Multi-omics prediction of cognitive decline, Alzheimer's disease, and death
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Molecular. Genetics & Pop Health
Abstract
This project will investigate epigenetic-outlier burden as a potential biological measure of ageing.
DNA methylation is one of several epigenetic mechanisms that can affect the expression of genes. An epigenetic outlier occurs when the methylation level at a specific site in an individual's genome differs greatly from the methylation level of the majority of the population in this location. Cross-sectionally the number of epigenetic-outliers (here defined as data points more than 3 times the inter-quartile range from the 25th/75th percentiles) in the population has been observed to increase with age (Gentilini et al. 2015).
We will try to replicate this finding in a local dataset (Generation Scotland). In addition, we will examine how epigenetic-outlier burden changes longitudinally within individuals, its relation to other biological clock measures and whether epigenetic-outlier burden can be useful for the prediction of age-related cognitive and health outcomes. To do so, we will use data from large longitudinal cohort studies, such as the Lothian Birth Cohort 1936 (LBC1936) and the Swedish Adoption/Twin Study of Aging (STATSA).
DNA methylation is one of several epigenetic mechanisms that can affect the expression of genes. An epigenetic outlier occurs when the methylation level at a specific site in an individual's genome differs greatly from the methylation level of the majority of the population in this location. Cross-sectionally the number of epigenetic-outliers (here defined as data points more than 3 times the inter-quartile range from the 25th/75th percentiles) in the population has been observed to increase with age (Gentilini et al. 2015).
We will try to replicate this finding in a local dataset (Generation Scotland). In addition, we will examine how epigenetic-outlier burden changes longitudinally within individuals, its relation to other biological clock measures and whether epigenetic-outlier burden can be useful for the prediction of age-related cognitive and health outcomes. To do so, we will use data from large longitudinal cohort studies, such as the Lothian Birth Cohort 1936 (LBC1936) and the Swedish Adoption/Twin Study of Aging (STATSA).
Organisations
People |
ORCID iD |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/N013166/1 | 30/09/2016 | 30/11/2025 | |||
| 2106012 | Studentship | MR/N013166/1 | 31/08/2018 | 30/08/2019 |