Abstract
Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs (MIR181B1 and MIR103A1) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3, may be mania state-specific markers. Additionally, four genes showed a nominal p-value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14, PYHIN1, UTRN, and DMXL2, and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine–cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness.
Highlights
Bipolar disorder (BD) is a severe and highly heritable psychiatric disorder, characterized by repeated manic episodes and depressive episodes [1]
Inpatients aged 20–65 years old who were diagnosed with BD and had a current manic episode according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition were referred by psychiatrists in several central and regional hospitals in Taipei
We focused on the manic feature in BD to capture state-specific transcriptome patterns using data from different platforms, and analyzed both coding and noncoding RNAs
Summary
Bipolar disorder (BD) is a severe and highly heritable psychiatric disorder, characterized by repeated manic episodes and depressive episodes [1]. Having the mania episode is a unique feature for diagnosing BD. The symptoms of mania episode include elevated mood, irritability, racing thoughts and rapid speech, inflated selfesteem, increased activity, reduced need for sleep, and engaged in risky behaviors [2]. Genome-wide association studies (GWAS) had huge impact on studying complex traits [5] and facilitated the identification of hundreds of genetic loci [6] and follow-up functional studies [7]. The mechanisms underlying episodic feature of BD are largely unknown. In this regard, the dynamic characteristics of transcriptome that are in response to physiological and environmental stimuli become a suitable genomic system to study the molecular alterations for manic episode
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