Evidence map›Paper›PMID 40963761›Full record

ArticlemedRxiv : the preprint server for health sciences2025

GWAS for Periodontitis Phenotypes Using Multi-Ancestry All of Us Research Platform.

Keith Sanders, Ardalan Naseri, Chun-Teh Lee, Junichi Iwata, Yixuan He, Bunmi Tokede, Muhammad Walji, Degui Zhi, Laila Rasmy

Abstract readPreprint
PubMed Full text at PMC Publisher
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

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

9 authors.

Keith SandersThe University of Texas Health Science Center at McWilliams School of Biomedical Informatics, Houston, Texas, USA.
Ardalan NaseriThe University of Texas Health Science Center at McWilliams School of Biomedical Informatics, Houston, Texas, USA.
Chun-Teh LeeDepartment of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, Texas, USA.
Junichi IwataDepartment of Orthodontics and Pediatric Dentistry, University of Michigan School of Dentistry, Ann Arbor, Michigan, USA.
Yixuan HeCenter for Human Genetics Department of Epidemiology, The University of Texas Health Science Center School of Public Health, Houston, TX, USA.
Bunmi TokedeOral Healthcare Quality and Safety, Diagnostic and Biomedical Sciences, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
Muhammad WaljiThe University of Texas Health Science Center at McWilliams School of Biomedical Informatics, Houston, Texas, USA.
Degui ZhiThe University of Texas Health Science Center at McWilliams School of Biomedical Informatics, Houston, Texas, USA.ORCID 0000-0001-7754-1890
Laila RasmyThe University of Texas Health Science Center at McWilliams School of Biomedical Informatics, Houston, Texas, USA.ORCID 0000-0002-2644-4908

Funding

Genetics of deep-learning-derived neuroimaging endophenotypes for Alzheimer's Disease (Parent grant)U01AG070112 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI FORNAGE, MYRIAM, JI, SHUIWANG · 2021 to 2025
$7.2M
Deep Learning Based Pharmacokinetic Model for VancomycinR01AI175699 · NIAID · METHODIST HOSPITAL RESEARCH INSTITUTE · PI NIGO, MASAYUKI · 2023 to 2025
$2.4M
Clinical foundation model for structured clinical dataR01LM014249 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Laila Rasmy Gindy Bekhet · 2023 to 2026
$1.4M
NIAID NIH HHS R01 AI175699NIA NIH HHS U01 AG070112NLM NIH HHS R01 LM014249
6 · The paper itself

Abstract

Periodontitis is a multifactorial inflammatory disease whose pathogenesis is associated with intricate interactions between genetic and environmental factors. Leveraging electronic health records data from the All of Us Research Program, we stratified periodontitis by clinically relevant dimensions: stage, grade, and extent. Based on these phenotypes, we performed a multi-ancestry genome-wide association study, focusing on predominant ancestry populations of African, European, and Admixed American. Our study cohort comprised 3,881 periodontitis patients and a control group of 10,760 patients with dental caries and without periodontitis. Ancestry-specific GWAS revealed significant genetic associations (P<5×10

Identifiers

PMID40963761
PMCPMC12440056

What OpenQuestion holds

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LicenceCC BY-NC
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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.