AI Article Synopsis
- Children with Autism Spectrum Disorder (ASD) show a wide range of social, communicative, and cognitive challenges, making it difficult to categorize their unique traits and genetic variations.
- A study combined genetic data (specifically single nucleotide polymorphisms or SNPs) with phenotype data to create a network that identifies clusters of related ASD traits, uncovering specific genes linked to these traits.
- The findings provide insights into the genetic links to various ASD characteristics, potentially enabling clinicians to develop more personalized interventions for improving patient outcomes.
Article Abstract
Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well as communicative and cognitive difficulties. It is a challenge to categorize the phenotypes of a particular ASD patient with their unique genetic variants. There is a need for a better understanding of the connections between genotype information and the phenotypes to sort out the heterogeneity of ASD. In this study, single nucleotide polymorphism (SNP) and phenotype data obtained from a simplex ASD sample are combined using a PheWAS-inspired approach to construct a phenotype-phenotype network. The network is clustered, yielding groups of etiologically related phenotypes. These clusters are analyzed to identify relevant genes associated with each set of phenotypes. The results identified multiple discriminant SNPs associated with varied phenotype clusters such as ASD aberrant behavior (self-injury, compulsiveness and hyperactivity), as well as IQ and language skills. Overall, these SNPs were linked to 22 significant genes. An extensive literature search revealed that eight of these are known to have strong evidence of association with ASD. The others have been linked to related disorders such as mental conditions, cognition, and social functioning.Clinical relevance- This study further informs on connections between certain groups of ASD phenotypes and their unique genetic variants. Such insight regarding the heterogeneity of ASD would support clinicians to advance more tailored interventions and improve outcomes for ASD patients.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/EMBC46164.2021.9629533 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A Qualitative Analysis of Unintentional Injuries in Autism Spectrum Disorder.
J Autism Dev Disord
January 2025
Department of Psychology, University of Alabama at Birmingham, AL, Birmingham, USA.
Purpose: Prior research demonstrates that children with autism are more likely to experience unintentional injuries than the general population. Limited research exists on the symptoms or traits directly related to autism and this elevated injury rate, especially from the perspective of families with children with autism. This study used qualitative methodology to elucidate risk factors that may contribute to unintentional injuries in children with autism from the perspective of mothers raising children with autism.
View Article and Find Full Text PDFConcordance Between Asthma Symptom Reports and Objective Lung Function, and Associations With Sleep Outcomes in Urban Children.
Pediatr Pulmonol
January 2025
Department of Pediatrics, Hasbro Children's Hospital, Providence, Rhode Island, USA.
Objectives: To examine the extent to which asthma symptom concordance (ASC) or discordance (ASD) is associated with sleep outcomes in children with persistent asthma. Also, to investigate whether the association between ASC and sleep outcomes varies as a function of children's level of asthma control and severity.
Methods: A retrospective data analysis of Project NAPS (Nocturnal Asthma and Performance in School), an observational study which examined asthma and sleep outcomes in children with persistent asthma.
Unlabelled: Autism Spectrum Disorder (ASD) is characterized by restricted and repetitive behaviors and social differences, both of which may manifest, in part, from underlying differences in corticostriatal circuits and reinforcement learning. Here, we investigated reinforcement learning in mice with mutations in either or , both high-confidence ASD risk genes associated with major syndromic forms of ASD. Using an odor-based two-alternative forced choice (2AFC) task, we tested adolescent mice of both sexes and found male and heterozygote (Het) mice showed enhanced learning performance compared to their wild type (WT) siblings.
View Article and Find Full Text PDFNeurodivergence and Threat: A Case Study on the Risk of Violent Fixations in Autism Spectrum Disorder.
Cureus
December 2024
Child and Adolescent Inpatient Unit, Tower Behavioral Health, Reading, USA.
Mass shootings have increasingly captured public attention in recent decades, prompting closer examination of the mental health of those responsible. This scrutiny often focuses on individuals with neurodevelopmental disorders, such as autism spectrum disorder (ASD). While epidemiological evidence is mixed on whether these individuals are more likely to commit acts of violence than the general public, certain behavioral characteristics may make them more vulnerable to extremist ideations.
View Article and Find Full Text PDFHarnessing Spectral Libraries From AVIRIS-NG Data for Precise PFT Classification: A Deep Learning Approach.
Plant Cell Environ
January 2025
Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India.
The generation of spectral libraries using hyperspectral data allows for the capture of detailed spectral signatures, uncovering subtle variations in plant physiology, biochemistry, and growth stages, marking a significant advancement over traditional land cover classification methods. These spectral libraries enable improved forest classification accuracy and more precise differentiation of plant species and plant functional types (PFTs), thereby establishing hyperspectral sensing as a critical tool for PFT classification. This study aims to advance the classification and monitoring of PFTs in Shoolpaneshwar wildlife sanctuary, Gujarat, India using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and machine learning techniques.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!