Rehawi Ghalia, Hagenberg Jonas, Sämann Philipp G, Moyon Lambert, Binder Elisabeth, List Markus, Marsico Annalisa, Knauer-Arloth Janine
Max Planck Institute of Psychiatry, 80804 Munich, Germany.
Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
iScience. 2025 Aug 13;28(9):113342. doi: 10.1016/j.isci.2025.113342. eCollection 2025 Sep 19.
Isoform-specific expression patterns have been linked to stress-related psychiatric disorders such as major depressive disorder (MDD). To further explore their involvement, we constructed co-expression networks using total gene expression (TE) and isoform ratio (IR) data from affected ( = 210, 81% with depressive symptoms) and unaffected ( = 95) individuals. Networks were validated using advanced graph generation methods. Our analysis revealed distinct differences in network topology and structure. Shared hubs exhibited unique co-regulatory patterns in each network, with key master hubs in the affected network showing association with psychiatric disorders. Gene Ontology enrichment highlighted condition-specific biological processes linked to each network's master hubs. Notably, isoform-level data uncovered unique co-regulatory interactions and enrichments not observed at the gene level. This is the first study to show network-level differences of gene and isoform co-expression between affected and unaffected individuals of stress-related psychiatric disorders, emphasizing the importance of isoforms in understanding the molecular mechanisms of these conditions.
亚型特异性表达模式与应激相关的精神疾病如重度抑郁症（MDD）有关。为了进一步探究它们的作用，我们使用来自受影响个体（n = 210，81%有抑郁症状）和未受影响个体（n = 95）的总基因表达（TE）和亚型比例（IR）数据构建了共表达网络。使用先进的图形生成方法对网络进行了验证。我们的分析揭示了网络拓扑结构和结构上的明显差异。共享枢纽在每个网络中表现出独特的共调控模式，受影响网络中的关键主枢纽与精神疾病相关。基因本体富集突出了与每个网络主枢纽相关的特定条件下的生物学过程。值得注意的是，亚型水平的数据揭示了在基因水平未观察到的独特共调控相互作用和富集。这是第一项显示应激相关精神疾病受影响和未受影响个体之间基因和亚型共表达的网络水平差异的研究，强调了亚型在理解这些疾病分子机制中的重要性。
