| Title: | Association of Reported Candidate Monogenic Genes With Lung Cancer Risk |
| Journal: | Clinical Lung Cancer |
| Published: | 26 Jan 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36781323/ |
| DOI: | https://doi.org/10.1016/j.cllc.2023.01.005 |
Publication 11012
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Abstract
INTRODUCTION/BACKGROUND: Published studies on association of germline monogenic genes and lung cancer risk were inconsistent. Our objective is to assess the validity of reported candidate monogenic genes for their association with lung cancer.</p>
MATERIALS AND METHODS: A systematic review of published papers prior to August 2022 was performed first to identify all genes where germline mutations were associated with lung cancer risk. We then performed a confirmation study in 2,050 lung cancer cases and 198,553 controls in the UK Biobank (UKB). Germline mutations of these genes were identified from sequencing data and annotated using The American College of Medical Genetics criteria. The robust SKAT-O, a gene-based analysis that properly controls for false positives due to unbalanced case-control ratio, was used for association tests adjusting for age at recruitment, gender, and genetic background.</p>
RESULTS: The systematic review identified 12 genes that were statistically significantly associated with lung cancer risk in at least one study (P < .05), including ATM, BLM, BRCA2, BRIP1, CHEK2, FANCA, FANCD2, MSH6, PMS1, RAD51C, RAD51D, and TP53. When pathogenic/likely pathogenic mutations were aggregated within each gene, the association was confirmed for ATM (P = 4.47E-4) at the study-wise significance level (P < .0042, Bonferroni correction for 12 tests). Suggestive evidence of association was found for 2 other genes, BRCA2 (P = .007) and TP53 (P = .03). Among these 3 genes, the lung cancer risks range from 1.95 (BRCA2) to 5.28 (TP53).</p>
CONCLUSION: This study provides statistical evidence for association of previously reported genes and lung cancer risk and has clinical utility for risk assessment and genetic counseling.</p>
9 Authors
- Andrew S Rifkin
- Ethan M Less
- Jun Wei
- Zhuqing Shi
- Siqun Lilly Zheng
- Brian T Helfand
- Peter J Hulick
- Seth B Krantz
- Jianfeng Xu
1 Application
| Application ID | Title |
|---|---|
| 50295 | Validity and performance of inherited risk assessment for common diseases using polygenic risk score, family history, and high-penetrance genes |
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