Principal Investigator: Assistant Professor Josh Knowles
Stanford University, Medicine, Falk CVRC, 300 Pasteur Drive, Stanford CA 94304, United StatesTags: 21506, GWAS, Heart Failure Risk, Mendelian randomization
Lead Collaborators: 1) Professor Erik Ingelsson
Collaborating Institutions and Addresses: 1) Uppsala University, Department of Medical Sciences, UCT/MTC, Dat Hammarskjölds väg 14B, Uppsala 75237, Sweden
Funding body: Internally funded from existing grants.
1a: Heart failure is a common disorder with high mortality. Underlying risk factors are incompletely understood, and its etiologic heterogeneity poses a significant therapeutic challenge. Further studies of risk factors for incident heart failure in large population-based studies can clarify underlying mechanisms, and Mendelian randomization can help address causality, thus illuminating potential therapeutic targets.
Specific Aim 1: To examine associations between known and novel risk factors and heart failure incidence, and develop comprehensive genetic risk scores for identified heart failure risk factors.
Specific Aim 2: Using Mendelian randomization, test the causal relationships of these risk factors on incident heart failure.
1b: This work specifically addresses UK biobank’s stated purpose by seeking to improve clinical heart failure outcomes by identifying causal factors upon which to target therapeutic efforts. Many clinical factors associated with heart failure onset, survival and symptoms exist, but the mechanism and treatment of these associations are still poorly understood. Here, we will hone our search for molecular targets in heart failure to focus work regarding both the mechanism by which these factors confer risk as well as potential therapies that truly modulate clinical phenotype in heart failure.
1c: To test the hypothesis above, we will first establish the risk of heart failure incidence from each potential risk factor. Candidate risk factors include known risk factors such as coronary artery disease, blood pressure, diabetes, smoking, heart rate, atrial fibrillation, body mass index, left ventricular hypertrophy, and lipids, but also unproven risk factors (including biomarkers, lifestyle factors, physiological measures and imaging phenotypes).
We will perform GWAS to identify variants associated with identified risk factors in observational analyses. To eliminate issues in such analyses, such as reverse causality and confounding, will use Mendelian randomization methodologies to establish causality.
1d: This study requires data from the full cohort of UK Biobank subjects to maximize power.