Biomarkers For Autism Spectrum Disorder Research Articles

Large-scale metagenomic analysis of oral microbiomes reveals markers for autism spectrum disorders.

The link between the oral microbiome and neurodevelopmental disorders remains a compelling hypothesis, still requiring confirmation in large-scale datasets. Leveraging over 7000 whole-genome sequenced salivary samples from 2025 US families with children diagnosed with autism spectrum disorders (ASD), our cross-sectional study shows that the oral microbiome composition can discriminate ASD subjects from neurotypical siblings (NTs, AUC = 0.66), with 108 differentiating species (q < 0.005). The relative abundance of these species is highly correlated with cognitive impairment as measured by Full-Scale Intelligence Quotient (IQ). ASD children with IQ < 70 also exhibit lower microbiome strain sharing with parents (p < 10-6) with respect to NTs. A two-pronged functional enrichment analysis suggests the contribution of enzymes from the serotonin, GABA, and dopamine degradation pathways to the distinct microbial community compositions observed between ASD and NT samples. Although measures of restrictive eating diet and proxies of oral hygiene show relatively minor effects on the microbiome composition, the observed associations with ASD and IQ may still represent unaccounted-for underlying differences in lifestyleamong groups. While causal relationships could not be established, our study provides substantial support to the investigation of oral microbiome biomarkers in ASD.

Proteomics analysis of extracellular vesicles for biomarkers of autism spectrum disorder

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by symptoms that include social interaction deficits, language difficulties and restricted, repetitive behavior. Early intervention through medication and behavioral therapy can eliminate some ASD-related symptoms and significantly improve the life-quality of the affected individuals. Currently, the diagnosis of ASD is highly limited.MethodsTo investigate the feasibility of early diagnosis of ASD, we tested extracellular vesicles (EVs) proteins obtained from ASD cases. First, plasma EVs were isolated from healthy controls (HCs) and ASD individuals and were analyzed using proximity extension assay (PEA) technology to quantify 1,196 protein expression level. Second, machine learning analysis and bioinformatic approaches were applied to explore how a combination of EV proteins could serve as biomarkers for ASD diagnosis.ResultsNo significant differences in the EV morphology and EV size distribution between HCs and ASD were observed, but the EV number was slightly lower in ASD plasma. We identified the top five downregulated proteins in plasma EVs isolated from ASD individuals: WW domain-containing protein 2 (WWP2), Heat shock protein 27 (HSP27), C-type lectin domain family 1 member B (CLEC1B), Cluster of differentiation 40 (CD40), and folate receptor alpha (FRalpha). Machine learning analysis and correlation analysis support the idea that these five EV proteins can be potential biomarkers for ASD.ConclusionWe identified the top five downregulated proteins in ASD EVs and examined that a combination of EV proteins could serve as biomarkers for ASD diagnosis.

Elemental examination in blood and urine samples of Jordanian children with autism spectrum disorder

Autism Spectrum disorder (ASD) is one of the psychiatric disorders with unknown etiology, which possibly affects children in the first three years of their life. This case-control study was performed to explore the differences in concentrations of 9 elements: sodium (Na), aluminum (Al), potassium (K), calcium (Ca), vanadium (V), manganese (Mn), cobalt (Co), thorium (Th), and uranium (U) in whole blood and urine specimens of children with ASD, neurotypical children, and their mothers. The study investigates the associations between the elements, sex, and severity of ASD. Methods and Materials: The study rincluded 21 children with ASD and 19 age-sex-matched neurotypical children. Elemental analysis was carried out by inductively coupled plasma-mass spectroscopy (ICP-MS). The behaviors of ASD were assessed using the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM–5) and the Childhood Autism Rating Scale (CARS). The results indicated a significant increase of Al (198 ± 87, p= 0.05) and significant decrease of Ca (50 ± 3, p= 0.007) and Mn (10 ± 1, p= 0.004) in blood sample of ASD compared to the neurotypical group. In the urine sample, a significant decrease level appeared in Ca (41 ± 10, p=0.05) of ASD compared to neurotypical. The maternal samples showed no significant difference between ASD and neurotypical. The main finding of this study could help the specialist to diagnose and relieve symptoms of ASD. Thus, the heavy and trace elements analysis is a biomarker for ASD.

Correlation of biochemical markers and inflammatory cytokines in autism spectrum disorder (ASD)

IntroductionAutism Spectrum Disorder (ASD) is a disorder that severely affects neurodevelopment, and its underlying causes are not yet entirely understood. Research suggests that there may be a connection between the occurrence of ASD and changes in immune responses. This study aims to know if some biochemical and inflammatory cytokines are promising biomarkers for ASD and whether they are involved in the pathogenesis of ASD.MethodsThe serum levels of CRP, TNF-α, TGF-β, IL-1β, IL-10, 1 L-8, and IL-6 were measured in all of the patients (n = 22) and in the healthy (n = 12) children using ELISA method.ResultsThe serum concentrations of IL-10 and IL-8 were significantly lower in the ASD patients compared to the control group (p < 0.05) and there were not significant differences between CRP, TNF-α, TGF-β, IL-6 and IL-1β levels in two groups. There were positive correlations between CRP and IL-10, also CRP and IL-8, in ASD group. In contrast to the ASD patients, the correlations of IL-8, IL-10, and CRP were not significant in the control group.ConclusionIn conclusion, this study highlights the potential role of certain biochemical markers and inflammatory cytokines in ASD. Specifically, the lower levels of IL-10 and IL-8 in ASD patients, along with the significant correlations between CRP and these cytokines, suggest an altered immune response in individuals with ASD. These findings support the hypothesis that immune dysregulation may be involved in ASD pathogenesis. Further research is needed to explore these biomarkers and their mechanistic links to ASD, which could lead to improved diagnostics or therapeutic strategies.

Screening biomarkers for autism spectrum disorder using plasma proteomics combined with machine learning methods

Background and aimsAutism spectrum disorder (ASD) is a common neurodevelopmental disorder in children. Early intervention is effective. Investigation of novel blood biomarkers of ASD facilitates early detection and intervention. Materials and MethodsSequential window acquisition of all theoretical spectra-mass spectrometry (SWATH-MS)-based proteomics technology and 30 DSM-V defined ASD cases versus age- and sex-matched controls were initially evaluated, and candidate biomarkers were screened using machine learning methods. Candidate biomarkers were validated by targeted proteomics multiple reaction monitoring (MRM) analysis using an independent group of 30 ASD cases vs. controls. ResultsFifty-one differentially expressed proteins (DEPs) were identified by SWATH analysis. They were associated with the immune response, complements and coagulation cascade pathways, and apolipoprotein-related metabolic pathways. Machine learning analysis screened 10 proteins as biomarker combinations (TFRC, PPBP, APCS, ALDH1A1, CD5L, SPARC, FGG, SHBG, S100A9, and PF4V1). In the MRM analysis, four proteins (PPBP, APCS, FGG, and PF4V1) were significantly different between the groups, and their combination as a screening indicator showed high potential (AUC = 0.8087, 95 % confidence interval 0.6904–0.9252, p < 0.0001). ConclusionsOur study provides data that suggests that a few plasma proteins have potential use in screening for ASD.

Investigating brain–gut microbiota dynamics and inflammatory processes in an autistic-like rat model using MRI biomarkers during childhood and adolescence

Autism spectrum disorder (ASD) is characterized by social interaction deficits and repetitive behaviors. Recent research has linked that gut dysbiosis may contribute to ASD-like behaviors. However, the exact developmental time point at which gut microbiota alterations affect brain function and behavior in patients with ASD remains unclear. We hypothesized that ASD-related brain microstructural changes and gut dysbiosis induce metabolic dysregulation and proinflammatory responses, which collectively contribute to the social behavioral deficits observed in early childhood. We used an autistic-like rat model that was generated via prenatal valproic acid exposure. We analyzed brain microstructural changes using diffusion tensor imaging (DTI) and examined microbiota, blood, and fecal samples for inflammation biomarkers. The ASD model rats exhibited significant brain microstructural changes in the anterior cingulate cortex, hippocampus, striatum, and thalamus; reduced microbiota diversity (Prevotellaceae and Peptostreptococcaceae); and altered metabolic signatures. The shift in microbiota diversity and density observed at postnatal day (PND) 35, which is a critical developmental period, underscored the importance of early ASD interventions. We identified a unique metabolic signature in the ASD model, with elevated formate and reduced acetate and butyrate levels, indicating a dysregulation in short-chain fatty acid (SCFA) metabolism. Furthermore, increased astrocytic and microglial activation and elevated proinflammatory cytokines—interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α)—were observed, indicating immune dysregulation. This study provided insights into the complex interplay between the brain and the gut, and indicated DTI metrics as potential imaging-based biomarkers in ASD, thus emphasizing the need for early childhood interventions.

Biomarkers for autism spectrum disorder: a short review

Background: Autism Spectrum Disorder (ASD) is characterized by social disabilities and stereotyped behaviors. There is a relevant social impact on autistic people’s lives and, therefore, biomarkers have become relevant for understanding neurobiological mechanisms. Objective: This study aims to review current knowledge about the role of biomarkers and their main scientific evidence in autism. Methods: We performed a non-systematic literature review through the PubMed database, using the keywords “biomarkers”, “autism” and “autism spectrum disorder”. The search was restricted to articles written in English, in the last 10 years. Results: Analyzing the articles found, it is possible to delimit the biomarkers according to the development of ASD, from the prenatal period with exposure to diseases or association of autism with other genetic diseases, through the immune and nutritional factors exposed during pregnancy, and for end those associated with diagnoses phase in which there is the presence of symptoms in which these markers can be used to aid in the diagnosis. Conclusion: Although preliminary, biomarkers may hold promise for prenatal and presymptomatic screening. It may also be used as predictors of treatment for autism spectrum disorder.

Correction of Batch Effect in Gut Microbiota Profiling of ASD Cohorts from Different Geographical Origins.

To date, there have been numerous metataxonomic studies on gut microbiota (GM) profiling based on the analyses of data from public repositories. However, differences in study population and wet and dry pipelines have produced discordant results. Herein, we propose a biostatistical approach to remove these batch effects for the GM characterization in the case of autism spectrum disorders (ASDs). An original dataset of GM profiles from patients with ASD was ecologically characterized and compared with GM public digital profiles of age-matched neurotypical controls (NCs). Also, GM data from seven case-control studies on ASD were retrieved from the NCBI platform and exploited for analysis. Hence, on each dataset, conditional quantile regression (CQR) was performed to reduce the batch effects originating from both technical and geographical confounders affecting the GM-related data. This method was further applied to the whole dataset matrix, obtained by merging all datasets. The ASD GM markers were identified by the random forest (RF) model. We observed a different GM profile in patients with ASD compared with NC subjects. Moreover, a significant reduction of technical- and geographical-dependent batch effects in all datasets was achieved. We identified Bacteroides_H, Faecalibacterium, Gemmiger_A_73129, Blautia_A_141781, Bifidobacterium_388775, and Phocaeicola_A_858004 as robust GM bacterial biomarkers of ASD. Finally, our validation approach provided evidence of the validity of the QCR method, showing high values of accuracy, specificity, sensitivity, and AUC-ROC. Herein, we proposed an updated biostatistical approach to reduce the technical and geographical batch effects that may negatively affect the description of bacterial composition in microbiota studies.

Gestational exposure to organophosphate esters and autism spectrum disorder and other non-typical development in a cohort with elevated familial likelihood

BackgroundGestational exposure to organophosphate esters (OPEs) is known to affect offspring neurodevelopment in animal studies. However, epidemiological evidence is inconsistent. MethodsParticipants were 277 mother-child pairs from MARBLES (Markers of Autism Risk in Babies – Learning Early Signs), a cohort with elevated familial likelihood of autism spectrum disorder (ASD). Nine OPE biomarker concentrations were quantified in maternal urine collected during the 2nd or 3rd trimesters of pregnancy. At age 3 years, children underwent clinical assessment for ASD and were classified into ASD, other non-typical development (non-TD), or typical development (TD). Multinomial logistic regression was used to estimate associations between each OPE biomarker and relative risk ratios for ASD and non-TD compared to TD. We examined effect modification by child sex and socioeconomic status. We also conducted a secondary analysis by using a continuous measure of ASD symptom severity as an outcome. Quantile-based g-computation was performed to examine the associations for an OPE mixture. ResultsOverall, no significant association was observed between the concentrations of each OPE biomarker or their mixture and relative risk for either ASD or non-TD. Effect modifications by child sex and maternal education were not observed. When the analysis was stratified by homeownership, among non-homeowners, ASD likelihood was increased with increased levels of bis(1-chloro-2-propyl) phosphate, bis(butoxyethyl) phosphate, and sum of di-n-butyl phosphate and di-iso-butyl phosphate (DBUP/DIBP) (pint < 0.10). Higher DBUP/DIBP were associated with increased ASD symptom severity scores. ConclusionThere was no clear evidence of gestational OPE exposure in association with relative risk for ASD; however, potential effect modification by homeownership was observed. Although our cohort includes children with elevated familial likelihood of ASD, this is the first study investigating the association between gestational OPE exposure and clinically-diagnosed ASD. Further research is needed to confirm our findings in the general population.

Turicibacter and Catenibacterium as potential biomarkers in autism spectrum disorders.

Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by social, behavioral, and cognitive impairments. Several comorbidities, including gastrointestinal (GI) dysregulations, are frequently reported in ASD children. Although studies in animals have shown the crucial role of the microbiota in key aspects of neurodevelopment, there is currently no consensus on how the alteration of microbial composition affects the pathogenesis of ASD. Moreover, disruption of the gut-brain axis (GBA) has been reported in ASD although with limited studies conducted on the Mediterranean population. In our study, we aimed to investigate gut microbiota composition in Lebanese ASD subjects, their unaffected siblings, and a control group from various regions in Lebanon using the 16S-rRNA sequencing (NGS). Our study revealed a lower abundance of Turicibacter and a significant enrichment on Proteobacteria in the ASD and siblings' groups compared to the controls, indicating that gut microbiota is probably affected by dietary habits, living conditions together with host genetic factors. The study also showed evidence of changes in the gut microbiome of ASD children compared to their siblings and the unrelated control. Bacteroidetes revealed a lower abundance in the ASD group compared to controls and siblings, conversely, Catenibacterium and Tenericutes revealed an increased abundance in the ASD group. Notably, our study identifies alterations in the abundance of Turicibacter and Catenibacterium in ASD children suggesting a possible link between these bacterial taxa and ASD and contributing to the growing body of evidence linking the microbiome to ASD.

Biomarkers and pathways in autism spectrum disorder: An individual meta-analysis based on proteomic and metabolomic data.

The utilization of biomarkers for the diagnosis and management of autism spectrum disorders (ASD) remains a relatively unexplored frontier in clinical practice. Proteomics and metabolomics are important tools for revealing key biomarkers and evaluating biological pathways in ASD. We conducted an individual meta-analysis to compare the consistency of biomarkers of ASD from central nervous system (brain and cerebrospinal fluid), circulatory system (blood), and non-invasive samples (urine, saliva, and faeces) and performed pathway enrichment analyses to identify pathways enriched in ASD. After screening 926 proteomics and 619 metabolomics articles, we collected data from 10 studies involving 940 differential proteins and 16 studies assessing a total of 748 differential metabolites. In brain tissue, blood, and urine of ASD cases and controls, flotillin-2 (FLOT2), apolipoprotein E (ApoE), and EH domain-containing protein 3 (EHD3) exhibit differential expression, while vinculin (VCL) displays variations in saliva, blood, and urine. Similarly, in case-control studies, gelsolin (GSN) shows differential expression in brain tissue, saliva, and urine, and malate dehydrogenase 2 (MDH2) in brain tissue, blood, and saliva. Hippuric acid and salicyluric acid were simultaneously found in the brain, blood, urine, and faeces. In terms of pathways, glycolysis/gluconeogenesis, carbon metabolism, and glutathione metabolism were enriched in the brain as well as in saliva or urine. In our study, we identified six shared protein and two metabolic markers in central nervous system, circulatory system, and non-invasive samples, underscoring their potential value for ASD diagnosis and management, warranting further research.

Autism spectrum disorder: difficulties in diagnosis and microRNA biomarkers.

We performed a PubMed search for microRNAs in autism spectrum disorder that could serve as diagnostic biomarkers in patients and selected 17 articles published from January 2008 to December 2023, of which 4 studies were performed with whole blood, 4 with blood plasma, 5 with blood serum, 1 with serum neural cell adhesion molecule L1-captured extracellular vesicles, 1 with blood cells, and 2 with peripheral blood mononuclear cells. Most of the studies involved children and the study cohorts were largely males. Many of the studies had performed microRNA sequencing or quantitative polymerase chain reaction assays to measure microRNA expression. Only five studies had used real-time polymerase chain reaction assay to validate microRNA expression in autism spectrum disorder subjects compared to controls. The microRNAs that were validated in these studies may be considered as potential candidate biomarkers for autism spectrum disorder and include miR-500a-5p, -197-5p, -424-5p, -664a-3p, -365a-3p, -619-5p, -664a- 3p, -3135a, -328-3p, and -500a-5p in blood plasma and miR-151a-3p, -181b-5p, -320a, -328, -433, -489, -572, -663a, -101-3p, -106b-5p, -19b-3p, -195-5p, and -130a-3p in blood serum of children, and miR-15b-5p and -6126 in whole blood of adults. Several important limitations were identified in the studies reviewed, and need to be taken into account in future studies. Further studies are warranted with children and adults having different levels of autism spectrum disorder severity and consideration should be given to using animal models of autism spectrum disorder to investigate the effects of suppressing or overexpressing specific microRNAs as a novel therapy.

Specific EEG resting state biomarkers in FXS and ASD

BackgroundFragile X syndrome (FXS) and autism spectrum disorder (ASD) are neurodevelopmental conditions that often have a substantial impact on daily functioning and quality of life. FXS is the most common cause of inherited intellectual disability (ID) and the most common monogenetic cause of ASD. Previous literature has shown that electrophysiological activity measured by electroencephalogram (EEG) during resting state is perturbated in FXS and ASD. However, whether electrophysiological profiles of participants with FXS and ASD are similar remains unclear. The aim of this study was to compare EEG alterations found in these two clinical populations presenting varying degrees of cognitive and behavioral impairments.MethodsResting state EEG signal complexity, alpha peak frequency (APF) and power spectral density (PSD) were compared between 47 participants with FXS (aged between 5–20), 49 participants with ASD (aged between 6–17), and 52 neurotypical (NT) controls with a similar age distribution using MANCOVAs with age as covariate when appropriate. MANCOVAs controlling for age, when appropriate, and nonverbal intelligence quotient (NVIQ) score were subsequently performed to determine the impact of cognitive functioning on EEG alterations.ResultsOur results showed that FXS participants manifested decreased signal complexity and APF compared to ASD participants and NT controls, as well as altered power in the theta, alpha and low gamma frequency bands. ASD participants showed exaggerated beta power compared to FXS participants and NT controls, as well as enhanced low and high gamma power compared to NT controls. However, ASD participants did not manifest altered signal complexity or APF. Furthermore, when controlling for NVIQ, results of decreased complexity in higher scales and lower APF in FXS participants compared to NT controls and ASD participants were not replicated.ConclusionsThese findings suggest that signal complexity and APF might reflect cognitive functioning, while altered power in the low gamma frequency band might be associated with neurodevelopmental conditions, particularly FXS and ASD.

Delving into the Complexity of Valproate-Induced Autism Spectrum Disorder: The Use of Zebrafish Models.

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition with several identified risk factors, both genetic and non-genetic. Among these, prenatal exposure to valproic acid (VPA) has been extensively associated with the development of the disorder. The zebrafish, a cost- and time-effective model, is useful for studying ASD features. Using validated VPA-induced ASD zebrafish models, we aimed to provide new insights into VPA exposure effects during embryonic development and to identify new potential biomarkers associated with ASD-like features. Dose-response analyses were performed in vivo to study larval phenotypes and mechanisms underlying neuroinflammation, mitochondrial dysfunction, oxidative stress, microglial cell status, and motor behaviour. Wild-type and transgenic Tg(mpeg1:EGFP) zebrafish were water-exposed to VPA doses (5 to 500 µM) from 6 to 120 h post-fertilisation (hpf). Embryos and larvae were monitored daily to assess survival and hatching rates, and numerous analyses and tests were conducted from 24 to 120 hpf. VPA doses higher than 50 µM worsened survival and hatching rates, while doses of 25 µM or more altered morphology, microglial status, and larval behaviours. VPA 50 µM also affected mRNA expression of inflammatory cytokines and neurogenesis-related genes, mitochondrial respiration, and reactive oxygen species accumulation. The study confirmed that VPA alters brain homeostasis, synaptic interconnections, and neurogenesis-related signalling pathways, contributing to ASD aetiopathogenesis. Further studies are essential to identify novel ASD biomarkers for developing new drug targets and tailored therapeutic interventions for ASD.

Face processing in animal models: implications for autism spectrum disorder.

Processing facial features is crucial to identify social partners (prey, predators, or conspecifics) and recognize and accurately interpret emotional expressions. Numerous studies in both human and non-human primates provided evidence promoting the notion of inherent mechanisms for detecting facial features. These mechanisms support a representation of faces independent of prior experiences and are vital for subsequent development in social and language domains. Moreover, deficits in processing faces are a reliable biomarker of autism spectrum disorder, appearing early and correlating with symptom severity. Face processing, however, is not only a prerogative of humans: other species also show remarkable face detection abilities. In this review, we present an overview of the current literature on face detection in vertebrate models that could be relevant to the study of autism.

Assessing the COX-2/PGE2 Ratio and Anti-Nucleosome Autoantibodies as Biomarkers of Autism Spectrum Disorders: Using Combined ROC Curves to Improve Diagnostic Values.

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by restricted and repetitive behaviors as well as difficulties with social interaction. Numerous studies have revealed aberrant lipid mediators and autoimmunity as a recognized etiological cause of ASD that is amenable to therapeutic intervention. In this study, the relationship between the relative cyclooxygenase-2/prostaglandin E2 ratio (COX-2/PGE2) as a lipid mediator marker and anti-nucleosome autoantibodies as an autoimmunity marker of ASD was investigated using multiple regression and combined receiver operating characteristic (ROC) curve analyses. The study also sought to identify the linear combination of these variables that optimizes the partial area under the ROC curves. There were forty ASD children and forty-two age- and gender-matched controls included in the current study. Using combined ROC curve analysis, a notable increase in the area under the curve was seen in the patient group, using the control group as a reference group. Additionally, it was reported that the combined markers had improved specificity and sensitivity. This study demonstrates how the predictive value of particular biomarkers associated with lipid metabolism and autoimmunity in children with ASD can be measured using a ROC curve analysis. This technique should help us better understand the etiological mechanism of ASD and how it may adversely affect cellular homeostasis, which is essential to maintaining healthy metabolic pathways. Early diagnosis and intervention may be facilitated by this knowledge.

Visual and auditory attention in individuals with DYRK1A and SCN2A disruptive variants.

This preliminary study sought to assess biomarkers of attention using electroencephalography (EEG) and eye tracking in two ultra-rare monogenic populations associated with autism spectrum disorder (ASD). Relative to idiopathic ASD (n = 12) and neurotypical comparison (n = 49) groups, divergent attention profiles were observed for the monogenic groups, such that individuals with DYRK1A (n = 9) exhibited diminished auditory attention condition differences during an oddball EEG paradigm whereas individuals with SCN2A (n = 5) exhibited diminished visual attention condition differences noted by eye gaze tracking when viewing social interactions. Findings provide initial support for alignment of auditory and visual attention markers in idiopathic ASD and neurotypical development but not monogenic groups. These results support ongoing efforts to develop translational ASD biomarkers within the attention domain.

Epigenetic Insights into Autism Spectrum Disorder: DNA Methylation Levels of NR3C1, ASCL1, and FOXO3 in Korean Autism Spectrum Disorder Sibling Pairs.

Previous research on autism spectrum disorder (ASD) in Koreans has primarily focused on genetic diversity because of its high heritability. However, the emerging recognition of transgenerational epigenetic changes has recently shifted research attention towards epigenetic perspectives. This study investigated the DNA methylation patterns of the promoter regions of candidate genes such as NR3C1, ASCL1, and FOXO3 in blood samples from ASD probands and their unaffected siblings. The analysis included 54 families (ASD proband group: 54; unaffected biological sibling group: 63). The diagnostic process involved screening the probands and their siblings for ASD based on the Diagnostic and Statistical Manual of Mental Disorders 5th edition. Intelligence, social ability, and medical history were thoroughly assessed using various scales and questionnaires. Genomic DNA from blood samples was analyzed using a methylation-sensitive quantitative polymerase chain reaction to examine the DNA methylation status of candidate genes. Methylation levels in candidate gene promoter regions differed significantly between the proband and sibling groups for all candidate genes. Correlation analysis between the proband and sibling groups revealed strong and significant correlations in NR3C1 and ASCL1 methylation. Additionally, in the analysis of the relationship between DNA and ASD phenotypes, FOXO3 methylation correlated with social quotient in probands, and ASCL1 methylation was associated with nonverbal communication, and daily living skills as measured by the Korean Vineland Adaptive Behavior Scale. Notably, ASCL1 methylation was significantly associated with parental age at pregnancy. This study proposes DNA methylation of NR3C1, ASCL1, and FOXO3 in peripheral blood samples is a potential epigenetic biomarker of ASD.

Transcriptomic Analysis Reveals Sex-Based Differences in The Prefrontal Cortex of Autism Spectrum Disorder Patients.

The prevalence of neurological disorders often varies by sex, with conditions such as Alzheimer's disease and autism spectrum disorder (ASD) demonstrating notable differences in incidence. The aim of this study is to understand the molecular basis for these divergences in order to facilitate the creation of sex-specific therapeutic strategies. This study is a bioinformatic analysis of publicly available RNA sequencing datasets involving autism patients. The study utilized RNA sequencing data from postmortem human brains' prefrontal cortex, including 38 neurotypical controls and 34 individuals with ASD. The sequencing data was obtained from previously published papers, and we downloaded the raw data from SRA. We investigated the molecular basis of sex-biased presentation in ASD through comprehensive transcriptomic analysis. Comparative analysis of gene expression between male and female subjects, both autistic and unaffected, was conducted, using a significance level of ≤0.01. In autistic individuals, 136 genes demonstrated differential expression between sexes, predominantly upregulated in males, indicating a bias in male gene expression. Among these, 12 genes were identified as risk factors in the SFARI dataset. While most sex-biased genes were autosomal, expression differences on sex chromosomes were also observed in neurotypical subjects. Notable genes included TCF7L2, collagen family genes, and solute carrier family genes. In ASD males, extracellular matrix (ECM) organization emerged as a significant pathway, while immune-related processes were prominent in unaffected individuals. Our study highlights the impact of the ECM pathway in ASD, with notable differences between sexes, particularly in males. MIR424 shows promise as a potential biomarker for ASD in males. Recognizing the importance of sex differences in ASD transcriptomic research is crucial, as these variances provide insights into the disorder's pathophysiology and may guide the development of more personalized treatments for both sexes.

Erroneous predictive coding across brain hierarchies in a non-human primate model of autism spectrum disorder

In autism spectrum disorder (ASD), atypical sensory experiences are often associated with irregularities in predictive coding, which proposes that the brain creates hierarchical sensory models via a bidirectional process of predictions and prediction errors. However, it remains unclear how these irregularities manifest across different functional hierarchies in the brain. To address this, we study a marmoset model of ASD induced by valproic acid (VPA) treatment. We record high-density electrocorticography (ECoG) during an auditory task with two layers of temporal control, and applied a quantitative model to quantify the integrity of predictive coding across two distinct hierarchies. Our results demonstrate a persistent pattern of sensory hypersensitivity and unstable predictions across two brain hierarchies in VPA-treated animals, and reveal the associated spatio-spectro-temporal neural signatures. Despite the regular occurrence of imprecise predictions in VPA-treated animals, we observe diverse configurations of underestimation or overestimation of sensory regularities within the hierarchies. Our results demonstrate the coexistence of the two primary Bayesian accounts of ASD: overly-precise sensory observations and weak prior beliefs, and offer a potential multi-layered biomarker for ASD, which could enhance our understanding of its diverse symptoms.