Evidence map›Paper›PMID 38425336›Full record

ArticleExposome2024

Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study.

Dillon Lloyd, John S House, Farida S Akhtari, Charles P Schmitt, David C Fargo, Elizabeth H Scholl, Jason Phillips, Shail Choksi, Ruchir Shah, Janet E Hall and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Exposome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
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

6 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Observational
  3. Article
  4. Article
  5. Global research trends on the human exposome: a bibliometric analysis (2005-2024).Environmental science and pollution research international · 2025
    Review
  6. 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

11 authors at 3 institutions in 1 country.

Dillon LloydBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
John S HouseBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.ORCID https://orcid.org/0000-0002-8447-7871
Farida S AkhtariBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Charles P SchmittDivision of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA.ORCID https://orcid.org/0000-0002-3148-2263
David C FargoOffice of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA.
Elizabeth H SchollSciome LLC, Durham, NC, USA.
Jason PhillipsSciome LLC, Durham, NC, USA.
Shail ChoksiSciome LLC, Durham, NC, USA.
Ruchir ShahSciome LLC, Durham, NC, USA.
Janet E HallClinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Alison A Motsinger-ReifBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.ORCID https://orcid.org/0000-0003-1346-2493
National Institute of Environmental Health Sciences · USScio Diamond Technology Corporation (United States) · USOffice of the Director · US

Funding

Personalized Environment and Genes Study (PEGS)ZICES103354 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI HALL, JANET · 2020 to 2024
$7.0M
The Personalized Environment and Genes StudyZIAES103394 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI MOTSINGER-REIF, ALISON · 2023 to 2025
$2.7M
6 · The paper itself

Abstract

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.

Indexed as

data sharingexposome dataexposome-wide association study (ExWAS)occupational exposuresPersonalized Environment and Genes Study (PEGS)web application

Identifiers

PMID38425336
PMCPMC10899804
OpenAlexW4392316474

What Socratic holds

Textmetadata
Read underepoch 390

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.