This 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, and proposes benzo[a]pyrene as a candidate environmental toxicant that may perturb CSF metabolism.
Abstract
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.
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.
Sara Hosseinpoor, H. Zali, Hassan Zohrevand et al.· PLoS ONE· 0 citations
Summary Early-onset schizophrenia (EOS) is a severe psychiatric disorder characterized by strong genetic contribution and metabolic alterations, including lipid dysregulation. To investigate the relationship between genetic variation and metabolic changes in EOS, we performed whole-exome sequencing and serum metabolome profiling in 28 patients with EOS and 20 healthy controls. We identified 114 high-risk genes and 117 differentially expressed metabolites. Of the risk genes with variants in multiple patients, 54.35% (25/46) were associated with clinical symptoms, and of the differentially expressed lipids, 34.88% (15/43) were correlated with clinical symptoms. By integrating protein-metabolite interactions and metabolite correlations, we constructed a gene-metabolite network and identified 19 high-risk genes linking to 31 dysregulated lipids. Twenty of these lipids were significantly down-regulated in patients, with 80% (16/20) showing further down-regulation in variant carriers. Our findings provide compelling evidence for a genetic-metabolic interaction in EOS pathogenesis and point to an alternative disease mechanism of schizophrenia.
Xiaoxue Yang, Wenjun Yu, Hong-Xu Pan et al.· iScience· 0 citations
An atlas of brain IDPs associated with bipolar disorder is established, by integrating epidemiological and genetic evidence, and candidate IDPs that were consistently associated with BD are highlighted across complementary analyses.
Wenzhuo Yang, Lin Pan, Haoqun Xie et al.· BMC Medicine· 0 citations
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.
Autism spectrum disorder (ASD) is a neurodevelopmental condition associated with metabolic and environmental factors. We investigated associations between urinary tryptophan-pathway metabolites and essential/toxic trace elements in children with ASD and healthy controls. In a cross-sectional cohort of 216 children (149 ASD, 67 controls), urinary tryptophan metabolites were quantified by LC-MS/MS and normalized to creatinine. Trace elements were assessed by ICP-MS. Matching yielded 1:1 (n = 57/57) and 1:2 (n = 30/60) age- and sex-matched subsets. Correlations (Pearson or Spearman, FDR-adjusted) and group comparisons were performed; autism severity (CARS) was analyzed within ASD. Creatinine-normalized tryptamine, 5-hydroxyindoleacetic acid, and N-acetyltryptophan showed moderate, positive correlations with essential elements (Mg, Zn, Se; r ≈ 0.5-0.7; N-acetyltryptophan and IAA correlated modestly with toxic elements (Tl, Cs; r ≈ 0.3-0.4). Group differences in individual metabolites and elements were modest; however, the composite toxic element index was significantly lower in ASD (P = .002). CARS scores did not show robust, FDR-corrected associations. Essential trace elements are closely linked to tryptophan metabolism, suggesting cofactor-dependent modulation in ASD. N-acetyltryptophan may serve as a sensor for specific toxic elements. Intervention studies are warranted to clarify causality.
Jusko Osredkar, Kristina Kumer, Maja Jekovec Vrhovšek et al.· International Journal of Try...· 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, L. Papale et al.· Molecular Psychiatry· 0 citations
