| Title: | Evolutionary analysis of ageing and age-related disorders in the extant human population |
| Lead Institution: | Albert Einstein College of Medicine |
| Principal investigator: | Professor Zhengdong Zhang |
Application 58069
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About
Identification of genetic factors underlying longevity is of paramount importance for the healthcare of the ageing population. It is believed that the specific pattern of disease coincidence in the ageing population is partly influenced by the genetic makeup of the respective population. Adaptation over the several thousand years has shaped the population gene pool and resulted in signatures of selection to be preserved in the genome of populations. We hypothesize that healthy ageing trajectories in the populations are influenced by the extent and the strength of components underlying age-related disorders. Previous studies have identified genetic variants underlying ageing-related disorders; nevertheless, the correlation of such variants with ageing outcomes are not well understood. Capitalizing on the extent of UK Biobank data, we study the genetic correlation between ageing-related diseases and explore the feasibility of developing composite scores for prediction and stratification healthy ageing trajectories in the population. To disentangle the impact of socio-economic variables on longevity interaction between the genetic makeup and household environment will be explored, and the contribution of each factor will be simultaneously modelled in a structural equation framework. Through analysis of signatures of selection across different age bins, we aim to capture the impact of ongoing selection on human longevity and assess the survival burden of genetic variants contributing to human quantitate traits. The overarching goal of our project is to identify pro-longevity variants that enable survival to older ages and disentangle variants that increase the chance of mortality.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 13073 | Polygenic prediction of human longevity on the supposition of pervasive pleiotropy | M. Reza Jabalameli (+13) | 2024 | Scientific Reports |
Enabling scientific discoveries that improve human health