Telomere length profiling and its implications: exploring metabolic traits, genetic associations and variant effects in the Singapore population

• Main Author: Nguyen, Thi Thu Trang
• Other Authors: Joanne Ngeow Yuen Yie
• Format: Thesis-Doctor of Philosophy
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Medicine, Health and Life Sciences
• Online Access: https://hdl.handle.net/10356/175783
• Institution: Nanyang Technological University

Telomeres, found at chromosomal ends, function to maintain genomic homeostasis and are associated with various cellular processes. To address the underrepresentation of telomere biology research in the Asian population, particularly in Singapore, this project seeks to investigate the telomere length (TL) profile, its associations, and the functional implications of specific telomere-related variants observed in both cancer cases identified from different clinical cohorts and the Singaporean general population. The hypothesis posits that there would be a difference in TL distribution among age groups, gender, and the three major ethnicities – Chinese, Indian, and Malay. Also, certain missense shelterin variants, reported clinically or discovered within critical domains, are anticipated to yield functional impact outcomes when subjected to different in-silico and in-vitro analyses. Firstly, telomere length estimation, association analysis, and variant classification for telomere-related variants reported from the SG10K cohorts were performed. These studies highlighted the contribution of shelterin complex variants in association with TL, particularly in the POT1 gene. Further investigation of promising missense POT1 variants using variant effect predictors, molecular dynamics simulation, and functional validations has revealed their effects on protein structure, stability, interactions, and functionality. Our findings have provided more insights into telomere profiling and telomere-related variant characteristics in the Singapore context while also affirming the effectiveness of molecular dynamics and variant effect predictors as computational tools for assessing missense variant effects.