The DOI matches its Crossref record; 129 of the 130 references it cites were found in a registry or an index.
Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap
Open accessPublished version of a preprint
Abstract
Genes overlap across psychiatric disease: Many genome-wide studies have examined genes associated with a range of neuropsychiatric disorders. However, the degree to which the genetic underpinnings of these diseases differ or overlap is unknown. Gandal et al. performed meta-analyses of transcriptomic studies covering five major psychiatric disorders and compared cases and controls to identify coexpressed gene modules. From this, they found that some psychiatric disorders share global gene expression patterns. This overlap in polygenic traits in neuropsychiatric disorders may allow for better diagnosis and treatment. Science , this issue p. 693
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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
“Interestingly, virtually all cluster D modules failed to overlap with modules showing significant associations with neuropsychiatric disorders (Figure S6A) and were therefore “AD specific.””
From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · 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
“In contrast, AD consensus clusters B and C strongly overlapped with several neuropsychiatric coexpression modules similarly enriched for microglial and neuronal expression signatures, respectively.”
From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · 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
“For example, module CD11, which was increased in autism, overlapped significantly with AD cluster B module FPturquoise (padj = 1.3 × 10−136) (Figure S6B).”
From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Gandal et al., 2018
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Previously, genes expressed by microglia have been implicated in AD in human GWASs”
From Cross-Species Single-Cell Analysis Reveals Divergence of the Primate Microglia Program (2019) · cites this paper as Gandal et al., 2018
Experimental — accuracy not yet measuredIn the citing paper
“Transcriptomic meta-analyses of human cerebral cortex across major neuropsychiatric disorders, including autism (ASD), schizophrenia (SZ), bipolar disorder (BD) and depression (MDD), have found the shared transcriptional dysregulation underlying convergent molecular neuropathology, such as a gradient of synaptic gene down-regulation and astroglial gene up-regulation in ASD, SZ and BD (ASD > SZ = B”
From Mechanisms of synaptic transmission dysregulation in the prefrontal cortex: pathophysiological implications (2022) · cites this paper as [120]
In the citing paper
“They found that differential expression effects were correlated between conditions, and that these correlations paralleled those between the genetic effects on those conditions (the genetic correlation).”
From Transcriptome-wide analysis of differential expression in perturbation atlases (2025) · cites this paper as [29]
In the citing paper
“Gandal et al29 conducted a large-scale differential expression analysis of post-mortem brain tissue from individuals with neuropsychiatric conditions, comparing them with neurotypical controls.”
From Transcriptome-wide analysis of differential expression in perturbation atlases (2025) · cites this paper as [29]
In the citing paper
“6 of the 14 modules previously reported to be altered in the ASD patients in the PsychEncode analysis were also significantly affected across 8 of our ASD/ND risk gene perturbations (fig. S14).”
From In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes (2020) · cites this paper as [34]
In the citing paper
“in individuals with ASD, the fraction of Ex5 was higher and that of oligodendrocytes, lower, with some commensurate increase for microglia and astrocytes (Fig. 2E and fig. S18) (24, 29).”
From Comprehensive functional genomic resource and integrative model for the human brain (2018) · cites this paper as [24]
In the citing paper
“RBFOX1 (also called A2BP1 ) encodes a splicing regulator mainly expressed in neurons and known to target several genes important to neuronal development, including NMDA receptor 1 and voltage-gated calcium channels (Gandal et al., 2018; Gehman et al., 2011; Hamada et al., 2015).”
From Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders (2019) · cites this paper as Gandal et al., 2018
In the citing paper
“These DE genes exhibited substantial enrichment for known pathways and cell type specific markers derived from single nucleus RNA-Seq in human brain (Fig 1D-E) (21), consistent with previously observed patterns (1, 19).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing 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).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing paper
“We observed significant concordance of DGE effect sizes with those from a microarray meta-analysis of each disorder (ASD: ⍴=0.8, SCZ: ⍴=0.78, BD: ⍴=0.64, Spearman ⍴ of log2FC, all P’s<10−16, (1))”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing 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).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing paper
“Previous work has identified downregulated neuronal modules in ASD and SCZ containing RBFOX1 as a hub (1, 16).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing paper
“Multiple neuronal and synaptic signaling pathways have been previously demonstrated to be downregulated in a diminishing gradient across ASD, SCZ, and BD brains without identification of clear disease-specific signals for these neuronal-synaptic gene sets (1, 2, 16, 19, 56, 57).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing paper
“including upregulation of astrocytes in SCZ and BD (1, 57)”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing paper
“although post-mortem microglial upregulation was observed only in ASD (1, 19, 70).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
In the citing paper
“Previous transcriptional networks related to ASD, BD and SCZ did not separate inhibitory and excitatory neuron signals (1).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [1]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Self-citationConducting Meta-Analyses in R with the metafor Package
Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658
Finding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
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
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
Self-citationLD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
Self-citationPopulation Structure and Eigenanalysis
Patterson, N., Price, A. L., & Reich, D. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020190 · Cited by 5,280
Lamb, J., Crawford, E. D., Peck, D., Modell, J. W., Blat, I. C., Wrobel, M. J., Lerner, J., Brunet, J.-P., Subramanian, A., Ross, K. N., et al. (2006) · Science · doi:10.1126/science.1132939 · Cited by 5,257
affy—analysis of Affymetrix GeneChip data at the probe level
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg405 · Cited by 5,221
The 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
Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt
Durinck, S., Spellman, P. T., Birney, E., & Huber, W. K. (2009) · Nature Protocols · doi:10.1038/nprot.2009.97 · Cited by 4,156
Howie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928
MAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004219 · Cited by 3,653
Robust relationship inference in genome-wide association studies
Manichaikul, A., Mychaleckyj, J. C., Rich, S. S., Daly, K., Sale, M., & Chen, W.-M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq559 · Cited by 3,541
(2013) · The Lancet · doi:10.1016/s0140-6736(12)62129-1 · Cited by 3,010
Synaptic, transcriptional and chromatin genes disrupted in autism
Study, T. D., De Rubeis, S., Autism, H. M. C. F., UK10K Consortium, The Autism Sequencing Consortium, He, X., Goldberg, A. P., Poultney, C. S., Samocha, K., Ercument Cicek, A., et al. (2014) · Nature · doi:10.1038/nature13772 · Cited by 2,746
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-citationLiu, J. Z., van Sommeren, S., Huang, H., Ng, S. C., Alberts, R., Takahashi, A., Ripke, S., Lee, J. C., Jostins, L., Shah, T., et al. (2015) · Nature Genetics · doi:10.1038/ng.3359 · Cited by 2,603
Self-citationThe contribution of de novo coding mutations to autism spectrum disorder
Iossifov, I., O’Roak, B. J., Sanders, S. J., Ronemus, M., Krumm, N., Levy, D., Stessman, H. A., Witherspoon, K. T., Vives, L., Patterson, K. E., et al. (2014) · Nature · doi:10.1038/nature13908 · Cited by 2,585
Self-citationMeta-analysis of the heritability of human traits based on fifty years of twin studies
Polderman, T. J. C., Benyamin, B., de Leeuw, C. A., Sullivan, P. F., van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015) · Nature Genetics · doi:10.1038/ng.3285 · Cited by 2,467
Self-citationSchizophrenia 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
Self-citationZhang, 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
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs
Cross-Disorder Group of the Psychiatric Genomics Consortium (2013) · Nature Genetics · doi:10.1038/ng.2711 · Cited by 2,263
Self-citationSporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165
De novo mutations revealed by whole-exome sequencing are strongly associated with autism
Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084
Self-citationlumi : a pipeline for processing Illumina microarray
Du, P., Kibbe, W. A., & Lin, S. M. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn224 · Cited by 2,028
Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
Langfelder, P., Zhang, B., & Horvath, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btm563 · Cited by 1,892
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
Self-citationStructural Variation of Chromosomes in Autism Spectrum Disorder
Marshall, C. R., Noor, A., Vincent, J. B., Lionel, A. C., Feuk, L., Skaug, J., Shago, M., Moessner, R., Pinto, D., Ren, Y., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2007.12.009 · Cited by 1,815
Self-citationMicroglia emerge as central players in brain disease
Salter, M. W., & Stevens, B. (2017) · Nature Medicine · doi:10.1038/nm.4397 · Cited by 1,767
Large recurrent microdeletions associated with schizophrenia.
GROUP, Stefansson, H., Rujescu, D., Cichon, S., Pietiläinen, O. P. H., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., et al. (2008) · Nature · doi:10.1038/nature07229 · Cited by 1,745
Self-citationPatterns and rates of exonic de novo mutations in autism spectrum disorders
Neale, B. M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K. E., Sabo, A., Lin, C.-F., Stevens, C., Wang, L.-S., Makarov, V., et al. (2012) · Nature · doi:10.1038/nature11011 · Cited by 1,734
Self-citationAssociation between Microdeletion and Microduplication at 16p11.2 and Autism
Weiss, L. A., Shen, Y., Korn, J. M., Arking, D. E., Miller, D. T., Fossdal, R., Saemundsen, E., Stefansson, H., Ferreira, M. A. R., Green, T., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa075974 · Cited by 1,666
Self-citationIntegrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease
Zhang, B., Gaiteri, C., Bodea, L.-G., Wang, Z., McElwee, J., Podtelezhnikov, A. A., Zhang, C., Xie, T., Tran, L., Dobrin, R., et al. (2013) · Cell · doi:10.1016/j.cell.2013.03.030 · Cited by 1,657
Self-citationDe novo mutations in schizophrenia implicate synaptic networks
Fromer, M., Pocklington, A. J., Kavanagh, D. H., Williams, H. J., Dwyer, S., Gormley, P., Georgieva, L., Rees, E., Palta, P., Ruderfer, D. M., et al. (2014) · Nature · doi:10.1038/nature12929 · Cited by 1,617
Self-citationDiagnostic exome sequencing in persons with severe intellectual disability
de Ligt, J., Willemsen, M. H., van Bon, B. W. M., Kleefstra, T., Yntema, H. G., Kroes, T., Vulto-van Silfhout, A. T., Koolen, D. A., de Vries, P., Gilissen, C., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1206524 · Cited by 1,546
Rare chromosomal deletions and duplications increase risk of schizophrenia
The International Schizophrenia Consortium (2008) · Nature · doi:10.1038/nature07239 · Cited by 1,475
De Novo Gene Disruptions in Children on the Autistic Spectrum
Iossifov, I., Ronemus, M., Levy, D., Wang, Z., Hakker, I., Rosenbaum, J., Yamrom, B., Lee, Y.-H., Narzisi, G., Leotta, A., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.04.009 · Cited by 1,446
Insights 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-citationAutism genome-wide copy number variation reveals ubiquitin and neuronal genes
Glessner, J. T., Wang, K., Cai, G., Korvatska, O., Kim, C. E., Wood, S., Zhang, H., Estes, A., Brune, C. W., Bradfield, J. P., et al. (2009) · Nature · doi:10.1038/nature07953 · Cited by 1,421
Self-citationPsychiatric 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-citationGenome-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
Self-citationSanders, S. J., Ercan-Sencicek, A. G., Hus, V., Luo, R., Murtha, M. T., Moreno-De-Luca, D., Chu, S. H., Moreau, M. P., Gupta, A. R., Thomson, S. A., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.002 · Cited by 1,263
Self-citationMost genetic risk for autism resides with common variation
Gaugler, T., Klei, L., Sanders, S. J., Bodea, C. A., Goldberg, A. P., Lee, A. B., Mahajan, M., Manaa, D., Pawitan, Y., Reichert, J., et al. (2014) · Nature Genetics · doi:10.1038/ng.3039 · Cited by 1,239
Self-citationWhiteford, H. A., Ferrari, A. J., Degenhardt, L., Feigin, V., & Vos, T. (2015) · PLOS ONE · doi:10.1371/journal.pone.0116820 · Cited by 1,175
A mega-analysis of genome-wide association studies for major depressive disorder
Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Ripke, S., Wray, N. R., Lewis, C. M., Hamilton, S. P., Weissman, M. M., Breen, G., Byrne, E. M., Blackwood, D. H. R., Boomsma, D. I., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.21 · Cited by 1,120
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-citationRauch, A., Wieczorek, D., Graf, E., Wieland, T., Endele, S., Schwarzmayr, T., Albrecht, B., Bartholdi, D., Beygo, J., Di Donato, N., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61480-9 · Cited by 1,041
Integrative 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
Self-citationGenotype Imputation with Thousands of Genomes
Howie, B., Marchini, J., & Stephens, M. (2011) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.111.001198 · Cited by 966
Sparse whole-genome sequencing identifies two loci for major depressive disorder
CONVERGE consortium, Cai, N., Bigdeli, T. B., Kretzschmar, W., Li, Y., Liang, J., Song, L., Hu, J., Li, Q., Jin, W., et al. (2015) · Nature · doi:10.1038/nature14659 · Cited by 864
CNVs: Harbingers of a Rare Variant Revolution in Psychiatric Genetics
Malhotra, D., & Sebat, J. (2012) · Cell · doi:10.1016/j.cell.2012.02.039 · Cited by 854
Elevated immune response in the brain of autistic patients
Li, X., Chauhan, A., Sheikh, A. M., Patil, S., Chauhan, V., Li, X.-M., Ji, L., Brown, T., & Malik, M. (2009) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2008.12.002 · Cited by 786
Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways
The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium (2015) · Nature Neuroscience · doi:10.1038/nn.3922 · Cited by 755
Self-citationFunctional 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-citationMicroduplications of 16p11.2 are associated with schizophrenia
Wellcome Trust Case Control Consortium, McCarthy, S. E., Makarov, V., Kirov, G., Addington, A. M., McClellan, J., Yoon, S., Perkins, D. O., Dickel, D. E., Kusenda, M., et al. (2009) · Nature Genetics · doi:10.1038/ng.474 · Cited by 711
Self-citationCNVs conferring risk of autism or schizophrenia affect cognition in controls
Stefansson, H., Meyer-Lindenberg, A., Steinberg, S., Magnusdottir, B., Morgen, K., Arnarsdottir, S., Bjornsdottir, G., Walters, G. B., Jonsdottir, G. A., Doyle, O. M., et al. (2014) · Nature · doi:10.1038/nature12818 · Cited by 699
The Danish Psychiatric Central Register.
Munk‐Jørgensen, P., & Mortensen, P. B. (1997) · PubMed · Cited by 698
Self-citationThe organization of the stress system and its dysregulation in depressive illness
Gold, P. W. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.163 · Cited by 654
Association Between Microdeletion and Microduplication at 16p11.2 and Autism
Weiss, L. A., Shen, Y., Korn, J. M., Arking, D. E., Miller, D. T., Fossdal, R., Sæmundsen, E., Stefánsson, H., Ferreira, M. A. R., Green, T. J., et al. (2008) · Obstetrical & Gynecological Survey · doi:10.1097/01.ogx.0000316305.61461.6f · Cited by 647
Self-citationPedersen, C. B., Mors, O. N., Bertelsen, A., Waltoft, B. L., Agerbo, E., McGrath, J. J., Mortensen, P. B., & Eaton, W. W. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.16 · Cited by 630
Self-citationRemoving technical variability in RNA-seq data using conditional quantile normalization
Hansen, K. D., Irizarry, R. A., & WU, Z. (2012) · Biostatistics · doi:10.1093/biostatistics/kxr054 · Cited by 607
The Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium (2017) · Molecular Autism · doi:10.1186/s13229-017-0137-9 · Cited by 587
The “quad‐partite” synapse: Microglia‐synapse interactions in the developing and mature CNS
Schafer, D. P., Lehrman, E. K., & Stevens, B. (2013) · Glia · doi:10.1002/glia.22389 · Cited by 570
Gulsuner, S., Walsh, T., Watts, A. C., Lee, M. K., Thornton, A. M., Casadei, S., Rippey, C., Shahin, H., Braff, D., Cadenhead, K. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.049 · Cited by 536
Self-citationSublime Microglia: Expanding Roles for the Guardians of the CNS
Salter, M. W., & Beggs, S. (2014) · Cell · doi:10.1016/j.cell.2014.06.008 · Cited by 531
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
Iwamoto, K., Bundo, M., & Kato, T. (2004) · Human Molecular Genetics · doi:10.1093/hmg/ddi022 · Cited by 496
Impaired mitochondrial function in psychiatric disorders
Manji, H. K., Kato, T., Prospero, N. A. D., Ness, S. L., Beal, M. F., Krams, M., & Chen, G. (2012) · Nature reviews. Neuroscience · doi:10.1038/nrn3229 · Cited by 493
Disruption of the neurexin 1 gene is associated with schizophrenia
Rujescu, D., Ingason, A., Cichon, S., Pietiläinen, O. P. H., Barnes, M. R., Toulopoulou, T., Picchioni, M., Vassos, E., Ettinger, U., Bramon, E., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddn351 · Cited by 471
Self-citationAkbarian, 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-citationDe novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia
Xu, B., Ionita-Laza, I., Roos, J. L., Boone, B., Woodrick, S., Sun, Y., Levy, S., Gogos, J. A., & Karayiorgou, M. (2012) · Nature Genetics · doi:10.1038/ng.2446 · Cited by 442
Increased exonic de novo mutation rate in individuals with schizophrenia
Girard, S. L., Gauthier, J., Noreau, A., Xiong, L., Zhou, S., Jouan, L., Dionne-Laporte, A., Spiegelman, D., Henrion, E., Diallo, O., et al. (2011) · Nature Genetics · doi:10.1038/ng.886 · Cited by 438
Levinson, D. F., Duan, J., Oh, S., Wang, K., Sanders, A. R., Shi, J., Zhang, N., Mowry, B. J., Olincy, A., Amin, F., et al. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.10060876 · Cited by 434
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
Self-citationGenetics and genomics of psychiatric disease
Geschwind, D. H., & Flint, J. (2015) · Science · doi:10.1126/science.aaa8954 · Cited by 424
Self-citationGene Coexpression Networks in Human Brain Identify Epigenetic Modifications in Alcohol Dependence
Ponomarev, I., Wang, S., Zhang, L., Harris, R. A., & Mayfield, R. D. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.3136-11.2012 · Cited by 387
Reactive Astrocytes Overexpress TSPO and Are Detected by TSPO Positron Emission Tomography Imaging
Lavisse, S., Guillermier, M., Hérard, A., Petit, F., Delahaye, M., Camp, N. V., Haim, L. B., Lebon, V., Rémy, P., Dollé, F., et al. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.1487-12.2012 · Cited by 381
Immune transcriptome alterations in the temporal cortex of subjects with autism
Garbett, K., Ebert, P. J., Mitchell, A., Lintas, C., Manzi, B., Mirnics, K., & Persico, A. M. (2008) · Neurobiology of Disease · doi:10.1016/j.nbd.2008.01.012 · Cited by 375
Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia
Ruderfer, D. M., Fanous, A. H., Ripke, S., McQuillin, A., Amdur, R. L., Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Cross-Disorder Working Group of the Psychiatric Genomics Consortium, Gejman, P. V., O'Donovan, M. C., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2013.138 · Cited by 364
Self-citationLarge-scale genomics unveils the genetic architecture of psychiatric disorders
Gratten, J., Wray, N. R., Keller, M. C., & Visscher, P. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3708 · Cited by 363
Dougherty, J. D., Schmidt, E. F., Nakajima, M., & Heintz, N. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq130 · Cited by 350
Pedersen, C. B., Bybjerg-Grauholm, J., Pedersen, M. G., Grove, J., Agerbo, E., Bækvad-Hansen, M., Poulsen, J. B., Hansen, C. S., McGrath, J. J., Als, T. D., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.196 · Cited by 338
Self-citationDuplications of the neuropeptide receptor gene VIPR2 confer significant risk for schizophrenia
Vacic, V., McCarthy, S., Malhotra, D., Murray, F., Chou, H.-H., Peoples, A., Makarov, V., Yoon, S., Bhandari, A., Corominas, R., et al. (2011) · Nature · doi:10.1038/nature09884 · Cited by 337
Recurrent de novo mutations implicate novel genes underlying simplex autism risk
O'Roak, B. J., Stessman, H. A., Boyle, E. A., Witherspoon, K. T., Martin, B., Lee, C., Vives, L., Baker, C., Hiatt, J. B., Nickerson, D. A., et al. (2014) · Nature Communications · doi:10.1038/ncomms6595 · Cited by 336
Deletion 17q12 is a recurrent copy number variant that confers high risk of autism and schizophrenia
Moreno-De-Luca, D., Mulle, J. G., Kaminsky, E. B., Sanders, S. J., Myers, S. M., Adam, M. P., Pakula, A. T., Eisenhauer, N. J., Uhas, K., Weik, L., et al. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.10.004 · Cited by 324
Girirajan, S., Dennis, M. Y., Baker, C. A., Malig, M., Coe, B. P., Campbell, C. D., Mark, K. M. K., Vu, T. H., Alkan, C., Cheng, Z., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.12.016 · Cited by 309
Strategies for aggregating gene expression data: The collapseRows R function
Miller, J. A., Cai, C., Langfelder, P., Geschwind, D. H., Kurian, S. M., Salomon, D. R., & Horvath, S. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-322 · Cited by 307
Self-citationPantazopoulos, H., Woo, T.-U. W., Lim, M. P., Lange, N., & Berretta, S. (2010) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.196 · Cited by 296
Xu, X., Wells, A., O’Brien, D. R., Nehorai, A., & Dougherty, J. D. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4488-13.2014 · Cited by 276
Genes and pathways underlying regional and cell type changes in Alzheimer’s disease
Miller, J. A., Woltjer, R. L., Goodenbour, J. M., Horvath, S., & Geschwind, D. H. (2013) · Genome Medicine · doi:10.1186/gm452 · Cited by 275
Self-citationSchumann, G., Coin, L. J., Lourdusamy, A., Charoen, P., Berger, K. H., Stacey, D., Desrivières, S., Aliev, F. A., Khan, A. A., Amin, N., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017288108 · Cited by 264
GO-Elite: a flexible solution for pathway and ontology over-representation
Zambon, A. C., Gaj, S., Ho, I., Hanspers, K., VRANIZAN, K. M., Evelo, C. T., Conklin, B. R., Pico, A. R., & Salomonis, N. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts366 · Cited by 263
Laurence, J. A., & Fatemi, S. H. (2005) · The Cerebellum · doi:10.1080/14734220500208846 · Cited by 248
Mason, M. J., Fan, G., Plath, K., Zhou, Q., & Horvath, S. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-327 · Cited by 243
Self-citationMicrodeletions of 3q29 confer high risk for schizophrenia
Mulle, J. G., Dodd, A. F., McGrath, J. A., Wolyniec, P. S., Mitchell, A. A., Shetty, A. C., Sobreira, N. L., Valle, D., Rudd, M. K., Satten, G., et al. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.07.013 · Cited by 223
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-citationA Cross-Study Comparison of Gene Expression Studies for the Molecular Classification of Lung Cancer
Parmigiani, G., Garrett-Mayer, E. S., Anbazhagan, R., & Gabrielson, E. W. (2004) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-03-0490 · Cited by 209
Molecular profiles of schizophrenia in the CNS at different stages of illness
Narayan, S., Tang, B., Head, S. R., Gilmartin, T. J., Sutcliffe, J. G., Dean, B., & Thomas, E. A. (2008) · Brain Research · doi:10.1016/j.brainres.2008.08.023 · Cited by 207
Regional variation in gene expression in the healthy colon is dysregulated in ulcerative colitis
Noble, C. L., Abbas, A. R., Cornelius, J., Lees, C. W., Ho, G., Toy, K. J., Modrusan, Z. D., Pal, N., Zhong, F. L., Chalasani, S., et al. (2008) · Gut · doi:10.1136/gut.2008.148395 · Cited by 206
Chow, M. L., Pramparo, T., Winn, M. E., Barnes, C. C., Li, H.-R., Weiss, L., Fan, J.-B., Murray, S., April, C., Belinson, H., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002592 · Cited by 202
A Quantitative Framework to Evaluate Modeling of Cortical Development by Neural Stem Cells
Stein, J. L., de la Torre-Ubieta, L., Tian, Y., Parikshak, N. N., Hernández, I. A., Marchetto, M. C., Baker, D. K., Lu, D., Hinman, C. R., Lowe, J. K., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.035 · Cited by 201
Self-citationMaycox, P. R., Kelly, F., Taylor, A. R., Bates, S., Reid, J. L., Logendra, R., Barnes, M. R., Larminie, C. G. C., Jones, N. A., Lennon, M. G., et al. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.18 · Cited by 200
Copy number variation in bipolar disorder
Green, E., Rees, E., Walters, J., Gordon‐Smith, K., Forty, L., Grozeva, D., Moran, J. L., Sklar, P. B., Ripke, S., Chambert, K. D., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.174 · Cited by 183
Self-citationClarke, T.-K., Lupton, M. K., Fernandez-Pujals, A. M., Starr, J., Davies, G., Cox, S., Pattie, A., Liewald, D. C., Hall, L. S., MacIntyre, D. J., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.12 · Cited by 179
Moreno-De-Luca, D., Sanders, S. J., Willsey, A. J., Mulle, J. G., Lowe, J. K., Geschwind, D. H., State, M. W., Martin, C. L., & Ledbetter, D. H. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.138 · Cited by 161
Self-citationTwo 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-citationOldham, M. C., Langfelder, P., & Horvath, S. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-63 · Cited by 154
Self-citationReinhart, V., Bove, S. E., Volfson, D., Lewis, D. A., Kleiman, R. J., & Lanz, T. A. (2015) · Neurobiology of Disease · doi:10.1016/j.nbd.2015.03.011 · Cited by 143
Self-citationSerotonergic transcriptional networks and potential importance to mental health
Deneris, E. S., & Wyler, S. C. (2012) · Nature Neuroscience · doi:10.1038/nn.3039 · Cited by 125
Granlund, A. V. B., Flatberg, A., Østvik, A. E., Drozdov, I. A., Gustafsson, B. I., Kidd, M. S., Beisvåg, V., TORP, S. H., Waldum, H. L., Martinsen, T. C., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0056818 · Cited by 119
qSVA 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-citationThe organization of the transcriptional network in specific neuronal classes
Winden, K. D., Oldham, M. C., Mirnics, K., Ebert, P. J., Swan, C. H., Levitt, P., Rubenstein, J. L., Horvath, S., & Geschwind, D. H. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.46 · Cited by 112
Self-citationRoles of the LHX3 and LHX4 LIM-homeodomain factors in pituitary development
Mullen, R. D., Colvin, S. C., Hunter, C. S., Savage, J. J., Walvoord, E. C., Bhangoo, A., Ten, S., Weigel, J. F. W., Pfäffle, R. W., & Rhodes, S. J. (2007) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2006.12.019 · Cited by 107
Chang, L., Jamain, S., Lin, C., Rujescu, D., Tseng, G. C., & Sibille, E. L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0090980 · Cited by 103
Coexpression networks identify brain region–specific enhancer RNAs in the human brain
Yao, P., Lin, P., Gokoolparsadh, A., Assareh, A. A., Thang, M. W. C., & Voineagu, I. (2015) · Nature Neuroscience · doi:10.1038/nn.4063 · Cited by 94
Duplication of the SLIT3 Locus on 5q35.1 Predisposes to Major Depressive Disorder
Glessner, J., Wang, K., Abou‐Sleiman, P. M., Zhang, H., Kim, C., Flory, J. H., Bradfield, J. P., Imielinski, M. B., Frackelton, E. C., Qiu, H., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015463 · Cited by 65
iPSC-derived neurons as a higher-throughput readout for autism: promises and pitfalls
Prilutsky, D., Palmer, N., Smedemark-Margulies, N., Schlaeger, T. M., Margulies, D. M., & Kohane, I. S. (2013) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2013.11.004 · Cited by 51
Length Bias Correction in Gene Ontology Enrichment Analysis Using Logistic Regression
Mi, G., Di, Y., Emerson, S., Cumbie, J. S., & Chang, J. H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046128 · Cited by 39
MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data
Cope, L., Zhong, X., Garrett, E., & Parmigiani, G. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1046 · Cited by 36
Martin, M. V., Mirnics, K., Nisenbaum, L. K., & Vawter, M. P. (2015) · Complex Psychiatry · doi:10.1159/000430786 · Cited by 22
Schumann, G., Coin, L., Lourdusamy, A., Charoen, P., Berger, K. H., Stacey, D., Desrivières, S., Alıev, F., Khan, A. A., Amin, N., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1106917108 · Cited by 14
Flagged first, then by citations
1 of the 130 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
The Lancet Commission on global mental health and sustainable development
Patel, V., Saxena, S., Lund, C., Thornicroft, G., Baingana, F., Bolton, P., Chisholm, D., Collins, P. Y., Cooper, J. L., Eaton, J., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31612-x · Cited by 3,692
Satterstrom, 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
“In contrast to post-mortem findings in adult ASD brains (Gandal et al., 2018; 22 Voineagu et al., 2011), no enrichment was observed in microglia.”
ResultSelf-citationGenomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
Lee, P. H., Anttila, V., Won, H., Feng, Y.-C. A., Rosenthal, J., Zhu, Z., Tucker-Drob, E. M., Nivard, M. G., Grotzinger, A. D., Posthuma, D., et al. (2019) · Cell · doi:10.1016/j.cell.2019.11.020 · Cited by 1,381
Self-citationTranscriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., et al. (2018) · Science · doi:10.1126/science.aat8127 · Cited by 1,247
Self-citationDuman, R. S., Sanacora, G., & Krystal, J. H. (2019) · Neuron · doi:10.1016/j.neuron.2019.03.013 · Cited by 1,026
Metadata
- Authors
- 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., Liu, C., White, K. P., CommonMind Consortium, PsychENCODE Consortium, iPSYCH-BROAD Working Group, Horvath, S., Geschwind, D. H., Sestan, N., Vaccarino, F., Gerstein, M., Weissman, S., Pochareddy, S., State, M., Knowles, J., Farnham, P., Akbarian, S., Pinto, D., Van Baekl, H., Dracheva, S., Jaffe, A., Hyde, T., Zandi, P., Crawford, G., Sullivan, P., Thompson, W. K., Mortensen, P. B., Agerbo, E., Pedersen, M. G., Pedersen, C. B., Mors, O., Børglum, A. D., Nordentoft, M., Hougaard, D. M., Bybjerg-Grauholm, J., Bækvad-Hansen, M., Martin, A. R., Dumont, A., Stevens, C., Churchhouse, C., Howrigan, D. P., Palmer, D. S., Robinson, E. B., Satterstrom, K. F., Cerrato, F., Huang, H., Goldstein, J., Moran, J., Julian, J. M., Kimberly, M., Patrick, C., Turley, P., Walters, R., Belliveau, R., Ripke, S., Poterba, T., Daly, M. J., Neale, B., Fromer, M., Roussos, P., Johnson, J. S., Shah, H. R., Mahajan, M. C., Schadt, E., Haroutunian, V., Ruderfer, D. M., Buxbaum, J. D., Sieberts, S. K., Dang, K., Logsdon, B., Mangravite, L. M., Peters, M., Gur, R. E., Hahn, C.-G., Devlin, B., Klei, L. L., Lewis, D., Lipska, B., Hirai, K., Toyoshiba, H., & Domenici, E.
- Affiliations
- University of California, Los Angeles (US)
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
- Mental Health Services (DK)
- University of Copenhagen (DK)
- Central South University (CN)
- University of Chicago (US)
- ORCID
- Gandal, Michael J.
- Haney, Jillian R.
- Parikshak, Neelroop N.
- Ramaswami, Gokul
- Schork, Andrew J.
- Appadurai, Vivek
- Buil, Alfonso
- Werge, Thomas M.
- Liu, Chunyu
- White, Kevin P.
- Horvath, Steve
- Geschwind, Daniel H.
- Vaccarino, Flora
- Gerstein, Mark
- Pochareddy, Sirisha
- State, Matthew
- Knowles, James
- Farnham, Peggy
- Akbarian, Schahram
- Pinto, Dalila
- Dracheva, Stella
- Jaffe, Andrew
- Hyde, Thomas
- Zandi, Peter
- Crawford, Gregory
- Thompson, Wesley Kurt
- Mortensen, Preben Bo
- Agerbo, Esben
- Pedersen, Carsten Bøcker
- Mors, Ole
- Børglum, Anders D.
- Nordentoft, Merete
- Martin, Alicia R.
- Stevens, Christine
- Howrigan, Daniel P.
- Palmer, Duncan S.
- Robinson, Elise B.
- Cerrato, Felecia
- Huang, Hailiang
- Goldstein, Jacqueline
- Moran, Jennifer
- Turley, Patrick
- Walters, Raymond
- Ripke, Stephan
- Poterba, Timothy
- Daly, Mark J.
- Neale, Benjamin
- Fromer, Menachem
- Roussos, Panos
- Johnson, Jessica S.
- Schadt, Eric
- Haroutunian, Vahram
- Ruderfer, Douglas M.
- Buxbaum, Joseph D.
- Sieberts, Solveig K.
- Dang, Kristen
- Logsdon, Ben
- Mangravite, Lara M.
- Peters, Mette
- Gur, Raquel E.
- Devlin, Bernie
- Klei, Lambertus L.
- Lewis, David
- Hirai, Keisuke
- Toyoshiba, Hiroyoshi
- Domenici, Enrico
- Venue
- Science
- Published
- 2018-02-09
- Volume
- 359
- Issue
- 6376
- Pages
- 693-697
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC5898828
- OpenAlex
- W2337092408
- Semantic Scholar
- cb5b301ef027f52b4cad525396f7946fd18fff35
- Cited by
- 1,095
- References
- 130
- Citations by year
- 2026: 107 · 2025: 92 · 2024: 111 · 2023: 97 · 2022: 122 · 2021: 160 · 2020: 155 · 2019: 163 · 2018: 81
- FWCI
- 84.93
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- National Institute of Mental Health (MH106438, MH094714, MH103339, MH110920, MH103340)
- Simons Foundation (206733)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- mental illness, polygenic overlap, gene expression, transcriptional dysregulation, molecular neuropathology, autism spectrum disorder, schizophrenia, bipolar disorder, depression, alcoholism, single nucleotide polymorphisms, pleiotropy
- MeSH terms
- Mental Disorders, Cerebral Cortex, Gene Expression Regulation, Humans, Nervous System Diseases, Transcription, Genetic, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Gene Expression Profiling
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.
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
