SynthesisAmerican journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics2017
Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis.
Synthesis in American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 3 of them syntheses that pooled it.
What it found
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The trial behind it
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Who cites it
40 citing papers in PubMed, 3 syntheses or guidelines pooled it, 79 citations in OpenAlex.
- Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses.Schizophrenia research · 2020Pooled it
- A meta-analysis of two high-risk prospective cohort studies reveals autism-specific transcriptional changes to chromatin, autoimmune, and environmental response genes in umbilical cord blood.Molecular autism · 2019Pooled it
- PTSD Blood Transcriptome Mega-Analysis: Shared Inflammatory Pathways across Biological Sex and Modes of Trauma.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2018Pooled it
- Persistent homology of blood gene co-expression networks reveals reduced cycle structure in autism spectrum disorder: a multi-cohort analysis.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Article
- Convergence and divergence of genes informed by common and rare variants of autism spectrum disorders in tissue-specific pathways and gene networks.Translational psychiatry · 2026Article
- The role of machine learning in autism spectrum disorder assessment and management.Pediatric research · 2025Review
- A joint complex network and machine learning approach for the identification of discriminative gene communities in autistic brain.PloS one · 2025Article
- Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Multimodal Data Integration.medRxiv : the preprint server for health sciences · 2024Article
- Transcriptome Study in Sicilian Patients with Autism Spectrum Disorder.Biomedicines · 2024Article
- The autism susceptibility kinase, TAOK2, phosphorylates eEF2 and modulates translation.Science advances · 2024Article
- A primer on the use of machine learning to distil knowledge from data in biological psychiatry.Molecular psychiatry · 2024Review
- Autistic spectrum disorder (ASD) - Gene, molecular and pathway signatures linking systemic inflammation, mitochondrial dysfunction, transsynaptic signalling, and neurodevelopment.Brain, behavior, & immunity - health · 2023Article
- Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs.Translational psychiatry · 2023Article
- BrainGENIE: The Brain Gene Expression and Network Imputation Engine.Translational psychiatry · 2023Article
- A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years.Molecular psychiatry · 2023Article
- Large 22q13.3 deletions perturb peripheral transcriptomic and metabolomic profiles in Phelan-McDermid syndrome.HGG advances · 2023Article
- Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression.Nature neuroscience · 2022Article
- Rare variants and the oligogenic architecture of autism.Trends in genetics : TIG · 2022Review
- Abnormal mTOR Activity in Pediatric Autoimmune Neuropsychiatric and MIA-Associated Autism Spectrum Disorders.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.