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Integrative Functional Genomic Analyses Implicate Specific Molecular Pathways and Circuits in Autism
Open accessAbstract
Genetic studies have identified dozens of autism spectrum disorder (ASD) susceptibility genes, raising two critical questions: 1) do these genetic loci converge on specific biological processes, and 2) where does the phenotypic specificity of ASD arise, given its genetic overlap with intellectual disability (ID)? To address this, we mapped ASD and ID risk genes onto co-expression networks representing developmental trajectories and transcriptional profiles representing fetal and adult cortical laminae. ASD genes tightly coalesce in modules that implicate distinct biological functions during human cortical development, including early transcriptional regulation and synaptic development. Bioinformatic analyses suggest translational regulation by FMRP and transcriptional co-regulation by common transcription factors connect these processes. At a circuit level, ASD genes are enriched in superficial cortical layers and glutamatergic projection neurons. Furthermore, we show that the patterns of ASD and ID risk genes are distinct, providing a novel biological framework for investigating the pathophysiology of ASD.
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In the citing paper
“several studies have supported a nexus in mid-fetal, glutamatergic neurons during cortical development, with modestly divergent findings regarding deep 56 versus”
From Autism spectrum disorder (2020) · cites this paper as [54]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Thus, in keeping with prior analyses (Chang et al., 2015; Parikshak et al., 2013; Willsey et al., 2013; Xuet al., 2014), ASD genes are expressed at high levels in the human cortex and early in development.”
From Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2020) · cites this paper as Parikshak et al., 2013
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Prior analyses have implicated excitatory glutamatergic neurons in the cortex and medium spiny neurons in the striatum in ASD (Chang et al., 2015; Parikshak et al., 2013; Willsey et al., 2013; Xu et al., 2014).”
From Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (2020) · cites this paper as Parikshak et al., 2013
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“nSR100 is strongly co-expressed in the developing human brain in a gene network module, M2, which is enriched for rare de novo ASD-associated mutations (Parikshak et al., 2013)”
From A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains (2014) · cites this paper as Parikshak et al., 2013
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This aligns with the observation that ASD risk gene coexpression networks are enriched in upper-layer neurons during development and that these neurons are preferentially affected in ASD patients6,34.”
From Single-cell brain organoid screening identifies developmental defects in autism (2023) · cites this paper as [6]
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In the citing paper
“Moreover, coexpression network analyses of ASD genes indicate that the developmental defects associated with ASD may arise during fetal stages5,6, periods that are difficult to investigate.”
From Single-cell brain organoid screening identifies developmental defects in autism (2023) · cites this paper as [6]
In the citing paper
“Ten of these genes (BRSK2, ITSN1, FEZF2, RALGAPB, NR4A2, EGR3, DPP6, CPZ, SH3RF3, and CLCN4) have expression data in developing fetal human cortex, and similar to Parikshak et al.45 they show a trend of increased expression at postconceptual week (PCW) 15–16 (Fig. 2c) and PCW 21 (Supplementary Fig. 10) in the cortical plate and subplate laminae”
From Exome sequencing of 457 autism families recruited online provides evidence for autism risk genes (2019) · cites this paper as [45]
In the citing paper
“Indeed, FXS and ASD are intertwined at the molecular level (Parikshak et al. 2013), suggesting that several common pathways and cellular mechanisms are shared amongst these 2 disorders.”
From Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories (2018) · cites this paper as Parikshak et al. 2013
In the citing paper
“Bioinformatics analyses suggest that these processes are connected via translational regulation by FMRP and transcriptional co-regulation by common transcription factors, mechanisms touched upon elsewhere in this review.”
From Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops (2016) · cites this paper as Parikshak et al., 2013
In the citing paper
“A later transition (∼20 weeks post-conception in humans, equivalent to perinatal mice) is marked by enhancement of a gene module that supports activity-dependent synaptic development.”
From Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops (2016) · cites this paper as Parikshak et al., 2013
In the citing paper
“The transitions between developmental phases have been charted by tracking expression of ASD- and ID-related genes through human cortical development (Parikshak et al., 2013).”
From Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops (2016) · cites this paper as Parikshak et al., 2013
In the citing paper
“An early transition (∼11 weeks post-conception) is indicated by attenuation of a gene module that opposes neuronal differentiation, giving way to one that favors it.”
From Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops (2016) · cites this paper as Parikshak et al., 2013
In the citing paper
“Recent studies integrating ASD candidate genes with spatiotemporal coexpression networks demonstrate that gene expression converge on the transcriptional regulation in pyramidal, glutamatergic cortical neurons during mid-fetal human development8, 9.”
From Altered proliferation and networks in neural cells derived from idiopathic autistic individuals (2017) · cites this paper as [8]
In the citing paper
“Strong evidence implicates a convergence of pathways at the transcriptome level in postmortem brains from ASD patients8, 32.”
From Altered proliferation and networks in neural cells derived from idiopathic autistic individuals (2017) · cites this paper as [8]
In the citing paper
“Because co-expressed genes imply co-regulation, our results provide further evidence for the suggested convergent transcriptional regulation in ASD8.”
From Altered proliferation and networks in neural cells derived from idiopathic autistic individuals (2017) · cites this paper as [8]
In the citing paper
“recent molecular biology findings suggest that large sets of ASD candidate genes contribute to molecular pathways that converge on a few functional networks (Hu, 2012; Voineagu et al., 2011), mainly involved with neuronal transcription regulation and synaptic plasticity (Parikshak et al., 2013).”
From From early markers to neuro-developmental mechanisms of autism (2014) · cites this paper as Parikshak et al., 2013
In the citing paper
“MEF2 interacts with FMRP to regulate glutamatergic synaptic function206”
From Immune mediators in the brain and peripheral tissues in autism spectrum disorder (2015) · cites this paper as [206]
In the citing paper
“some gene network analyses suggest the existence of molecular processes that distinguish ASD from ID (Parikshak et al., 2013; Satterstrom et al., 2018b)”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Parikshak et al., 2013
In the citing paper
“network analysis provides an organizing framework that can divide large gene sets into biologically coherent modules for prioritization (Parikshak et al., 2015; Parikshak et al., 2013), or add power to GWAS (Horn et al., 2018)”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Parikshak et al., 2013
In the citing paper
“ASD risk variants are enriched in cortical glutamatergic neurons expressed during neurogenesis and neuronal migration during fetal cortical development in human and mouse (Parikshak et al., 2013; Willsey et al., 2013).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Parikshak et al., 2013
In the citing paper
“Another study has identified several developmentally co-regulated modules of gene expression in fetal brain that are enriched in ASD risk genes, with layer 2–4 and glutamatergic projection neurons showing strongest enrichment (Parikshak et al., 2013).”
From Getting to the cores of autism (2019) · cites this paper as Parikshak et al., 2013
In the citing paper
“Remarkably, CTX.M24 was significantly enriched for lncRNAs, genes expressed highly during fetal cortical development, and genes harbouring protein-disrupting mutations found in ASD, suggesting that lncRNAs will be important targets for investigation in ASD10,25 (FDR < 0.05, Extended Data Fig. 9a, g).”
From Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism (2016) · cites this paper as [10]
In the citing paper
“Moreover, 20 of these lncRNAs have been shown to interact with microRNA (miRNA)–protein complexes, and 9 with the fragile X mental retardation protein (FMRP), whose mRNA targets are enriched in ASD risk genes9,10.”
From Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism (2016) · cites this paper as [10]
In the citing paper
“In this regard, it is notable that the observed transcriptome changes are consistent with an ongoing process that is triggered largely by genetic and prenatal factors3,9,10,23, but that evolves during the first decade of brain development.”
From Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism (2016) · cites this paper as [10]
In the citing paper
“A major advantage of network analysis over DGE analysis is that it can identify multiple levels of molecular organization within the hierarchy of brain region, cell type, organelle and molecular pathways using only transcriptional data, and can thus enable integration with other information, such as known pathway annotations, protein interactions and other molecular profiling data11,12,26,27”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [27]
In the citing paper
“Notably, the genome-wide approach27 assessed both ASD and intellectual disability genes, and further suggested that the disruption of the upper neocortical layers (layers 2–4) is related to ASD-like phenotypes and not intellectual disability.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [27]
In the citing paper
“One network study defined robust co-expression modules that were reproducible in independent data and identified five developmentally regulated co-expression modules that were enriched for PPIs and ASD risk genes27.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [27]
In the citing paper
“Integration of ChIP–seq, CHD8 knockdown and gene co-expression suggested that CHD8 directly regulates co-expression modules that are enriched for rare de novo mutations and genes found in the proliferating layers of the fetal cortex27.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [27]
In the citing paper
“Importantly, both of these studies found convergence for rare de novo ASD-associated mutations during early fetal and mid-fetal development, with the greatest enrichment for risk in genes found in cortical glutamatergic neurons.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [27]
In the citing paper
“Both genome-wide27 and seeded114 co-expression network analysis further connected FMRP targets with multiple forms of ASD genetic risk, including copy number variations (CNVs)114.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [27]
In the citing paper
“This suggests involvement of autism risk factors in early development of excitatory cortical neurons, consistent with other recent studies39,40.”
From Transcriptional landscape of the prenatal human brain (2014) · cites this paper as [39]
In the citing paper
“Recent evidence11, 12, 13, 14, 15, 16, 17, 18, 19, 20 has also catalyzed the concept that genetic and non-genetic factors and their interaction, may act at very early periods of fetal brain development and potentially alter protein or gene expression regulation leading to shared pathways for complex ASD-related phenotypes.”
From Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder (2018) · cites this paper as [15]
In the citing paper
“Using the WW data, we observe enrichment at an empirical P ≤ .05 for the synaptic co-expression network M13 [48], Mendelian disease genes [11], and both human (HARs) and primate-accelerated regions (PARs) [49]. None of these enrichments exceeded the experiment-wise corrected P ≤ .05.”
In the citing paper
“Moreover, genes assigned to NeuN+ specific peaks were enriched in the synaptic co-expression modules during neurodevelopment34 (Fig. 2d).”
From Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders (2021) · cites this paper as [34]
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Metadata
- Authors
- Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Geschwind, Daniel H.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 155
- Issue
- 5
- Pages
- 1008-1021
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3934107
- OpenAlex
- W2071598557
- Semantic Scholar
- 88ac6e0ed254a3fc3759edd1837f4f50cea9a119
- Cited by
- 1,039
- References
- 85
- Citations by year
- 2026: 55 · 2025: 64 · 2024: 59 · 2023: 72 · 2022: 73 · 2021: 90 · 2020: 122 · 2019: 104 · 2018: 90 · 2017: 85 · 2016: 82 · 2015: 81 · 2014: 59 · 2013: 2
- FWCI
- 40.22
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (5r01mh094714-04)
- National Institute of Mental Health (5R01MH094714, R01-MH094714, F30MH099886, R01MH100027, R01MH060233, T32MH073526, R37MH060233, RC2MH089921)
- National Institute of Neurological Disorders and Stroke (P30NS062691)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- autism spectrum disorder, intellectual disability, ASD risk genes, co-expression network, cortical development, cortical layers, transcriptional regulation, synaptic development, FMRP, translational regulation, transcription factors, glutamatergic projection neurons, superficial cortical layers
- MeSH terms
- Brain, Cerebral Cortex, Child Development Disorders, Pervasive, Gene Expression Regulation, Humans, Neurons, Transcription, Genetic, Gene Regulatory Networks, Genome-Wide Association Study
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