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PMID: 42026034 已发表 · epublish 英语

Identification of susceptibility modules and genes through WGCNA and ceRNA network analysis in neuropathic pain-induced anxiodepression.

Translational psychiatry ·第 16 卷 ·第 1 期 ·2026-04-23

He Y, Xu Y, Xing F, Shi X, Zhang F, Xing M, Liu Y, Zhang W, Wei X, Yuan J

摘要

Neuropathic pain (NP) is frequently comorbid with anxiety and depression, yet the underlying molecular mechanisms in the brain remain poorly understood, hindering the development of targeted therapies. This study aimed to identify key transcriptional networks and regulatory pathways in the anterior cingulate cortex (ACC) associated with NP-induced anxiodepression. We analyzed transcriptomic data (GSE92718) from the ACC of a mouse model of chronic NP. By comparing differentially expressed genes at a time point manifesting anxiodepressive-like behavior (8-week post-injury) against those with pain alone (2-week), we constructed a weighted gene co-expression network (WGCNA). A key module (blue module) significantly correlated with the anxiodepressive phenotype was enriched for synaptic signaling (glutamatergic/GABAergic), neuroplasticity, and key pathways like MAPK and Ras. Within this module, we identified 7 pivotal lncRNAs and 5 hub mRNAs (Flt1, Slc38a2, Bmpr1b, Pdgfra, Gng2) via integrated lncRNA-mRNA-pathway and protein-protein interaction network analyses. Furthermore, we established a competing endogenous RNA (ceRNA) network, revealing a core regulatory axis comprising 3 hub lncRNAs, 5 hub mRNAs, and 40 miRNAs. The aberrant expression of the five hub mRNAs in the ACC was specifically validated in mice with anxiodepressive phenotypes using RT-PCR. Our findings unveil a critical ceRNA network and implicate dysregulated synaptic genes in the ACC as key drivers of NP-induced anxiodepression, providing novel insights into its molecular basis and highlighting potential diagnostic biomarkers and therapeutic targets.

文献信息
期刊
Translational psychiatry
期刊简称
Transl Psychiatry
ISSN
2158-3188
发表日期
2026-04-23
语言
英语
国家/地区
United States
NLM ID
101562664
分析服务
分析服务

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