Autism Spectrum Disorder: A Neuro-Immunometabolic Hypothesis of the Developmental Origins

Multimodal Morphometric Similarity Network Analysis of Autism Spectrum Disorder

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties in social interaction, communication, and repetitive behaviors. Neuroimaging studies have revealed structural and functional neural changes in individuals with ASD compared to healthy subjects. Objectives: This study aimed to investigate brain network structural connectivity in ASD using Morphometric Similarity Network (MSN) analysis. Methods: Data from the Autism Brain Imaging Data Exchange (ABIDE) were analyzed, comprising 597 individuals with ASD and 644 healthy controls. Structural connectivity was assessed using cortical morphometric features. Global and regional network indices, including the density index, node degree, node strength, and clustering coefficients, were evaluated. Results: Among the global network indices, when using a threshold value of 0.4, ASD patients compared to HCs showed a lower density (p = 0.041) and higher negative clustering (p = 0.0051) coefficients. For regional network indices, ASD patients showed a lower bilateral superior frontal cortices degree (left hemisphere: p = 0.014; right hemisphere: p = 0.0038) and strength (left: p = 0.017; right: p = 0.018). Additionally, they showed higher negative clustering coefficients in the bilateral superior frontal cortices (left, p = 0.0088; right, p = 0.0056) and bilateral pars orbitalis (left, p = 0.016; right, p = 0.0006), as well as lower positive clustering in the bilateral frontal pole (left, p = 0.03; right, p = 0.044). Conclusions: These findings highlight significant alterations in both global and regional brain network organization in ASD, which may contribute to the disorder's cognitive and behavioral manifestations. Future studies are needed to investigate the pathophysiological mechanisms underlying these structural connectivity changes, to inform the development of more targeted and individualized therapeutic interventions for individuals with ASD.

Neuroplasticity of children in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that encompasses a range of symptoms including difficulties in verbal communication, social interaction, limited interests, and repetitive behaviors. Neuroplasticity refers to the structural and functional changes that occur in the nervous system to adapt and respond to changes in the external environment. In simpler terms, it is the brain's ability to learn and adapt to new environments. However, individuals with ASD exhibit abnormal neuroplasticity, which impacts information processing, sensory processing, and social cognition, leading to the manifestation of corresponding symptoms. This paper aims to review the current research progress on ASD neuroplasticity, focusing on genetics, environment, neural pathways, neuroinflammation, and immunity. The findings will provide a theoretical foundation and insights for intervention and treatment in pediatric fields related to ASD.

Unraveling the immunogenetic landscape of autism spectrum disorder: a comprehensive bioinformatics approach

Background

Autism spectrum disorder (ASD) is a disease characterized by social disorder. Recently, the population affected by ASD has gradually increased around the world. There are great difficulties in diagnosis and treatment at present.

Methods

The ASD datasets were obtained from the Gene Expression Omnibus database and the immune-relevant genes were downloaded from a previously published compilation. Subsequently, we used WGCNA to screen the modules related to the ASD and immune. We also choose the best combination and screen out the core genes from Consensus Machine Learning Driven Signatures (CMLS). Subsequently, we evaluated the genetic correlation between immune cells and ASD used GNOVA. And pleiotropic regions identified by PLACO and CPASSOC between ASD and immune cells. FUMA was used to identify pleiotropic regions, and expression trait loci (EQTL) analysis was used to determine their expression in different tissues and cells. Finally, we use qPCR to detect the gene expression level of the core gene.

Results

We found a close relationship between neutrophils and ASD, and subsequently, CMLS identified a total of 47 potential candidate genes. Secondly, GNOVA showed a significant genetic correlation between neutrophils and ASD, and PLACO and CPASSOC identified a total of 14 pleiotropic regions. We annotated the 14 regions mentioned above and identified a total of 6 potential candidate genes. Through EQTL, we found that the CFLAR gene has a specific expression pattern in neutrophils, suggesting that it may serve as a potential biomarker for ASD and is closely related to its pathogenesis.

Conclusions

In conclusion, our study yields unprecedented insights into the molecular and genetic heterogeneity of ASD through a comprehensive bioinformatics analysis. These valuable findings hold significant implications for tailoring personalized ASD therapies.

Roles of Epigenetics and Glial Cells in Drug-Induced Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by severe deficits in social communication and interaction, repetitive movements, abnormal focusing on objects, or activity that can significantly affect the quality of life of the afflicted. Neuronal and glial cells have been implicated. It has a genetic component but can also be triggered by environmental factors or drugs. For example, prenatal exposure to valproic acid or acetaminophen, or ingestion of propionic acid, can increase the risk of ASD. Recently, epigenetic influences on ASD have come to the forefront of investigations on the etiology, prevention, and treatment of this disorder. Epigenetics refers to DNA modifications that alter gene expression without making any changes to the DNA sequence. Although an increasing number of pharmaceuticals and environmental chemicals are being implicated in the etiology of ASD, here, we specifically focus on the molecular influences of the abovementioned chemicals on epigenetic alterations in neuronal and glial cells and their potential connection to ASD. We conclude that a better understanding of these phenomena can lead to more effective interventions in ASD.

Autism Spectrum Disorder: Brain Areas Involved, Neurobiological Mechanisms, Diagnoses and Therapies

Autism spectrum disorder (ASD), affecting over 2% of the pre-school children population, includes an important fraction of the conditions accounting for the heterogeneity of autism. The disease was discovered 75 years ago, and the present review, based on critical evaluations of the recognized ASD studies from the beginning of 1990, has been further developed by the comparative analyses of the research and clinical reports, which have grown progressively in recent years up to late 2023. The tools necessary for the identification of the ASD disease and its related clinical pathologies are genetic and epigenetic mutations affected by the specific interaction with transcription factors and chromatin remodeling processes occurring within specific complexes of brain neurons. Most often, the ensuing effects induce the inhibition/excitation of synaptic structures sustained primarily, at dendritic fibers, by alterations of flat and spine response sites. These effects are relevant because synapses, established by specific interactions of neurons with glial cells, operate as early and key targets of ASD. The pathology of children is often suspected by parents and communities and then confirmed by ensuing experiences. The final diagnoses of children and mature patients are then completed by the combination of neuropsychological (cognitive) tests and electro-/magneto-encephalography studies developed in specialized centers. ASD comorbidities, induced by processes such as anxieties, depressions, hyperactivities, and sleep defects, interact with and reinforce other brain diseases, especially schizophrenia. Advanced therapies, prescribed to children and adult patients for the control of ASD symptoms and disease, are based on the combination of well-known brain drugs with classical tools of neurologic and psychiatric practice. Overall, this review reports and discusses the advanced knowledge about the biological and medical properties of ASD.

Heart Rate Variability Code: Does It Exist and Can We Hack It?

A code is generally defined as a system of signals or symbols for communication. Experimental evidence is synthesized for the presence and utility of such communication in heart rate variability (HRV) with particular attention to fetal HRV: HRV contains signatures of information flow between the organs and of response to physiological or pathophysiological stimuli as signatures of states (or syndromes). HRV exhibits features of time structure, phase space structure, specificity with respect to (organ) target and pathophysiological syndromes, and universality with respect to species independence. Together, these features form a spatiotemporal structure, a phase space, that can be conceived of as a manifold of a yet-to-be-fully understood dynamic complexity. The objective of this article is to synthesize physiological evidence supporting the existence of HRV code: hereby, the process-specific subsets of HRV measures indirectly map the phase space traversal reflecting the specific information contained in the code required for the body to regulate the physiological responses to those processes. The following physiological examples of HRV code are reviewed, which are reflected in specific changes to HRV properties across the signal-analytical domains and across physiological states and conditions: the fetal systemic inflammatory response, organ-specific inflammatory responses (brain and gut), chronic hypoxia and intrinsic (heart) HRV (iHRV), allostatic load (physiological stress due to surgery), and vagotomy (bilateral cervical denervation). Future studies are proposed to test these observations in more depth, and the author refers the interested reader to the referenced publications for a detailed study of the HRV measures involved. While being exemplified mostly in the studies of fetal HRV, the presented framework promises more specific fetal, postnatal, and adult HRV biomarkers of health and disease, which can be obtained non-invasively and continuously.