versus controls. In the HNPCC trial, although a significant P value was not obtained by the single SNP genotype analysis, significant associations were detected for several multilocus haplotypes in an 11-million-bp region that contained the MSH2 gene. This work demonstrates the power of the LD mapping approach in an isolated population and its general applicability to the identification of novel cancer-causing genes.
Keywords: clinical article; controlled study; unclassified drug; gene mutation; single nucleotide polymorphism; dna-binding proteins; polymorphism, single nucleotide; proto-oncogene proteins; colorectal cancer; allele; cancer susceptibility; genetic predisposition to disease; protein; genotype; linkage disequilibrium; haplotype; statistical significance; microsatellite instability; human genome; logistic regression analysis; fisher exact test; protein msh2; colorectal neoplasms, hereditary nonpolyposis; adenosine triphosphatases; muts homolog 2 protein; autosomal dominant disorder; dna helicases; gene location; autosomal recessive disorder; gene linkage disequilibrium; maximum likelihood method; bloom syndrome; protein blm; humans; human; priority journal; article
Journal Title: Cancer Research
Volume: 64
Issue: 21
ISSN: 0008-5472
Publisher: American Association for Cancer Research  
Date Published: 2004-11-01
Start Page: 8116
End Page: 8125
Language: English
DOI: 10.1158/0008-5472.can-04-1411
PROVIDER: scopus
PUBMED: 15520224
DOI/URL:
Notes: Cancer Res. -- Cited By (since 1996):10 -- Export Date: 16 June 2014 -- CODEN: CNREA -- Source: Scopus
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MSK Authors
  1. Shaokun Chuai
    29 Chuai
  2. Nandita Mitra
    22 Mitra
  3. Kenneth Offit
    789 Offit
  4. Khedoudja Nafa
    243 Nafa
  5. Alexander D Smith
    28 Smith
  6. Nathan A Ellis
    74 Ellis
  7. Tian Z Ye
    14 Ye