Chrome Extension
WeChat Mini Program
Use on ChatGLM

Association between rare pathogenic variants in established cancer risk genes and the diagnosis of single and multiple common cancers: A UK Biobank study.

Journal of Clinical Oncology(2024)

Cited 0|Views13
No score
Abstract
10505 Background: Much of our understanding of cancer risk attributable to rare pathogenic variants (RPV) is derived from family-based and case-only cohort studies, which may be limited by ascertainment bias. We sought to identify associations between RPVs and cancer diagnoses in a large population-based study. Methods: We conducted a case-control study using the UK Biobank. We performed gene-based aggregate testing to examine the relationship between RPVs (defined as pathogenic or likely pathogenic variants) in 96 genes implicated in cancer risk and the diagnosis of 11 common cancers using the combined optimal unified sequence kernel association test (SKAT-O). Odds ratios (OR) and 95% confidence intervals (CI) were then calculated using Firth logistic regression. Results were adjusted for age, sex and genetic ancestry. Bonferroni-adjusted p-values were used to determine statistical significance. Variant pathogenicity was determined by American College of Medical Genetics criteria. Results: We identified 24 genes in which RPVs were statistically significantly associated with at least one of 11 common cancers among 183,626 individuals. The presence of an RPV in one of these 24 genes was associated with increased odds of one cancer (OR 1.8; 95% CI: 1.7-2.0), and multiple cancers (OR 2.5; 95% CI: 2.2-2.9). Conclusions: This large population-based study identified 24 established cancer risk genes in which RPVs were associated with common cancers. We identified both known and novel associations between cancer and RPVs. Some associations—i.e. renal/pancreas and MEN1—may be due to ascertainment and/or misclassification bias. We also show that individuals with RPVs in cancer risk genes not only have higher odds of one cancer diagnosis, but also multiple cancers.[Table: see text]
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined