Ting Wang1, Jingjin Yang1, Xiaoming Ji1, Minjie Chu2, Ruyang Zhang3, Juncheng Dai3, Guangfu Jin3, Zhibin Hu3, Hongbing Shen3, Chunhui Ni4. 1. Department of Occupational Medicine and Environmental Health, School of Public Health, Nanjing Medical University, Nanjing, China. 2. Department of Epidemiology and Biostatistics and Ministry of Education (MOE) Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Department of Epidemiology and Biostatistics, School of Public Health, Nantong University, Nantong, Jiangsu, China. 3. Department of Epidemiology and Biostatistics and Ministry of Education (MOE) Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. 4. Department of Occupational Medicine and Environmental Health, School of Public Health, Nanjing Medical University, Nanjing, China. Electronic address: chni@njmu.edu.cn.
Abstract
OBJECTIVE: The aim of this investigation was to identify pathways involved in pneumoconiosis susceptibility, clarify their potential mechanisms, and generate SNP-to-gene to pathway hypotheses using an analytical pathway-based approach. METHODS: The identify candidate causal SNPs and pathways (ICSNPathway) was used to perform pathway analysis of a GWAS dataset for pneumoconiosis, which, after quality control filtering, harbored genotypes of 710,999 SNPs in 202 pneumoconiosis cases and 198 exposed controls. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and functional annotation of the most significant SNPs; the second stage involved annotation of biological mechanisms for the selected candidate SNPs using improved-gene set enrichment analysis. RESULTS: ICSNPathway analysis identified 18 candidate SNPs, involving 13 genes and 30 candidate pathways and revealed 13 hypothetical biological mechanisms. The strongest hypothetical biological mechanism was that rs8120 and rs2292151 alters the role of TICAM1, a gene involved in various pathways and processes, including positive regulation of tumor necrosis factor (TNF) production, innate immune response-activating signal transduction, positive regulation of the innate immune response, and the biosynthesis of type I interferon (0.001<p<0.008; 0.001< false discovery rate (FDR) <0.035). The second strongest mechanism was that rs2230656 modulates HIST3H3 to affect its role in chromatin assembly processes (p<0.001; FDR <0.001). The third mechanism was that rs11592462 modulates CDH23, which regulates organization of the inner ear stereocilia, auditory receptor cell morphogenesis, ear morphogenesis, and cellular homeostasis (0.001<p<0.006; 0.001<FDR<0.044). Of 13 candidate genes, TICAM1, HIST3H3, CA1, CA3, PTPRZ1, and IL27RA are associated with fibrosis. Some of the 30 candidate pathways, which include positive regulation of TNF production, innate immune response-activating signal transduction, and regulation of innate immune response, may be associated with susceptibility to pneumoconiosis. Other candidate genes and pathways were novel or lacking fibrosis-related research. CONCLUSION: By applying ICSNPathway analysis to the pneumoconiosis GWAS data, we identified candidate SNPs, genes such as TICAM1 and HIST3H3, and pathways involved in the positive regulation of TNF production that may contribute to pneumoconiosis susceptibility. Further analyses are needed to validate the results.
OBJECTIVE: The aim of this investigation was to identify pathways involved in pneumoconiosis susceptibility, clarify their potential mechanisms, and generate SNP-to-gene to pathway hypotheses using an analytical pathway-based approach. METHODS: The identify candidate causal SNPs and pathways (ICSNPathway) was used to perform pathway analysis of a GWAS dataset for pneumoconiosis, which, after quality control filtering, harbored genotypes of 710,999 SNPs in 202 pneumoconiosis cases and 198 exposed controls. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and functional annotation of the most significant SNPs; the second stage involved annotation of biological mechanisms for the selected candidate SNPs using improved-gene set enrichment analysis. RESULTS: ICSNPathway analysis identified 18 candidate SNPs, involving 13 genes and 30 candidate pathways and revealed 13 hypothetical biological mechanisms. The strongest hypothetical biological mechanism was that rs8120 and rs2292151 alters the role of TICAM1, a gene involved in various pathways and processes, including positive regulation of tumor necrosis factor (TNF) production, innate immune response-activating signal transduction, positive regulation of the innate immune response, and the biosynthesis of type I interferon (0.001<p<0.008; 0.001< false discovery rate (FDR) <0.035). The second strongest mechanism was that rs2230656 modulates HIST3H3 to affect its role in chromatin assembly processes (p<0.001; FDR <0.001). The third mechanism was that rs11592462 modulates CDH23, which regulates organization of the inner ear stereocilia, auditory receptor cell morphogenesis, ear morphogenesis, and cellular homeostasis (0.001<p<0.006; 0.001<FDR<0.044). Of 13 candidate genes, TICAM1, HIST3H3, CA1, CA3, PTPRZ1, and IL27RA are associated with fibrosis. Some of the 30 candidate pathways, which include positive regulation of TNF production, innate immune response-activating signal transduction, and regulation of innate immune response, may be associated with susceptibility to pneumoconiosis. Other candidate genes and pathways were novel or lacking fibrosis-related research. CONCLUSION: By applying ICSNPathway analysis to the pneumoconiosis GWAS data, we identified candidate SNPs, genes such as TICAM1 and HIST3H3, and pathways involved in the positive regulation of TNF production that may contribute to pneumoconiosis susceptibility. Further analyses are needed to validate the results.