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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Several studies have supported a nexus in mid-fetal, glutamatergic neurons during cortical development, with modestly divergent findings regarding deep versus superficial cortical layers.
“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]
The Discussion (page unavailable) reports convergence with parallel work on fetal cortical development and describes stronger enrichment in superficial-layer glutamatergic neurons, alongside a weaker lower-layer signal. But the paper locates its clearest cell-type and layer enrichment in adult cortex; it does not establish the claimed nexus specifically in mid-fetal glutamatergic neurons. (LLM, conf=0.83)
Experimental — accuracy not yet measuredASD genes are expressed at high levels in the human cortex and early in development.
“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
The Results section on RDNVs in early fetal development reports high cortical expression during early neurodevelopment for a subset of ASD-associated genes (113 of 598 RDNV-affected genes). The paper also distinguishes these early-expression modules from ASD-associated synaptic modules with later developmental patterns, so it does not establish the claim for ASD genes generally. Page numbers are unavailable in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredPrior analyses have implicated excitatory glutamatergic neurons in the cortex and medium spiny neurons in the striatum in ASD.
“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
The Discussion (page unavailable) links ASD risk-enriched gene modules to glutamatergic neurons in upper cortical layers, supporting the cortical part of the claim. The paper passages do not implicate medium spiny neurons in the striatum; searches for those terms found no supporting passage. (LLM, conf=0.88)
Experimental — accuracy not yet measuredASD risk gene coexpression networks are enriched in upper-layer neurons during development and these neurons are preferentially affected in ASD patients.
“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]
The Results (page unavailable) link ASD-risk coexpression modules to upper-layer neuron markers and report that genes recurrently mutated in ASD probands tend to be expressed in superficial layers. The Discussion (page unavailable) treats disruption of upper-layer neurons as a prediction, not a direct observation that those neurons are preferentially affected in patients; it also says the strongest layer enrichment was found in adult tissue. (LLM, conf=0.84)
Experimental — accuracy not yet measuredCoexpression network analyses of autism spectrum disorder genes indicate that developmental defects associated with autism spectrum disorder may arise during fetal stages.
“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]
Ten candidate genes have expression data in developing fetal human cortex and show a trend of increased expression at postconceptual week 15-16 and week 21 in the cortical plate and subplate laminae.
“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]
FXS and ASD are intertwined at the molecular level, suggesting that several common pathways and cellular mechanisms are shared between the two disorders.
“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
Computational analyses indicate that these processes are linked through FMRP-mediated translational control and shared transcription factors.
“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
A later transition, near 20 weeks post-conception in humans (perinatal in mice), is marked by increased expression of a module supporting activity-dependent synaptic development.
“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
Researchers have mapped developmental phase transitions by following ASD- and ID-related gene expression across human cortical development.
“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
At about 11 weeks post-conception, an early transition is marked by reduced expression of a module that inhibits neuronal differentiation and increased expression of one that promotes it.
“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
ASD candidate gene expression converges on transcriptional regulation in pyramidal, glutamatergic cortical neurons during mid-fetal human development.
“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]
Strong evidence implicates a convergence of pathways at the transcriptome level in postmortem brains from ASD patients.
“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]
Because co-expressed genes imply co-regulation, the results provide further evidence for the suggested convergent transcriptional regulation in ASD.
“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]
Large sets of ASD candidate genes contribute to molecular pathways that converge on a few functional networks, mainly involved with neuronal transcription regulation and synaptic plasticity.
“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
MEF2 works with FMRP to control glutamatergic synaptic activity.
“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]
Some gene network analyses suggest that molecular processes distinguish autism spectrum disorder from intellectual disability.
“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
Network analysis provides an organizing framework that can divide large gene sets into biologically coherent modules for prioritization or add power to genome-wide association studies.
“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
Autism spectrum disorder risk variants are enriched in cortical glutamatergic neurons expressed during neurogenesis and neuronal migration during fetal cortical development in human and mouse.
“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
Developmentally co-regulated modules of gene expression in fetal brain are enriched in ASD risk genes, with layer 2-4 and glutamatergic projection neurons showing strongest enrichment.
“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
lncRNAs will be important targets for investigation in ASD.
“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]
FMRP mRNA targets are enriched in ASD risk genes.
“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]
The observed transcriptome changes are consistent with an ongoing process triggered largely by genetic and prenatal factors but evolving during the first decade of brain development.
“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]
nSR100 is strongly co-expressed in the developing human brain in gene network module M2, which is enriched for rare de novo ASD-associated mutations.
“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
Network analysis 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 enable integration with other information.
“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]
The genome-wide approach assessed both ASD and intellectual disability genes and suggested that disruption of upper neocortical layers (layers 2-4) is related to ASD-like phenotypes and not intellectual disability.
“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]
One network study defined robust co-expression modules reproducible in independent data and identified five developmentally regulated co-expression modules enriched for PPIs and ASD risk genes.
“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]
Integration of ChIP-seq, CHD8 knockdown, and co-expression data suggested that CHD8 directly regulates co-expression modules enriched for rare de novo mutations and fetal cortical proliferating-layer genes.
“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]
Both of these studies found convergence for rare de novo ASD-associated mutations during early fetal and mid-fetal development, with greatest enrichment for risk in genes found in cortical glutamatergic neurons.
“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]
FMRP targets are connected to multiple forms of ASD genetic risk, including copy number variations, by genome-wide and seeded co-expression network analyses.
“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]
This overlap suggests involvement of autism risk factors in early development of excitatory cortical neurons.
“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]
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.
“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]
Using WW data, INRICH enrichment analysis observed enrichment at empirical P ≤ .05 for the synaptic co-expression network M13, Mendelian disease genes, and human and primate-accelerated regions; none exceeded experiment-wise corrected P ≤ .05.
“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.”
Genes assigned to NeuN+ specific peaks are enriched in synaptic co-expression modules during neurodevelopment.
“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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Identification of common genetic risk variants for autism spectrum disorder
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“Comparing our gene modules to previously published candidate ASD gene networks obtained using WGCNA (Parikshak et al., 2013) shows that our M4 strongly overlaps with previously identified M16 (p = 5.”
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Self-citationFOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders
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Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice
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Self-citationSex/Gender Differences and Autism: Setting the Scene for Future Research
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Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
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Self-citationFrom the genetic architecture to synaptic plasticity in autism spectrum disorder
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Single-cell genomics identifies cell type–specific molecular changes in autism
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Sex-specific transcriptional signatures in human depression
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Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
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“A GO analysis of genes with ASD-associated misregulation of microexons reveals significant enrichment of terms related to axonogenesis and synapse biology (Figure 7E), processes that have been previously implicated in autism (Gilman et al., 2011; Parikshak et al., 2013; Voineagu et al., 2011).”
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“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 factors 3,9,10,23 , but that evolves during the first decade of brain development.”
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Self-citationMapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex
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Immune mediators in the brain and peripheral tissues in autism spectrum disorder
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Self-citationInherited and de novo genetic risk for autism impacts shared networks
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Self-citationDefining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
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“One approach to this problem integrates prior information, such as gene or protein-protein interaction (PPI) networks to boost the signal of missense variation (Parikshak et al., 2013).”
BackgroundInfluentialSelf-citationSystems biology and gene networks in neurodevelopmental and neurodegenerative disorders
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Self-citationThe Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis
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CHD8 haploinsufficiency results in autistic-like phenotypes in mice
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The ASD Living Biology: from cell proliferation to clinical phenotype
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Self-citationGene expression in human brain implicates sexually dimorphic pathways in autism spectrum disorders
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Self-citationHistone Acetylome-wide Association Study of Autism Spectrum Disorder
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- 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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