Dataset Information

Integrative post-genome-wide association analysis of CDKN2A and TP53 SNPs and risk of esophageal adenocarcinoma.

ABSTRACT: Incidence of esophageal adenocarcinoma (EA) in Western countries has increased markedly in recent decades. Although several risk factors have been identified for EA and its precursor, Barrett's esophagus (BE), including reflux, Caucasian race, male gender, obesity, and smoking, less is known about the role of inherited genetic variation. Frequent somatic mutations in the tumor suppressor genes CDKN2A and TP53 were recently reported in EA tumors, while somatic alterations at 9p (CDKN2A) and 17p (TP53) have been implicated as predictors of progression from BE to EA. Motivated by these findings, we used data from a genome-wide association study of 2515 EA cases and 3207 controls to analyze 37 germline single nucleotide polymorphisms at the CDKN2A and TP53 loci. Three CDKN2A polymorphisms were nominally associated (P < 0.05) with reduced risk of EA: rs2518720 C>T [intronic, odds ratio 0.90, P = 0.0121, q = 0.3059], rs3088440 G>A (3'UTR, odds ratio 0.84, P = 0.0186, q = 0.3059), and rs4074785 C>T (intronic, odds ratio 0.85, P = 0.0248, q = 0.3059). None of the TP53 single nucleotide polymorphisms reached nominal significance. Two of the CDKN2A variants identified were also associated with reduced risk of progression from BE to EA, when assessed in a prospective cohort of 408 BE patients: rs2518720 (hazard ratio 0.57, P = 0.0095, q = 0.0285) and rs3088440 (hazard ratio 0.34, P = 0.0368, q = 0.0552). In vitro functional studies of rs3088440, a single nucleotide polymorphism located in the seed sequence of a predicted miR-663b binding site, suggested a mechanism whereby the G>A substitution may attenuate miR-663b-mediated repression of the CDKN2A transcript. This study provides the first evidence that germline variation at the CDKN2A locus may influence EA susceptibility.

SUBMITTER: Buas MF

PROVIDER: S-EPMC4247522 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrative post-genome-wide association analysis of CDKN2A and TP53 SNPs and risk of esophageal adenocarcinoma.

Buas Matthew F MF Levine David M DM Makar Karen W KW Utsugi Heidi H Onstad Lynn L Li Xiaohong X Galipeau Patricia C PC Shaheen Nicholas J NJ Hardie Laura J LJ Romero Yvonne Y Bernstein Leslie L Gammon Marilie D MD Casson Alan G AG Bird Nigel C NC Risch Harvey A HA Ye Weimin W Liu Geoffrey G Corley Douglas A DA Blount Patricia L PL Fitzgerald Rebecca C RC Whiteman David C DC Wu Anna H AH Reid Brian J BJ Vaughan Thomas L TL

Carcinogenesis 20141003 12

Incidence of esophageal adenocarcinoma (EA) in Western countries has increased markedly in recent decades. Although several risk factors have been identified for EA and its precursor, Barrett's esophagus (BE), including reflux, Caucasian race, male gender, obesity, and smoking, less is known about the role of inherited genetic variation. Frequent somatic mutations in the tumor suppressor genes CDKN2A and TP53 were recently reported in EA tumors, while somatic alterations at 9p (CDKN2A) and 17p ( ...[more]

PMID: 25280564

Similar Datasets

Project description:BackgroundRecently mixed linear models are used to address the issue of "missing" heritability in traditional Genome-wide association studies (GWAS). The models assume that all single-nucleotide polymorphisms (SNPs) are associated with the phenotypes of interest. However, it is more common that only a small proportion of SNPs have significant effects on the phenotypes, while most SNPs have no or very small effects. To incorporate this feature, we propose an efficient Hierarchical Bayesian Model (HBM) that extends the existing mixed models to enforce automatic selection of significant SNPs. The HBM models the SNP effects using a mixture distribution of a point mass at zero and a normal distribution, where the point mass corresponds to those non-associative SNPs.ResultsWe estimate the HBM using Gibbs sampling. The estimation performance of our method is first demonstrated through two simulation studies. We make the simulation setups realistic by using parameters fitted on the Framingham Heart Study (FHS) data. The simulation studies show that our method can accurately estimate the proportion of SNPs associated with the simulated phenotype and identify these SNPs, as well as adapt to certain model mis-specification than the standard mixed models. In addition, we analyze data from the FHS and the Health and Retirement Study (HRS) to study the association between Body Mass Index (BMI) and SNPs on Chromosome 16, and replicate the identified genetic associations. The analysis of the FHS data identifies 0.3% SNPs on Chromosome 16 that affect BMI, including rs9939609 and rs9939973 on the FTO gene. These two SNPs are in strong linkage disequilibrium with rs1558902 (Rsq =0.901 for rs9939609 and Rsq =0.905 for rs9939973), which has been reported to be linked with obesity in previous GWAS. We then replicate the findings using the HRS data: the analysis finds 0.4% of SNPs associated with BMI on Chromosome 16. Furthermore, around 25% of the genes that are identified to be associated with BMI are common between the two studies.ConclusionsThe results demonstrate that the HBM and the associated estimation algorithm offer a powerful tool for identifying significant genetic associations with phenotypes of interest, among a large number of SNPs that are common in modern genetics studies.

Dataset Information

Integrative post-genome-wide association analysis of CDKN2A and TP53 SNPs and risk of esophageal adenocarcinoma.

Publications

Integrative post-genome-wide association analysis of CDKN2A and TP53 SNPs and risk of esophageal adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets