Post-mortem molecular profiling of three psychiatric disorders

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Abstract

Background

Psychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets.

Methods

We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1.

Results

We compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients.

Conclusions

We provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0458-5) contains supplementary material, which is available to authorized users.

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Most cited references 33

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Primate anterior cingulate cortex: where motor control, drive and cognition interface.

T. Paus (2001)

Controversy surrounds the function of the anterior cingulate cortex. Recent discussions about its role in behavioural control have centred on three main issues: its involvement in motor control, its proposed role in cognition and its relationship with the arousal/drive state of the organism. I argue that the overlap of these three domains is key to distinguishing the anterior cingulate cortex from other frontal regions, placing it in a unique position to translate intentions to actions.

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A systematic review and meta-analysis of recovery in schizophrenia.

E. Jääskeläinen, P Juola, N Hirvonen … (2013)

Our primary aims were (a) to identify the proportion of individuals with schizophrenia and related psychoses who met recovery criteria based on both clinical and social domains and (b) to examine if recovery was associated with factors such as gender, economic index of sites, and selected design features of the study. We also examined if the proportions who met our definition of recovery had changed over time. A comprehensive search strategy was used to identify potential studies, and data were extracted for those that met inclusion criteria. The proportion who met our recovery criteria (improvements in both clinical and social domains and evidence that improvements in at least 1 of these 2 domains had persisted for at least 2 years) was extracted from each study. Meta-regression techniques were used to explore the association between the recovery proportions and the selected variables. We identified 50 studies with data suitable for inclusion. The median proportion (25%-75% quantiles) who met our recovery criteria was 13.5% (8.1%-20.0%). Studies from sites in countries with poorer economic status had higher recovery proportions. However, there were no statistically significant differences when the estimates were stratified according to sex, midpoint of intake period, strictness of the diagnostic criteria, duration of follow-up, or other design features. Based on the best available data, approximately, 1 in 7 individuals with schizophrenia met our criteria for recovery. Despite major changes in treatment options in recent decades, the proportion of recovered cases has not increased.

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Decision tree supported substructure prediction of metabolites from GC-MS profiles

Jan Hummel, Nadine Strehmel, Joachim Selbig … (2010)

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most widespread routine technologies applied to the large scale screening and discovery of novel metabolic biomarkers. However, currently the majority of mass spectral tags (MSTs) remains unidentified due to the lack of authenticated pure reference substances required for compound identification by GC-MS. Here, we accessed the information on reference compounds stored in the Golm Metabolome Database (GMD) to apply supervised machine learning approaches to the classification and identification of unidentified MSTs without relying on library searches. Non-annotated MSTs with mass spectral and retention index (RI) information together with data of already identified metabolites and reference substances have been archived in the GMD. Structural feature extraction was applied to sub-divide the metabolite space contained in the GMD and to define the prediction target classes. Decision tree (DT)-based prediction of the most frequent substructures based on mass spectral features and RI information is demonstrated to result in highly sensitive and specific detections of sub-structures contained in the compounds. The underlying set of DTs can be inspected by the user and are made available for batch processing via SOAP (Simple Object Access Protocol)-based web services. The GMD mass spectral library with the integrated DTs is freely accessible for non-commercial use at http://gmd.mpimp-golm.mpg.de/. All matching and structure search functionalities are available as SOAP-based web services. A XML + HTTP interface, which follows Representational State Transfer (REST) principles, facilitates read-only access to data base entities.

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Author and article information

Contributors

Richard M. Myers: 256-327-0431 , rmyers@hudsonalpha.org

Journal

Journal ID (nlm-ta): Genome Med

Journal ID (iso-abbrev): Genome Med

Title: Genome Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-994X

Publication date (Electronic): 28 July 2017

Publication date PMC-release: 28 July 2017

Publication date Collection: 2017

Volume: 9

Electronic Location Identifier: 72

Affiliations

[1 ]ISNI 0000 0004 0408 3720, GRID grid.417691.c, , HudsonAlpha Institute for Biotechnology, ; 601 Genome Way, Huntsville, AL 35806 USA

[2 ]ISNI 0000000106344187, GRID grid.265892.2, Department of Genetics, , The University of Alabama at Birmingham, ; Birmingham, AL USA

[3 ]ISNI 0000000086837370, GRID grid.214458.e, , Mental Health Research Institute, University of Michigan, ; Ann Arbor, MI USA

[4 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Department of Psychiatry and Human Behavior, College of Medicine, , University of California, ; Irvine, CA USA

[5 ]ISNI 0000000419368956, GRID grid.168010.e, Department of Psychiatry, , Stanford University School of Medicine, ; Stanford, CA USA

[6 ]ISNI 000000041936877X, GRID grid.5386.8, , Psychiatry, Weill Cornell Medical College, ; New York, NY USA

[7 ]ISNI 0000000086837370, GRID grid.214458.e, Department of Human Genetics, , University of Michigan, ; Ann Arbor, MI USA

[8 ]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, , Present address: Duke University, ; Durham, NC USA

[9 ]ISNI 0000 0001 2193 0096, GRID grid.223827.e, , Present address: University of Utah School of Medicine, ; Salt Lake City, UT USA

Article

Publisher ID: 458

DOI: 10.1186/s13073-017-0458-5

PMC ID: 5534072

PubMed ID: 28754123

SO-VID: 654131ff-f456-4199-8d95-0e21373ed968

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 13 October 2016

Date accepted : 6 July 2017

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100007440, J.B. and M.K. Pritzker Family Foundation;

Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;

Award ID: 5T32GM008361-21

Award Recipient : Ryne C. Ramaker

Funded by: FundRef http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;

Award ID: 1UL1TR001417-01

Award Recipient : Sara J. Cooper

Custom metadata

ScienceOpen disciplines: Molecular medicine

Keywords: schizophrenia,bipolar disorder,major depressive disorder,rna sequencing,metabolomics,egr1

Data availability:

ScienceOpen disciplines: Molecular medicine

Keywords: schizophrenia, bipolar disorder, major depressive disorder, rna sequencing, metabolomics, egr1

Post-mortem molecular profiling of three psychiatric disorders

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Most cited references 33

Primate anterior cingulate cortex: where motor control, drive and cognition interface.

A systematic review and meta-analysis of recovery in schizophrenia.

Decision tree supported substructure prediction of metabolites from GC-MS profiles

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