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Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq
Published on: April 19, 2013
Genetic susceptibility loci and predictive/diagnostic model for gallstone disease risk
Lili Pan1, Shuang Yao1, Xueting Zhu2
1Clinical Medical Research Center, The First People's Hospital of Changzhou & the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu Province 213003, China.
Abstract:
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.
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