Evidence mapPaperPMID 40404628Full record

ArticleNature communications2025

Insights from the Biorepository and Integrative Genomics pediatric resource.

Silvia Buonaiuto, Franco Marsico, Akram Mohammed, Lokesh K Chinthala, Ernestine K Amos-Abanyie, Regeneron Genetics Center, Pjotr Prins, Khyobeni Mozhui, Robert J Rooney, Robert W Williams and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

14 authors.

Silvia Buonaiuto *Dept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.ORCID http://orcid.org/0000-0002-7423-7110
Franco Marsico *Dept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.
Akram MohammedCenter for Biomedical Informatics, UTHSC, Memphis, TN, USA.ORCID http://orcid.org/0000-0001-8093-8637
Lokesh K ChinthalaCenter for Biomedical Informatics, UTHSC, Memphis, TN, USA.ORCID http://orcid.org/0000-0002-1258-8353
Ernestine K Amos-AbanyieDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.ORCID http://orcid.org/0000-0003-1338-2733
Regeneron Genetics Center
Pjotr PrinsDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.
Khyobeni MozhuiDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.ORCID http://orcid.org/0000-0002-6623-4112
Robert J RooneyDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.
Robert W WilliamsDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.
Robert L DavisCenter for Biomedical Informatics, UTHSC, Memphis, TN, USA.ORCID http://orcid.org/0000-0001-8807-0019
Terri H FinkelDept of Pediatrics, Division of Rheumatology, UTHSC, Memphis, TN, USA.
Chester W BrownDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA.
Vincenza ColonnaDept of Genetics, Genomics and Informatics, UTHSC, Memphis, TN, USA. vcolonna@uthsc.edu.ORCID http://orcid.org/0000-0002-3966-0474

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Biorepository and Integrative Genomics (BIG) Initiative in Tennessee has developed a pioneering resource to address gaps in genomic research by linking genomic, phenotypic, and environmental data from a diverse Mid-South population, including underrepresented groups. We analyzed 13,152 exomes from BIG and found significant genetic diversity, with 50% of participants inferred to have non-European or several types of admixed ancestry. Ancestry within the BIG cohort is stratified, with distinct geographic and demographic patterns, as African ancestry is more common in urban areas, while European ancestry is more common in suburban regions. We observe ancestry-specific rates of novel genetic variants, which are enriched for functional or clinical relevance. Disease prevalence analysis linked ancestry and environmental factors, showing higher odds ratios for asthma and obesity in minority groups, particularly in the urban area. Finally, we observe discrepancies between self-reported race and genetic ancestry, with related individuals self-identifying in differing racial categories. These findings underscore the limitations of race as a biomedical variable. BIG has proven to be an effective model for community-centered precision medicine. We integrated genomics education, and fostered great trust among the contributing communities. Future goals include cohort expansion, and enhanced genomic analysis, to ensure equitable healthcare outcomes.

Indexed as

Biological Specimen BanksGenomicsAdolescentAsthmaChildCohort StudiesFemaleGenetic VariationHumansMaleRacial GroupsTennessee

Identifiers

PMID40404628
PMCPMC12098674

What Socratic holds

Textmetadata
LicenceCC BY
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.