Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch
Year: 2022
Type: article
Study design: Observational Study
Abstract: Background Absence of a dicrotic notch on finger photoplethysmography (PPG) is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease (CVD). However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident CVD. Methods In 169,787 participants in the UK Biobank, we identified absent dicrotic notch on PPG and created a novel continuous trait reflecting notch smoothness using machine learning. Next, we determined the heritability, genetic basis, polygenic risk, and clinical relations for the binary absent notch trait and the newly derived continuous notch smoothness trait. Results Heritability of the continuous notch smoothness trait was 7.5%, compared with 5.6% for the binary absent notch trait. A genome wide association study of notch smoothness identified 15 significant loci, implicating genes including NT5C2 (P=1.2×10 −26 ), IGFBP3 (P=4.8×10 −18 ), and PHACTR1 (P=1.4×10 −13 ), compared with 6 loci for the binary absent notch trait. Notch smoothness stratified risk of incident myocardial infarction or coronary artery disease, stroke, heart failure, and aortic stenosis. A polygenic risk score for notch smoothness was associated with incident CVD and all-cause death in UK Biobank participants without available PPG data. Conclusion We found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on PPG was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident CVD. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Funders: American Heart Association, Amgen, Bristol-Myers Squibb, Pfizer, AstraZeneca, Bayer, GlaxoSmithKline, Sanofi, Gilead Sciences, Alnylam Pharmaceuticals, Celladon Corporation, Ironwood Pharmaceuticals, Incorporated, Broad Institute, Sarnoff Cardiovascular Research Foundation, MyoKardia, Maze Therapeutics, National Institutes of Health, Sanofi Pasteur, Medical Research Council, National Heart, Lung, and Blood Institute
Awards: G1062825794, G147578628, Precision Medicine in Ischemic Stroke and Atrial Fibrillation (PreMISe-AF), G2279902555, G3029506724, Eicosanoid Profiles as Determinants of HFpEF, G3897532131, G4077987447, G4405986302, G453267231, G475755283, The Association of Metabolic Disease and Pulmonary Hypertension, G5850737185, G6355960561, Advancing Atrial Fibrillation Precision Medicine, G7448027469, Mentoring in Arrhythmia Research, Mentoring in Patient-Oriented and Translational HFpEF Research, G8630864450, G8985676510, G9000146605, G9000208878, Training Grant in Cardiovascular Research, Genomics of Cardiac Arrhythmias
OpenAlex ID: W4313280090