Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes
Abstract Lung cancer is a malignant tumor with a high morbidity and mortality rate worldwide, causing an increasing disease burden. Of these, the most common type is non-small cell lung cancer (NSCLC), which accounts for 80–85% of all lung cancer cases. Genetic research is crucial for continuously d...
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Nature Portfolio
2025-03-01
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| author | Xiaohang Xu Luopiao Xu Zeyong Lang Gege Sun Junlong Pan Xue Li Zilong Bian Xifeng Wu |
| author_facet | Xiaohang Xu Luopiao Xu Zeyong Lang Gege Sun Junlong Pan Xue Li Zilong Bian Xifeng Wu |
| author_sort | Xiaohang Xu |
| collection | DOAJ |
| description | Abstract Lung cancer is a malignant tumor with a high morbidity and mortality rate worldwide, causing an increasing disease burden. Of these, the most common type is non-small cell lung cancer (NSCLC), which accounts for 80–85% of all lung cancer cases. Genetic research is crucial for continuously discovering susceptibility genes related to lung cancer for in-depth study. The role of genetic predisposition in the development of NSCLC, particularly within circadian rhythm pathways known to govern various physiological processes, is increasingly acknowledged. Yet, the association between genetic variants of circadian rhythm-related genes and NSCLC susceptibility among Chinese populations is not fully understood. This study carried out a two-phase (discovery and validation stages) research design to identify genetic variants associated with NSCLC risk within the circadian rhythm pathway. We employed extensive whole-genome sequencing (WGS) for 1,104 NSCLC cases and 9,635 controls. FastGWA-GLMM was used for single-locus risk association analysis of NSCLC, and we screened candidate SNPs in the validation set that comprised 4,444 cases and 174,282 controls from the Biobank Japan Project (BBJ). Furthermore, GCTA-COJO conditional analysis was utilized to confirm SNPs related to NSCLC risk. Finally, potential genetic variations that may regulate gene expression were explored in GTEx and QTLbase. RNA sequencing data were utilized for transcriptomic verification. Our study identified eight candidate SNPs associated with NSCLC susceptibility within the circadian rhythm pathway that met the requirement with P < 0.05 in both the discovery and validation populations. After conditional analysis, five of these SNPs remained. The A allele of CUL1 rs78524436 (ORmeta = 1.18, 95%CI: 1.09–1.29, P meta = 7.99e-5) and the A allele of TEF rs9611588 (ORmeta = 1.06, 95%CI: 1.02–1.10, P meta = 1.28e-3) were associated with an increased risk of NSCLC. The A allele of FBXL21 rs2069868 (ORmeta = 0.86, 95%CI: 0.80–0.96, P meta = 4.78e-4), the T allele of CSNK1D rs147316973 (ORmeta = 0.76, 95%CI: 0.65–0.88, P meta = 5.93e-4), and the A allele of RORA rs1589701 (ORmeta = 0.94, 95%CI: 0.91–0.98, P meta = 3.40e-3) were associated with a lower risk of NSCLC, separately. The eQTL results revealed an association between RORA rs1589701 and TEF rs9611588 with the expression levels of RORA and TEF, respectively. Transcriptome data indicated that RORA and TEF showed lower expression levels in tumor tissues compared to normal tissues (P < 0.001). Moreover, poorer survival was observed in patients with lower RORA and TEF expressions (log-rank P < 0.05). Our findings spotlight potential susceptibility loci within circadian rhythm pathway genes that modulate NSCLC carcinogenesis, which enriches the understanding of the genetic susceptibility of NSCLC in the Chinese population and provides a more solid basis for exploring the biological mechanism of circadian rhythm genes in NSCLC. |
| format | Article |
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| institution | DOAJ |
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| publishDate | 2025-03-01 |
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| spelling | doaj-art-9f2ccf0e567b45a296fd2cd6d8aa1a572025-08-20T03:06:01ZengNature PortfolioScientific Reports2045-23222025-03-0115111310.1038/s41598-025-92083-9Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genesXiaohang Xu0Luopiao Xu1Zeyong Lang2Gege Sun3Junlong Pan4Xue Li5Zilong Bian6Xifeng Wu7Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of MedicineAbstract Lung cancer is a malignant tumor with a high morbidity and mortality rate worldwide, causing an increasing disease burden. Of these, the most common type is non-small cell lung cancer (NSCLC), which accounts for 80–85% of all lung cancer cases. Genetic research is crucial for continuously discovering susceptibility genes related to lung cancer for in-depth study. The role of genetic predisposition in the development of NSCLC, particularly within circadian rhythm pathways known to govern various physiological processes, is increasingly acknowledged. Yet, the association between genetic variants of circadian rhythm-related genes and NSCLC susceptibility among Chinese populations is not fully understood. This study carried out a two-phase (discovery and validation stages) research design to identify genetic variants associated with NSCLC risk within the circadian rhythm pathway. We employed extensive whole-genome sequencing (WGS) for 1,104 NSCLC cases and 9,635 controls. FastGWA-GLMM was used for single-locus risk association analysis of NSCLC, and we screened candidate SNPs in the validation set that comprised 4,444 cases and 174,282 controls from the Biobank Japan Project (BBJ). Furthermore, GCTA-COJO conditional analysis was utilized to confirm SNPs related to NSCLC risk. Finally, potential genetic variations that may regulate gene expression were explored in GTEx and QTLbase. RNA sequencing data were utilized for transcriptomic verification. Our study identified eight candidate SNPs associated with NSCLC susceptibility within the circadian rhythm pathway that met the requirement with P < 0.05 in both the discovery and validation populations. After conditional analysis, five of these SNPs remained. The A allele of CUL1 rs78524436 (ORmeta = 1.18, 95%CI: 1.09–1.29, P meta = 7.99e-5) and the A allele of TEF rs9611588 (ORmeta = 1.06, 95%CI: 1.02–1.10, P meta = 1.28e-3) were associated with an increased risk of NSCLC. The A allele of FBXL21 rs2069868 (ORmeta = 0.86, 95%CI: 0.80–0.96, P meta = 4.78e-4), the T allele of CSNK1D rs147316973 (ORmeta = 0.76, 95%CI: 0.65–0.88, P meta = 5.93e-4), and the A allele of RORA rs1589701 (ORmeta = 0.94, 95%CI: 0.91–0.98, P meta = 3.40e-3) were associated with a lower risk of NSCLC, separately. The eQTL results revealed an association between RORA rs1589701 and TEF rs9611588 with the expression levels of RORA and TEF, respectively. Transcriptome data indicated that RORA and TEF showed lower expression levels in tumor tissues compared to normal tissues (P < 0.001). Moreover, poorer survival was observed in patients with lower RORA and TEF expressions (log-rank P < 0.05). Our findings spotlight potential susceptibility loci within circadian rhythm pathway genes that modulate NSCLC carcinogenesis, which enriches the understanding of the genetic susceptibility of NSCLC in the Chinese population and provides a more solid basis for exploring the biological mechanism of circadian rhythm genes in NSCLC.https://doi.org/10.1038/s41598-025-92083-9Non-small cell lung cancerCircadian rhythm genesGenome-wide association studyGene expression |
| spellingShingle | Xiaohang Xu Luopiao Xu Zeyong Lang Gege Sun Junlong Pan Xue Li Zilong Bian Xifeng Wu Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes Scientific Reports Non-small cell lung cancer Circadian rhythm genes Genome-wide association study Gene expression |
| title | Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes |
| title_full | Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes |
| title_fullStr | Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes |
| title_full_unstemmed | Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes |
| title_short | Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes |
| title_sort | identification of potential susceptibility loci for non small cell lung cancer through whole genome sequencing in circadian rhythm genes |
| topic | Non-small cell lung cancer Circadian rhythm genes Genome-wide association study Gene expression |
| url | https://doi.org/10.1038/s41598-025-92083-9 |
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