Evidence map›Paper›PMID 41927563›Full record

ArticleScientific data2026

Personalized Environment and Genes Study (PEGS) Dataset-a resource for genomic, exposomic, and geospatial data.

Farida S Akhtari, Jennifer Madenspacher, Diane D'Agostin, Samantha Shuptrine, Nathaniel MacNell, Rebecca Ritter, Adam Burkholder, Zongli Xu, Jasmine A Mack, John S House and 7 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. 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. Article
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

17 authors.

Farida S AkhtariBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Jennifer MadenspacherClinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Diane D'AgostinClinical Research Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Samantha ShuptrineDLH Corporation, Bethesda, MD, USA.
Nathaniel MacNellDLH Corporation, Bethesda, MD, USA.
Rebecca RitterDLH Corporation, Bethesda, MD, USA.
Adam BurkholderOffice of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA.
Zongli XuBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA.
Jasmine A MackBiostatistics 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 http://orcid.org/0000-0002-8447-7871
Daniel J SchaidDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Shannon K McDonnellDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Shepherd H SchurmanClinical Research Core, National Institute on Aging, Bethesda, MD, USA.ORCID http://orcid.org/0000-0002-9133-7906
David C FargoOffice of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA.
Charles P SchmittOffice of Data Science, National Institute of Environmental Health Science, Durham, NC, USA.ORCID http://orcid.org/0000-0002-3148-2263
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. alison.motsinger-reif@nih.gov.ORCID http://orcid.org/0000-0003-1346-2493

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Personalized Environment and Genes Study (PEGS) is a unique resource comprising genetic and environmental exposure data linked to geospatial data. The PEGS cohort contains 19,445 demographically diverse participants who provided phenotype and exposure data by completing three surveys. Whole-genome sequencing was performed for a subset of 4,737 participants to interrogate common and rare variants and structural variations, including high-resolution human leukocyte antigen (HLA) variants. Geographic coordinates were assigned to participant addresses, enabling the use of distance to contaminant sources and area-level air-pollutant concentrations as surrogates for exposure. Several available tools are available to explore these data and results of exposome-wide association studies (ExWAS) conducted in the data. The i2b2 Query and Analysis Tool enables approved users to build customizable queries for exploring basic statistics from de-identified and aggregated PEGS data. PEGS Explorer allows users to explore published ExWAS results and rigorously calculated exposure correlations. Globe visualizations in this tool reflect the complex mixtures involved in the exposome and allow users to visualize correlations between exposures and common, complex diseases.

Indexed as

Environmental ExposureExposomeGenome-Wide Association StudyGenomicsHLA AntigensHumansHLA Antigens

Identifiers

PMID41927563
PMCPMC13216552

What OpenQuestion holds

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LicenceCC BY
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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.