Longitudinal multi-omic datasets to inform precision medicine and ageing

Lead Supervisor
Dr Kerrin Small
Reader
Department of Twin Research and Genetic Epidemiology, King’s College London
kerrin.small@kcl.ac.uk

Co-supervisor
Dr Claire Steves
Clinical Senior Lecturer, King’s College London

Project Details

This project will examine the interplay of multiple environments and diseases using the largest Twin cohort in the UK in a unique longitudinal gene expression (RNAseq) and metabolomics dataset. The project will investigate how changes in ‘omics predict changes in disease-related traits, and the extent to which omics including gene expression varies in healthy ageing individuals. The project will incorporate health and environment data collected in TwinsUK clinics over the last 20 years and linked electronic health records.

Datasets

We will use the TwinsUK dataset, which includes data collected on 12,000 twins over the last 23 years.  We will focus on the TwinsUK multi-omic data and linked Electronic Health Records. 

Keywords

‘omics twins RNA-seq health EHR environment metabolism ageing