Download Principal Investigator Professor Cathryn Lewis

Principal Investigator
Professor Cathryn Lewis
Address
King's College London, SGDP Centre, Institute of Psychiatry, Psychology &
Neuroscience, de Crespigny Park, London SE5 8AF
Lead Collaborators: Dr Mark Hamer
Collaborating Institutions and Addresses: University of Loughborough
Summary of research
mHealth, Exercise, Fitness, Genetics, Metabolism
Application Lay Summary:
1a: The aims of this research are to a) identify genetic variants associated with
physical activity, b) establish the total genetic contribution to activity and the
genetic overlap between physical activity and cardio-respiratory fitness, and c)
create a genetic risk score by summing the information across all activityassociated genetic variants (UK Biobank) to predict blood metabolite levels
(Metabolomics GWAS Server – publicly-available data). We would like to
quantify the extent to which physical activity and fitness are under the influence
of genetic variation using whole-genome data, and create a genetic risk map
between activity and human blood metabolites.
1b: Understanding the genetic links between activity, fitness, and blood
metabolites will provide insight into the benefits of activity, and may inform drug
prescription and reveal new drug (and exercise) targets. To move the concept of
personalised medicine into clinical practice we need to link all an individual's
information, including activity levels and genetics. Clinicians and individuals will
benefit from being better able to navigate the sea of health-related information;
individuals will be better equipped to make healthy choices and play an active
role in their healthcare, especially the elderly and chronically ill.
1c: This research will test for association between summary phenotype data on
tracking and fitness and genetic variants in genome-wide association studies
(GWAS). Techniques that consider all the evidence from GWAS results
simultaneously (e.g. polygenic risk scoring, SNP-heritability methods), making
use of data from the UK Biobank project and publicly-available GWAS data for
blood metabolites (Shin et al. Nature Genetics, 2014) will also be applied.
All analyses will be performed using freely-available, powerful, and up-to-date
software.
1d: The subset of UK Biobank participants with availability of (1) activity tracker
and cardio-respiratory fitness data, and (2) genotype data.