Evidence map›Paper›PMID 32817414›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Multiomic blood correlates of genetic risk identify presymptomatic disease alterations.

Michael Wainberg, Andrew T Magis, John C Earls, Jennifer C Lovejoy, Nasa Sinnott-Armstrong, Gilbert S Omenn, Leroy Hood, Nathan D Price

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Review
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  3. Article
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  7. Review
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  9. Article
  10. Article
  11. Review
  12. An epidemiological introduction to human metabolomic investigations.Trends in endocrinology and metabolism: TEM · 2023
    Review
  13. Cumulative Genetic Score andNeurology. Genetics · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. The Coaching for Cognition in Alzheimer's (COCOA) trial: Study design.Alzheimer's & dementia (New York, N. Y.) · 2022
    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

8 authors.

Michael WainbergInstitute for Systems Biology, Seattle, WA 98109.
Andrew T MagisInstitute for Systems Biology, Seattle, WA 98109.ORCID 0000-0003-0576-677X
John C EarlsInstitute for Systems Biology, Seattle, WA 98109.
Jennifer C LovejoyInstitute for Systems Biology, Seattle, WA 98109.
Nasa Sinnott-ArmstrongDepartment of Genetics, Stanford University, Stanford, CA 94305.
Gilbert S OmennDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-8976-6074
Leroy HoodInstitute for Systems Biology, Seattle, WA 98109; lhood@systemsbiology.org nathan.price@systemsbiology.org.ORCID 0000-0001-7158-3678
Nathan D PriceInstitute for Systems Biology, Seattle, WA 98109; lhood@systemsbiology.org nathan.price@systemsbiology.org.

Funding

Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI FRED H GAGE · 2004 to 2026
$102.6M
Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
NIA NIH HHS U19 AG023122NIEHS NIH HHS P30 ES017885
6 · The paper itself

Abstract

Transitions from health to disease are characterized by dysregulation of biological networks under the influence of genetic and environmental factors, often over the course of years to decades before clinical symptoms appear. Understanding these dynamics has important implications for preventive medicine. However, progress has been hindered both by the difficulty of identifying individuals who will eventually go on to develop a particular disease and by the inaccessibility of most disease-relevant tissues in living individuals. Here we developed an alternative approach using polygenic risk scores (PRSs) based on genome-wide association studies (GWAS) for 54 diseases and complex traits coupled with multiomic profiling and found that these PRSs were associated with 766 detectable alterations in proteomic, metabolomic, and standard clinical laboratory measurements (clinical labs) from blood plasma across several thousand mostly healthy individuals. We recapitulated a variety of known relationships (e.g., glutamatergic neurotransmission and inflammation with depression, IL-33 with asthma) and found associations directly suggesting therapeutic strategies (e.g., Ω-6 supplementation and IL-13 inhibition for amyotrophic lateral sclerosis) and influences on longevity (leukemia inhibitory factor, ceramides). Analytes altered in high-genetic-risk individuals showed concordant changes in disease cases, supporting the notion that PRS-associated analytes represent presymptomatic disease alterations. Our results provide insights into the molecular pathophysiology of a range of traits and suggest avenues for the prevention of health-to-disease transitions.

Indexed as

Asymptomatic DiseasesBiomarkersCohort StudiesDatabases, GeneticDisease ProgressionGenetic Predisposition to DiseaseGenetic TestingGenome-Wide Association StudyHumansMetabolomicsMultifactorial InheritancePolymorphism, Single NucleotideProteomicsRisk FactorsBiomarkersmetabolomicspolygenic risk scorespresymptomatic diseaseproteomics

Identifiers

PMID32817414
PMCPMC7474629

What OpenQuestion holds

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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.