Evidence map›Paper›PMID 40714005›Full record

ArticleCell reports methods2025

Genetic analyses of eight complex diseases using predicted continuous representations of disease.

Robert Chen, Ghislain Rocheleau, Ben Omega Petrazzini, Iain S Forrest, Joshua K Park, Áine Duffy, Ha My T Vy, Daniel Jordan, Ron Do

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Robert ChenThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Ghislain RocheleauThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Ben Omega PetrazziniThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Iain S ForrestThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Joshua K ParkThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Áine DuffyThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Ha My T VyThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Daniel JordanThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Ron DoThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: ron.do@mssm.edu.

Funding

Towards an integrated map of causal connections for common, complex diseasesR35GM124836 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Ron Do · 2017 to 2026
$3.9M
NIGMS NIH HHS R35 GM124836
6 · The paper itself

Abstract

We evaluated whether predicted continuous disease representations could enhance genetic discovery beyond case-control genome-wide association study (GWAS) phenotypes across eight complex diseases in up to 485,448 UK Biobank participants. Predicted phenotypes had high genetic correlations with case-control phenotypes (median r

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyCase-Control StudiesFemaleHumansMaleMultifactorial InheritancePhenotypePolymorphism, Single NucleotideCP: computational biologyCP: geneticselectronic health recordsgenome-wide association studymachine learning

Identifiers

PMID40714005
PMCPMC12461582

What Socratic holds

Textmetadata
LicenceCC BY-NC
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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 Socratic graph.