Diseases (Basel, Switzerland) · 2025
Comprehensive Explorations and Preliminary Experimental Verification of RNA Modification-Related Diagnostic Markers in the Subtype Classification of Peripheral Blood-Derived Mononuclear Cells Derived from Post-Traumatic Stress Disorder Patients.
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Wang Lesheng, Luo Gaomeng, Liu Sha, Xu Zhipeng, Wei Wei, Li Xiang
Аннотация
BACKGROUND: The precise role of RNA modification in post-traumatic stress disorder (PTSD) remains incompletely understood. This study aims to elucidate the effects of five common RNA modifications in PTSD, specifically m6A, m5C, m1A, m7G, and ψ.
METHODS: We extracted data from the GEO repository to conduct a series of bioinformatics analyses. These included differential analysis to identify key regulators of five common RNA modifications, model construction using random forest (RF), least absolute shrinkage and selection operator (LASSO), and nomogram techniques, as well as consensus clustering of RNA modification subtypes. Furthermore, GO enrichment analysis was performed on DEGs associated with various RNA modification patterns. Immune cell infiltration was assessed using PCA and ssGSEA. RT-qPCR was performed to validate RNA modification-related genes (RMGs).
RESULTS: Twenty-one differentially expressed RMGs were identified. LASSO and RF intersection yielded eight signature genes (YTHDC1, IGFBP1, IGF2BP1, ALKBH5, NSUN4, TET2, TET3, WDR4) that robustly diagnosed PTSD (AUC = 0.804). Furthermore, these feature genes were validated using RT-qPCR, which was basically consistent with the results of bioinformatics analysis. Consensus clustering analysis may reveal two distinguishable subtypes: clusterA marked by high immunoinflammation, and clusterB characterized by high-neuroendocrine dysregulation.
CONCLUSIONS: RMGs may play a crucial role in the pathogenesis of PTSD. Analyzing RNA modification patterns could offer potential diagnostic markers and help to guide immunotherapeutic approaches or neurotransmitter system interventions for PTSD in the future.
METHODS: We extracted data from the GEO repository to conduct a series of bioinformatics analyses. These included differential analysis to identify key regulators of five common RNA modifications, model construction using random forest (RF), least absolute shrinkage and selection operator (LASSO), and nomogram techniques, as well as consensus clustering of RNA modification subtypes. Furthermore, GO enrichment analysis was performed on DEGs associated with various RNA modification patterns. Immune cell infiltration was assessed using PCA and ssGSEA. RT-qPCR was performed to validate RNA modification-related genes (RMGs).
RESULTS: Twenty-one differentially expressed RMGs were identified. LASSO and RF intersection yielded eight signature genes (YTHDC1, IGFBP1, IGF2BP1, ALKBH5, NSUN4, TET2, TET3, WDR4) that robustly diagnosed PTSD (AUC = 0.804). Furthermore, these feature genes were validated using RT-qPCR, which was basically consistent with the results of bioinformatics analysis. Consensus clustering analysis may reveal two distinguishable subtypes: clusterA marked by high immunoinflammation, and clusterB characterized by high-neuroendocrine dysregulation.
CONCLUSIONS: RMGs may play a crucial role in the pathogenesis of PTSD. Analyzing RNA modification patterns could offer potential diagnostic markers and help to guide immunotherapeutic approaches or neurotransmitter system interventions for PTSD in the future.