Evidence map›Paper›PMID 31155286›Full record

ArticleAmerican journal of human genetics2019

Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland.

Sini Kerminen, Alicia R Martin, Jukka Koskela, Sanni E Ruotsalainen, Aki S Havulinna, Ida Surakka, Aarno Palotie, Markus Perola, Veikko Salomaa, Mark J Daly and 2 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

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

  1. Pooled it
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12 more citing papers are in PubMed but not listed here.

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

12 authors.

Sini KerminenInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland.
Alicia R MartinAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, 02142, USA.
Jukka KoskelaInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland.
Sanni E RuotsalainenInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland.
Aki S HavulinnaInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland.
Ida SurakkaInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.
Aarno PalotieInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA.
Markus PerolaInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; National Institute of Health and Welfare, Helsinki 00271, Finland.
Veikko SalomaaNational Institute of Health and Welfare, Helsinki 00271, Finland.
Mark J DalyInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, 02142, USA.
Samuli RipattiInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland.
Matti PirinenInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Helsinki Institute for Information Technology and Department of Mathematics and Statistics, University of Helsinki, Helsinki 00014, Finland. Electronic address: matti.pirinen@helsinki.fi.

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 scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.

Indexed as

Genetic MarkersGenetics, PopulationPolymorphism, Single NucleotideQuantitative Trait, HeritableAdultAgedArthritis, RheumatoidBody Mass IndexColitis, UlcerativeCoronary Artery DiseaseCrohn DiseaseFemaleFinlandGenetic Association StudiesGeographyHumansGenetic Markersgenetic predictiongenetic structurepopulation stratification

Identifiers

PMID31155286
PMCPMC6562021

What OpenQuestion holds

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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.