Evidence map›Paper›PMID 39747598›Full record

ArticleNature genetics2025

Fine-mapping causal tissues and genes at disease-associated loci.

Benjamin J Strober, Martin Jinye Zhang, Tiffany Amariuta, Jordan Rossen, Alkes L Price

Abstract read
In one paragraph

Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Review
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  9. Distinguishing causal from tagging enhancers using single-cell multiome data.medRxiv : the preprint server for health sciences · 2026
    Article
  10. Article
  11. Review
  12. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Benjamin J StroberDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. bstrober@hsph.harvard.edu.ORCID 0000-0003-2969-2808
Martin Jinye ZhangDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0003-0006-2466
Tiffany AmariutaHalıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0003-0121-1726
Jordan RossenDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Alkes L PriceDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. aprice@hsph.harvard.edu.ORCID 0000-0002-2971-7975

Funding

Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
Statistical methods to localize disease heritability and identify biological mechanismsR37MH107649 · NIMH · BROAD INSTITUTE, INC. · PI Benjamin Michael Neale · 2019 to 2026
$7.0M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
Joint genomic and statistical analyses of schizophrenia and bipolar to decipher genetic susceptibilityR01MH115676 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Roel A Ophoff, Bogdan Pasaniuc · 2018 to 2026
$5.9M
Predicting the impact of genetic variants, genes and pathways on human DiseaseU01HG012009 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ALKES L PRICE, Soumya Raychaudhuri · 2021 to 2026
$4.2M
Integrative modelling of single-cell data to elucidate the genetic architecture of complex diseaseR01HG013083 · NHGRI · DANA-FARBER CANCER INST · PI ALEXANDER GUSEV, ALKES L PRICE · 2024 to 2026
$1.5M
Integrative modelling of single-cell data to elucidate the genetic architecture of complex diseaseR56HG013083 · NHGRI · DANA-FARBER CANCER INST · PI GUSEV, ALEXANDER, PRICE, ALKES L · 2023 to 2023
$400k
Fine-mapping causal tissues at disease-associated loci to infer disease subtypesF32HG012889 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI STROBER, BENJAMIN · 2023 to 2025
$171k
Methods for multi-ancestry and multi-trait fine-mapping and genetic risk predictionF31HG013040 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ROSSEN, JORDAN · 2023 to 2024
$81k
NHGRI NIH HHS F31 HG013040NHGRI NIH HHS F32 HG012889NHGRI NIH HHS R01 HG006399NHGRI NIH HHS R01 HG013083NHGRI NIH HHS R56 HG013083NHGRI NIH HHS U01 HG012009NIMH NIH HHS R01 MH101244NIMH NIH HHS R01 MH115676NIMH NIH HHS R37 MH107649U.S. Department of Health & Human Services | National Institutes of Health (NIH) RO1 HG006399U.S. Department of Health & Human Services | National Institutes of Health (NIH) RO1 MH101244U.S. Department of Health & Human Services | National Institutes of Health (NIH) RO1 MH115676U.S. Department of Health & Human Services | National Institutes of Health (NIH) UO1 HG012009
6 · The paper itself

Abstract

Complex diseases often have distinct mechanisms spanning multiple tissues. We propose tissue-gene fine-mapping (TGFM), which infers the posterior inclusion probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing summary statistics and expression quantitative trait loci (eQTL) data; TGFM also assigns PIPs to non-mediated variants. TGFM accounts for co-regulation across genes and tissues and models uncertainty in cis-predicted expression models, enabling correct calibration. We applied TGFM to 45 UK Biobank diseases or traits using eQTL data from 38 Genotype-Tissue Expression (GTEx) tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease or trait, of which 11% were gene-tissue pairs. Causal gene-tissue pairs identified by TGFM reflected both known biology (for example, TPO-thyroid for hypothyroidism) and biologically plausible findings (for example, SLC20A2-artery aorta for diastolic blood pressure). Application of TGFM to single-cell eQTL data from nine cell types in peripheral blood mononuclear cells (PBMCs), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs.

Indexed as

Chromosome MappingGenetic Predisposition to DiseaseQuantitative Trait LociGenome-Wide Association StudyGenotypeHumansOrgan SpecificityPolymorphism, Single Nucleotide

Identifiers

PMID39747598
PMCPMC12413687

What Socratic holds

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Registered trials

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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 Socratic graph.