Principal Investigator: Professor Euan Ashley
Stanford University, Medicine, 870 Quarry Road, Stanford, CA 94305, United StatesTags: 22282, activity, cardiovascular, environment, exercise, fitness, genetics
1a: The proposed study will examine the relationship between genetics and environment on exercise capacity, a known indicator of cardiovascular and overall health.
Aim 1. Generate a comprehensive null model of exercise capacity. Specifically, develop a regression model that best explains the outcome of exercise capacity using design variables and covariates without strong genetic influence, such as BMI. The model will then be extended to incorporate genetic information (i.e. SNP data).
Aim 2. Generate activity signatures using accelerometer data.
Aim 3. GWAS of exercise capacity.
1b: Knowledge about how the combination of genetic variants and physical activity patterns affect exercise capacity will support further translational research. Identifying patterns of physical activity that increase exercise capacity will potentially determine valuable guidelines for providing individuals with feedback on lifestyle changes that may prove beneficial for their overall health.
1c: We will use regression techniques to select the most informative conventional predictors of exercise capacity (such as heart rate). In addition, we will apply machine-learning techniques to accelerometry data in order to generate hidden activity signatures. The combination of conventional variables such as smoking and analytically defined activity signatures will then be correlated with genetic variants through GWAS.
1d: Full cohort
“We would like to examine the ICD9/10 codes associated with cardiovascular disease. The complete list of codes that we are interested in has been provided to UK Biobank (we would like both the ICD9 & ICD10 codes from the list that are available in the UK Biobank database). At this time we will not be using the date of diagnosis in our analysis, we will only be checking whether each subject has the diagnosis or not.”
PROJECT EXTENSION – APPROVED 17.11.2017
“We have performed GWAS analysis to determine variants that are associated with physical activity phenotypes. We would now like to establish causality in some of these associations by performing Mendelian Randomization analysis. We would like to use the mortality data as outcomes for the MR analysis.”lease do not hesitate to contact me if you require any additional information.
Last updated Nov 20, 2017