{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T04:26:12Z","timestamp":1786940772815,"version":"build-2736575974"},"reference-count":33,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background\/Objectives: GWASs have identified more than 250 prostate cancer (PCa) predisposition loci, predominantly in European and partly Asian cohorts. The Kazakh population is markedly under-represented in international genetic studies, limiting existing risk models. This study aimed to analyze the distribution of 102 PCa-associated single-nucleotide polymorphism (SNP) genotypes and alleles and to identify reliable population-specific associations with PCa risk in Kazakh men. Methods: This retrospective case\u2013control study included 941 Kazakh men (476 with histologically confirmed PCa and 465 cancer-free controls). Genomic DNA extracted from peripheral blood was genotyped with TaqMan\u00ae OpenArray\u00ae technology on a QuantStudio 12K Flex system. Associations were assessed by Pearson\u2019s \u03c72 test and logistic regression, with genotypic and allelic odds ratios (OR) and 95% confidence intervals (CI). Two-step multiple-testing correction (Bonferroni and Benjamini\u2013Hochberg false-discovery rate, FDR) was applied. Predictive models were built using classification and regression trees (CART) and stepwise logistic regression. Results: Of 102 SNPs, 39 showed nominally significant genotypic differences; 12 remained significant after Bonferroni correction and 2 after FDR (14 in total). Several of the corrected loci were significant at both the genotypic and allelic level. Allelic ORs ranged from 0.37 (protective rs10187424 T allele) to 4.81 (rs1545985). A parsimonious seven-SNP autosomal logistic-regression model achieved an apparent AuROC of 0.84 (10-fold cross-validated 0.82); adding age as a covariate raised discrimination to 0.87. Ten of the fourteen significant loci remained significant after age adjustment, and six of these formed a core signal robust to both age imbalance and genotyping-quality concerns. Conclusions: This first large-scale SNP-association study in Kazakh men shows allele-frequency profiles resembling East Asian rather than European populations, confirming the need for population-specific genetic risk-assessment tools. The seven-SNP model showed high discriminatory power in the training set and requires external validation before clinical application.<\/jats:p>","DOI":"10.3390\/genes17080956","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T15:48:36Z","timestamp":1786722516000},"page":"956","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Population-Specific Genetic Markers of Prostate Cancer Risk in Kazakh Men: Association Analysis of 102 SNPs and Risk Prediction Modeling"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-3289-2181","authenticated-orcid":false,"given":"Kairat","family":"Kazbekov","sequence":"first","affiliation":[{"name":"Medical Center Hospital of the President\u2019s Affairs Administration of the Republic of Kazakhstan, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yerbol","family":"Zhapparov","sequence":"additional","affiliation":[{"name":"International Oncological Tomotherapy Center \u201cUmit\u201d, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2976-259X","authenticated-orcid":false,"given":"Nasrulla","family":"Shanazarov","sequence":"additional","affiliation":[{"name":"Medical Center Hospital of the President\u2019s Affairs Administration of the Republic of Kazakhstan, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valery","family":"Benberin","sequence":"additional","affiliation":[{"name":"Medical Center Hospital of the President\u2019s Affairs Administration of the Republic of Kazakhstan, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sergey","family":"Zinchenko","sequence":"additional","affiliation":[{"name":"Department of Surgery, Kazan Federal University, Kazan 420008, Republic of Tatarstan, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8300-2006","authenticated-orcid":false,"given":"Ainagul","family":"Kazbekova","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Astana Medical University, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,14]]},"reference":[{"key":"ref_1","first-page":"229","article-title":"Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. 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