Investigating the genome-wide association and risk factors for multi-organ ageing
Approved Research ID: 96511
Approval date: December 22nd 2022
This project aims to find key biomarkers of human ageing, through the analysis of organ-level phenotypes. We will focuses on accurate estimation of biological age through novel calculation methods and the investigation of important risk factors related to multi-organ functions, to ultimately achieve a healthier lifespan. For this purpose, we firstly carry out a collection of clinical and multi-scale, multi-modal, multi-omics data to extract ageing-related "deep phenotypes", such as phenotypes derived from medical imaging, cognitive phenotypes, etc. Secondly, we will explore the associations among genotypes and phenotypes via statistical methods, e.g., GWAS and PheWAS. Then we build a spatiotemporal and dynamic gene-phenotype network to predict ageing-related outcomes, such as biological age, frailty, and cognitive function impairment. Thirdly, we aim to identify novel biomarkers through AI algorithms that can tremendously prompt early warning and intervention of ageing. Finally, we hope to build an explicable model for biological age estimationon the UKBB data, and to test the model on an independent population. In addition, we will assess the effect of COVID-19 on the ageing process. The project lasts for a period of 3 years. We hope to gain more intrinsic understanding of the ageing mechanism.