Dataset Information

Systematic meta-analyses of gene-specific genetic association studies in prostate cancer.

ABSTRACT: In the past twenty-five years, over 700 case-control association studies on the risk of prostate cancer have been published worldwide, but their results were largely inconsistent. To facilitate following and explaining these findings, we performed a systematic meta-analysis using allelic contrasts for gene-specific SNVs from at least three independent population-based case-control studies, which were published in the field of prostate cancer between August 1, 1990 and August 1, 2015. Across 66 meta-analyses, a total of 20 genetic variants involving 584,100 subjects in 19 different genes (KLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) exhibited significant association with prostate cancer. The average summary OR was 1.33 (ranging from: 1.016-3.788) for risk alleles and 0.838 (ranging from: 0.757-0.896) for protective alleles. Of these positive variants, FOXP4 rs1983891, LMTK2 rs6465657 and RFX6 rs339331 had not been previously meta-analyzed. Further analyses with sufficient power design and investigations of the potential biological roles of these genetic variants in prostate cancer should be conducted.

SUBMITTER: Hao Q

PROVIDER: S-EPMC5008361 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Systematic meta-analyses of gene-specific genetic association studies in prostate cancer.

Hao Qiang Q Wei Dong D Zhang Yaoguang Y Chen Xin X Yang Fan F Yang Ze Z Zhu Xiaoquan X Wang Jianye J

Oncotarget 20160401 16

In the past twenty-five years, over 700 case-control association studies on the risk of prostate cancer have been published worldwide, but their results were largely inconsistent. To facilitate following and explaining these findings, we performed a systematic meta-analysis using allelic contrasts for gene-specific SNVs from at least three independent population-based case-control studies, which were published in the field of prostate cancer between August 1, 1990 and August 1, 2015. Across 66 m ...[more]

PMID: 26967244

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Project description:BackgroundAlthough genetic studies have reported a number of loci associated with cutaneous melanoma (CM) risk, a comprehensive synopsis of genetic association studies published in the field and systematic meta-analysis for all eligible polymorphisms have not been reported.MethodsWe systematically annotated data from all genetic association studies published in the CM field (n = 145), including data from genome-wide association studies (GWAS), and performed random-effects meta-analyses across all eligible polymorphisms on the basis of four or more independent case-control datasets in the main analyses. Supplementary analyses of three available datasets derived from GWAS and GWAS-replication studies were also done. Nominally statistically significant associations between polymorphisms and CM were graded for the strength of epidemiological evidence on the basis of the Human Genome Epidemiology Network Venice criteria. All statistical tests were two-sided.ResultsForty-two polymorphisms across 18 independent loci evaluated in four or more datasets including candidate gene studies and available GWAS data were subjected to meta-analysis. Eight loci were identified in the main meta-analyses as being associated with a risk of CM (P < .05) of which four loci showed a genome-wide statistically significant association (P < 1 × 10(-7)), including 16q24.3 (MC1R), 20q11.22 (MYH7B/PIGU/ASIP), 11q14.3 (TYR), and 5p13.2 (SLC45A2). Grading of the cumulative evidence by the Venice criteria suggested strong epidemiological credibility for all four loci with genome-wide statistical significance and one additional gene at 9p23 (TYRP1). In the supplementary meta-analyses, a locus at 9p21.3 (CDKN2A/MTAP) reached genome-wide statistical significance with CM and had strong epidemiological credibility.ConclusionsTo the best of our knowledge, this is the first comprehensive field synopsis and systematic meta-analysis to identify genes associated with an increased susceptibility to CM.

Dataset Information

Systematic meta-analyses of gene-specific genetic association studies in prostate cancer.

Publications

Systematic meta-analyses of gene-specific genetic association studies in prostate cancer.

Similar Datasets

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