Evidence map›Paper›PMID 40463540›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Extracting and calibrating evidence of variant pathogenicity from population biobank data.

Vineel Bhat, Tian Yu, Lara Brown, Vikas Pejaver, Matthew Lebo, Steven Harrison, Christopher A Cassa

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Vineel BhatDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0002-6583-8176
Tian YuDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Lara BrownDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Vikas PejaverInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY.
Matthew LeboLaboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Boston, MA.
Steven HarrisonBroad Institute of MIT and Harvard, Cambridge, MA.
Christopher A CassaDivision of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0002-5771-9177

Funding

Integrated pathogenicity assessment of clinically actionable genetic variantsR01HG010372 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASSA, CHRISTOPHER · 2018 to 2022
$3.5M
Systematic integration of variant interpretation tools into genetic and genomic risk predictionR01HG013350 · NHGRI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Vikas Rao Pejaver · 2024 to 2026
$1.7M
Integrative computational-experimental approaches to stratify monogenic disease riskR56HG012681 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASSA, CHRISTOPHER, SHERWOOD, RICHARD I · 2023 to 2023
$300k
NHGRI NIH HHS R01 HG010372NHGRI NIH HHS R01 HG013350NHGRI NIH HHS R56 HG012681
6 · The paper itself

Abstract

Genomic medicine requires a robust evidence base of variant phenotypic impacts, which remains incomplete even in extensively studied monogenic disease genes. Here, we evaluated the broad potential of using population cohort data to identify evidence that can be used in variant assessment. Across 41 genes related to 18 clinically actionable monogenic phenotypes, we calculated variant-level odds ratios of disease enrichment using data from 469,803 UK Biobank participants. We found significant differences in odds ratio values between ClinVar-labeled pathogenic and benign variants in 11 phenotypes, spanning both common and rare disorders. To facilitate clinical translation, we calibrated the strength of evidence provided by variant-level odds ratios to align with American College of Medical Genetics and Genomics (ACMG/AMP) interpretation guidelines (PS4 criterion), and found that odds ratios may reach 'moderate', 'strong', or 'very strong' evidence, varying by phenotype and gene. Overall, we found that 2.6% (N = 12,350) of participants harbor a rare VUS with at least 'moderate' evidence of pathogenicity - an indication of potentially unrecognized disease risk. Finally, by incorporating computational and functional data alongside population-based odds ratios, we identified variants that met criteria for clinical reclassification. Notably, using this approach, we identified that 12.4% of rare VUS in

Identifiers

PMID40463540
PMCPMC12132127

What Socratic holds

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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.