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 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.

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.

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.

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.

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.

Protein Biomarkers of Autism Spectrum Disorder Identified by Computational and Experimental Methods.

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects millions of people worldwide. However, there are currently no reliable biomarkers for ASD diagnosis. Materials and Methods: The strategy of computational prediction combined with experimental verification was used to identify blood protein biomarkers for ASD. First, brain tissue-based transcriptome data of ASD were collected from Gene Expression Omnibus database and analyzed to find ASD-related genes by bioinformatics method of significance analysis of microarrays. Then, a prediction program of blood-secretory proteins was applied on these genes to predict ASD-related proteins in blood. Furthermore, ELISA was used to verify these proteins in plasma samples of ASD patients. Results: A total of 364 genes were identified differentially expressed in brain tissue of ASD, among which 59 genes were predicted to encode ASD-related blood-secretory proteins. After functional analysis and literature survey, six proteins were chosen for experimental verification and five were successfully validated. Receiver operating characteristic curve analyses showed that the area under the curve of SLC25A12, LIMK1, and RARS was larger than 0.85, indicating that they are more powerful in discriminating ASD cases from controls. Conclusion: SLC25A12, LIMK1, and RARS might serve as new potential blood protein biomarkers for ASD. Our findings provide new insights into the pathogenesis and diagnosis of ASD.

[Application of the Children Neuropsychological and Behavioral Scale-Revision 2016 in young children with autism spectrum disorder].

OBJECTIVE: To compare the assessment results of the Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) between young children with autism spectrum disorder (ASD) and global developmental delay (GDD, without ASD) and to explore whether CNBS-R2016 could be helpful to early identification of ASD. METHODS: A total of 260 ASD and 371 GDD children aged 18-30 months were enrolled to finish the assessment of CNBS-R2016. The development quotients (DQs) of the five domains of CNBS-R2016 including gross motor, fine motor, adaptability, language and social behavior were compared between the two groups. The receiver operating characteristic (ROC) curve was used to evaluate the value of the autism-predicted domain in identifying ASD and GDD. RESULTS: The DQs of all the five domains in the ASD group were lower than those in the GDD group (P<0.05). The language DQ and total DQ of the ASD group had a negative correlation with the score of the autism-predicted domain (rs=-0.566, -0.552 respectively, P<0.01). When the cut-off value of the autism-predicted domain was 10.5, the largest area under the ROC curve was 0.835, and the sensitivity and specificity for the diagnosis of ASD were 0.750 and 0.798 respectively. CONCLUSIONS: The development of ASD children aged 18-30 months is worse than that of GDD children. CNBS-R2016 may be helpful to distinguish ASD from children with developmental delay.

Biomarkers in autism spectrum disorders: Current progress.

Autism spectrum disorder (ASD) refers to a group of complex neurodevelopmental disorders characterized by social interaction and communication deficits and repetitive and stereotyped behaviors. As the etiology and pathogenesis of the disorder have not yet been elucidated, specific treatment and reliable diagnostic biomarkers are not available. Early behavioral interventions have been shown to substantially improve symptoms in children with ASD. Given the rapidly increasing prevalence of ASD, there is an urgent need to identify related diagnostic biomarkers. Although specific diagnostic markers for ASD have not been identified, the related research has made progress in different aspects. This review summarizes recent findings of the use of genes, proteins, peptides, and metabolites as diagnostic markers for ASD. The associated techniques include genetic testing and proteomic and metabolomic analyses. In addition, some studies have focused on single or several proteins and metabolites. Moreover, transcriptomic analysis, immune disturbances and cytokine may also be used for this purpose. The pathogenesis involving genes, proteins, and metabolites is also discussed here.

Comparative Proteomics Analysis of Serum Proteins in Gestational Diabetes during Early and Middle Stages of Pregnancy.

PURPOSE: This study is designed to screen serum proteins that may serve as biomarkers for gestational diabetes mellitus (GDM), and clarify the mechanisms of disease. EXPERIMENTAL DESIGN: By using isobaric tags for relative and absolute quantitation proteomics analysis, serum proteins levels were quantified in pregnant women who subsequently developed GDM (12-16 weeks), GDM patients (24-28 weeks), and their corresponding controls. The strategy of mixing samples is used in proteomic analysis. RESULTS: Thirty-one and 27 differentially expressed proteins are identified in the serum of pregnant women with developed GDM at 12-16 weeks and GDM patients during 24-28 weeks, respectively. Thirty eight and 28 proteins are identified in 24-28 weeks versus 12-16 weeks controls (24/12 CTR group), and 24-28 weeks GDM patients versus 12-16 weeks women with subsequently developed GDM (24/12 GDM group), respectively. Most of these proteins in the case and control subjects are associated with diabetes and maternal and perinatal short- and long-term complications. CONCLUSIONS AND CLINICAL RELEVANCE: The results highlight the roles of complement system and the blood clotting cascade in the pathogenesis of GDM. Differentially expressed proteins may serve as potential biomarkers for GDM prediction and diagnosis in the future.

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-1ß (IL-1ß), 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.

Advances in Biomarker Studies in Autism Spectrum Disorders.

Autism spectrum disorder (ASD) is a neurological and developmental condition that begins early in childhood and lasts throughout life. The epidemiology of ASD is continuously increasing all over the world with huge social and economical burdens. As the etiology of autism is not completely understood, there is still no medication available for the treatment of this disorder. However, some behavioral interventions are available to improve the core and associated symptoms of autism, particularly when initiated at an early stage. Thus, there is an increasing demand for finding biomarkers for ASD. Although diagnostic biomarkers have not yet been established, research efforts have been carried out in neuroimaging and biological analyses including genomics and gene testing, proteomics, metabolomics, transcriptomics, and studies of the immune system, inflammation, and microRNAs. Here, we will review the current progress in these fields and focus on new methods, developments, research strategies, and studies of blood-based biomarkers.

iTRAQ-Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism.

PURPOSE: Autism is a childhood neurological disorder with poorly understood etiology and pathology. This study is designed to identify differentially expressed proteins that might serve as potential biomarkers for autism. EXPERIMENTAL DESIGN: We perform iTRAQ (isobaric tags for relative and absolute quantitation) analysis for normal and autistic children's plasma of the same age group. RESULTS: The results show that 24 differentially expressed proteins were identified between autistic subjects and controls. For the first time, differential expression of complement C5 (C5) and fermitin family homolog 3 (FERMT3) are related to autism. Five proteins, that is, complement C3 (C3), C5, integrin alpha-IIb (ITGA2B), talin-1 (TLN1), and vitamin D-binding protein (GC) were validated via enzyme-linked immunosorbent assay (ELISA). By ROC (receiver operating characteristic) analysis, combinations of these five proteins C3, C5, GC, ITGA2B, and TLN1 distinguished autistic children from healthy controls with a high AUC (area under the ROC curve) value (0.982, 95% CI, 0.957-1.000, p < 0.000). CONCLUSION: These above described proteins are found involved in different pathways that have previously been linked to the pathophysiology of autism spectrum disorders (ASDs). The results strongly support that focal adhesions, acting cytoskeleton, cell adhesion, motility and migration, synaptogenesis, and complement system are involved in the pathogenesis of autism, and highlight the important role of platelet function in the pathophysiology of autism.

Redox proteomic identification of carbonylated proteins in autism plasma: insight into oxidative stress and its related biomarkers in autism.

BACKGROUND: Autism is a severe childhood neurological disorder with poorly understood etiology and pathology. Currently, there is no authentic laboratory test to confirm the diagnosis of autism. Oxidative damage may play a central role in the pathogenesis of autism. Present study is an effort to search for possible biomarkers of autism and further clarify the molecular changes associated with oxidative stress that occurs in the plasma of autistic children. METHODS: We performed redox proteomics analysis to compare carbonylated proteins in the plasma of autistic subjects and healthy controls. Immunoprecipitation and Western blot analysis were used to validate carbonylated proteins identified by the redox proteomics. RESULTS: Protein carbonylation levels in two proteins, complement component C8 alpha chain and Ig kappa chain C were found to be significantly increased in autistic patients compared with controls. These two proteins were successfully validated via immunoprecipitation and Western blot analysis. CONCLUSIONS: The results further highlight the role of oxidative stress in the pathogenesis of autism and provide some information for the diagnosis and/or monitoring of autism.