Omics measures of ageing and application to risk stratification.
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Molecular. Genetics & Pop Health
Abstract
As ageing is the most important risk factor for the majority of killer diseases, a greater understanding of its underlying mechanisms and how it impacts health has medical implications. This project will use a variety of omics phenotypes such as: metabolomics, proteomics, lipidomics and glycomics as well as over 200 complex trait phenotype and genome-wide SNP data and imputations for millions of SNPs to investigate biological age and chronological age. This project will utilise data from several population based cohorts: ORCADES, Viking, Korcula, Generation Scotland (GS:SFHS) and UK Biobank 500k.
The aim of the project is to identify omic traits predictive of chronological and biological age. Biological age being defined as the deterioration of multiple biological systems that result in phenotypic signs of ageing: reduced physical and cognitive function and increased susceptibility to disease. This project aims to establish meaningful measures of biological age via two routes. First, by testing associations between omic traits, complex phenotypes and chronological age. Second, by constructing phenotypic indices of ageing using phenotypes associated with ageing and frailty such as cognitive decline, BMI and blood pressure.
Using these measures of ageing, the project aims to construct predictive indices of ageing. The project also aims to develop genetic instruments for integral omics traits for use in Mendelain randomisation to assess the causality of omics measures and disease status on biological age.
The project also aims to stratify patients for disease risk, mortality and survival based on the value of biological age inferred from omics data and compare performance with the use of chronological age as a predictor.
The aim of the project is to identify omic traits predictive of chronological and biological age. Biological age being defined as the deterioration of multiple biological systems that result in phenotypic signs of ageing: reduced physical and cognitive function and increased susceptibility to disease. This project aims to establish meaningful measures of biological age via two routes. First, by testing associations between omic traits, complex phenotypes and chronological age. Second, by constructing phenotypic indices of ageing using phenotypes associated with ageing and frailty such as cognitive decline, BMI and blood pressure.
Using these measures of ageing, the project aims to construct predictive indices of ageing. The project also aims to develop genetic instruments for integral omics traits for use in Mendelain randomisation to assess the causality of omics measures and disease status on biological age.
The project also aims to stratify patients for disease risk, mortality and survival based on the value of biological age inferred from omics data and compare performance with the use of chronological age as a predictor.
People |
ORCID iD |
| Peter Joshi (Primary Supervisor) | |
| Erin MacDonald-Dunlop (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/N013166/1 | 01/10/2016 | 30/09/2025 | |||
| 1938560 | Studentship | MR/N013166/1 | 01/09/2017 | 28/02/2021 | Erin MacDonald-Dunlop |
| Description | Edinburgh-Estonia |
| Organisation | University of Tartu |
| Country | Estonia |
| Sector | Academic/University |
| PI Contribution | This is an ongoing collaboration between my research group and the group at the University of Tartu, that has involved, before I arrived int he group collaborations on multiple projects leading to publications as well as joint grant writing and exchange of students. For my research, I have written a pipeline to perform several analyses on collaborator's data in order to replicate and validate work done with my own data in Edinburgh. |
| Collaborator Contribution | In terms of my project collaborator's have replicated the analysis performed in our data in their own data sets. |
| Impact | This collaboration has resulted in several publications and joint grant applications as well as the exchange of students. |
| Start Year | 2017 |
| Description | SCALLOP Consortium |
| Organisation | SCALLOP Consortium |
| Sector | Private |
| PI Contribution | Our research group contributed GWAS summary statistics to all of the ongoing meta-analysis projects. I am the lead analyst for one of the meta-analysis projects and the downstream analysis are being done by me and other members of our research group. |
| Collaborator Contribution | All research groups involved in this consortium contributed data in the form of GWAS summary statistics and analysts. With the lead on different projects being distributed evenly among centres involved in the collaboration. |
| Impact | This consortium will deliver several publications, one is under review with more that 5 more being actively worked on consortium wide. |
| Start Year | 2017 |
| Description | Public Talk Ornkey Science Festival |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Every year members of the Wilson group give public talks/lectures to members of the public at the Orkney Science Festival as many of the members of the public are participants in the primary cohort used for research by my research group the Orkney Complex Disease Study (ORCADES). This gives the science interested population of Orkney and many participants to know what sort of work is fuelled by their contribution to science. I gave a talk on my work which does focus on individuals from Orkney and was glad to get interest and discussion about my work and what else could be done using the ORCADES data and how that could impact precision medicine and knowledge about health. I also had the opportunity to chat to potential participants and increase interest in participation in general. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://oisf.org/ |
| Description | Science webinar "Driving next-generation medicine discovery: Exposing causal biomarker-disease relationships using proteogenomics" |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Webinar hosted by Science/AAAS entitled "Driving next-generation medicine discovery: Exposing causal biomarker-disease relationships using proteogenomics". We gave presentations to a wide ranging scientific audience. |
| Year(s) Of Engagement Activity | 2021 |