Cited by 1,247Autism Spectrum Disorder ResearchSchizophrenia research and treatmentRNA Research and Splicing

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 access
Gandal, Michael J., Zhang, Pan, Hadjimichael, Evi, Walker, Rebecca L., Chen, Chao, Liu, Shuang, Won, Hyejung, van Bakel, Harm, Varghese, Merina, Wang, Yongjun, Shieh, Annie W., Haney, Jillian, Parhami, Sepideh, Belmont, Judson, Kim, Minsoo, Moran Losada, Patricia, Khan, Zenab, Mleczko, Justyna, Xia, Yan, Dai, Rujia, Wang, Daifeng, Yang, Yucheng T., Xu, Min, Fish, Kenneth, Hof, Patrick R., Warrell, Jonathan, Fitzgerald, Dominic, White, Kevin, Jaffe, Andrew E., PsychENCODE Consortium, Peters, Mette A., Gerstein, Mark, Liu, Chunyu, Iakoucheva, Lilia M., Pinto, Dalila, Geschwind, Daniel H., Ashley-Koch, Allison E., Crawford, Gregory E., Garrett, Melanie E., Song, Lingyun, Safi, Alexias, Johnson, Graham D., Wray, Gregory A., Reddy, Timothy E, Goes, Fernando S., Zandi, Peter, Bryois, Julien, Jaffe, Andrew E., Price, Amanda J., Ivanov, Nikolay A., Collado-Torres, Leonardo, Hyde, Thomas M., Burke, Emily E., Kleiman, Joel E., Tao, Ran, Shin, Joo Heon, Akbarian, Schahram, Girdhar, Kiran, Jiang, Yan, Kundakovic, Marija, Brown, Leanne, Kassim, Bibi S., Park, Royce B., Wiseman, Jennifer R, Zharovsky, Elizabeth, Jacobov, Rivka, Devillers, Olivia, Flatow, Elie, Hoffman, Gabriel E., Lipska, Barbara K., Lewis, David A., Haroutunian, Vahram, Hahn, Chang-Gyu, Charney, Alexander W., Dracheva, Stella, Kozlenkov, Alexey, Belmont, Judson, DelValle, Diane, Francoeur, Nancy, Hadjimichael, Evi, Pinto, Dalila, van Bakel, Harm, Roussos, Panos, Fullard, John F., Bendl, Jaroslav, Hauberg, Mads E., Mangravite, Lara M, Peters, Mette A., Chae, Yooree, Peng, Junmin, Niu, Mingming, Wang, Xusheng, Webster, Maree J., Beach, Thomas G., Chen, Chao, Jiang, Yi, Dai, Rujia, Shieh, Annie W., Liu, Chunyu, Grennan, Kay S., Xia, Yan, Vadukapuram, Ramu, Wang, Yongjun, Fitzgerald, Dominic, Cheng, Lijun, Brown, Miguel, Brown, Mimi, Brunetti, Tonya, Goodman, Thomas, Alsayed, Majd, Gandal, Michael J., Geschwind, Daniel H., Won, Hyejung, Polioudakis, Damon, Wamsley, Brie, Yin, Jiani, Hadzic, Tarik, De La Torre Ubieta, Luis, Swarup, Vivek, Sanders, Stephan J., State, Matthew W., Werling, Donna M., An, Joon-Yong, Sheppard, Brooke, Willsey, A. Jeremy, White, Kevin P., Ray, Mohana, Giase, Gina, Kefi, Amira, Mattei, Eugenio, Purcaro, Michael, Weng, Zhiping, Moore, Jill, Pratt, Henry, Huey, Jack, Borrman, Tyler, Sullivan, Patrick F., Giusti-Rodriguez, Paola, Kim, Yunjung, Sullivan, Patrick, Szatkiewicz, Jin, Rhie, Suhn Kyong, Armoskus, Christoper, Camarena, Adrian, Farnham, Peggy J., Spitsyna, Valeria N., Witt, Heather, Schreiner, Shannon, Evgrafov, Oleg V., Knowles, James A., Gerstein, Mark, Liu, Shuang, Wang, Daifeng, Navarro, Fabio C. P., Warrell, Jonathan, Clarke, Declan, Emani, Prashant S., Gu, Mengting, Shi, Xu, Xu, Min, Yang, Yucheng T., Kitchen, Robert R., Gürsoy, Gamze, Zhang, Jing, Carlyle, Becky C., Nairn, Angus C., Li, Mingfeng, Pochareddy, Sirisha, Sestan, Nenad, Skarica, Mario, Li, Zhen, Sousa, Andre M. M., 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, Weissman, Sherman, Roychowdhury, Tanmoy, Abyzov, Alexej·2018·Science

Abstract

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

Crossref · 10.1126/science.aat8127

Cites

146 of 147 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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Show all 128 claims

  • It may state two separate claims as one. 85
  • Probably not a substantial claim. 25
102 of 102
  • 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.”
5 of 5

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  • Disease-associated module categories total 63, not 61

    Minor

    The stated categories contain 5, 22, and 36 modules, which sum to 63 rather than the reported 61 disease-associated modules.

    Reported 61 · recomputed 63

  • Eight reported BD genes are followed by eleven names

    Minor

    The text says eight genes showed consistent association, but the accompanying list names eleven.

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Research works printed but not linked: 2

  1. A. E. Jaffe et al . Developmental And Genetic Regulation Of The Human Cortex Transcriptome In Schizophrenia. bioRxiv 124321 [Preprint]. 22 November 2017. .10.1101/124321 · DOI
  2. PEC_DAC_RNAseq.py doi:.10.7303/syn12026837.1 · DOI

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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
Venue
Science
Published
2018-12-14
Volume
362
Issue
6420
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2904884010
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
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

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