Gene Signalling Pathways, Putative Biomarkers and Hypothetical Modulation in Autism Spectrum Disorders

GENETIC AND MOLECULAR MECHANISMS IN PEDIATRIC NEUROLOGICAL DISORDERS: A SYSTEMATIC REVIEW

The study provides an integrated framework linking genetic variation to molecular dysfunction and clinical outcomes, offering valuable insights for future research and therapeutic development in pediatric neurology.

Shared molecular dysregulation across neuropsychiatric disorders reveals candidate therapeutic targets.

An integrated systems biology and machine learning framework for identifying potential biomarkers and pathways in autism spectrum disorder

Background Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders whose underlying molecular mechanisms and biological processes remain incompletely understood. In this study, we used a multi-layered systems biology approach to prioritize candidate genes and regulatory factors associated with ASD. Method Gene expression data from peripheral blood samples were obtained from the Gene Expression Omnibus (GEO) database (GSE18123). Using analyses performed in R software, differentially expressed genes (DEGs) in patients with ASD were identified (p-value < 0.05 and |log2FC| > 0.5). These DEGs were used to perform weighted gene co-expression network analysis (WGCNA) and construct a protein–protein interaction (PPI) network. By integrating the results of these network analyses with feature selection techniques (LASSO and random forest feature importance), candidate genes associated with ASD were prioritized and evaluated using qRT-PCR in the valproic acid (VPA)-induced rat model of autism. Furthermore, a gene regulatory network (GRN) was constructed to identify the regulatory factors associated with DEGs. Result TLR8 and CASP4 were prioritized as candidate genes that may be associated with ASD, because they were located within the co-expression module that showed the strongest correlation with ASD, were identified as key nodes of the PPI network, and were selected by feature selection algorithms. Our experimental validation showed increased expression of TLR8 and CASP4 in the autism model compared with controls; TLR8 was upregulated in both the hippocampus and peripheral blood, whereas CASP4 was upregulated only in the hippocampus. Furthermore, GRN analysis identified miR-891b and miR-627-3p as potential regulators of TLR8, and miR-26b-5p as associated with CASP4. Conclusion These 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.

Exploring shared genetic pathways and gene interplay in major neurodegenerative diseases: a comprehensive review.

Neurodegenerative diseases are progressive disorders that involve the loss and dysfunction of neurons. Alzheimer's disease, Parkinson's disease, Amyotrophic lateral sclerosis, Huntington's disease, Frontotemporal dementia are examples of diseases. While different clinically, these disorders have a common genetic, molecular and cellular basis. This review examines the common genetic pathways, along with the interactions between genes of major neurodegenerative diseases, with a focus on the key genes, such as APOE, SNCA, MAPT, TARDBP, LRRK2 and HTT. The common pathogenic mechanisms considered to play a major role in disease progression include protein misfolding and aggregation, mitochondrial dysfunction, oxidative stress, neuroinflammation, diminished autophagy, and impaired lysosomal function, as well as synaptic degeneration. The review also emphasizes the role of systems biology strategies, such as genome-wide association studies, transcriptomics, proteomics, metabolomics, interactome analysis, and multi-omics integration, to unveiling complex molecular networks in neurodegeneration. Furthermore, the emerging biomarker strategies and therapeutic strategies targeting convergence signaling pathways including NF-κB, PI3K-Akt-mTOR, MAPK and Wnt/β-catenin are summarized. The common genetic basis and the cross-connecting molecular mechanisms of the various neurodegenerative diseases could help in the discovery of new biomarkers and pan-therapeutic targets. Further advances in molecular genetics, computational biology and precision medicine are needed to enhance early detection and the creation of effective disease-modifying treatments.

Multi-Omic Analysis of Cerebrospinal Fluid Metabolites in Autism Spectrum Disorder: Biomarker Identification, Metabolic Genetics Insights, and Network Toxicology

Background: Although genetic-environmental interactions are established in autism spectrum disorder (ASD), how environmental toxicants confer susceptibility remains unclear. This study aimed to investigate potential relationship between genetically predicted cerebrospinal fluid (CSF), metabolite levels and ASD liability, and to prioritize regulatory genes, key pathways, and candidate environmental toxicants. Methods: Using two ASD GWAS datasets (exploration data: 18,381 ASD cases/27,969 controls; validation data: 18,235 ASD cases/36,741 controls), we applied multi-omics approaches to prioritize ASD-associated CSF metabolites, regulatory SNPs, and genes. Enrichment analysis and protein–protein interaction (PPI) network analysis were performed on these metabolite-related genes to explore the potential mechanisms linking CSF metabolic disturbances to ASD. Finally, candidate environmental neurotoxicants were screened through protein-chemical interaction analysis, with binding relationships assessed via molecular docking prediction. Results: Two-sample Mendelian randomization (MR) analysis prioritized adenine and proline as candidate CSF metabolites with potential risk associations with ASD. Summary-data-based MR (SMR) prioritized 39 brain-specific quantitative trait loci (QTL) involving 35 candidate regulatory genes, including dual-metabolite modulator GRM8. Functional enrichment analyses suggested potential associations with mitochondrial dysfunction, Hippo signaling pathway, and microtubule dynamics impairment, with protein–protein interaction networks highlighting KATNA1/KATNAL2 as hubs. Protein-chemical interaction screening nominated 14 candidate environmental toxicants, including established chemicals (acetaminophen, valproic acid, estradiol) and novel candidates (SB-431542, K 7174, benzo[a]pyrene), with docking affinity assessed computationally. Conclusions: Our study provides suggestive evidence that elevated adenine and proline may be potential risk factors for ASD and suggests possible involvement of the mitochondrial–Hippo–microtubule pathway. We also propose benzo[a]pyrene as a candidate environmental toxicant that may perturb CSF metabolism. However, given the limited statistical significance, these findings require further validation.

The Microbiota–Gut–Brain Axis in Autism Spectrum Disorder: From Pathophysiological Mechanisms to Precision Therapeutics, A Comprehensive Review

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by persistent social communication deficits and restricted, repetitive behaviors. Gastrointestinal symptoms are common and often correlate with symptom severity, implicating the microbiota–gut–brain axis as a potential mechanism linking gut dysbiosis with neurodevelopment through neural, immune, endocrine, and metabolic pathways. This review summarizes current evidence on alterations in the gut microbiota in ASD and critically examines whether these changes contribute to disease pathogenesis or represent secondary effects. It highlights recent advances in multi-kingdom microbiome profiling, metabolomics, mechanistic studies of neuroinflammation, and neurotransmitter signaling and considers major confounding factors, including diet, medication, and gastrointestinal comorbidities. Emerging studies emphasize microbial function over taxonomy. In the largest multi-kingdom analysis, 31 microbial and functional markers distinguished children with ASD from neurotypical controls with an area under the curve of 0.91, driven primarily by ubiquinol-7 and thiamine diphosphate biosynthesis pathways rather than individual taxa. Metabolomic and genetic studies suggest that microbial metabolites may mediate behavioral effects. Microbiota transfer therapy and fecal microbiota transplantation have demonstrated sustained improvements in gastrointestinal and behavioral outcomes, whereas probiotics and dietary interventions have produced inconsistent results. Although alterations in the gut microbiome are consistently observed in ASD, specific microbial signatures remain heterogeneous, and causality remains unproven. Functional microbial pathways appear more informative than taxonomic composition for biomarker discovery and therapeutic development. Future progress requires prospective birth cohorts, pre-diagnostic sampling, mechanistic validation, and adequately powered randomized trials before microbiome-based diagnostics and therapies can be translated into clinical practice.