Evidence map›Paper›PMID 41333919›Full record

ArticleMediators of inflammation2025

Causal Gene Identification and Biomarker Prioritization in Periodontitis via Integrative Multiomics and Mendelian Randomization.

Haokun Mo, Lulu Chen, Shanshan Ren, Yue Wu, Ai Tian

Abstract read
In one paragraph

Article in Mediators of inflammation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

5 authors.

Haokun MoSchool of Stomatology, Guizhou Medical University, Guiyang, Guizhou, China.
Lulu ChenSchool of Stomatology, Guizhou Medical University, Guiyang, Guizhou, China.
Shanshan RenSchool of Stomatology, Guizhou Medical University, Guiyang, Guizhou, China.
Yue WuMedical Collaboration Department, Affiliated Hengyang Hospital of Hunan Normal University and Hengyang Central Hospital, Hengyang, Hunan, China.ORCID https://orcid.org/0009-0001-9031-7794
Ai TianSchool of Stomatology, Guizhou Medical University, Guiyang, Guizhou, China.ORCID https://orcid.org/0009-0000-1849-0624

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Periodontitis is a common inflammatory disease that compromises oral and systemic health. This study aimed to elucidate its molecular mechanisms and identify potential biomarkers for early diagnosis and precision treatment. Methods: We integrated genome-wide association study (GWAS) and transcriptomic data from periodontitis patients and healthy controls. Summary data-based Mendelian randomization (SMR) and the heterogeneity in dependent instruments (HEIDI) test were used to identify genetically associated genes. Differentially expressed genes (DEGs) were identified using LIMMA, and weighted gene co-expression network analysis (WGCNA) revealed disease-related gene modules. Candidate biomarkers were prioritized through intersection analysis and evaluated using five machine learning algorithms. Causal relationships were further validated by two-sample Mendelian randomization (TSMR). Functional enrichment was assessed via gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA), and immune infiltration was analyzed using CIBERSORT. Results: SMR identified 360 gene-trait associations, with 320 passing the HEIDI test, corresponding to 294 unique genes. DEGs were enriched in immune and neuronal development pathways. WGCNA uncovered nine gene modules associated with periodontitis. Intersection and machine learning analyses identified five key biomarkers-GPX2, IGKV2D-30, CD34, GSTA4, and NYNRIN-with strong predictive performance, validated by MR analysis ( Conclusion: This integrative multiomics analysis uncovers causal genes and robust biomarkers involved in periodontitis pathogenesis, providing new insights for early detection and individualized treatment strategies. Further experimental validation is needed to confirm their functional roles in disease progression and therapeutic potential.

Indexed as

BiomarkersMendelian Randomization AnalysisPeriodontitisGene Expression ProfilingGene Regulatory NetworksGenome-Wide Association StudyHumansMachine LearningMultiomicsTranscriptomeBiomarkersbiomarkersMendelian randomizationperiodontitisSMRWGCNA

Identifiers

PMID41333919
PMCPMC12668852

What Socratic holds

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Registered trials

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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 Socratic graph.