Evidence map›Paper›PMID 37868335›Full record

ArticleBioinformatics advances2023

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

Lorena Sandoval, Saleet Jafri, Jeya Balaji Balasubramanian, Praphulla Bhawsar, Jacob L Edelson, Yasmmin Martins, Wolfgang Maass, Stephen J Chanock, Montserrat Garcia-Closas, Jonas S Almeida

Abstract read
In one paragraph

Article in Bioinformatics advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. The Polygenic Score Catalog: new functionality and tools to enable FAIR research.medRxiv : the preprint server for health sciences · 2024
    Article
  4. FAIR privacy-preserving operation of large genomic variant calling format (VCF) data without download or installation.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lorena SandovalDepartment of Biomedical Informatics, George Mason University, Fairfax, VA 22030, United States.ORCID https://orcid.org/0000-0002-0206-0993
Saleet JafriDepartment of Biomedical Informatics, George Mason University, Fairfax, VA 22030, United States.
Jeya Balaji BalasubramanianDivision of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.
Praphulla BhawsarDivision of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.
Jacob L EdelsonDivision of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.
Yasmmin MartinsBioinformatics Laboratory, National Laboratory for Scientific Computing, Petropolis 25651, Brazil.ORCID https://orcid.org/0000-0002-6830-1948
Wolfgang MaassSaarland University, 66123 Saarbrücken, Germany.
Stephen J ChanockDivision of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.ORCID https://orcid.org/0000-0002-2324-3393
Montserrat Garcia-ClosasDivision of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.ORCID https://orcid.org/0000-0003-1033-2650
Jonas S AlmeidaDivision of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.ORCID https://orcid.org/0000-0002-7883-7922

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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].

Identifiers

PMID37868335
PMCPMC10589913

What OpenQuestion holds

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Registered trials

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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.