Dataset Information

Deciphering associations for lung cancer risk through imputation and analysis of 12,316 cases and 16,831 controls.

ABSTRACT: Recent genome-wide association studies have identified common variants at multiple loci influencing lung cancer risk. To decipher the genetic basis of the association signals at 3q28, 5p15.33, 6p21.33, 9p21 and 12p13.33, we performed a meta-analysis of data from five genome-wide association studies in populations of European ancestry totalling 12?316 lung cancer cases and 16?831 controls using imputation to recover untyped genotypes. For four of the regions, it was possible to refine the association signal identifying a smaller region of interest likely to harbour the functional variant. Our analysis did not provide evidence that any of the associations at the loci being a consequence of synthetic associations rather than linkage disequilibrium with a common risk variant at these risk loci.

SUBMITTER: Wang Y

PROVIDER: S-EPMC4795209 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Deciphering associations for lung cancer risk through imputation and analysis of 12,316 cases and 16,831 controls.

Wang Yufei Y Wei Yongyue Y Gaborieau Valerie V Shi Jianxin J Han Younghun Y Timofeeva Maria N MN Su Li L Li Yafang Y Eisen Timothy T Amos Christopher I CI Landi Maria Teresa MT Christiani David C DC McKay James D JD Houlston Richard S RS

European journal of human genetics : EJHG 20150325 12

Recent genome-wide association studies have identified common variants at multiple loci influencing lung cancer risk. To decipher the genetic basis of the association signals at 3q28, 5p15.33, 6p21.33, 9p21 and 12p13.33, we performed a meta-analysis of data from five genome-wide association studies in populations of European ancestry totalling 12 316 lung cancer cases and 16 831 controls using imputation to recover untyped genotypes. For four of the regions, it was possible to refine the associa ...[more]

PMID: 25804397

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Project description:BackgroundEvidence suggests that MDM2 T309G polymorphism may be a risk factor for several cancers. Increasing investigations have been conducted on the association of MDM2 T309G polymorphisms with lung cancer risk and have yielded conflicting results. Previous meta-analyses on this issue have reported inconclusive data. The aim of the present study was to derive a more precise estimation of the relationship.Methods and findingsUpdated meta-analyses examining the association between MDM2 T309G polymorphism and lung cancer risk were performed. Separate analyses on ethnicity, smoking status, histological types and gender as well as source of controls were also implemented. Eligible studies were identified for the period up to Feb 2012. Lastly, ten publications including eleven case-control studies were selected for analysis. The overall data failed to indicate a significant association between MDM2 T309G polymorphism and lung cancer risk (GG vs TT OR = 1.14; 95%CI = 0.95-1.37; dominant model: OR = 1.05; 95%CI = 0.92-1.19; recessive model: OR = 1.12; 95%CI = 0.99-1.27). In a subgroup analysis by smoking status, increased lung cancer risk was shown among never-smokers (GG vs TT: OR = 1.76; 95%CI = 1.36-2.29; dominant model: OR = 1.48; 95%CI = 1.22-1.81; recessive model: OR = 1.37; 95%CI = 1.11-1.69). In subgroup analysis by gender, elevated risk was presented among women under a recessive model (OR = 1.29; 95%CI = 1.04-1.59). In the subgroup analysis by ethnicity, histological types and source of controls, no marked associations were observed.ConclusionsCompared to the previous meta-analyses, the results of this study confirmed that MDM2 T309G polymorphism might be a risk factor for lung cancer among never-smokers. However, the data failed to suggest a marked association between the G allele of MDM2 T309G and lung cancer risk among Asians. More interestingly, subgroup analysis by gender indicated that homozygous GG alleles might raise lung cancer risk among females.

Dataset Information

Deciphering associations for lung cancer risk through imputation and analysis of 12,316 cases and 16,831 controls.

Publications

Deciphering associations for lung cancer risk through imputation and analysis of 12,316 cases and 16,831 controls.

Similar Datasets

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