Dataset Information

Modeling Inflammation in Autism Spectrum Disorders Using Stem Cells.

ABSTRACT: Recent reports show an increase in the incidence of Autism Spectrum Disorders (ASD) to 1 in every 59 children up to 8 years old in 11 states in North America. Induced pluripotent stem cell (iPSC) technology offers a groundbreaking platform for the study of polygenic neurodevelopmental disorders in live cells. Robust inflammation states and immune system dysfunctions are associated with ASD and several cell types participate on triggering and sustaining these processes. In this review, we will examine the contribution of neuroinflammation to the development of autistic features and discuss potential therapeutic approaches. We will review the available tools, emphasizing stem cell modeling as a technology to investigate the various molecular pathways and different cell types involved in the process of neuroinflammation in ASD.

SUBMITTER: Freitas BC

PROVIDER: S-EPMC6299043 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Modeling Inflammation in Autism Spectrum Disorders Using Stem Cells.

Freitas Beatriz C BC Mei Arianna A Mendes Ana Paula D APD Beltrão-Braga Patricia C B PCB Marchetto Maria Carolina MC

Frontiers in pediatrics 20181212

Recent reports show an increase in the incidence of Autism Spectrum Disorders (ASD) to 1 in every 59 children up to 8 years old in 11 states in North America. Induced pluripotent stem cell (iPSC) technology offers a groundbreaking platform for the study of polygenic neurodevelopmental disorders in live cells. Robust inflammation states and immune system dysfunctions are associated with ASD and several cell types participate on triggering and sustaining these processes. In this review, we will ex ...[more]

PMID: 30619789

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Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males. Gene expression profiling of 116 LCL from autistic (87) and nonautistic (29) individuals were obtained using a custom-printed DNA microarray containing 39,936 elements (TIGR 40K Human array, GPL3427) and a reference design in which each sample was compared to the Stratagene Universal Human RNA standard. The 87 autistic samples were divided into phenotypic subgroups (language, mild, savant) on the basis of cluster analyses of scores from an autism diagnostic questionnaire, the Autism Diagnostic Interview-Revised instrument. Differentially expressed genes were determined for all autistic vs. control groups, as well as for each of 3 phenotypic ASD groups and controls.

Dataset Information

Modeling Inflammation in Autism Spectrum Disorders Using Stem Cells.

Publications

Modeling Inflammation in Autism Spectrum Disorders Using Stem Cells.

Similar Datasets

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