scholarly journals Chromosomal Abnormalities in Patients With Autism Spectrum Disorders From Taiwan

2013 ◽  
Vol 162 (7) ◽  
pp. 734-741 ◽  
Author(s):  
Hsiao-Mei Liao ◽  
Susan Shur-Fen Gau ◽  
Wen-Che Tsai ◽  
Jye-Siung Fang ◽  
Ying-Cheng Su ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Chromosomal Abnormalities ◽  
Autism Spectrum ◽  
Spectrum Disorders

scholarly journals Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

2020 ◽  
Vol 21 (17) ◽  
pp. 6274
Author(s):  
Maria Vittoria Ristori ◽  
Stefano Levi Mortera ◽  
Valeria Marzano ◽  
Silvia Guerrera ◽  
Pamela Vernocchi ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Biomarker Discovery ◽  
Chromosomal Abnormalities ◽  
Single Gene ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Autism Spectrum ◽  
Added Value ◽  
Diagnostic Tools ◽  
Spectrum Disorders

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

scholarly journals Assessment and Treatment in Autism Spectrum Disorders: A Focus on Genetics and Psychiatry

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Merlin G. Butler ◽  
Erin L. Youngs ◽  
Jennifer L. Roberts ◽  
Jessica A. Hellings
Keyword(s):  
Autism Spectrum Disorders ◽  
Chromosomal Abnormalities ◽  
Psychiatric Treatment ◽  
Single Gene ◽  
Challenging Behaviors ◽  
Autism Spectrum ◽  
Metabolic Disturbances ◽  
Dna Deletions ◽  
Assessment And Treatment ◽  
Spectrum Disorders

Autism spectrum disorders (ASDs) are neurobehavioral disorders characterized by abnormalities in three behavioral domains including social interaction, impaired communication, and repetitive stereotypic behaviors. ASD affects approximately 1% of children and is on the rise with significant genetic mechanisms underlying these disorders. We review the current understanding of the role of genetic and metabolic factors contributing to ASD with the use of new genetic technology. Fifty percent is diagnosed with chromosomal abnormalities, small DNA deletions/duplications, single-gene conditions, or metabolic disturbances. Genetic evaluation is discussed along with psychiatric treatment and approaches for selection of medication to treat associated challenging behaviors or comorbidities seen in ASD. We emphasize the importance of prioritizing treatment based on target symptom clusters and in what order for individuals with ASD, as the treatment may vary from patient to patient.

Autism spectrum disorders associated with chromosomal abnormalities

2010 ◽  
Vol 4 (3) ◽  
pp. 319-327 ◽  
Author(s):  
Adriana Lo-Castro ◽  
Arianna Benvenuto ◽  
Cinzia Galasso ◽  
Cristina Porfirio ◽  
Paolo Curatolo
Keyword(s):  
Autism Spectrum Disorders ◽  
Chromosomal Abnormalities ◽  
Autism Spectrum ◽  
Spectrum Disorders

scholarly journals Identification of Copy Number Variation by Array-CGH in Portuguese Children and Adolescents Diagnosed with Autism Spectrum Disorders

2019 ◽  
Vol 50 (06) ◽  
pp. 367-377
Author(s):  
S. Monteiro ◽  
J. Pinto ◽  
A. Mira Coelho ◽  
M. Leão ◽  
S. Dória
Keyword(s):  
Autism Spectrum Disorders ◽  
Copy Number ◽  
Array Cgh ◽  
Chromosomal Abnormalities ◽  
Daily Practice ◽  
Autism Spectrum ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Uncertain Significance ◽  
Spectrum Disorders

Background Autism spectrum disorders (ASD) affect many children with an estimated prevalence of 1%. Array-comparative genomic hybridization (CGH) offers significant sensitivity for the identification of submicroscopic chromosomal abnormalities and it is one of the most used techniques in daily practice. The main objective of this study was to describe the usefulness of array-CGH in the etiologic diagnosis of ASD. Methods Two-hundred fifty-three patients admitted to a neurogenetic outpatient clinic and diagnosed with ASD were selected for array-CGH (4 × 180K microarrays). Public databases were used for classification in accordance with the American College of Medical Genetics Standards and Guidelines. Results About 3.56% (9/253) of copy number variations (CNVs) were classified as pathogenic. When likely pathogenic CNVs were considered, the rate increased to 11.46% (29/253). Some CNVs apparently not correlated to the ASD were also found. Considering a phenotype–genotype correlation, the patients were divided in two groups. One group according to previous literature includes all the CNVs related to ASDs (23 CNVs present in 22 children) and another with those apparently not related to ASD (10 CNVs present in 7 children). In 18 patients, a next-generation sequencing (NGS) panel were performed. From these, one pathogenic and 16 uncertain significance variants were identified. Conclusion The results of our study are in accordance with the literature, highlighting the relevance of array-CGH in the genetic of diagnosis of ASD population, namely when associated with other features. Our study also reinforces the need for complementarity between array-CGH and NGS panels or whole exome sequencing in the etiological diagnosis of ASD.

Disfluency Characteristics Observed in Young Children With Autism Spectrum Disorders: A Preliminary Report

2010 ◽  
Vol 20 (2) ◽  
pp. 42-50 ◽  
Author(s):  
Laura W. Plexico ◽  
Julie E. Cleary ◽  
Ashlynn McAlpine ◽  
Allison M. Plumb
Keyword(s):  
Autism Spectrum Disorders ◽  
Young Children ◽  
Children With Autism ◽  
Descriptive Study ◽  
Autism Spectrum ◽  
Typically Developing ◽  
Children With Asd ◽  
Young Children With Autism ◽  
Spectrum Disorders ◽  
Developmental Stuttering

This descriptive study evaluates the speech disfluencies of 8 verbal children between 3 and 5 years of age with autism spectrum disorders (ASD). Speech samples were collected for each child during standardized interactions. Percentage and types of disfluencies observed during speech samples are discussed. Although they did not have a clinical diagnosis of stuttering, all of the young children with ASD in this study produced disfluencies. In addition to stuttering-like disfluencies and other typical disfluencies, the children with ASD also produced atypical disfluencies, which usually are not observed in children with typically developing speech or developmental stuttering. (Yairi & Ambrose, 2005).

Aging and Autism

2012 ◽  
Vol 17 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Pamela A. Smith
Keyword(s):  
Health Care ◽  
Autism Spectrum Disorders ◽  
Patient Group ◽  
Older Patients ◽  
Geriatric Patients ◽  
Recent Literature ◽  
Communication Disorders ◽  
Autism Spectrum ◽  
Need For Support ◽  
Spectrum Disorders

In this article, I will review the available recent literature about the aging population with autism, a patient group that researchers know little about and a group that is experiencing a growing need for support from communication disorders professionals. Speech-language pathologists working with geriatric patients should become familiar with this issue, as the numbers of older patients with autism spectrum disorders is likely to increase. Our profession and our health care system must prepare to meet the challenge these patients and residents will present as they age.

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