| Title: | Genetic architecture of lung cancer revealed by common and rare variant analyses across population-scale biobanks |
| Journal: | npj Precision Oncology |
| Published: | 13 Jul 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42443585/ |
| DOI: | https://doi.org/10.1038/s41698-026-01558-z |
| URL: | https://www.nature.com/articles/s41698-026-01558-z_reference.pdf |
Publication 20287
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Abstract
Genome-wide association studies have predominantly implicated common variants in lung cancer susceptibility, whereas the contribution of rare non-coding variation remains incompletely defined. This study comprised 52,550 cases and 1,617,173 controls across three whole-genome sequencing (WGS) cohorts (UK Biobank, the 100,000 Genomes Project, and All of Us) and five imputed genotype-array datasets aimed to identify rare non-coding determinants of lung cancer risk. Two complementary approaches were applied: position-based single-variant testing for variants with adequate allele counts, and gene-based testing aggregating rare and ultra-rare ncRNA variants to increase power. Single-variant meta-analysis identified two novel rare non-coding variants reaching sequencing-based genome-wide significance: rs763076863C22orf46 at 22q13.2 [OR (95% CI): 5.94 (3.46-10.19), P = 4.55 × 10-9] and rs1014871851WWOX at 16q23.1 [OR (95% CI): 7.55 (4.50-12.67), P = 3.71 × 10-9]. Functional annotation-informed gene-based analyses prioritized 37 candidate ncRNAs using eQTL, expression, proteomics, prognosis, cis-Mendelian randomization drug-target evidence, and external replication. CLEC12A-AS1 ranked highest; multi-omics association and chain mediation analyses supported an indirect pathway linking CLEC12A-AS1 burden to lung cancer risk via modulation of CLEC12A. Collectively, results indicate contributions from both individually detectable rare variants and cumulative ultra-rare functional burden within ncRNA regions, highlighting the CLEC12A-AS1/CLEC12A axis as a potential biomarker and translational target.</p>
9 Authors
- Jingyi Zhao
- Lei Qiao
- Yixin Zhang
- Hao Hong
- Qinhui Fan
- David C. Christiani
- Feng Chen
- Yang Zhao
- Sipeng Shen
Enabling scientific discoveries that improve human health