Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications.
Wei-Shi LiuBang-Sheng WuLiu YangShi-Dong ChenYa-Ru ZhangYue-Ting DengXin-Rui WuXiao-Yu HeJing YangJian-Feng FengWei ChengYu-Ming XuJin-Tai YuPublished in: GeroScience (2024)
Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (>ā0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.
Keyphrases
- genome wide
- copy number
- dna methylation
- bioinformatics analysis
- genome wide identification
- risk assessment
- gene expression
- single cell
- metabolic syndrome
- genome wide analysis
- climate change
- high throughput
- skeletal muscle
- transcription factor
- artificial intelligence
- insulin resistance
- peripheral blood
- childhood cancer