Advances in Biomarker Studies in Autism Spectrum Disorders

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD. We provided an overview of the ASD molecular mechanisms identified by multi-omics studies and convergent mechanism in different genetic backgrounds. The comorbidities, mechanisms associated with important physiological and metabolic abnormalities (i.e., inflammation, immunity, oxidative stress, and mitochondrial dysfunction), and gut microbial disorder in ASD were reviewed. The non-targeted omics and targeting studies of diagnostic markers for ASD were also reviewed. Moreover, we summarized the progress and methods of behavioral and educational interventions, intervention methods related to technological devices, and research on medical interventions and potential drug targets. This review highlighted the application of high-throughput omics methods in ASD research and emphasized the importance of seeking homogeneity from heterogeneity and exploring the convergence of disease mechanisms, biomarkers, and intervention approaches, and proposes that taking into account individuality and commonality may be the key to achieve accurate diagnosis and treatment of ASD.

A comparison between children and adolescents with autism spectrum disorders and healthy controls in biomedical factors, trace elements, and microbiota biomarkers: a meta-analysis

Introduction

Autism spectrum disorder (ASD) is a multifaceted developmental condition that commonly appears during early childhood. The etiology of ASD remains multifactorial and not yet fully understood. The identification of biomarkers may provide insights into the underlying mechanisms and pathophysiology of the disorder. The present study aimed to explore the causes of ASD by investigating the key biomedical markers, trace elements, and microbiota factors between children with autism spectrum disorder (ASD) and control subjects.

Methods

Medline, PubMed, ProQuest, EMBASE, Cochrane Library, PsycINFO, Web of Science, and EMBSCO databases have been searched for publications from 2012 to 2023 with no language restrictions using the population, intervention, control, and outcome (PICO) approach. Keywords including "autism spectrum disorder," "oxytocin," "GABA," "Serotonin," "CRP," "IL-6," "Fe," "Zn," "Cu," and "gut microbiota" were used for the search. The Joanna Briggs Institute (JBI) critical appraisal checklist was used to assess the article quality, and a random model was used to assess the mean difference and standardized difference between ASD and the control group in all biomedical markers, trace elements, and microbiota factors.

Results

From 76,217 records, 43 studies met the inclusion and exclusion criteria and were included in this meta-analysis. The pooled analyses showed that children with ASD had significantly lower levels of oxytocin (mean differences, MD = -45.691, 95% confidence interval, CI: -61.667, -29.717), iron (MD = -3.203, 95% CI: -4.891, -1.514), and zinc (MD = -6.707, 95% CI: -12.691, -0.722), lower relative abundance of Bifidobacterium (MD = -1.321, 95% CI: -2.403, -0.238) and Parabacteroides (MD = -0.081, 95% CI: -0.148, -0.013), higher levels of c-reactive protein, CRP (MD = 0.401, 95% CI: 0.036, 0.772), and GABA (MD = 0.115, 95% CI: 0.045, 0.186), and higher relative abundance of Bacteroides (MD = 1.386, 95% CI: 0.717, 2.055) and Clostridium (MD = 0.281, 95% CI: 0.035, 0.526) when compared with controls. The results of the overall analyses were stable after performing the sensitivity analyses. Additionally, no substantial publication bias was observed among the studies.

Interpretation

Children with ASD have significantly higher levels of CRP and GABA, lower levels of oxytocin, iron, and zinc, lower relative abundance of Bifidobacterium and Parabacteroides, and higher relative abundance of Faecalibacterium, Bacteroides, and Clostridium when compared with controls. These results suggest that these indicators may be a potential biomarker panel for the diagnosis or determining therapeutic targets of ASD. Furthermore, large, sample-based, and randomized controlled trials are needed to confirm these results.

A Systematic Investigation of Complement and Coagulation-Related Protein in Autism Spectrum Disorder Using Multiple Reaction Monitoring Technology

Autism spectrum disorder (ASD) is one of the common neurodevelopmental disorders in children. Its etiology and pathogenesis are poorly understood. Previous studies have suggested potential changes in the complement and coagulation pathways in individuals with ASD. In this study, using multiple reactions monitoring proteomic technology, 16 of the 33 proteins involved in this pathway were identified as differentially-expressed proteins in plasma between children with ASD and controls. Among them, CFHR3, C4BPB, C4BPA, CFH, C9, SERPIND1, C8A, F9, and F11 were found to be altered in the plasma of children with ASD for the first time. SERPIND1 expression was positively correlated with the CARS score. Using the machine learning method, we obtained a panel composed of 12 differentially-expressed proteins with diagnostic potential for ASD. We also reviewed the proteins changed in this pathway in the brain and blood of patients with ASD. The complement and coagulation pathways may be activated in the peripheral blood of children with ASD and play a key role in the pathogenesis of ASD.

Poly (ADP-Ribose) polymerase 1 and parthanatos in neurological diseases: From pathogenesis to therapeutic opportunities

Poly (ADP-ribose) polymerase-1 (PARP-1) is the most extensively studied member of the PARP superfamily, with its primary function being the facilitation of DNA damage repair processes. Parthanatos is a type of regulated cell death cascade initiated by PARP-1 hyperactivation, which involves multiple subroutines, including the accumulation of ADP-ribose polymers (PAR), binding of PAR and apoptosis-inducing factor (AIF), release of AIF from the mitochondria, the translocation of the AIF/macrophage migration inhibitory factor (MIF) complex, and massive MIF-mediated DNA fragmentation. Over the past few decades, the role of PARP-1 in central nervous system health and disease has received increasing attention. In this review, we discuss the biological functions of PARP-1 in neural cell proliferation and differentiation, memory formation, brain ageing, and epigenetic regulation. We then elaborate on the involvement of PARP-1 and PARP-1-dependant parthanatos in various neuropathological processes, such as oxidative stress, neuroinflammation, mitochondrial dysfunction, excitotoxicity, autophagy damage, and endoplasmic reticulum (ER) stress. Additional highlight contains PARP-1's implications in the initiation, progression, and therapeutic opportunities for different neurological illnesses, including neurodegenerative diseases, stroke, autism spectrum disorder (ASD), multiple sclerosis (MS), epilepsy, and neuropathic pain (NP). Finally, emerging insights into the repurposing of PARP inhibitors for the management of neurological diseases are provided. This review aims to summarize the exciting advancements in the critical role of PARP-1 in neurological disorders, which may open new avenues for therapeutic options targeting PARP-1 or parthanatos.

A study of genetic heterogeneity in autism spectrum disorders based on plasma proteomic and metabolomic analysis: multiomics study of autism heterogeneity

Genetic heterogeneity poses a challenge to research and clinical translation of autism spectrum disorder (ASD). In this study, we conducted a plasma proteomic and metabolomic study of children with ASD with and without risk genes (de novo mutation) and controls to explore the impact of genetic heterogeneity on the search for biomarkers for ASD. In terms of the proteomic and metabolomic profiles, the groups of children with ASD carrying and those not carrying de novo mutation tended to cluster and overlap, and integrating them yielded differentially expressed proteins and differential metabolites that effectively distinguished ASD from controls. The mechanisms associated with them focus on several common and previously reported mechanisms. Proteomics results highlight the role of complement, inflammation and immunity, and cell adhesion. The main pathways of metabolic perturbations include amino acid, vitamin, glycerophospholipid, tryptophan, and glutamates metabolic pathways and solute carriers-related pathways. Integrating the two omics analyses revealed that L-glutamic acid and malate dehydrogenase may play key roles in the pathogenesis of ASD. These results suggest that children with ASD may have important underlying common mechanisms. They are not only potential therapeutic targets for ASD but also important contributors to the study of biomarkers for the disease.

Neurometabolite levels in the brains of patients with autism spectrum disorders: A meta-analysis of proton magnetic resonance spectroscopy studies (N = 1501)

Evidence suggests that neurometabolite alterations may be involved in the pathophysiology of autism spectrum disorders (ASDs). We performed a meta-analysis of proton magnetic resonance spectroscopy (1H-MRS) studies to examine the neurometabolite levels in the brains of patients with ASD. A systematic search of PubMed and Web of Science identified 54 studies for the meta-analysis. A random-effects meta-analysis demonstrated that compared with the healthy controls, patients with ASD had lower N-acetyl-aspartate-containing compound (NAA) and choline-containing compound (Cho) levels and NAA/(creatine-containing compound) Cr ratios in the gray matter and lower NAA and glutamate + glutamine (Glx) levels in the white matter. Furthermore, NAA and gamma-aminobutyric acid (GABA) levels, NAA/Cr ratios, and GABA/Cr ratios were significantly decreased in the frontal cortex of patients with ASD, whereas glutamate (Glu) levels were increased in the prefrontal cortex. Additionally, low NAA levels and GABA/Cr ratios in the temporal cortex, low NAA levels and NAA/Cr ratios in the parietal and dorsolateral prefrontal cortices, and low NAA levels in the cerebellum and occipital cortex were observed in patients with ASD. Meta-regression analysis revealed that age was positively associated with effect size in studies analyzing the levels of gray matter NAA and white matter Glx. Taken together, these results provide strong clinical evidence that neurometabolite alterations in specific brain regions are associated with ASD and age is a confounding factor for certain neurometabolite levels in patients with ASD.

A Potential Biomarker of Brain Activity in Autism Spectrum Disorders: A Pilot fNIRS Study in Female Preschoolers

Autism spectrum disorder (ASD) refers to a neurodevelopmental condition whose detection still remains challenging in young females due to the heterogeneity of the behavioral phenotype and the capacity of camouflage. The availability of quantitative biomarkers to assess brain function may support in the assessment of ASD. Functional Near-infrared Spectroscopy (fNIRS) is a non-invasive and flexible tool that quantifies cortical hemodynamic responses (HDR) that can be easily employed to describe brain activity. Since the study of the visual phenotype is a paradigmatic model to evaluate cerebral processing in many neurodevelopmental conditions, we hypothesized that visually-evoked HDR (vHDR) might represent a potential biomarker in ASD females. We performed a case-control study comparing vHDR in a cohort of high-functioning preschooler females with ASD (fASD) and sex/age matched peers. We demonstrated the feasibility of visual fNIRS measurements in fASD, and the possibility to discriminate between fASD and typical subjects using different signal features, such as the amplitude and lateralization of vHDR. Moreover, the level of response lateralization was correlated to the severity of autistic traits. These results corroborate the cruciality of sensory symptoms in ASD, paving the way for the validation of the fNIRS analytical tool for diagnosis and treatment outcome monitoring in the ASD population.

The use of data independent acquisition based proteomic analysis and machine learning to reveal potential biomarkers for autism spectrum disorder

Autism spectrum disorder (ASD) is a complex neurological developmental disorder in children, and is associated with social isolation and restricted interests. The etiology of this disorder is still unknown. There is neither any confirmed laboratory test nor any effective therapeutic strategy to diagnose or cure it. We performed data independent acquisition (DIA) and multiple reaction monitoring (MRM) analysis of plasma from children with ASD and controls. The result showed that 45 differentially expressed proteins (DEPs) were identified between autistic subjects and controls. Among these, only one DEP was down-regulated in ASD; other DEPs were up-regulated in ASD children's plasma. These proteins are found associated with complement and coagulation cascades, vitamin digestion and absorption, cholesterol metabolism, platelet degranulation, selenium micronutrient network, extracellular matrix organization and inflammatory pathway, which have been reported to be related to ASD. After MRM verification, five key proteins in complement pathway (PLG, SERPINC1, and A2M) and inflammatory pathway (CD5L, ATRN, SERPINC1, and A2M) were confirmed to be significantly up-regulated in ASD group. Through the screening of machine learning model and MRM verification, we found that two proteins (biotinidase and carbonic anhydrase 1) can be used as early diagnostic markers of ASD (AUC = 0.8, p = 0.0001). SIGNIFICANCE: ASD is the fastest growing neurodevelopmental disorder in the world and has become a major public health problem worldwide. Its prevalence has been steadily increasing, with a global prevalence rate of 1%. Early diagnosis and intervention can achieve better prognosis. In this study, data independent acquisition (DIA) and multiple reaction monitoring (MRM) analysis was applied to analyze the plasma proteome of ASD patients (31 (±5) months old), and 378 proteins were quantified. 45 differentially expressed proteins (DEPs) were identified between the ASD group and the control group. They mainly were associated with platelet degranulation, ECM proteoglycar, complement and coagulation cascades, selenium micronutrient network, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), cholesterol metabolism, vitamin metabolism, and inflammatory pathway. Through the integrated machine learning methods and the MRM verification of independent samples, it is considered that biotinidase and carbon anhydrase 1 have the potential to become biomarkers for the early diagnosis of ASD. These results complement proteomics database of the ASD patients, broaden our understanding of ASD, and provide a panel of biomarkers for the early diagnosis of ASD.

Thiol disulfide homeostasis in psychiatric disorders: A comprehensive review

Thiol-disulfide couple maintains an intracellular redox status. Dynamic thiol-disulfide homeostasis acts crucial parts in metabolic processes involving signal mechanisms, inflammation, antioxidant defense. Thiol-disulfide homeostasis have been implicated in numerous diseases. In this comprehensive review we identified the studies that examined the thiol-disulfide homeostasis in psychiatric disorders. Most cases demonstrated alterations in thiol-disulfide homeostasis and in most of them the thiol-disulfide balance tended to change direction to the disulfide side, that is, to the oxidative side. Currently, the fact that N-acetylcysteine, a thiol-containing compound, is of great interest as a new treatment approach in psychiatric disorders and the role of glutathione, the most abundant thiol, in the brain highlights the importance of evaluating the thiol-disulfide balance in psychiatric disorders.

miRNAs as biomarkers of autism spectrum disorder: a systematic review and meta-analysis

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex clinical manifestations that arise between 18 and 36 months of age. Social interaction deficiencies, a restricted range of interests, and repetitive stereotyped behaviors are characteristics which are sometimes difficult to detect early. Several studies show that microRNAs (miRs/miRNAs) are strongly implicated in the development of the disorder and affect the expression of genes related to different neurological pathways involved in ASD. The present systematic review and meta-analysis addresses the current status of miRNA studies in different body fluids and the most frequently dysregulated miRNAs in patients with ASD. We used a combined approach to summarize miRNA fold changes in different studies using the mean values. In addition, we summarized p values for differential miRNA expression using the Fisher method. Our literature search yielded a total of 133 relevant articles, 27 of which were selected for qualitative analysis based on the inclusion and exclusion criteria, and 16 studies evaluating miRNAs whose data were completely reported were ultimately included in the meta-analysis. The most frequently dysregulated miRNAs across the analyzed studies were miR-451a, miR-144-3p, miR-23b, miR-106b, miR150-5p, miR320a, miR92a-2-5p, and miR486-3p. Among the most dysregulated miRNAs in individuals with ASD, miR-451a is the most relevant to clinical practice and is associated with impaired social interaction. Other miRNAs, including miR19a-3p, miR-494, miR-142-3p, miR-3687, and miR-27a-3p, are differentially expressed in various tissues and body fluids of patients with ASD. Therefore, all these miRNAs can be considered candidates for ASD biomarkers. Saliva may be the optimal biological fluid for miRNA measurements, because it is easy to collect from children compared to other biological fluids.

Sulforaphane Treatment in Children with Autism: A Prospective Randomized Double-Blind Study

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder with repetitive behaviour which affects interaction and communication. Sulforaphane (SFN), an isothiocyanate abundant in the seeds and sprouts of cruciferous vegetables, has been shown to be effective in alleviating autistic behaviour. We performed a prospective double-blind placebo-controlled study to examine the possible effect of SFN in a paediatric cohort aged three to seven years based on measurements of the Autism Diagnostic Observation Schedule-2 (ADOS-2), the Social Responsiveness Scale-2 (SRS-2), and the Aberrant Behaviour Checklist (ABC). The study consisted of three visits over the duration of 36 weeks (baseline, 18 weeks, and 36 weeks). Twenty-eight of the 40 randomized children completed the study. The mean total raw scores on ABC and SRS-2 improved in both groups, but none of the changes reached statistical significance (ABC: 0 weeks p = 0.2742, 18 weeks p = 0.4352, and 36 weeks 0.576; SRS-2: 0 weeks p = 0.5235, 18 weeks p = 0.9176, and 36 weeks 0.7435). Changes in the assessment of the ADOS-2 subscale scores also did not differ between the two study cohorts (ADOS-2: 0 weeks p = 0.8782, 18 weeks p = 0.4788, and 36 weeks 0.9414). We found no significant clinical improvement in the behavioural outcome measures evaluated in children with ASD aged 3-7 years that were treated with sulforaphane.

Trace Element Changes in the Plasma of Autism Spectrum Disorder Children and the Positive Correlation Between Chromium and Vanadium

Existing data demonstrate a significant correlation between autism spectrum disorder (ASD) and the status of biologically essential and toxic trace elements. However, there is still a lack of data on the steady state of trace elements in ASD. We performed a case-control study to explore the association between the risk of ASD and 23 trace elements in plasma. The results showed that children with ASD had considerably decreased lithium (Li), manganese (Mn), selenium (Se), barium (Ba), mercury (Hg), and tin (Sn) levels when compared to their age- and sex-matched controls. Meanwhile, children with ASD had considerably increased plasma chromium (Cr) and vanadium (V) concentrations. We also divided each group into subgroups based on age and gender and created element-related networks for each subgroup. We detected significant element correlations within or between subgroups, as well as changes in correlations that included all elements examined. Finally, more element correlations were observed among males, which may open a new avenue for understanding the complicated process behind the sex ratio of children with ASD. Overall, our data revealed a novel relationship between elements and ASD, which may extend current understanding about ASD.

A Combined Proteomics and Metabolomics Profiling to Investigate the Genetic Heterogeneity of Autistic Children

Autism spectrum disorder (ASD) has become one of the most common neurological developmental disorders in children. However, the study of ASD diagnostic markers faces significant challenges due to the existence of heterogeneity. In this study, genetic testing was performed on children who were clinically diagnosed with ASD. Children with ASD susceptibility genes and healthy controls were studied. The proteomics of plasma and peripheral blood mononuclear cells (PBMCs) as well as plasma metabolomics were carried out. The results showed that although there was genetic heterogeneity in children with ASD, the differentially expressed proteins (DEPs) in plasma, peripheral blood mononuclear cells, and differential metabolites in plasma could still effectively distinguish autistic children from controls. The mechanism associated with them focuses on several common and previously reported mechanisms of ASD. The biomarkers for ASD diagnosis could be found by taking differentially expressed proteins and differential metabolites into consideration. Integrating omics data, glycerophospholipid metabolism and N-glycan biosynthesis might play a critical role in the pathogenesis of ASD.

The autism biomarkers consortium for clinical trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials

BACKGROUND

Eye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD).

METHODS

The autism biomarkers consortium for clinical trials conducted a multisite, observational study of 6-11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications.

RESULTS

All tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills.

LIMITATIONS

No specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts.

CONCLUSIONS

All ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA's Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.

Oxidative Stress in Autism Spectrum Disorder-Current Progress of Mechanisms and Biomarkers

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder that has been diagnosed in an increasing number of children around the world. Existing data suggest that early diagnosis and intervention can improve ASD outcomes. However, the causes of ASD remain complex and unclear, and there are currently no clinical biomarkers for autism spectrum disorder. More mechanisms and biomarkers of autism have been found with the development of advanced technology such as mass spectrometry. Many recent studies have found a link between ASD and elevated oxidative stress, which may play a role in its development. ASD is caused by oxidative stress in several ways, including protein post-translational changes (e.g., carbonylation), abnormal metabolism (e.g., lipid peroxidation), and toxic buildup [e.g., reactive oxygen species (ROS)]. To detect elevated oxidative stress in ASD, various biomarkers have been developed and employed. This article summarizes recent studies about the mechanisms and biomarkers of oxidative stress. Potential biomarkers identified in this study could be used for early diagnosis and evaluation of ASD intervention, as well as to inform and target ASD pharmacological or nutritional treatment interventions.

Brain exosomes as minuscule information hub for Autism Spectrum Disorder

INTRODUCTION

Autism spectrum disorder (ASD) is a neurodevelopmental disorder initiating in the first three years of life. Early initiation of management therapies can significantly improve the health and quality of life of ASD subjects. Thus, indicating the need for suitable biomarkers for the early identification of ASD. Various biological domains were investigated in the quest for reliable biomarkers. However, most biomarkers are in the preliminary stage, and clinical validation is yet to be defined. Exosome based research gained momentum in various Central Nervous System disorders for biomarker identification. However, the utility and prospect of exosomes in ASD is still underexplored.

AREAS COVERED

In the present review, we summarized the biomarker discovery current status and the future of brain-specific exosomes in understanding pathophysiology and its potential as a biomarker. The studies reviewed herein were identified via systematic search (dated: June 2021) of PubMed using variations related to autism (ASD OR autism OR Autism spectrum disorder) AND exosomes AND/OR biomarkers.

EXPERT OPINION

As exosomess are highly relevant in brain disorders like ASD, direct access to brain tissue for molecular assessment is ethically impossible. Thus investigating the brain-derived exosomes would undoubtedly answer many unsolved aspects of the pathogenesis and provide reliable biomarkers.

Altered Metabolic Characteristics in Plasma of Young Boys with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a serious neurodevelopmental disorder with no clinical biomarker. This study used untargeted metabolomic analysis to identify metabolic characteristics in plasma that can distinguish ASD children. 29 boys with ASD (3.02 ± 0.67 years) and 30 typically developing (TD) boys (3.13 ± 0.46 years) were recruited. Developmental and behavioral assessments were conducted in ASD group. Samples of plasma were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The association between metabolite concentration and scale score was assessed by Spearman rank correlation. Altered metabolic characteristics were found in boys with ASD. In Receiver Operating Characteristic (ROC) analysis, ornithine had the highest AUC (Area under ROC) value. Furthermore, the concentration of choline and ornithine was negatively correlated with ABC-language score in ASD group.

Ensemble classification of autism spectrum disorder using structural magnetic resonance imaging features

Background

Autism spectrum disorder (ASD) is characterized by a spectrum of social and communication impairments and rigid and stereotyped behaviors that have a neurodevelopmental origin. Although many imaging studies have reported structural and functional alterations in multiple brain regions, clinically useful diagnostic imaging biomarkers for ASD remain unavailable.

Methods

In this study, we applied machine learning (ML) models to regional volumetric and cortical thickness data from the largest structural magnetic resonance imaging (sMRI) dataset available from the Enhancing Neuro Imaging Genetics Through Meta-Analysis (ENIGMA) consortium (1833 subjects with ASD and 1838 without ASD; age range: 1.5-64; average age: 15.6; male/female ratio: 4.2:1).

Results

The highest classification accuracy on a hold-out test set was achieved using a stacked Extra Tree Classifier. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.62 (95% confidence interval [CI]: 0.57, 0.68) and the area under the precision-recall curve was 0.58. Learning curve analysis showed the good fit of the model and suggests that more training examples will not likely benefit model performance.

Conclusions

Our results suggest that sMRI volumetric and cortical thickness data alone may not provide clinically sufficient useful diagnostic biomarkers for ASD. Developing clinically useful imaging classifiers for ASD will benefit from combining other data modalities or feature types, such as functional MRI data and raw images that can leverage other machine learning (ML) techniques such as convolutional neural networks.

Dental Pulp-Derived Mesenchymal Stem Cells for Modeling Genetic Disorders

A subpopulation of mesenchymal stem cells, developmentally derived from multipotent neural crest cells that form multiple facial tissues, resides within the dental pulp of human teeth. These stem cells show high proliferative capacity in vitro and are multipotent, including adipogenic, myogenic, osteogenic, chondrogenic, and neurogenic potential. Teeth containing viable cells are harvested via minimally invasive procedures, based on various clinical diagnoses, but then usually discarded as medical waste, indicating the relatively low ethical considerations to reuse these cells for medical applications. Previous studies have demonstrated that stem cells derived from healthy subjects are an excellent source for cell-based medicine, tissue regeneration, and bioengineering. Furthermore, stem cells donated by patients affected by genetic disorders can serve as in vitro models of disease-specific genetic variants, indicating additional applications of these stem cells with high plasticity. This review discusses the benefits, limitations, and perspectives of patient-derived dental pulp stem cells as alternatives that may complement other excellent, yet incomplete stem cell models, such as induced pluripotent stem cells, together with our recent data.

Neurodevelopmental signatures of narcotic and neuropsychiatric risk factors in 3D human-derived forebrain organoids

It is widely accepted that narcotic use during pregnancy and specific environmental factors (e.g., maternal immune activation and chronic stress) may increase risk of neuropsychiatric illness in offspring. However, little progress has been made in defining human-specific in utero neurodevelopmental pathology due to ethical and technical challenges associated with accessing human prenatal brain tissue. Here we utilized human induced pluripotent stem cells (hiPSCs) to generate reproducible organoids that recapitulate dorsal forebrain development including early corticogenesis. We systemically exposed organoid samples to chemically defined "enviromimetic" compounds to examine the developmental effects of various narcotic and neuropsychiatric-related risk factors within tissue of human origin. In tandem experiments conducted in parallel, we modeled exposure to opiates (μ-opioid agonist endomorphin), cannabinoids (WIN 55,212-2), alcohol (ethanol), smoking (nicotine), chronic stress (human cortisol), and maternal immune activation (human Interleukin-17a; IL17a). Human-derived dorsal forebrain organoids were consequently analyzed via an array of unbiased and high-throughput analytical approaches, including state-of-the-art TMT-16plex liquid chromatography/mass-spectrometry (LC/MS) proteomics, hybrid MS metabolomics, and flow cytometry panels to determine cell-cycle dynamics and rates of cell death. This pipeline subsequently revealed both common and unique proteome, reactome, and metabolome alterations as a consequence of enviromimetic modeling of narcotic use and neuropsychiatric-related risk factors in tissue of human origin. However, of our 6 treatment groups, human-derived organoids treated with the cannabinoid agonist WIN 55,212-2 exhibited the least convergence of all groups. Single-cell analysis revealed that WIN 55,212-2 increased DNA fragmentation, an indicator of apoptosis, in human-derived dorsal forebrain organoids. We subsequently confirmed induction of DNA damage and apoptosis by WIN 55,212-2 within 3D human-derived dorsal forebrain organoids. Lastly, in a BrdU pulse-chase neocortical neurogenesis paradigm, we identified that WIN 55,212-2 was the only enviromimetic treatment to disrupt newborn neuron numbers within human-derived dorsal forebrain organoids. Cumulatively this study serves as both a resource and foundation from which human 3D biologics can be used to resolve the non-genomic effects of neuropsychiatric risk factors under controlled laboratory conditions. While synthetic cannabinoids can differ from naturally occurring compounds in their effects, our data nonetheless suggests that exposure to WIN 55,212-2 elicits neurotoxicity within human-derived developing forebrain tissue. These human-derived data therefore support the long-standing belief that maternal use of cannabinoids may require caution so to avoid any potential neurodevelopmental effects upon developing offspring in utero.

ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a class of neurodevelopmental disorders characterized by genetic and environmental risk factors. The pathogenesis of ASD has a strong genetic basis, consisting of rare de novo or inherited variants among a variety of multiple molecules. Previous studies have shown that microRNAs (miRNAs) are involved in neurogenesis and brain development and are closely associated with the pathogenesis of ASD. However, the regulatory mechanisms of miRNAs in ASD are largely unclear. In this work, we present a stepwise method, ASDmiR, for the identification of underlying pathogenic genes, networks, and modules associated with ASD. First, we conduct a comparison study on 12 miRNA target prediction methods by using the matched miRNA, lncRNA, and mRNA expression data in ASD. In terms of the number of experimentally confirmed miRNA-target interactions predicted by each method, we choose the best method for identifying miRNA-target regulatory network. Based on the miRNA-target interaction network identified by the best method, we further infer miRNA-target regulatory bicliques or modules. In addition, by integrating high-confidence miRNA-target interactions and gene expression data, we identify three types of networks, including lncRNA-lncRNA, lncRNA-mRNA, and mRNA-mRNA related miRNA sponge interaction networks. To reveal the community of miRNA sponges, we further infer miRNA sponge modules from the identified miRNA sponge interaction network. Functional analysis results show that the identified hub genes, as well as miRNA-associated networks and modules, are closely linked with ASD. ASDmiR is freely available at https://github.com/chenchenxiong/ASDmiR.

Detection of disease-associated microRNAs - application for autism spectrum disorders

Autism spectrum disorders (ASD) diagnostic procedure still lacks a uniform biological marker. This review gathers the information on microRNAs (miRNAs) specifically as a possible source of biomarkers of ASD. Extracellular vesicles, and their subset of exosomes, are believed to be a tool of cell-to-cell communication, and they are increasingly considered to be carriers of such a marker. The interest in studying miRNAs in extracellular vesicles grows in all fields of study and therefore should not be omitted in the field of neurodevelopmental disorders. The summary of miRNAs associated with brain cells and ASD either studied directly in the tissue or biofluids are gathered in this review. The heterogeneity in findings from different studies points out the fact that unified methods should be established, beginning with the determination of the accurate patient and control groups, through to sample collection, processing, and storage conditions. This review, based on the available literature, proposes the standardized approach to obtain the results that would not be affected by technical factors. Nowadays, the method of high-throughput sequencing seems to be the most optimal to analyze miRNAs. This should be followed by the uniformed bioinformatics procedure to avoid misvalidation. At the end, the proper validation of the obtained results is needed. With such an approach as is described in this review, it would be possible to obtain a reliable biomarker that would characterize the presence of ASD.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Mitochondrial dysfunction: A hidden trigger of autism?

Autism is a heterogeneous neurodevelopmental and neuropsychiatric disorder with no precise etiology. Deficits in cognitive functions uncover at early stages and are known to have an environmental and genetic basis. Since autism is multifaceted and also linked with other comorbidities associated with various organs, there is a possibility that there may be a fundamental cellular process responsible for this. These reasons place mitochondria at the point of interest as it is involved in multiple cellular processes predominantly involving metabolism. Mitochondria encoded genes were taken into consideration lately because it is inherited maternally, has its own genome and also functions the time of embryo development. Various researches have linked mitochondrial mishaps like oxidative stress, ROS production and mt-DNA copy number variations to autism. Despite dramatic advances in autism research worldwide, the studies focusing on mitochondrial dysfunction in autism is rather minimal, especially in India. India, owing to its rich diversity, may be able to contribute significantly to autism research. It is vital to urge more studies in this domain as it may help to completely understand the basics of the condition apart from a genetic standpoint. This review focuses on the worldwide and Indian scenario of autism research; mitochondrial abnormalities in autism and possible therapeutic approaches to combat it.

Biomarker Exploration in Human Peripheral Blood Mononuclear Cells for Monitoring Sulforaphane Treatment Responses in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is one of the most common neurodevelopmental disorders with no drugs treating the core symptoms and no validated biomarkers for clinical use. The multi-functional phytochemical sulforaphane affects many of the biochemical abnormalities associated with ASD. We investigated potential molecular markers from three ASD-associated physiological pathways that can be affected by sulforaphane: redox metabolism/oxidative stress; heat shock response; and immune dysregulation/inflammation, in peripheral blood mononuclear cells (PBMCs) from healthy donors and patients with ASD. We first analyzed the mRNA levels of selected molecular markers in response to sulforaphane ex vivo treatment in PBMCs from healthy donors by real-time quantitative PCR. All of the tested markers showed quantifiability, accuracy and reproducibility. We then compared the expression levels of those markers in PBMCs taken from ASD patients in response to orally-delivered sulforaphane. The mRNA levels of cytoprotective enzymes (NQO1, HO-1, AKR1C1), and heat shock proteins (HSP27 and HSP70), increased. Conversely, mRNA levels of pro-inflammatory markers (IL-6, IL-1β, COX-2 and TNF-α) decreased. Individually none is sufficiently specific or sensitive, but when grouped by function as two panels, these biomarkers show promise for monitoring pharmacodynamic responses to sulforaphane in both healthy and autistic humans, and providing guidance for biomedical interventions.

[Thrombodynamic correlates of catatonia severity in children with autism]

AIM

To study a correlation between the values of thrombodynamics parameters of hypercoagulation measured by the thrombodynamics test and the severity of catatonia in children with infantile psychosis in childhood autism (F84.02).

MATERIAL AND METHODS

Twenty-four patients (22 boys and 2 girls) aged from 3 to 13 years, were studied. The severity of catatonia was determined by BFCRS. A thrombodynamic test was performed in platelet-free plasma using the analyzer T-2 Thrombodynamics Device (Hemacore LLC, Russia).

RESULTS

Thrombodynamic (TD) parameters of clot growth rates from the activator (V, Vi and Vst) were statistically significantly higher than normal values. Similar results were obtained for Clot Size at 30 min (CS, μm): Tlag and D values were within normal limits. The values of Time of appearance of spontaneous clots (Tsp min) were less than the lower limit values for the norm (30 min). Correlation analysis showed that the severity of catatonia is positively correlated with the initial clot growth rate (Vi) (p=0.009) and negatively with Tsp (p=0.002). With an increase in the time of appearance of spontaneous clots (due to a decrease in the procoagulant activity of platelet microparticles in the plasma of patients), the severity of catatonia in children with ASD decreases.

CONCLUSION

The results suggest that normalizing plasma and platelet hemostasis is important for increasing the effectiveness of treatment of patients with ASD with catatonia.

Genes Positively Selected in Domesticated Mammals Are Significantly Dysregulated in the Blood of Individuals with Autism Spectrum Disorders

Human self-domestication (i.e., the presence of traits in our species that are commonly found in domesticated animals) has been hypothesized to have contributed to the emergence of many human-specific features, including aspects of our cognition and behavior. Signs of self-domestication have been claimed to be attenuated in individuals with autism spectrum disorders (ASD), this conceivably accounting for facets of their distinctive cognitive and behavioral profile, although this possibility needs to be properly tested. In this study, we have found that candidate genes for mammal domestication, but not for neural crest development and function, are significantly dysregulated in the blood of subjects with ASD. The set of differentially expressed genes (DEGs) is enriched in biological and molecular processes, as well as in pathological phenotypes, of relevance for the etiology of ASD, like lipid metabolism, cell apoptosis, the activity of the insulin-like growth factor, gene expression regulation, skin/hair anomalies, musculoskeletal abnormalities, and hearing impairment. Moreover, among the DEGs, there are known candidates for ASD and/or genes involved in biological processes known to be affected in ASD. Our findings give support to the view that one important aspect of the etiopathogenesis of ASD is the abnormal manifestation of features of human self-domestication.

China Multi-Center Preschool Autism Project (CMPAP): Design and Methodologies to Identify Clinical Symptom Features and Biomarkers of Autism Spectrum Disorders

Background: The etiology of autism spectrum disorder (ASD) has not yet been fully identified, but it seems to be triggered by complex genetic and environmental risk factors. Moreover, the tremendous etiological and clinical differences among individuals with ASD has had a major negative impact on early diagnosis and individualized treatment. Earlier diagnosis of precise clinical subtypes of ASD could lead to individualized treatment and a better prognosis. However, few large-scale epidemiological studies have explored precise clinical subtypes and clinically meaningful biomarkers, especially in China. Methods and Design: The China Multi-center Preschool Autism Project (CMPAP) includes nearly 3,000 children-1,469 individuals with ASD and 1,499 typically-developing (TD) controls-from 13 cities in China. Using a case-control design, each participant was comprehensively characterized in terms of feeding and disease history, maternal history, family history, clinical core symptoms, comorbidities, biochemical markers, genomics, urine/fecal metabonomics, and intestinal flora. In addition, data on environmental risk factors were obtained using interviews and electronic medical records. Conclusion: The study was designed to: (1) investigate age at diagnosis and treatment and family and social support for preschool children with ASD in China, (2) develop a more accurate clinical subtype and intervention system for the ICD-11, and (3) find the specific genes and environmental markers of different subtypes, which will help in the development of early diagnosis and individual intervention programs for preschool children with ASD. This study will provide the basis for improving national health policies for ASD in China.

Proteomics Study of Peripheral Blood Mononuclear Cells (PBMCs) in Autistic Children

Autism is one of the most common neurological developmental disorder associated with social isolation and restricted interests in children. The etiology of this disorder is still unknown. There is neither any confirmed laboratory test nor any effective therapeutic strategy to diagnose or cure it. To search for biomarkers for early detection and exploration of the disease mechanisms, here, we investigated the protein expression signatures of peripheral blood mononuclear cells (PBMCs) in autistic children compared with healthy controls by using isobaric tags for relative and absolute quantitation (iTRAQ) proteomics approach. The results showed a total of 41 proteins as differentially expressed in autistic group as compared to control. These proteins are found associated with metabolic pathways, endoplasmic reticulum (ER) stress and protein folding, endocytosis, immune and inflammatory response, plasma lipoprotein particle organization, and cell adhesion. Among these, 17 proteins (13 up-regulated and four down-regulated) are found to be linked with mitochondria. Eight proteins including three already reported proteins in our previous studies were selected to be verified. Five already reported autism associated pro-inflammatory cytokines [interferon-γ (IFN-γ), interleukin-1β (IL-1β), IL-6, IL-12, and tumor necrosis factor-α (TNF-α)] were detected in plasma by enzyme-linked immunosorbent assay (ELISA) analysis. The results were consistent with proteomic results and reports from previous literature. These results proposed that PBMCs from autistic children might be activated, and ER stress, unfolded protein response (UPR), acute-phase response (APR), inflammatory response, and endocytosis may be involved in autism occurrence. These reported proteins may serve as potential biomarkers for early diagnosis of autism. More specifically, simultaneous detection of three proteins [complement C3 (C3), calreticulin (CALR), and SERPINA1] in the plasma and PBMCs could increase the authenticity of detection.