Aug 2026· Brain Research· pp.
150485
· 0 citations· 55 references
Medicine
TL;DR
This study integrated mRNA expression profiles from five post-mortem brain tissue GEO datasets to identify ASD-associated genes and found that EIF4A1 mRNA expression was significantly elevated in ASD subjects and rescued by treatment with the antipsychotics olanzapine or risperidone.
Abstract
Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition with complex genetic and molecular mechanism. Identifying reliable molecular biomarkers remains a critical challenge. In this study, we integrated mRNA expression profiles from five post-mortem brain tissue GEO datasets to identify ASD-associated genes. Following batch effect correction, differentially expressed genes (DEGs) were analysed and Weighted Gene Co-expression Network Analysis (WGCNA) was performed to screen genes correlated with ASD. Then, five machine learning algorithms - Random Forest, LASSO, Boruta, CatBoost, and LightGBM - were applied to screen hub genes. Lastly, alterations of the hub gene(s) were investigated with a maternal immune activation (MIA) rat model using poly I:C by measuring mRNA expression of the hub genes in the rat nucleus accumbens (NAc) and caudate putamen (CPu). A total of 30 DEGs and 54 WGCNA module genes were identified, yielding 29 key candidates by intersecting these two gene sets. EIF4A1 (Eukaryotic Translation Initiation Factor 4A1) was the sole gene consistently ranked among the top five by all five machine learning algorithms. Analysis of the integrated dataset confirmed that EIF4A1 mRNA expression was significantly elevated in ASD subjects. Finally, using the MIA rat model of ASD, we found that EIF4A1 mRNA expression was significantly down-regulated in the NAc and CPu, and this deficit was rescued by treatment with the antipsychotics olanzapine or risperidone. In conclusion, the present study positions EIF4A1 as a promising candidate molecular indicator with potential implications for understanding disease mechanisms and developing targeted interventions of ASD.
Findings indicate that CASP4 and TLR8, together with their associated regulatory miRNAs, may represent promising biomarkers and potential therapeutic targets for future ASD research and contribute to a better understanding of the pathophysiological mechanisms underlying ASD.
Sara Hosseinpoor, H. Zali, Hassan Zohrevand et al.· PLoS ONE· 0 citations
Parkinson’s disease (PD) pathogenesis involves complex molecular mechanisms, with emerging evidence implicating RNA modifications (RM). This study sought to explore RM-associated key genes and their roles in PD progression.
Transcriptomic datasets GSE6613 (training) and GSE72267 (validation) were analyzed. Differentially expressed genes (DEGs) between PD and controls were recognized. WGCNA was performed to identify RM-associated module genes. Machine learning algorithms, Receiver Operating Characteristic (ROC) analysis, and gene expression validation were applied to screen key genes. Nomogram construction, functional enrichment, immune infiltration analysis were conducted to investigate the biological mechanisms and therapeutic potential of the key genes. The bioinformatics findings were further supported by RT-qPCR experiments in a small clinical cohort (
n
= 5 per group), though these preliminary results require validation in larger independent samples.
Through intersection of 507 DEGs and 2,091 RM-associated module genes, 63 candidate genes related to RM in PD were identified. Machine learning, ROC analysis, gene expression validation, and clinical experiments were further employed to identify two key genes (NOL7 and TXLNA). A nomogram constructed based on key genes demonstrated moderate diagnostic efficacy for PD, with an area under the curve of 0.792. Enrichment analyses revealed associations of the key genes with neuroactive pathways, such as spliceosome and ribosome. Immune infiltration analysis suggested a negative correlation between NOL7 and NKT (cor = -0.30,
P
< 0.05). Furthermore, danazol was predicted to be a compound associated with both NOL7 and TXLNA. Molecular docking analysis revealed that danazol exhibited a relatively favorable binding affinity for NOL7 (-6.3 kcal/mol), whereas its binding affinity for TXLNA was weaker (-4.7 kcal/mol).
NOL7 and TXLNA were validated as blood biomarkers for PD derived from an RNA modification-associated transcriptional module, offering insights into epigenetic dysregulation and immune interactions. The nomogram provided a preliminary framework for PD risk assessment, and the drug prediction offered potential candidates for future therapeutic exploration.
Meiling Chen, Peng Chen, Liya Suo et al.· BMC Neurology· 0 citations
RNA-sequencing, 3-dimensional protein-centric chromatin conformation, and whole genome DNA methylation sequencing approaches are used to investigate hippocampal tissue from an ASD mouse model to determine if multi-omic data integration improves the resolution of key molecular pathways contributing to the complex ASD phenotype.
Carolina D Alberca, Kwangmoon Park, Ligia A. Papale et al.· Molecular Psychiatry· 0 citations
Background The genesis of Parkinson’s disease (PD), a common central neurodegenerative disorder, involves dysregulation of protein posttranslational modifications (PTM). The primary objective of this study was to screen key PTM-associated genes (PTMGs) serving as diagnostic indicators and potential therapeutic targets in PD. Methods Peripheral blood transcriptomic data for PD cohorts and healthy controls were retrieved from publicly accessible repositories. Candidate genes were identified by overlapping differentially expressed genes (DEGs) with established PTMGs via differential expression profiling. Machine learning-based screening approaches were used for the selection of feature genes. Key genes were validated via receiver operating characteristic curve assessment combined with verification of expression levels. Subsequently, enrichment analysis, immune infiltration assessment, chromosome mapping, prediction of ribonucleic acid (RNA) modification sites, and compound screening were further explored. Results A total of 404 DEGs were identified, 19 of which overalpped with PTMGs and were thus selected as candidate genes. ML-based analysis narrowed these to eight feature genes, among which those coding for beta-1,4-galactosyltransferase 3 (B4GALT3), ring finger and FYVE-like domain-containing E3 ubiquitin protein ligase (RFFL), and GABA type A receptor-associated protein (GABARAP) were validated as key genes based on their diagnostic performance and consistent downregulation in the PD group (p < 0.05). Gene set enrichment analysis demonstrated significant enrichment within immune signaling cascades. Analysis of immune cell infiltration revealed diminished populations of activated B lymphocytes, activated CD4-positive T cells, and natural killer T cell subsets in the PD group, which exhibited predominantly positive associations with the identified key genes (p < 0.05). Chromosome mapping localized B4GALT3 to chromosome 1 and RFFL/GABARAP to chromosome 17. High-confidence m6A methylation sites were predicted for B4GALT3 and RFFL. Compound screening identified 34 potential compounds targeting these genes, including valproic acid and phenobarbital. Conclusion This study identified B4GALT3, RFFL, and GABARAP as key PTMGs in PD, highlighting their roles in PD genesis and potential as diagnostic biomarkers.
Bangzhi Wang, Zhuo Huang, Rong Wang et al.· PLoS ONE· 0 citations
Schizophrenia (SCZ) involves immune dysregulation and synaptic deficits, yet the molecular link between peripheral inflammation and central synaptic pathology remains unclear. We integrated blood transcriptomes from four SCZ cohorts (478 samples: 245 patients, 233 controls) and validated findings in single-cell brain data and an ELNI mouse model. After batch correction, 272 genes were differentially expressed, with S100A8 as the top upregulated immune gene. WGCNA identified a disease-associated module (blue, 133 genes, r = 0.16, p = 7 × 10⁻⁴) containing S100A8; its intersection with differentially expressed genes yielded 44 key genes enriched for cytoplasmic translation, mitochondrial electron transport, and innate immunity. Machine learning ranked S100A8 as the top discriminative feature, and its upregulation was robust across four independent analytic pipelines. CIBERSORTx revealed increased neutrophils and decreased regulatory T and resting NK cells in patients, with S100A8 correlating positively with neutrophils. Single-cell analysis showed that S100A8-expressing cells were specifically expanded in microglia (2.98% → 3.94%, OR = 1.34), and S100A8⁺ microglia displayed an activated state with coordinated upregulation of complement (C1QA/B/C) and phagocytic genes and downregulation of homeostatic markers (P2RY12, CX3CR1). In ELNI mice exhibiting SCZ-like behaviors, S100A8/S100A9 were upregulated in hippocampus and frontal cortex, accompanied by CD68 induction and reduced synaptophysin, with S100A8 correlating positively with CD68 and negatively with synaptophysin. Molecular docking identified hydroxyzine as a candidate S100A8 ligand. These convergent findings establish S100A8 as a hub linking peripheral immune dysregulation to microglial activation and synaptic pathology in SCZ, highlighting it as a candidate biomarker and therapeutic target.
Tengfei Chen, Liu Qing, Xiangyu Chen et al.· Psychiatry Research· 0 citations
Astrocytic upregulation of HSP90AA1 is associated with altered synapse-related intercellular communication patterns in the PD substantia nigra, potentially involving a predicted TP53 associated regulatory component.
Yiyuan Xu, Yanfeng Shi, Yan Li et al.· International Journal of Mol...· 0 citations
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