BACKGROUND: Prostate-specific antigen (PSA) is a useful marker for prostate cancer (PCa) and is widely used for screening of PCa. Previous studies have shown that genetic components influence the levels of PSA, and some of these genetic components would lead to better diagnostic sensitivity and specificity to PCa. However, genetic studies for PSA from Asian countries are limited. Our aim was to identify genetic components influencing PSA levels in the Japanese population using genome-wide association study (GWAS) and to analyse whether genetic components would lead to better screening abilities of PCa. METHODS: We performed a GWAS comprising 1086 male subjects using 303 283 single nucleotide proteins, followed by a replication study of 1302 subjects. PSA levels were quantified by chemiluminescence immunoassay method. Quantitative linear regression analysis was performed to assess genetic components of PSA levels. A total of 413 subjects with prostate biopsies were analysed to examine whether genetic determinants would improve diagnostic ability. RESULTS: Rs16856139 in SLC45A3, the same region as the previous Chinese study, showed an overall significant association with PSA levels (p=2.4×10(-11)) along with rs1058205 in KLK3. In silico analysis revealed significant association between rs16856139 and expression of SLC45A3. Genetic scores of PSA showed a dose-dependent decrease of area under curve (AUC) of PCa and successfully subgrouped the individuals with significantly different AUC (p≤0.0097). CONCLUSIONS: Rs16856139, associated with the expression of SLC45A3, is significantly associated with the levels of PSA in the Japanese population. Classification of subjects based on PSA genetic determinants would improve screening ability of PSA to detect PCa. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
BACKGROUND:Prostate-specific antigen (PSA) is a useful marker for prostate cancer (PCa) and is widely used for screening of PCa. Previous studies have shown that genetic components influence the levels of PSA, and some of these genetic components would lead to better diagnostic sensitivity and specificity to PCa. However, genetic studies for PSA from Asian countries are limited. Our aim was to identify genetic components influencing PSA levels in the Japanese population using genome-wide association study (GWAS) and to analyse whether genetic components would lead to better screening abilities of PCa. METHODS: We performed a GWAS comprising 1086 male subjects using 303 283 single nucleotide proteins, followed by a replication study of 1302 subjects. PSA levels were quantified by chemiluminescence immunoassay method. Quantitative linear regression analysis was performed to assess genetic components of PSA levels. A total of 413 subjects with prostate biopsies were analysed to examine whether genetic determinants would improve diagnostic ability. RESULTS:Rs16856139 in SLC45A3, the same region as the previous Chinese study, showed an overall significant association with PSA levels (p=2.4×10(-11)) along with rs1058205 in KLK3. In silico analysis revealed significant association between rs16856139 and expression of SLC45A3. Genetic scores of PSA showed a dose-dependent decrease of area under curve (AUC) of PCa and successfully subgrouped the individuals with significantly different AUC (p≤0.0097). CONCLUSIONS:Rs16856139, associated with the expression of SLC45A3, is significantly associated with the levels of PSA in the Japanese population. Classification of subjects based on PSA genetic determinants would improve screening ability of PSA to detect PCa. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Authors: Thomas J Hoffmann; Michael N Passarelli; Rebecca E Graff; Nima C Emami; Lori C Sakoda; Eric Jorgenson; Laurel A Habel; Jun Shan; Dilrini K Ranatunga; Charles P Quesenberry; Chun R Chao; Nirupa R Ghai; David Aaronson; Joseph Presti; Tobias Nordström; Zhaoming Wang; Sonja I Berndt; Stephen J Chanock; Jonathan D Mosley; Robert J Klein; Mridu Middha; Hans Lilja; Olle Melander; Mark N Kvale; Pui-Yan Kwok; Catherine Schaefer; Neil Risch; Stephen K Van Den Eeden; John S Witte Journal: Nat Commun Date: 2017-01-31 Impact factor: 14.919