Evidence map›Paper›PMID 40929101›Full record

ArticlePloS one2025

HLX and SLC25A20: Immunologic regulators bridging ankylosing spondylitis and uveitis via multi-omics integration and machine learning.

Weiming Cai, Huayan Chen, Dong Huang, Xiaoli Ma, Dongbo Jiang, Tangming Guan

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

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Weiming CaiDepartment of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong Province, China.
Huayan ChenDepartment of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong Province, China.
Dong HuangDepartment of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong Province, China.
Xiaoli MaDepartment of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong Province, China.
Dongbo JiangDepartment of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong Province, China.
Tangming GuanDepartment of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong Province, China.ORCID 0000-0002-4617-8221

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnkylosing spondylitis (AS), a chronic inflammatory disorder affecting axial joints, is frequently complicated by uveitis. However, the molecular mechanisms linking AS to secondary uveitis remain poorly understood.

methodsWe integrated transcriptomic datasets from AS (GSE73754) and uveitis (GSE194060) cohorts to identify shared molecular pathways. Differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning (LASSO, SVM-RFE, random forest) were combined to prioritize biomarkers. Molecular docking was performed to evaluate drug-target interactions using Vina scores (≤-7 kcal/mol threshold).

resultsCross-disease analysis revealed 697 overlapping dysregulated genes (481 upregulated, 216 downregulated), enriched in GTPase signaling and immune pathways. WGCNA identified disease-specific co-expression modules (AS: brown/tan modules, r = 0.39/0.35; uveitis: brown module, r = 0.49). Machine learning nominated HLX and SLC25A20 as core biomarkers, demonstrating robust diagnostic accuracy in discovery (AS AUC: 0.688/0.700; uveitis AUC: 0.867/0.838) and validation cohorts (AS AUC: 0.653/0.667; uveitis AUC: 0.662/0.736). Immune profiling linked HLX to neutrophil infiltration (r = 0.55, p < 0.01) and SLC25A20 to T helper cell regulation (r = 0.36, p < 0.01). Molecular docking identified high-affinity ligands for SLC25A20, including amiodarone (-8.0 kcal/mol) and estradiol (-7.7 kcal/mol), with folic acid showing dual binding potential (HLX: -7.5 kcal/mol; SLC25A20: -8.2 kcal/mol).

conclusionHLX and SLC25A20 emerge as immunologic regulators bridging AS and uveitis pathogenesis. These findings provide actionable targets for precision diagnostics and therapeutic development in AS-associated uveitis.

Indexed as

Machine LearningSpondylitis, AnkylosingUveitisBiomarkersGene Expression ProfilingGene Regulatory NetworksHumansMolecular Docking SimulationMultiomicsTranscriptomeBiomarkers

Identifiers

PMID40929101
PMCPMC12422499

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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.