Evidence map›Paper›PMID 42200542›Full record

ReviewEnvironmental science & technology2026

Vision for Exposomics-Scale Investigation: A Heuristic for Exposure-Wide Association Studies (ExWAS).

Chirag J Patel, Gary W Miller, Alison A Motsinger-Reif

Abstract readReview
In one paragraph

Review in Environmental science & technology, 2026. 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

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

3 authors.

Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, United States.ORCID 0000-0002-8756-8525
Gary W MillerDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States.ORCID 0000-0001-8984-1284
Alison A Motsinger-ReifNational Institute of Environmental Health Sciences (NIEHS), National Institutes of Health, Durham, North Carolina 27709, United States.

Funding

NEXUS: Network for Exposomics in the U.S.U24ES036819 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Rima Habre, GARY W MILLER · 2024 to 2026
$4.6M
NIEHS NIH HHS U24 ES036819
6 · The paper itself

Abstract

Exposomics has the potential to revolutionize biomedical research. However, the transition from hypothesis-driven to discovery-driven research has created tension between expansive screening and the risk of false discoveries. To meet the rigorous expectations of funders, editors, and the broader scientific community, the field requires clear benchmarks for a specific discovery-oriented design within exposomics: the Exposure-Wide Association Study (ExWAS). Here, we propose a heuristic framework for ExWAS based on the 5 I's: Inclusive, Informative, Immense, Integrative, and Iterative. We distinguish ExWAS from the broader enterprise of exposomics: high-resolution personal sensor studies, high-throughput screening in model systems, targeted biomonitoring, and single-exposure causal studies are essential and complementary. We operationalize each 'I' as a set of graded thresholds rather than absolute gates, so that smaller groups and under-resourced cohorts can participate through federated and meta-analytic designs. Mirroring the systematic rigor of genomics, these criteria provide a roadmap for minimizing spurious associations while preserving discovery power and supporting the eventual creation of an "Exposome-Phenome Catalog" analogous to the GWAS Catalog.

Indexed as

Environmental ExposureExposomeGenome-Wide Association StudyHeuristicsHumansarchitectureexposomeexposome-wide association studyheuristicphenome

Identifiers

PMID42200542
PMCPMC13261867

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.