ArticleCirculation. Genomic and precision medicine2023
Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch.
Article in Circulation. Genomic and precision medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Prognostic Utility of the Dicrotic Notch Index in Patients Undergoing Transcatheter Aortic Valve Replacement.Structural heart : the journal of the Heart Team · 2026Article
- An algorithm to detect dicrotic notch in arterial blood pressure and photoplethysmography waveforms using the iterative envelope mean method.Computer methods and programs in biomedicine · 2024Article
- Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction.Nature genetics · 2024Article
- Photoplethysmography and intracardiac pressures: early insights from a pilot study.European heart journal. Digital health · 2024Article
- Predicting cardiovascular disease risk using photoplethysmography and deep learning.PLOS global public health · 2024Article
- Current and future strategies for targeting the endothelin pathway in cardiovascular disease.Nature cardiovascular research · 2023Review
- Unsupervised representation learning improves genomic discovery and risk prediction for respiratory and circulatory functions and diseases.medRxiv : the preprint server for health sciences · 2023Article
- Arterial pulse wave modeling and analysis for vascular-age studies: a review from VascAgeNet.American journal of physiology. Heart and circulatory physiology · 2023Review
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundAbsence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease.
methodsIn 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography 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.
resultsHeritability 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
conclusionsWe found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on photoplethysmography was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident cardiovascular disease. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.