Hong Liu1, Bo Wang, Chunsheng Han. 1. State Key Laboratory of Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Abstract
BACKGROUND: Genome-wide and replication association studies (GWAs) have identified multiple loci at which common variants modestly influence the risk of developing prostate cancer (PCa). To enhance the power to identify loci associated with PCa, we constructed a meta-analysis of GWAs on PCa. METHODS: Articles evaluating the effects of genome-wide SNPs on PCa were identified by searching the PubMed database. After extraction of relevant data, main and subgroup meta-analyses were performed to assess the effects of relevant SNPs on PCa. RESULTS: 21 eligible articles containing 71 subgroups were included in this meta-analysis. Significant associations were found between 31 SNPs and PCa. They were rs445114, rs620861, rs983085, rs1016343, rs1447295, rs1859962, rs2660753, rs2710646, rs2735839, rs3760511, rs4242382, rs4430796, rs4962416, rs5945572, rs5945619, rs6470494, rs6501455, rs6983267, rs6983561, rs7000448, rs7214479, rs7501939, rs7920517, rs7931342, rs9364554, rs9623117, rs10090154, rs10486567, rs10896449, rs10993994, and rs16901979. The weighted odds ratios for above SNPs ranged between 0.64 and 1.88 (all P < 0.05). Subgroup analysis further indicated that the significant associations of some SNPs existed only in specific ancestry population (P < 10⁻⁵). CONCLUSIONS: The current meta-analysis demonstrated the moderate effects of above 31 SNPs on PCa and 14 independent PCa risk loci were identified.
BACKGROUND: Genome-wide and replication association studies (GWAs) have identified multiple loci at which common variants modestly influence the risk of developing prostate cancer (PCa). To enhance the power to identify loci associated with PCa, we constructed a meta-analysis of GWAs on PCa. METHODS: Articles evaluating the effects of genome-wide SNPs on PCa were identified by searching the PubMed database. After extraction of relevant data, main and subgroup meta-analyses were performed to assess the effects of relevant SNPs on PCa. RESULTS: 21 eligible articles containing 71 subgroups were included in this meta-analysis. Significant associations were found between 31 SNPs and PCa. They were rs445114, rs620861, rs983085, rs1016343, rs1447295, rs1859962, rs2660753, rs2710646, rs2735839, rs3760511, rs4242382, rs4430796, rs4962416, rs5945572, rs5945619, rs6470494, rs6501455, rs6983267, rs6983561, rs7000448, rs7214479, rs7501939, rs7920517, rs7931342, rs9364554, rs9623117, rs10090154, rs10486567, rs10896449, rs10993994, and rs16901979. The weighted odds ratios for above SNPs ranged between 0.64 and 1.88 (all P < 0.05). Subgroup analysis further indicated that the significant associations of some SNPs existed only in specific ancestry population (P < 10⁻⁵). CONCLUSIONS: The current meta-analysis demonstrated the moderate effects of above 31 SNPs on PCa and 14 independent PCa risk loci were identified.
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