Association of genes with phenotype in autism spectrum disorder

Rare Pathogenic Variants Identified in Whole Exome Sequencing of Monozygotic Twins With Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a childhood-onset complex neurodevelopmental disorder characterized by problems with communication and social interaction and restricted, repetitive, stereotyped behavior. The prevalence of ASD is one in 36 children. The genetic architecture of ASD is complex in spite of its high heritability. To identify the potential candidate genes of ASD, we carried out a comprehensive genetic study of monozygotic (MZ) twins concordant or discordant for ASD.

METHODS

Five MZ twins and their parents were recruited for the study. Four of the twins were concordant, whereas one was discordant for ASD. Whole exome sequencing was conducted for the twins and their parents. The exome DNA was enriched using Twist Human Customized Core Exome Kit, and paired-end sequencing was performed on HiSeq system.

RESULTS

We identified several rare and pathogenic variants (homozygous recessive, compound heterozygous, de novo) in ASD-affected individuals.

CONCLUSION

We report novel variants in individuals diagnosed with ASD. Several of these genes are involved in brain-related functions and not previously reported in ASD. Intriguingly, some of the variants were observed in the genes involved in sensory perception (auditory [MYO15A, PLEC, CDH23, UBR3, GPSM2], olfactory [OR9K2], gustatory [TAS2R31], and visual [CDH23, UBR3]). This is the first comprehensive genetic study of MZ twins in an Indian population. Further validation is required to determine whether these variants are associated with ASD.

The Use of CGH Arrays for Identifying Copy Number Variations in Children with Autism Spectrum Disorder

Autism spectrum disorders (ASDs) encompass a broad group of neurodevelopmental disorders with varied clinical symptoms, all being characterized by deficits in social communication and repetitive behavior. Although the etiology of ASD is heterogeneous, with many genes involved, a crucial role is believed to be played by copy number variants (CNVs). The present study examines the role of copy number variation in the development of isolated ASD, or ASD with additional clinical features, among a group of 180 patients ranging in age from two years and four months to 17 years and nine months. Samples were taken and subjected to array-based comparative genomic hybridization (aCGH), the gold standard in detecting gains or losses in the genome, using a 4 × 180 CytoSure Autism Research Array, with a resolution of around 75 kb. The results indicated the presence of nine pathogenic and six likely pathogenic imbalances, and 20 variants of uncertain significance (VUSs) among the group. Relevant variants were more prevalent in patients with ASD and additional clinical features. Twelve of the detected variants, four of which were probably pathogenic, would not have been identified using the routine 8 × 60 k microarray. These results confirm the value of microarrays in ASD diagnostics and highlight the need for dedicated tools.

Influence of β-catenin signaling on neurogenesis in neuropsychiatric disorders: Anxiety and depression

It has been proven that stress, mainly in the early years of life, can lead to anxiety and mood problems. Current treatments for psychiatric disorders are not enough, and some of them show intolerable side effects, emphasizing the urgent need for new treatment targets. Hence, a better understanding of the different brain networks, which are involved in the response to anxiety and depression, may evoke treatments with more specific targets. One of these targets is β-catenin that regulates brain circuits. β-Catenin has a dual response toward stress, which may influence coping or vulnerability to stress response. Indeed, β-catenin signaling involves several processes such as inflammation-directed brain repair, inflammation-induced brain damage, and neurogenesis. Interestingly, β-catenin reduction is accompanied by low neurogenesis, which leads to anxiety and depression. However, in another state, this reduction activates a compensatory mechanism that enhances neurogenesis to protect against depression but may precipitate anxiety. Thus, understanding the molecular mechanism of β-catenin could enhance our knowledge about anxiety and depression's pathophysiology, potentially improving clinical results by targeting it. Herein, the different states of β-catenin were discussed, shedding light on possible drugs that showed action on psychiatric disorders through β-catenin.

Pre-autism: What a paediatrician should know about early diagnosis of autism‎

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as "pre-autism" when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

Using Machine Learning to Explore Shared Genetic Pathways and Possible Endophenotypes in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a heterogeneous condition, characterized by complex genetic architectures and intertwined genetic/environmental interactions. Novel analysis approaches to disentangle its pathophysiology by computing large amounts of data are needed. We present an advanced machine learning technique, based on a clustering analysis on genotypical/phenotypical embedding spaces, to identify biological processes that might act as pathophysiological substrates for ASD. This technique was applied to the VariCarta database, which contained 187,794 variant events retrieved from 15,189 individuals with ASD. Nine clusters of ASD-related genes were identified. The 3 largest clusters included 68.6% of all individuals, consisting of 1455 (38.0%), 841 (21.9%), and 336 (8.7%) persons, respectively. Enrichment analysis was applied to isolate clinically relevant ASD-associated biological processes. Two of the identified clusters were characterized by individuals with an increased presence of variants linked to biological processes and cellular components, such as axon growth and guidance, synaptic membrane components, or transmission. The study also suggested other clusters with possible genotype-phenotype associations. Innovative methodologies, including machine learning, can improve our understanding of the underlying biological processes and gene variant networks that undergo the etiology and pathogenic mechanisms of ASD. Future work to ascertain the reproducibility of the presented methodology is warranted.

Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure

The excitatory/inhibitory (E/I) imbalance hypothesis posits that imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism. However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. We used innovative analysis methods-combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT) to investigate relationships between genetic variance, brain structure and autism symptomatology of participants from the AIMS-2-TRIALS LEAP cohort (autism = 359, male/female = 258/101; neurotypical control participants = 279, male/female = 178/101) aged 6-30 years. Using competitive gene-set analyses, we investigated whether aggregated genetic variation in glutamate and GABA gene-sets could be associated with behavioral measures of autism symptoms and brain structural variation. Further, using the same gene-sets, we corelated expression profiles throughout the cortex with differences in CT between autistic and neurotypical control participants, as well as in separate sensory subgroups. The glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group. In adolescents and adults, brain regions with greater gene-expression of glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants although in opposing directions. Additionally, the gene expression profiles were associated with CT profiles in separate sensory subgroups. Our results suggest complex relationships between E/I related genetics and autism symptom profiles as well as brain structure alterations, where there may be differential roles for glutamate and GABA.

Autism and duplication of 17q12q21.2 by array-CGH: a case report

OBJECTIVE

Autism spectrum disorder (ASD) affects cognitive development and social interaction on different levels. Genetic and environmental factors are associated with secondary ASD. Genetic inheritance is mainly polygenic, and 10% are copy number variations (CNVs). Array comparative genomic hybridization (array-CGH) is used to identify CNVs. This report aimed to discuss autism spectrum disorder and its diagnosis by array comparative genomic hybridization, highlighting the association with the pathogenic duplication of 17q12q21.2.

CASE DESCRIPTION

A male baby was born at 37 weeks' gestation by cesarean section. The child showed strabismus, cryptorchidism, hypertelorism, frontal bossing, and developmental delay, walking at 25 months and talking at 4 years. At the age of 2 years, array-CGH of peripheral blood revealed a 5.6-Mb 17q12q21.2 duplication or arr 17q12q21.2 (34,815,527-40,213.109)x3 encompassing 190 genes, including HNF-1B and LHX1. The child was clinically diagnosed with ASD.

COMMENTS

Changes in the 17q12 segment, such as the duplication found, have been associated with the development of several problems in previous studies, mainly kidney diseases and behavioral disorders. Located at this chromosome region, HNF1's homeobox B codes a member of the superfamily containing homeodomain of transcription factors. Another gene associated with abnormalities in neurological development regarding 17q12 deletions is LHX1, as shown in this case study. LHX1 plays a role in the migration and differentiation of GABA neurons, modulating the survival of pre-optical interneurons, thus affecting cellular migration and distribution in the cortex. Changes in this control result in flaws in interneuron development, contributing to the pathophysiology of psychiatric diseases.

Insights on dental care management and prevention in children with autism spectrum disorder (ASD). What is new?

Autistic subjects represent a severe concern to dentistry due to the considerable difficulty in managing their oral health, maintaining routine toothbrushing, and preventing dental and periodontal problems. The social and economic burden of managing dental care in autism spectrum disorder (ASD) children is particularly cumbersome for families and public and private health expenditure, especially when children reach the dentist following a late diagnosis with evident oral health problems. An early diagnosis of ASD helps dentists better address these children's oral health. Unfortunately, insufficient attention is paid to the training and education of general pediatricians, dentists, and dental hygienists, allowing them to get to approach the different clinical aspects of ASD. Usually, children diagnosed with ASD are scheduled for dental appointments like their neurotypical peers, whereas their needs are typically complex and personalized. Scant attention is also devoted to these patients by commercial manufacturers of dental products and devices for oral hygiene and prevention of caries and periodontal diseases, leaving parents without the support and often failing when they address the oral health of autistic children. The difficulties of oral care do not derive simply from the behavior of ASD patients, as is commonly assumed, and therefore cannot be overcome solely by the patience and attention of parents and dentists. Genetics, dietary habits, sensory impairments, and cognition disorders are other causes contributing in various degrees to the impact on the mood and psychological reactions of autistic children towards dentists. How can we prevent teeth caries, periodontal disorders, and other oral health impairments by properly managing ASD children? This manuscript gives an up-to-date overview of these problems and helps to provide good remarks.

Prediction of Communicative Disorders Linked to Autistic Spectrum Disorder Based on Early Psychomotor Analysis

This systematic review evaluated psychomotor differences between children with and without siblings who have autism spectrum disorder (ASD), as well as the most reliable psychomotor skills that can help predict ASD and its associated language disorders. Literature from 2005 to 2020 was searched using the following databases: PubMed, Trip Medical Database, Cochrane, Web of Science, Science Direct, and Brain. A total 11 papers were included. Fine motor skills and joint attention displayed reliable results in order to predict ASD and its associated language disorders. The period between the first and the second year of life was considered the most appropriate one for the assessment of psychomotor skills. The best period to predict language disorders and ASD diagnosis is around 36 months old.

Zebrafish Modeling of Autism Spectrum Disorders, Current Status and Future Prospective

Autism spectrum disorder (ASD) refers to a complicated range of childhood neurodevelopmental disorders which can occur via genetic or non-genetic factors. Clinically, ASD is associated with problems in relationships, social interactions, and behaviors that pose many challenges for children with ASD and their families. Due to the complexity, heterogeneity, and association of symptoms with some neuropsychiatric disorders such as ADHD, anxiety, and sleep disorders, clinical trials have not yielded reliable results and there still remain challenges in drug discovery and development pipeline for ASD patients. One of the main steps in promoting lead compounds to the suitable drug for commercialization is preclinical animal testing, in which the efficacy and toxicity of candidate drugs are examined in vivo. In recent years, zebrafish have been able to attract the attention of many researchers in the field of neurological disorders such as ASD due to their outstanding features. The presence of orthologous genes for ASD modeling, the anatomical similarities of parts of the brain, and similar neurotransmitter systems between zebrafish and humans are some of the main reasons why scientists draw attention to zebrafish as a prominent animal model in preclinical studies to discover highly effective treatment approaches for the ASD through genetic and non-genetic modeling methods.

Population-based genetic effects for developmental stuttering

Despite a lifetime prevalence of at least 5%, developmental stuttering, characterized by prolongations, blocks, and repetitions of speech sounds, remains a largely idiopathic speech disorder. Family, twin, and segregation studies overwhelmingly support a strong genetic influence on stuttering risk; however, its complex mode of inheritance combined with thus-far underpowered genetic studies contribute to the challenge of identifying and reproducing genes implicated in developmental stuttering susceptibility. We conducted a trans-ancestry genome-wide association study (GWAS) and meta-analysis of developmental stuttering in two primary datasets: The International Stuttering Project comprising 1,345 clinically ascertained cases from multiple global sites and 6,759 matched population controls from the biobank at Vanderbilt University Medical Center (VUMC), and 785 self-reported stuttering cases and 7,572 controls ascertained from The National Longitudinal Study of Adolescent to Adult Health (Add Health). Meta-analysis of these genome-wide association studies identified a genome-wide significant (GWS) signal for clinically reported developmental stuttering in the general population: a protective variant in the intronic or genic upstream region of SSUH2 (rs113284510, protective allele frequency = 7.49%, Z = -5.576, p = 2.46 × 10^-8) that acts as an expression quantitative trait locus (eQTL) in esophagus-muscularis tissue by reducing its gene expression. In addition, we identified 15 loci reaching suggestive significance (p < 5 × 10^-6). This foundational population-based genetic study of a common speech disorder reports the findings of a clinically ascertained study of developmental stuttering and highlights the need for further research.

Brain exosomes as minuscule information hub for Autism Spectrum Disorder

INTRODUCTION

Autism spectrum disorder (ASD) is a neurodevelopmental disorder initiating in the first three years of life. Early initiation of management therapies can significantly improve the health and quality of life of ASD subjects. Thus, indicating the need for suitable biomarkers for the early identification of ASD. Various biological domains were investigated in the quest for reliable biomarkers. However, most biomarkers are in the preliminary stage, and clinical validation is yet to be defined. Exosome based research gained momentum in various Central Nervous System disorders for biomarker identification. However, the utility and prospect of exosomes in ASD is still underexplored.

AREAS COVERED

In the present review, we summarized the biomarker discovery current status and the future of brain-specific exosomes in understanding pathophysiology and its potential as a biomarker. The studies reviewed herein were identified via systematic search (dated: June 2021) of PubMed using variations related to autism (ASD OR autism OR Autism spectrum disorder) AND exosomes AND/OR biomarkers.

EXPERT OPINION

As exosomess are highly relevant in brain disorders like ASD, direct access to brain tissue for molecular assessment is ethically impossible. Thus investigating the brain-derived exosomes would undoubtedly answer many unsolved aspects of the pathogenesis and provide reliable biomarkers.

Text mining of gene-phenotype associations reveals new phenotypic profiles of autism-associated genes

Autism is a spectrum disorder with wide variation in type and severity of symptoms. Understanding gene-phenotype associations is vital to unravel the disease mechanisms and advance its diagnosis and treatment. To date, several databases have stored a large portion of gene-phenotype associations which are mainly obtained from genetic experiments. However, a large proportion of gene-phenotype associations are still buried in the autism-related literature and there are limited resources to investigate autism-associated gene-phenotype associations. Given the abundance of the autism-related literature, we were thus motivated to develop Autism_genepheno, a text mining pipeline to identify sentence-level mentions of autism-associated genes and phenotypes in literature through natural language processing methods. We have generated a comprehensive database of gene-phenotype associations in the last five years' autism-related literature that can be easily updated as new literature becomes available. We have evaluated our pipeline through several different approaches, and we are able to rank and select top autism-associated genes through their unique and wide spectrum of phenotypic profiles, which could provide a unique resource for the diagnosis and treatment of autism. The data resources and the Autism_genpheno pipeline are available at: https://github.com/maiziezhoulab/Autism_genepheno .

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.

A proteomic analysis of urine biomarkers in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by early-onset social-communication challenges, restricted and repetitive behaviors, or unusual sensory-motor behaviors. A lack of specific biomarkers hinders the early diagnosis and treatment of this disease in many children. This study analyzes and validates potential urinary biomarkers using mass spectrometry proteomics. Global proteomics profiles of urine from 19 ASD patients and 19 healthy control subjects were compared to identify significantly changed proteins. These proteins were validated with targeted proteomics using parallel reaction monitoring (PRM) in an independent validation set consisting of samples from 40 ASD patients and 38 healthy controls. A total of 34 significantly changed proteins were found in the discovery set, among which seven proteins were identified as potential biomarkers for ASD through PRM assays in the validation set. Of these seven proteins, immunoglobulin kappa variable 4-1, immunoglobulin kappa variable 3-20, and immunoglobulin lambda variable 1-51 were up-regulated, while ATP synthase F1 subunit alpha, 10 kDa heat shock protein, apolipoprotein C-III, and arylsulfatase F were down-regulated. Six of these seven proteins support previous findings that ASD is accompanied by altered immune response and lipid metabolism, as well as mitochondrial dysfunction. This study lays the groundwork for additional research using biomarkers to clinically diagnose ASD. The proteomics and PRM raw data of this study have been deposited under the accession number IPX0002592000 at iProX. SIGNIFICANCE: This study identified 34 proteins in urine of ASD patients that were significantly changed from the urinary proteins of healthy subjects using LC-MS/MS-based proteomics in a discovery set. Seven of these proteins were validated by PRM analysis in an independent validation set. This report represents the first description of combined label-free quantitative proteomics and PRM analysis of targeted proteins for discovery of ASD urinary biomarkers. The results will be helpful for early diagnosis and can provide additional insight into the molecular mechanisms of ASD.

Preeclampsia Drives Molecular Networks to Shift Toward Greater Vulnerability to the Development of Autism Spectrum Disorder

Preeclampsia (PE) confers a significant risk for subsequent diagnosis with autism spectrum disorder (ASD), with the mechanisms underlying this observation being largely unknown. To identify molecular networks affected by both PE and ASD, we conducted a large-scale literature data mining and a gene set enrichment analysis (GSEA), followed by an expression mega-analysis in 13 independently profiled ASD datasets. Sets of genes implicated in ASD and in PE significantly overlap (156 common genes; p = 3.14E⁻⁶⁷), with many biological pathways shared (94 pathways; p < 1.00E⁻²¹). A set of PE-driven molecular triggers possibly contributing to worsening the risk of subsequent ASD was identified, possibly representing a regulatory shift toward greater vulnerability to the development of ASD. Mega-analysis of expression highlighted RPS4Y1, an inhibitor of STAT3 that is expressed in a sexually dimorphic manner, as a contributor to both PE and ASD, which should be evaluated as a possible contributor to male predominance in ASD. A set of PE-driven molecular triggers may shift the developing brain toward a greater risk of ASD. One of these triggers, chromosome Y encoded gene RPS4Y1, an inhibitor of STAT3 signaling, warrants evaluation as a possible contributor to male predominance in ASD.

The role of neuroglia in autism spectrum disorders

Neuroglia are a large class of neural cells of ectodermal (astroglia, oligodendroglia, and peripheral glial cells) and mesodermal (microglia) origin. Neuroglial cells provide homeostatic support, protection, and defense to the nervous tissue. Pathological potential of neuroglia has been acknowledged since their discovery. Research of the recent decade has shown the key role of all classes of glial cells in autism spectrum disorders (ASD), although molecular mechanisms defining glial contribution to ASD are yet to be fully characterized. This narrative conceptualizes recent findings of the broader roles of glial cells, including their active participation in the control of cerebral environment and regulation of synaptic development and scaling, highlighting their putative involvement in the etiopathogenesis of ASD.