Low-pass whole genome sequencing as a cost-effective alternative to chromosomal microarray analysis for low- and middle-income countries.

Low-pass whole genome sequencing (LP-WGS) has been applied as alternative method to detect copy number variants (CNVs) in the clinical setting. Compared with chromosomal microarray analysis (CMA), the sequencing-based approach provides a similar resolution of CNV detection at a lower cost. In this study, we assessed the efficiency and reliability of LP-WGS as a more affordable alternative to CMA. A total of 1363 patients with unexplained neurodevelopmental delay/intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies were enrolled. Those patients were referred from 15 nonprofit organizations and university centers located in different states in Brazil. The analysis of LP-WGS at 1x coverage (>50kb) revealed a positive testing result in 22% of the cases (304/1363), in which 219 and 85 correspond to pathogenic/likely pathogenic (P/LP) CNVs and variants of uncertain significance (VUS), respectively. The 16% (219/1363) diagnostic yield observed in our cohort is comparable to the 15%-20% reported for CMA in the literature. The use of commercial software, as demonstrated in this study, simplifies the implementation of the test in clinical settings. Particularly for countries like Brazil, where the cost of CMA presents a substantial barrier to most of the population, LP-WGS emerges as a cost-effective alternative for investigating copy number changes in cytogenetics.

Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment.

There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.

A Novel Mutation in the MAP7D3 Gene in Two Siblings with Severe Intellectual Disability and Autistic Traits: Concurrent Assessment of BDNF Functional Polymorphism, X-Inactivation and Oxidative Stress to Explain Disease Severity.

Intellectual disabilities (ID) and autism spectrum disorders (ASD) are characterized by extreme genetic and phenotypic heterogeneity. However, understanding this heterogeneity is difficult due to the intricate interplay among multiple interconnected genes, epigenetic factors, oxidative stress, and environmental factors. Employing next-generation sequencing (NGS), we revealed the genetic cause of ID and autistic traits in two patients from a consanguineous family followed by segregation analysis. Furthermore, in silico prediction methods and 3D modeling were conducted to predict the effect of the variants. To establish genotype-phenotype correlation, X-chromosome inactivation using Methylation-specific PCR and oxidative stress markers were also investigated. By analyzing the NGS data of the two patients, we identified a novel frameshift mutation c.2174_2177del (p.Thr725MetfsTer2) in the MAP7D3 gene inherited from their mother along with the functional BDNF Val66Met polymorphism inherited from their father. The 3D modeling demonstrated that the p.Thr725MetfsTer2 variant led to the loss of the C-terminal tail of the MAP7D3 protein. This change could destabilize its structure and impact kinesin-1's binding to microtubules via an allosteric effect. Moreover, the analysis of oxidative stress biomarkers revealed an elevated oxidative stress in the two patients compared to the controls. To the best of our knowledge, this is the first report describing severe ID and autistic traits in familial cases with novel frameshift mutation c.2174_2177del in the MAP7D3 gene co-occurring with the functional polymorphism Val66M in the BDNF gene. Besides, our study underlines the importance of investigating combined genetic variations, X-chromosome inactivation (XCI) patterns, and oxidative stress markers for a better understanding of ID and autism etiology.

Caregiver-based perception of disease burden in Schaaf-Yang syndrome.

BACKGROUND: Schaaf-Yang syndrome (SYS) is a neurodevelopmental disorder caused by truncating variants in the paternally expressed MAGEL2 gene in the Prader-Willi syndrome-region on chromosome 15q. In addition to hypotonia and intellectual disability, individuals with SYS are frequently affected by neonatal contractures and autism spectrum disorder. In this study, we focus on the burden of disease on patients and their families for the first time. METHODS: Based on the online SYS Patient Voices Survey the perspective of 81 primary caregivers on SYS was assessed. RESULTS: The perceived severity of muscular and developmental manifestations dominated the evaluation of the phenotype in early childhood, while behavioral issues were considered more impactful later in life. Importantly, an apprehension toward symptoms with a later onset was observed in caregivers of younger children. Available therapeutic options, while mostly effective, did not sufficiently alleviate the total burden of disease. Overall, parents stated that caring for an individual with SYS was very challenging, affecting their daily lives and long-term planning. CONCLUSION: Our study demonstrates the necessity for treatments that, adapted to age and in accordance with the caregivers' prioritization, improve the patients' medical condition and thus facilitate their and their families' social participation.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population.

Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment. Objective: To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations. Design, Setting, and Participants: This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022. Main Outcomes and Measures: The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations. Results: Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] ß, 0.83 [0.02]; P = 4.22 × 10-6). Conclusions and Relevance: This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Assessment of vulnerability dimensions considering Family History and environmental interplay in Autism Spectrum Disorder.

BACKGROUND: Despite previous studies have recently shown Autism Spectrum Disorders (ASD) as having a strong genetics background, over a minimum environmental background, no study up to date has investigated the interplay between genetics and environment. METHODS: We have collected data regarding Family History (FH) and Environmental Factors (EF) from 2,141 individuals with ASD and their caretakers throughout Brazil, based on an online questionnaire. Most of the ASD individuals were males (81%) and the average age was 02 years minimum for males and females, and the maximum age was 41 years for males and 54 for females. People from all states in Brazil have answered the questionnaire. Genetic inheritance was obtained based on the declared FH of Psychiatric and Neurological diagnosis. As for EF, exposure to risk factors during pregnancy was considered, like infections, diabetes, drugs/chemicals exposure, socioeconomic, and psychological factors. Respondents were invited to answer the questionnaire in lectures given throughout Brazil, and by the social networks of the NGO "The Tooth Fairy Project". A Multiple Correspondence Analysis (MCA) was conducted to search vulnerability dimensions, and a Cluster Analysis was conducted to classify and identify the subgroups. RESULTS: Regarding EF, social and psychological exposures contributed to the first two dimensions. Concerning FH, the first dimension represented psychiatric FH, while the second represented neurological FH. When analyzed together, EF and FH contributed to two new dimensions: 1. psychiatric FH, and 2. a psychosocial component. Using Cluster Analysis, it was not possible to isolate subgroups by genetic vulnerability or environmental exposure. Instead, a gradient of psychiatric FH with similar contributions of EF was observed. CONCLUSION: In this study, it was not possible to isolate groups of patients that correspond to only one component, but rather a continuum with different compositions of genetic and environmental interplay.

Concurrent Assessment of Oxidative Stress and MT-ATP6 Gene Profiling to Facilitate Diagnosis of Autism Spectrum Disorder (ASD) in Tamil Nadu Population.

Autism spectrum disorder (ASD) is a neurodevelopmental disability that causes social impairment, debilitated verbal or nonverbal conversation, and restricted/repeated behavior. Recent research reveals that mitochondrial dysfunction and oxidative stress might play a pivotal role in ASD condition. The goal of this case-control study was to investigate oxidative stress and related alterations in ASD patients. In addition, the impact of mitochondrial DNA (mtDNA) mutations, particularly MT-ATP6, and its link with oxidative stress in ASD was studied. We found that ASD patient's plasma had lower superoxide dismutase (SOD) and higher catalase (CAT) activity, resulting in lower SOD/CAT ratio. MT-ATP6 mutation analysis revealed that four variations, 8865 G>A, 8684 C>T, 8697 G>A, and 8836 A>G, have a frequency of more than 10% with missense and synonymous (silent) mutations. It was observed that abnormalities in mitochondrial complexes (I, III, V) are more common in ASD, and it may have resulted in MT-ATP6 changes or vice versa. In conclusion, our findings authenticate that oxidative stress and genetics both have an equal and potential role behind ASD and we recommend to conduct more such concurrent research to understand their unique mechanism for better diagnosis and therapeutic for ASD.

The people behind the papers - Rana Fetit and David Price.

16p11.2 microdeletions are genetically associated with autism spectrum disorder (ASD), but the links to the various patient phenotypes are not well understood. In a new paper in Development, Rana Fetit and colleagues use ventral organoids derived from induced pluripotent stem cells to dissect the effect of 16p11.2 microdeletions on interneuron development. We caught up with corresponding author Rana Fetit and group leader David Price to find out more about their research.

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment.

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection.

BACKGROUND: Transgenerational epigenetic risks associated with complex health outcomes, such as autism spectrum disorder (ASD), have attracted increasing attention. Transgenerational environmental risk exposures with potential for epigenetic effects can be effectively identified using space-time clustering. Specifically applied to ancestors of individuals with disease outcomes, space-time clustering characterized for vulnerable developmental stages of growth can provide a measure of relative risk for disease outcomes in descendants. OBJECTIVES: (1) Identify space-time clusters of ancestors with a descendent with a clinical ASD diagnosis and matched controls. (2) Identify developmental windows of ancestors with the highest relative risk for ASD in descendants. (3) Identify how the relative risk may vary through the maternal or paternal line. METHODS: Family pedigrees linked to residential locations of ASD cases in Utah have been used to identify space-time clusters of ancestors. Control family pedigrees of none-cases based on age and sex have been matched to cases 2:1. The data have been categorized by maternal or paternal lineage at birth, childhood, and adolescence. A total of 3957 children, both parents, and maternal and paternal grandparents were identified. Bernoulli space-time binomial relative risk (RR) scan statistic was used to identify clusters. Monte Carlo simulation was used for statistical significance testing. RESULTS: Twenty statistically significant clusters were identified. Thirteen increased RR (> 1.0) space-time clusters were identified from the maternal and paternal lines at a p-value < 0.05. The paternal grandparents carry the greatest RR (2.86-2.96) during birth and childhood in the 1950's-1960, which represent the smallest size clusters, and occur in urban areas. Additionally, seven statistically significant clusters with RR < 1 were relatively large in area, covering more rural areas of the state. CONCLUSION: This study has identified statistically significant space-time clusters during critical developmental windows that are associated with ASD risk in descendants. The geographic space and time clusters family pedigrees with over 3 + generations, which we refer to as a person's geographic legacy, is a powerful tool for studying transgenerational effects that may be epigenetic in nature. Our novel use of space-time clustering can be applied to any disease where family pedigree data is available.

Neurocognitive, behavioral and socio-adaptive functioning assessment in a case of Coffin-Siris syndrome: A holistic approach/perspective beyond the identification of the disorder.

PURPOSE: Coffin-Siris syndrome (CSS) is a rare genetic disorder characterized by the presence of particular facies, congenital malformations, intellectual developmental disorder, behavioral issues, and speech and language impairment. Thorough neuropsychological assessments in the case of CSS have been reported infrequently, and its subdomains are poorly defined. A detailed description of the clinical, neurocognitive, behavioral, socio-adaptive sequelae of the patient with CSS is provided. RESULTS: The clinical diagnosis in the patient was confirmed by genetic analysis, which identified the presence of mutation of ARID1B gene; the parents' Sanger sequencing reported normal. The neuropsychological assessments revealed borderline intellectual functioning (IQ-75, verbal > performance) with a mild socio-adaptive deficit score of 64 as suggested by the adaptive scale. The behavioral profile reported that the child had significant difficulties in the attention subdomain with concern in social and thought subdomains. The child met the profile for mild severity of Autism Spectrum Disorder and did not meet the criteria for Attention Deficit Hyperactivity Disorder. In addition, the child had scholastic difficulties in reading and mathematical skills. CONCLUSION: Neurocognitive, behavioral, socio-adaptive functioning and comorbidity assessment in order to provide holistic management of such children after thorough evaluation is essential for their overall functioning.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels.

PURPOSE: Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not. METHODS: Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship. RESULTS: As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants. CONCLUSION: Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.

Clinical utility and cost-effectiveness analysis of chromosome testing concomitant with chromosomal microarray of patients with constitutional disorders in a U.S. academic medical center.

Chromosomal microarray (CMA) is now widely used as first-tier testing for the detection of copy number variants (CNVs) and absence of heterozygosity (AOH) in patients with multiple congenital anomalies (MCA), autism spectrum disorder (ASD), developmental delay (DD), and/or intellectual disability (ID). Chromosome analysis is commonly used to complement CMA in the detection of balanced genomic aberrations. However, the cost-effectiveness and the impact on clinical management of chromosome analysis concomitant with CMA were not well studied, and there is no consensus on how to best utilize these two tests. To assess the clinical utility and cost-effectiveness of chromosome analysis concomitant with CMA in patients with MCA, ASD, DD, and/or ID, we retrospectively analyzed 3,360 postnatal cases for which CMA and concomitant chromosome analysis were performed in the Colorado Genetic Laboratory (CGL) at the University Of Colorado School Of Medicine. Chromosome analysis alone yielded a genetic diagnosis in two patients (0.06%) and contributed additional information to CMA results in 199 (5.92%) cases. The impact of abnormal chromosome results on patient management was primarily related to counseling for reproductive and recurrence risks assessment (101 cases, 3.01%) while a few (5 cases, 0.15%) led to changes in laboratory testing and specialist referral (25 cases, 0.74%). The incremental cost-effectiveness ratio (ICER) of combined testing demonstrated the cost of each informative chromosome finding was significantly higher for patients with clinically insignificant (CI) CMA findings versus clinically significant (CS) CMA results. Our results suggest that a stepwise approach with CMA testing with reflex to chromosome analysis on cases with CS CMA findings is a more cost-effective testing algorithm for patients with MCA, ASD, and/or DD/ID.

Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits.

Epidemiological studies show high comorbidity between different mental health problems, indicating that individuals with a diagnosis of one disorder are more likely to develop other mental health problems. Genetic studies reveal substantial sharing of genetic factors across mental health traits. However, mental health is also genetically correlated with socio-economic status (SES), and it is therefore important to investigate and disentangle the genetic relationship between mental health and SES. We used summary statistics from large genome-wide association studies (average N ~ 160,000) to estimate the genetic overlap across nine psychiatric disorders and seven substance use traits and explored the genetic influence of three different indicators of SES. Using genomic structural equation modelling, we show significant changes in patterns of genetic correlations after partialling out SES-associated genetic variation. Our approach allows the separation of disease-specific genetic variation and genetic variation shared with SES, thereby improving our understanding of the genetic architecture of mental health.

La neuroanatomía y neurofisiología en la comprensión de los trastornos del espectro autista / Neuroanatomy and neurophysiology in the study of autism spectrum disorders

Introducción: Los trastornos de espectro autista se caracterizan por presentar un déficit en la interacción y comunicación social con presencia de patrones repetitivos y restrictivos de comportamiento, intereses y actividades. En ellos estarían implicadas causas genéticas, ambientales y del desarrollo del sistema nervioso central. Un mayor conocimiento de la neuroanatomía y la neurofisiología ayudaría a comprender mejor este trastorno del neurodesarrollo. Objetivo: Profundizar en el conocimiento neuroanatómico y neurofisiológico de los trastornos del espectro autista. Métodos: Se realizó una búsqueda bibliográfica acerca del tema en las bases de datos LILACS, Scopus, SciELO, Pubmed, Medigraphic. Se escogieron 13 documentos, todos correspondientes a artículos originales que abordan el tema desde diferentes aristas. De los documentos, dos fueron localizados en Scopus, uno en Pubmed, cuatro en Medigrafhic, dos en LILACS y cuatro en SciELO. Resultados: Los trastornos de espectro autista se producen por una alteración estructural y funcional de la corteza cerebral. Los estudios de neuroimágenes han demostrado las alteraciones estructurales, fundamentalmente en la corteza prefrontal y sus conexiones, principal región encefálica implicada en la regulación de la conducta social. Las técnicas de secuenciación genómica de nueva generación muestran el origen genético en casos donde los estudios previamente señalados han resultado ser normales. Conclusiones: La profundización del conocimiento neuroanatómico y neurofisiológico de los trastornos de espectro autista permiten comprenderlos mejor(AU)

Introduction: Autism spectrum disorders are characterized by social deficits and communication difficulties, as well as restrictive, repetitive behavior patterns, interests and activities. Their causes may be genetic, environmental or related to the development of the central nervous system. Broader knowledge about neuroanatomy and neurophysiology could lead to a better understanding of this neurodevelopmental disorder. Objective: Gain insight into the neuroanatomy and neurophysiology of autism spectrum disorders. Methods: A bibliographic search about the topic was conducted in the databases LILACS, Scopus, SciELO, Pubmed and Medigraphic. A total 13 documents were selected, all of which were original papers approaching the topic from different perspectives. Two of the documents were obtained from Scopus, one from Pubmed, four from Medigraphic, two from LILACS and four from SciELO. Results: Autism spectrum disorders are caused by a structural and functional alteration of the cerebral cortex. Neuroimaging studies have shown the structural alterations, which mainly occur in the prefrontal cortex and its connections, the principal encephalic region involved in social behavior regulation. New generation genomic sequencing techniques reveal a genetic origin in cases where previous studies have been normal. Conclusions: Broader knowledge about the neuroanatomy and neurophysiology of autism spectrum disorders lead to their better understanding(AU)

Assessment of children in the autistic spectrum disorder that carry the Thr92Ala-DIO2 polymorphism.

INTRODUCTION: A polymorphism in the type 2 deiodinase (Thr92Ala-DIO2) gene has been associated with behavioral and cognitive dysfunction as well as neurodegeneration and oxidative stress in the central nervous system. OBJECTIVE: To test whether the minor allele (Ala92) frequency (MAF) is increased in children in the autism spectrum disorder (ASD), and whether carriers of the minor allele exhibit more severe symptoms and/or worse adaptive behavior. STUDY DESIGN: ASD children were evaluated at baseline and yearly throughout the study by psychologists using the following tools: autism behavior checklist, Vineland Adaptative Behaviour Scales II, non-verbal intelligence test SON-R 21/2-7, SON-R 6-40, Weschler scale for intelligence, and autism treatment evaluation checklist. SETTINGS: Academic outpatient mental health facility in Sao Paulo, Brazil. PARTICIPANTS: ASD boys and girls younger than 18 years of age. 132 consecutive ASD children, mostly boys (~ 80%); ~ 50% was classified as verbal. Exclusion criteria were coexistence of sensory and/or physical impairment, or any associated genetic syndromes. RESULTS: Median follow-up was for an uninterrupted period of 937 days (139-1375 days), which did not vary significantly among the genotypes. The MAF was 47% in ASD patients vs. 51% in a local reference population with similar ethnic background; the clinical severity and progression were not affected by the minor allele. Carriers of the minor allele exhibited higher adaptive behavior in the domains "daily living skills" and "communication", which correlated positively with the dose of the minor allele. CONCLUSION: The MAF is not different in ASD children, but carriers of the Thr92Ala-DIO2 polymorphism exhibited higher adaptive behavior.

Diagnostic Yield and Economic Implications of Whole-Exome Sequencing for ASD Diagnosis in Israel.

Whole-exome sequencing (WES) is an effective approach to identify the susceptibility of genetic variants of autism spectrum disorder (ASD). The Israel Ministry of Health supports WES as an adjunct tool for ASD diagnosis, despite its unclear diagnostic yield and cost effectiveness. To address this knowledge gap, we applied WES to a population-based sample of 182 Bedouin and Jewish children with ASD from southern Israel, and assessed its yield in a gene panel of 205 genes robustly associated with ASD. We then compared the incremental cost-effectiveness ratios (ICERs) for an ASD diagnosis by WES, chromosomal microarray analysis (CMA), and CMA + WES. Overall, 32 ASD candidate variants were detected in 28 children, corresponding to an overall WES diagnostic yield of 15.4%. Interestingly, the diagnostic yield was significantly higher for the Bedouin children than for the Jewish children, i.e., 27.6% vs. 11.1% (p = 0.036). The most cost-effective means for genetic testing was the CMA alone, followed closely by the CMA + WES strategy (ICER = USD 117 and USD 124.8 per child). Yet, WES alone could become more cost effective than the other two approaches if there was to be a 25% increase in its yield or a 50% decrease in its cost. These findings suggest that WES should be recommended to facilitate ASD diagnosis in Israel, especially for highly consanguineous populations, such as the Bedouin.

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children.

Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as Autistic Spectrum Disorder (ASD). We performed a combined approach of miRNA expression profiling by NanoString technology, followed by validation experiments in qPCR, and 16S rRNA microbiome analysis on saliva from 53 ASD and 27 neurologically unaffected control (NUC) children. MiR-29a-3p and miR-141-3p were upregulated, while miR-16-5p, let-7b-5p, and miR-451a were downregulated in ASD compared to NUCs. Microbiome analysis on the same subjects revealed that Rothia, Filifactor, Actinobacillus, Weeksellaceae, Ralstonia, Pasteurellaceae, and Aggregatibacter increased their abundance in ASD patients, while Tannerella, Moryella and TM7-3 decreased. Variations of both miRNAs and microbes were statistically associated to different neuropsychological scores related to anomalies in social interaction and communication. Among miRNA/bacteria associations, the most relevant was the negative correlation between salivary miR-141-3p expression and Tannerella abundance. MiRNA and microbiome dysregulations found in the saliva of ASD children are potentially associated with cognitive impairments of the subjects. Furthermore, a potential cross-talking between circulating miRNAs and resident bacteria could occur in saliva of ASD.

Clinical Assessment, Genetics, and Treatment Approaches in Autism Spectrum Disorder (ASD).

Autism spectrum disorder (ASD) consists of a genetically heterogenous group of neurobehavioral disorders characterized by impairment in three behavioral domains including communication, social interaction, and stereotypic repetitive behaviors. ASD affects more than 1% of children in Western societies, with diagnoses on the rise due to improved recognition, screening, clinical assessment, and diagnostic testing. We reviewed the role of genetic and metabolic factors which contribute to the causation of ASD with the use of new genetic technology. Up to 40 percent of individuals with ASD are now diagnosed with genetic syndromes or have chromosomal abnormalities including small DNA deletions or duplications, single gene conditions, or gene variants and metabolic disturbances with mitochondrial dysfunction. Although the heritability estimate for ASD is between 70 and 90%, there is a lower molecular diagnostic yield than anticipated. A likely explanation may relate to multifactorial causation with etiological heterogeneity and hundreds of genes involved with a complex interplay between inheritance and environmental factors influenced by epigenetics and capabilities to identify causative genes and their variants for ASD. Behavioral and psychiatric correlates, diagnosis and genetic evaluation with testing are discussed along with psychiatric treatment approaches and pharmacogenetics for selection of medication to treat challenging behaviors or comorbidities commonly seen in ASD. We emphasize prioritizing treatment based on targeted symptoms for individuals with ASD, as treatment will vary from patient to patient based on diagnosis, comorbidities, causation, and symptom severity.