Underpinnings Of Autism Spectrum Disorder Research Articles

Neuro connect: Integrating data-driven and BiGRU classification for enhanced autism prediction from fMRI data

ABSTRACT Autism Spectrum Disorder (ASD) poses a significant challenge in early diagnosis and intervention due to its multifaceted clinical presentation and lack of objective biomarkers. This research presents a novel approach, termed Neuro Connect, which integrates data-driven techniques with Bidirectional Gated Recurrent Unit (BiGRU) classification to enhance the prediction of ASD using functional Magnetic Resonance Imaging (fMRI) data. This study uses both structural and functional neuroimaging data to investigate the complex brain underpinnings of autism spectrum disorder (ASD). They use an Auto-Encoder (AE) to efficiently reduce dimensionality while retaining critical information by learning and compressing important characteristics from high-dimensional data. We treat the feature-extracted data using a BiGRU model for the classification task of predicting ASD. They provide a new optimization strategy, the Horse Herd Algorithm (HHA), and show that it outperforms other established optimizers, such SGD and Adam, in order to improve classification accuracy. The model’s performance is greatly enhanced by the HHA’s novel optimization technique, which more precisely refines weight modifications made during training. The proposed ASD and EEG dataset accuracy value is 99.5%, and 99.3 compared to the existing method the proposed has a high accuracy value.

Frontal and occipital brain glutathione levels are unchanged in autistic adults.

The neurobiological underpinnings of Autism Spectrum Disorder (ASD) are diverse and likely multifactorial. One possible mechanism is increased oxidative stress leading to altered neurodevelopment and brain function. However, this hypothesis has mostly been tested in post-mortem studies. So far, available in vivo studies in autistic individuals have reported no differences in glutathione (GSH) levels in frontal, occipital, and subcortical regions. However, these studies were limited by the technically challenging quantification of GSH, the main brain antioxidant molecule. This study aimed to overcome previous studies' limitations by using a GSH-tailored spectroscopy sequence and optimised quantification methodology to provide clarity on GSH levels in autistic adults. We used spectral editing proton-magnetic resonance spectroscopy (1H-MRS) combined with linear combination model fitting to quantify GSH in the dorsomedial prefrontal cortex (DMPFC) and medial occipital cortex (mOCC) of autistic and non-autistic adults (male and female). We compared GSH levels between groups. We also examined correlations between GSH and current autism symptoms, measured using the Autism Quotient (AQ). Data were available from 31 adult autistic participants (24 males, 7 females) and 40 non-autistic participants (21 males, 16 females); the largest sample to date. The GSH levels did not differ between groups in either region. No correlations with AQ were observed. GSH levels as measured using 1H-MRS are unaltered in the DMPFC and mOCC regions of autistic adults, suggesting that oxidative stress in these cortical regions is not a marked neurobiological signature of ASD.

Identification of two novel autism genes, TRPC4 and SCFD2, in Qatar simplex families through exome sequencing.

This study investigated the genetic underpinnings of autism spectrum disorder (ASD) in a Middle Eastern cohort in Qatar using exome sequencing. The study identified six candidate autism genes in independent simplex families, including both four known and two novel autosomal dominant and autosomal recessive genes associated with ASD. The variants consisted primarily of de novo and homozygous missense and splice variants. Multiple individuals displayed more than one candidate variant, suggesting the potential involvement of digenic or oligogenic models. These variants were absent in the Genome Aggregation Database (gnomAD) and exhibited extremely low frequencies in the local control population dataset. Two novel autism genes, TRPC4 and SCFD2, were discovered in two Qatari autism individuals. Furthermore, the D651A substitution in CLCN3 and the splice acceptor variant in DHX30 were identified as likely deleterious mutations. Protein modeling was utilized to evaluate the potential impact of three missense variants in DEAF1, CLCN3, and SCFD2 on their respective structures and functions, which strongly supported the pathogenic natures of these variants. The presence of multiple de novo mutations across trios underscored the significant contribution of de novo mutations to the genetic etiology of ASD. Functional assays and further investigations are necessary to confirm the pathogenicity of the identified genes and determine their significance in ASD. Overall, this study sheds light on the genetic factors underlying ASD in Qatar and highlights the importance of considering diverse populations in ASD research.

Serotonin transporter availability in adults with autism\u2014a positron emission tomography study

Impairments in social interaction and communication, in combination with restricted, repetitive behaviors and interests, define the neurodevelopmental diagnosis of autism spectrum disorder (ASD). The biological underpinnings of ASD are not well known, but the hypothesis of serotonin (5-HT) involvement in the neurodevelopment of ASD is one of the longest standing. Reuptake through the 5-HT transporter (5-HTT) is the main pathway decreasing extracellular 5-HT in the brain and a marker for the 5-HT system, but in vivo investigations of the 5-HTT and the 5-HT system in ASD are scarce and so far inconclusive. To quantify possible alterations in the 5-HT system in ASD, we used positron emission tomography and the radioligand [11C]MADAM to measure 5-HTT availability in the brain of 15 adults with ASD and 15 controls. Moreover, we examined correlations between regional 5-HTT availability and behavioral phenotype assessments regarding ASD core symptoms. In the ASD group, we found significantly lower 5-HTT availability in total gray matter, brainstem, and 9 of 18 examined subregions of gray matter. In addition, several correlations between regional 5-HTT availability and social cognitive test performance were found. The results confirm the hypothesis that 5-HTT availability is lower in the brain of adult individuals with ASD, and are consistent with the theory of 5-HT involvement in ASD neurodevelopment. The findings endorse the central role of 5-HT in the physiology of ASD, and confirm the need for a continued investigation of the 5-HT system in order to disentangle the biology of ASD.

Vascular contributions to 16p11.2 deletion autism syndrome modeled in mice.

While the neuronal underpinnings of autism spectrum disorder (ASD) are being unraveled, vascular contributions to ASD remain elusive. Here, we investigated postnatal cerebrovascular development in the 16p11.2df/+ mouse model of 16p11.2 deletion ASD syndrome. We discover that 16p11.2 hemizygosity leads to male-specific, endothelium-dependent structural and functional neurovascular abnormalities. In 16p11.2df/+ mice, endothelial dysfunction results in impaired cerebral angiogenesis at postnatal day 14, and in altered neurovascular coupling and cerebrovascular reactivity at postnatal day 50. Moreover, we show that there is defective angiogenesis in primary 16p11.2df/+ mouse brain endothelial cells and in induced-pluripotent-stem-cell-derived endothelial cells from human carriers of the 16p11.2 deletion. Finally, we find that mice with an endothelium-specific 16p11.2 deletion (16p11.2ΔEC) partially recapitulate some of the behavioral changes seen in 16p11.2 syndrome, specifically hyperactivity and impaired motor learning. By showing that developmental 16p11.2 haploinsufficiency from endothelial cells results in neurovascular and behavioral changes in adults, our results point to a potential role for endothelial impairment in ASD.

Neuroanatomical underpinnings of autism symptomatology in carriers and non-carriers of the 22q11.2 microdeletion

BackgroundA crucial step to understanding the mechanistic underpinnings of autism spectrum disorder (ASD), is to examine if the biological underpinnings of ASD in genetic high-risk conditions, like 22q11.2 deletion syndrome (22q11.2DS), are similar to those in idiopathic illness. This study aimed to examine if ASD symptomatology in 22q11.2DS is underpinned by the same—or distinct—neural systems that mediate these symptoms in non-deletion carriers.MethodsWe examined vertex-wise estimates of cortical volume (CV), surface area (SA), and cortical thickness across 131 individuals between 6 and 25 years of age including (1) 50 individuals with 22q11.2DS, out of which n = 25 had a diagnosis of ASD, (2) 40 non-carriers of the microdeletion with a diagnosis of ASD (i.e., idiopathic ASD), and (3) 41 typically developing (TD) controls. We employed a 2-by-2 factorial design to identify neuroanatomical variability associated with the main effects of 22q11.2DS and ASD, as well as their interaction. Further, using canonical correlation analysis (CCA), we compared neuroanatomical variability associated with the complex (i.e., multivariate) clinical phenotype of ASD between 22q11.2 deletion carriers and non-carriers.ResultsThe set of brain regions associated with the main effect of 22q11.2DS was distinct from the neuroanatomical underpinnings of the main effect of ASD. Moreover, significant 22q11.2DS-by-ASD interactions were observed for CV and SA in the dorsolateral prefrontal cortex, precentral gyrus, and posterior cingulate cortex, suggesting that the neuroanatomy of ASD is significantly modulated by 22q11.2DS (p < 0.01). We further established that the multivariate patterns of neuroanatomical variability associated with differences in symptom profiles significantly differed between 22q11.2 deletion carriers and non-carriers.LimitationsWe employed a multicenter design to overcome single-site recruitment limitations; however, FreeSurfer-derived measures of surface anatomy have been shown to be highly reliable across scanner platforms and field strengths. Further, we controlled for gender to address the differing distribution between idiopathic ASD individuals and the other groups. Nonetheless, the gender distribution in our sample reflects that of the respective populations, adding to the generalizability of our results. Last, we included individuals with a relatively wide age range (i.e., 6–25 years).ConclusionsOur findings indicate that neuroanatomical correlates of ASD symptomatology in carriers of the 22q11.2 microdeletion diverge from those in idiopathic ASD.

Improving Diagnosis of Autism Spectrum Disorder and Disentangling its Heterogeneous Functional Connectivity Patterns Using Capsule Networks.

Functional connectivity (FC) analysis is an appealing tool to aid diagnosis and elucidate the neurophysiological underpinnings of autism spectrum disorder (ASD). Many machine learning methods have been developed to distinguish ASD patients from healthy controls based on FC measures and identify abnormal FC patterns of ASD. Particularly, several studies have demonstrated that deep learning models could achieve better performance for ASD diagnosis than conventional machine learning methods. Although promising classification performance has been achieved by the existing machine learning methods, they do not explicitly model heterogeneity of ASD, incapable of disentangling heterogeneous FC patterns of ASD. To achieve an improved diagnosis and a better understanding of ASD, we adopt capsule networks (CapsNets) to build classifiers for distinguishing ASD patients from healthy controls based on FC measures and stratify ASD patients into groups with distinct FC patterns. Evaluation results based on a large multi-site dataset have demonstrated that our method not only obtained better classification performance than state-of-the-art alternative machine learning methods, but also identified clinically meaningful subgroups of ASD patients based on their vectorized classification outputs of the CapsNets classification model.

High resolution analysis of rare copy number variants in patients with autism spectrum disorder from Taiwan

Rare genomic copy number variations (CNVs) (frequency <1%) contribute a part to the genetic underpinnings of autism spectrum disorders (ASD). The study aimed to understand the scope of rare CNV in Taiwanese patients with ASD. We conducted a genome-wide CNV screening of 335 ASD patients (299 males, 36 females) from Taiwan using Affymetrix Genome-Wide Human SNP Array 6.0 and compared the incidence of rare CNV with that of 1093 control subjects (525 males, 568 females). We found a significantly increased global burden of rare CNVs in the ASD group compared to the controls as a whole or when the rare CNVs were classified by the size and types of CNV. Further analysis confirmed the presence of several rare CNVs at regions strongly associated with ASD as reported in the literature in our sample. Additionally, we detected several new private pathogenic CNVs in our samples and five patients carrying two pathogenic CNVs. Our data indicate that rare genomic CNVs contribute a part to the genetic landscape of our ASD patients. These CNVs are highly heterogeneous, and the clinical interpretation of the pathogenic CNVs of ASD is not straightforward in consideration of the incomplete penetrance, varied expressivity, and individual genetic background.

The neuroanatomy of autism spectrum disorder: An overview of structural neuroimaging findings and their translatability to the clinical setting.

Autism spectrum disorder is a complex neurodevelopmental disorder, which is accompanied by differences in brain anatomy, functioning and brain connectivity. Due to its neurodevelopmental character, and the large phenotypic heterogeneity among individuals on the autism spectrum, the neurobiology of autism spectrum disorder is inherently difficult to describe. Nevertheless, significant progress has been made in characterizing the neuroanatomical underpinnings of autism spectrum disorder across the human life span, and in identifying the molecular pathways that may be affected in autism spectrum disorder. Moreover, novel methodological frameworks for analyzing neuroimaging data are emerging that make it possible to characterize the neuroanatomy of autism spectrum disorder on the case level, and to stratify individuals based on their individual phenotypic make up. While these approaches are increasingly more often employed in the research setting, their applicability in the clinical setting remains a vision for the future. The aim of the current review is to (1) provide a general overview of recent structural neuroimaging findings examining the neuroanatomy of autism spectrum disorder across the human life span, and in males and females with the condition, (2) highlight potential neuroimaging (bio)markers that may in the future be used for the stratification of autism spectrum disorder individuals into biologically homogeneous subgroups and (3) inform treatment and intervention strategies.

Resting state functional magnetic resonance imaging and neural network classified autism and control

Although the neurodevelopmental and genetic underpinnings of autism spectrum disorder (ASD) have been investigated, the etiology of the disorder has remained elusive, and clinical diagnosis continues to rely on symptom-based criteria. In this study, to classify both control subjects and a large sample of patients with ASD, we used resting state functional magnetic resonance imaging (rs-fMRI) and a neural network. Imaging data from 312 subjects with ASD and 328 subjects with typical development was downloaded from the multi-center research project. Only subjects under 20 years of age were included in this analysis. Correlation matrices computed from rs-fMRI time-series data were entered into a probabilistic neural network (PNN) for classification. The PNN classified the two groups with approximately 90% accuracy (sensitivity = 92%, specificity = 87%). The accuracy of classification did not differ among the institutes, or with respect to experimental and imaging conditions, sex, handedness, or intellectual level. Medication status and degree of head movement did not affect accuracy values. The present study indicates that an intrinsic connectivity matrix produced from rs-fMRI data could yield a possible biomarker of ASD. These results support the view that altered network connectivity within the brain contributes to the neurobiology of ASD.

Elucidating the neurophysiological underpinnings of autism spectrum disorder: new developments.

The study of neurophysiological approaches together with rare and common risk factors for Autism Spectrum Disorder (ASD) allows elucidating the specific underlying neurobiology of ASD. Whereas most neurophysiologically based research in ASD to date has focussed on case-control differences based on the DSM- or ICD-based categorical ASD diagnosis, more recent studies have aimed at studying genetically and/or neurophysiologically defined homogeneous ASD subgroups for specific neuronal biomarkers. This review addresses the neurophysiological investigation of ASD by evoked and event-related potentials, by EEG/MEG connectivity measures such as coherence, and transcranial magnetic stimulation. As an example of classical neurophysiological studies in ASD, we report event-related potential studies which have illustrated which brain areas and processing stages are affected in the visual perception of socially relevant stimuli. However, a paradigm shift has taken place in recent years focussing on how these findings can be tracked down to basic neuronal functions such as deficits in cortico-cortical connectivity and the interaction between brain areas. Disconnectivity, for example, can again be related to genetically induced shifts in the excitation/inhibition balance. Genetic causes of ASD may be grouped by their effects on the brain's system level to identify ASD subgroups which respond differentially to therapeutic interventions.

Pupillometry reveals a mechanism for the Autism Spectrum Disorder (ASD) advantage in visual tasks.

Research on the neural underpinnings of Autism Spectrum Disorder (ASD) has focussed primarily on impairments of social interaction and communication. Less is known though about the second diagnostic criterion of restricted behaviors and interests. Uniquely in this domain, alongside impairments stands an ‘ASD advantage' characterised by superior performance on many visual tasks. We recently found that 2-year-olds with ASD dramatically outperform age-matched, typically developing controls on visual search. Here we use task-evoked, phasic pupil responses – a sensitive, involuntary measure of effort and a biomarker of the locus coeruleus-norepinephrine (LC-NE) system's modulation of attention – to isolate a causal factor: a ‘hyperphasic' LC-NE system compels (here, advantageously) focussed attention. However, this focussed attention in other contexts may contribute to restricted behaviors and interests.

Co-segregation of Social Cognition, Executive Function and Local Processing Style in Children with ASD, their Siblings and Normal Controls

Cognitive research proposes that social cognition (SC), executive functions (EF) and local processing style (weak CC) may be fruitful areas for research into the familial-genetic underpinnings of Autism Spectrum Disorders (ASD). The performance of 140 children with ASD, 172 siblings and 127 controls on tasks measuring SC (face recognition, affective prosody, and facial emotion recognition), EF (inhibition, cognitive flexibility, and verbal working memory) and local processing style was assessed. Compelling evidence was found for the interrelatedness of SC and EF, but not local processing style, within individuals and within families, suggesting that these domains tend to co-segregate in ASD. Using the underlying shared variance of these constructs in genetic research may increase the power for detecting susceptibility genes for ASD.

P-711 - Genetic syndromes and the autism spectrum

Autistic features are present in a variety of genetic syndromes and have stimulated research into the genetic underpinnings of autism spectrum disorders. To understand this genetic heterogeneity, various techniques can be used such as cytogenetic research, linkage studies, and association studies. At present, CGH-microarray technique is primarily used, which enables examination of the complete genome for the presence of microdeletions and duplications or so-called copy-number variations (CNVs). The most investigated syndromes are fragile-X syndrome, Rett's disorder, tuberous sclerosis and 22q11microdeletion syndrome. In addition, metabolic disorders as well as a variety of somatic diseases may be accompanied by autistic symptoms. To study the genetics involved in autism spectrum disorders. Review of the literature about the most investigated genetic syndromes. Data from own studies in patients with 22q11 microdeletion syndrome are briefly discussed against the background of the results from the literature on other genetic syndromes that are rather frequently related to autism. Fragile-X syndrome, Rett's disorder, tuberous sclerosis complex, 22q11 microdeletion syndrome, and metabolic disorders like X-linked creatine transporter deficiency syndrome, all deal with mutations or copy number variants in genes that code for proteins responsible for neuronal growth and maturation, and/or synaptic functioning. From the vast amount of information, it becomes obvious that autism is a very heterogeneous disorder both phenotypically and genotypically, reason why the search for single high impact genes will not be very successful. Focus should be given to the endophenotype strategy to unravel potential gene-brain-behaviour relationships in autism spectrum disorders.

Molecular genetics of autism spectrum disorder.

We are on the brink of exciting discoveries into the molecular genetic underpinnings of autism spectrum disorder. Overwhelming evidence of genetic involvement coupled with increased societal attention to the disorder has drawn in more researchers and more research funding. Autism is a strongly genetic yet strikingly complex disorder, in which evidence from different cases supports chromosomal disorders, rare single gene mutations, and multiplicative effects of common gene variants. With more and more interesting yet sometimes divergent findings emerging every year, it is tempting to view these initial molecular studies as so much noise, but the data have also started to coalesce in certain areas. In particular, recent studies in families with autism spectrum disorder have identified uncommon occurrences of a novel genetic syndrome caused by disruptions of the NLGN4 gene on chromosome Xp22. Previous work had identified another uncommon syndrome that is caused by maternal duplications of the chromosome 15q11-13 region. We highlight other converging findings, point toward those areas most likely to yield results, and emphasize the contributions of multiple approaches to identifying the genes of interest.