Back to search

Article

Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health research

2022-03-03

Abstract excerpt

<h4>Introduction</h4> A major challenge to enabling precision health at a global scale is the bias between those who enroll in state sponsored genomic research and those suffering from chronic disease. More than 30 million people have been genotyped by direct-to-consumer (DTC) companies such as 23andMe, Ancestry DNA, and MyHeritage, providing a potential mechanism for democratizing access to medical interventions...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
afaa5e3a-79e4-5fd2-a745-bc918efba406
DOI
10.1101/2022.03.01.22271722
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health researchDOI 10.1101/2022.03.01.22271722
Select a neighboring publication to make it the new centre.