Genetic Variation across Phenotypic Severity of Autism

Resolving heterogeneity in dynamics of synchronization stability within the salience network in autism spectrum disorder

BACKGROUND

Heterogeneity in resting-state functional connectivity (FC) are one of the characteristics of autism spectrum disorder (ASD). Traditional resting-state FC primarily focuses on linear correlations, ignoring the nonlinear properties involved in synchronization between networks or brain regions.

METHODS

In the present study, the cross-recurrence quantification analysis, a nonlinear method based on dynamical systems, was utilized to quantify the synchronization stability between brain regions within the salience network (SN) of ASD. Using the resting-state functional magnetic resonance imaging data of 207 children (ASD/typically-developing controls (TC): 105/102) in Autism Brain Imaging Data Exchange database, we analyzed the laminarity and trapping time differences of the synchronization stability between the ASD subtype derived by a K-means clustering analysis and the TC group, and examined the relationship between synchronization stability and the severity of clinical symptoms of the ASD subtypes.

RESULTS

Based on the synchronization stability within the SN of ASD, we identified two subtypes that showed opposite changes in synchronization stability relative to the TC group. In addition, the synchronization stability of ASD subtypes 1 and 2 can predict the social interaction and communication impairments, respectively.

CONCLUSIONS

These findings reveal that ASD subgroups with different patterns of synchronization stability within the SN appear distinct clinical symptoms, and highlight the importance of exploring the potential neural mechanism of ASD from a nonlinear perspective.

Theoretical-Methodological Foundations for the Global Integration Method (Método de Integração Global-MIG) in the Treatment of Autism Spectrum Disorder

Currently, there is no intervention model for autism spectrum disorder (ASD) that addresses all levels and factors of the International Classification of Functioning, Disability and Health (ICF, WHO). The most researched programs focus on naturalistic, developmental and behavioral approaches to socio-communication. Less attention has been paid to motor and environmental reactivity aspects (behavior/interest restriction and sensory reactivity). The evidence rationale for the Global Integration Method (MIG, "Método de Integração Global"), a model addressing sensorimotor reactivity in addition to socio-communication, is presented. MIG is an integrative, interdisciplinary, family-oriented intervention and naturalistic program that addresses all levels and moderating factors of ASD's impact. MIG's theoretical rationale is based on the predictive coding impairment and embodied cognition hypotheses. MIG incorporates both bottom-up (flexible therapeutic suit, social-motor synchronization) and top-down (schematic social information processing, narratives, imagery) strategies to promote the building and use of accurate, flexible and context-sensitive internal predictive models. MIG is based on the premises that predictive coding improves both socio-communication and environmental reactivity, and that the postural stabilization provided by the flexible therapeutic suit frees information processing resources for socio-cognitive learning. MIG builds on interdisciplinary, professionally and parentally mediated work based on behavioral principles of intensive training in a situated environment.

Comprehensive systematic review and meta-analysis of the association between common genetic variants and autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is neurodevelopmental disorder characterized by stereotyped behavior and deficits in communication and social interactions. To date, numerous studies have investigated the associations between genetic variants and ASD risk. However, the results of these published studies lack a clear consensus. In the present study, we performed a systematic review on the association between genetic variants and ASD risk. Meanwhile, we conducted a meta-analysis on available data to identify the association between the single nucleotide polymorphisms (SNPs) of candidate genes and ASD risk.

METHODS

We systematically searched public databases including English and Chinese from their inception to August 1, 2022. Two independent reviewers extracted data and assessed study quality. Odds ratio and 95 % confidence interval were used as effect indexes to evaluate the association between the SNPs of candidate genes and the risk of ASD. Heterogeneity was explored through subgroup, sensitivity, and meta-regression analyses. Publication bias was assessed by using Egger's and Begg's tests for funnel plot asymmetry. In addition, TSA analysis were performed to confirm the study findings.

RESULTS

We summarized 84 SNPs of 32 candidate genes from 81 articles included in the study. Subsequently, we analyzed 16 SNPs of eight genes by calculating pooled ORs, and identified eight significant SNPs of contactin associated protein 2 (CNTNAP2), methylentetrahydrofolate reductase (MTHFR), oxytocin receptor (OXTR), and vitamin D receptor (VDR). Results showed that seven SNPs, including the CNTNAP2 rs2710102 (homozygote, heterozygote, dominant and allelic models) and rs7794745 (heterozygote and dominant models), MTHFR C677T (homozygote, heterozygote, dominant, recessive and allelic models) and A1298C (dominant and allelic models), OXTR rs2254298 (homozygote and recessive models), VDR rs731236 (homozygote, dominant, recessive and allelic models) and rs2228570 (homozygote and recessive models), were showed to be correlated with an increased ASD risk. By contrast, the VDR rs7975232 was correlated with a decreased the risk of ASD under the homozygote and allelic models.

CONCLUSION

Our study summarized research evidence on the genetic variants of ASD and provides a broad and detailed overview of ASD risk genes. The C677T and A1298C polymorphisms of MTHFR, rs2710102 and rs7794745 polymorphisms of CNTNAP2, rs2254298 polymorphism of OXTR, and rs731236 and rs2228570 polymorphisms of VDR were genetic risk factors. The rs7975232 polymorphism of VDR was a genetic protective factor for ASD. Our study provides novel clues to clinicians and healthcare decision-makers to predict ASD susceptibility.

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Identification of potentially pathogenic variants for autism spectrum disorders using gene-burden analysis

Gene- burden analyses have lately become a very successful way for the identification of genes carrying risk variants underlying the analysed disease. This approach is also suitable for complex disorders like autism spectrum disorder (ASD). The gene-burden analysis using Testing Rare Variants with Public Data (TRAPD) software was conducted on whole exome sequencing data of Slovenian patients with ASD to determine potentially novel disease risk variants in known ASD-associated genes as well as in others. To choose the right control group for testing, principal component analysis based on the 1000 Genomes and ASD cohort samples was conducted. The subsequent protein structure and ligand binding analysis usingI-TASSER package were performed to detect changes in protein structure and ligand binding to determine a potential pathogenic consequence of observed mutation. The obtained results demonstrate an association of two variants-p.Glu198Lys (PPP2R5D:c.592G>A) and p.Arg253Gln (PPP2R5D:c.758G>A) with the ASD. Substitution p.Glu198Lys (PPP2R5D:c.592G>A) is a variant, previously described as pathogenic in association with ASD combined with intellectual disability, whereas p.Arg253Gln (PPP2R5D:c.758G>A) has not been described as an ASD-associated pathogenic variant yet. The results indicate that the filtering process was suitable and could be used in the future for detection of novel pathogenic variants when analysing groups of ASD patients.

Dissecting the multifaceted contribution of the mitochondrial genome to autism spectrum disorder

Autism spectrum disorder (ASD) is a clinically heterogeneous class of neurodevelopmental conditions with a strong, albeit complex, genetic basis. The genetic architecture of ASD includes different genetic models, from monogenic transmission at one end, to polygenic risk given by thousands of common variants with small effects at the other end. The mitochondrial DNA (mtDNA) was also proposed as a genetic modifier for ASD, mostly focusing on maternal mtDNA, since the paternal mitogenome is not transmitted to offspring. We extensively studied the potential contribution of mtDNA in ASD pathogenesis and risk through deep next generation sequencing and quantitative PCR in a cohort of 98 families. While the maternally-inherited mtDNA did not seem to predispose to ASD, neither for haplogroups nor for the presence of pathogenic mutations, an unexpected influence of paternal mtDNA, apparently centered on haplogroup U, came from the Italian families extrapolated from the test cohort (n = 74) when compared to the control population. However, this result was not replicated in an independent Italian cohort of 127 families and it is likely due to the elevated paternal age at time of conception. In addition, ASD probands showed a reduced mtDNA content when compared to their unaffected siblings. Multivariable regression analyses indicated that variants with 15%-5% heteroplasmy in probands are associated to a greater severity of ASD based on ADOS-2 criteria, whereas paternal super-haplogroups H and JT were associated with milder phenotypes. In conclusion, our results suggest that the mtDNA impacts on ASD, significantly modifying the phenotypic expression in the Italian population. The unexpected finding of protection induced by paternal mitogenome in term of severity may derive from a role of mtDNA in influencing the accumulation of nuclear de novo mutations or epigenetic alterations in fathers' germinal cells, affecting the neurodevelopment in the offspring. This result remains preliminary and needs further confirmation in independent cohorts of larger size. If confirmed, it potentially opens a different perspective on how paternal non-inherited mtDNA may predispose or modulate other complex diseases.

Yield of array-CGH analysis in Tunisian children with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic underpinnings. Microarray-based comparative genomic hybridization (aCGH) technology has been proposed as a first-level test in the genetic diagnosis of ASD and of neurodevelopmental disorders in general.

METHODS

We performed aCGH on 98 Tunisian children (83 boys and 15 girls) diagnosed with ASD according to DSM-IV criteria.

RESULTS

"Pathogenic" or "likely pathogenic" copy number variants (CNVs) were detected in 11 (11.2%) patients, CNVs of "uncertain clinical significance" in 26 (26.5%), "likely benign" or "benign" CNVs were found in 37 (37.8%) and 24 (24.5%) patients, respectively. Gene set enrichment analysis involving genes spanning rare "pathogenic," "likely pathogenic," or "uncertain clinical significance" CNVs, as well as SFARI database "autism genes" in common CNVs, detected eight neuronal Gene Ontology classes among the top 10 most significant, including synapse, neuron differentiation, synaptic signaling, neurogenesis, and others. Similar results were obtained performing g: Profiler analysis. Neither transcriptional regulation nor immune pathways reached significance.

CONCLUSIONS

aCGH confirms its sizable diagnostic yield in a novel sample of autistic children from North Africa. Recruitment of additional families is under way, to verify whether genetic contributions to ASD in the Tunisian population, differently from other ethnic groups, may involve primarily neuronal genes, more than transcriptional regulation and immune-related pathways.

The Role of Genetics, Epigenetics, and the Environment in ASD: A Mini Review

According to recent findings, variances in autism spectrum disorder (ASD) risk factors might be determined by several factors, including molecular genetic variants. Accumulated evidence has also revealed the important role of biological and chemical pathways in ASD aetiology. In this paper, we assess several reviews with regard to their quality of evidence and provide a brief outline of the presumed mechanisms of the genetic, epigenetic, and environmental risk factors of ASD. We also review some of the critical literature, which supports the basis of each factor in the underlying and specific risk patterns of ASD. Finally, we consider some of the implications of recent research regarding potential molecular targets for future investigations.

Can Autism Be Diagnosed with Artificial Intelligence? A Narrative Review

Radiomics with deep learning models have become popular in computer-aided diagnosis and have outperformed human experts on many clinical tasks. Specifically, radiomic models based on artificial intelligence (AI) are using medical data (i.e., images, molecular data, clinical variables, etc.) for predicting clinical tasks such as autism spectrum disorder (ASD). In this review, we summarized and discussed the radiomic techniques used for ASD analysis. Currently, the limited radiomic work of ASD is related to the variation of morphological features of brain thickness that is different from texture analysis. These techniques are based on imaging shape features that can be used with predictive models for predicting ASD. This review explores the progress of ASD-based radiomics with a brief description of ASD and the current non-invasive technique used to classify between ASD and healthy control (HC) subjects. With AI, new radiomic models using the deep learning techniques will be also described. To consider the texture analysis with deep CNNs, more investigations are suggested to be integrated with additional validation steps on various MRI sites.

The Role of Ion Channel-Related Genes in Autism Spectrum Disorder: A Study Using Next-Generation Sequencing

The clinical heterogeneity of autism spectrum disorder (ASD) is closely associated with the diversity of genes related to ASD pathogenesis. With their low effect size, it has been hard to define the role of common variants of genes in ASD phenotype. In this study, we reviewed genetic results and clinical scores widely used for ASD diagnosis to investigate the role of genes in ASD phenotype considering their functions in molecular pathways. Genetic data from next-generation sequencing (NGS) were collected from 94 participants with ASD. We analyzed enrichment of cellular processes and gene ontology using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). We compared clinical characteristics according to genetic functional characteristics. We found 266 genes containing nonsense, frame shift, missense, and splice site mutations. Results from DAVID revealed significant enrichment for “ion channel” with an enrichment score of 8.84. Moreover, ASD participants carrying mutations in ion channel-related genes showed higher total IQ (p = 0.013) and lower repetitive, restricted behavior (RRB)-related scores (p = 0.003) and mannerism subscale of social responsiveness scale scores, compared to other participants. Individuals with variants in ion channel genes showed lower RRB scores, suggesting that ion channel genes might be relatively less associated with RRB pathogenesis. These results contribute to understanding of the role of common variants in ASD and could be important in the development of precision medicine of ASD.

Genetic architecture of autism spectrum disorder: Lessons from large-scale genomic studies

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a strong genetic component. Recently developed genomic technologies, including microarray and next-generation sequencing (NGS), have enabled researchers to genetic analyses aimed at identifying genetic variations associated with ASD and to elucidate the genetic architecture of the disorder. Large-scale microarray, exome sequencing analyses, and robust statistical methods have resulted in successful gene discovery and identification of high-confidence ASD genes from among de novo and inherited variants. Efforts have been made to understand the genetic architecture of ASD using whole-genome sequencing and genome-wide association studies aimed at identifying noncoding mutations and common variants associated with ASD. In addition, the development of systems biology approaches has resulted in the integration of genetic findings with functional genomic datasets, thereby providing a unique insight into the functional convergence of ASD risk genes and their neurobiology. In this review, we summarize the latest findings of ASD genetic studies involving large cohorts and discuss their implications in ASD neurobiology and in clinical practice.

Etiological investigation of genetic cause in autism spectrum disorder

AIMS: The aims of this study were to characterize the etiological investigation of genetic cause in the autism spectrum disorder and to determine the factors related to its identification.METHODS: A retrospective descriptive study, with an analytical component, included children and adolescents with autism spectrum disorder followed in consultation at a level 2 hospital, between November 2017 and October 2019. The following variables were analyzed: age, sex, age at the first consultation, family history, objective examination, cognitive assessment, etiological investigation of genetic cause and etiological diagnosis of genetic cause. Statistical analysis was performed using the SPSS®v23 program (significance level 0.05).RESULTS: We identified 153 children with autism spectrum disorder, of which 48 underwent a genetic cause investigation: 45 performed microarray analysis (15.6% pathogenic); 42 carried out a molecular study of the Fragile X syndrome (one altered); two performed sequencing of the methyl CpG binding protein 2 (MECP2) gene (one altered). The diagnosis of genetic cause was made in 18.8% of the sample. The identification of the etiology of a genetic cause was related to global development delay/ intellectual disability (p = 0.04) and the presence of relevant family history (p = 0.005).CONCLUSIONS: The diagnostic yield of the genetic study was higher in patients with a global development delay /intellectual disability and in patients with relevant family history.

Genetic and molecular biology of autism spectrum disorder among Middle East population: a review

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disease, characterized by impaired social communication, executive dysfunction, and abnormal perceptual processing. It is more frequent among males. All of these clinical manifestations are associated with atypical neural development. Various genetic and environmental risk factors are involved in the etiology of autism. Genetic assessment is essential for the early detection and intervention which can improve social communications and reduce abnormal behaviors. Although, there is a noticeable ASD incidence in Middle East countries, there is still a lack of knowledge about the genetic and molecular biology of ASD among this population to introduce efficient diagnostic and prognostic methods.

MAIN BODY

In the present review, we have summarized all of the genes which have been associated with ASD progression among Middle East population. We have also categorized the reported genes based on their cell and molecular functions.

CONCLUSIONS

This review clarifies the genetic and molecular biology of ASD among Middle East population and paves the way of introducing an efficient population based panel of genetic markers for the early detection and management of ASD in Middle East countries.

The Relationship between Autism and Ehlers-Danlos Syndromes/Hypermobility Spectrum Disorders

Considerable interest has arisen concerning the relationship between hereditary connective tissue disorders such as the Ehlers-Danlos syndromes (EDS)/hypermobility spectrum disorders (HSD) and autism, both in terms of their comorbidity as well as co-occurrence within the same families. This paper reviews our current state of knowledge, as well as highlighting unanswered questions concerning this remarkable patient group, which we hope will attract further scientific interest in coming years. In particular, patients themselves are demanding more research into this growing area of interest, although science has been slow to answer that call. Here, we address the overlap between these two spectrum conditions, including neurobehavioral, psychiatric, and neurological commonalities, shared peripheral neuropathies and neuropathologies, and similar autonomic and immune dysregulation. Together, these data highlight the potential relatedness of these two conditions and suggest that EDS/HSD may represent a subtype of autism.

The effect of background strain on the behavioral phenotypes of the MDGA2+/- mouse model of autism spectrum disorder

The membrane-associated mucin (MAM) domain containing glycosylphosphatidylinositol anchor 2 protein single knock-out mice (MDGA2^+/- ) are models of ASD. We examined the behavioral phenotypes of male and female MDGA2^+/- and wildtype mice on C57BL6/NJ and C57BL6/N backgrounds at 2 months of age and measured MDGA2, neuroligin 1 and neuroligin 2 levels at 7 months. Mice on the C57BL6/NJ background performed better than those on the C57BL6/N background in visual ability and in learning and memory performance in the Morris water maze and differed in measures of motor behavior and anxiety. Mice with the MDGA2^+/- genotype differed from WT mice in motor, social and repetitive behavior and anxiety, but most of these effects involved interactions between MDGA2^+/- genotype and background strain. The background strain also influenced MDGA2 levels and NLGN2 association in MDGA2^+/- mice. Our findings emphasize the importance of the background strain used in studies of genetically modified mice.

Involvement of the 14-3-3 Gene Family in Autism Spectrum Disorder and Schizophrenia: Genetics, Transcriptomics and Functional Analyses

The 14-3-3 protein family are molecular chaperones involved in several biological functions and neurological diseases. We previously pinpointed YWHAZ (encoding 14-3-3ζ) as a candidate gene for autism spectrum disorder (ASD) through a whole-exome sequencing study, which identified a frameshift variant within the gene (c.659-660insT, p.L220Ffs*18). Here, we explored the contribution of the seven human 14-3-3 family members in ASD and other psychiatric disorders by investigating the: (i) functional impact of the 14-3-3ζ mutation p.L220Ffs*18 by assessing solubility, target binding and dimerization; (ii) contribution of common risk variants in 14-3-3 genes to ASD and additional psychiatric disorders; (iii) burden of rare variants in ASD and schizophrenia; and iv) 14-3-3 gene expression using ASD and schizophrenia transcriptomic data. We found that the mutant 14-3-3ζ protein had decreased solubility and lost its ability to form heterodimers and bind to its target tyrosine hydroxylase. Gene-based analyses using publicly available datasets revealed that common variants in YWHAE contribute to schizophrenia (p = 6.6 × 10-7), whereas ultra-rare variants were found enriched in ASD across the 14-3-3 genes (p = 0.017) and in schizophrenia for YWHAZ (meta-p = 0.017). Furthermore, expression of 14-3-3 genes was altered in post-mortem brains of ASD and schizophrenia patients. Our study supports a role for the 14-3-3 family in ASD and schizophrenia.