scholarly journals A systematic review of common genetic variation and biological pathways in autism spectrum disorder

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Diego Alejandro Rodriguez-Gomez ◽  
Danna Paola Garcia-Guaqueta ◽  
Jesús David Charry-Sánchez ◽  
Elias Sarquis-Buitrago ◽  
Mariana Blanco ◽  
...  
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Genetic Variation ◽  
Postsynaptic Membrane ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Cell Junction ◽  
Biological Processes ◽  
Common Genetic Variation ◽  
Kegg Pathway Database

Abstract Background Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent deficits in social communication and interaction. Common genetic variation appears to play a key role in the development of this condition. In this systematic review, we describe the relationship between genetic variations and autism. We created a gene dataset of the genes involved in the pathogenesis of autism and performed an over-representation analysis to evaluate the biological functions and molecular pathways that may explain the associations between these variants and the development of ASD. Results 177 studies and a gene set composed of 139 were included in this qualitative systematic review. Enriched pathways in the over-representation analysis using the KEGG pathway database were mostly associated with neurotransmitter receptors and their subunits. Major over-represented biological processes were social behavior, vocalization behavior, learning and memory. The enriched cellular component of the proteins encoded by the genes identified in this systematic review were the postsynaptic membrane and the cell junction. Conclusions Among the biological processes that were examined, genes involved in synaptic integrity, neurotransmitter metabolism, and cell adhesion molecules were significantly involved in the development of autism.

scholarly journals How rare and common risk variation jointly affect liability for autism spectrum disorder

2020 ◽  
Author(s):  
Lambertus Klei ◽  
Lora Lee McClain ◽  
Behrang Mahjani ◽  
Klea Panayidou ◽  
Silvia De Rubeis ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Genetic Variation ◽  
Rare Variants ◽  
Population Level ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Common Genetic Variation ◽  
Control Subjects ◽  
Mutation Carriers ◽  
Risk Variants

AbstractBackgroundGenetic studies have implicated rare and common variation in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study.MethodsTo explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variation (Simons Simplex Collection and Population-Based Autism Genetics & Environment Study). We analyzed data from 3,011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3,011 subjects matched for ancestry to ASD subjects; and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk for ASD (henceforth burden), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a rare damaging variant implicated in risk for ASD (mutation carriers); ASD subjects who do not (non-carriers); and unaffected subjects, who are assumed to be non-carriers.ResultsBurden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For mutation carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability.LimitationsOnly 258 ASD subjects were known mutation carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific mutations or genes. Also, a small fraction of subjects that are categorized as non-carriers could be mutation carriers.ConclusionsLiability arising from common and rare risk variation likely combine additively to determine risk for any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare mutation affecting risk.

scholarly journals How rare and common risk variation jointly affect liability for autism spectrum disorder

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lambertus Klei ◽  
Lora Lee McClain ◽  
Behrang Mahjani ◽  
Klea Panayidou ◽  
Silvia De Rubeis ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Genetic Variation ◽  
Rare Variants ◽  
Population Level ◽  
Population Based ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Common Genetic Variation ◽  
Control Subjects ◽  
Risk Variants

Abstract Background Genetic studies have implicated rare and common variations in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study. Methods To explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variations (Simons Simplex Collection and Population-Based Autism Genetics and Environment Study). We analyzed data from 3011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3011 subjects matched for ancestry to ASD subjects and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk of ASD (henceforth “burden”), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a potentially damaging variant implicated in risk of ASD (“PDV carriers”); ASD subjects who do not (“non-carriers”); and unaffected subjects who are assumed to be non-carriers. Results Burden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For PDV carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability. Limitations Only 305 ASD subjects were known PDV carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific PDVs or genes. Also, a small fraction of subjects that are categorized as non-carriers could be PDV carriers. Conclusions Liability arising from common and rare risk variations likely combines additively to determine risk of any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare PDV affecting risk.

Parent Education in Studies With Nonverbal and Minimally Verbal Participants With Autism Spectrum Disorder: A Systematic Review

2020 ◽  
Vol 29 (2) ◽  
pp. 890-902
Author(s):  
Lynn Kern Koegel ◽  
Katherine M. Bryan ◽  
Pumpki Lei Su ◽  
Mohini Vaidya ◽  
Stephen Camarata
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Parent Education ◽  
Autism Spectrum ◽  
Verbal Communication ◽  
Fidelity Of Implementation ◽  
Spectrum Disorder ◽  
Education Programs ◽  
Minimally Verbal ◽  
Parent Education Programs

Purpose The purpose of this systematic review was to identify parent education procedures implemented in intervention studies focused on expressive verbal communication for nonverbal (NV) or minimally verbal (MV) children with autism spectrum disorder (ASD). Parent education has been shown to be an essential component in the habilitation of individuals with ASD. Parents of individuals with ASD who are NV or MV may particularly benefit from parent education in order to provide opportunities for communication and to support their children across the life span. Method ProQuest databases were searched between the years of 1960 and 2018 to identify articles that targeted verbal communication in MV and NV individuals with ASD. A total of 1,231 were evaluated to assess whether parent education was implemented. We found 36 studies that included a parent education component. These were reviewed with regard to (a) the number of participants and participants' ages, (b) the parent education program provided, (c) the format of the parent education, (d) the duration of the parent education, (e) the measurement of parent education, and (f) the parent fidelity of implementation scores. Results The results of this analysis showed that very few studies have included a parent education component, descriptions of the parent education programs are unclear in most studies, and few studies have scored the parents' implementation of the intervention. Conclusions Currently, there is great variability in parent education programs in regard to participant age, hours provided, fidelity of implementation, format of parent education, and type of treatment used. Suggestions are made to provide both a more comprehensive description and consistent measurement of parent education programs.

Herbal Medicine as an Alternative Treatment in Autism Spectrum Disorder: A Systematic Review

2018 ◽  
Vol 19 (5) ◽  
pp. 454-459 ◽  
Author(s):  
Francielly Mourao Gasparotto ◽  
Francislaine Aparecida dos Reis Lívero ◽  
Sara Emilia Lima Tolouei Menegati ◽  
Arquimedes Gasparotto Junior
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Herbal Medicine ◽  
Alternative Treatment ◽  
Autism Spectrum ◽  
Spectrum Disorder

Diagnostic test accuracy for use of machine learning in diagnosis of autism spectrum disorder: A Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Sun Jae Moon ◽  
Jin Seub Hwang ◽  
Rajesh Kana ◽  
John Torous ◽  
Jung Won Kim
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Meta Analysis ◽  
Learning Algorithms ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Machine Learning Algorithms ◽  
Spectrum Disorder ◽  
Test Accuracy

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.

scholarly journals Scalp acupuncture for Autism spectrum disorder: a systematic review

2020 ◽  
Vol 440 ◽  
pp. 042094
Author(s):  
Huaimin Yi ◽  
Yajun Han ◽  
Mengxin Li ◽  
Jiong Wang ◽  
Liping Yang
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Scalp Acupuncture ◽  
Spectrum Disorder

Autism spectrum disorder and air pollution: a systematic review and meta-analysis

2021 ◽  
pp. 116856
Author(s):  
Frédéric Dutheil ◽  
Aurélie Comptour ◽  
Roxane Morlon ◽  
Martial Mermillod ◽  
Bruno Pereira ◽  
...  
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Air Pollution ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Spectrum Disorder

scholarly journals Review of Cognitive Characteristics of Autism Spectrum Disorder Using Performance on Six Subtests on Four Versions of the Wechsler Intelligence Scale for Children

2021 ◽  
Author(s):  
Mizuho Takayanagi ◽  
Yoko Kawasaki ◽  
Mieko Shinomiya ◽  
Hoshino Hiroshi ◽  
Satoshi Okada ◽  
...  
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Block Design ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Intelligence Scale ◽  
Cognitive Characteristics ◽  
Children With Asd ◽  
The Right ◽  
The Impact

AbstractThis study was a systematic review of research using the Wechsler Intelligence Scale for Children (WISC) with Autism Spectrum Disorder (ASD) to examine cognitive characteristics of children with ASD beyond the impact of revisions based on WISC and diagnostic criteria changes. The classic “islets of ability” was found in individuals with full-scale IQs < 100. The “right-descending profiles” were observed among high IQ score individuals. High levels on the Block Design and low Coding levels were consistently found regardless of the variation in intellectual functioning or diagnosis. This review identified patterns of cognitive characteristics in ASD individuals using empirical data that researchers may have previously been aware of, based on their experiences, owing to the increased prevalence of ASD.

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