Urinary Markers of Oxidative Stress in Children with Autism Spectrum Disorder (ASD)

Shorter telomere length in children with autism spectrum disorder is associated with oxidative stress

Objective

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder caused by a complex interaction between genetic and environmental risk factors. The balance between antioxidant capacity and oxidative stress (OS) induced free radicals may be crucial during the pathophysiological development of ASD.

Methods

In this study, 96 children with ASD who met the diagnostic and statistical manual of mental disorders were collected, and the number of children in the typical development (TD) group was matched by 1:1. Digital PCR (dPCR) for telomere length (TL) expression in ASD in peripheral blood leukocytes. Urine levels of 8-hydroxy-2-deoxyguanosine (8-OHdG) content were measured by tandem triple quadrupole mass spectrometry and corrected by urinary creatinine levels. The levels of superoxide dismutase (SOD), catalase (CAT), and capacity (AOC) were detected by kits.

Results

The TL of the ASD group was shorter than the TD group (p < 0.01) and had some accurate predictive significance for the identification of ASD (AUC = 0.632, 95% CI: 0.533-0.710, p = 0.002). Both 8-OHdG content and SOD activity in the ASD group were significantly higher than those in the TD group (p < 0.05). Shortened TL (Monofactor: 2.20 (1.22, 3.96), p = 0.009; Multifactor: 2.22 (1.22, 4.00), p = 0.008) and reduced CAT activity (Monofactor: 2.31 (1.28, 4.17), p = 0.006; Multifactor: 2.31 (1.28, 4.18), p = 0.006) are risk factors for the development of ASD, while reduced 8-OHdG content (Monofactor: 0.29 (0.14, 0.60), p = 0.001; Multifactor: 0.27 (0.13, 0.57), p = 0.001) and reduced SOD activity (Monofactor: 0.55 (0.31, 0.98), p = 0.042; Multifactor: 0.54 (0.30, 0.98), p = 0.042) are protective factors for the development of ASD.

Conclusion

In this study, TL and OS were significantly different between the ASD group and the TD group. As guanine-rich telomere sequences were likely damaged by oxygen free radicals, creating OS, which is a factor in the incidence and progression of ASDs. In conclusion, oxidative damage occurs in the bodies of children with ASD, which may lead to sustained disease progression and severe clinical manifestations. We assume that timely supplementation of antioxidants is very likely to be a potential treatment for early intervention in children with ASD. Identification and detection of OS-related biomarkers may contribute to early diagnosis and timely interventions in young patients with ASD.

Relationship between Excreted Uremic Toxins and Degree of Disorder of Children with ASD

Autism spectrum disorder (ASD) is a complex developmental disorder in which communication and behavior are affected. A number of studies have investigated potential biomarkers, including uremic toxins. The aim of our study was to determine uremic toxins in the urine of children with ASD (143) and compare the results with healthy children (48). Uremic toxins were determined with a validated high-performance liquid chromatography coupled to mass spectrometry (LC-MS/MS) method. We observed higher levels of p-cresyl sulphate (pCS) and indoxyl sulphate (IS) in the ASD group compared to the controls. Moreover, the toxin levels of trimethylamine N-oxide (TMAO), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were lower in ASD patients. Similarly, for pCS and IS in children classified, according to the intensity of their symptoms, into mild, moderate, and severe, elevated levels of these compounds were observed. For mild severity of the disorder, elevated levels of TMAO and comparable levels of SDMA and ADMA for ASD children as compared to the controls were observed in the urine. For moderate severity of ASD, significantly elevated levels of TMAO but reduced levels of SDMA and ADMA were observed in the urine of ASD children as compared to the controls. When the results obtained for severe ASD severity were considered, reduced levels of TMAO and comparable levels of SDMA and ADMA were observed in ASD children.

Correlation and predictive ability of sensory characteristics and social interaction in children with autism spectrum disorder

Background

Individuals with autism spectrum disorder (ASD) often have different social characteristics and particular sensory processing patterns, and these sensory behaviors may affect their social functioning. The objective of our study is to investigate the sensory profiles of children with ASD and their association with social behavior. Specifically, we aim to identify the predictive role of sensory processing in social functioning.

Methods

The Short Sensory Profile (SSP) was utilized to analyze sensory differences between ASD children and their peers. The Social Responsiveness Scale (SRS) and other clinical scales were employed to assess the social functioning of children with ASD. Additionally, the predictive ability of sensory perception on social performance was discussed using random forest and support vector machine (SVM) models.

Results

The SSP scores of ASD children were lower than those of the control group, and there was a significant negative correlation between SSP scores and clinical scale scores (P < 0.05). The random forest and SVM models, using all the features, showed higher sensitivity, while the random forest model with 7-feature factors had the highest specificity. The area under the receiver operating characteristic (ROC) curve (AUC) for all the models was higher than 0.8.

Conclusion

Autistic children in our study have different patterns of sensory processing than their peers, which are significantly related to their patterns of social functioning. Sensory features can serve as a good predictor of social functioning in individuals with ASD.

Measuring Some Oxidative Stress Biomarkers in Autistic Syrian Children and Their Siblings: A Case-Control Study

Objective:

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder whose cause remains unknown. Oxidative stress is one of the possible causes of many disorders, including neurological ones. This study aims to measure some oxidative stress biomarkers (Malondialdehyde “MDA,” Advanced Oxidation Protein Product “AOPP,” Glutathione “GSH”) within Syrian children with ASD.

Methods:

MDA, AOPP & GSH were measured in the plasma of a total of 60 children. The ages of the children ranged from 1 to 13 years old. Thirty children had ASD and were compared with 30 controls that don’t have ASD. Fifteen of the controls were siblings of an ASD child, while the remaining 15 had no relations with ASD.

Results:

MDA and AOPP plasma levels were higher in ASD children compared with non-related controls (P = .0001). However, there were no significant differences between MDA and AOPP plasma levels in ASD children in comparison with related controls (P > .05). Alternatively, GSH plasma levels were lower in ASD children compared with both related and non-related controls (P = .0001).

Conclusion:

Further studies are needed to investigate more regarding the diagnostic use of oxidative stress biomarkers, and the therapeutic use of antioxidants in children affected with the autism spectrum disorder.

Maternal obesity, diabetes, preeclampsia, and asthma during pregnancy and likelihood of autism spectrum disorder with gastrointestinal disturbances in offspring

LAY ABSTRACT

Autism spectrum disorder is heterogeneous and often accompanied by co-occurring conditions. Previous studies have shown that maternal health conditions during pregnancy including obesity, diabetes, preeclampsia, and asthma were associated with increased likelihood of autism. However, little has been done examining the likelihood associated with autism with co-occurring conditions. This study assessed these maternal health conditions in relationship to autism and gastrointestinal disturbances, a common co-occurring condition in children diagnosed with autism. Data included 308,536 mother-child pairs from one integrated health care system with comprehensive electronic medical records. Among the study cohort, 5,131 (1.7%) children had a diagnosis of autism by age 5. Gastrointestinal disturbances were present in 35.4% of children diagnosed with autism and 25.1% of children without autism diagnoses. Our results showed that each of the four maternal health conditions during pregnancy was associated with increased likelihood of gastrointestinal disturbances, autism without gastrointestinal disturbances, and autism with gastrointestinal disturbances. For all four maternal health conditions, the association was greatest for likelihood of autism with gastrointestinal disturbances. Given that children diagnosed with autism are more likely to have gastrointestinal disturbances and over 80% of gastrointestinal disturbances in this cohort were diagnosed prior to autism diagnosis, this study suggests that there may be common biological pathways between autism and gastrointestinal disturbances impacted by these maternal exposures. Future studies are warranted to assess associations between different exposures and autism with other co-occurring conditions to increase our understanding of autism heterogeneity.

Multivariate Analysis of Metabolomic and Nutritional Profiles among Children with Autism Spectrum Disorder

There have been promising results regarding the capability of statistical and machine-learning techniques to offer insight into unique metabolomic patterns observed in ASD. This work re-examines a comparative study contrasting metabolomic and nutrient measurements of children with ASD (n = 55) against their typically developing (TD) peers (n = 44) through a multivariate statistical lens. Hypothesis testing, receiver characteristic curve assessment, and correlation analysis were consistent with prior work and served to underscore prominent areas where metabolomic and nutritional profiles between the groups diverged. Improved univariate analysis revealed 46 nutritional/metabolic differences that were significantly different between ASD and TD groups, with individual areas under the receiver operator curve (AUROC) scores of 0.6–0.9. Many of the significant measurements had correlations with many others, forming two integrated networks of interrelated metabolic differences in ASD. The TD group had 189 significant correlation pairs between metabolites, vs. only 106 for the ASD group, calling attention to underlying differences in metabolic processes. Furthermore, multivariate techniques identified potential biomarker panels with up to six metabolites that were able to attain a predictive accuracy of up to 98% for discriminating between ASD and TD, following cross-validation. Assessing all optimized multivariate models demonstrated concordance with prior physiological pathways identified in the literature, with some of the most important metabolites for discriminating ASD and TD being sulfate, the transsulfuration pathway, uridine (methylation biomarker), and beta-amino isobutyrate (regulator of carbohydrate and lipid metabolism).

Identification of Pathogenetic Brain Regions via Neuroimaging Data for Diagnosis of Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a kind of neurodevelopmental disorder that often occurs in children and has a hidden onset. Patients usually have lagged development of communication ability and social behavior and thus suffer an unhealthy physical and mental state. Evidence has indicated that diseases related to ASD have commonalities in brain imaging characteristics. This study aims to study the pathogenesis of ASD based on brain imaging data to locate the ASD-related brain regions. Specifically, we collected the functional magnetic resonance image data of 479 patients with ASD and 478 normal subjects matched in age and gender and used a machine-learning framework named random support vector machine cluster to extract distinctive brain regions from the preprocessed data. According to the experimental results, compared with other existing approaches, the method used in this study can more accurately distinguish patients from normal individuals based on brain imaging data. At the same time, this study found that the development of ASD was highly correlated with certain brain regions, e.g., lingual gyrus, superior frontal gyrus, medial gyrus, insular lobe, and olfactory cortex. This study explores the effectiveness of a novel machine-learning approach in the study of ASD brain imaging and provides a reference brain area for the medical research and clinical treatment of ASD.

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.

COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification, allows to analyze the presence of the most common microbial organisms, their antibiotic resistance, the severity of the infection and the set of the most probable geographical locations from which the studied strain could have originated. The online platform integrates a user friendly interface which allows easy visualization of the results. We envision this tool will not only have immediate implications for management of the ongoing COVID-19 pandemic, but will also improve our readiness to respond to other infectious outbreaks.

How Robust is the Evidence for a Role of Oxidative Stress in Autism Spectrum Disorders and Intellectual Disabilities?

Growing interest in the pathogenesis of autism spectrum disorders (ASDs) and other intellectual and developmental disabilities (IDD) has led to emerging evidence implicating a role for oxidative stress. However, understanding the strength of this association is made challenging by the use of a variety of purported biomarkers of oxidative stress, many of which have either uncertain specificity or flawed methods of analysis. This review aims to address this issue, which is widespread in the ASD and IDD literature, by providing readers with information concerning the strengths and limitations of the choice and analysis of biomarkers of oxidative stress. We highlight that biomarkers and assays should be specific, sensitive, reproducible, precise, robust, and chosen with careful consideration. Future studies should be sufficiently powered and address sample collection, processing, and storage which are, additionally, poorly considered, sources of bad practice, and potential errors. Only with these issues considered, will the data lead to conclusions as to the precise role of oxidative stress in ASDs and IDD.

Disruption of circadian rhythm and risk of autism spectrum disorder: role of immune-inflammatory, oxidative stress, metabolic and neurotransmitter pathways

Circadian rhythms in most living organisms are regulated by light and synchronized to an endogenous biological clock. The circadian clock machinery is also critically involved in regulating and fine-tuning neurodevelopmental processes. Circadian disruption during embryonic development can impair crucial phases of neurodevelopment. This can contribute to neurodevelopmental disorders like autism spectrum disorder (ASD) in the offspring. Increasing evidence from studies showing abnormalities in sleep and melatonin as well as genetic and epigenetic changes in the core elements of the circadian pathway indicate a pivotal role of circadian disruption in ASD. However, the underlying mechanistic basis through which the circadian pathways influence the risk and progression of ASD are yet to be fully discerned. Well-recognized mechanistic pathways in ASD include altered immune-inflammatory, nitro oxidative stress, neurotransmission and synaptic plasticity, and metabolic pathways. Notably, all these pathways are under the control of the circadian clock. It is thus likely that a disrupted circadian clock will affect the functioning of these pathways. Herein, we highlight the possible mechanisms through which aberrations in the circadian clock might affect immune-inflammatory, nitro-oxidative, metabolic pathways, and neurotransmission, thereby driving the neurobiological sequelae leading to ASD.

Folic acid ameliorates neonatal isolation-induced autistic like behaviors in rats: epigenetic modifications of BDNF and GFAP promotors

The current study investigated the role of epigenetic dysregulation of brain derived neurotrophic factor (BDNF) and glial fibrillary acidic protein (GFAP) genes and oxidative stress as possible mechanisms of autistic-like behaviors in neonatal isolation model in rats and the impact of folic acid administration on these parameters. Forty Wistar albino pups were used as follows: control, folic acid administered, isolated, and isolated folic acid treated groups. Isolated pups were separated from their mothers for 90 min daily from postnatal day (PND) 1 to 11. Pups (isolated or control) received either the vehicle or folic acid (4 mg/kg/day) orally from PND 1 to 29. Behavioral tests were done from PND 30 to 35. Oxidative stress markers and antioxidant defense in the frontal cortex homogenate were determined. DNA methylation of BDNF and GFAP genes was determined by qPCR. Histopathological examination was carried out. Neonatal isolation produced autistic-like behaviors that were associated with BDNF and GFAP hypomethylation, increased oxidative stress, increased inflammatory cell infiltration, and structural changes in the frontal cortex. Folic acid administration concurrently with isolation reduced neonatal isolation-induced autistic-like behaviors, decreased oxidative stress, regained BDNF and GFAP gene methylation, and ameliorated structural changes in the frontal cortices of isolated folic acid treated rats. Novelty: Neonatal isolation induces "autistic-like" behavior and these behaviors are reversed by folic acid supplementation. Neonatal isolation induces DNA hypomethylation of BDNF and GFAP, increased oxidative stress markers, and neuroinflammation. All of these changes were reversed by daily folic acid supplementation.

Neuroprotective Effects of Quercetin in Pediatric Neurological Diseases

Oxidative stress is a crucial event underlying several pediatric neurological diseases, such as the central nervous system (CNS) tumors, autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Neuroprotective therapy with natural compounds used as antioxidants has the potential to delay, ameliorate or prevent several pediatric neurological diseases. The present review provides an overview of the most recent research outcomes following quercetin treatment for CNS tumors, ASD and ADHD as well as describes the potential in vitro and in vivo ameliorative effect on oxidative stress of bioactive natural compounds, which seems like a promising future therapy for these diseases. The neuroprotective effects of quercetin against oxidative stress can also be applied in the management of several neurodegenerative disorders with effects such as anti-cancer, anti-inflammatory, anti-viral, anti-obesity and anti-microbial. Therefore, quercetin appears to be a suitable adjuvant for therapy against pediatric neurological diseases.

The role of glutathione redox imbalance in autism spectrum disorder: A review

The role of glutathione in autism spectrum disorder (ASD) is emerging as a major topic, due to its role in the maintenance of the intracellular redox balance. Several studies have implicated glutathione redox imbalance as a leading factor in ASD, and both ASD and many other neurodevelopmental disorders involve low levels of reduced glutathione (GSH), high levels of oxidized glutathione (GSSG), and abnormalities in the expressions of glutathione-related enzymes in the blood or brain. Glutathione metabolism, through its impact on redox environment or redox-independent mechanisms, interferes with multiple mechanisms involved in ASD pathogenesis. Glutathione-mediated regulation of glutamate receptors [e.g., N-methyl-d-aspartate (NMDA) receptor], as well as the role of glutamate as a substrate for glutathione synthesis, may be involved in the regulation of glutamate excitotoxicity. However, the interaction between glutathione and glutamate in the pathogenesis of brain diseases may vary from synergism to antagonism. Modulation of glutathione is also associated with regulation of redox-sensitive transcription factors nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1) and downstream signaling (proinflammatory cytokines and inducible enzymes), thus providing a significant impact on neuroinflammation. Mitochondrial dysfunction, as well as neuronal apoptosis, may also provide a significant link between glutathione metabolism and ASD. Furthermore, it has been recently highlighted that glutathione can affect and modulate DNA methylation and epigenetics. Review analysis including research studies meeting the required criteria for analysis showed statistically significant differences between the plasma GSH and GSSG levels as well as GSH:GSSG ratio in autistic patients compared with healthy individuals (P = 0.0145, P = 0.0150 and P = 0.0202, respectively). Therefore, the existing data provide a strong background on the role of the glutathione system in ASD pathogenesis. Future research is necessary to investigate the role of glutathione redox signaling in ASD, which could potentially also lead to promising therapeutics.

Severity Detection for the Coronavirus Disease 2019 (COVID-19) Patients Using a Machine Learning Model Based on the Blood and Urine Tests

The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections.

Oxidative Stress in Autism Spectrum Disorder

According to the United States Centers for Disease Control and Prevention (CDC), as of July 11, 2016, the reported average incidence of children diagnosed with an autism spectrum disorder (ASD) was 1 in 68 (1.46%) among 8-year-old children born in 2004 and living within the 11 monitoring sites' surveillance areas in the United States of America (USA) in 2012. ASD is a multifaceted neurodevelopmental disorder that is also considered a hidden disability, as, for the most part; there are no apparent morphological differences between children with ASD and typically developing children. ASD is diagnosed based upon a triad of features including impairment in socialization, impairment in language, and repetitive and stereotypic behaviors. The increasing incidence of ASD in the pediatric population and the lack of successful curative therapies make ASD one of the most challenging disorders for medicine. ASD neurobiology is thought to be associated with oxidative stress, as shown by increased levels of reactive oxygen species and increased lipid peroxidation, as well as an increase in other indicators of oxidative stress. Children with ASD diagnosis are considered more vulnerable to oxidative stress because of their imbalance in intracellular and extracellular glutathione levels and decreased glutathione reserve capacity. Several studies have suggested that the redox imbalance and oxidative stress are integral parts of ASD pathophysiology. As such, early assessment and treatment of antioxidant status may result in a better prognosis as it could decrease the oxidative stress in the brain before it can induce more irreversible brain damage. In this review, many aspects of the role of oxidative stress in ASD are discussed, taking into account that the process of oxidative stress may be a target for therapeutic interventions.

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.

Resveratrol in Autism Spectrum Disorders: Behavioral and Molecular Effects

Resveratrol (RSV) is a polyphenolic stillbenoid with significant anti-oxidative and anti-inflammatory properties recently tested in animal models of several neurological diseases. Altered immune alteration and oxidative stress have also been found in patients with autism spectrum disorders (ASD), and these alterations could add to the pathophysiology associated with ASD. We reviewed the current evidence about the effects of RSV administration in animal models and in patients with ASD. RSV administration improves the core-symptoms (social impairment and stereotyped activity) in animal models and it also displays beneficial effects in other behavioral abnormalities such as hyperactivity, anxiety and cognitive function. The molecular mechanisms by which RSV restores or improves behavioral abnormalities in animal models encompass both normalization of central and peripheral immune alteration and oxidative stress markers and new molecular mechanisms such as expression of cortical gamma-amino butyric acid neurons, certain type of miRNAs that regulate spine growth. One randomized, placebo-controlled clinical trial (RCT) suggested that RSV add-on risperidone therapy improves comorbid hyperactivity/non-compliance, whereas no effects where seen in core symptoms of ASD No RCTs about the effect of RSV as monotherapy have been performed and the results from preclinical studies encourage its feasibility. Further clinical trials should also identify those ASD patients with immune alterations and/or with increased oxidative stress markers that would likely benefit from RSV administration.

Severity Detection for the Coronavirus Disease 2019 (COVID-19) Patients Using a Machine Learning Model Based on the Blood and Urine Tests

The recent outbreak of the coronavirus disease-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections.