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Schizophr Res. 2019 Aug 4. pii: S0920-9964(19)30316-0. doi: 10.1016/j.schres.2019.07.036. [Epub ahead of print]

Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses.

Author information

1
Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA.
2
MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK.
3
Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Behavior, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA; Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
4
School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.; Department of Anatomy, Faculty of Medical Sciences, University of Sri Jayawardenepura, Nugegoda, Sri Lanka; Faculty of Medicine, Sir John Kotelawala Defence University, Ratmalana, Sri Lanka.
5
School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, Australia.
6
School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.; Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia.
7
School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia; Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia.
8
School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.; Hunter Medical Research Institute, Newcastle, Australia; Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia.
9
Department of Anatomy, Faculty of Medical Sciences, University of Sri Jayawardenepura, Nugegoda, Sri Lanka.
10
School of Psychiatry, University of New South Wales, Kensington, New South Wales, Australia.
11
School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, Australia; Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia.
12
Center for Behavioral Genomics, Department of Psychiatry, Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA; Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, USA.
13
Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: stephen.glatt@psychgenelab.com.

Abstract

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.

KEYWORDS:

Biomarker; Bipolar disorder; Peripheral blood; Schizophrenia; Transcriptome

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