The DOI matches its Crossref record; 60 of the 61 references it cites were found in a registry or an index; none of the 49 sources its claims cite is checked for support yet.
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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“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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- It may state two separate claims as one. 32
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plaincorrelationaln = 9- Asserted: passes — The authors put it forward as true.
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
boostedcorrelationaln = 9- Asserted: passes — The authors put it forward as true.
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In the paper
“Of the six modules associated with ASD, three were upregulated and three were downregulated, and each showed significant cell-type enrichment (Fig. 4a, b).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Significant upregulation in the 15q11.1–13.2 region (cis) was evident in duplication carriers, but not in idiopathic ASD (Fig. 3a).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plainn = 9- Asserted: passes — The authors put it forward as true.
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In the paper
“Remarkably, CTX.M24 was significantly enriched for lncRNAs, genes expressed highly during fetal cortical development, and genes harbouring protein-disrupting mutations found in ASD, suggesting that lncRNAs will be important targets for investigation in ASD10,25 (FDR < 0.05, Extended Data Fig. 9a, g).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [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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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“revealing strong concordance but a lower average fold change in the cerebellum.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
boostedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
What the sources say
- Not checked yetcites [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
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“ESRP2 is expressed but not significantly different between ASD and control cortex.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“PCR validation and sashimi plots for nine splicing events delineated in Extended Data Fig. 4d”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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In the paper
“Module plot and GO term enrichment for CTX.M24, which is enriched in ASD-associated rare variants and lncRNAs.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Example of a strongly conserved lncRNA, which shows robust expression in all three species.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
boosted- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“ESRP1 is not expressed in cortex”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Approximately 85% of ASD samples are classified successfully around a false positive rate of 20%.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
What the sources say
- Not checked yetcites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
- Not checked yetcites [47] Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“RT–PCR validation of the two lncRNAs shown in Fig. 1c, d; P values computed by two-sided Wilcoxon rank-sum test.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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In the paper
“The first principal component of the cortex differential splicing set is strongly associated with diagnosis, but not other factors.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
boostedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood1–3.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [1] Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46, 881–885 (2014) source
- Not checked yetcites [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 yetcites [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
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [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
boosted- Asserted: passes — The authors put it forward as true.
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [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 yetcites [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
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
boosted- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
boostedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [16] Li, Y. I. et al. RNA splicing is a primary link between genetic variation and disease. Science 352, 600–604 (2016) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
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In the paper
“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).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“Moreover, 20 of these lncRNAs have been shown to interact with microRNA (miRNA)–protein complexes, and 9 with the fragile X mental retardation protein (FMRP), whose mRNA targets are enriched in ASD risk genes9,10.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [9] Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014) source
- Not checked yetcites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [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
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In the paper
“Remarkably, CTX.M24 was significantly enriched for lncRNAs, genes expressed highly during fetal cortical development, and genes harbouring protein-disrupting mutations found in ASD, suggesting that lncRNAs will be important targets for investigation in ASD10,25 (FDR < 0.05, Extended Data Fig. 9a, g).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [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 yetcites [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
hedged- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Co-expression network analysis.
What the sources say
- Not checked yetcites [39] Langfelder, P. & Horvath, S. Eigengene networks for studying the relationships between co-expression modules. BMC Syst. Biol. 1, 54 (2007) source
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In the paper
“The sample dissections, RNA extractions, and RNA sequencing experiments were randomized (Supplementary Information).”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Brain tissue.
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In the paper
“In this regard, it is notable that the observed transcriptome changes are consistent with an ongoing process that is triggered largely by genetic and prenatal factors3,9,10,23, but that evolves during the first decade of brain development.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
What the sources say
- Not checked yetcites [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 yetcites [9] Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014) source
- Not checked yetcites [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 yetcites [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
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In the paper
“Similar to d except for the differential alternative splicing analysis.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
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In the paper
“the known positive correlation between SRRM4 and RBFOX1 and anticorrelation between PTBP1 and SRRM4 (refs 14,19)”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Extended Data
What the sources say
- Not checked yetcites [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 yetcites [19] Raj, B. et al. A global regulatory mechanism for activating an exon network required for neurogenesis. Mol. Cell 56, 90–103 (2014) source
boostedcorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Enrichment analysis of gene sets and common variation.
boosted- Asserted: passes — The authors put it forward as true.
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In the paper
“The investigators were blinded to diagnosis until the analysis but unblinded during the analysis.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Brain tissue.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > Abstract
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“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.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Quantitative real-time PCR validation.
plain- Asserted: passes — The authors put it forward as true.
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What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“No statistical methods were used to predetermine sample size.”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Brain tissue.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredIn the citing paper
“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 the citing paper
“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
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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
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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.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Co-expression network analysis.
“quartic splines”
§ Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism > METHODS > Co-expression network analysis.
“(degree = 2, span = 2/3)”
Citations
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“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).”
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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
“, 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
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
“, 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 293
“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
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 295
“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
“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
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 239
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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 221
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 200
Romero-García, R., Warrier, V., Bullmore, E. T., Baron‐Cohen, S., & Bethlehem, R. A. I. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0023-7 · Cited by 186
“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 178
“…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
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 177
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
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
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
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 194
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 188
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 171
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 163
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Fetit, 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
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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 148
“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 122
“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
“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 155
“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 122
Self-citationIdentification 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
“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-citationCNV biology in neurodevelopmental disorders
Takumi, T., & Tamada, K. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.12.004 · Cited by 121
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
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 123
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 109
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
“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
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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 120
“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 89
“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., Keogh, J. M., Patel, N. A., Strohbehn, G. W., Lo, K., Humphrey, J., Hokken‐Koelega, A. C. S., Damen, L., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.018 · Cited by 114
“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
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 113
“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 111
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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
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 97
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 101
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“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
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“…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
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Dysregulation of Parvalbumin Expression in the Cntnap2−/− Mouse Model of Autism Spectrum Disorder
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“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
Self-citationCytosolic Ca 2+ Buffers Are Inherently Ca 2+ Signal ModulatorsPreprint
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“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 103
“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 86
Self-citationTranscriptomic 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
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 79
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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 79
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“(F) Significant enrichment of genes upregulated in postmortem ASD cortex (32).”
BackgroundInfluentialAutism spectrum disorder: pathogenesis, biomarker, and intervention therapy
Zhuang, H., Liang, Z., Ma, G., Qureshi, A., Ran, X., Feng, C., Liu, X., Yan, X., & Shen, L. (2024) · MedComm · doi:10.1002/mco2.497 · Cited by 111
The role of long non-coding RNAs in the pathogenesis of hereditary diseases
Sparber, P. A., Filatova, A. Y., Khantemirova, M., & Skoblov, M. Y. (2019) · BMC Medical Genomics · doi:10.1186/s12920-019-0487-6 · Cited by 81
Deep evolutionary conservation of autism-related genes
Shpigler, H. Y., Saul, M. C., Corona, F., Block, L. N., Cash-Ahmed, A. C., Zhao, S. D., & Robinson, G. E. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1708127114 · Cited by 70
“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
Swarup, V., Chang, T. S., Duong, D. M., Dammer, E. B., Dai, J., Lah, J. J., Johnson, E. C. B., Seyfried, N. T., Levey, A. I., & Geschwind, D. H. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107807 · Cited by 78
“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).”
BackgroundSelf-citationWang, W., Corominas, R., & Lin, G. N. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00258 · Cited by 70
Identification of conserved proteomic networks in neurodegenerative dementia
Swarup, V., Chang, T. S., Duong, D. M., Dammer, E. B., Lah, J. J., Johnson, E. E. C. B., Seyfried, N. T., Levey, A. I., & Geschwind, D. H. (2019) · doi:10.1101/825802 · Cited by 78
Self-citationNie, J., Li, T.-X., Zhang, X., & Liu, J. (2019) · Non-Coding RNA · doi:10.3390/ncrna5020036 · Cited by 76
“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].”
BackgroundDear, R., Wagstyl, K., Seidlitz, J., Markello, R. D., Arnatkevičiūtė, A., Anderson, K. M., Bethlehem, R. A. I., Raznahan, A., Bullmore, E. T., & Vértes, P. E. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01624-4 · Cited by 84
Metadata
- 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
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