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Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer.

ABSTRACT: Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung cancer was explored using sequential kernel association test (SKAT) analysis. For single variant analysis, we combined the result of specific study using fixed-effect meta-analysis. We performed functional exploration of significant associations based on features from public databases. To further detect the biological mechanism underlying identified observations, pathway enrichment analysis were conducted with R package "clusterProfiler." SNP-set analysis revealed the overall associations between variants of 8 cancer types and lung cancer risk. Single variant analysis identified 6 novel SNPs related to lung cancer risk after multiple correction (P fdr < 0.10), including rs1707302 (1p34.1, OR = 0.93, 95% CI: 0.90-0.97, P = 7.60 × 10-4), rs2516448 (6p21.33, OR = 1.07, 95% CI: 1.03-1.11, P = 1.00 × 10-3), rs3869062 (6p22.1, OR = 0.91, 95% CI: 0.86-0.96, P = 7.10 × 10-4), rs174549 (11q12.2, OR = 0.90, 95% CI: 0.87-0.94, P = 1.00 × 10-7), rs7193541 (16q23.1, OR = 0.93, 95% CI: 0.90-0.96, P = 1.20 × 10-4), and rs8064454 (17q12, OR = 1.07, 95% CI: 1.03-1.11, P = 4.30 × 10-4). The eQTL analysis and functional annotation suggested that these variants might modify lung cancer susceptibility through regulating the expression of related genes. Pathway enrichment analysis showed that genes modulated by these variants play important roles in cancer carcinogenesis. Our findings demonstrate the pleiotropic associations between non-lung cancer susceptibility loci and lung cancer risk, providing important insights into the shared mechanisms of carcinogenesis across cancers.

SUBMITTER: Wang L

PROVIDER: S-EPMC6974684 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer.

Wang Lijuan L Zhu Meng M Wang Yuzhuo Y Fan Jingyi J Sun Qi Q Ji Mengmeng M Fan Xikang X Xie Junxing J Dai Juncheng J Jin Guangfu G Hu Zhibin Z Ma Hongxia H Shen Hongbing H

Frontiers in oncology 20200115

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung ...[more]

PMID: 32010612

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Project description:OBJECTIVE:Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease and has a strong genomic component. To date, JIA genetic association studies have had limited sample sizes, used heterogeneous patient populations, or included only candidate regions. The aim of this study was to identify new associations between JIA patients with oligoarticular disease and those with IgM rheumatoid factor (RF)-negative polyarticular disease, which are clinically similar and the most prevalent JIA disease subtypes. METHODS:Three cohorts comprising 2,751 patients with oligoarticular or RF-negative polyarticular JIA were genotyped using the Affymetrix Genome-Wide SNP Array 6.0 or the Illumina HumanCoreExome-12+ Array. Overall, 15,886 local and out-of-study controls, typed on these platforms or the Illumina HumanOmni2.5, were used for association analyses. High-quality single-nucleotide polymorphisms (SNPs) were used for imputation to 1000 Genomes prior to SNP association analysis. RESULTS:Meta-analysis showed evidence of association (P < 1 × 10-6 ) at 9 regions: PRR9_LOR (P = 5.12 × 10-8 ), ILDR1_CD86 (P = 6.73 × 10-8 ), WDFY4 (P = 1.79 × 10-7 ), PTH1R (P = 1.87 × 10-7 ), RNF215 (P = 3.09 × 10-7 ), AHI1_LINC00271 (P = 3.48 × 10-7 ), JAK1 (P = 4.18 × 10-7 ), LINC00951 (P = 5.80 × 10-7 ), and HBP1 (P = 7.29 × 10-7 ). Of these, PRR9_LOR, ILDR1_CD86, RNF215, LINC00951, and HBP1 were shown, for the first time, to be autoimmune disease susceptibility loci. Furthermore, associated SNPs included cis expression quantitative trait loci for WDFY4, CCDC12, MTP18, SF3A1, AHI1, COG5, HBP1, and GPR22. CONCLUSION:This study provides evidence of both unique JIA risk loci and risk loci overlapping between JIA and other autoimmune diseases. These newly associated SNPs are shown to influence gene expression, and their bounding regions tie into molecular pathways of immunologic relevance. Thus, they likely represent regions that contribute to the pathology of oligoarticular JIA and RF-negative polyarticular JIA.

Dataset Information

Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer.

Publications

Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer.

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