Faculty, Staff and Student Publications
Publication Date
6-1-2024
Journal
Cancer Epidemiology, Boiomarkers & Prevention
Abstract
BACKGROUND: The complex relationship between measured leukocyte telomere length (LTL), genetically predicted LTL (gTL), and carcinogenesis is exemplified by lung cancer. We previously reported associations between longer pre-diagnostic LTL, gTL, and increased lung cancer risk among European and East Asian populations. However, we had limited statistical power to examine the associations among never smokers by gender and histology.
METHODS: To investigate further, we conducted nested case-control analyses on an expanded sample of never smokers from the prospective Shanghai Women's Health Studies (798 cases and 792 controls) and Shanghai Men's Health Studies (161 cases and 162 controls). We broke the case-control matching and used multivariable unconditional logistic regression models to estimate the ORs and 95% confidence intervals (CI) of incident lung cancer and adenocarcinoma (LUAD), in relation to LTL measured using quantitative PCR and gTL determined using a polygenic score. In addition, we conducted Mendelian randomization (MR) using MR-PRESSO.
RESULTS: We found striking dose-response relationships between longer LTL and gTL, and increased lung cancer risk among never-smoking women (P trendLTL = 4×10-6; P trendgTL = 3×10-4). Similarly, among never-smoking men, longer measured LTL was associated with over triple the risk compared with those with the shortest (OR, 3.48; 95% CI, 1.85-6.57). The overall results were similar for LUAD among women and men. MR analyses supported causal associations with LUAD among women (OR1 SD gTL, 1.19; 95% CI, 1.03-1.37; P = 0.03).
CONCLUSIONS: Longer pre-diagnostic LTL is associated with increased lung cancer risk among never smokers.
IMPACT: Our findings firmly support the role of longer telomeres in lung carcinogenesis.
Keywords
leukocyte telomere length, lung cancer, lung adenocarcinoma, pre-diagnostic biomarker, epidemiology
Included in
Biomedical Informatics Commons, Clinical Epidemiology Commons, Community Health and Preventive Medicine Commons, Oncology Commons, Social and Behavioral Sciences Commons
Comments
PMID: 37721487