Evidence map›Paper›PMID 40887492›Full record

ArticleScientific reports2025

ACO1 OGDH axis drives mitochondrial immune crosstalk in preeclampsia through systems biology enabling dual target therapy.

Minglong Wu, Luxin Zhang

Abstract read
In one paragraph

Article in Scientific reports, 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

2 authors.

Minglong WuDepartment of Obstetrics and Gynecology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China. hkzz336@126.com.ORCID http://orcid.org/0009-0000-3007-5132
Luxin ZhangSchool of Medicine, Jianghan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preeclampsia (PE), a devastating pregnancy complication affecting 5% of gravidas worldwide, exhibits poorly characterized connections between mitochondrial dysfunction and immune dysregulation. This study aims to identify integrated mitochondrial-immune biomarkers for preeclampsia by multi-omics analysis of severe PE cohorts, enabling mechanistic insights and diagnostic potential. We developed a novel computational framework integrating multi-omics analysis (GSE10588 transcriptomics), machine learning (LASSO-SVM algorithm), and molecular dynamics simulation. This pipeline systematically identified mitochondrial-immune hubs from 1,589 PE-related DEGs and 188 mitochondrial regulators, followed by in silico validation of therapeutic targets. Fifteen candidate genes were identified by intersecting 1,589 DEGs and 188 MRGs. PPIs revealed associations with the citrate cycle (TCA cycle). Machine learning prioritized ACO1 and OGDH as biomarkers, showing opposite expression trends (ACO1: higher in controls; OGDH: elevated in PE). Both localized to chromosomes 9 and 7, respectively, with nuclear predominance. Enrichment linked them to cytokine-cytokine receptor and neuroactive ligand-receptor pathways. Immune infiltration highlighted correlations with activated NK cells and CD8+ T cells. Regulatory networks implicated lncRNAs (e.g., KCNQ1OT1), miRNAs (e.g., hsa-miR-214-3p), and TFs (e.g., TFAP2A). Drug predictions and docking identified devimistat and acetylcysteine as potential binders. This study establishes ACO1 and OGDH as context-specific mitochondrial-immune coordinators in preeclampsia. We propose a computationally derived dual-target therapeutic strategy, wherein ACO1 agonism aims to restore metabolic homeostasis while OGDH inhibition targets pathological overactivation. These findings, originating from in silico analyses, require preclinical validation through experimental models. Additionally, the mitochondrial-immune scoring system serves as a candidate tool for PE subtyping.

Indexed as

Coenzyme A LigasesMitochondriaPre-EclampsiaSystems BiologyBiomarkersFemaleGene Regulatory NetworksHumansMachine LearningPregnancyBiomarkersCoenzyme A LigasesDrug repurposingMachine learningMitochondrial-immune coordinationMolecular dynamics simulationPreeclampsia

Identifiers

PMID40887492
PMCPMC12399757

What Socratic holds

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LicenceCC BY-NC-ND
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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.