Objective:In this study,we aimed to identify novel genetic loci and protein biomarkers associated with silicosis susceptibility in Chinese workers through integrated proteomic and genomic analyses and to develop an ea...Objective:In this study,we aimed to identify novel genetic loci and protein biomarkers associated with silicosis susceptibility in Chinese workers through integrated proteomic and genomic analyses and to develop an early diagnostic prediction model.Methods:A genome-wide association study(GWAS)was conducted on 163 patients with silicosis and 183 controls,followed by Olink proteomic profiling of 92 plasma proteins.Protein quantitative trait loci(pQTL)mapping,Mendelian randomization(MR),and Bayesian co-localization were used to infer causal relationships.A causal protein risk score(CPRS)model integrating genetic and proteomic data was developed and validated using 10-fold cross-validation.Results:GWAS identified 16 novel risk loci(P<1×10^(-5)),including rs6677666(WLS)and rs2272528(COL4A4).MR analysis revealed eight plasma proteins associated with silicosis risk,with MMP12,EGF,Gal_9,GZMA,and ICOSLG showing significant differential expression(P<0.05).The CPRS model combining these proteins demonstrated a high diagnostic accuracy(AUC=0.915),outperforming traditional clinical variables.Conclusion:This multi-omics study uncovered genetic and proteomic markers linked to silicosis susceptibility and established a robust predictive model.The integration of GWAS and proteomics offers novel insights into the pathogenesis of silicosis,and supports development of early detection and prevention policies for high-risk populations.展开更多
基金Supported by the Jiangsu Provincial Social Development Program of the Key R&D Project(BE2022803)Natural Science Foundation of Jiangsu(BK20201485)+1 种基金Jiangsu Provincial Key Medical Discipline(ZDXK202249)Scientific Research Project of Jiangsu Health Commission(M2022085).
文摘Objective:In this study,we aimed to identify novel genetic loci and protein biomarkers associated with silicosis susceptibility in Chinese workers through integrated proteomic and genomic analyses and to develop an early diagnostic prediction model.Methods:A genome-wide association study(GWAS)was conducted on 163 patients with silicosis and 183 controls,followed by Olink proteomic profiling of 92 plasma proteins.Protein quantitative trait loci(pQTL)mapping,Mendelian randomization(MR),and Bayesian co-localization were used to infer causal relationships.A causal protein risk score(CPRS)model integrating genetic and proteomic data was developed and validated using 10-fold cross-validation.Results:GWAS identified 16 novel risk loci(P<1×10^(-5)),including rs6677666(WLS)and rs2272528(COL4A4).MR analysis revealed eight plasma proteins associated with silicosis risk,with MMP12,EGF,Gal_9,GZMA,and ICOSLG showing significant differential expression(P<0.05).The CPRS model combining these proteins demonstrated a high diagnostic accuracy(AUC=0.915),outperforming traditional clinical variables.Conclusion:This multi-omics study uncovered genetic and proteomic markers linked to silicosis susceptibility and established a robust predictive model.The integration of GWAS and proteomics offers novel insights into the pathogenesis of silicosis,and supports development of early detection and prevention policies for high-risk populations.
