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Background <p>Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) share overlapping features but arise from distinct molecular mechanisms. Competitive endogenous RNA (ceRNA) networks, where long non-coding RNAs (lncRNAs) and mRNAs compete for shared microRNAs (miRNAs), represent a key regulatory layer. This study sought to identify disorder-specific and convergent ceRNA regulatory signatures across these conditions.</p> Method <p>We constructed an integrative analysis of whole-transcriptome and small RNA sequencing data from peripheral blood samples of monozygotic twin pairs discordant for disease. Differentially expressed mRNAs, lncRNAs, and miRNAs were identified within each discordant pair and integrated with co-expression modules from external transcriptomic datasets constructed by Multiscale Embedded Gene Co-expression Network Analysis (MEGENA). This enabled the construction of disorder-specific ceRNA networks and the identification of core regulatory components.</p> Results <p>We identified ceRNA networks for each disorder, revealing 19 miRNAs shared across all three disorders, while lncRNAs and mRNAs were primarily disorder-specific. Among the shared miRNAs, hsa-miR-29a-3p was downregulated in both SCZ and MDD, regulating distinct ceRNA axes involving <i>COL6A6</i>. Functional enrichment analysis of hub ceRNA networks revealed the convergent involvement of extracellular matrix (ECM)-receptor interaction pathways. Notably, <i>COL6A6</i> (SCZ and MDD) and <i>ITGB8</i> (BD) were key components of these pathways. Validation using independent brain and blood transcriptomic datasets demonstrated strong predictive potential for <i>ITGB8</i> in the blood and prefrontal cortex for BD and SCZ, and moderate predictive potential for <i>COL6A6</i> in the blood and anterior cingulate gyrus for SCZ.</p> Conclusions <p>This study identifies non-coding RNA–mediated regulatory networks implicated in the molecular etiology of psychiatric disorders. Our findings provide a foundation for precision diagnostics and targeted therapeutic strategies in psychiatry.</p>

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Integrative ceRNA network analysis in monozygotic twins reveals shared and disorder-specific molecular signatures in major psychiatric disorders

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月14日

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  • Chenglin Lu,
  • Jianqiang Bi,
  • Ruobing Liu,
  • Jiazhuo Lan,
  • Yang He,
  • Chaoying Ni,
  • Xiaohui Wu,
  • Cunyou Zhao

摘要

Background

Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) share overlapping features but arise from distinct molecular mechanisms. Competitive endogenous RNA (ceRNA) networks, where long non-coding RNAs (lncRNAs) and mRNAs compete for shared microRNAs (miRNAs), represent a key regulatory layer. This study sought to identify disorder-specific and convergent ceRNA regulatory signatures across these conditions.

Method

We constructed an integrative analysis of whole-transcriptome and small RNA sequencing data from peripheral blood samples of monozygotic twin pairs discordant for disease. Differentially expressed mRNAs, lncRNAs, and miRNAs were identified within each discordant pair and integrated with co-expression modules from external transcriptomic datasets constructed by Multiscale Embedded Gene Co-expression Network Analysis (MEGENA). This enabled the construction of disorder-specific ceRNA networks and the identification of core regulatory components.

Results

We identified ceRNA networks for each disorder, revealing 19 miRNAs shared across all three disorders, while lncRNAs and mRNAs were primarily disorder-specific. Among the shared miRNAs, hsa-miR-29a-3p was downregulated in both SCZ and MDD, regulating distinct ceRNA axes involving COL6A6. Functional enrichment analysis of hub ceRNA networks revealed the convergent involvement of extracellular matrix (ECM)-receptor interaction pathways. Notably, COL6A6 (SCZ and MDD) and ITGB8 (BD) were key components of these pathways. Validation using independent brain and blood transcriptomic datasets demonstrated strong predictive potential for ITGB8 in the blood and prefrontal cortex for BD and SCZ, and moderate predictive potential for COL6A6 in the blood and anterior cingulate gyrus for SCZ.

Conclusions

This study identifies non-coding RNA–mediated regulatory networks implicated in the molecular etiology of psychiatric disorders. Our findings provide a foundation for precision diagnostics and targeted therapeutic strategies in psychiatry.