Dataset Information

Developmental regression and mitochondrial function in children with autism.

ABSTRACT: BACKGROUND:Developmental regression (DR) occurs in about one-third of children with Autism Spectrum Disorder (ASD) yet it is poorly understood. Current evidence suggests that mitochondrial function in not normal in many children with ASD. However, the relationship between mitochondrial function and DR has not been well-studied in ASD. METHODS:This cross-sectional study of 32 children, 2 to 8 years old with ASD, with (n = 11) and without (n = 12) DR, and non-ASD controls (n = 9) compared mitochondrial respiration and mtDNA damage and copy number between groups and their relation to standardized measures of ASD severity. RESULTS:Individuals with ASD demonstrated lower ND1, ND4, and CYTB copy number (Ps < 0.01) as compared to controls. Children with ASD and DR had higher maximal oxygen consumption rate (Ps < 0.02), maximal respiratory capacity (P < 0.05), and reserve capacity (P = 0.01) than those with ASD without DR. Coupling Efficiency and Maximal Respiratory Capacity were associated with disruptive behaviors but these relationships were different for those with and without DR. Higher ND1 copy number was associated with better behavior. CONCLUSIONS:This study suggests that individuals with ASD and DR may represent a unique metabolic endophenotype with distinct abnormalities in respiratory function that may put their mitochondria in a state of vulnerability. This may allow physiological stress to trigger mitochondrial decompensation as is seen clinically as DR. Since mitochondrial function was found to be related to ASD symptoms, the mitochondria could be a potential target for novel therapeutics. Additionally, identifying those with vulnerable mitochondrial before DR could result in prevention of ASD.

SUBMITTER: Singh K

PROVIDER: S-EPMC7261756 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Developmental regression and mitochondrial function in children with autism.

Singh Kanwaljit K Singh Indrapal N IN Diggins Eileen E Connors Susan L SL Karim Mohammad A MA Lee David D Zimmerman Andrew W AW Frye Richard E RE

Annals of clinical and translational neurology 20200428 5

<h4>Background</h4>Developmental regression (DR) occurs in about one-third of children with Autism Spectrum Disorder (ASD) yet it is poorly understood. Current evidence suggests that mitochondrial function in not normal in many children with ASD. However, the relationship between mitochondrial function and DR has not been well-studied in ASD.<h4>Methods</h4>This cross-sectional study of 32 children, 2 to 8 years old with ASD, with (n = 11) and without (n = 12) DR, and non-ASD controls (n = 9) co ...[more]

PMID: 32343046

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Project description:BackgroundCare for children with autism spectrum disorder (ASD) can be challenging for families and medical care systems. This is especially true in low- and- middle-income countries such as Bangladesh. To improve family-practitioner communication and developmental monitoring of children with ASD, mCARE (Mobile-Based Care for Children with Autism Spectrum Disorder Using Remote Experience Sampling Method) was developed. Within this study, mCARE was used to track child milestone achievement and family sociodemographic assets to inform mCARE feasibility/scalability and family asset-informed practitioner recommendations.ObjectiveThe objectives of this paper are threefold. First, it documents how mCARE can be used to monitor child milestone achievement. Second, it demonstrates how advanced machine learning models can inform our understanding of milestone achievement in children with ASD. Third, it describes family/child sociodemographic factors that are associated with earlier milestone achievement in children with ASD (across 5 machine learning models).MethodsUsing mCARE-collected data, this study assessed milestone achievement in 300 children with ASD from Bangladesh. In this study, we used 4 supervised machine learning algorithms (decision tree, logistic regression, K-nearest neighbor [KNN], and artificial neural network [ANN]) and 1 unsupervised machine learning algorithm (K-means clustering) to build models of milestone achievement based on family/child sociodemographic details. For analyses, the sample was randomly divided in half to train the machine learning models and then their accuracy was estimated based on the other half of the sample. Each model was specified for the following milestones: Brushes teeth, Asks to use the toilet, Urinates in the toilet or potty, and Buttons large buttons.ResultsThis study aimed to find a suitable machine learning algorithm for milestone prediction/achievement for children with ASD using family/child sociodemographic characteristics. For Brushes teeth, the 3 supervised machine learning models met or exceeded an accuracy of 95% with logistic regression, KNN, and ANN as the most robust sociodemographic predictors. For Asks to use toilet, 84.00% accuracy was achieved with the KNN and ANN models. For these models, the family sociodemographic predictors of "family expenditure" and "parents' age" accounted for most of the model variability. The last 2 parameters, Urinates in toilet or potty and Buttons large buttons, had an accuracy of 91.00% and 76.00%, respectively, in ANN. Overall, the ANN had a higher accuracy (above ~80% on average) among the other algorithms for all the parameters. Across the models and milestones, "family expenditure," "family size/type," "living places," and "parent's age and occupation" were the most influential family/child sociodemographic factors.ConclusionsmCARE was successfully deployed in a low- and middle-income country (ie, Bangladesh), providing parents and care practitioners a mechanism to share detailed information on child milestones achievement. Using advanced modeling techniques this study demonstrates how family/child sociodemographic elements can inform child milestone achievement. Specifically, families with fewer sociodemographic resources reported later milestone attainment. Developmental science theories highlight how family/systems can directly influence child development and this study provides a clear link between family resources and child developmental progress. Clinical implications for this work could include supporting the larger family system to improve child milestone achievement.

Project description:BackgroundThe etiology of autism spectrum disorders (ASD) is very heterogeneous. Mitochondrial dysfunction has been described in ASD; however, primary mitochondrial disease has been genetically proven in a small subset of patients. The main goal of the present study was to investigate correlations between mitochondrial DNA (mtDNA) changes and alterations of genes associated with mtDNA maintenance or ASD.MethodsSixty patients with ASD and sixty healthy individuals were screened for common mtDNA mutations. Next generation sequencing was performed on patients with major mtDNA deletions (mtdel-ASD) using two gene panels to investigate nuclear genes that are associated with ASD or are responsible for mtDNA maintenance. Cohorts of healthy controls, ASD patients without mtDNA alterations, and patients with mitochondrial disorders (non-ASD) harbouring mtDNA deletions served as comparison groups.ResultsMtDNA deletions were confirmed in 16.6% (10/60) of patients with ASD (mtdel-ASD). In 90% of this mtdel-ASD children we found rare SNVs in ASD-associated genes (one of those was pathogenic). In the intergenomic panel of this cohort one likely pathogenic variant was present. In patients with mitochondrial disease in genes responsible for mtDNA maintenance pathogenic mutations and variants of uncertain significance (VUS) were detected more frequently than those found in patients from the mtdel-ASD or other comparison groups. In healthy controls and in patients without a mtDNA deletion, only VUS were detected in both panel.ConclusionsMtDNA alterations are more common in patients with ASD than in control individuals. MtDNA deletions are not isolated genetic alterations found in ASD; they coexist either with other ASD-associated genetic risk factors or with alterations in genes responsible for intergenomic communication. These findings indicate that mitochondrial dysfunction is not rare in ASD. The occurring mtDNA deletions in ASD may be mostly a consequence of the alterations of the causative culprit genes for autism or genes responsible for mtDNA maintenance, or because of the harmful effect of environmental factors.

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Developmental regression and mitochondrial function in children with autism.

Publications

Developmental regression and mitochondrial function in children with autism.

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