PRScalc, a privacy-preserving calculation of raw polygenic risk scores from direct-to-consumer genomics data

• Published in: Bioinformatics advances 2023-01, Vol.3 (1), p.vbad145-vbad145
• Main Authors: Sandoval, Lorena, Jafri, Saleet, Balasubramanian, Jeya Balaji, Bhawsar, Praphulla, Edelson, Jacob L, Martins, Yasmmin, Maass, Wolfgang, Chanock, Stephen J, Garcia-Closas, Montserrat, Almeida, Jonas S
• Format: Article
• Language: English
• Subjects: Application Note
• ISSN: 2635-0041; 2635-0041
• DOI: 10.1093/bioadv/vbad145

Abstract Motivation Currently, the Polygenic Score (PGS) Catalog curates over 400 publications on over 500 traits corresponding to over 3000 polygenic risk scores (PRSs). To assess the feasibility of privately calculating the underlying multivariate relative risk for individuals with consumer genomics data, we developed an in-browserPRS calculator for genomic data that does not circulate any data or engage in any computation outside of the user's personal device. Results A prototype personal risk score calculator, created for research purposes, was developed to demonstrate how the PGS Catalog can be privately and readily applied to readily available direct-to-consumer genetic testing services, such as 23andMe. No software download, installation, or configuration is needed. The PRS web calculator matches individual PGS catalog entries with an individual's 23andMe genome data composed of 600k to 1.4 M single-nucleotide polymorphisms (SNPs). Beta coefficients provide researchers with a convenient assessment of risk associated with matched SNPs. This in-browser application was tested in a variety of personal devices, including smartphones, establishing the feasibility of privately calculating personal risk scores with up to a few thousand reference genetic variations and from the full 23andMe SNP data file (compressed or not). Availability and implementation The PRScalc web application is developed in JavaScript, HTML, and CSS and is available at GitHub repository (https://episphere.github.io/prs) under an MIT license. The datasets were derived from sources in the public domain: [PGS Catalog, Personal Genome Project].