The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation

Samuel A Lambert^{1

2

3

4}, Laurent Gil^{5

6

7}, Simon Jupp⁸, Scott C Ritchie^{9

5

10

11}, Yu Xu^{9

5}, Annalisa Buniello⁸, Aoife McMahon⁸, Gad Abraham^{9

12}, Michael Chapman^{5

6

7}, Helen Parkinson^{6

8}, John Danesh^{5

6

7

10

11

13}, Jacqueline A L MacArthur¹⁴, Michael Inouye^{15

16

17

18

19

20

21}

Affiliations

¹ Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. sl925@medschl.cam.ac.uk.
² British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. sl925@medschl.cam.ac.uk.
³ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK. sl925@medschl.cam.ac.uk.
⁴ European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK. sl925@medschl.cam.ac.uk.
⁵ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁶ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
⁷ Wellcome Sanger Institute, Hinxton, UK.
⁸ European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
⁹ Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
¹⁰ National Institute for Health Research Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
¹¹ British Heart Foundation Cambridge Centre of Research Excellence, Department of Clinical Medicine, University of Cambridge, Cambridge, UK.
¹² Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
¹³ NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
¹⁴ European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK. jalm@ebi.ac.uk.
¹⁵ Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁶ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁷ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁸ National Institute for Health Research Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁹ British Heart Foundation Cambridge Centre of Research Excellence, Department of Clinical Medicine, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
²⁰ Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia. mi336@medschl.cam.ac.uk.
²¹ The Alan Turing Institute, London, UK. mi336@medschl.cam.ac.uk.

PMID: 33692568
PMCID: PMC11165303
DOI: 10.1038/s41588-021-00783-5

The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation

Samuel A Lambert et al. Nat Genet. 2021 Apr.

. 2021 Apr;53(4):420-425.

doi: 10.1038/s41588-021-00783-5.

Authors

Affiliations

¹ Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. sl925@medschl.cam.ac.uk.
² British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. sl925@medschl.cam.ac.uk.
³ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK. sl925@medschl.cam.ac.uk.
⁴ European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK. sl925@medschl.cam.ac.uk.
⁵ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁶ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
⁷ Wellcome Sanger Institute, Hinxton, UK.
⁸ European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
⁹ Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
¹⁰ National Institute for Health Research Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
¹¹ British Heart Foundation Cambridge Centre of Research Excellence, Department of Clinical Medicine, University of Cambridge, Cambridge, UK.
¹² Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
¹³ NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
¹⁴ European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK. jalm@ebi.ac.uk.
¹⁵ Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁶ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁷ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁸ National Institute for Health Research Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. mi336@medschl.cam.ac.uk.
¹⁹ British Heart Foundation Cambridge Centre of Research Excellence, Department of Clinical Medicine, University of Cambridge, Cambridge, UK. mi336@medschl.cam.ac.uk.
²⁰ Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia. mi336@medschl.cam.ac.uk.
²¹ The Alan Turing Institute, London, UK. mi336@medschl.cam.ac.uk.

PMID: 33692568
PMCID: PMC11165303
DOI: 10.1038/s41588-021-00783-5

Abstract

We present the Polygenic Score (PGS) Catalog (https://www.PGSCatalog.org), an open resource of published scores (including variants, alleles and weights) and consistently curated metadata required for reproducibility and independent applications. The PGS Catalog has capabilities for user deposition, expert curation and programmatic access, thus providing the community with a platform for PGS dissemination, research and translation.

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Conflict of interest statement

Competing interests J.D. is part of the International Cardiovascular and Metabolic Advisory Board for Novartis (since 2010); the Steering Committee of UK Biobank (since 2011); the MRC International Advisory Group (ING), London (since 2013); the MRC High Throughput Science Omics Panel, London (since 2013); the Scientific Advisory Committee for Sanofi (since 2013); the International Cardiovascular and Metabolism Research and Development Portfolio Committee for Novartis; and the Astra Zeneca Genomics Advisory Board (2018).

Figures

**Fig. 1. Common aspects of PGS analyses that are captured and displayed in the PGS Catalog.**
a, PGS analyses can broadly be described in two stages: determining the set of variants and weights that will predict a trait of interest (score development) and an evaluation of how predictive the PGS is in an external set of samples (PGS evaluation). Major data items (Box 1) that can be queried and browsed in the PGS Catalog are highlighted as colored boxes and linked to metadata items that are recorded. b,c, Examples of how PGS metadata are displayed for each score on https://www.PGSCatalog.org (example score PGS000013; ref. [13]), including score details, contributing samples and score development/training (b) and performance metrics and evaluated samples (c). Sections are highlighted with colored bars corresponding to the data objects that they display in a.

**Fig. 2. Benchmarking the association of nine colorectal cancer PGSs in UKB.**
Each PGS was evaluated with a Cox proportional hazards regression model (age as timescale) to predict colorectal cancer status. Each model was fitted separately for each ancestry group. The standardized effect size (hazard ratio), together with the 95% confidence interval (CI), describes the increase in hazard per s.d. increase in each PGS. Models were adjusted for sex, age at recruitment, recruitment country, genotyping array and the first ten genetic principal components within each ancestry group.

See this image and copyright information in PMC

References

1. Lambert SA, Abraham G & Inouye M Hum. Mol. Genet. 28, R133–R142 (2019). (R2). - PubMed
1. Torkamani A, Wineinger NE & Topol EJ Nat. Rev. Genet. 19, 581–590 (2018). - PubMed
1. Chatterjee N, Shi J & García-Closas M Nat. Rev. Genet. 17, 392–406 (2016). - PMC - PubMed
1. Wray NR, Kemper KE, Hayes BJ, Goddard ME & Visscher PM Genetics 211, 1131–1141 (2019). - PMC - PubMed
1. Evans DM, Visscher PM & Wray NR Hum. Mol. Genet. 18, 3525–3531 (2009). - PubMed

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The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation

Affiliations

The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical