Biomarkers in autism spectrum disorder: the old and the new

Exploring autism via the retina: Comparative insights in children with autism spectrum disorder and typical development

Autism spectrum disorder (ASD) is a widely recognized neurodevelopmental disorder, yet the identification of reliable imaging biomarkers for its early diagnosis remains a challenge. Considering the specific manifestations of ASD in the eyes and the interconnectivity between the brain and the eyes, this study investigates ASD through the lens of retinal analysis. We specifically examined differences in the macular region of the retina using optical coherence tomography (OCT)/optical coherence tomography angiography (OCTA) images between children diagnosed with ASD and those with typical development (TD). Our findings present potential novel characteristics of ASD: the thickness of the ellipsoid zone (EZ) with cone photoreceptors was significantly increased in ASD; the large-caliber arteriovenous of the inner retina was significantly reduced in ASD; these changes in the EZ and arteriovenous were more significant in the left eye than in the right eye. These observations of photoreceptor alterations, vascular function changes, and lateralization phenomena in ASD warrant further investigation, and we hope that this work can advance interdisciplinary understanding of ASD.

Reversal of Autism Symptoms among Dizygotic Twins through a Personalized Lifestyle and Environmental Modification Approach: A Case Report and Review of the Literature

The prevalence of autism has been increasing at an alarming rate. Even accounting for the expansion of autism spectrum disorder diagnostic (ASD) criteria throughout the 1990's, there has been an over 300% increase in ASD prevalence since the year 2000. The often debilitating personal, familial, and societal sequelae of autism are generally believed to be lifelong. However, there have been several encouraging case reports demonstrating the reversal of autism diagnoses, with a therapeutic focus on addressing the environmental and modifiable lifestyle factors believed to be largely underlying the condition. This case report describes the reversal of autism symptoms among dizygotic, female twin toddlers and provides a review of related literature describing associations between modifiable lifestyle factors, environmental exposures, and various clinical approaches to treating autism. The twins were diagnosed with Level 3 severity ASD "requiring very substantial support" at approximately 20 months of age following concerns of limited verbal and non-verbal communication, repetitive behaviors, rigidity around transitions, and extensive gastrointestinal symptoms, among other common symptoms. A parent-driven, multidisciplinary, therapeutic intervention involving a variety of licensed clinicians focusing primarily on addressing environmental and modifiable lifestyle factors was personalized to each of the twin's symptoms, labs, and other outcome measures. Dramatic improvements were noted within several months in most domains of the twins' symptoms, which manifested in reductions of Autism Treatment Evaluation Checklist (ATEC) scores from 76 to 32 in one of the twins and from 43 to 4 in the other twin. The improvement in symptoms and ATEC scores has remained relatively stable for six months at last assessment. While prospective studies are required, this case offers further encouraging evidence of ASD reversal through a personalized, multidisciplinary approach focusing predominantly on addressing modifiable environmental and lifestyle risk factors.

The Impact of Antenatal Corticosteroids on the Metabolome of Preterm Newborns: An Untargeted Approach

We analyzed and compared variations in the urinary metabolome, as well as postnatal clinical outcomes among preterm infants, based on the timing of antenatal corticosteroid (ACS) administration in response to preterm labor onset in their mothers. This was a prospective observational study held in the Neonatal Intensive Care Unit, Department of Woman's and Child's Health, Padova University Hospital (Italy). A urine sample was obtained from each patient within 24 h of birth; Mass Spectrometry-based untargeted metabolomics analysis was then conducted. We searched for any significant disparities in the metabolomic profile of preterm newborns subjected to antenatal corticosteroid (ACS) treatment at varying timings; their correlation with clinical outcomes were also evaluated. The group receiving ACS within the optimal time window (1-7 days before delivery) exhibited elevated levels of cysteine, N-acetylglutamine, propionyl carnitine and 5-hydroxyindolacetic acid, coupled with a decrease in pipecolic acid. Clinically, this group demonstrated a reduced need for invasive ventilation (p = 0.04). In conclusion, metabolomics analysis identified several metabolites that discriminated preterm infants whose mothers received ACS within the recommended time window. Elevated levels of cysteine and 5-Hydroxyindoleacetic acid, metabolites characterized by antioxidant and anti-inflammatory properties, were observed in these infants. This metabolic profile correlated with improved respiratory outcomes, as evidenced by a reduced necessity for invasive ventilation at birth.

A Systematic Review on Autism and Hyperserotonemia: State-of-the-Art, Limitations, and Future Directions

Hyperserotonemia is one of the most studied endophenotypes in autism spectrum disorder (ASD), but there are still no unequivocal results about its causes or biological and behavioral outcomes. This systematic review summarizes the studies investigating the relationship between blood serotonin (5-HT) levels and ASD, comparing diagnostic tools, analytical methods, and clinical outcomes. A literature search on peripheral 5-HT levels and ASD was conducted. In total, 1104 publications were screened, of which 113 entered the present systematic review. Of these, 59 articles reported hyperserotonemia in subjects with ASD, and 26 presented correlations between 5-HT levels and ASD-core clinical outcomes. The 5-HT levels are increased in about half, and correlations between hyperserotonemia and clinical outcomes are detected in a quarter of the studies. The present research highlights a large amount of heterogeneity in this field, ranging from the characterization of ASD and control groups to diagnostic and clinical assessments, from blood sampling procedures to analytical methods, allowing us to delineate critical topics for future studies.

Serum brain-derived neurotrophic factor concentration is different between autism spectrum disorders and intellectual disability children and adolescents

PURPOSE

Recent studies showed that mature brain-derived neurotrophic factor (mBDNF) and its precursor proBDNF are associated with autism spectrum disorders (ASD). Whether their levels are different between ASD and intellectual disability (ID) subjects is not clear. The aim of this study is to compare the serum mBDNF and proBDNF concentration, and mBNDF/proBDNF ratio in ASD and ID volunteers.

METHODS

Children and adolescents with ASD or ID between the ages of 4 and 22 were recruited in Tianjin, China. Serum mBDNF and proBDNF level were tested and Wechsler Preschool and Primary Scale of Intelligence (WPPSI), Wechsler Intelligence Scale for Children (WISC), and Childhood Autism Rating Scale (CARS) evaluations were conducted.

RESULTS

Serum mBDNF concentration and the ratio of mBDNF to proBDNF was higher in ASD subjects than that in ID subjects (P = 0.035 and P < 0.001, respectively), while serum proBDNF of ASD participants was lower compared to that of ID participants (P < 0.001). CARS score was positively correlated with serum mBDNF level (r = 0.33, P = 0.004) and m/p ratio (r = 0.39, P < 0.001), and negatively correlated with serum proBDNF level (r = -0.39, <0.001) after adjusting for age and IQ. The AUC of mBDNF, proBDNF, and m/p ratio were 0.741, 0.790, and 0.854, respectively, after adjusted for age and IQ.

CONCLUSION

Serum mBDNF, proBDNF and m/p ratio were different between ASD and ID group. The three biomarkers displayed good diagnostic values for classification of ASD and ID subjects.

Glucose transporter 1 deficiency, AMP-activated protein kinase activation and immune dysregulation in autism spectrum disorder: Novel biomarker sources for clinical diagnosis

The neurophysiological basis of autism spectrum disorder (ASD) is still uncertain. Nevertheless, studies support the hypotheses that oxidative stress, neuroinflammation, immune dysregulation, and metabolic stress are contributors. In this study, the serum levels of 3-nitrotyrosine (3-NT), hypoxia-inducible factor 1 α (HIF-1 α), heat shock protein 70 (HSP-70), interleukin-17A (IL-17A), IL-35, vitamin D3 (VITD), glucose transporter-1 (GUT1), and AMP-activated protein kinase (AMPK) were estimated in Saudi ASD children versus age-matched neurotypical controls, aiming to investigate whether these parameters have potential roles in the pathophysiologic mechanisms of ASD and hoping to find a reliable marker for early ASD diagnosis. This study included 25 ASD children and 25 typically developing children (3-11 years old). The diagnosis of ASD cases was made based on the Autism Diagnostic Observation Schedule (ADOS) and the Statistical Manual of Mental Disorders (DSM-5). ASD subjects were commonly male and revealed an intelligence quotient (IQ) < 70.The results detected that ASD children have remarkable greater serum levels of nitrosative stress (3-NT), hypoxia (HIF-1 α), inflammatory (HSP-70, IL-17A, and AMPK) biomarkers and lower serum levels of anti-inflammatory (IL-35 and VITD) and metabolic stress (GUT-1) biomarkers versus age-matched controls (P ≤ 0.0001). Pearson's correlation study revealed that 3-NT was positively associated with HIF-1 α and HSP-70. HIF-1 α was also positively correlated with HSP-70. AMPK was positively associated with GUT-1, however, IL-17A was negatively correlated with IL-35 and VITD.Limitation:No specific therapeuticdrugs were administered in this study, and further studies are required to confirm the role of the selected biomarkers in ASD managements.

Conclusion

Changes in concentrations of different biomarkers indicate that they are involved in oxidative stress, metabolic stress, immune dysregulation and ASD pathogenesis. Hence, these parameters can prove to be promising biomarkers as well as therapeutic targets for the timely diagnosis and treatment of ASD patients.

IL-6, homocysteine, and autism spectrum phenotypes: an investigation among adults with autism spectrum disorder and their first-degree relatives

BACKGROUND

The importance of recognizing different kinds of autism spectrum presentations among adults, including subthreshold forms and the broad autism phenotype (BAP), has been increasingly highlighted in recent studies. Meanwhile, the possible involvement of immune system deregulation and altered methylation/trans-sulfuration processes in autism spectrum disorder (ASD) is gaining growing attention, but studies in this field are mainly focused on children. In this framework, the aim of this study was to compare plasmatic concentrations of IL-6 and homocysteine (HCY) among adults with ASD, their first-degree relatives, and healthy controls (CTLs), investigating also possible correlations with specific autism symptoms.

METHODS

Plasma concentrations of IL-6 and HCY were measured in a group of adult subjects with ASD, their first-degree relatives (BAP group), and healthy controls (CTL). All participants were also evaluated with psychometric instruments.

RESULTS

IL-6 and HCY concentrations were significantly higher in the ASD group than in CTLs, while BAP subjects reported intermediate results. Significant correlations were reported between biochemical parameters and psychometric scales, particularly for the dimension of ruminative thinking.

CONCLUSIONS

These findings support the hypothesis of a key involvement of HCY-related metabolism and immune system alteration in autism spectrum pathophysiology. HCY and IL-6 seem to show different associations with specific autism dimensions.

Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder

Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.

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 Review on Integrated ZnO-Based SERS Biosensors and Their Potential in Detecting Biomarkers of Neurodegenerative Diseases

Surface-enhanced Raman spectroscopy (SERS) applications in clinical diagnosis and spectral pathology are increasing due to the potential of the technique to bio-barcode incipient and differential diseases via real-time monitoring of biomarkers in fluids and in real-time via biomolecular fingerprinting. Additionally, the rapid advancements in micro/nanotechnology have a visible influence in all aspects of science and life. The miniaturization and enhanced properties of materials at the micro/nanoscale transcended the confines of the laboratory and are revolutionizing domains such as electronics, optics, medicine, and environmental science. The societal and technological impact of SERS biosensing by using semiconductor-based nanostructured smart substrates will be huge once minor technical pitfalls are solved. Herein, challenges in clinical routine testing are addressed in order to understand the context of how SERS can perform in real, in vivo sampling and bioassays for early neurodegenerative disease (ND) diagnosis. The main interest in translating SERS into clinical practice is reinforced by the practical advantages: portability of the designed setups, versatility in using nanomaterials of various matter and costs, readiness, and reliability. As we will present in this review, in the frame of technology readiness levels (TRL), the current maturity reached by semiconductor-based SERS biosensors, in particular that of zinc oxide (ZnO)-based hybrid SERS substrates, is situated at the development level TRL 6 (out of 9 levels). Three-dimensional, multilayered SERS substrates that provide additional plasmonic hot spots in the z-axis are of key importance in designing highly performant SERS biosensors for the detection of ND biomarkers.

Translating neuroimaging changes to neuro-endophenotypes of autistic spectrum disorder: a narrative review

Background

Autism-spectrum disorder is a neurodevelopmental disorder with heterogeneity in etiopathogenesis and clinical presentation. Neuroanatomical and neurophysiological abnormalities may represent neural endophenotypes for autism spectrum disorders which may help identify subgroups of patients seemingly similar in clinical presentation yet different in their pathophysiological underpinnings. Furthermore, a thorough understanding of the pathophysiology of disease can pave the way to effective treatments, prevention, and prognostic predictions. The aim of this review is to identify the predominant neural endophenotypes in autism-spectrum disorder. The evidence was researched at the following electronic databases: Pubmed, PsycINFO, Scopus, Web of Science, and EMBASE.

Results

Enlarged brain, especially frontotemporal cortices have been consistently reported by structural neuroimaging, whereas functional neuroimaging has revealed frontotemporal dysconnectivity.

Conclusions

Regrettably, many of these findings have not been consistent. Therefore, translating these findings into neural endophenotype is by far an attempt in its budding stage. The structural and functional neuroimaging changes may represent neural endophenotypes unique to autism-spectrum disorder. Despite inconsistent results, a clinically meaningful finding may require combined efforts of autism-spectrum-disorder researchers focused on different aspects of basic, genetic, neuroimaging, and clinical research.

Implications of the endocannabinoid system and the therapeutic action of cannabinoids in autism spectrum disorder: A literature review

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, onset in early childhood and associated with cognitive, social, behavioral, and sensory impairments. The pathophysiology is still unclear, and it is believed that genetic and environmental factors are fully capable of influencing ASD, especially cell signaling and microglial functions. Furthermore, the endocannabinoid system (ECS) participates in the modulation of various brain processes and is also involved in the pathophysiological mechanisms of this condition. Due to the health and quality of life impacts of autism for the patient and his/her family and the lack of effective medications, the literature has elucidated the possibility that Cannabis phytocannabinoids act favorably on ASD symptoms, probably through the modulation of neurotransmitters, in addition to endogenous ligands derived from arachidonic acid, metabolizing enzymes and even transporters of the membrane. These findings support the notion that there are links between key features of ASD and ECS due to the favorable actions of cannabidiol (CBD) and other cannabinoids on symptoms related to behavioral and cognitive disorders, as well as deficits in communication and social interaction, hyperactivity, anxiety and sleep disorders. Thus, phytocannabinoids emerge as therapeutic alternatives for ASD.

Cognitive theories of autism based on the interactions between brain functional networks

Cognitive functions are directly related to interactions between the brain's functional networks. This functional organization changes in the autism spectrum disorder (ASD). However, the heterogeneous nature of autism brings inconsistency in the findings, and specific pattern of changes based on the cognitive theories of ASD still requires to be well-understood. In this study, we hypothesized that the theory of mind (ToM), and the weak central coherence theory must follow an alteration pattern in the network level of functional interactions. The main aim is to understand this pattern by evaluating interactions between all the brain functional networks. Moreover, the association between the significantly altered interactions and cognitive dysfunctions in autism is also investigated. We used resting-state fMRI data of 106 subjects (5-14 years, 46 ASD: five female, 60 HC: 18 female) to define the brain functional networks. Functional networks were calculated by applying four parcellation masks and their interactions were estimated using Pearson's correlation between pairs of them. Subsequently, for each mask, a graph was formed based on the connectome of interactions. Then, the local and global parameters of the graph were calculated. Finally, statistical analysis was performed using a two-sample t-test to highlight the significant differences between autistic and healthy control groups. Our corrected results show significant changes in the interaction of default mode, sensorimotor, visuospatial, visual, and language networks with other functional networks that can support the main cognitive theories of autism. We hope this finding sheds light on a better understanding of the neural underpinning of autism.

Detoxification Role of Metabolic Glutathione S-Transferase (GST) Genes in Blood Lead Concentrations of Jamaican Children with and without Autism Spectrum Disorder

Glutathione S-transferases (GST) are involved in the detoxification of exogenous chemicals including lead (Pb). Using data from 344 pairs of autism spectrum disorder (ASD) cases and age- and sex-matched typically developing (TD) controls (2−8 years old) from Jamaica, we investigated the interaction between three GST genes and ASD status as determinants of blood Pb concentrations (BPbCs). We found that ASD cases had lower geometric mean BPbCs than TD children (1.74 vs. 2.27 µg/dL, p < 0.01). Using a co-dominant genetic model, ASD cases with the Ile/Val genotype for the GSTP1 Ile105Val polymorphism had lower GM BPbCs than TD controls, after adjusting for a known interaction between GSTP1 and GSTT1, child’s parish, socioeconomic status, consumption of lettuce, fried plantains, and canned fish (Ile/Val: 1.78 vs. 2.13 µg/dL, p = 0.03). Similarly, among carriers of the I/I or I/D (I*) genotype for GSTT1 and GSTM1, ASD cases had lower adjusted GM BPbCs than TD controls (GSTT1 I*: 1.61 vs. 1.91 µg/dL, p = 0.01; GSTM1 I*: 1.71 vs. 2.04 µg/dL, p = 0.01). Our findings suggest that genetic polymorphisms in GST genes may influence detoxification of Pb by the enzymes they encode in Jamaican children with and without ASD.

Research-Based Intervention (RBI) for Autism Spectrum Disorder: Looking beyond Traditional Models and Outcome Measures for Clinical Trials

The rising prevalence of Autism Spectrum Disorders (ASD) has led to a quickly increasing need for effective interventions. Several criteria and measures have been developed to critically assess these interventions with particular focus on the evaluation of the efficacy. Given the huge diversity of ASD symptoms and the different levels of severity across individuals, identifying a one size fits all intervention approach is challenging, and the question What works and for whom? Remains still unanswered. Why do we seem to be dragging our feet on this fundamental issue? The main aim of this paper is to answer this question through four non-alternative points. First, there are a scarce number of studies with a solid methodology. Secondly, most trials on intervention efficacy for ASD are designed exclusively in terms of behavioral outcomes. Thirdly, there is a reduced use of biologically oriented outcome measures. Fourthly, in most clinical trials, appropriate practices emerging from research evidence are not systematically applied. A strong effort to improve the methodology of clinical trials is mandatory for the future of autism research. The development of a research-based intervention (RBI) perspective aimed at better integrating: (a) evidence-based approaches; (b) more sensitive behavioral outcome measures; and (c) biomarkers, with the aim of increasing a more detailed clustering of phenotypes, may strongly improve our approach to a precision medicine.

Potential protein markers in children with Autistic Spectrum Disorder (ASD) revealed by salivary proteomics

The lack of specific pharmacological therapy for Autistic Spectrum Disorder (ASD) and its clinical heterogeneity demand efforts directed toward the identification of biomarkers to aid in diagnosis. Proteomics offers a new perspective for studying the altered proteins associated with autism spectrum disorders (ASD) and we have saliva as an easy-to-collect biological fluid with important biomolecules for investigating biomarkers in various diseases. In this sense, saliva could be used to identify potential biomarkers of ASD. In the current work, saliva samples were collected from children with different degrees of ASD and healthy children and proteomics approaches were applied to generate data on differentially expressed proteins between groups which will serve as a basis for future validation studies as protein markers. Data are available via ProteomeXchange with identifier PXD030065. As results, 132 proteins were present in 80% of the saliva pools of all analyzed groups. Twenty-five proteins were identified as overexpressed in the group of severe and mild/moderate ASD carriers, among which, eight were identified as potential biomarkers for ASD.

Management of Autism Spectrum Disorder in Italian Units of Child and Adolescent Mental Health: Diagnostic and Referral Pathways

Overall, the present pilot study provides detailed information on clinical management for Autism Spectrum Disorder (ASD) referral and diagnosis processes that are mandatory for child and adolescent mental health management. The analysis of ASD management, even if carried out on a selected sample of Child and Adolescent Mental Health (CAMH) units, represents a good approximation of how, in Italian outpatient settings, children and adolescents with ASD are recognised and eventually diagnosed. One of the aims of the study was to verify the adherence of Italian CAMH units to international recommendations for ASD referral and diagnosis and whether these processes can be traced using individual chart reports. Overall, the analysis evidenced that Italian CAMH units adopt an acceptable standard for ASD diagnosis, although the reporting of the ASD managing process in the individual chart is not always accurate. Furthermore, data collected suggest some improvements that CAMH units should implement to fill the gap with international recommendations, namely, establishing a multidisciplinary team for diagnosis, improving the assessment of physical and mental conditions by the use of standardised tools, implementing a specific assessment for challenging behaviours that could allow timely and specific planning of intervention.

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.

Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression

BACKGROUND

The search of biomarkers in the field of depression requires easy implementable tests that are biologically rooted. Qualitative analysis of verbal fluency tests (VFT) are good candidates, but its cerebral correlates are unknown.

METHODS

We collected qualitative semantic and phonemic VFT scores along with grey and white matter anatomical MRI of depressed (n = 26) and healthy controls (HC, n = 25) women. Qualitative VFT variables are the "clustering score" (i.e. the ability to produce words within subcategories) and the "switching score" (i.e. the ability to switch between clusters). The clustering and switching scores were automatically calculated using a data-driven approach. Brain measures were cortical thickness (CT) and fractional anisotropy (FA). We tested for associations between CT, FA and qualitative VFT variables within each group.

RESULTS

Patients had reduced switching VFT scores compared to HC. Thicker cortex was associated with better switching score in semantic VFT bilaterally in the frontal (superior, rostral middle and inferior gyri), parietal (inferior parietal lobule including the supramarginal gyri), temporal (transverse and fusiform gyri) and occipital (lingual gyri) lobes in the depressed group. Positive association between FA and the switching score in semantic VFT was retrieved in depressed patients within the corpus callosum, right inferior fronto-occipital fasciculus, right superior longitudinal fasciculus extending to the anterior thalamic radiation (all p < 0.05, corrected).

CONCLUSION

Together, these results suggest that automatic qualitative VFT scores are associated with brain anatomy and reinforce its potential use as a surrogate for depression cerebral bases.

Saliva nitrite is higher in male children with autism spectrum disorder and positively correlated with serum nitrate

OBJECTIVES

Nitric oxide (NO) plays a vital role in neurological development. As an easily accessible and non-invasive fluid, saliva hasn't been evaluated for nitrite among children with autism spectrum disorder (ASD). This study aims to quantify saliva nitrite and explore its relation with serum NO.

METHODS

Saliva sampling and pretreatment methods were optimized, followed by NO measurement via chemiluminescence for 126 ASD children and 129 normally developing children (ND).

RESULTS

In the ASD group, saliva nitrite was significantly higher than that in the ND, with concentrations of 4.97 ± 3.77 μM and 2.66 ± 2.07 μM (p < 0.0001), respectively. Positive correlation was observed between saliva NO2- and serum NO3- in ASD children, which didn't exist in the ND group. Male children in the ASD group had significantly higher NO than that in boys of the ND group, without significant difference between girls in both groups. Correlation was not found between saliva or serum NO and severity of these ASD children.

DISCUSSION

It is reported for the first time that saliva nitrite was positively correlated with serum nitrate in ASD children, with significantly higher NO only in autistic boys. Non-invasive saliva might serve as a predictor of health status of ASD children.

Can stratification biomarkers address the heterogeneity of autism spectrum disorder?

The search for biomarkers for autism spectrum disorder (henceforth autism) has received a lot of attention due to their potential clinical relevance. The clinical and aetiological heterogeneity of autism suggests the presence of subgroups. The lack of identification of a valid diagnostic biomarker for autism, and the inconsistencies seen in studies assessing differences between autism and typically developing control groups, may be partially explained by the vast heterogeneity observed in autism. The focus now is to better understand the clinical and biological heterogeneity and identify stratification biomarkers, which are measures that describe subgroups of individuals with shared biology. Using stratification approaches to assess treatment within pre-defined subgroups could clarify who may benefit from different treatments and therapies, and ultimately lead to more effective individualised treatment plans.

Eye gaze as a biomarker in the recognition of autism spectrum disorder using virtual reality and machine learning: A proof of concept for diagnosis

The core symptoms of autism spectrum disorder (ASD) mainly relate to social communication and interactions. ASD assessment involves expert observations in neutral settings, which introduces limitations and biases related to lack of objectivity and does not capture performance in real-world settings. To overcome these limitations, advances in technologies (e.g., virtual reality) and sensors (e.g., eye-tracking tools) have been used to create realistic simulated environments and track eye movements, enriching assessments with more objective data than can be obtained via traditional measures. This study aimed to distinguish between autistic and typically developing children using visual attention behaviors through an eye-tracking paradigm in a virtual environment as a measure of attunement to and extraction of socially relevant information. The 55 children participated. Autistic children presented a higher number of frames, both overall and per scenario, and showed higher visual preferences for adults over children, as well as specific preferences for adults' rather than children's faces on which looked more at bodies. A set of multivariate supervised machine learning models were developed using recursive feature selection to recognize ASD based on extracted eye gaze features. The models achieved up to 86% accuracy (sensitivity = 91%) in recognizing autistic children. Our results should be taken as preliminary due to the relatively small sample size and the lack of an external replication dataset. However, to our knowledge, this constitutes a first proof of concept in the combined use of virtual reality, eye-tracking tools, and machine learning for ASD recognition. LAY SUMMARY: Core symptoms in children with ASD involve social communication and interaction. ASD assessment includes expert observations in neutral settings, which show limitations and biases related to lack of objectivity and do not capture performance in real settings. To overcome these limitations, this work aimed to distinguish between autistic and typically developing children in visual attention behaviors through an eye-tracking paradigm in a virtual environment as a measure of attunement to, and extraction of, socially relevant information.

Convergent Canonical Pathways in Autism Spectrum Disorder from Proteomic, Transcriptomic and DNA Methylation Data

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with extensive genetic and aetiological heterogeneity. While the underlying molecular mechanisms involved remain unclear, significant progress has been facilitated by recent advances in high-throughput transcriptomic, epigenomic and proteomic technologies. Here, we review recently published ASD proteomic data and compare proteomic functional enrichment signatures with those of transcriptomic and epigenomic data. We identify canonical pathways that are consistently implicated in ASD molecular data and find an enrichment of pathways involved in mitochondrial metabolism and neurogenesis. We identify a subset of differentially expressed proteins that are supported by ASD transcriptomic and DNA methylation data. Furthermore, these differentially expressed proteins are enriched for disease phenotype pathways associated with ASD aetiology. These proteins converge on protein–protein interaction networks that regulate cell proliferation and differentiation, metabolism, and inflammation, which demonstrates a link between canonical pathways, biological processes and the ASD phenotype. This review highlights how proteomics can uncover potential molecular mechanisms to explain a link between mitochondrial dysfunction and neurodevelopmental pathology.

Corpus callosum size and homotopic connectivity in Autism spectrum disorder

By examining how morphology of the corpus callosum (CC) in autism spectrum disorder (ASD) may affect functional communication across hemispheres, we hope to provide new insights into the structure-function relationship in the brain. We used a sample of 94 participants from the Autism Brain Imaging Data Exchange (ABIDE) database (55 typically-developing (TD) and 39 with ASD). The CC was segmented into five sub-regions (anterior, mid-anterior, central, mid-posterior, posterior) using FreeSurfer software, which were further examined for group differences. The total volume and specific sub-region volumes of the CC, and interhemispheric (homotopic) functional connectivity were calculated, along with the relationship between volume and connectivity. These measures were correlated with social ability assessed by the Social Responsiveness Scale (SRS). The central sub-region of CC was significantly smaller in ASD, although there was no group difference in total CC volume. ASD participants also showed stronger homotopic connectivity in the superior frontal gyrus. SRS scores were negatively correlated with the CC central sub-region volumes in ASD. The findings of this study add to the body of research showing morphological differences in the CC in ASD as well as connectivity differences. The absence of a significant relationship between structure and homotopic functional connectivity aligns with previous findings.

Oxytocin system dysfunction in patients with treatment-resistant schizophrenia: Alterations of blood oxytocin levels and effect of a genetic variant of OXTR

Treatment-resistant schizophrenia (TRS) has a quite complex pathophysiology that includes not only severe positive symptoms but also other symptom domains. Much attention has been devoted to the overlapping psychological and biological profiles of schizophrenia and autistic spectrum disorder (ASD). We compared TRS patients (n = 30) with schizophrenia patients in remission (RemSZ, n = 28) and ASD patients (n = 28), focusing on general cognitive and social cognitive impairment and oxytocin system dysfunction. Our analyses revealed that there was no difference in oxytocin concentration among the three groups. The TRS patients' oxytocin blood concentrations were positively correlated with their processing speed and theory-of-mind scores, whereas the RemSZ and ASD groups had no significant relation with any measures. Rs53576, a single nucleotide polymorphism on the oxytocin receptor gene, affected social cognition abilities in the schizophrenia group. Although the overall findings are preliminary, they indicate that oxytocin system dysfunction could be involved in the serious cognitive deficits in TRS patients. Further, these results suggest that patients with TRS might have early neurodevelopmental abnormalities based on their shared biological features with ASD patients.

An Epigenetically Distinct Subset of Children With Autism Spectrum Disorder Resulting From Differences in Blood Cell Composition

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that often involves impaired cognition, communication difficulties and restrictive, repetitive behaviors. ASD is extremely heterogeneous both clinically and etiologically, which represents one of the greatest challenges in studying the molecular underpinnings of ASD. While hundreds of ASD-associated genes have been identified that confer varying degrees of risk, no single gene variant accounts for >1% of ASD cases. Notably, a large number of ASD-risk genes function as epigenetic regulators, indicating potential epigenetic dysregulation in ASD. As such, we compared genome-wide DNA methylation (DNAm) in the blood of children with ASD (n = 265) to samples from age- and sex-matched, neurotypical controls (n = 122) using the Illumina Infinium HumanMethylation450 arrays. Results: While DNAm patterns did not distinctly separate ASD cases from controls, our analysis identified an epigenetically unique subset of ASD cases (n = 32); these individuals exhibited significant differential methylation from both controls than the remaining ASD cases. The CpG sites at which this subset was differentially methylated mapped to known ASD risk genes that encode proteins of the nervous and immune systems. Moreover, the observed DNAm differences were attributable to altered blood cell composition, i.e., lower granulocyte proportion and granulocyte-to-lymphocyte ratio in the ASD subset, as compared to the remaining ASD cases and controls. This ASD subset did not differ from the rest of the ASD cases in the frequency or type of high-risk genomic variants. Conclusion: Within our ASD cohort, we identified a subset of individuals that exhibit differential methylation from both controls and the remaining ASD group tightly associated with shifts in immune cell type proportions. This is an important feature that should be assessed in all epigenetic studies of blood cells in ASD. This finding also builds on past reports of changes in the immune systems of children with ASD, supporting the potential role of altered immunological mechanisms in the complex pathophysiology of ASD. The discovery of significant molecular and immunological features in subgroups of individuals with ASD may allow clinicians to better stratify patients, facilitating personalized interventions and improved outcomes.

Blood biomarker discovery for autism spectrum disorder: A proteomic analysis

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. A wide range of putative biological markers for ASD is currently being investigated. Proteomic analyses indicate that the levels of many proteins in plasma/serum are altered in ASD, suggesting that a panel of proteins may provide a blood biomarker for ASD. Serum samples from 76 boys with ASD and 78 typically developing (TD) boys, 18 months-8 years of age, were analyzed to identify possible early biological markers for ASD. Proteomic analysis of serum was performed using SomaLogic’s SOMAScan^TM assay 1.3K platform. A total of 1,125 proteins were analyzed. There were 86 downregulated proteins and 52 upregulated proteins in ASD (FDR < 0.05). Combining three different algorithms, we found a panel of 9 proteins that identified ASD with an area under the curve (AUC) = 0.8599±0.0640, with specificity and sensitivity of 0.8217±0.1178 and 0.835±0.1176, respectively. All 9 proteins were significantly different in ASD compared with TD boys, and were significantly correlated with ASD severity as measured by ADOS total scores. Using machine learning methods, a panel of serum proteins was identified that may be useful as a blood biomarker for ASD in boys. Further verification of the protein biomarker panel with independent test sets is warranted.

Emerging mechanisms of valproic acid-induced neurotoxic events in autism and its implications for pharmacological treatment

Autism spectrum disorder (ASD) is a sort of mental disorder marked by deficits in cognitive and communication abilities. To date no effective cure for this pernicious disease has been available. Valproic acid (VPA) is a broad-spectrum, antiepileptic drug, and it is also a potent teratogen. Epidemiological studies have shown that children exposed to VPA are at higher risk for ASD during the first trimester of their gestational development. Several animal and human studies have demonstrated important behavioral impairments and morphological changes in the brain following VPA treatment. However, the mechanism of VPA exposure-induced ASD remains unclear. Several factors are involved in the pathological phase of ASD, including aberrant excitation/inhibition of synaptic transmission, neuroinflammation, diminished neurogenesis, oxidative stress, etc. In this review, we aim to outline the current knowledge of the critical pathophysiological mechanisms underlying VPA exposure-induced ASD. This review will give insight toward understanding the complex nature of VPA-induced neuronal toxicity and exploring a new path toward the development of novel pharmacological treatment against ASD.

Associations of Metabolic Genes (GSTT1, GSTP1, GSTM1) and Blood Mercury Concentrations Differ in Jamaican Children with and without Autism Spectrum Disorder

We investigated interactive roles of three metabolic glutathione S-transferase (GST) genes (GSTP1, GSTT1, and GSTM1) and autism spectrum disorder (ASD) status in relation to blood Hg concentrations (BHC) of Jamaican children. We used data from 266 children (2-8 years) with ASD and their 1:1 age- and sex-matched typically developing (TD) controls. After adjusting General Linear Models for child’s age, socioeconomic status, consumption of leafy vegetables, fried plantain, canned fish, and the interaction between GSTP1 and GSTT1, we found significant interactions between GSTP1 and ASD status in relation to BHC either in a co-dominant or dominant genetic model for GSTP1(P < 0.001, P = 0.007, respectively). In the co-dominant model for the Ile105Val GSTP1 polymorphism, geometric mean (GM) BHC in ASD cases with genotype Ile/Ile were significantly higher than in cases with the Ile/Val genotype (0.73 vs. 0.48 µg/L, P = 0.01). In contrast, in TD controls with the Ile/Val genotype GM BHC were significantly higher than in those with the Ile/Ile genotype (0.72 vs. 0.49 µg/L, P = 0.03) or the Val/Val genotype (0.72 vs. 0.51 µg/L, P = 0.04). Although our findings are consistent with the role of GSTP1 in detoxification of Hg, replication in other populations is warranted.

Autism spectrum disorder in India: a scoping review

Autism is a grand challenge in global mental health to be dealt with on a priority basis. Phenotypic knowledge, biological understanding, and evidence-based intervention studies are all from western countries. We know very little about autism in the low- and middle-income countries (LMIC). Lack of infrastructure and difficulties in operationalizing research has widened the knowledge gap. We performed a comprehensive scoping review of research in Autism Spectrum Disorder in India to have an overall impression, identify gaps, and formulate evidence-based recommendations for further study. We searched PubMed, SCOPUS, and Cochrane Library to identify relevant Indian studies. A hundred and fifty-nine publications met the inclusion criteria. Most of the research contribution in autism is from few tertiary care medical centres, technological institutes, and not-for-profit organizations. We identified various themes of research like clinical profile, interventions, biomarkers, psychological, social, epidemiological, and risk factors. Evidence-based intervention studies, translation and adaptation of standard diagnostic instruments, and qualitative research on the experience of autism appeared to be state of the art. However, epidemiological studies, biomarkers identification, risk assessment studies were of low quality. There is a need for nationwide studies with representative sampling on epidemiology, biomarkers, and risk factors for a complete evaluation of the actual burden and biology of autism in India. Also, there is a need to design implementation research to evaluate the effectiveness of evidence-based interventions in routine healthcare settings. We recommend that future research should fill these gaps in understanding autism and improving its outcome in India.

A Novel UHPLC-MS Method Targeting Urinary Metabolomic Markers for Autism Spectrum Disorder

Autism spectrum disorder is a heterogeneous neurodevelopmental disease. Currently, no biomarker of this disease is known. Diagnosis is performed through observation, standardized behavioral scales, and interviews with parents. In practice, diagnosis is often delayed to the average age of four years or even more which adversely affects a child’s perspective. A laboratory method allowing to detect the disorder at earlier stages is of a great need, as this could help the patients to start with treatment at a younger age, even prior to the clinical diagnosis. Recent evidence indicates that metabolomic markers should be considered as diagnostic markers, also serving for further differentiation and characterization of different subgroups of the autism spectrum. In this study, we developed an ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry method for the simultaneous determination of six metabolites in human urine. These metabolites, namely methylguanidine, N-acetyl arginine, inosine, indole-3-acetic acid, indoxyl sulfate and xanthurenic acid were selected as potential biomarkers according to prior metabolomic studies. The analysis was carried out by means of reversed-phase liquid chromatography with gradient elution. Separation of the metabolites was performed on a Phenomenex Luna^® Omega Polar C18 (100 × 1.0 mm, 1.6 µm) column at a flow rate of 0.15 mL/min with acetonitrile/water 0.1% formic acid aqueous as the mobile phase. The analysis was performed on a group of children with autism spectrum disorder and age-matched controls. In school children, we have detected disturbances in the levels of oxidative stress markers connected to arginine and purine metabolism, namely methylguanidine and N-acetylargine. Also, products of gut bacteria metabolism, namely indoxyl sulfate and indole-3-acetic acid, were found to be elevated in the patients’ group. We can conclude that this newly developed method is fast, sensitive, reliable, and well suited for the quantification of proposed markers.

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.

Recent Progress on Relevant microRNAs in Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose pathogenesis is unclear and is affected by both genetic and environmental factors. The microRNAs (miRNAs) are a kind of single-stranded non-coding RNA with 20-22 nucleotides, which normally inhibit their target mRNAs at a post-transcriptional level. miRNAs are involved in almost all biological processes and are closely related to ASD and many other diseases. In this review, we summarize relevant miRNAs in ASD, and analyze dysregulated miRNAs in brain tissues and body fluids of ASD patients, which may contribute to the pathogenesis and diagnosis of ASD.

Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry

Data science and digital technologies have the potential to transform diagnostic classification. Digital technologies enable the collection of big data, and advances in machine learning and artificial intelligence enable scalable, rapid, and automated classification of medical conditions. In this review, we summarize and categorize various data-driven methods for diagnostic classification. In particular, we focus on autism as an example of a challenging disorder due to its highly heterogeneous nature. We begin by describing the frontier of data science methods for the neuropsychiatry of autism. We discuss early signs of autism as defined by existing pen-and-paper-based diagnostic instruments and describe data-driven feature selection techniques for determining the behaviors that are most salient for distinguishing children with autism from neurologically typical children. We then describe data-driven detection techniques, particularly computer vision and eye tracking, that provide a means of quantifying behavioral differences between cases and controls. We also describe methods of preserving the privacy of collected videos and prior efforts of incorporating humans in the diagnostic loop. Finally, we summarize existing digital therapeutic interventions that allow for data capture and longitudinal outcome tracking as the diagnosis moves along a positive trajectory. Digital phenotyping of autism is paving the way for quantitative psychiatry more broadly and will set the stage for more scalable, accessible, and precise diagnostic techniques in the field.

Social endophenotypes in autism spectrum disorder: A scoping review

Endophenotypes are measurable markers of genetic vulnerability to current or future disorder. Autism spectrum disorder (ASD) is well-suited to be examined within an endophenotype framework given past and current emphases on the broader autism phenotype and early detection. We conducted a scoping review to identify potential socially-related endophenotypes of ASD. We focused on paradigms related to sociality (e.g., theory of mind (TOM), social attention), which comprise most of this literature. We integrated findings from traditional behavioral paradigms with brain-based measures (e.g., electroencephalography, functional magnetic resonance imaging). Broadly, infant research regarding social attention and responsivity (Research Domain Criteria (RDoC) domain of affiliation) and attention to faces and voices (social communication) finds consistent abnormality in vulnerable infant siblings. Several additional paradigms that have shown differences in vulnerable infants and young children include animacy perception tasks (perception and understanding of others), measures of recognition and response to familiar faces (attachment), and joint attention and false-belief tasks (understanding mental states). Research areas such as alexithymia (the perception and understanding of self), empathic responding, and vocal prosody may hold interest; however, challenges in measurement across populations and age ranges is a limiting factor. Future work should address sex differences and age dependencies, specificity to ASD, and heterogeneous genetic pathways to disorder within samples individuals with ASD and relatives.

Changes in the development of subcortical structures in autism spectrum disorder

Many studies have reported abnormalities in the volume of subcortical structures in individuals with autism spectrum disorder (ASD), and many of these change with age. However, most studies that have investigated subcortical structures were cross-sectional and did not accurately segment the subcortical structures. In this study, we used volBrain, an automatic and reliable quantitative analysis tool, and a longitudinal design to examine developmental changes in the volume of subcortical structures in ASD, and quantified the relation between subcortical volume development and clinical correlates. Nineteen individuals with ASD (16 males; age: 12.53 ± 2.34 years at baseline; interval: 2.33 years) and 14 typically developing controls (TDC; 12 males; age: 13.50 ± 1.77 years at baseline; interval: 2.31 years) underwent T1-weighted MRI at two time points. Bilaterally, hippocampus volume increased from baseline to follow-up in both ASD and TDC, with no difference between groups. Left caudate and right thalamus volume decreased in ASD, but did not change in TDC. The decreases in left caudate and right thalamus volume were related to ASD social score. Right amygdala volume was larger in ASD than in TDC at baseline but not at follow-up. These results confirm previous cross-sectional findings regarding the development of subcortical structures in ASD. The association between developmental changes in left caudate and right thalamus volume and ASD social score offers an explanation for the social deficits in ASD. Results also captured the different abnormality of amygdala volume between childhood and late adolescence.

A Metabolomics Approach to Screening for Autism Risk in the Children's Autism Metabolome Project

Autism spectrum disorder (ASD) is biologically and behaviorally heterogeneous. Delayed diagnosis of ASD is common and problematic. The complexity of ASD and the low sensitivity of available screening tools are key factors in delayed diagnosis. Identification of biomarkers that reduce complexity through stratification into reliable subpopulations can assist in earlier diagnosis, provide insight into the biology of ASD, and potentially suggest targeted interventions. Quantitative metabolomic analysis was performed on plasma samples from 708 fasting children, aged 18 to 48 months, enrolled in the Children's Autism Metabolome Project (CAMP). The primary goal was to identify alterations in metabolism helpful in stratifying ASD subjects into subpopulations with shared metabolic phenotypes (i.e., metabotypes). Metabotypes associated with ASD were identified in a discovery set of 357 subjects. The reproducibility of the metabotypes was validated in an independent replication set of 351 CAMP subjects. Thirty-four candidate metabotypes that differentiated subsets of ASD from typically developing participants were identified with sensitivity of at least 5% and specificity greater than 95%. The 34 metabotypes formed six metabolic clusters based on ratios of either lactate or pyruvate, succinate, glycine, ornithine, 4-hydroxyproline, or α-ketoglutarate with other metabolites. Optimization of a subset of new and previously defined metabotypes into a screening battery resulted in 53% sensitivity (95% confidence interval [CI], 48%-57%) and 91% specificity (95% CI, 86%-94%). Thus, our metabolomic screening tool detects more than 50% of the autistic participants in the CAMP study. Further development of this metabolomic screening approach may facilitate earlier referral and diagnosis of ASD and, ultimately, more targeted treatments. LAY SUMMARY: Analysis of a selected set of metabolites in blood samples from children with autism and typically developing children identified reproducible differences in the metabolism of about half of the children with autism. Testing for these differences in blood samples can be used to help screen children as young as 18 months for risk of autism that, in turn, can facilitate earlier diagnoses. In addition, differences may lead to biological insights that produce more precise treatment options. We are exploring other blood-based molecules to determine if still a higher percentage of children with autism can be detected using this strategy. Autism Res 2020, 13: 1270-1285. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.

Nuclear Factor Kappa B in Autism Spectrum Disorder: A Systematic Review

BACKGROUND

The nuclear factor kappa B (NF-κB) is composed of a series of transcription factors, which are involved in the expression of a plethora of target genes, many of these genes contributing to the regulation of inflammatory responses. Consistent with its central role in inflammatory responses, existing studies of the neurobiological basis for ASD propose the involvement of NF-κB in the etiology of this disorder.

OBJECTIVES

The present review aimed to systematically characterize extant literatures regarding the role of NF-κB in the etiology of ASD through data derived from both human studies and animal models.

METHODS

A systematic electronic search was conducted for records indexed within Pubmed, EMBASE, or Web of Science to identify potentially eligible studies. Study inclusion and data extraction was agreed by two independent authors after reviewing the abstract and full text.

RESULTS

Among the 371 articles identified in the initial screening, 18 articles met the eligibility criteria for this review, including 14 human case-control studies compared the expression or activation of NF-κB between ASD cases and controls as well as 4 animal studies used mouse model of ASD to examine the level of NF-κB and further evaluate its changes after different drug treatments. These included 18 studies, although relatively small in quantity, appear to support the role of NF-κB in the etiology of ASD.

CONCLUSIONS

Evidence generated from both human studies and animal models supported the involvement of NF-κB in the neurobiological basis of ASD, despite some concern about whether it functions as a primary contributor causes ASD onset or rather an ancillary factor regulates ASD pathogenesis. The increased understanding of NF-κB in the neurobiological basis of ASD could aid the emergence of clinically relevant diagnostic biomarkers and novel therapeutic strategies acting on the underlying disease pathogenesis. These results suggested that potential methodological differences between studies need to be accounted for and keep open the discussion over the existence of aberrantly NF-κB signaling in ASD subjects.

Medium and long-term effects of low doses of Chlorpyrifos during the postnatal, preweaning developmental stage on sociability, dominance, gut microbiota and plasma metabolites

Autism spectrum disorder (ASD) is a complex neurodevelopmental pathology characterized by altered verbalizations, reduced social interaction behavior, and stereotypies. Environmental factors have been associated with its development. Some researchers have focused on pesticide exposure. Chlorpyrifos (CPF) is the most used Organophosphate. Previous developmental studies with CPF showed decreased, enhanced or no effect on social outcomes eminently in mice. The study of CPF exposure during preweaning stages on social behavior is sparse in mice and non-existent in rats. d stressors could be at the basis of ASD development, and around postnatal day 10 in the rat is equivalent to the human birthday in neurodevelopmental terms. We explored the effects of exposure to low doses (1mg/kg/mL/day) of CPF during this stage regarding: sociability, dominance gut microbiome and plasma metabolomic profile, since alterations in these systems have also been linked to ASD. There was a modest influence of CPF on social behavior in adulthood, with null effects during adolescence. Dominance and hierarchical status were not affected by exposure. Dominance status explained the significant reduction in reaction to social novelty observed on the sociability test. CPF induced a significant gut microbiome dysbiosis and triggered a hyperlipidemic, hypoglycemic/hypogluconeogenesis and a general altered cell energy production in females. These behavioral results in rats extend and complement previous studies with mice and show novel influences on gut metagenomics and plasma lipid profile and metabolomics, but do not stablish a relation between the exposure to CPF and the ASD phenotype. The effects of dominance status on reaction to social novelty have an important methodological meaning for future research on sociability.

Fourier Transform Infrared Spectroscopy Based Complementary Diagnosis Tool for Autism Spectrum Disorder in Children and Adolescents

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that begins early in life and continues lifelong with strong personal and societal implications. It affects about 1%-2% of the children population in the world. The absence of auxiliary methods that can complement the clinical evaluation of ASD increases the probability of false identification of the disorder, especially in the case of very young children. In this study, analytical models for auxiliary diagnosis of ASD in children and adolescents, based on the analysis of patients' blood serum ATR-FTIR (Attenuated Total Reflectance-Fourier Transform Infrared) spectra, were developed. The models use chemometrics (either Principal Component Analysis (PCA) or Partial Least Squares Discriminant Analysis (PLS-DA)) methods, with the infrared spectra being the X-predictor variables. The two developed models exhibit excellent classification performance for samples of ASD individuals vs. healthy controls. Interestingly, the simplest, unsupervised PCA-based model results to have a global performance identical to the more demanding, supervised (PLS-DA)-based model. The developed PCA-based model thus appears as the more economical alternative one for use in the clinical environment. Hierarchical clustering analysis performed on the full set of samples was also successful in discriminating the two groups.

Applications of Near Infrared Photoacoustic Spectroscopy for Analysis of Human Respiration: A Review

In this review, applications of near-infrared photoacoustic spectroscopy are presented as an opportunity to evaluate human respiration because the measurement of breath is fast, intact and simple to implement. Recently, analytical methods for measuring biomarkers in exhaled air have been extensively developed. With laser-based photoacoustic spectroscopy, volatile organic compounds can be identified with high sensitivity, at a high rate, and with very good selectivity. The literature review has shown the applicability of near-infrared photoacoustic spectroscopy to one of the problems of the real world, i.e., human health. In addition, the review will consider and explore different breath sampling methods for human respiration analysis.

Serotonin (5-HT) neuron-specific inactivation of Cadherin-13 impacts 5-HT system formation and cognitive function

Genome-wide screening approaches identified the cell adhesion molecule Cadherin-13 (CDH13) as a risk factor for neurodevelopmental disorders, nevertheless the contribution of CDH13 to the disease mechanism remains obscure. CDH13 is involved in neurite outgrowth and axon guidance during early brain development and we previously provided evidence that constitutive CDH13 deficiency influences the formation of the raphe serotonin (5-HT) system by modifying neuron-radial glia interaction. Here, we dissect the specific impact of CDH13 on 5-HT system development and function using a 5-HT neuron-specific Cdh13 knockout mouse model (conditional Cdh13 knockout, Cdh13 cKO). Our results show that exclusive inactivation of CDH13 in 5-HT neurons selectively increases 5-HT neuron density in the embryonic dorsal raphe, with persistence into adulthood, and serotonergic innervation of the developing prefrontal cortex. At the behavioral level, adult Cdh13 cKO mice display delayed acquisition of several learning tasks and a subtle impulsive-like phenotype, with decreased latency in a sociability paradigm alongside with deficits in visuospatial memory. Anxiety-related traits were not observed in Cdh13 cKO mice. Our findings further support the critical role of CDH13 in the development of dorsal raphe 5-HT circuitries, a mechanism that may underlie specific clinical features observed in neurodevelopmental disorders.

Higher Levels of Low Molecular Weight Sulfur Compounds and Homocysteine Thiolactone in the Urine of Autistic Children

In this study, the levels of concentration of homocysteine thiolactone (HTL), cysteine (Cys), and cysteinylglycine (CysGly) in the urine of autistic and non-autistic children were investigated and compared. HTL has never been analyzed in autistic children. The levels of low molecular weight sulfur compounds in the urine of both groups were determined by validated methods based on high-performance liquid chromatography with spectrofluorometric and diode-array detectors. The statistical data show a significant difference between the examined groups. Children with autism were characterized by a significantly higher level of HTL (p = 5.86 × 10⁻⁸), Cys (p = 1.49 × 10⁻¹⁰) and CysGly (p = 1.06 × 10⁻⁸) in urine compared with the control group. A difference in the p-value of <0.05 is statistically significant. Higher levels of HTL, Cys, and CysGly in the urine of 41 children with autism, aged 3 to 17, were observed. The obtained results may indicate disturbances in the metabolism of methionine, Cys, and glutathione in some autistic patients. These preliminary results suggest that further research with more rigorous designs and a large number of subjects is needed.

Study protocol for an evaluation of ASDetect - a Mobile application for the early detection of autism

Background

Autism Spectrum Conditions (ASC) can be reliably diagnosed by 24 months of age. However, despite the well-known benefits of early intervention, there is still a research-practice gap in the timely identification of ASC, particularly in low-resourced settings. The Social Attention and Communication Surveillance (SACS) tool, which assesses behavioural markers of autism between 12 to 24 months of age, has been implemented in Maternal and Child Health (MCH) settings, with excellent psychometric properties. ASDetect is a free mobile application based on the SACS, which is designed to meet the need for an effective, evidence-based tool for parents, to learn about children’s early social-communication development and assess their child’s ‘likelihood’ for ASC.

Study aims

The primary aim of this study is to evaluate the psychometric properties of ASDetect in the early detection of children with ASC. A secondary aim is to assess ASDetect’s acceptability and parental user experience with the application.

Methods

Families are recruited to download the application and participate in the study via social media, health professionals (e.g., MCH nurses, paediatricians) and word of mouth. All participating caregivers complete a demographic questionnaire, survey regarding their user experience, and the Social Responsiveness Scale-2 (SRS-2), an autism screening questionnaire; they are also invited to participate in focus groups. Children identified at ‘high likelihood’ for ASC based on the ASDetect results, the SRS-2 or parental and/or professional concerns undergo a formal, gold-standard, diagnostic assessment. Receiver Operating Characteristic analyses will be used to assess psychometric properties of ASDetect. Thematic analyses will be used to explore themes arising in the focus groups to provide insights regarding user experiences with the app. Multiple regression analyses will be carried out to determine the extent to which demographic factors, parental stress and beliefs on health surveillance and child results on ASDetect are associated with the parental user-experience of the application.

Discussion

With a strong evidence-base and global access, ASDetect has the potential to empower parents by providing them with knowledge of their child’s social-communication development, validating and reassuring any parental concerns, and supporting them in communicating with other health professionals, ultimately enhancing child and family outcomes and well-being.

Identification, Evaluation, and Management of Children With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with reported prevalence in the United States of 1 in 59 children (approximately 1.7%). Core deficits are identified in 2 domains: social communication/interaction and restrictive, repetitive patterns of behavior. Children and youth with ASD have service needs in behavioral, educational, health, leisure, family support, and other areas. Standardized screening for ASD at 18 and 24 months of age with ongoing developmental surveillance continues to be recommended in primary care (although it may be performed in other settings), because ASD is common, can be diagnosed as young as 18 months of age, and has evidenced-based interventions that may improve function. More accurate and culturally sensitive screening approaches are needed. Primary care providers should be familiar with the diagnostic criteria for ASD, appropriate etiologic evaluation, and co-occurring medical and behavioral conditions (such as disorders of sleep and feeding, gastrointestinal tract symptoms, obesity, seizures, attention-deficit/hyperactivity disorder, anxiety, and wandering) that affect the child's function and quality of life. There is an increasing evidence base to support behavioral and other interventions to address specific skills and symptoms. Shared decision making calls for collaboration with families in evaluation and choice of interventions.  This single clinical report updates the 2007 American Academy of Pediatrics clinical reports on the evaluation and treatment of ASD in one publication with an online table of contents and section view available through the American Academy of Pediatrics Gateway to help the reader identify topic areas within the report.

Urinary NOx, a novel potential biomarker for autism spectrum disorder

Nitric oxide (NO) participates in many physiological and pathological processes in human. Urine tests tell a lot about health, which are convenient and harmless. Redox stress, including imbalance of reactive nitrogen species and its metabolites NO_x, has been gaining increased attention in autism spectrum disorder (ASD) research. However, concentrations of urinary nitrite and nitrate among the ASD population stay unclear. In this study, nitrite and nitrate were precisely measured in urine specimens from 44 ASD children, 30 healthy children (the control group) and 28 healthy adults with an optimized and validated analytic method. For the first time, concentrations of urinary NO_x in ASD and healthy children were reported. Nitrite in the ASD population is higher than in the control group, with concentrations of 0.8708 ± 0.1121 μM (0.1556-3.0393 μM) and 0.5938 ± 0.07276 μM (0.1134-2.1004 μM) (p = 0.0420), respectively. Nitrite in the adult groups is 0.5808 ± 0.0985 μM (0.0808-1.9335 μM), which is similar to that in the control group. On the contrary, urinary nitrate concentration in ASD children is lower than that in the control group, which are 2.875 ± 0.2716 mM (0.3264-7.1835 mM) and 4.558 ± 0.5915 mM (1.1860-15.8555 mM) (p = 0.0133), respectively. Nitrate in adults is also significantly lower than that in the control, 2.799 ± 0.3640 mM (0.2507-8.6978 mM) and 4.558 ± 0.5915 mM (p = 0.0146), respectively. Nitrite/nitrate ratios for ASD and the control groups were 0.3496 ± 0.04382 x 10^-3 and 0.1604 ± 0.01862 x 10^-3 (p = 0.0002), which again indicated the probability of NO_x as a novel biomarker. Furthermore, no correlation between NO_x and gender, as well as sample collection timing was found. Taken together, the association between NO_x and ASD was significant. Urinary nitrite, nitrate and NO₂^-/NO₃^-, might serve as a new biomarker for ASD diagnosis during pursuit of harmless, fast, and convenient diagnostic method. Further studies are needed for the metabolic pathways of NO_x in ASD pathogenesis.

Influence of the Type of Delivery, Use of Oxytocin, and Maternal Age on POU5F1 Gene Expression in Stem Cells Derived from Wharton's Jelly within the Umbilical Cord

The paper presents an evaluation of the POU5F1 gene expression in mesenchymal stem cells derived from Wharton's jelly within the umbilical cord, collected from 36 patients during labor. The study is the first one to show that the expression of POU5F1 in mesenchymal stem cells has been dependent on maternal age, birth order, route of delivery, and use of oxytocin. Our research proves that the POU5F1 gene expression in mesenchymal stem cells decreases with each subsequent pregnancy and delivery. Wharton's jelly stem cells obtained from younger women and during their first delivery, as well as patients treated with oxytocin, show higher POU5F1 gene expression when compared with the subsequent deliveries. This leads to a conclusion that they are characterized by a lower level of differentiation, which in turn results in their greater plasticity and greater proliferative potential. Probably, they are also clinically more useful.

IL-37 is increased in brains of children with autism spectrum disorder and inhibits human microglia stimulated by neurotensin

Autism spectrum disorder (ASD) does not have a distinct pathogenesis or effective treatment. Increasing evidence supports the presence of immune dysfunction and inflammation in the brains of children with ASD. In this report, we present data that gene expression of the antiinflammatory cytokine IL-37, as well as of the proinflammatory cytokines IL-18 and TNF, is increased in the amygdala and dorsolateral prefrontal cortex of children with ASD as compared to non-ASD controls. Gene expression of IL-18R, which is a receptor for both IL-18 and IL-37, is also increased in the same brain areas of children with ASD. Interestingly, gene expression of the NTR3/sortilin receptor is reduced in the amygdala and dorsolateral prefrontal cortex. Pretreatment of cultured human microglia from normal adult brains with human recombinant IL-37 (1 to 100 ng/mL) inhibits neurotensin (NT)-stimulated secretion and gene expression of IL-1β and CXCL8. Another key finding is that NT, as well as the proinflammatory cytokines IL-1β and TNF increase IL-37 gene expression in cultured human microglia. The data presented here highlight the connection between inflammation and ASD, supporting the development of IL-37 as a potential therapeutic agent of ASD.