The DOI matches its Crossref record; 146 of the 147 references it cites were found in a registry or an index, and 1 are not checked yet; none of the 123 sources its claims cite is checked for support yet.
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Open accessAbstract
INTRODUCTION: Our understanding of the pathophysiology of psychiatric disorders, including autism spectrum disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BD), lags behind other fields of medicine. The diagnosis and study of these disorders currently depend on behavioral, symptomatic characterization. Defining genetic contributions to disease risk allows for biological, mechanistic understanding but is challenged by genetic complexity, polygenicity, and the lack of a cohesive neurobiological model to interpret findings. RATIONALE: The transcriptome represents a quantitative phenotype that provides biological context for understanding the molecular pathways disrupted in major psychiatric disorders. RNA sequencing (RNA-seq) in a large cohort of cases and controls can advance our knowledge of the biology disrupted in each disorder and provide a foundational resource for integration with genomic and genetic data. RESULTS: Analysis across multiple levels of transcriptomic organization—gene expression, local splicing, transcript isoform expression, and coexpression networks for both protein-coding and noncoding genes—provides an in-depth view of ASD, SCZ, and BD molecular pathology. More than 25% of the transcriptome exhibits differential splicing or expression in at least one disorder, including hundreds of noncoding RNAs (ncRNAs), most of which have unexplored functions but collectively exhibit patterns of selective constraint. Changes at the isoform level, as opposed to the gene level, show the largest effect sizes and genetic enrichment and the greatest disease specificity. We identified coexpression modules associated with each disorder, many with enrichment for cell type–specific markers, and several modules significantly dysregulated across all three disorders. These enabled parsing of down-regulated neuronal and synaptic components into a variety of cell type– and disease-specific signals, including multiple excitatory neuron and distinct interneuron modules with differential patterns of disease association, as well as common and rare genetic risk variant enrichment. The glial-immune signal demonstrates shared disruption of the blood-brain barrier and up-regulation of NFkB-associated genes, as well as disease-specific alterations in microglial-, astrocyte-, and interferon-response modules. A coexpression module associated with psychiatric medication exposure in SCZ and BD was enriched for activity-dependent immediate early gene pathways. To identify causal drivers, we integrated polygenic risk scores and performed a transcriptome-wide association study and summary-data–based Mendelian randomization. Candidate risk genes—5 in ASD, 11 in BD, and 64 in SCZ, including shared genes between SCZ and BD—are supported by multiple methods. These analyses begin to define a mechanistic basis for the composite activity of genetic risk variants. CONCLUSION: Integration of RNA-seq and genetic data from ASD, SCZ, and BD provides a quantitative, genome-wide resource for mechanistic insight and therapeutic development at Resource.PsychENCODE.org. These data inform the molecular pathways and cell types involved, emphasizing the importance of splicing and isoform-level gene regulatory mechanisms in defining cell type and disease specificity, and, when integrated with genome-wide association studies, permit the discovery of candidate risk genes. The PsychENCODE cross-disorder transcriptomic resource.: Human brain RNA-seq was integrated with genotypes across individuals with ASD, SCZ, BD, and controls, identifying pervasive dysregulation, including protein-coding, noncoding, splicing, and isoform-level changes. Systems-level and integrative genomic analyses prioritize previously unknown neurogenetic mechanisms and provide insight into the molecular neuropathology of these disorders.
Checked 2026-10-06 · 1 reference not checked yet
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 of 123 cited sources checked · 0 supported · 0 flagged
None of the sources cited for this claim have been checked yet.
In the 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).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked yetcites [1] Gandal MJ, Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science. 359, 693– 697 (2018). 29439242 PMC5898828 source
- Not checked yetcites [19] Parikshak NN, Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature. 540, 423– 427 (2016). 27919067 PMC7102905 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“exhibited greatest overlap with excitatory neuron clusters (OR’s> 4, Fisher’s exact test, FDR’s<10−10)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These isoform-only DE genes were more likely to be downregulated than upregulated in disease (one sample t-test, P<10−16)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“In addition, isoform-level alterations in disease exhibited substantially larger effect sizes compared with gene-level changes (mean |log2FC| 0.25 vs 0.14, P<2×10−16, K-S test), particularly for protein coding biotypes (Fig 1A), consistent with recent work demonstrating the importance of splicing dysregulation in disease pathogenesis (25).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
What the sources say
- Not checked yetcites [25] Li YI, RNA splicing is a primary link between genetic variation and disease. Science. 352, 600– 604 (2016). 27126046 PMC5182069 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and showed significant enrichment for neuron projection development, mRNA metabolism, and synaptic pathways (FDR<3×10−3; Table S1).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Altogether, over a quarter of the brain transcriptome was affected in at least one disorder (Fig 1A-C; complete gene list, Table S1).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There was significant cross-disorder correlation in PSI changes (Spearman’s ⍴=0.59 SCZ-BD, ⍴=0.52 SCZ-ASD, all P<10−4)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“As a class, NPncRNAs were under greater selective constraint compared to all Gencode annotated ncRNAs (Fig 1F), consistent with the observed increased purifying selection in brain-expressed genes (27).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
What the sources say
- Not checked yetcites [27] di Iulio J, The human noncoding genome defined by genetic diversity. Nat. Genet 50, 333– 337 (2018). 29483654 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“We also find significant enrichment of splicing changes in targets of two RNA binding proteins that regulate synaptic transmission and whose targets are implicated in both ASD and SCZ, the neuronal splicing regulator RBFOX1 (FDR=5.16×10−11) (32) and the fragile X mental retardation protein (FMRP) (FDR=3.10×10−21) (33).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
What the sources say
- Not checked yetcites [32] Lee J-A, Cytoplasmic Rbfox1 Regulates the Expression of Synaptic and Autism-Related Genes. Neuron. 89, 113– 128 (2016). 26687839 PMC4858412 source
- Not checked yetcites [33] Darnell JC, FMRP stalls ribosomal translocation on mRNAs linked to synaptic function and autism. Cell. 146, 247– 261 (2011). 21784246 PMC3232425 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“Transcript-level differential expression also showed the greatest enrichment for SCZ SNP-heritability, as measured by stratified LD score regression (21, 39) (Fig 3B).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Identifying Drivers of Transcriptome Dysregulation
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked yetcites [39] Finucane HK, Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet 47, 1228– 1235 (2015). 26414678 PMC4626285 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Not matched
- It may state two separate claims as one. 85
- Probably not a substantial claim. 25
In the paper
“In accordance with previous results (1), we observed pervasive differential gene expression (DGE) in ASD, SCZ, and BD (n=1611, 4821, and 1119 genes at FDR<0.05, respectively; Fig 1A; Table S1).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
What the sources say
- Not checked yetcites [1] Gandal MJ, Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science. 359, 693– 697 (2018). 29439242 PMC5898828 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Expanding these analyses to the transcript isoform-level, we observe widespread differential transcript expression (DTE) across ASD, SCZ, and BD (n=767, 3803, and 248 isoforms at FDR<0.05, respectively; Table S1).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“There was substantial cross-disorder sharing of this DE signal and a gradient of transcriptomic severity with the largest changes in ASD compared with SCZ or BD (ASD vs SCZ, mean |log2FC| 0.26 vs 0.10, P<2×10−16, Kolmogorov-Smirnov (K-S) test; ASD vs BD, mean |log2FC| 0.26 vs 0.15, P<2×10−16, K-S test), as observed previously (1).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
What the sources say
- Not checked yetcites [1] Gandal MJ, Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science. 359, 693– 697 (2018). 29439242 PMC5898828 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, although isoform and gene-level changes exhibited similar pathway and cell type enrichments (e.g. Fig 1D-E), isoform-level analysis identified DE transcripts that did not show DGE (‘isoform-only DE’), including 811 in SCZ, 294 in ASD, and 60 in BD.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Gene and Isoform Expression Alterations in Disease
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Based on Gencode annotations, we identify 944 ncRNAs exhibiting gene- or isoform-level DE in at least one disorder (herein referred to as ‘neuropsychiatric (NP) ncRNAs’ (21)), 693 of which were DE in SCZ, 178 in ASD, and 174 in BD, of which 208, 60, and 52 are annotated as intergenic long non-coding RNAs (lincRNAs), in each disorder, respectively.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DS genes overlapped significantly with DTE results for ASD and SCZ (Fig S8B), but not BD, which likely still remains underpowered.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and subsequently, overlap among DS genes (Fig 2A-B), although the majority of splicing changes still are disorder specific.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of 4821 DE genes in SCZ, only 143 showed even nominal association between effect size magnitude and age. Similar associations were seen in 29 of 1119 DE genes in BD and 85 of 1611 DE genes in ASD.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Identifying Drivers of Transcriptome Dysregulation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“We identified 18 genes or isoforms whose expression was significantly associated with PRS ((21); Bonferroni-corrected P < 0.05), 16 in ASD, 2 in SCZ, with none in BD (Fig 3C; Table S4).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and LINC00634, an unstudied brain enriched lincRNA downregulated in SCZ (log2FC −0.06, FDR 0.027) with a genome-wide significant SCZ TWAS association as described below.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Significant associations with PRS were observed for DGE and DTE signal in SCZ, with greater polygenic association at the isoform level in accordance with the larger transcript isoform effect sizes observed.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Identifying Drivers of Transcriptome Dysregulation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We identified 515 DS intron clusters in 472 genes across all disorders (FDR<0.1), 117 of which (25%) contained one or more novel exons (Table S3; Fig 2A).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The most commonly observed local splicing change was exon skipping (41–60%), followed by alternative 5’ exon inclusion (e.g. due to alternative promoter usage; 11–21%) and alternative 3’ splice site usage (5–18%) (Table S3; Fig S8A).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Another example is CADPS, which is located within an ASD GWAS risk locus and supported by Hi-C defined chromatin interactions as a putative target gene (38) and manifests multiple isoform and splice alterations in ASD (Fig S9; Tables S1 and S3).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
What the sources say
- Not checked yetcites [38] Grove J, Common risk variants identified in autism spectrum disorder. bioRxiv (2017), p. 224774. source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“We identify 74 NPncRNAs (~8%) under purifying selection in humans, with average exon-level context-dependent tolerance scores (CDTS) below the 10th percentile (21).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Over 200 NPncRNAs exhibited broad and non-specific expression patterns across cell types, whereas 66 were expressed within a specific cell type class (Table S2).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notable examples are: LINC00996, which is downregulated in SCZ (log2FC −0.71, FDR<5×10−11) and BD (log2FC −0.45, FDR=0.02) and restricted to microglia in brain (Fig S6)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“GRIN1 encodes the obligatory subunit of the NMDA-type glutamate ionotropic receptors, is upregulated in SCZ and BD and shows increased skipping of exon 4 in both ASD and SCZ that impacts its extracellular ligand-binding domain (Fig 2E-G).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“LINC00343, expressed in excitatory neurons, and downregulated in BD (log2FC −0.33, FDR=0.012) with a trend in SCZ (log2FC −0.15, FDR 0.065)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Differential Expression of the Non-coding Transcriptome
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Notably, 48 DS genes (10%; FDR=8.8×10−4) encode RNA binding proteins or splicing factors (34), with at least six splicing factors also showing DTE in ASD (MATR3), SCZ (QKI, RBM3, SRRM2, U2AF1) or both (SRSF11).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
What the sources say
- Not checked yetcites [34] Sebestyén E, Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks. Genome Res. 26, 732– 744 (2016). 27197215 PMC4889968 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The second most abundant RBFOX1 isoform is in another module, isoM17, which is downregulated in both ASD and SCZ (Fig 6B).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, the two modules show differential association with common genetic risk (Fig 6E), with isoM2 exhibiting GWAS enrichment across SCZ, BD, and MDD.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of the 107 conditionally significant genes prioritized by TWAS, 62 were further supported by SMR (PSMR<0.05, PHEIDI>0.05) and 11 were also concordantly DE in SCZ brain in the same direction as predicted by TWAS.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“isoM13 showed the greatest overall significance of enrichment for SCZ and educational attainment GWAS, and was also enriched in BD GWAS to a lesser degree,”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Networks Refine Shared Cross-Disorder Signals
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Most genes identified in this analysis show disease-specific effects, as only four genes (MCHR1, VPS45, SNAP91, DCLK3) showed overlap between SCZ and BD TWAS, and none overlapped with ASD.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“This includes the 17q21.31 region, which showed multiple PRS associations as described above, but did not reach genome-wide significance in the largest GWAS to date (38).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
What the sources say
- Not checked yetcites [38] Grove J, Common risk variants identified in autism spectrum disorder. bioRxiv (2017), p. 224774. source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In SCZ, TWAS identifies 193 genes of which 107 remain significant following conditional analysis at each gene within multi-hit loci.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The module pair geneM1/isoM2, downregulated only in ASD (Fig 6B), contains the predominant brain-expressed RBFOX1 isoform and includes several cation channels (e.g., HCN1, SCN8A).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Concordantly, we find a strong positive correlation between C4A expression and genetically imputed C4A copy number (R=0.36, P=6×10−21) and imputed number of C4-HERV elements (R=0.35, P=4×10−20), but a slight negative association with C4B copy number (R=−0.087, P=0.03; ref (21)).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Five modules are shared across all three disorders, 3 up and two downregulated; 22 modules are shared by 2 of the 3 disorders, and 36 demonstrate more specific patterns of dysregulation in either ASD, SCZ or BD (Fig 5; Table S5).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Networks Refine Shared Cross-Disorder Signals
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The third biological process, geneM26/isoM22 (Fig 5C), is downregulated, and enriched for endothelial and pericyte genes, with hubs that represent markers of the blood-brain barrier, including ITIH5, SLC38A5, ABCB1, and GPR124, a critical regulator of brain-specific angiogenesis (53, 54).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Networks Refine Shared Cross-Disorder Signals
What the sources say
- Not checked yetcites [53] Daneman R, The mouse blood-brain barrier transcriptome: a new resource for understanding the development and function of brain endothelial cells. PLoS One. 5, e13741 (2010). 21060791 PMC2966423 source
- Not checked yetcites [54] Obermeier B, Daneman R, Ransohoff RM, Development, maintenance and disruption of the blood-brain barrier. Nat. Med 19, 1584– 1596 (2013). 24309662 PMC4080800 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We do observe neuronal modules broadly dysregulated across multiple disorders, including a neuronal/synaptic module (isoM18) with multiple isoforms of the known ASD risk gene, ANK2, as hubs.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Consistent with expectations, modules showed enrichment for gene ontology pathways and we identified modules strongly and selectively enriched for markers of all major CNS cell types (Fig 5A-B; Fig S12)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Networks Refine Shared Cross-Disorder Signals
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Altogether, 64 genes were consistently prioritized across multiple methods, including 10 ncRNAs (Table S4; (21)).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the isoform-level networks captured greater detail and a larger proportion were associated with disease GWAS than gene-level networks (61% vs 41% with nominal GWAS enrichment, P=0.07, χ2; Fig 5A).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Networks Refine Shared Cross-Disorder Signals
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Of the seven TWAS-significant genes at this locus, conditional analysis prioritizes one – LRRC37A, which is further supported by SMR and Hi-C interaction in fetal brain (38).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
What the sources say
- Not checked yetcites [38] Grove J, Common risk variants identified in autism spectrum disorder. bioRxiv (2017), p. 224774. source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A previous TWAS study in SCZ primarily based on non-neural tissue prioritized 157 genes, 37 of which are identified here, a significant overlap (OR 61, p<10−42, Fisher’s exact test).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These included a number of intriguing novel candidates for SCZ: two downregulated lysine methyltransferayjec9vses (SETD6, SETD8); RERE, a downregulated, mutationally intolerant nuclear receptor co-regulator of retinoic acid signaling associated with a rare neurodevelopmental genetic syndrome; LINC00634, a downregulated poorly annotated brain-enriched lincRNA; and SLC12A5, encoding a mitochondrial”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A notable example is geneM2/isoM13, which is enriched for oligodendrocyte markers and neuron projection developmental pathways and is downregulated in ASD and SCZ, with a trend in BD (Fig 5C).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Networks Refine Shared Cross-Disorder Signals
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Here, we find that isoM17 shows greater enrichment for nuclear RBFOX1 targets (Fig 6C), whereas isoM2 shows stronger overlap with cytoplasmic targets (32).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [32] Lee J-A, Cytoplasmic Rbfox1 Regulates the Expression of Synaptic and Autism-Related Genes. Neuron. 89, 113– 128 (2016). 26687839 PMC4858412 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In BD, TWAS prioritizes 17 genes across 14 distinct loci (Bonferroni-corrected P<0.05; Fig 4; Table S4), none of which exhibited DE.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“The interferon response module (geneM32) contains critical components of the IFN-stimulated gene factor 3 (ISGF3) complex”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
What the sources say
- Not checked yetcites [71] Rusinova I, Interferome v2.0: an updated database of annotated interferon-regulated genes. Nucleic Acids Res. 41, D1040– 6 (2013). 23203888 PMC3531205 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“all preserved in the signed networks with strong cell type and GWAS enrichments”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“This module pair contained as hubs the two major GABA synthesizing enzymes (GAD1, GAD2), multiple GABA transporters (SLC6A1, SLC24A3), many other known interneuron markers (RELN, VIP), as well as DLX1 and the lncRNA DLX6-AS1, both critical known regulators of inhibitory neuron development (62).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [62] Bond AM, Balanced gene regulation by an embryonic brain ncRNA is critical for adult hippocampal GABA circuitry. Nat. Neurosci 12, 1020– 1027 (2009). 19620975 PMC3203213 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Indeed, geneM21/isoM30 was associated with genes downregulated by chronic high-doses (but not low-doses) of haloperidol, as well as genes upregulated by the antidepressant fluoxetine (Fig S11A).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — 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 pattern is clearly distinct from ASD, which shows a dynamic trajectory, but remains upregulated throughout (Fig 7F).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We provide a table of putative mRNA targets for these brain expressed lncRNAs, including 209 exhibiting DE in ASD, 122 in BD and 241 in SCZ (Table S6).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“including geneM7, enriched for synaptic and metabolic processes with the splicing regulator NOVA2 (Fig 5C).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The increased resolution here allowed us to identify several modules enriched in inhibitory interneuron markers (Fig 5B), including geneM23/isoM19, which is downregulated in ASD and SCZ, with a trend toward downregulation observed in BD;”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Several neuronal modules that distinguish between the disorders differentiate BD and SCZ from ASD, including the module pair geneM21/isoM30 (Fig 5C), which captures known elements of activity-dependent neuronal gene regulation, whose hubs include classic early-response (ARC, EGR1, NPAS4, NR4A1) and late-response genes (BDNF, HOMER1) (40).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [40] West AE, Greenberg ME, Neuronal activity-regulated gene transcription in synapse development and cognitive function. Cold Spring Harb. Perspect. Biol 3 (2011), doi: 10.1101/cshperspect.a005744. PMC3098681 21555405 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A large proportion of disease-associated co-expression modules are enriched for cell type specific markers, as is overall disease DE signal”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These switch isoforms show markedly different expression patterns, belonging to different co-expression modules, geneM3/isoM1 (Fig 7C) and isoM18”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“are down and upregulated in ASD and SCZ, respectively (Fig S17).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“are up and downregulated in ASD and SCZ, respectively (Fig S17).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“present both in the cell nucleus and cytoplasm (Fig 8A; Fig S16)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Genes with switch isoforms are also enriched for the regulatory targets of two ASD risk genes, CHD8 and FMRP, as well as highly mutationally constrained genes (pLI>0.99), syndromic ASD genes, and in genes with de novo exonic mutations in ASD, SCZ and BD (Fig 8F; Table S7; (21)).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“whereas LINC01166 is significantly downregulated in BD (log2FC −0.17, FDR<0.05) with trends in ASD and SCZ (FDR’s < 0.1).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“which are enriched in astrocyte and neuronal cell types, respectively (Fig 5A; Fig S12).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“most of these ncRNAs show significant CNS enrichment, but until now, have limited functional annotation.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A module enriched for microglial-associated genes, for example, shows a clear distinction between disorders, with strong upregulation observed on ASD and significant downregulation in SCZ and BD.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Such regulatory relationships show substantial heterogeneity across human cell types, tissues, and developmental stages (10), and are often highly species-specific (11).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Introduction
What the sources say
- Not checked yetcites [10] GTEx Consortium, Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 348, 648– 660 (2015). 25954001 PMC4547484 source
- Not checked yetcites [11] Reilly SK, Evolutionary genomics. Evolutionary changes in promoter and enhancer activity during human corticogenesis. Science. 347, 1155– 1159 (2015). 25745175 PMC4426903 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the 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).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Introduction
What the sources say
- Not checked yetcites [2] Fromer M, Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci 19, 1442– 1453 (2016). 27668389 PMC5083142 source
- Not checked yetcites [19] Parikshak NN, Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature. 540, 423– 427 (2016). 27919067 PMC7102905 source
- Not checked yetcites [20] Kang HJ, Spatio-temporal transcriptome of the human brain. Nature. 478, 483– 489 (2011). 22031440 PMC3566780 source
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Studies have identified hundreds of causal genetic variants robustly associated with these disorders, and thousands more that likely contribute to their pathogenesis (4).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Introduction
What the sources say
- Not checked yetcites [4] Gandal MJ, Leppa V, Won H, Parikshak NN, Geschwind DH, The road to precision psychiatry: translating genetics into disease mechanisms. Nat. Neurosci 19, 1397– 1407 (2016). 27786179 PMC9012265 source
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Extensive quality control steps were taken within and across individual studies resulting in the detection of 16,541 protein-coding and 9,233 non-coding genes with the Gencode v19 annotations ((21); Fig S3).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Introduction
What the sources say
- Not matchedcites [21] See supplemental methods.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedn = 2,188Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim have been checked yet.
In the 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).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
What the sources say
- Not checked yetcites [19] Parikshak NN, Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature. 540, 423– 427 (2016). 27919067 PMC7102905 source
- Not checked yetcites [30] Irimia M, A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell. 159, 1511– 1523 (2014). 25525873 PMC4390143 source
- Not checked yetcites [2] Fromer M, Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci 19, 1442– 1453 (2016). 27668389 PMC5083142 source
- Not checked yetcites [24] Jaffe AE, Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis. Nat. Neurosci 21, 1117– 1125 (2018). 30050107 PMC6438700 source
- Not checked yetcites [31] Akula N, RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder. Mol. Psychiatry 19, 1179– 1185 (2014). 24393808 PMC5560442 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“We used surrogate variable correction in our analyses to account for such unmeasured confounders (43), which is a standard approach (44).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Identifying Drivers of Transcriptome Dysregulation
What the sources say
- Not checked yetcites [43] Leek JT, Storey JD, Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet. 3, 1724– 1735 (2007). 17907809 PMC1994707 source
- Not checked yetcites [44] GTEx Consortium, Genetic effects on gene expression across human tissues. Nature. 550, 204 (2017). 29022597 PMC5776756 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
“Notably, DS exhibited greatest overlap with the ncRNA signal, suggesting a role for non-coding genes in regulating local splicing events.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Identifying Drivers of Transcriptome Dysregulation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“We used LeafCutter (29) to assess local differential splicing (DS) differences in ASD, SCZ and BD using de novo aligned RNA-seq reads, controlling for the same covariates as DGE/DTE (Fig S7).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Local Splicing Dysregulation in Disease
What the sources say
- Not checked yetcites [29] Li YI, Annotation-free quantification of RNA splicing using LeafCutter. Nat. Genet 50, 151– 158 (2018). 29229983 PMC5742080 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Experiments in mouse indicate that RBFOX1 has distinct nuclear and cytoplasmic isoforms with differing functions, the nuclear isoform primarily regulating pre-mRNA alternative splicing, and the cytoplasmic isoform binding to the 3’ UTR to stabilize target transcripts involved in regulation of neuronal excitability (28, 32, 58, 60).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [28] Vuong CK, Black DL, Zheng S, The neurogenetics of alternative splicing. Nat. Rev. Neurosci 17, 265– 281 (2016). 27094079 PMC4861142 source
- Not checked yetcites [32] Lee J-A, Cytoplasmic Rbfox1 Regulates the Expression of Synaptic and Autism-Related Genes. Neuron. 89, 113– 128 (2016). 26687839 PMC4858412 source
- Not checked yetcites [58] Vuong CK, Rbfox1 Regulates Synaptic Transmission through the Inhibitory Neuron-Specific vSNARE Vamp1. Neuron. 98, 127– 141.e7 (2018). 29621484 PMC5890944 source
- Not checked yetcites [60] Gehman LT, The splicing regulator Rbfox1 (A2BP1) controls neuronal excitation in the mammalian brain. Nat. Genet 43, 706– 711 (2011). 21623373 PMC3125461 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“However, expression of all three was also significantly (P<0.05) correlated with imputed C4A copy number, suggesting pleiotropic effects.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt 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
“The two isoforms with PRS associations in BD (NCALD, SNF8) were non-significant in TWAS, perhaps due to lack of a nearby genome-wide significant locus or isoform-specific regulation, suggesting those expression changes may be driven by trans-acting factors.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
“However, the large sample size, coupled with the specificity of isoform-level qualifications, enabled us to identify synaptic modules containing unique isoforms with distinct disease associations and to separate signals from excitatory and inhibitory neurons (Fig 5B).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“Overall, this analysis provides a core set of strong candidate genes implicated by risk loci, and provides a mechanistic basis for the composite activity of disease risk variants.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Transcriptome-wide Association
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Previous work has identified downregulated neuronal modules in ASD and SCZ containing RBFOX1 as a hub (1, 16).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [1] Gandal MJ, Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science. 359, 693– 697 (2018). 29439242 PMC5898828 source
- Not checked yetcites [16] Voineagu I, Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature. 474, 380– 384 (2011). 21614001 PMC3607626 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Previous work has identified differential activation of glial and neural-immune processes in brain from patients with psychiatric disorders (16, 52, 57, 66–69)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
What the sources say
- Not checked yetcites [16] Voineagu I, Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature. 474, 380– 384 (2011). 21614001 PMC3607626 source
- Not checked yetcites [52] Chen C, Two gene co-expression modules differentiate psychotics and controls. Mol. Psychiatry 18, 1308– 1314 (2013). 23147385 PMC4018461 source
- Not checked yetcites [57] Ramaker RC, Post-mortem molecular profiling of three psychiatric disorders. Genome Med. 9, 72 (2017). 28754123 PMC5534072 source
- Not checked yetcites [66] Birnbaum R, Investigating the neuroimmunogenic architecture of schizophrenia. Mol. Psychiatry 23, 1251– 1260 (2018). 28485405 source
- Not checked yetcites [67] Fillman SG, Increased inflammatory markers identified in the dorsolateral prefrontal cortex of individuals with schizophrenia. Mol. Psychiatry 18, 206– 214 (2013). 22869038 source
- Not checked yetcites [68] Pacifico R, Davis RL, Transcriptome sequencing implicates dorsal striatum-specific gene network, immune response and energy metabolism pathways in bipolar disorder. Mol. Psychiatry 22, 441– 449 (2017). 27350034 source
- Not checked yetcites [69] Rao JS, Harry GJ, Rapoport SI, Kim HW, Increased excitotoxicity and neuroinflammatory markers in postmortem frontal cortex from bipolar disorder patients. Mol. Psychiatry 15, 384– 392 (2010). 19488045 PMC2844920 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“Although these modules were not significantly downregulated in ASD, subsampling indicates that the differences between disorders could be driven by sample size (Fig S14).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“the lncRNA DLX6-AS1, a known development regulator of interneuron specification (62)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
What the sources say
- Not checked yetcites [62] Bond AM, Balanced gene regulation by an embryonic brain ncRNA is critical for adult hippocampal GABA circuitry. Nat. Neurosci 12, 1020– 1027 (2009). 19620975 PMC3203213 source
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“and both microglia and astrocytes in ASD (19, 70).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
What the sources say
- Not checked yetcites [19] Parikshak NN, Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature. 540, 423– 427 (2016). 27919067 PMC7102905 source
- Not checked yetcites [70] Gupta S, Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun 5, 5748 (2014). 25494366 PMC4270294 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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
“Two additional immune-related modules appear to represent more broadly expressed signaling pathways: interferon response (geneM32) and NFkB (geneM5/isoM5).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Remarkably, a nearly identical module was recently identified as a sex-specific transcriptional signature of major depression and stress susceptibility (64).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [64] Labonté B, Sex-specific transcriptional signatures in human depression. Nat. Med 23, 1102– 1111 (2017). 28825715 PMC5734943 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“As a subset of lncRNAs are thought to function by repressing mRNA targets (72)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
What the sources say
- Not checked yetcites [72] Necsulea A, The evolution of lncRNA repertoires and expression patterns in tetrapods. Nature. 505, 635– 640 (2014). 24463510 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“maximally diverges from controls during early adulthood, coincident with typical disease onset in SCZ and BD (~25).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Cross-sectional post-mortem expression trajectories across age reflect disease progression and timing relative to clinical onset.
None of the sources cited for this claim have been checked yet.
In the paper
“including upregulation of astrocytes in SCZ and BD (1, 57)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
What the sources say
- Not checked yetcites [1] Gandal MJ, Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science. 359, 693– 697 (2018). 29439242 PMC5898828 source
- Not checked yetcites [57] Ramaker RC, Post-mortem molecular profiling of three psychiatric disorders. Genome Med. 9, 72 (2017). 28754123 PMC5534072 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“the top GWAS-supported, and strongly upregulated, risk gene for SCZ (5).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
What the sources say
- Not checked yetcites [5] Sekar A, Schizophrenia risk from complex variation of complement component 4. Nature. 530, 177– 183 (2016). 26814963 PMC4752392 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“LINC00473 is regulated by synaptic activity and downregulates immediate early gene expression (74)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
What the sources say
- Not checked yetcites [74] Pruunsild P, Bengtson CP, Bading H, Networks of Cultured iPSC-Derived Neurons Reveal the Human Synaptic Activity-Regulated Adaptive Gene Program. Cell Rep. 18, 122– 135 (2017). 28052243 PMC5236011 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt 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
“peaking during early development, coincident with clinical onset.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Cross-sectional post-mortem expression trajectories across age reflect disease progression and timing relative to clinical onset.
In the paper
“Evidence supports hyperactive complement-mediated synaptic pruning in SCZ pathophysiology, presumably through microglia (5)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Distinct Trajectories of Neural-Immune Dysregulation
What the sources say
- Not checked yetcites [5] Sekar A, Schizophrenia risk from complex variation of complement component 4. Nature. 530, 177– 183 (2016). 26814963 PMC4752392 source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“These genes play critical roles in regulating synaptic plasticity and the balance of excitatory and inhibitory synapses (40).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Neuronal Isoform Networks Capture Disease Specificity
What the sources say
- Not checked yetcites [40] West AE, Greenberg ME, Neuronal activity-regulated gene transcription in synapse development and cognitive function. Cold Spring Harb. Perspect. Biol 3 (2011), doi: 10.1101/cshperspect.a005744. PMC3098681 21555405 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“NIPBL, a gene associated with Cornelia de Lange Syndrome (80)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
What the sources say
- Not checked yetcites [80] Krantz ID, Cornelia de Lange syndrome is caused by mutations in NIPBL, the human homolog of Drosophila melanogaster Nipped-B. Nat. Genet 36, 631– 635 (2004). 15146186 PMC4902017 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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
“These data confirm the importance of microexon regulation in neuropsychiatric disorders beyond ASD, and their potential role in distinguishing among biological pathways differentially affected across conditions.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“alternative splicing patterns are more distinct than in other organ systems (82).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
What the sources say
- Not checked yetcites [82] Melé M, Human genomics. The human transcriptome across tissues and individuals. Science. 348, 660– 665 (2015). 25954002 PMC4547472 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“At each step of analysis, we have attempted to mitigate the contribution of these factors through known and hidden covariate correction, assessment of age trajectories, and via enrichment for causal genetic variation.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“several studies have demonstrated that genes carrying microexons are preferentially expressed in brain and their splicing is dysregulated in ASD (30, 82, 83).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
What the sources say
- Not checked yetcites [30] Irimia M, A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell. 159, 1511– 1523 (2014). 25525873 PMC4390143 source
- Not checked yetcites [82] Melé M, Human genomics. The human transcriptome across tissues and individuals. Science. 348, 660– 665 (2015). 25954002 PMC4547472 source
- Not checked yetcites [83] Quesnel-Vallières M, Misregulation of an Activity-Dependent Splicing Network as a Common Mechanism Underlying Autism Spectrum Disorders. Mol. Cell 64, 1023– 1034 (2016). 27984743 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“SOX2-OT is a heavily spliced, evolutionarily-conserved lncRNA exhibiting predominant brain expression and a hub of these oligodendrocyte modules, without previous mechanistic links to myelination (75, 76).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
What the sources say
- Not checked yetcites [75] Amaral PP, Complex architecture and regulated expression of the Sox2ot locus during vertebrate development. RNA. 15, 2013– 2027 (2009). 19767420 PMC2764477 source
- Not checked yetcites [76] Mercer TR, Dinger ME, Sunkin SM, Mehler MF, Mattick JS, Specific expression of long noncoding RNAs in the mouse brain. Proc. Natl. Acad. Sci. U. S. A 105, 716– 721 (2008). 18184812 PMC2206602 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“This likely varies by transcript class, and some of the modest correlations are likely due to low abundance genes, such as ncRNAs”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
“Several broad shared patterns of gene expression dysregulation have been observed in post mortem brain in previous studies, most prominently, a gradient of downregulation of neuronal and synaptic signaling genes, and upregulation of glial-immune or neuroinflammatory signals.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“SMARCA2, a member of the BAF-complex strongly implicated in several neurodevelopmental disorders including ASD (79)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
What the sources say
- Not checked yetcites [79] Koga M, Involvement of SMARCA2/BRM in the SWI/SNF chromatin-remodeling complex in schizophrenia. Hum. Mol. Genet 18, 2483– 2494 (2009). 19363039 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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
“by performing a well-powered brain-relevant TWAS in SCZ, and to a lesser extent in BD and ASD”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Discussion
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“the ASD risk gene ANK2 (81)”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
What the sources say
- Not checked yetcites [81] Sanders SJ, Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci. Neuron. 87, 1215– 1233 (2015). 26402605 PMC4624267 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“an established regulator of oligodendrocyte-gene splicing also located in this module (77, 78).”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
What the sources say
- Not checked yetcites [77] Aberg K, Saetre P, Jareborg N, Jazin E, Human QKI, a potential regulator of mRNA expression of human oligodendrocyte-related genes involved in schizophrenia. Proc. Natl. Acad. Sci. U. S. A 103, 7482– 7487 (2006). 16641098 PMC1464365 source
- Not checked yetcites [78] Barry G, The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing. Mol. Psychiatry 19, 486– 494 (2014). 23628989 source
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“These analyses predict critical roles for these or these often overlooked non-coding genes in oligodendrocyte function (77, 78) and potentially in psychiatric conditions.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Non-coding Modules and lncRNA Regulatory Relationships
What the sources say
- Not checked yetcites [77] Aberg K, Saetre P, Jareborg N, Jazin E, Human QKI, a potential regulator of mRNA expression of human oligodendrocyte-related genes involved in schizophrenia. Proc. Natl. Acad. Sci. U. S. A 103, 7482– 7487 (2006). 16641098 PMC1464365 source
- Not checked yetcites [78] Barry G, The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing. Mol. Psychiatry 19, 486– 494 (2014). 23628989 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“likely cell type specific interactions that suggest distinct functions of the isoforms of this gene in different neural cell types and diseases.”
§ Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder > Isoform Network Specificity and Switching
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
Post-mortem brain transcriptomes from these cohorts are a valid proxy for the molecular pathology of ASD, SCZ, and BD.
“We present results of the analysis of RNA-sequencing (RNA-Seq) data from the PsychENCODE Consortium (17), integrating genetic and genomic data from over 2000 well-curated, high-quality post-mortem brain samples from individuals with SCZ, BD, ASD, and controls (18).”
The paper relies on this without support.
The cell-type marker sets used for enrichment and deconvolution accurately identify the corresponding brain cell types.
“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).”
The paper relies on this without support.
Cross-sectional post-mortem expression trajectories across age reflect disease progression and timing relative to clinical onset.
“peaking during early development, coincident with clinical onset.”
“maximally diverges from controls during early adulthood, coincident with typical disease onset in SCZ and BD (~25).”
The paper relies on this without support.
Negative correlation between an lncRNA and an mRNA within a co-expression module indicates a regulatory repression relationship.
“As a subset of lncRNAs are thought to function by repressing mRNA targets (72), we applied csuWGCNA (73) to identify potential regulatory relationships (21).”
“which captured 7186 negatively correlated lncRNA-mRNA pairs within the same module (Fig S15).”
The paper relies on this without support.
Enrichment of a co-expression module for GWAS signals supports a causal role for that module in disease.
“This neuronal module was significantly enriched for both BD and SCZ GWAS signals, supporting a causal role for this module.”
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
“that includes enhancers controlling gene expression in the central nervous system (Fazel Darbandi, et al. 2016) and sequences associated with either hyper- or hypo-socialization/vocalization pathologies such as Williams-Buren syndrome (Poitras, et al. 2010) or ASDs (Gandal, et al. 2018).”
From DLX5/6 GABAergic Expression Affects Social Vocalization: Implications for Human Evolution (2021) · cites this paper as Gandal, et al. 2018
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, recent evidence from genome-wide association studies (GWAS) and other follow-up analyses has suggested that a proportion of the genetic risk of neurological and psychiatric diseases acts through myeloid cells22–25.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [25]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“the modules including these DLX genes and other key genetic components of GABAergic neurons constitute the major hub for both ASD and schizophrenia (Gandal, et al. 2018).”
From DLX5/6 GABAergic Expression Affects Social Vocalization: Implications for Human Evolution (2021) · cites this paper as Gandal, et al. 2018
In the citing paper
“TWAS identified 708 SCZ-associated genes (TWAS SCZ genes) whose imputed expression values are correlated with SCZ (FDR<0.05).”
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 [40]
In the citing paper
“Differentially expressed genes (DEG) in postmortem brains with psychiatric disorders were obtained from Gandal et al., 201840 (FDR<0.05).”
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 [40]
In the citing paper
“Using these data, we identified noncoding regions of transcription and sets of differentially expressed and coexpressed genes (21, 22).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [22]
In the citing paper
“Broadly, we take an unbiased view of all 5024 modules and higher-order groupings constructed from these and then prioritize a subset of ~180 modules and groupings for each psychiatric disorder, showing these to be enriched in specific functional categories and to intersect substantially with the modules from more disease-focused analyses (Fig. 8, B and C, and fig. S49) (22).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [22]
In the citing paper
“For SCZ, which is the best characterized of the three disorders, we find enrichments for pathways and genes known to be associated with the disease, including glutamatergic-synapse pathway genes, such as GRIN1; calcium-signaling pathway and astrocyte-marker genes; and complement cascade pathway genes such as C4A, C4B, and CLU (Fig. 8D) (22).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [22]
In the citing paper
“In particular, we found that cross-disorder prioritized modules are associated with functional categories such as “immune processes,” “synaptic activity,” and “splicing,” consistent with the findings from more disease-focused analyses (Fig. 8C) (22).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [22]
In the citing paper
“Other prioritized modules include well-characterized genes such as MIAT, RBFOX1, and ANK2 (SCZ); RELA, NFkB2, and NIPBL (ASD); and HOMER1 (BPD), consistent with the results of (22).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [22]
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 Gandal et al., 2018
In the citing paper
“Recent studies have highlighted the importance of aberrant alternative splicing of mRNA in the brains of subjects with an ASD diagnosis (Corominas et al., 2014; Gandal et al., 2018; Irimia et al., 2014; 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 Gandal et al., 2018
In the citing paper
“In contrast to AD in which multiple glial cells are implicated, previous work has indicated neurons as the central cell-type harboring genetic risk for the majority of psychiatric disorders3,22,46,58–61.”
From Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders (2021) · cites this paper as [59]
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.
Disease-associated module categories total 63, not 61
MinorThe stated categories contain 5, 22, and 36 modules, which sum to 63 rather than the reported 61 disease-associated modules.
Reported 61 · recomputed 63
“Of a combined 90 modules, including 34 gene- (geneM) and 56 isoform-level (isoM) modules, 61 (68%) showed significant association with at least one disorder, demonstrating the pervasive nature of transcriptome dysregulation in psychiatric disease. Five modules are shared across all three disorders, 3 up and two downregulated; 22 modules are shared by 2 of the 3 disorders, and 36 demonstrate more specific patterns”
Eight reported BD genes are followed by eleven names
MinorThe text says eight genes showed consistent association, but the accompanying list names eleven.
“Eight genes showed consistent association (21) across multiple analyses”
“BMPR1B, DCLK3, HAPLN4, HLF, LMAN2L, MCHR1, UBE2Q2L, SNAP91, TTC39A, TMEM258, and VPS45”
Citations
Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citationPrimer3—new capabilities and interfaces
Untergasser, A., Cutcutache, I., Kõressaar, T., Ye, J., Faircloth, B., Remm, M., & Rozen, S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks596 · Cited by 9,165
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
Self-citationSzklarczyk, D., Morris, J. H., Cook, H., Kuhn, M., Wyder, S., Simonovic, M., Santos, A., Doncheva, N. T., Roth, A., Bork, P., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw937 · Cited by 6,980
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
Self-citationThe Pfam protein families database: towards a more sustainable future
Finn, R. D., Coggill, P., Eberhardt, R. Y., Eddy, S. R., Mistry, J., Mitchell, A. L., Potter, S. C., Punta, M., Qureshi, M., Sangrador-Vegas, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1344 · Cited by 5,975
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease
Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., David, E., Baruch, K., Lara-Astaiso, D., Toth, B., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.018 · Cited by 5,493
The ENCODE Project Consortium (2007) · Nature · doi:10.1038/nature05874 · Cited by 5,223
Self-citationThe Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
Siepel, A., Bejerano, G., Pedersen, J. S., Hinrichs, A. S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L. W., Richards, S., et al. (2005) · Genome Research · doi:10.1101/gr.3715005 · Cited by 3,971 · cited 1×
“DE ncRNAs were further annotated for tissue-specificity using GTEx v6 data (10, 82), evolutionary conservation using phyloP and phastCons scores (92, 93), and exonlevel selective constraint via CDTS (27).”
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352
Human Protein Reference Database--2009 update
Prasad, T. S. K., Goel, R., Kandasamy, K., Keerthikumar, S., Kumar, S., Mathivanan, S., Telikicherla, D., Raju, R., Shafreen, R. B., Venugopal, A., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn892 · Cited by 3,252
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124
Integrating common and rare genetic variation in diverse human populations
The International HapMap 3 Consortium (2010) · Nature · doi:10.1038/nature09298 · Cited by 3,026
eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0090-3 · Cited by 3,005
Self-citationPartitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604
Self-citationAn atlas of active enhancers across human cell types and tissues
The FANTOM Consortium, Andersson, R., Gebhard, C., Miguel-Escalada, I., Hoof, I., Bornholdt, J., Boyd, M., Chen, Y., Zhao, X., Schmidl, C., et al. (2014) · Nature · doi:10.1038/nature12787 · Cited by 2,550
Long Noncoding RNAs: Cellular Address Codes in Development and Disease
Batista, P. J., & Chang, H. Y. (2013) · Cell · doi:10.1016/j.cell.2013.02.012 · Cited by 2,531
Integrative approaches for large-scale transcriptome-wide association studies
Gusev, A., Ko, A., Shi, H., Bhatia, G., Chung, W., Penninx, B. W. J. H., Jansen, R., de Geus, E. J. C., Boomsma, D. I., Wright, F. A., et al. (2016) · Nature Genetics · doi:10.1038/ng.3506 · Cited by 2,479
Self-citationDevelopment, maintenance and disruption of the blood-brain barrier
Obermeier, B., Daneman, R., & Ransohoff, R. M. (2013) · Nature Medicine · doi:10.1038/nm.3407 · Cited by 2,452
Schizophrenia risk from complex variation of complement component 4
Sekar, A., Bialas, A. R., de Rivera, H., Davis, A., Hammond, T. R., Kamitaki, N., Tooley, K., Presumey, J., Baum, M., Van Doren, V., et al. (2016) · Nature · doi:10.1038/nature16549 · Cited by 2,394
Detection of nonneutral substitution rates on mammalian phylogenies
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R., & Siepel, A. (2010) · Genome Research · doi:10.1101/gr.097857.109 · Cited by 2,353
Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.013 · Cited by 2,295
Insights into RNA Biology from an Atlas of Mammalian mRNA-Binding Proteins
Castello, A., Fischer, B., Eichelbaum, K., Horos, R., Beckmann, B. M., Strein, C., Davey, N. E., Humphreys, D. T., Preiss, T., Steinmetz, L. M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.031 · Cited by 2,132
Spatio-temporal transcriptome of the human brain
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., et al. (2011) · Nature · doi:10.1038/nature10523 · Cited by 2,084
Self-citationFMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism
Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., et al. (2011) · Cell · doi:10.1016/j.cell.2011.06.013 · Cited by 2,072
Self-citationCapturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis
Leek, J. T., & Storey, J. D. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030161 · Cited by 1,930
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912
Self-citationTranscriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
Voineagu, I., Wang, X., Johnston, P., Lowe, J. K., Tian, Y., Horvath, S., Mill, J., Cantor, R. M., Blencowe, B. J., & Geschwind, D. H. (2011) · Nature · doi:10.1038/nature10110 · Cited by 1,874 · cited 3×
“Multiple neuronal and synaptic signaling pathways have been previously shown to be downregulated in a diminishing gradient across ASD, SCZ, and BD brains without identification of clear disease-specific signals for these neuronalsynaptic gene sets (13, 15, 18, 19, 56, 57).”
Self-citation20 years of the SMART protein domain annotation resource
Letunic, I., & Bork, P. (2017) · Nucleic Acids Res. · doi:10.1093/nar/gkx922 · Cited by 1,810
A gene-based association method for mapping traits using reference transcriptome data
Gamazon, E. R., Wheeler, H. E., Shah, K. P., Mozaffari, S. V., Aquino-Michaels, K., Carroll, R. J., Eyler, A. E., Denny, J. C., Nicolae, D. L., Cox, N. J., et al. (2015) · Nature Genetics · doi:10.1038/ng.3367 · Cited by 1,790
GERAD1 Consortium, Pardiñas, A. F., CRESTAR Consortium, Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., Legge, S. E., Bishop, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0059-2 · Cited by 1,552
Self-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
Self-citationThe BioPlex network: a systematic exploration of the human interactome
Huttlin, E. L., Ting, L., Bruckner, R. J., Gebreab, F., Gygi, M. P., Szpyt, J., Tam, S., Zarraga, G., Colby, G., Baltier, K., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.043 · Cited by 1,425
A survey of human brain transcriptome diversity at the single cell level
Darmanis, S., Sloan, S. A., Zhang, Y., Enge, M., Caneda, C., Shuer, L. M., Hayden Gephart, M. G., Barres, B. A., & Quake, S. R. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1507125112 · Cited by 1,401
Psychiatric GWAS Consortium Bipolar Disorder Working Group, Sklar, P., Ripke, S., Scott, L. J., Andreassen, O. A., Cichon, S., Craddock, N., Edenberg, H. J., Nurnberger, J. I., Rietschel, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.943 · Cited by 1,344
Self-citationThe human transcriptome across tissues and individuals
Melé, M., Ferreira, P. G., Reverter, F., DeLuca, D. S., Monlong, J., Sammeth, M., Young, T. R., Goldmann, J. M., Pervouchine, D. D., Sullivan, T. J., et al. (2015) · Science · doi:10.1126/science.aaa0355 · Cited by 1,304
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Vilhjálmsson, B. J., Yang, J., Finucane, H. K., Gusev, A., Lindström, S., Ripke, S., Genovese, G., Loh, P.-R., Bhatia, G., Do, R., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.09.001 · Cited by 1,303
Self-citationCORUM: the comprehensive resource of mammalian protein complexes—2009
Ruepp, A., Wägele, B., Lechner, M., Brauner, B., Dunger-Kaltenbach, I., Fobo, G., Frishman, G., Montrone, C., & Mewes, H. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp914 · Cited by 1,299
Genome-wide association study identifies 74 loci associated with educational attainment
Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., et al. (2016) · Nature · doi:10.1038/nature17671 · Cited by 1,297
The mRNA-Bound Proteome and Its Global Occupancy Profile on Protein-Coding Transcripts
Baltz, A. G., Munschauer, M., Schwanhäußer, B., Vasile, A. I., Murakawa, Y., Schueler, M., Youngs, N., Penfold-Brown, D., Drew, K., Milek, M., et al. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.05.021 · Cited by 1,215
Origin, fate and dynamics of macrophages at central nervous system interfaces
Goldmann, T., Wieghofer, P., Jordão, M. J. C., Prutek, F., Hagemeyer, N., Frenzel, K., Amann, L., Staszewski, O., Kierdorf, K., Krueger, M., et al. (2016) · Nature Immunology · doi:10.1038/ni.3423 · Cited by 1,209
Whiteford, H. A., Ferrari, A. J., Degenhardt, L., Feigin, V., & Vos, T. (2015) · PLOS ONE · doi:10.1371/journal.pone.0116820 · Cited by 1,175
Specific expression of long noncoding RNAs in the mouse brain
Mercer, T. R., Dinger, M. E., Sunkin, S. M., Mehler, M. F., & Mattick, J. S. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706729105 · Cited by 1,103
Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
Gandal, M. J., Haney, J. R., Parikshak, N. N., Leppa, V., Ramaswami, G., Hartl, C., Schork, A. J., Appadurai, V., Buil, A., Werge, T. M., et al. (2018) · Science · doi:10.1126/science.aad6469 · Cited by 1,095
Self-citationGene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., Ruderfer, D. M., Oh, E. C., Topol, A., Shah, H. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4399 · Cited by 1,091
Self-citationIntegrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039
Self-citationStudy, L. C., Okbay, A., Baselmans, B. M. L., De Neve, J.-E., Turley, P., Nivard, M. G., Fontana, M. A., Meddens, S. F. W., Linnér, R. K., Rietveld, C. A., et al. (2016) · Nature Genetics · doi:10.1038/ng.3552 · Cited by 1,013
The BioGRID interaction database: 2017 update
Chatr‐aryamontri, A., Oughtred, R., Boucher, L., Rust, J., Chang, C., Kolas, N. K., O’Donnell, L., Oster, S. K., Theesfeld, C. L., Sellam, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1102 · Cited by 985
The evolution of lncRNA repertoires and expression patterns in tetrapods
Necsulea, A., Soumillon, M., Warnefors, M., Liechti, A., Daish, T., Zeller, U., Baker, J. C., Grützner, F., & Kaessmann, H. (2014) · Nature · doi:10.1038/nature12943 · Cited by 984
Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain
Lake, B. B., Chen, S., Sos, B. C., Fan, J., Kaeser, G. E., Yung, Y. C., Duong, T. E., Gao, D., Chun, J., Kharchenko, P. V., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4038 · Cited by 983
A framework for the interpretation of de novo mutation in human disease
Samocha, K. E., Robinson, E. B., Sanders, S. J., Stevens, C., Sabo, A., McGrath, L. M., Kosmicki, J. A., Rehnström, K., Mallick, S., Kirby, A., et al. (2014) · Nature Genetics · doi:10.1038/ng.3050 · Cited by 979
A human phenome-interactome network of protein complexes implicated in genetic disorders
Lage, K., Karlberg, E., Størling, Z. M., Olason, P., Pedersen, A., Rigina, O., Hinsby, A., Tümer, Z., Pociot, F., Tommerup, N., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1295 · Cited by 973
Comprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965
Self-citationNeuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
Lake, B. B., Ai, R., Kaeser, G. E., Salathia, N. S., Yung, Y. C., Liu, R., Wildberg, A., Gao, D., Fung, H.-L., Chen, S., et al. (2016) · Science · doi:10.1126/science.aaf1204 · Cited by 957
Application of a translational profiling approach for the comparative analysis of CNS cell types
Doyle, J. P., Dougherty, J. D., Heiman, M., Schmidt, E. F., Stevens, T. R., Ma, G., Bupp, S., Shrestha, P., Shah, R. D., Doughty, M. L., et al. (2008) · Cell · doi:10.1016/j.cell.2008.10.029 · Cited by 912
Visualizing Genomic Data Using Gviz and Bioconductor
Hahne, F., & Ivánek, R. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3578-9_16 · Cited by 893
INTERFEROME v2.0: an updated database of annotated interferon-regulated genes
Rusinova, I., Forster, S., Yu, S., Kannan, A., Masse, M., Cumming, H., Chapman, R., & Hertzog, P. J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1215 · Cited by 878
Advancing 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
Self-citationIntegrative functional genomic analysis of human brain development and neuropsychiatric risks
Li, M., Santpere, G., Imamura Kawasawa, Y., Evgrafov, O. V., Gulden, F. O., Pochareddy, S., Sunkin, S. M., Li, Z., Shin, Y., Zhu, Y., et al. (2018) · Science · doi:10.1126/science.aat7615 · Cited by 810
Self-citationThe ExAC browser: displaying reference data information from over 60 000 exomes
Karczewski, K. J., Weisburd, B., Thomas, B., Solomonson, M., Ruderfer, D. M., Kavanagh, D., Hamamsy, T., Lek, M., Samocha, K. E., Cummings, B. B., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw971 · Cited by 790
Annotation-free quantification of RNA splicing using LeafCutter
Li, Y. I., Knowles, D. A., Humphrey, J., Barbeira, A. N., Dickinson, S. P., Im, H. K., & Pritchard, J. K. (2018) · Nature Genetics · doi:10.1038/s41588-017-0004-9 · Cited by 765
Functional organization of the transcriptome in human brain
Oldham, M. C., Konopka, G., Iwamoto, K., Langfelder, P., Kato, T., Horvath, S., & Geschwind, D. H. (2008) · Nature Neuroscience · doi:10.1038/nn.2207 · Cited by 752
Self-citationSex-specific transcriptional signatures in human depression
Labonté, B., Engmann, O., Purushothaman, I., Menard, C., Wang, J., Tan, C., Scarpa, J. R., Moy, G., Loh, Y.-H. E., Cahill, M., et al. (2017) · Nature Medicine · doi:10.1038/nm.4386 · Cited by 748
Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes
(2018) · doi:10.1016/j.cell.2018.05.046 · Cited by 744
Self-citationKrantz, I. D., McCallum, J., DeScipio, C., Kaur, M., Gillis, L. A., Yaeger, D., Jukofsky, L., Wasserman, N., Bottani, A., Morris, C. A., et al. (2004) · Nature Genetics · doi:10.1038/ng1364 · Cited by 713
Assessment of transcript reconstruction methods for RNA-seq
The RGASP Consortium, Steijger, T., Abril, J. F., Engström, P. G., Kokocinski, F., Hubbard, T. J., Guigó, R., Harrow, J., & Bertone, P. (2013) · Nature Methods · doi:10.1038/nmeth.2714 · Cited by 699
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 2×
“Finally, several studies have demonstrated that genes carrying microexons are preferentially expressed in the brain and their splicing is dysregulated in ASD (30, 82, 83).”
Self-citationGenome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism
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., et al. (2016) · Nature · doi:10.1038/nature20612 · Cited by 685 · cited 8×
“this signal from astrocyte and microglial populations (13, 19).”
InfluentialSelf-citationRNA splicing is a primary link between genetic variation and disease
Li, Y. I., van de Geijn, B., Raj, A., Knowles, D. A., Petti, A. A., Golan, D., Gilad, Y., & Pritchard, J. K. (2016) · Science · doi:10.1126/science.aad9417 · Cited by 660
Genetic identification of brain cell types underlying schizophrenia
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Skene, N. G., Bryois, J., Bakken, T. E., Breen, G., Crowley, J. J., Gaspar, H. A., Giusti-Rodriguez, P., Hodge, R. D., Miller, J. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0129-5 · Cited by 651
Self-citationGenomic views of distant-acting enhancers
Visel, A., Rubin, E. M., & Pennacchio, L. A. (2009) · Nature · doi:10.1038/nature08451 · Cited by 610
Fillman, S. G., Cloonan, N., Catts, V. S., Miller, L. C., Wong, J., McCrossin, T., Cairns, M., & Weickert, C. S. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.110 · Cited by 609
The Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium (2017) · Molecular Autism · doi:10.1186/s13229-017-0137-9 · Cited by 587
Daneman, R., Zhou, L., Agalliu, D., Cahoy, J. D., Kaushal, A., & Barres, B. A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013741 · Cited by 577
Neuronal Activity-Regulated Gene Transcription in Synapse Development and Cognitive Function
West, A. E., & Greenberg, M. E. (2011) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a005744 · Cited by 532
Immune mediators in the brain and peripheral tissues in autism spectrum disorder
Estes, M. L., & McAllister, A. K. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3978 · Cited by 514
g:Profiler—a web server for functional interpretation of gene lists (2011 update)
Reimand, J., Arak, T., & Vilo, J. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr378 · Cited by 506
Gupta, S., Ellis, S. E., Ashar, F. N., Moes, A., Bader, J. S., Zhan, J., West, A. B., & Arking, D. E. (2014) · Nature Communications · doi:10.1038/ncomms6748 · Cited by 504 · cited 2×
“Previous work has identified differential activation of glial and neural-immune processes in brains from patients with psychiatric disorders (15, 52, 57, 66–69), including up-regulation of astrocytes in SCZ and BD (13, 57) and both microglia and astrocytes in ASD (19, 70).”
The RNA-binding protein repertoire of embryonic stem cells
Kwon, S. C., Yi, H., Eichelbaum, K., Föehr, S., Fischer, B., You, K. T., Castelló, A., Krijgsveld, J., Hentze, M. W., & Kim, V. N. (2013) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2638 · Cited by 462
HINT: High-quality protein interactomes and their applications in understanding human disease
Das, J., & Yu, H. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-92 · Cited by 462
Akbarian, S., Liu, C., Knowles, J. A., Vaccarino, F. M., Farnham, P. J., Crawford, G. E., Jaffe, A. E., Pinto, D., Dracheva, S., Geschwind, D. H., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4156 · Cited by 451
Self-citationIncreased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia
Genovese, G., Fromer, M., Stahl, E. A., Ruderfer, D. M., Chambert, K., Landén, M., Moran, J. L., Purcell, S. M., Sklar, P., Sullivan, P. F., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4402 · Cited by 444
Self-citationRao, J. S., Harry, G. J., Rapoport, S. I., & Kim, H. W. (2010) · Molecular Psychiatry · doi:10.1038/mp.2009.47 · Cited by 432
Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430 · cited 2×
“S12), facilitating computational deconvolution of cell type–specific signatures (14, 49, 51).”
Self-citationBond, A. M., VanGompel, M. J. W., Sametsky, E. A., Clark, M. F., Savage, J. C., Disterhoft, J. F., & Kohtz, J. D. (2009) · Nature Neuroscience · doi:10.1038/nn.2371 · Cited by 399
GeneMANIA Prediction Server 2013 Update
Zuberi, K., Franz, M., Rodriguez, H., Montojo, J., Lopes, C. T., Bader, G. D., & Morris, Q. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt533 · Cited by 396
Genetic Control of Individual Differences in Gene-Specific Methylation in Human Brain
Zhang, D., Cheng, L., Badner, J. A., Chen, C., Chen, Q., Luo, W., Craig, D. W., Redman, M., Gershon, E. S., & Liu, C. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.02.005 · Cited by 395
Self-citationBarry, G., Briggs, J. A., Vanichkina, D. P., Poth, E. M., Beveridge, N. J., Ratnu, V. S., Nayler, S. P., Nones, K., Hu, J., Bredy, T. W., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2013.45 · Cited by 394
A Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging
Miller, J. A., Oldham, M. C., & Geschwind, D. H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4098-07.2008 · Cited by 385
Self-citationThe BrainSeq Consortium, Jaffe, A. E., Straub, R. E., Shin, J. H., Tao, R., Gao, Y., Collado-Torres, L., Kam-Thong, T., Xi, H. S., Quan, J., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0197-y · Cited by 364
Self-citationSchizophrenia and autism: both shared and disorder-specific pathogenesis via perinatal inflammation?
MEYER, U., FELDON, J., & DAMMANN, O. (2011) · Pediatric Research · doi:10.1203/pdr.0b013e318212c196 · Cited by 357
Hamdan, F. F., Gauthier, J., Araki, Y., Lin, D.-T., Yoshizawa, Y., Higashi, K., Park, A.-R., Spiegelman, D., Dobrzeniecka, S., Piton, A., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.02.001 · Cited by 349
Cartography of neurexin alternative splicing mapped by single-molecule long-read mRNA sequencing
Treutlein, B., Gokce, O., Quake, S. R., & Südhof, T. C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403244111 · Cited by 348
The neurogenetics of alternative splicing
Vuong, C. K., Black, D. L., & Zheng, S. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.27 · Cited by 340
The splicing regulator Rbfox1 (A2BP1) controls neuronal excitation in the mammalian brain
Gehman, L. T., Stoilov, P., Maguire, J., Damianov, A., Lin, C.-H., Shiue, L., Ares, M., Mody, I., & Black, D. L. (2011) · Nature Genetics · doi:10.1038/ng.841 · Cited by 331
Evolutionary changes in promoter and enhancer activity during human corticogenesis
Reilly, S. K., Yin, J., Ayoub, A. E., Emera, D., Leng, J., Cotney, J., Sarro, R., Rakic, P., & Noonan, J. P. (2015) · Science · doi:10.1126/science.1260943 · Cited by 297
Self-citationTruncating mutations in NRXN2 and NRXN1 in autism spectrum disorders and schizophrenia
Gauthier, J., Siddiqui, T. J., Huashan, P., Yokomaku, D., Hamdan, F. F., Champagne, N., Lapointe, M., Spiegelman, D., Noreau, A., Lafrenière, R. G., et al. (2011) · Human Genetics · doi:10.1007/s00439-011-0975-z · Cited by 286
Sebestyén, E., Singh, B., Miñana, B., Pagès, A., Mateo, F., Pujana, M. A., Valcárcel, J., & Eyras, E. (2016) · Genome Research · doi:10.1101/gr.199935.115 · Cited by 276
Li, J. Z., Vawter, M. P., Walsh, D. M., Tomita, H., Evans, S. J., Choudary, P. V., Lopez, J. F., Avelar, A., Shokoohi, V., Chung, T., et al. (2004) · Human Molecular Genetics · doi:10.1093/hmg/ddh065 · Cited by 261
Mason, M. J., Fan, G., Plath, K., Zhou, Q., & Horvath, S. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-327 · Cited by 243
Cytoplasmic Rbfox1 Regulates the Expression of Synaptic and Autism-Related Genes
Lee, J.-A., Damianov, A., Lin, C.-H., Fontes, M., Parikshak, N. N., Anderson, E. S., Geschwind, D. H., Black, D. L., & Martin, K. C. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.025 · Cited by 232
Self-citationEvolutionary toggling of the MAPT 17q21.31 inversion region
Zody, M. C., Jiang, Z., Fung, H.-C., Antonacci, F., Hillier, L. W., Cardone, M. F., Graves, T. A., Kidd, J. M., Cheng, Z., Abouelleil, A., et al. (2008) · Nature Genetics · doi:10.1038/ng.193 · Cited by 227
The road to precision psychiatry: translating genetics into disease mechanisms
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Neuroscience · doi:10.1038/nn.4409 · Cited by 223
Self-citationPost-mortem molecular profiling of three psychiatric disorders
Ramaker, R. C., Bowling, K. M., Lasseigne, B. N., Hagenauer, M. H., Hardigan, A. A., Davis, N. S., Gertz, J., Cartagena, P. M., Walsh, D. M., Vawter, M. P., et al. (2017) · Genome Medicine · doi:10.1186/s13073-017-0458-5 · Cited by 219
RBFOX1 regulates both splicing and transcriptional networks in human neuronal development
Fogel, B. L., Wexler, E., Wahnich, A., Friedrich, T., Vijayendran, C., Gao, F., Parikshak, N., Konopka, G., & Geschwind, D. H. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds240 · Cited by 216
Self-citationComplex architecture and regulated expression of the Sox2ot locus during vertebrate development
Amaral, P. P., Neyt, C., Wilkins, S. J., Askarian-Amiri, M. E., Sunkin, S. M., Perkins, A. C., & Mattick, J. S. (2009) · RNA · doi:10.1261/rna.1705309 · Cited by 209
Åberg, K., Saetre, P., Jareborg, N., & Jazin, E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601213103 · Cited by 208
Love, M. I., Hogenesch, J. B., & Irizarry, R. A. (2016) · Nature Biotechnology · doi:10.1038/nbt.3682 · Cited by 186
Quesnel-Vallières, M., Dargaei, Z., Irimia, M., Gonatopoulos-Pournatzis, T., Ip, J. Y., Wu, M., Sterne-Weiler, T., Nakagawa, S., Woodin, M. A., Blencowe, B. J., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.11.033 · Cited by 178
Rosenblat, J. D., Brietzke, E., Mansur, R. B., Maruschak, N. A., Lee, Y., & McIntyre, R. S. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.08.058 · Cited by 172
The human noncoding genome defined by genetic diversity
di Iulio, J., Bartha, I., Wong, E. H. M., Yu, H.-C., Lavrenko, V., Yang, D., Jung, I., Hicks, M. A., Shah, N., Kirkness, E. F., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0062-7 · Cited by 161
Two gene co-expression modules differentiate psychotics and controls
Chen, C., Cheng, L., Grennan, K., Pibiri, F., Zhang, C., Badner, J. A., Members of the Bipolar Disorder Genome Study (BiGS) Consortium, Gershon, E. S., & Liu, C. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.146 · Cited by 157
Self-citationLow load for disruptive mutations in autism genes and their biased transmission
Iossifov, I., Levy, D., Allen, J., Ye, K., Ronemus, M., Lee, Y.-H., Yamrom, B., & Wigler, M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1516376112 · Cited by 156 · cited 1×
“(1 and 2) genes from SFARI Gene database; vulnerable ASD genes (105);”
Oldham, M. C., Langfelder, P., & Horvath, S. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-63 · Cited by 154
Systematic analysis of gene expression patterns associated with postmortem interval in human tissues
Zhu, Y., Wang, L., Yin, Y., & Yang, E. (2017) · Scientific Reports · doi:10.1038/s41598-017-05882-0 · Cited by 129
Akula, N., Barb, J., Jiang, X., Wendland, J. R., Choi, K. H., Sen, S. K., Hou, L., Chen, D. T. W., Laje, G., Johnson, K., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2013.170 · Cited by 116
Self-citationqSVA framework for RNA quality correction in differential expression analysis
Jaffe, A. E., Tao, R., Norris, A. L., Kealhofer, M., Nellore, A., Shin, J. H., Kim, D., Jia, Y., Hyde, T. M., Kleinman, J. E., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1617384114 · Cited by 114
Self-citationInvolvement of SMARCA2/BRM in the SWI/SNF chromatin-remodeling complex in schizophrenia
Koga, M., Ishiguro, H., Yazaki, S., Horiuchi, Y., Arai, M., Niizato, K., Iritani, S., Itokawa, M., Inada, T., Iwata, N., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp166 · Cited by 112
Rbfox1 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
Wilkinson, B., Grepo, N., Thompson, B. L., Kim, J. Y., Wang, K., Evgrafov, O. V., Lu, W., Knowles, J. A., & Campbell, D. B. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.62 · Cited by 101
Self-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-citationNguyen, H. T., Bryois, J., Kim, A., Dobbyn, A. L., Huckins, L. M., Muñoz‐Manchado, A. B., Ruderfer, D. M., Genovese, G., Fromer, M., Xu, X., et al. (2017) · Genome Medicine · doi:10.1186/s13073-017-0497-y · Cited by 87
Self-citationFirst glimpses of the neurobiology of autism spectrum disorder
Sanders, S. J. (2015) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.10.002 · Cited by 84
Pruunsild, P., Bengtson, C. P., & Bading, H. (2017) · Cell Reports · doi:10.1016/j.celrep.2016.12.018 · Cited by 78
Normalizing RNA-Sequencing Data by Modeling Hidden Covariates with Prior Knowledge
Mostafavi, S., Battle, A. J., Zhu, X., Urban, A. E., Levinson, D. F., Montgomery, S. B., & Koller, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068141 · Cited by 75
Investigating the neuroimmunogenic architecture of schizophrenia
Birnbaum, R., Jaffe, A. E., Chen, Q., Shin, J. H., BrainSeq Consortium, Schubert, C. R., O'Donnell, P., Quan, J., Wendland, J. R., Xi, H. S., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.89 · Cited by 67
Self-citationPacifico, R., & Davis, R. L. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.94 · Cited by 61
Functional genomics bridges the gap between quantitative genetics and molecular biologyPreprint
Lappalainen, T. (2015) · Genome Research · doi:10.1101/gr.190983.115 · Cited by 51
Benton, C. S., Miller, B. H., Skwerer, S., Suzuki, O., Schultz, L. E., Cameron, M. D., Marron, J. S., Pletcher, M. T., & Wiltshire, T. (2011) · Psychopharmacology · doi:10.1007/s00213-011-2574-z · Cited by 49
Ellis, S. E., Panitch, R., West, A. B., & Arking, D. E. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.87 · Cited by 48
de Bartolomeis, A., Buonaguro, E. F., Latte, G., Rossi, R., Marmo, F., Iasevoli, F., & Tomasetti, C. (2017) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2017.00240 · Cited by 44
Wesseling, H., Xu, B., Want, E. J., Holmes, E. C., Guest, P. C., Karayiorgou, M., Gogos, J. A., & Bahn, S. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.27 · Cited by 25
csuWGCNA: a combination of signed and unsigned WGCNA to capture negative correlations
Dai, R., Xia, Y., Liu, C., & Chen, C. (2018) · doi:10.1101/288225 · Cited by 13
Self-citationA single cell transcriptomic analysis of human neocortical developmentPreprint
Polioudakis, D., de la Torre-Ubieta, L., Langerman, J., Elkins, A. G., Stein, J. L., Vuong, C. K., Opland, C. K., Lu, D., Connell, W., Ruzzo, E. K., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/401885 · Cited by 7
Self-citationInterpreting noncoding genetic variation in complex traits and human disease
Ward, L. D., & Kellis, M. (2012) · Nature Biotechnology · doi:10.1038/nbt.2422 · Cited by 6 · cited 1×
“The majority of disease-associated genetic variation lies in noncoding regions (5) enriched for noncoding RNAs (ncRNAs) and cis-regulatory elements that regulate gene expression and splicing of their cognate coding gene targets (6, 7).”
BackgroundStructures of membrane proteins
Finkelstein, J. M. (2014) · Nature · doi:10.1038/nature13372 · Cited by 6
Mette (2018) · Synapse · doi:10.7303/syn12080241 · Cited by 5
Fahrenkamp-Uppenbrink, J. (2015) · Science · doi:10.1126/science.aaa3167 · Cited by 1
Flagged first, then by citations
Cited by
Sorted by citations
Mapping genomic loci implicates genes and synaptic biology in schizophrenia
Trubetskoy, V., Pardiñas, A. F., Qi, T., Panagiotaropoulou, G., Awasthi, S., Bigdeli, T. B., Bryois, J., Chen, C.-Y., Dennison, C. A., Hall, L. S., et al. (2022) · Nature · doi:10.1038/s41586-022-04434-5 · Cited by 2,964
Self-citationSatterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321
Self-citationMullins, N., Forstner, A. J., O’Connell, K. S., Coombes, B., Coleman, J. R. I., Qiao, Z., Als, T. D., Bigdeli, T. B., Børte, S., Bryois, J., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00857-4 · Cited by 1,517
Self-citationTranscriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex
Maynard, K. R., Collado-Torres, L., Weber, L. M., Uytingco, C., Barry, B. K., Williams, S. R., Catallini, J. L., Tran, M. N., Besich, Z., Tippani, M., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00787-0 · Cited by 1,222
Self-citationHuman Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice
Sharon, G., Cruz, N. J., Kang, D.-W., Gandal, M. J., Wang, B., Kim, Y.-M., Zink, E. M., Casey, C. P., Taylor, B. C., Lane, C. J., et al. (2019) · Cell · doi:10.1016/j.cell.2019.05.004 · Cited by 1,182
Self-citation
Metadata
- Authors
- Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., Shieh, A. W., Haney, J., Parhami, S., Belmont, J., Kim, M., Moran Losada, P., Khan, Z., Mleczko, J., Xia, Y., Dai, R., Wang, D., Yang, Y. T., Xu, M., Fish, K., Hof, P. R., Warrell, J., Fitzgerald, D., White, K., Jaffe, A. E., PsychENCODE Consortium, Peters, M. A., Gerstein, M., Liu, C., Iakoucheva, L. M., Pinto, D., Geschwind, D. H., Ashley-Koch, A. E., Crawford, G. E., Garrett, M. E., Song, L., Safi, A., Johnson, G. D., Wray, G. A., Reddy, T. E., Goes, F. S., Zandi, P., Bryois, J., Jaffe, A. E., Price, A. J., Ivanov, N. A., Collado-Torres, L., Hyde, T. M., Burke, E. E., Kleiman, J. E., Tao, R., Shin, J. H., Akbarian, S., Girdhar, K., Jiang, Y., Kundakovic, M., Brown, L., Kassim, B. S., Park, R. B., Wiseman, J. R., Zharovsky, E., Jacobov, R., Devillers, O., Flatow, E., Hoffman, G. E., Lipska, B. K., Lewis, D. A., Haroutunian, V., Hahn, C.-G., Charney, A. W., Dracheva, S., Kozlenkov, A., Belmont, J., DelValle, D., Francoeur, N., Hadjimichael, E., Pinto, D., van Bakel, H., Roussos, P., Fullard, J. F., Bendl, J., Hauberg, M. E., Mangravite, L. M., Peters, M. A., Chae, Y., Peng, J., Niu, M., Wang, X., Webster, M. J., Beach, T. G., Chen, C., Jiang, Y., Dai, R., Shieh, A. W., Liu, C., Grennan, K. S., Xia, Y., Vadukapuram, R., Wang, Y., Fitzgerald, D., Cheng, L., Brown, M., Brown, M., Brunetti, T., Goodman, T., Alsayed, M., Gandal, M. J., Geschwind, D. H., Won, H., Polioudakis, D., Wamsley, B., Yin, J., Hadzic, T., De La Torre Ubieta, L., Swarup, V., Sanders, S. J., State, M. W., Werling, D. M., An, J.-Y., Sheppard, B., Willsey, A. J., White, K. P., Ray, M., Giase, G., Kefi, A., Mattei, E., Purcaro, M., Weng, Z., Moore, J., Pratt, H., Huey, J., Borrman, T., Sullivan, P. F., Giusti-Rodriguez, P., Kim, Y., Sullivan, P., Szatkiewicz, J., Rhie, S. K., Armoskus, C., Camarena, A., Farnham, P. J., Spitsyna, V. N., Witt, H., Schreiner, S., Evgrafov, O. V., Knowles, J. A., Gerstein, M., Liu, S., Wang, D., Navarro, F. C. P., Warrell, J., Clarke, D., Emani, P. S., Gu, M., Shi, X., Xu, M., Yang, Y. T., Kitchen, R. R., Gürsoy, G., Zhang, J., Carlyle, B. C., Nairn, A. C., Li, M., Pochareddy, S., Sestan, N., Skarica, M., Li, Z., Sousa, A. M. M., Santpere, G., Choi, J., Zhu, Y., Gao, T., Miller, D. J., Cherskov, A., Yang, M., Amiri, A., Coppola, G., Mariani, J., Scuderi, S., Szekely, A., Vaccarino, F. M., Wu, F., Weissman, S., Roychowdhury, T., & Abyzov, A.
- Affiliations
- University of California San Diego (US)
- University of California, Los Angeles (US)
- Icahn School of Medicine at Mount Sinai (US)
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA.
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
- Sage Bionetworks (US)
- Yale University (US)
- Stony Brook University (US)
- SUNY Upstate Medical University (US)
- Corresponding author
- Iakoucheva, Lilia M.
- ORCID
- Zhang, Pan
- Walker, Rebecca L.
- Varghese, Merina
- Haney, Jillian
- Parhami, Sepideh
- Kim, Minsoo
- Moran Losada, Patricia
- Fish, Kenneth
- Hof, Patrick R.
- White, Kevin
- Iakoucheva, Lilia M.
- Crawford, Gregory E.
- Song, Lingyun
- Safi, Alexias
- Johnson, Graham D.
- Wray, Gregory A.
- Reddy, Timothy E
- Goes, Fernando S.
- Zandi, Peter
- Bryois, Julien
- Price, Amanda J.
- Ivanov, Nikolay A.
- Hyde, Thomas M.
- Tao, Ran
- Shin, Joo Heon
- Akbarian, Schahram
- Girdhar, Kiran
- Jiang, Yan
- Park, Royce B.
- Wiseman, Jennifer R
- Zharovsky, Elizabeth
- Hoffman, Gabriel E.
- Lewis, David A.
- Haroutunian, Vahram
- Charney, Alexander W.
- Dracheva, Stella
- Kozlenkov, Alexey
- Francoeur, Nancy
- Roussos, Panos
- Fullard, John F.
- Bendl, Jaroslav
- Hauberg, Mads E.
- Mangravite, Lara M
- Peng, Junmin
- Niu, Mingming
- Wang, Xusheng
- Webster, Maree J.
- Jiang, Yi
- Cheng, Lijun
- Brown, Miguel
- Brunetti, Tonya
- Wamsley, Brie
- Yin, Jiani
- Swarup, Vivek
- Sanders, Stephan J.
- State, Matthew W.
- Werling, Donna M.
- An, Joon-Yong
- Sheppard, Brooke
- Willsey, A. Jeremy
- Giase, Gina
- Kefi, Amira
- Mattei, Eugenio
- Purcaro, Michael
- Weng, Zhiping
- Moore, Jill
- Pratt, Henry
- Huey, Jack
- Borrman, Tyler
- Kim, Yunjung
- Szatkiewicz, Jin
- Rhie, Suhn Kyong
- Camarena, Adrian
- Farnham, Peggy J.
- Spitsyna, Valeria N.
- Witt, Heather
- Schreiner, Shannon
- Evgrafov, Oleg V.
- Knowles, James A.
- Clarke, Declan
- Emani, Prashant S.
- Gu, Mengting
- Shi, Xu
- Kitchen, Robert R.
- Gürsoy, Gamze
- Zhang, Jing
- Carlyle, Becky C.
- Nairn, Angus C.
- Li, Mingfeng
- Pochareddy, Sirisha
- Li, Zhen
- Santpere, Gabriel
- Choi, Jinmyung
- Zhu, Ying
- Gao, Tianliuyun
- Miller, Daniel J.
- Cherskov, Adriana
- Yang, Mo
- Amiri, Anahita
- Coppola, Gianfilippo
- Mariani, Jessica
- Scuderi, Soraya
- Szekely, Anna
- Vaccarino, Flora M.
- Wu, Feinan
- Roychowdhury, Tanmoy
- Abyzov, Alexej
- Venue
- Science
- Published
- 2018-12-14
- Volume
- 362
- Issue
- 6420
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6443102
- OpenAlex
- W2904884010
- Semantic Scholar
- 8841331ef6fa66e8859f0a5e26e240c3f57a16e9
- Cited by
- 1,247
- References
- 147
- Citations by year
- 2026: 126 · 2025: 145 · 2024: 168 · 2023: 166 · 2022: 176 · 2021: 201 · 2020: 162 · 2019: 92 · 2018: 4
- FWCI
- 69.69
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of Mental Health
- NIH Office of the Director (U01MH103340, R01MH110920)
- Simons Foundation
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- autism spectrum disorder, schizophrenia, bipolar disorder, transcriptome-wide association study, differential splicing, gene co-expression modules, non-coding RNA, genetic risk variants, polygenic risk score, Mendelian randomization, cell type-specific gene expression, blood-brain barrier, microglia, astrocytes, interferon response, immediate early genes, candidate risk genes
- MeSH terms
- Autism Spectrum Disorder, Bipolar Disorder, Brain, Humans, RNA Splicing, Schizophrenia, Sequence Analysis, RNA, Genetic Predisposition to Disease, Protein Isoforms, Transcriptome
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.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review