The Polygenic Risk Score Knowledge Base Offers a Centralized Online Repository for Calculating and Contextualizing Polygenic Risk Scores

Overview

Journal Commun Biol

Specialty Biology

Date 2022 Sep 2

PMID 36056235

Authors

Madeline L Page

Elizabeth L Vance

Matthew E Cloward

Ed Ringger

Louisa Dayton

Mark T W Ebbert

Justin B Miller

John S K Kauwe

Affiliations

Soon will be listed here.

Abstract

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Citing Articles

PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine.

Jin J, Li B, Wang X, Yang X, Li Y, Wang R medRxiv. 2025; .

PMID: 39990574 PMC: 11844566. DOI: 10.1101/2025.02.07.25321875.

PGSXplorer: an integrated nextflow pipeline for comprehensive quality control and polygenic score model development.

Yaras T, Oktay Y, Karakulah G PeerJ. 2025; 13:e18973.

PMID: 39959831 PMC: 11829630. DOI: 10.7717/peerj.18973.

Genal: a Python toolkit for genetic risk scoring and Mendelian randomization.

Rivier C, Clocchiatti-Tuozzo S, Huo S, Torres-Lopez V, Renedo D, Sheth K Bioinform Adv. 2025; 5(1):vbae207.

PMID: 39776894 PMC: 11706532. DOI: 10.1093/bioadv/vbae207.

A systematic evaluation of the performance and properties of the UK Biobank Polygenic Risk Score (PRS) Release.

Thompson D, Wells D, Selzam S, Peneva I, Moore R, Sharp K PLoS One. 2024; 19(9):e0307270.

PMID: 39292644 PMC: 11410272. DOI: 10.1371/journal.pone.0307270.

The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank.

Don J, Schork A, Glusman G, Rappaport N, Cummings S, Duggan D Geroscience. 2024; 46(4):3911-3927.

PMID: 38451433 PMC: 11226417. DOI: 10.1007/s11357-024-01107-1.

References

Richardson T, Harrison S, Hemani G, Davey Smith G . An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome. Elife. 2019; 8. PMC: 6400585. DOI: 10.7554/eLife.43657. View

Mills M, Rahal C . The GWAS Diversity Monitor tracks diversity by disease in real time. Nat Genet. 2020; 52(3):242-243. DOI: 10.1038/s41588-020-0580-y. View

Mars N, Kerminen S, Feng Y, Kanai M, Lall K, Thomas L . Genome-wide risk prediction of common diseases across ancestries in one million people. Cell Genom. 2022; 2(4):None. PMC: 9010308. DOI: 10.1016/j.xgen.2022.100118. View

Chatterjee N, Wheeler B, Sampson J, Hartge P, Chanock S, Park J . Projecting the performance of risk prediction based on polygenic analyses of genome-wide association studies. Nat Genet. 2013; 45(4):400-5, 405e1-3. PMC: 3729116. DOI: 10.1038/ng.2579. View

Shin J, Lee S . GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data. Genome Biol. 2021; 22(1):183. PMC: 8218431. DOI: 10.1186/s13059-021-02403-1. View

Choi J, Jia G, Wen W, Long J, Zheng W . Evaluating polygenic risk scores in assessing risk of nine solid and hematologic cancers in European descendants. Int J Cancer. 2020; 147(12):3416-3423. DOI: 10.1002/ijc.33176. View

Manolio T, Collins F, Cox N, Goldstein D, Hindorff L, Hunter D . Finding the missing heritability of complex diseases. Nature. 2009; 461(7265):747-53. PMC: 2831613. DOI: 10.1038/nature08494. View

Tam V, Patel N, Turcotte M, Bosse Y, Pare G, Meyre D . Benefits and limitations of genome-wide association studies. Nat Rev Genet. 2019; 20(8):467-484. DOI: 10.1038/s41576-019-0127-1. View

Lambert S, Gil L, Jupp S, Ritchie S, Xu Y, Buniello A . The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation. Nat Genet. 2021; 53(4):420-425. PMC: 11165303. DOI: 10.1038/s41588-021-00783-5. View

10.

Lambert J, Ibrahim-Verbaas C, Harold D, Naj A, Sims R, Bellenguez C . Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet. 2013; 45(12):1452-8. PMC: 3896259. DOI: 10.1038/ng.2802. View

11.

Zhao W, Rasheed A, Tikkanen E, Lee J, Butterworth A, Howson J . Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease. Nat Genet. 2017; 49(10):1450-1457. PMC: 5844224. DOI: 10.1038/ng.3943. View

12.

Ellinghaus D, Degenhardt F, Bujanda L, Buti M, Albillos A, Invernizzi P . Genomewide Association Study of Severe Covid-19 with Respiratory Failure. N Engl J Med. 2020; 383(16):1522-1534. PMC: 7315890. DOI: 10.1056/NEJMoa2020283. View

13.

Pal L, Yu C, Mount S, Moult J . Insights from GWAS: emerging landscape of mechanisms underlying complex trait disease. BMC Genomics. 2015; 16 Suppl 8:S4. PMC: 4480957. DOI: 10.1186/1471-2164-16-S8-S4. View

14.

Matoba N, Akiyama M, Ishigaki K, Kanai M, Takahashi A, Momozawa Y . GWAS of smoking behaviour in 165,436 Japanese people reveals seven new loci and shared genetic architecture. Nat Hum Behav. 2019; 3(5):471-477. DOI: 10.1038/s41562-019-0557-y. View

15.

Goris A, van Setten J, Diekstra F, Ripke S, Patsopoulos N, Sawcer S . No evidence for shared genetic basis of common variants in multiple sclerosis and amyotrophic lateral sclerosis. Hum Mol Genet. 2013; 23(7):1916-22. PMC: 3943520. DOI: 10.1093/hmg/ddt574. View

16.

Hirschhorn J . Genomewide association studies--illuminating biologic pathways. N Engl J Med. 2009; 360(17):1699-701. DOI: 10.1056/NEJMp0808934. View

17.

Choi S, OReilly P . PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience. 2019; 8(7). PMC: 6629542. DOI: 10.1093/gigascience/giz082. View

18.

Harold D, Abraham R, Hollingworth P, Sims R, Gerrish A, Hamshere M . Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nat Genet. 2009; 41(10):1088-93. PMC: 2845877. DOI: 10.1038/ng.440. View

19.

Hyde C, Nagle M, Tian C, Chen X, Paciga S, Wendland J . Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet. 2016; 48(9):1031-6. PMC: 5706769. DOI: 10.1038/ng.3623. View

20.

Lo M, Kauppi K, Fan C, Sanyal N, Reas E, Sundar V . Identification of genetic heterogeneity of Alzheimer's disease across age. Neurobiol Aging. 2019; 84:243.e1-243.e9. PMC: 6783343. DOI: 10.1016/j.neurobiolaging.2019.02.022. View