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
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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]
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limma powers differential expression analyses for RNA-sequencing and microarray studies
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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
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Self-citationLD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
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Mercedes, L., Buczek, M. J., Kafadar, E., DiDomenico, G. E., Jung, B., Zimmerman, D., Schabdach, J., Himes, M. M., Sotardi, S. T., Vossough, A., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-106431 · Cited by 1
Self-citationHamed, N. F., Alqahtani, A. M., Alshaibani, F., Elsharif, S. M., Alamri, S. A. S., & Serhan, A. I. (2025) · Cureus · doi:10.7759/cureus.94607 · Cited by 1
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
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