Lili Pan , Shuang Yao , Xueting Zhu , Guanghua Luo
{"title":"胆结石疾病风险的遗传易感位点和预测/诊断模型","authors":"Lili Pan , Shuang Yao , Xueting Zhu , Guanghua Luo","doi":"10.1016/j.gene.2025.149758","DOIUrl":null,"url":null,"abstract":"<div><div>This study screened and identified gallstone disease (GSD) high-frequency mutation sites through sequencing of whole blood samples from 197 cases and 191 controls. Subsequently, a self-developed two-dimensional PCR (2D-PCR) method was employed to genotype the GSD susceptibility loci, which were determined through genome-wide association studies (GWAS), in 595 cases and 393 controls: <em>TM4SF4</em> (rs9843304), <em>GCKR</em> (rs1260326), and <em>CYP7A1</em> (rs6471717). We compared the genotype and allele frequencies among these groups, and performed univariate and multivariate logistic regression analyses to identify risk factors for GSD. The R programming language was used to develop a predictive model, validated through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). After adjusting for sex and age, the rs9843304 TT genotype (OR: 0.51, 95 % CI: 0.36–0.74, <em>P</em> < 0.001) and and rs1260326 TT genotype (OR: 0.65, 95 % CI: 0.45–0.95, <em>P</em> = 0.03) were significantly associated with a lower risk of GSD compared to the CC genotype. Two nomograms were constructed and validated: (1) a comprehensive diagnostic model including liver-function tests, and (2) a streamlined predictive model excluding them. Discrimination, calibration and clinical utility were assessed with ROC curves, calibration plots and DCA. The full model achieved AUCs of 0.800 (training) and 0.806 (validation); the simplified model reached 0.713 and 0.746. Calibration curves indicated a good fit and DCA showed net-benefit thresholds of 0.38–1.00 (training) and 0.30–1.00 (validation) for the simplified model, and 0.18–1.00 for the full model. In summary, 2D-PCR offers an efficient, low-cost platform for GSD genetic screening, and the nomograms enable individualized risk prediction suitable for primary-care and health-check settings.</div></div>","PeriodicalId":12499,"journal":{"name":"Gene","volume":"969 ","pages":"Article 149758"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic susceptibility loci and predictive/diagnostic model for gallstone disease risk\",\"authors\":\"Lili Pan , Shuang Yao , Xueting Zhu , Guanghua Luo\",\"doi\":\"10.1016/j.gene.2025.149758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study screened and identified gallstone disease (GSD) high-frequency mutation sites through sequencing of whole blood samples from 197 cases and 191 controls. Subsequently, a self-developed two-dimensional PCR (2D-PCR) method was employed to genotype the GSD susceptibility loci, which were determined through genome-wide association studies (GWAS), in 595 cases and 393 controls: <em>TM4SF4</em> (rs9843304), <em>GCKR</em> (rs1260326), and <em>CYP7A1</em> (rs6471717). We compared the genotype and allele frequencies among these groups, and performed univariate and multivariate logistic regression analyses to identify risk factors for GSD. The R programming language was used to develop a predictive model, validated through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). After adjusting for sex and age, the rs9843304 TT genotype (OR: 0.51, 95 % CI: 0.36–0.74, <em>P</em> < 0.001) and and rs1260326 TT genotype (OR: 0.65, 95 % CI: 0.45–0.95, <em>P</em> = 0.03) were significantly associated with a lower risk of GSD compared to the CC genotype. Two nomograms were constructed and validated: (1) a comprehensive diagnostic model including liver-function tests, and (2) a streamlined predictive model excluding them. Discrimination, calibration and clinical utility were assessed with ROC curves, calibration plots and DCA. The full model achieved AUCs of 0.800 (training) and 0.806 (validation); the simplified model reached 0.713 and 0.746. Calibration curves indicated a good fit and DCA showed net-benefit thresholds of 0.38–1.00 (training) and 0.30–1.00 (validation) for the simplified model, and 0.18–1.00 for the full model. In summary, 2D-PCR offers an efficient, low-cost platform for GSD genetic screening, and the nomograms enable individualized risk prediction suitable for primary-care and health-check settings.</div></div>\",\"PeriodicalId\":12499,\"journal\":{\"name\":\"Gene\",\"volume\":\"969 \",\"pages\":\"Article 149758\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gene\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378111925005475\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gene","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378111925005475","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Genetic susceptibility loci and predictive/diagnostic model for gallstone disease risk
This study screened and identified gallstone disease (GSD) high-frequency mutation sites through sequencing of whole blood samples from 197 cases and 191 controls. Subsequently, a self-developed two-dimensional PCR (2D-PCR) method was employed to genotype the GSD susceptibility loci, which were determined through genome-wide association studies (GWAS), in 595 cases and 393 controls: TM4SF4 (rs9843304), GCKR (rs1260326), and CYP7A1 (rs6471717). We compared the genotype and allele frequencies among these groups, and performed univariate and multivariate logistic regression analyses to identify risk factors for GSD. The R programming language was used to develop a predictive model, validated through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). After adjusting for sex and age, the rs9843304 TT genotype (OR: 0.51, 95 % CI: 0.36–0.74, P < 0.001) and and rs1260326 TT genotype (OR: 0.65, 95 % CI: 0.45–0.95, P = 0.03) were significantly associated with a lower risk of GSD compared to the CC genotype. Two nomograms were constructed and validated: (1) a comprehensive diagnostic model including liver-function tests, and (2) a streamlined predictive model excluding them. Discrimination, calibration and clinical utility were assessed with ROC curves, calibration plots and DCA. The full model achieved AUCs of 0.800 (training) and 0.806 (validation); the simplified model reached 0.713 and 0.746. Calibration curves indicated a good fit and DCA showed net-benefit thresholds of 0.38–1.00 (training) and 0.30–1.00 (validation) for the simplified model, and 0.18–1.00 for the full model. In summary, 2D-PCR offers an efficient, low-cost platform for GSD genetic screening, and the nomograms enable individualized risk prediction suitable for primary-care and health-check settings.
期刊介绍:
Gene publishes papers that focus on the regulation, expression, function and evolution of genes in all biological contexts, including all prokaryotic and eukaryotic organisms, as well as viruses.