ReviewTranslational psychiatry2016
A common molecular signature in ASD gene expression: following Root 66 to autism.
Review in Translational psychiatry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled 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
- Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2017Pooled it
- Transcriptomic signature comparisons identify conserved key events and respiratory disease signatures most similar to wildfire-relevant exposure.Chemico-biological interactions · 2026Article
- Rare Copy Number Variants Intersecting Parkinson's-associated Genes in a Cohort of children With Autism Spectrum Disorders.Neuroscience insights · 2025Article
- Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Multimodal Data Integration.medRxiv : the preprint server for health sciences · 2024Article
- A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years.Molecular psychiatry · 2023Article
- Scribble Controls Social Motivation Behavior through the Regulation of the ERK/Mnk1 Pathway.Cells · 2022Article
- Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value.BMC bioinformatics · 2020Article
- Comprehensive Profiling of Gene Expression in the Cerebral Cortex and Striatum of BTBRTF/ArtRbrc Mice Compared to C57BL/6J Mice.Frontiers in cellular neuroscience · 2020Article
- Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.Translational psychiatry · 2018Article
- Coalitional game theory as a promising approach to identify candidate autism genes.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes.BMC genomics · 2017Article
- Expression of Reactive Oxygen Species-Related Transcripts in Egyptian Children With Autism.Biomarker insights · 2017Article
- Identification of chemicals that mimic transcriptional changes associated with autism, brain aging and neurodegeneration.Nature communications · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Several gene expression experiments on autism spectrum disorders have been conducted using both blood and brain tissue. Individually, these studies have advanced our understanding of the molecular systems involved in the molecular pathology of autism and have formed the bases of ongoing work to build autism biomarkers. In this study, we conducted an integrated systems biology analysis of 9 independent gene expression experiments covering 657 autism, 9 mental retardation and developmental delay and 566 control samples to determine if a common signature exists and to test whether regulatory patterns in the brain relevant to autism can also be detected in blood. We constructed a matrix of differentially expressed genes from these experiments and used a Jaccard coefficient to create a gene-based phylogeny, validated by bootstrap. As expected, experiments and tissue types clustered together with high statistical confidence. However, we discovered a statistically significant subgrouping of 3 blood and 2 brain data sets from 3 different experiments rooted by a highly correlated regulatory pattern of 66 genes. This Root 66 appeared to be non-random and of potential etiologic relevance to autism, given their enriched roles in neurological processes key for normal brain growth and function, learning and memory, neurodegeneration, social behavior and cognition. Our results suggest that there is a detectable autism signature in the blood that may be a molecular echo of autism-related dysregulation in the brain.
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Registered trials
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