Evidence map›Paper›PMID 35591975›Full record

ArticleCell genomics2022

Genome-wide risk prediction of common diseases across ancestries in one million people.

Nina Mars, Sini Kerminen, Yen-Chen A Feng, Masahiro Kanai, Kristi Läll, Laurent F Thomas, Anne Heidi Skogholt, Pietro Della Briotta Parolo, Biobank Japan Project, FinnGen and 12 more

Abstract read
In one paragraph

Article in Cell genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 1 pooled it
–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

57 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

22 authors.

Nina MarsInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.
Sini KerminenInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.
Yen-Chen A FengPsychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Masahiro KanaiAnalytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Kristi LällEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Laurent F ThomasDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
Anne Heidi SkogholtK. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway.
Pietro Della Briotta ParoloInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.
Biobank Japan Project
FinnGen
Benjamin M NealeAnalytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Jordan W SmollerPsychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Maiken E GabrielsenK. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway.
Kristian HveemK. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway.
Reedik MägiEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Koichi MatsudaDepartment of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo, Tokyo, Japan.
Yukinori OkadaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Matti PirinenInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.
Aarno PalotieInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.
Andrea GannaInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.
Alicia R MartinAnalytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Samuli RipattiInstitute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland.

Funding

Generalizing polygenic risk prediction methods across populations for insights into psychiatric diseaseK99MH117229 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN, ALICIA · 2018 to 2019
$262k
NIMH NIH HHS K99 MH117229
6 · The paper itself

Abstract

Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate. All four PRSs had similar accuracy across European and Asian populations, with poorer transferability in the smaller group of individuals of African ancestry. The PRSs had highly similar effect sizes in different populations of European ancestry, and in early- and late-settlement regions with different recent population bottlenecks in Finland. Comparing genome-wide PRSs to PRSs containing a smaller number of variants, the highly polygenic, genome-wide PRSs generally displayed higher effect sizes and better transferability across global ancestries. Our findings indicate that in the populations investigated, the current genome-wide polygenic scores for common diseases have potential for clinical utility within different health-care settings for individuals of European ancestry, but that the utility in individuals of African ancestry is currently much lower.

Indexed as

ancestrybreast cancercoronary artery diseasediabetesglobal healthhealth disparitiespolygenic risk scoreprecision medicineprostate cancerrisk prediction

Identifiers

PMID35591975
PMCPMC9010308

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.