Research Post
Purpose: We aimed to analyze and compare leukocyte telomere length (LTL) and age-dependent LTL attrition between childhood cancer survivors and noncancer controls, and to evaluate the associations of LTL with treatment exposures, chronic health conditions (CHC), and health behaviors among survivors.
Experimental Design: We included 2,427 survivors and 293 noncancer controls of European ancestry, drawn from the participants in St. Jude Lifetime Cohort Study (SJLIFE), a retrospective hospital-based study with prospective follow-up (2007–2016). Common nonneoplastic CHCs (59 types) and subsequent malignant neoplasms (5 types) were clinically assessed. LTL was measured with whole-genome sequencing data.
Results: After adjusting for age at DNA sampling, gender, genetic risk score based on 9 SNPs known to be associated with telomere length, and eigenvectors, LTL among survivors was significantly shorter both overall [adjusted mean (AM) = 6.20 kb; SE = 0.03 kb] and across diagnoses than controls (AM = 6.69 kb; SE = 0.07 kb). Among survivors, specific treatment exposures associated with shorter LTL included chest or abdominal irradiation, glucocorticoid, and vincristine chemotherapies. Significant negative associations of LTL with 14 different CHCs, and a positive association with subsequent thyroid cancer occurring out of irradiation field were identified. Health behaviors were significantly associated with LTL among survivors aged 18 to 35 years (Ptrend = 0.03).
Conclusions: LTL is significantly shorter among childhood cancer survivors than noncancer controls, and is associated with CHCs and health behaviors, suggesting LTL as an aging biomarker may be a potential mechanistic target for future intervention studies designed to prevent or delay onset of CHCs in childhood cancer survivors.
Feb 9th 2023
Research Post
Feb 6th 2023
Research Post
Read this research paper, co-authored by Fellow & Canada CIFAR AI Chair at Russ Greiner: Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms
Jul 7th 2022
Research Post
Read this research paper, co-authored by Fellow & Canada CIFAR AI Chair Russ Greiner: Prediction of Obsessive-Compulsive Disorder: Importance of neurobiology-aided feature design and cross-diagnosis transfer learning
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