Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism
Open accessAbstract
Autism spectrum disorder (ASD) involves substantial genetic contributions. These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood. Here, through post-mortem genome-wide transcriptome analysis of the largest cohort of samples analysed so far, to our knowledge, we interrogate the noncoding transcriptome, alternative splicing, and upstream molecular regulators to broaden our understanding of molecular convergence in ASD. Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes. Our data suggest that SOX5, a transcription factor involved in neuron fate specification, contributes to this reduction in regional differences. We further demonstrate that a genetically defined subtype of ASD, chromosome 15q11.2-13.1 duplication syndrome (dup15q), shares the core transcriptomic signature observed in idiopathic ASD. Co-expression network analysis reveals that individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades, and suggests that genetic risk for ASD may influence changes in regional cortical gene expression. Our findings illustrate how diverse genetic perturbations can lead to phenotypic convergence at multiple biological levels in a complex neuropsychiatric disorder.
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- Findingown data
ASD cortex shows dysregulation of primate-specific long noncoding RNAs.
“Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes.”
Quote in the paperSubstantial claim - Findingown data
ASD cortex shows downregulation of alternative splicing of activity-dependent neuron-specific exons.
“Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes.”
Quote in the paperSubstantial claim - Findingown data
ASD cortex shows attenuation of the normal gene expression differences between the frontal and temporal lobes.
“Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes.”
Quote in the paperSubstantial claim - Findingown data
Gene expression in ASD can separate samples by disease status.
“We performed a classification analysis to confirm that gene expression in ASD could separate samples by disease status (Extended Data Fig. 2a) and confirmed the technical quality of our data with qRT–PCR (Extended Data Fig. 2b, c).”
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There are high correlations between splicing factor expression and differential splicing in ASD cortex.
“Therefore, we next investigated whether the shared splicing signature in ASD could be explained by perturbations in splicing factors known to be important in nervous system function8,14 (Extended Data Fig. 4j), and found high correlations between splicing factor expression and differential splicing in the cortex (Fig. 1f) but not the cerebellum (Fig. 1g).”
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- Findingown data
The downregulated gene set in ASD cortex is enriched in neuron-expressed genes and neuronal pathways, including PVALB and SYT2.
“We next evaluated enrichment of the gene sets for pathways and cell types (Extended Data Fig. 2d, e), and found that the downregulated set was enriched in genes expressed in neurons and involved in neuronal pathways, including PVALB and SYT2, which are highly expressed in interneurons; by contrast, the upregulated gene set was enriched in genes expressed in microglia and astrocytes8.”
Quote in the paperSubstantial claim - Findingown data
The ASD-associated lncRNAs as a group are enriched in brain relative to other tissues.
“As a group, these lncRNAs are enriched in the brain relative to other tissues (Extended Data Fig. 2l, m) and most that have been evaluated across species exhibit primate-specific expression patterns in the brain11, which we confirm for several transcripts (Supplementary Information, Extended Data Fig. 3a–h).”
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ASD-related expression changes are consistently stronger in cortex than in cerebellum.
“The lack of significant DGE in the cerebellum is explained by the fact that changes in expression were consistently stronger in the cortex than in the cerebellum (Extended Data Fig. 2h), which suggests that the cortex is more selectively vulnerable to these transcriptomic alterations.”
Quote in the paperSubstantial claim - Findingown data
There is no significant differential splicing signal in the cerebellum.
“We found a significant differential splicing signal over background in the cortex (1,127 differential splicing events in 833 genes; Methods), but not in the cerebellum (P distributions in Extended Data Fig. 4b, c).”
Quote in the paperSubstantial claim - Findingown data
There is a significant differential splicing signal over background in ASD cortex, with 1,127 differential splicing events in 833 genes.
“We found a significant differential splicing signal over background in the cortex (1,127 differential splicing events in 833 genes; Methods), but not in the cerebellum (P distributions in Extended Data Fig. 4b, c).”
Quote in the paperSubstantial claim - Findingown data
The ACP set is enriched in Wnt signalling, calcium binding, and neuronal genes.
“Pathway and cell-type analysis showed that the ACP set is enriched in Wnt signalling, calcium binding, and neuronal genes (Extended Data Fig. 6i, j, Supplementary Information).”
Quote in the paperNot a substantial claim - Findingown data
The genetically defined ASD subtype dup15q shares the core transcriptomic signature observed in idiopathic ASD.
“We further demonstrate that a genetically defined subtype of ASD, chromosome 15q11.2–13.1 duplication syndrome (dup15q), shares the core transcriptomic signature observed in idiopathic ASD.”
Quote in the paperSubstantial claim - Findingown data
Individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades.
“Co-expression network analysis reveals that individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades, and suggests that genetic risk for ASD may influence changes in regional cortical gene expression.”
Quote in the paperSubstantial claim - Findingown data
Differential splicing events in ASD cortex are significantly enriched in events previously shown to be regulated by neuronal activity.
“Indeed, differential splicing events were significantly enriched in those previously shown to be regulated by neuronal activity21 (Fig. 1h).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [21] Maze, I. et al. Critical role of histone turnover in neuronal transcription and plasticity. Neuron 87, 77–94 (2015) source
Not checked in the free run.
- Findingown data
Microglial and synaptic modules exhibit significant anticorrelation.
“It also confirms that downregulated modules are enriched in synaptic function and neuronal genes, that upregulated modules are enriched in genes associated with inflammatory pathways and glial function4,8, and that microglial and synaptic modules exhibit significant anticorrelation (Fig. 4c).”
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Differential gene expression between control cortex and ASD cortex replicates with strong concordance (R2 = 0.60) with prior microarray profiles.
“We first validated differential gene expression (DGE) between samples of cortex from control individuals and those with ASD (ASD cortex) by comparing gene expression with that of different individuals from those previously profiled by microarray8, and found strong concordance (R2 = 0.60; Fig. 1a, Extended Data Fig. 1i).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Findingown data
Most differential splicing events in ASD cortex involve exclusion of neuron-specific exons.
“Cell-type specific enrichment and pathway analysis of alternative splicing demonstrated that most differential splicing events involve exclusion of neuron-specific exons17 (Fig. 1e, Extended Data Fig. 4i).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [17] Zhang, Y. et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34, 11929–11947 (2014) source
Not checked in the free run.
- Findingown data
The downregulated modules CTX.M10 and CTX.M16 are enriched in genes previously related to neuronal firing rate.
“Furthermore, the downregulated modules CTX.M10 and CTX.M16 are enriched in genes previously related to neuronal firing rate, consistent with the overlap of dysregulated splicing with events regulated by neuronal activity (Extended Data Fig. 9b and Fig. 1h).”
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There is no significant differential gene expression in the cerebellum at FDR < 0.05.
“Although there was no significant DGE in the cerebellum (FDR < 0.05, P distributions in Fig. 1b), similar to observations in a smaller cohort8, there was a replication signal in the cerebellum and overall concordance between ASD-related fold changes in the cortex and cerebellum (Extended Data Fig. 2f–h).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Findingcitation
Most evaluated ASD-associated lncRNAs exhibit primate-specific expression patterns in brain.
“As a group, these lncRNAs are enriched in the brain relative to other tissues (Extended Data Fig. 2l, m) and most that have been evaluated across species exhibit primate-specific expression patterns in the brain11, which we confirm for several transcripts (Supplementary Information, Extended Data Fig. 3a–h).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] Necsulea, A. et al. The evolution of lncRNA repertoires and expression patterns in tetrapods. Nature 505, 635–640 (2014) source
Not checked in the free run.
- Findingown data
There is a remarkable difference in CTX.M19 and CTX.M20 during the first two decades of life.
“We identified a remarkable difference in CTX.M19 and CTX.M20 during the first two decades of life (Fig. 4g, additional age trajectories in Extended Data Fig. 9f) that is most consistent with an evolving process during early brain development that stabilizes starting in late childhood and early adolescence.”
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Compared with a prior RNA-seq study of occipital cortex, there is a weak but significant correlation in fold changes, mostly due to upregulated genes (P = 0.038).
“Despite significant technical differences that reduce power to detect DGE, and profiling of different brain regions in that study, there was a weak but significant correlation in fold changes, which was due mostly to upregulated genes in both studies (P = 0.038, Extended Data Fig. 2i, j).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [4] Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014) source
Not checked in the free run.
- Findingown data
Other phenotypes with larger, better-powered GWAS also demonstrate enrichment.
“However, other phenotypes with larger, better-powered genome-wide association studies (GWAS) also demonstrate enrichment (Extended Data Fig. 9h–i).”
Quote in the paperNot a substantial claim - Findingown data
There is no such correlation between splicing factor expression and differential splicing in the cerebellum.
“Therefore, we next investigated whether the shared splicing signature in ASD could be explained by perturbations in splicing factors known to be important in nervous system function8,14 (Extended Data Fig. 4j), and found high correlations between splicing factor expression and differential splicing in the cortex (Fig. 1f) but not the cerebellum (Fig. 1g).”
Quote in the paperSubstantial claim - Findingown data
The first principal components for protein coding DGE, lncRNA DGE, and differential splicing are highly correlated (R2 > 0.8).
“When we compared the first principal component across samples for protein coding DGE, lncRNA DGE and differential splicing, we found remarkably high correlations (R2 > 0.8), indicating that molecular convergence is likely to be a unitary phenomenon across multiple levels of transcriptome regulation in ASD (Fig. 1i).”
Quote in the paperSubstantial claim - Findingown data
Sixty lncRNAs are in the differential gene expression set in ASD cortex.
“We next explored lncRNAs, most of which have little functional annotation, and identified 60 lncRNAs in the DGE set (FDR < 0.05, Extended Data Fig. 2k).”
Quote in the paperSubstantial claim - Findingown data
Predicted SOX5 targets exhibited net down-regulation, consistent with the repressive function of SOX5.
“We confirmed that a significant proportion of ACP genes are regulated by SOX5 by overexpressing it in human neural progenitors. SOX5 induced synaptic genes and repressed cell proliferation (Fig. 2e), and predicted SOX5 targets exhibited net down-regulation, consistent with the repressive function of SOX5 (Fig. 2f, Extended Data Fig. 6l, m).”
Quote in the paperSubstantial claim - Findingown data
Downregulated modules are enriched in synaptic function and neuronal genes.
“It also confirms that downregulated modules are enriched in synaptic function and neuronal genes, that upregulated modules are enriched in genes associated with inflammatory pathways and glial function4,8, and that microglial and synaptic modules exhibit significant anticorrelation (Fig. 4c).”
Quote in the paperSubstantial claim - Findingcitation
Nine of the ASD-associated lncRNAs interact with FMRP.
“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.”
Quote in the paperSubstantial claim - Findingown data
In ASD cortex compared with control cortex, 558 genes show decreased expression.
“Compared to control cortex, 584 genes showed increased expression and 558 showed decreased expression in ASD cortex (Fig. 1b; Benjamini–Hochberg FDR < 0.05, linear mixed effects model; see Methods).”
Quote in the paperSubstantial claim - Findingown data
The upregulated module CTX.M20 was not found in previous analyses.
“Remarkably, the upregulated module CTX.M20 was not found in previous analyses, overlaps significantly with the ACP set (FDR < 0.05, Extended Data Fig. 9a), and contains genes implicated in development and regulation of cell differentiation (Fig. 4f).”
Quote in the paperNot a substantial claim - Findingown data
CTX.M24 exhibits significant enrichment for rare mutations found in ASD.
“One module, CTX.M24, exhibited significant enrichment for rare mutations found in ASD, while rare de novo mutations associated with intellectual disability were most strongly enriched in CTX.M22 (FDR < 0.05, Extended Data Fig. 9a).”
Quote in the paperSubstantial claim - Findingcitation
Twenty of the ASD-associated lncRNAs interact with miRNA-protein complexes.
“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.”
Quote in the paperSubstantial claim - Findingown data
In ASD cortex compared with control cortex, 584 genes show increased expression.
“Compared to control cortex, 584 genes showed increased expression and 558 showed decreased expression in ASD cortex (Fig. 1b; Benjamini–Hochberg FDR < 0.05, linear mixed effects model; see Methods).”
Quote in the paperSubstantial claim - Findingown data
Upregulated modules are enriched in genes associated with inflammatory pathways and glial function.
“It also confirms that downregulated modules are enriched in synaptic function and neuronal genes, that upregulated modules are enriched in genes associated with inflammatory pathways and glial function4,8, and that microglial and synaptic modules exhibit significant anticorrelation (Fig. 4c).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [4] Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014) source
Not checked in the free run.
- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Findingcitation
LINC00693 and LINC00689 interact with miRNA processing complexes.
“We highlight two primate-specific lncRNAs, LINC00693 and LINC00689. Both interact with miRNA processing complexes and are typically downregulated during development12, but are upregulated in ASD cortex (Fig. 1c, d, Extended Data Fig. 2n).”
Quote in the paperSubstantial claim - Findingown data
The upregulated gene set in ASD cortex is enriched in microglia- and astrocyte-expressed genes.
“We next evaluated enrichment of the gene sets for pathways and cell types (Extended Data Fig. 2d, e), and found that the downregulated set was enriched in genes expressed in neurons and involved in neuronal pathways, including PVALB and SYT2, which are highly expressed in interneurons; by contrast, the upregulated gene set was enriched in genes expressed in microglia and astrocytes8.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Findingown data
The differential splicing molecular signature is not driven by differential gene expression.
“Notably, the differential splicing molecular signature is not driven by DGE (Extended Data Fig. 4h), consistent with the observation that splicing alterations are related to common disease risk independently of gene expression changes16.”
Quote in the paperSubstantial claim - Findingown data
CTX.M20 contains genes implicated in development and regulation of cell differentiation.
“Remarkably, the upregulated module CTX.M20 was not found in previous analyses, overlaps significantly with the ACP set (FDR < 0.05, Extended Data Fig. 9a), and contains genes implicated in development and regulation of cell differentiation (Fig. 4f).”
Quote in the paperNot a substantial claim - Findingown data
Enrichment for ASD-associated common variation is observed in CTX.M20 at FDR < 0.1.
“By contrast, enrichment for ASD-associated common variation was observed in CTX. M20 (FDR < 0.1, Extended Data Fig. 9h–1, Methods).”
Quote in the paperSubstantial claim - Findingown data
Genome-wide (trans) DGE and differential splicing patterns are highly concordant between dup15q and ASD.
“Remarkably, genome-wide (trans) DGE and differential splicing patterns were highly concordant between dup15q and ASD (Fig. 3b, c, Extended Data Fig. 7c–e).”
Quote in the paperSubstantial claim - Findingown data
CTX.M20 overlaps significantly with the ACP set.
“Remarkably, the upregulated module CTX.M20 was not found in previous analyses, overlaps significantly with the ACP set (FDR < 0.05, Extended Data Fig. 9a), and contains genes implicated in development and regulation of cell differentiation (Fig. 4f).”
Quote in the paperSubstantial claim - Findingown data
Rare de novo mutations associated with intellectual disability are most strongly enriched in CTX.M22.
“One module, CTX.M24, exhibited significant enrichment for rare mutations found in ASD, while rare de novo mutations associated with intellectual disability were most strongly enriched in CTX.M22 (FDR < 0.05, Extended Data Fig. 9a).”
Quote in the paperSubstantial claim - Findingown data
Specific lncRNA transcripts show primate-specific expression, being present in human and macaque or only in human but not in mouse.
“Examples of specific lncRNA transcripts that show primate-specific (in human and macaque, or only in human, but not in mouse) expression.”
Quote in the paperNot a substantial claim - Findingown data
Neuronal splicing factor expression levels across samples form three major clusters.
“demonstrating three major clusters”
Quote in the paperNot a substantial claim - Findingown data
Transcription factor motifs are significantly enriched in the ACP gene set.
“Enrichment statistics for transcription factor motifs found to be significantly enriched in the ACP set”
Quote in the paperNot a substantial claim - Findingown data
Differentially expressed lncRNAs show significantly different expression in brain compared with other tissues.
“Lines above the plot indicate pairwise significance with a one-sided Wilcoxon rank-sum test between brain and the other tissues.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [12] Jaffe, A. E. et al. Developmental regulation of human cortex transcription and its clinical relevance at single base resolution. Nat. Neurosci. 18, 154–161 (2015) source
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- Findingown data
ASD versus control fold changes are similar in frontal cortex and temporal cortex.
“Comparison of fold changes between frontal cortex (FC) and temporal cortex (TC) for all samples, demonstrating similar changes in both regions.”
Quote in the paperNot a substantial claim - Findingown data
Differential splicing analysis identifies events that are independent of the differential gene expression signal.
“Differential splicing analysis identifies events independent of DGE signal.”
Quote in the paperSubstantial claim - Findingown data
Four module eigengenes, CTX.M4, CTX.M9, CTX.M10, and CTX.M16, are associated with ASD.
“Temporal trajectories for four module eigengenes (CTX.M4, CTX.M9, CTX.M10, CTX.M16) associated with ASD”
Quote in the paperNot a substantial claim - Findingown data
Differentially expressed lncRNAs show significantly different expression in brain compared with embryonic stem cells and stem-cell-derived cell types.
“Similar to l, except for embryonic stem cells and stem-cell-derived cell types.”
Quote in the paperNot a substantial claim - Findingown data
ASD cortex differential gene expression principal component 1 differs significantly from controls for samples with dup15q mutations, ADI-R-confirmed diagnoses, and clinically supported diagnoses.
“Samples from individuals with diagnoses confirmed by dup15q mutations, confirmed by Autism Diagnostic Interview-Revised (ADI-R), and supported by clinical records are all significantly different from controls by two-sided pairwise Wilcoxon rank sum tests.”
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The genes for these nine splicing events are not in the differential gene expression set but are detected in the differential alternative splicing set because of altered transcript structure.
“Notably, these genes are not in the DGE set, but are detected in the differential alternative splicing set owing to altered transcript structure.”
Quote in the paperNot a substantial claim - Findingown data
Three cerebellum modules are associated with ASD.
“Grey bars with labels signify three ASD-associated modules.”
Quote in the paperSubstantial claim - Findingown data
ASD versus control differential gene expression fold changes replicate between previously evaluated and newly analyzed ASD samples in cortex when measured by RNA-seq.
“Independent replication of ASD versus control DGE fold changes between previously evaluated and new ASD samples in cortex by RNA-seq using samples from ref. 8”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Findingown data
ASD-associated modules are enriched with modules from ref. 4.
“Enrichment of ASD-associated modules with that from ref. 4.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [4] Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014) source
Not checked in the free run.
- Findingown data
The first principal component of the cortex differential gene expression set is primarily associated with diagnosis and not with other factors.
“The first principal component of the cortex DGE set is primarily associated with diagnosis, and not with other factors.”
Quote in the paperSubstantial claim - Findingown data
ASD versus control differential gene expression fold changes replicate between previously evaluated and newly analyzed ASD samples from cerebellum by microarray and RNA-seq.
“Independent replication analysis of ASD versus control DGE fold changes between previously evaluated and new ASD samples from cerebellum by microarray and RNA-seq using samples from ref. 8”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Premisecitation
Autism spectrum disorder has a substantial genetic component.
“Autism spectrum disorder (ASD) involves substantial genetic contributions.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [1] Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46, 881–885 (2014) source
Not checked in the free run.
- cites [2] Gratten, J., Visscher, P. M., Mowry, B. J. & Wray, N. R. Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease. Nat. Genet. 45, 234–238 (2013) source
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- cites [3] de la Torre-Ubieta, L., Won, H., Stein, J. L. & Geschwind, D. H. Advancing the understanding of autism disease mechanisms through genetics. Nat. Med. 22, 345–361 (2016) source
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- Interpretationown data
SOX5 contributes to the reduction in regional gene expression differences in ASD.
“Our data suggest that SOX5, a transcription factor involved in neuron fate specification, contributes to this reduction in regional differences.”
Quote in the paperSubstantial claim - Interpretationown data
Dysregulation of lncRNAs is an integral component of the transcriptomic signature of ASD.
“These data show that dysregulation of lncRNAs, many of which are brain-enriched, primate-specific, and predicted to affect protein expression through miRNA or FMRP interactions, is an integral component of the transcriptomic signature of ASD.”
Quote in the paperSubstantial claim - Interpretationown data
The cortex is more selectively vulnerable to these transcriptomic alterations in ASD.
“The lack of significant DGE in the cerebellum is explained by the fact that changes in expression were consistently stronger in the cortex than in the cerebellum (Extended Data Fig. 2h), which suggests that the cortex is more selectively vulnerable to these transcriptomic alterations.”
Quote in the paperSubstantial claim - Premisecitation
Previous experimental perturbation of Rbfox1, SRRM4, and PTBP1 shows strong overlap with the differential splicing changes found in ASD cortex.
“Previous experimental perturbation of three splicing factors, Rbfox1 (ref. 18), SRRM4 (ref. 19), and PTBP1 (ref. 20), shows strong overlap with the differential splicing changes found in ASD cortex, further supporting these predicted relationships (Fig. 1h, Extended Data Fig. 5b).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [18] Lovci, M. T. et al. Rbfox proteins regulate alternative mRNA splicing through evolutionarily conserved RNA bridges. Nat. Struct. Mol. Biol. 20, 1434–1442 (2013) source
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- cites [19] Raj, B. et al. A global regulatory mechanism for activating an exon network required for neurogenesis. Mol. Cell 56, 90–103 (2014) source
Not checked in the free run.
- cites [20] Gueroussov, S. et al. An alternative splicing event amplifies evolutionary differences between vertebrates. Science 349, 868–873 (2015) source
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- Interpretationown data
Molecular convergence is likely a unitary phenomenon across multiple levels of transcriptome regulation in ASD.
“When we compared the first principal component across samples for protein coding DGE, lncRNA DGE and differential splicing, we found remarkably high correlations (R2 > 0.8), indicating that molecular convergence is likely to be a unitary phenomenon across multiple levels of transcriptome regulation in ASD (Fig. 1i).”
Quote in the paperSubstantial claim - Interpretationown data
The difference in CTX.M19 and CTX.M20 trajectories is most consistent with an evolving process during early brain development that stabilizes starting in late childhood and early adolescence.
“We identified a remarkable difference in CTX.M19 and CTX.M20 during the first two decades of life (Fig. 4g, additional age trajectories in Extended Data Fig. 9f) that is most consistent with an evolving process during early brain development that stabilizes starting in late childhood and early adolescence.”
Quote in the paperSubstantial claim - Interpretationown data
Diverse genetic perturbations can lead to phenotypic convergence at multiple biological levels in a complex neuropsychiatric disorder.
“Our findings illustrate how diverse genetic perturbations can lead to phenotypic convergence at multiple biological levels in a complex neuropsychiatric disorder.”
Quote in the paperSubstantial claim - Interpretationown data
Because CTX.M20 is enriched for the ACP gene set, there is a potential link between polygenic risk and regional attenuation of gene expression in ASD.
“As CTX.M20 is enriched for the ACP gene set, this suggests a potential link between polygenic risk and regional attenuation of gene expression in ASD.”
Quote in the paperSubstantial claim - Interpretationreasoning
The highly overlapping expression pattern shared by individuals with dup15q and the majority of those with idiopathic ASD represents an evolving adaptive or maladaptive response to a primary insult rather than a secondary environmental hit.
“Parsimony suggests that the highly overlapping expression pattern shared by individuals with dup15q and the majority of those with idiopathic ASD represents an evolving adaptive or maladaptive response to a primary insult rather than a secondary environmental hit.”
Quote in the paperSubstantial claim - Interpretationown data
Attenuated patterning of SOX5 between cortical regions contributes to direct alterations in patterning of SOX5 targets.
“These findings support the prediction that attenuated patterning of the transcription factor SOX5 between cortical regions contributes to direct alterations in patterning of SOX5 targets.”
Quote in the paperSubstantial claim - Study design and conductown data
qRT-PCR confirmed the technical quality of the RNA-seq data.
“We performed a classification analysis to confirm that gene expression in ASD could separate samples by disease status (Extended Data Fig. 2a) and confirmed the technical quality of our data with qRT–PCR (Extended Data Fig. 2b, c).”
Quote in the paperNot a substantial claim - Interpretationown data
Genetic risk for ASD may influence changes in regional cortical gene expression.
“Co-expression network analysis reveals that individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades, and suggests that genetic risk for ASD may influence changes in regional cortical gene expression.”
Quote in the paperSubstantial claim - Interpretationreasoning
The absence of neuronal splicing factor differential expression or correlation with splicing changes in cerebellum suggests these splicing factors contribute to cortex-biased differential splicing.
“The absence of neuronal splicing factor DGE or correlation with splicing changes in the cerebellum is consistent with the absence of a differential splicing signal in the cerebellum and suggests that these splicing factors contribute to cortex-biased differential splicing.”
Quote in the paperSubstantial claim - Study design and conductown data
Dup15q cortex differential gene expression findings are similar when different control samples are used.
“Comparison of DGE fold changes demonstrating that using different control samples (control samples used in the idiopathic analysis, column 2 of Extended Data Fig. 7b) for the dup15q cortex analysis yields similar findings.”
Quote in the paperNot a substantial claim - Premisecitation
The period of synapse elimination and stabilization after birth in humans corresponds to late childhood.
“This corresponds to the period of synapse elimination and stabilization after birth in humans28,29, which may have significant implications for intervention.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [28] Huttenlocher, P. R. Morphometric study of human cerebral cortex development. Neuropsychologia 28, 517–527 (1990) source
Not checked in the free run.
- cites [29] Khundrakpam, B. S., Lewis, J. D., Zhao, L., Chouinard-Decorte, F. & Evans, A. C. Brain connectivity in normally developing children and adolescents. Neuroimage 134, 192–203 (2016) source
Not checked in the free run.
- Interpretationcitation
Primate-specific lncRNAs are probably relevant to understanding human higher cognition.
“Our analyses also reveal primate-specific lncRNAs that are probably relevant to understanding human higher cognition11,30.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [11] Necsulea, A. et al. The evolution of lncRNA repertoires and expression patterns in tetrapods. Nature 505, 635–640 (2014) source
Not checked in the free run.
- cites [30] Zhang, Y. E., Landback, P., Vibranovski, M. D. & Long, M. Accelerated recruitment of new brain development genes into the human genome. PLoS Biol. 9, e1001179 (2011) source
Not checked in the free run.
- Interpretationown data
Aberrant microglia-neuron interactions reflect an early alteration in developmental trajectory that becomes more evident in late childhood.
“We interpret these data to suggest that aberrant microglia–neuron interactions reflect an early alteration in developmental trajectory that becomes more evident in late childhood.”
Quote in the paperSubstantial claim - Interpretationown data
The moderate agreement between ref. 4 and this study is largely driven by concordant upregulation of microglial genes in both studies.
“Co-expression network analysis demonstrated that the moderate agreement is largely driven by concordance in upregulation of microglial genes in both studies”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [4] Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014) source
Not checked in the free run.
- Study design and conductown data
Confounders do not drive the clustering of about two-thirds of ASD cortex samples.
“demonstrating that confounders do not drive clustering of about two-thirds of samples.”
Quote in the paperSubstantial claim - Interpretationreasoning
Some of the transcriptome changes in ASD are likely consequences or compensatory responses rather than causal factors.
“Although we observe no significant association of the ASD-associated transcriptome signature with either clinical or technical confounders, some of the changes are likely to represent consequences or compensatory responses, rather than causal factors.”
Quote in the paperSubstantial claim
- May combine two claims. 32
- The quote only partly states this claim. 1
- Classified as probably not a substantial claim. 14
May combine two claims.
Findingown dataAlterations in dup15q cortex are of greater magnitude and more homogeneous than those observed in idiopathic ASD cortex.
“Moreover, alterations in dup15q cortex were of greater magnitude and more homogeneous than those observed in idiopathic ASD cortex (Fig. 3d, Extended Data Fig. 7f, g).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn control subjects, 523 genes differ significantly in expression between frontal and temporal cortex, but these genes do not differ significantly in ASD; this is the attenuated cortical patterning set.
“We confirmed this in our larger cohort and identified 523 genes that differed significantly in expression between the frontal cortex and the temporal cortex in control subjects, but not those with ASD (Fig. 2a); we refer to these genes as the ‘attenuated cortical patterning’ (ACP) set (Extended Data Fig. 6a).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThere is a replication signal in the cerebellum and overall concordance between ASD-related fold changes in cortex and cerebellum.
“Although there was no significant DGE in the cerebellum (FDR < 0.05, P distributions in Fig. 1b), similar to observations in a smaller cohort8, there was a replication signal in the cerebellum and overall concordance between ASD-related fold changes in the cortex and cerebellum (Extended Data Fig. 2f–h).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
May combine two claims.
Findingown dataIn dup15q cerebellum, the DGE signal is weaker than in cortex, and cis changes are more concordant with cortex than trans changes.
“Analysis of DGE in the cerebellum confirmed a weaker signal than in the cortex and demonstrated that cis changes in dup15q cerebellum (Extended Data Fig. 7h–j) were more concordant with the cortex than trans changes (Extended Data Fig. 7k, l), further supporting the observation that the cortex is selectively vulnerable to transcriptomic alteration in ASD.”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataOf the 24 co-expression modules identified, six are associated with ASD: three upregulated and three downregulated, each showing significant cell-type enrichment.
“Of the six modules associated with ASD, three were upregulated and three were downregulated, and each showed significant cell-type enrichment (Fig. 4a, b).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSOX5 is the sole member of the ACP set among the identified transcription factors, and its correlation with predicted targets in control brains is lost in ASD.
“Among the transcription factors identified, SOX5 was of particular interest because of its known role in mammalian corticogenesis23,24, its sole membership in the ACP set, and its correlation with predicted targets in the brains of control subjects, which is lost in ASD (Fig. 2b–d).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSeveral other ASD-associated modules show a weaker common variant signal, including CTX.M16, which also shows a signal for schizophrenia polygenic risk.
“Several other ASD-associated modules showed a weaker common variant signal for ASD, including CTX.M16, which also shows a signal for schizophrenia polygenic risk.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn dup15q carriers, there is significant upregulation in the 15q11.1-13.2 region (cis), but this is not seen in idiopathic ASD.
“Significant upregulation in the 15q11.1–13.2 region (cis) was evident in duplication carriers, but not in idiopathic ASD (Fig. 3a).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataCTX.M24 is significantly enriched for lncRNAs, genes expressed highly during fetal cortical development, and genes harbouring protein-disrupting mutations found 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).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMost cortex modules are preserved in the cerebellum, but with weaker associations to ASD.
“We also found preservation of most cortex modules in the cerebellum, but with weaker associations to ASD (Extended Data Fig. 10a–h, Supplementary Table 4), consistent with the DGE analysis showing that ASD-related changes are substantially smaller in the cerebellum.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLINC00693 and LINC00689 are typically downregulated during development but are upregulated in ASD cortex.
“We highlight two primate-specific lncRNAs, LINC00693 and LINC00689. Both interact with miRNA processing complexes and are typically downregulated during development12, but are upregulated in ASD cortex (Fig. 1c, d, Extended Data Fig. 2n).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [12] Jaffe, A. E. et al. Developmental regulation of human cortex transcription and its clinical relevance at single base resolution. Nat. Neurosci. 18, 154–161 (2015) source
Not checked in the free run.
May combine two claims.
Findingown dataOverexpression of SOX5 in human neural progenitors induced synaptic genes and repressed cell proliferation.
“We confirmed that a significant proportion of ACP genes are regulated by SOX5 by overexpressing it in human neural progenitors. SOX5 induced synaptic genes and repressed cell proliferation (Fig. 2e), and predicted SOX5 targets exhibited net down-regulation, consistent with the repressive function of SOX5 (Fig. 2f, Extended Data Fig. 6l, m).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataCortex and cerebellum differential gene expression fold changes are strongly concordant, but the average fold change is lower in cerebellum.
“revealing strong concordance but a lower average fold change in the cerebellum.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataSamples from ref. 4 have lower RNA integrity, lower sequencing depth, greater 5′−3′ bias, and greater variability across quality-control metrics than samples in this study.
“Compared to this study, samples from ref. 4 were prepared by poly(A) selection RNA-seq, exhibit lower RNA integrity number (RIN, median 4.8 versus 7.3), have lower median sequencing depth (11 million versus 40 million), exhibit greater 5′−3′ bias, and have generally greater variability across all QC metrics.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [4] Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014) source
Not checked in the free run.
May combine two claims.
Findingown dataESRP2 is expressed in cortex but is not significantly different between ASD and control cortex.
“ESRP2 is expressed but not significantly different between ASD and control cortex.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataNine splicing events were validated by PCR.
“PCR validation and sashimi plots for nine splicing events delineated in Extended Data Fig. 4d”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataCTX.M24 is enriched in ASD-associated rare variants and lncRNAs.
“Module plot and GO term enrichment for CTX.M24, which is enriched in ASD-associated rare variants and lncRNAs.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataOne lncRNA is strongly conserved and shows robust expression in human, macaque, and mouse.
“Example of a strongly conserved lncRNA, which shows robust expression in all three species.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Findingnone givenESRP1 is not expressed in cortex.
“ESRP1 is not expressed in cortex”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAn elastic net model trained on RNA-seq data from ref. 8 classifies ASD versus control status in independent samples, with about 85% of ASD samples classified successfully around a false positive rate of 20%.
“Approximately 85% of ASD samples are classified successfully around a false positive rate of 20%.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- cites [47] Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010) source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataTwo lncRNAs shown in Fig. 1c,d were validated by RT-PCR.
“RT–PCR validation of the two lncRNAs shown in Fig. 1c, d; P values computed by two-sided Wilcoxon rank-sum test.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe first principal component of the cortex differential splicing set is strongly associated with diagnosis and not with other factors.
“The first principal component of the cortex differential splicing set is strongly associated with diagnosis, but not other factors.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe genetic contributions to ASD are highly heterogeneous but may converge on common pathways that are not yet well understood.
“These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood1–3.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [1] Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46, 881–885 (2014) source
Not checked in the free run.
- cites [2] Gratten, J., Visscher, P. M., Mowry, B. J. & Wray, N. R. Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease. Nat. Genet. 45, 234–238 (2013) source
Not checked in the free run.
- cites [3] de la Torre-Ubieta, L., Won, H., Stein, J. L. & Geschwind, D. H. Advancing the understanding of autism disease mechanisms through genetics. Nat. Med. 22, 345–361 (2016) source
Not checked in the free run.
May combine two claims.
Study design and conductown dataConfounders do not account for the differential splicing signal; it was reproduced with an alternative pipeline and validated with RT-PCR.
“We confirmed that confounders do not account for the differential splicing signal, reproduced the global differential splicing signal with an alternative pipeline15, and performed technical validation with RT–PCR (Extended Data Figs 4d–g, 5a), confirming the differential splicing analysis.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [15] Wu, J., Anczuków, O., Krainer, A. R., Zhang, M. Q. & Zhang, C. OLego: fast and sensitive mapping of spliced mRNA-Seq reads using small seeds. Nucleic Acids Res . 41, 5149–5163 (2013) source
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationSOX5 has a known role in mammalian corticogenesis.
“Among the transcription factors identified, SOX5 was of particular interest because of its known role in mammalian corticogenesis23,24, its sole membership in the ACP set, and its correlation with predicted targets in the brains of control subjects, which is lost in ASD (Fig. 2b–d).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [23] Kwan, K. Y. et al. SOX5 postmitotically regulates migration, postmigratory differentiation, and projections of subplate and deep-layer neocortical neurons. Proc. Natl Acad. Sci. USA 105, 16021–16026 (2008) source
Not checked in the free run.
- cites [24] Lamb, A. N. et al. Haploinsufficiency of SOX5 at 12p12.1 is associated with developmental delays with prominent language delay, behavior problems, and mild dysmorphic features. Hum. Mutat. 33, 728–740 (2012) source
Not checked in the free run.
May combine two claims.
Study design and conductown dataAttenuation of cortical patterning in ASD is robust: the ACP set is not more variable than other genes, the effect is robust to removal of previously analysed samples, and it is observed with a different classification approach.
“We demonstrated the robustness of attenuation in cortical patterning in ASD by confirming that the ACP set was not more variable than other genes, that attenuation of cortical patterning was robust to removal of previously analysed samples8, and that the effect could also be observed using a different classification approach (Extended Data Fig. 6b–h).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
May combine two claims.
Interpretationown dataThe co-expression analysis corroborates and extends previous work by identifying sub-modules of previously identified modules, demonstrating greater biological specificity.
“This analysis corroborates and extends previous work by identifying sub-modules of those previously identified, thus demonstrating greater biological specificity (Extended Data Figs 8e, 9a).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationSplicing alterations are related to common disease risk independently of gene expression changes.
“Notably, the differential splicing molecular signature is not driven by DGE (Extended Data Fig. 4h), consistent with the observation that splicing alterations are related to common disease risk independently of gene expression changes16.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [16] Li, Y. I. et al. RNA splicing is a primary link between genetic variation and disease. Science 352, 600–604 (2016) source
Not checked in the free run.
May combine two claims.
Study design and conductown dataThe ASD cortex differential expression signal is consistent across methods, unrelated to major confounders, and present in more than two-thirds of ASD samples.
“This DGE signal was consistent across methods, unrelated to major confounders, and found in more than two-thirds of ASD samples (Extended Data Fig. 1j–m).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFMRP 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.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [9] Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014) source
Not checked in the free run.
- cites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source
Not checked in the free run.
May combine two claims.
Interpretationown dataThe overlap supports a model of ASD pathophysiology based on changes in excitation/inhibition balance and neuronal activity and suggests that alterations in transcript structure are likely important.
“This overlap supports a model of ASD pathophysiology based on changes in the balance of excitation and inhibition and in neuronal activity22 and suggests that alterations in transcript structure are likely to be an important component.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [22] Mullins, C., Fishell, G. & Tsien, R. W. Unifying views of autism spectrum disorders: a consideration of autoregulatory feedback loops. Neuron 89, 1131–1156 (2016) source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable).
Interpretationown datalncRNAs 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).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source
Not checked in the free run.
- cites [25] Willsey, A. J. et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell 155, 997–1007 (2013) source
Not checked in the free run.
May combine two claims.
Interpretationown dataThe dup15q DGE and splicing analyses provide further biological validation of the ASD transcriptomic signature and show that a genetically defined form of ASD exhibits similar changes to idiopathic ASD.
“Together, the DGE and differential splicing analyses in dup15q provide further biological validation of the ASD transcriptomic signature and demonstrate that a genetically defined form of ASD exhibits similar changes to idiopathic ASD.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe modified WGCNA used bootstrapping 100 times and a consensus network to ensure that a subset of samples does not drive the network structure.
“Notably, we used a modified version of WGCNA that involves bootstrapping the underlying dataset 100 times and constructing 100 networks. The consensus of these networks (median edge strength across all bootstrapped networks) was then used as the final network39, ensuring that a subset of samples does not drive the network structure.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [39] Langfelder, P. & Horvath, S. Eigengene networks for studying the relationships between co-expression modules. BMC Syst. Biol. 1, 54 (2007) source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenSample dissections, RNA extractions, and RNA sequencing experiments were randomized.
“The sample dissections, RNA extractions, and RNA sequencing experiments were randomized (Supplementary Information).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationThe 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.”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [3] de la Torre-Ubieta, L., Won, H., Stein, J. L. & Geschwind, D. H. Advancing the understanding of autism disease mechanisms through genetics. Nat. Med. 22, 345–361 (2016) source
Not checked in the free run.
- cites [9] Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014) source
Not checked in the free run.
- cites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source
Not checked in the free run.
- cites [23] Kwan, K. Y. et al. SOX5 postmitotically regulates migration, postmigratory differentiation, and projections of subplate and deep-layer neocortical neurons. Proc. Natl Acad. Sci. USA 105, 16021–16026 (2008) source
Not checked in the free run.
Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based).
Study design and conductown dataDup15q differential alternative splicing findings are similar when different control samples are used.
“Similar to d except for the differential alternative splicing analysis.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSRRM4 and RBFOX1 expression are positively correlated, and PTBP1 and SRRM4 expression are anticorrelated.
“the known positive correlation between SRRM4 and RBFOX1 and anticorrelation between PTBP1 and SRRM4 (refs 14,19)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [14] Irimia, M. et al. A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell 159, 1511–1523 (2014) source
Not checked in the free run.
- cites [19] Raj, B. et al. A global regulatory mechanism for activating an exon network required for neurogenesis. Mol. Cell 56, 90–103 (2014) source
Not checked in the free run.
May combine two claims.
Study design and conductown dataLonger genes are not more likely to contain differential splicing events; the correlation between number of detected events and gene length is minimal (R2 = 0.004).
“However, the correlation between the number of detected events in genes and gene length is minimal (R2 = 0.004), and the correlation is even smaller for events at P < 0.01 (R2 = 0.00012) demonstrating that longer genes are not more likely to contain differential splicing events.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenInvestigators were blinded to diagnosis until the analysis but were unblinded during the analysis.
“The investigators were blinded to diagnosis until the analysis but unblinded during the analysis.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataCo-expression of lncRNAs with genes harbouring ASD-associated protein coding mutations suggests that these noncoding RNAs are involved in similar biological functions and are potential candidate ASD risk loci.
“Co-expression of lncRNAs with genes harbouring ASD-associated protein coding mutations suggests that these noncoding RNAs are involved in similar biological functions and are potential candidate ASD risk loci.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductreasoningThe qRT-PCR validation sample size is underpowered to evaluate significant changes in many genes or splicing events, but the goal was to validate the accuracy of the data and analyses across genes.
“Notably, this sample size is underpowered to evaluate significant changes in many genes or splicing events; however, the goal was to validate the accuracy of our data and analyses across genes, so we show the correlation of fold changes between ASD and control across genes or events.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenNo statistical methods were used to predetermine sample size.
“No statistical methods were used to predetermine sample size.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Post-mortem brain transcriptome measurements reflect the molecular pathology of ASD in living individuals.
“Here, through post-mortem genome-wide transcriptome analysis of the largest cohort of samples analysed so far, to our knowledge4–7, we interrogate the noncoding transcriptome, alternative splicing, and upstream molecular regulators to broaden our understanding of molecular convergence in ASD.”
The paper relies on this without support.
The control subjects are free of ASD and comparable to the ASD subjects in ways that do not confound the transcriptomic comparisons.
“We performed rRNA-depleted RNA sequencing (RNA-seq) of 251 post-mortem samples of frontal and temporal cortex and cerebellum from 48 individuals with ASD and 49 control subjects (Methods and Extended Data Fig. 1a–h).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ASD postmortem brains exhibit cell-type specific gene expression signatures such as upregulation of glial genes and downregulation of neuronal genes.
“For example, ASD postmortem brains exhibit cell-type specific gene expression signatures such as upregulation of glial genes and downregulation of neuronal genes30.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [30]
In autism spectrum disorder, analyses replicated using different methods and samples implicate synaptic and neuronal signaling pathways overlapping with other causal gene-based network methods.
“In ASD, these analyses, replicated using different methods and samples, implicate synaptic and neuronal signaling pathways overlapping with other causal gene-based network methods (Parikshak et al., 2016; Voineagu et al., 2011).”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Parikshak et al., 2016
The study combined RNA-seq data from eight studies through a uniform processing pipeline, yielding 2188 samples that passed QC, from 1695 unique subjects, including 279 technical replicates.
“Data was generated across eight studies (2, 19, 20), uniformly processed, and combined through a consolidated genomic data processing pipeline ((21); Fig S1), yielding a total of 2188 samples passing quality control (QC) for this analysis, representing frontal and temporal cerebral cortex from 1695 unique subjects across the lifespan, including 279 technical replicates (Fig S2).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
DGE effect sizes were concordant with previous RNA-seq studies of individual disorders.
“and with previous RNA-Seq studies of individual disorders (ASD: ⍴=0.96, ref (19); SCZ ⍴=0.78, ref (2); SCZ ⍴=0.80, ref (24); BD ⍴=0.85, ref (1); Spearman ⍴ of log2FC, all P’s<10−16).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
DE genes were enriched for known pathways and cell-type-specific markers from single-nucleus RNA-seq in human brain.
“These DE genes exhibited substantial enrichment for known pathways and cell type specific markers derived from single nucleus RNA-Seq in human brain (Fig 1D-E) (21), consistent with previously observed patterns (1, 19).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
ASD DS intron clusters overlapped 42% with a previous study using a different method and a subset of samples.
“We found significant overlap (42%, P=3.42×10−27; Fisher’s exact test) of the ASD DS intron clusters and splicing changes identified in a previous study (19) that used a different method and only a subset of the samples in our ASD and control cohorts (Table S3).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
Previous studies identified alterations in local splicing events in ASD and in smaller cohorts in SCZ and BD.
“Previous studies have identified alterations in local splicing events in ASD (19, 30) and in smaller cohorts in SCZ (2, 24) and BD (31).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
Multiple neuronal and synaptic signaling pathways have been previously demonstrated to be downregulated in a diminishing gradient across ASD, SCZ, and BD brains without clear disease-specific signals.
“Multiple neuronal and synaptic signaling pathways have been previously demonstrated to be downregulated in a diminishing gradient across ASD, SCZ, and BD brains without identification of clear disease-specific signals for these neuronal-synaptic gene sets (1, 2, 16, 19, 56, 57).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
Prior studies found both microglia and astrocytes upregulated in autism spectrum disorder.
“and both microglia and astrocytes in ASD (19, 70).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
Post-mortem microglial upregulation has been observed only in autism spectrum disorder.
“although post-mortem microglial upregulation was observed only in ASD (1, 19, 70).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [19]
Post-mortem genome-wide transcriptome analysis in humans revealed age-related changes in the trajectory of microglial and synaptic dysfunction that may reflect an early developmental alteration in microglial function.
“In humans, post-mortem genome-wide transcriptome analysis has revealed age-related changes in the trajectory of microglial and synaptic dysfunction that may reflect an early developmental alteration in microglial function163.”
From Microglial signatures and their role in health and disease (2018) · cites this paper as [163]
DEGs in 22q11DS were enriched for schizophrenia-associated variants, but not for DEGs found in ASD or schizophrenia postmortem brain tissue.
“We observed an enrichment for variants associated with schizophrenia, but not for DEG found in ASD or SCZ postmortem brain tissue35,36.”
From Neuronal defects in a human cellular model of 22q11.2 deletion syndrome (2020) · cites this paper as [35]
The transcriptional program in ASD brains is distinct from that of TD brains.
“The transcriptional program in ASD brains is distinct from that of TD brains (Gandal et al., 2018; Parikshak et al., 2016; Voineagu et al., 2011).”
From Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice (2019) · cites this paper as Parikshak et al., 2016
Changes in microglial density, morphology, and transcriptional state have been observed in postmortem brain tissue of patients with neurological and psychiatric disorders.
“For decades, changes in microglial density, morphology, and transcriptional state have been observed in postmortem brain tissue of patients with neurological and psychiatric disorders17–21.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [21]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Spline degree conflicts with its description
MinorThe methods call the fitted curves quartic, which means degree 4, but specify degree 2, which is quadratic.
“quartic splines”
“(degree = 2, span = 2/3)”
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Self-citationLD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559 · see citing works
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Differential analysis of gene regulation at transcript resolution with RNA-seq
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“Disease GWAS studies evaluated include ASD 54 , schizophrenia 55 , inflammatory bowel disease 56 , type 2 diabetes mellitus 57 and serum lipid levels 58 .”
The contribution of de novo coding mutations to autism spectrum disorder
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InfluentialSpatio-temporal transcriptome of the human brain
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Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis
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“Disease GWAS studies evaluated include ASD 54 , schizophrenia 55 , inflammatory bowel disease 56 , type 2 diabetes mellitus 57 and serum lipid levels 58 .”
Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
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Self-citationTranscriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
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“…cortical patterning in ASD by confirming that the ACP set was not more variable than other genes, that attenuation of cortical patterning was robust to removal of previously analysed samples 8 , and that the effect could also be observed using a different classification approach (Extended Data Fig.”
InfluentialSelf-citationInsights into autism spectrum disorder genomic architecture and biology from 71 risk loci
Sanders, S. J., He, X., Willsey, A. J., Ercan-Sencicek, A. G., Samocha, K. E., Cicek, A. E., Murtha, M. T., Bal, V. H., Bishop, S. L., Dong, S., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.016 · Cited by 1,430 · cited 1× · see citing works
“…with multiple gene sets from this RNA-seq study, post-mortem ASD cortex microarray 8 , human cortical development 10 , the set of all brain-expressed lncRNAs, genes enriched for ASD-associated rare variants 26 , and genes with de novo variants associated with intellectual disability (ID) 9 .”
Self-citationFast R Functions for Robust Correlations and Hierarchical Clustering
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Self-citationMorphometric study of human cerebral cortex development
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“This corresponds to the period of synapse elimination and stabilization after birth in humans 28,29 , which may have significant implications for intervention.”
Most genetic risk for autism resides with common variation
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Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
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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.”
InfluentialSelf-citationThe evolution of lncRNA repertoires and expression patterns in tetrapods
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InfluentialEigengene networks for studying the relationships between co-expression modules
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“The consensus of these networks (median edge strength across all bootstrapped networks) was then used as the final network 39 , ensuring that a subset of samples does not drive the network structure.”
Self-citationAdvancing the understanding of autism disease mechanisms through genetics
de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016) · Nature Medicine · doi:10.1038/nm.4071 · Cited by 827 · cited 1× · see citing works
“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.”
Self-citationAllen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system
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A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains
Irimia, M., Weatheritt, R. J., Ellis, J. D., Parikshak, N. N., Gonatopoulos-Pournatzis, T., Babor, M., Quesnel-Vallières, M., Tapial, J., Raj, B., O’Hanlon, D., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.035 · Cited by 693 · cited 3× · see citing works
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Self-citationRNA splicing is a primary link between genetic variation and disease
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“4h), consistent with the observation that splicing alterations are related to common disease risk independently of gene expression changes 16 .”
GENCODE: producing a reference annotation for ENCODE
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Postmortem brain abnormalities of the glutamate neurotransmitter system in autism
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“We also compared our results to an RNA-seq study of protein coding genes in the occipital cortex of individuals with ASD and control subjects 4 .”
Rbfox proteins regulate alternative mRNA splicing through evolutionarily conserved RNA bridges
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Immune transcriptome alterations in the temporal cortex of subjects with autism
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Self-citationGenetic risk for autism spectrum disorders and neuropsychiatric variation in the general population
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“Disease GWAS studies evaluated include ASD 54 , schizophrenia 55 , inflammatory bowel disease 56 , type 2 diabetes mellitus 57 and serum lipid levels 58 .”
EGASP: the human ENCODE Genome Annotation Assessment Project.
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Critical Role of Histone Turnover in Neuronal Transcription and Plasticity
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“Among the transcription factors identified, SOX5 was of particular interest because of its known role in mammalian corticogenesis 23,24 , its sole membership in the ACP set, and its correlation with predicted targets in the brains of control subjects, which is lost in ASD (Fig.”
GO-Elite: a flexible solution for pathway and ontology over-representation
Zambon, A. C., Gaj, S., Ho, I., Hanspers, K., VRANIZAN, K. M., Evelo, C. T., Conklin, B. R., Pico, A. R., & Salomonis, N. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts366 · Cited by 263 · see citing works
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“These data contribute to a consistent emerging picture of the molecular pathology of ASD 4,7,8,10,25–27 .”
Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops
Mullins, C., Fishell, G., & Tsien, R. W. (2016) · Neuron · doi:10.1016/j.neuron.2016.02.017 · Cited by 167 · cited 1× · see citing works
“This overlap supports a model of ASD pathophysiology based on changes in the balance of excitation and inhibition and in neuronal activity 22 and suggests that alterations in transcript structure are likely to be an important component.”
Accelerated Recruitment of New Brain Development Genes into the Human Genome
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“Our analyses also reveal primate-specific lncRNAs that are probably relevant to understanding human higher cognition 11,30 .”
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“Both interact with miRNA processing complexes and are typically down-regulated during development 12 , but are upregulated in ASD cortex (Fig.”
An alternative splicing event amplifies evolutionary differences between vertebrates
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Self-citationBlumenthal, I., Ragavendran, A., Erdin, S., Klei, L., Sugathan, A., Guide, J. R., Manavalan, P., Zhou, J. Q., Wheeler, V. C., Levin, J. Z., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.05.004 · Cited by 145 · cited 1× · see citing works
“These data contribute to a consistent emerging picture of the molecular pathology of ASD 4,7,8,10,25–27 .”
Dittmar, K. A., Jiang, P., Park, J. W., Amirikian, K., Wan, J., Shen, S., Xing, Y., & Carstens, R. P. (2012) · Molecular and Cellular Biology · doi:10.1128/mcb.06536-11 · Cited by 139 · see citing works
A Global Regulatory Mechanism for Activating an Exon Network Required for Neurogenesis
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Self-citationOLego: fast and sensitive mapping of spliced mRNA-Seq reads using small seeds
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“…of transcript splicing, MATS 35 ) with PSI values obtained via another method (read alignment by OLego followed by PSI quantification with Quantas 15 ). g , Comparison of Δ PSI values between RT–PCR and RNA-seq for nine splicing events (Supplementary Table 3). h , Differential splicing analysis…”
The organization of the transcriptional network in specific neuronal classes
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“Among the transcription factors identified, SOX5 was of particular interest because of its known role in mammalian corticogenesis 23,24 , its sole membership in the ACP set, and its correlation with predicted targets in the brains of control subjects, which is lost in ASD (Fig.”
Brain connectivity in normally developing children and adolescents
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“This corresponds to the period of synapse elimination and stabilization after birth in humans 28,29 , which may have significant implications for intervention.”
Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease
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Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general populationPreprint
Robinson, E., Pourcain, B. S., Anttila, V., Kosmicki, J. A., Bulik-Sullivan, B. K., Grove, J., Maller, J., Samocha, K. E., Sanders, S., Ripke, S., et al. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/027771 · Cited by 34 · see citing works
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Identification of common genetic risk variants for autism spectrum disorder
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InfluentialSelf-citationMicroglial signatures and their role in health and disease
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Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice
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BackgroundMethodInfluentialSelf-citationComprehensive functional genomic resource and integrative model for the human brain
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Self-citationSelenium Drives a Transcriptional Adaptive Program to Block Ferroptosis and Treat Stroke
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Self-citationSingle-cell genomics identifies cell type–specific molecular changes in autism
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Self-citationInherited and de novo genetic risk for autism impacts shared networks
Ruzzo, E. K., Pérez-Cano, L., Jung, J.-Y., Wang, L.-K., Kashef-Haghighi, D., Hartl, C., Singh, C., Xu, J., Hoekstra, J. N., Leventhal, O., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.015 · Cited by 457 · see citing works
Self-citationDefining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
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The Role of m6A/m-RNA Methylation in Stress Response Regulation
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Long-term maturation of human cortical organoids matches key early postnatal transitions
Gordon, A., Yoon, S., Tran, S. S., Makinson, C. D., Park, J. Y., Andersen, J., Valencia, A. M., Horvath, S., Xiao, X. G., Huguenard, J. R., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00802-y · Cited by 352 · see citing works
Self-citationTranscriptome and epigenome landscape of human cortical development modeled in organoids
Amiri, A., Coppola, G., Scuderi, S., Wu, F., Roychowdhury, T., Liu, F., Pochareddy, S., Shin, Y., Safi, A., Song, L., et al. (2018) · Science · doi:10.1126/science.aat6720 · Cited by 303 · see citing works
“3B) and overlapped with neuronal and synaptic modules down-regulated in the ASD postmortem cerebral cortex (25) as well as with a synapse module up-regulated in brain organoids from ASD individuals with macrocephaly (6).”
BackgroundInfluentialSelf-citationBroad transcriptomic dysregulation occurs across the cerebral cortex in ASD
Gandal, M. J., Haney, J. R., Wamsley, B., Yap, C. X., Parhami, S., Emani, P. S., Chang, N., Chen, G. T., Hoftman, G. D., de Alba, D., et al. (2022) · Nature · doi:10.1038/s41586-022-05377-7 · Cited by 281 · see citing works
“(5) A two-tailed P-value was obtained from testing the ‘true’ difference against the permuted distribution.”
MethodSelf-citationHistone Acetylome-wide Association Study of Autism Spectrum Disorder
Sun, W., Poschmann, J., Cruz-Herrera del Rosario, R., Parikshak, N. N., Hajan, H. S., Kumar, V., Ramasamy, R., Belgard, T. G., Elanggovan, B., Wong, C. C. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.031 · Cited by 306 · see citing works
“To investigate the consistency between chromatin aberrations and gene expression changes in ASD, we focused on promoter regions of differentially expressed (DE) genes (FDR % 0.05; linear mixed model) (Parikshak et al., 2016).”
BackgroundMethodResultInfluentialSelf-citationSey, N. Y. A., Hu, B., Mah, W., Fauni, H., McAfee, J. C., Rajarajan, P., Brennand, K. J., Akbarian, S., & Won, H. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0603-0 · Cited by 297 · see citing works
Wan, Y.-W., Al-Ouran, R., Mangleburg, C. G., Perumal, T. M., Lee, T. V., Allison, K., Swarup, V., Funk, C. C., Gaiteri, C., Allen, M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107908 · Cited by 295 · see citing works
“, 2016), metanetwork, rWGCNA (Parikshak et al., 2016), speakEasy (Gaiteri et al.”
Self-citationSchafer, S. T., Paquola, A. C. M., Stern, S., Gosselin, D., Ku, M., Pena, M., Kuret, T. J. M., Liyanage, M., Mansour, A. A., Jaeger, B. N., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0295-x · Cited by 288 · see citing works
Cross talk: the microbiota and neurodevelopmental disorders
Kelly, J. R., Minuto, C., Cryan, J. F., Clarke, G., & Dinan, T. G. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00490 · Cited by 271 · see citing works
“, 2016), and genes that encode proteins for synaptic formation, microglial function, transcriptional regulation and chromatin-remodeling pathways are implicated (De Rubeis et al., 2014; Parikshak et al., 2016).”
BackgroundInnate immune dysfunction and neuroinflammation in autism spectrum disorder (ASD)
Hughes, H. K., Moreno, R. J., & Ashwood, P. (2022) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2022.12.001 · Cited by 288 · see citing works
“The second module associated with ASD was enriched in overexpressed immune genes, and later work by this same group supported these findings (Voineagu, 2011; Parikshak, 2016).”
Lopes, K. D. P., Snijders, G. J. L., Humphrey, J., Allan, A., Sneeboer, M. A. M., Navarro, E., Schilder, B. M., Vialle, R. A., Parks, M., Missall, R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00976-y · Cited by 273 · see citing works
Signalling pathways in autism spectrum disorder: mechanisms and therapeutic implications
Jiang, C.-C., Lin, L., Long, S., Ke, X., Fukunaga, K., Lu, Y., & Han, F. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01081-0 · Cited by 272 · see citing works
“The evolution of lncRNA-specific and synaptic function-enriched gene expression in primates suggests that this category of RNAs may have a broad range of roles in the brain and may help to elucidate the aetiology of ASD.(31,278,279) In animal studies, mice with heterozygous knockout of miR-137 show repetitive behaviou…”
BackgroundGermline Chd8 haploinsufficiency alters brain development in mouse
Gompers, A. L., Su-Feher, L., Ellegood, J., Copping, N. A., Riyadh, M. A., Stradleigh, T. W., Pride, M. C., Schaffler, M. D., Wade, A. A., Catta-Preta, R., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4592 · Cited by 266 · see citing works
“DS genes identified in Chd8 + / del5 mouse brain were enriched for DS-associated genes identified in post-mortem ASD cortex 24 ( P = 1.2 × 10 −17 ), suggesting that DS in Chd8 + / del5 mice is linked to ASD-relevant DS ( Supplementary Fig.”
InfluentialMolecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer’s disease
Otero-Garcia, M., Mahajani, S. U., Wakhloo, D., Tang, W., Xue, Y.-Q., Morabito, S., Pan, J., Oberhauser, J., Madira, A. E., Shakouri, T., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.06.021 · Cited by 262 · see citing works
Self-citationGenomics, convergent neuroscience and progress in understanding autism spectrum disorder
Willsey, H. R., Willsey, A. J., Wang, B., & State, M. W. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00576-7 · Cited by 234 · see citing works
Wang, X., Wang, B., Wu, C., Wang, J., & Sun, M. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24031819 · Cited by 305 · see citing works
Widespread RNA editing dysregulation in brains from autistic individuals
Tran, S. S., Jun, H.-I., Bahn, J. H., Azghadi, A., Ramaswami, G., Nostrand, E. L. V., Nguyen, T. B., Hsiao, Y.-H. E., Lee, C., Pratt, G. A., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0287-x · Cited by 217 · see citing works
Self-citationPrenatal Origins of ASD: The When, What, and How of ASD Development
Courchesne, E., Gazestani, V., & Lewis, N. E. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2020.03.005 · Cited by 191 · see citing works
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“Adult gene co-expression modules (Parikshak et al., 2016).”
BackgroundInfluentialLeung, S. K., Jeffries, A. R., Castanho, I., Jordan, B. T., Moore, K., Davies, J. P., Dempster, E. L., Bray, N. J., O’Neill, P., Tseng, E., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110022 · Cited by 168 · see citing works
“…feature of many neuropsychiatric and neurodegenerative diseases (Mills and Janitz, 2012), with recent studies highlighting splicing differences associated with autism (Parikshak et al., 2016), schizophrenia (SZ) (Takata, Matsumoto and Kato, 2017), and Alzheimer’s disease (AD) (Raj et al., 2018).”
Self-citationAutism-like phenotype and risk gene mRNA deadenylation by CPEB4 mis-splicing
Parras, A., Anta, H., Santos‐Galindo, M., Swarup, V., Elorza, A., Nieto-González, J. L., Picó, S., Hernández, I. H., Díaz‐Hernandéz, J. I., Belloc, E., et al. (2018) · Nature · doi:10.1038/s41586-018-0423-5 · Cited by 175 · see citing works
Self-citationRegulation of Neuronal Differentiation, Function, and Plasticity by Alternative Splicing
Furlanis, E., & Scheiffele, P. (2018) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100617-062826 · Cited by 171 · see citing works
Neuronal defects in a human cellular model of 22q11.2 deletion syndrome
Khan, T. A., Revah, O., Gordon, A., Yoon, S.-J., Krawisz, A. K., Goold, C., Sun, Y., Kim, C. H., Tian, Y., Li, M.-Y., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1043-9 · Cited by 186 · see citing works
Self-citationAutism spectrum disorder: insights into convergent mechanisms from transcriptomics
Quesnel-Vallières, M., Weatheritt, R. J., Cordes, S. P., & Blencowe, B. J. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0066-2 · Cited by 167 · see citing works
Self-citationEvaluating measures of association for single-cell transcriptomics
Skinnider, M. A., Squair, J. W., & Foster, L. J. (2019) · Nature Methods · doi:10.1038/s41592-019-0372-4 · Cited by 145 · see citing works
The Role of Gut Dysbiosis in the Pathophysiology of Neuropsychiatric Disorders
Anand, N., Gorantla, V. R., & Chidambaram, S. B. (2022) · Cells · doi:10.3390/cells12010054 · Cited by 191 · see citing works
Single-cell genomics and regulatory networks for 388 human brains
Emani, P. S., Liu, J. J., Clarke, D., Jensen, M., Warrell, J., Gupta, C., Meng, R., Lee, C.-Y., Xu, S., Dursun, C., et al. (2024) · Science · doi:10.1126/science.adi5199 · Cited by 168 · see citing works
Self-citationBehavioral neuroscience of autism
Takumi, T., Tamada, K., Hatanaka, F., Nakai, N., & Bolton, P. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.04.012 · Cited by 163 · see citing works
Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder
Buch, A. M., Vértes, P. E., Seidlitz, J., Kim, S. H., Grosenick, L., & Liston, C. M. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01259-x · Cited by 156 · see citing works
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Identification of evolutionarily conserved gene networks mediating neurodegenerative dementia
Swarup, V., Hinz, F. I., Rexach, J. E., Noguchi, K.-I., Toyoshiba, H., Oda, A., Hirai, K., Sarkar, A., Seyfried, N. T., Cheng, C., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0223-3 · Cited by 136 · see citing works
“This measure combines module density and intramodular connectivity metrics to give a composite statistic where Z > 2 suggests moderate preservation and Z > 10 suggests high preservation 32 .”
Self-citationFetit, R., Hillary, R. F., Price, D. J., & Lawrie, S. M. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.07.014 · Cited by 148 · see citing works
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Reintroduction of the archaic variant of NOVA1 in cortical organoids alters neurodevelopment
Trujillo, C. A., Rice, E. S., Schaefer, N. K., Chaim, I. A., Wheeler, E. C., Madrigal, A. A., Buchanan, J., Preißl, S., Wang, A., Negraes, P. D., et al. (2021) · Science · doi:10.1126/science.aax2537 · Cited by 146 · see citing works
“Alternative splicing is thought to be particularly important in the brain, because neural tissues express a number of brain-specific splicing factors necessary for proper corticaldevelopment ( 17 , 35 ).”
BackgroundComprehensive evaluation of deconvolution methods for human brain gene expression
Sutton, G. J., Poppe, D., Simmons, R. K., Walsh, K., Nawaz, U., Lister, R., Gagnon-Bartsch, J. A., & Voineagu, I. (2022) · Nature Communications · doi:10.1038/s41467-022-28655-4 · Cited by 117 · see citing works
“Pseudo-bulk ASD vs. Control simulated data .”
BackgroundMethodInfluentialDysregulation of Cortical Neuron DNA Methylation Profile in Autism Spectrum Disorder
Nardone, S., Sams, D. S., Zito, A., Reuveni, E., & Elliott, E. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx250 · Cited by 137 · see citing works
“For commercial re-use, please contact journals.permissions@oup.com histone H3 at lysine 27 (H3K27ac) (Sun et al. 2016), long noncoding (lnRNA) (Ziats and Rennert 2013; Parikshak et al. 2016), and micro-RNA (miRNA) (Mor et al. 2015; Wu et al. 2016).”
BackgroundMolecular cascades and cell type–specific signatures in ASD revealed by single-cell genomics
Wamsley, B., Bicks, L. K., Cheng, Y., Kawaguchi, R., Quintero, D., Grundman, J., Liu, J., Xiao, S., Hawken, N., Margolis, M., et al. (2024) · Science · doi:10.1126/science.adh2602 · Cited by 151 · see citing works
“BA4/6 samples were pre-viouslysubjectedtobulkstudies:Parikshak etal ., Nature 2016 ( 7 ); Gandal et al ., Science 2018 ( 8 ), andasmallsubset ofsamples(sixsamples)were processed for a different single-cell analysis in Gandal et al ., Nature 2022 ( 14 ).”
MethodSelf-citationGonatopoulos-Pournatzis, T., Wu, M., Braunschweig, U., Roth, J. F., Han, H. R., Best, A. J., Raj, B., Aregger, M., O’Hanlon, D., Ellis, J. D., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.10.008 · Cited by 119 · see citing works
Self-citationCNV biology in neurodevelopmental disorders
Takumi, T., & Tamada, K. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.12.004 · Cited by 116 · see citing works
Epigenetics of Autism Spectrum Disorder
Siu, M. T., & Weksberg, R. (2017) · Advances in Experimental Medicine and Biology · doi:10.1007/978-3-319-53889-1_4 · Cited by 121 · see citing works
Altered expression of histamine signaling genes in autism spectrum disorder
Wright, C., Shin, J. H., Rajpurohit, A., Deep‐Soboslay, A., Collado‐Torres, L., Brandon, N. J., Hyde, T. M., Kleinman, J. E., Jaffe, A. E., Cross, A. J., et al. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.87 · Cited by 120 · see citing works
Splicing Activation by Rbfox Requires Self-Aggregation through Its Tyrosine-Rich Domain
Yi, Y., Wang, X., Vuong, C. K., Lin, C.-H., Damianov, A., & Black, D. L. (2017) · Cell · doi:10.1016/j.cell.2017.06.022 · Cited by 104 · see citing works
The Parvalbumin Hypothesis of Autism Spectrum Disorder
Filice, F., Janickova, L., Henzi, T., Bilella, A., & Schwaller, B. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.577525 · Cited by 118 · see citing works
“This is in line with RNAseq results from cortical samples of ASD patients demonstrating that UCP2 is among the most strongly upregulated transcripts (Parikshak et al., 2016; Schwede et al., 2018).”
ResultSingle-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue
Hardwick, S. A., Hu, W., Joglekar, A., Fan, L., Collier, P. G., Foord, C., Balacco, J., Lanjewar, S., Sampson, M. M., Koopmans, F., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01231-3 · Cited by 119 · see citing works
Lombardo, M. V., Pramparo, T., Gazestani, V., Warrier, V., Bethlehem, R. A. I., Barnes, C. C., Lopez, L., Lewis, N. E., Eyler, L. T., Pierce, K., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0281-3 · Cited by 95 · see citing works
Baglietto‐Vargas, D., Forner, S., Cai, L., Martini, A. C., Trujillo‐Estrada, L., Swarup, V., Nguyen, M. M. T., Huynh, K. D., Javonillo, D. I., Tran, K. M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22624-z · Cited by 112 · see citing works
“Seed-free Aβ (1-40) peptide was prepared in 10 mM NaOH and filtered through a 30-kDa cutoff filter.”
MethodSelf-citationBayesian estimation of cell type–specific gene expression with prior derived from single-cell dataPreprint
Wang, J., Roeder, K., & Devlin, B. (2021) · Genome Research · doi:10.1101/gr.268722.120 · Cited by 86 · see citing works
“allows assessment of tissue fromhundreds of samples, thereby producing rich data sets (Allen et al. 2016; Parikshak et al. 2016; The GTEx Consortium 2017; Bennett et al. 2018; Wang et al. 2018).”
BackgroundMethodInfluentialBochukova, E. G., Lawler, K., Croizier, S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.018 · Cited by 115 · see citing works
“Interestingly, this cellular transcriptomic profile aligns with that seen in autism (Parikshak et al., 2016), in several neurodegenerative diseases, and in the aging brain (Blalock et al., 2004; Lu et al., 2004) (Figure S2A), suggesting that fundamental mechanisms regulating neuronal…”
BackgroundGenetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms
Walker, R. L., Ramaswami, G., Hartl, C., Mancuso, N., Gandal, M. J., de la Torre-Ubieta, L., Paşaniuc, B., Stein, J. L., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.09.021 · Cited by 262 · see citing works
Self-citationSapkota, D., Lake, A. M., Yang, W., Yang, C., Wesseling, H., Guise, A. J., Uncu, C., Dalal, J. S., Kraft, A. W., Lee, J., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2018.12.077 · Cited by 111 · see citing works
“Alternative splicing is well studied and known to be modulated by neural activity and disease states and in a cell-type-specific manner in the CNS (Hermey et al., 2017; Licatalosi and Darnell, 2006; Parikshak et al., 2016; Quesnel-Vallières et al., 2016; Zhang et al., 2014b).”
BackgroundInfluentialRNA-binding proteins balance brain function in health and disease
Schieweck, R., Ninkovic, J., & Kiebler, M. A. (2020) · Physiological Reviews · doi:10.1152/physrev.00047.2019 · Cited by 104 · see citing works
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Self-citationRbfox1 Regulates Synaptic Transmission through the Inhibitory Neuron-Specific vSNARE Vamp1
Vuong, C. K., Wei, W., Lee, J.-A., Lin, C.-H., Damianov, A., de la Torre-Ubieta, L., Halabi, R., Otis, K. O., Martin, K. C., O’Dell, T. J., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.008 · Cited by 102 · see citing works
Self-citationMatoba, N., Liang, D., Sun, H., Aygün, N., McAfee, J. C., Davis, J. E., Raffield, L. M., Qian, H., Piven, J., Li, Y., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00953-9 · Cited by 95 · see citing works
Rbfox1 Mediates Cell-type-Specific Splicing in Cortical Interneurons
Wamsley, B., Jaglin, X. H., Favuzzi, E., Quattrocolo, G., Nigro, M. J., Yusuf, N., Khodadadi‐Jamayran, A., Rudy, B., & Fishell, G. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.026 · Cited by 100 · see citing works
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Zhou, Y., Shao, Y., Hu, W., Zhang, J., Shi, Y., Kong, X., & Jiang, J. (2022) · Cell Death and Differentiation · doi:10.1038/s41418-022-01049-1 · Cited by 93 · see citing works
“According to studies, the abnormal sequence and spatial structure [16–19], the abnormal expression level, and the abnormal interaction with binding proteins of lncRNAs are all associated with the occurrence of human diseases such as cancer [20], degenerative neurological diseases [21, 22], and a variety of metabolic d…”
BackgroundWang, M., Wei, P.-C., Lim, C. K., Gallina, I. S., Marshall, S., Marchetto, M. C., Alt, F. W., & Gage, F. H. (2020) · Cell Stem Cell · doi:10.1016/j.stem.2019.12.013 · Cited by 105 · see citing works
Transcriptomic Perspectives on Neocortical Structure, Development, Evolution, and Disease
Lein, E. S., Belgard, T. G., Hawrylycz, M., & Molnár, Z. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-013858 · Cited by 92 · see citing works
Self-citationDeRosa, B. A., Hokayem, J. A. E., Artimovich, E., Garcia‐Serje, C., Phillips, A. W., Booven, D. V., Nestor, J. E., Wang, L., Cuccaro, M. L., Vance, J. M., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-26495-1 · Cited by 93 · see citing works
Quartier, A., Chatrousse, L., Redin, C. E., Keime, C., Haumesser, N., Maglott, A., Brino, L., Gras, S. L., Benchoua, A., Mandel, J., et al. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.01.002 · Cited by 84 · see citing works
Eltokhi, A., Janmaat, I. E., Genedi, M., Haarman, B. C. M., & Sommer, I. E. (2020) · Journal of Neuroscience Research · doi:10.1002/jnr.24616 · Cited by 100 · see citing works
“…associated with the functioning of microglia have shown higher expression levels in brain samples from patients with ASD in comparison to controls (Parikshak et al., 2016), and gene co-expression network analysis of postmortem ASD brain tissue identified an upregulation of glial markers in the…”
ResultXia, Y., Dai, R., Wang, K., Jiao, C., Zhang, C., Xu, Y., Li, H., Jing, X., Chen, Y., Jiang, Y., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-019-0416-2 · Cited by 80 · see citing works
Shah, S., Molinaro, G., Liu, B., Wang, R., Huber, K. M., & Richter, J. D. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.02.076 · Cited by 91 · see citing works
Dysregulation of Parvalbumin Expression in the Cntnap2−/− Mouse Model of Autism Spectrum Disorder
Lauber, E., Filice, F., & Schwaller, B. (2018) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00262 · Cited by 86 · see citing works
Wong, C. C. Y., Smith, R. G., Hannon, E., Ramaswami, G., Parikshak, N. N., Assary, E., Troakes, C., Poschmann, J., Schalkwyk, L. C., Sun, W., et al. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz052 · Cited by 98 · see citing works
“These results suggest that there are convergent molecular signatures in the cortex associated with different forms of ASD, reinforcing the findings from a recent study of gene expression (11) and H3K27ac (12) undertaken in an overlapping set of samples.”
BackgroundMethodResultInfluentialSelf-citationCommon risk variants identified in autism spectrum disorder
Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R., Won, H., Pallesen, J., Agerbo, E., Andreassen, O. A., Anney, R., et al. (2017) · doi:10.1101/224774 · Cited by 89 · see citing works
Self-citationCytosolic Ca 2+ Buffers Are Inherently Ca 2+ Signal ModulatorsPreprint
Schwaller, B. (2019) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a035543 · Cited by 89 · see citing works
“RNA-seq and RT-qPCR analyses of postmortem samples of prefrontal cortex (PFC), temporal cortex, and cerebellum revealed PVALB gene transcripts to be among the most strongly down-regulated ones in the ASD group (Parikshak et al. 2016).”
BackgroundInducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia
Chandran, V., Gao, K., Swarup, V., Versano, R., Dong, H., Jordan, M. C., & Geschwind, D. H. (2017) · eLife · doi:10.7554/elife.30054 · Cited by 96 · see citing works
“WGCNA 251 permits identification of modules of highly co-expressed genes whose grouping reflects shared 252 biological functions and key functional pathways, as well as key hub genes within the modules, and has 253 been widely applied to understanding disease related transcriptomes(52, 53).”
BackgroundSelf-citationHartl, C., Ramaswami, G., Pembroke, W. G., Muller, S., Pintacuda, G., Saha, A., Parsana, P., Battle, A. J., Lage, K., & Geschwind, D. H. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00887-5 · Cited by 82 · see citing works
Self-citationMicroexons: at the nexus of nervous system development, behaviour and autism spectrum disorder
Gonatopoulos-Pournatzis, T., & Blencowe, B. J. (2020) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2020.03.007 · Cited by 77 · see citing works
Self-citationLombardo, M. V., Eyler, L. T., Moore, A., Datko, M., Barnes, C. C., Cha, D., Courchesne, E., & Pierce, K. (2019) · eLife · doi:10.7554/elife.47427 · Cited by 80 · see citing works
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Pearl, J. R., Colantuoni, C., Bergey, D. E., Funk, C. C., Shannon, P. T., Basu, B., Casella, A. M., Oshone, R. T., Hood, L., Price, N. D., et al. (2019) · Cell Systems · doi:10.1016/j.cels.2019.01.002 · Cited by 60 · see citing works
The Landscape of Circular RNA Expression in the Human Brain
Gokoolparsadh, A., Anwar, F., & Voineagu, I. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.07.029 · Cited by 78 · see citing works
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“(F) Significant enrichment of genes upregulated in postmortem ASD cortex (32).”
BackgroundInfluentialAutism spectrum disorder: pathogenesis, biomarker, and intervention therapy
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The role of long non-coding RNAs in the pathogenesis of hereditary diseases
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Deep evolutionary conservation of autism-related genes
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“Human autism gene sets of interest were derived from the Gene Scoring Module set from the September 2016 revision of the SFARI database (24) and genes identified from microarray (25) and RNA-seq (26) gene expression experiments on postmortem samples of brain tissue from autism patients.”
BackgroundMethodIdentification of Conserved Proteomic Networks in Neurodegenerative Dementia
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“Since genetic variation associated with disease is causal in this regard, we next integrated genome-wide association studies (GWAS), so as to understand each module’s relationship to potential causal mechanisms (Gandal et al., 2018a; Parikshak et al., 2016).”
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Identification of conserved proteomic networks in neurodegenerative dementia
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“Furthermore, 20 of these lncRNAs (including LINC00693 and LINC00689) have been shown to interact with miRNA–protein complexes, and nine with the fragile X mental retardation protein (FMRP), whose mRNA targets were enriched in autism risk genes [105].”
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- Authors
- Parikshak, N. N., Swarup, V., Belgard, T. G., Irimia, M., Ramaswami, G., Gandal, M. J., Hartl, C., Leppa, V., Ubieta, L. D. L. T., Huang, J., Lowe, J. K., Blencowe, B. J., Horvath, S., & Geschwind, D. H.
- Affiliations
- University of California, Los Angeles (US)
- Universitat Pompeu Fabra (ES)
- University of Toronto (CA)
- Corresponding author
- Geschwind, Daniel H.
- ORCID
- Venue
- Nature
- Published
- 2016-12-05
- Volume
- 540
- Issue
- 7633
- Pages
- 423-427
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7102905
- OpenAlex
- W2560760305
- Semantic Scholar
- 16b7fc7c9c26dd8a077bd54c3c7ae75b50e9dc8d
- Cited by
- 685
- References
- 61
- Citations by year
- 2026: 45 · 2025: 54 · 2024: 65 · 2023: 57 · 2022: 75 · 2021: 94 · 2020: 113 · 2019: 83 · 2018: 61 · 2017: 34 · 2016: 3
- FWCI
- 38.40
- Type
- journal article
- Language
- en
- Update notices
- correction (2018-07-11)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Simons Foundation
- University of Toronto
- National Institutes of Health (5r01mh094714-04, MH060233)
- Canadian Institutes of Health Research
- National Institute of Mental Health (R01-MH094714, F30MH099886, R01MH100027, 5R01 MH09714, MH100027, T32MH073526, R37MH060233)
- 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 › Cancer Research › Cancer-related molecular mechanisms research
- Keywords
- autism spectrum disorder, long non-coding RNA, alternative splicing, SOX5, frontal and temporal cortex, microglial function, synaptic function, age-related gene expression, co-expression network, molecular convergence
- MeSH terms
- Autism Spectrum Disorder, Animals, Autopsy, Chromosome Aberrations, Chromosomes, Human, Pair 15, Exons, Frontal Lobe, Gene Expression Regulation, Humans, Intellectual Disability, Neurons, Primates, Species Specificity, Temporal Lobe, Genome, Human, Case-Control Studies, Alternative Splicing, Gene Expression Profiling, SOXD Transcription Factors, Transcriptome, RNA, Long Noncoding
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.
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