Literature DB >> 34068138

A Comprehensive Review on the Role of Non-Coding RNAs in the Pathophysiology of Bipolar Disorder.

Soudeh Ghafouri-Fard1, Elham Badrlou1, Mohammad Taheri2, Kenneth M Dürsteler3,4, Annette Beatrix Brühl5, Dena Sadeghi-Bahmani5,6,7, Serge Brand5,6,8,9.   

Abstract

AIM: Bipolar disorder is a multifactorial disorder being linked with dysregulation of several genes. Among the recently acknowledged factors in the pathophysiology of bipolar disorder are non-coding RNAs (ncRNAs).
METHODS: We searched PubMed and Google Scholar databases to find studies that assessed the expression profile of miRNAs, lncRNAs and circRNAs in bipolar disorder.
RESULTS: Dysregulated ncRNAs in bipolar patients have been enriched in several neuron-related pathways such as GABAergic and glutamatergic synapses, morphine addiction pathway and redox modulation.
CONCLUSION: Altered expression of these transcripts in bipolar disorder provides clues for identification of the pathogenesis of this disorder and design of targeted therapies for the treatment of patients.

Entities:  

Keywords:  bipolar disorder; circRNA; lncRNA; miRNA

Year:  2021        PMID: 34068138      PMCID: PMC8152970          DOI: 10.3390/ijms22105156

Source DB:  PubMed          Journal:  Int J Mol Sci        ISSN: 1422-0067            Impact factor:   5.923


1. Introduction

Bipolar disorder (BD) is a multifactorial disorder characterized by the occurrence of severe mood impairment episodes, neuropsychological complications, immunological alterations, and perturbation in personal/social functions [1]. As one of the main sources of disability all over the world [2], BD is associated with premature death from the co-existence of other medical conditions as well as suicide attempts [3,4]. Several genetic and environmental parameters have been recognized to modulate the risk of BD, yet most of them being liked with a number of other mental disorders as well. The causal link between a few of these risk factors and BD has been established [5]. Among the recently acknowledged factors in the pathophysiology of BD are non-coding RNAs (ncRNAs) [6]. These transcripts participate in the epigenetic marking of several genes through modulating chromatin configuration and RNA editing. Their binding with complementary sequences in the genome might alter methylation or RNA sites. Moreover, long ncRNAs (lncRNAs) are implicated in the complicated regulatory systems that control the expression of target genes [7]. Transcript profiling in autopsy samples of medial frontal gyrus from bipolar patients and non-psychiatric controls have shown differential expression of ten lncRNA transcripts and a global higher number of alternative spliced variants in these patients [6]. Other types of ncRNAs such as microRNAs (miRNAs) and circular RNAs (circRNAs) have also been dysregulated in brain tissues or peripheral blood of patients with BD [6,8]. We performed a comprehensive search in PubMed and Google Scholar databases to find studies that assessed expression profile of miRNAs, lncRNAs and circRNAs in BD. This study is study is a narrative review and studies have been selected and discussed based on preference/choices from the authors. We included studies that reported dysregulation of ncRNAs between BD patients and normal controls. We also included data regarding the expression profile of targets of ncRNAs whenever this data was provided in the original articles.

2. CircRNAs and BD

CircRNAs have a circular secondary structure. This structure is formed by the rear-splicing of a single-stranded linear RNA and the creation of a covalent link. These procedures lead to the formation of an encircled non-polyadenylated RNA structure. Compared with linear RNAs, circRNAs have higher stability resulting from a lack of accessible ends for exoribonucleases. They are about 0.1–10% of linear transcripts in eukaryotes [9]. CircRNAs participate in brain development and integrity of neurons [10,11]. A number of studies have demonstrated the release of brain-specific circRNAs into the peripheral blood in the course of neurological disease, potentiating these transcripts as biomarkers for showing disease progression or response to therapies [9]. Few studies have assessed the expression of circRNAs in brain samples of patients with BD obtained through autopsy. Luykx et al. have shown up-regulation of two circRNAs in brain tissues of bipolar patients. These transcripts were originated from the NEBL and EPHA3 loci, respectively [6]. The latter locus is involved in the development of CNS. Eph receptors of the protein-tyrosine kinase family participate in the production of neurotransmitters, construction of dendritic spines, and synaptic and postsynaptic events [12]. Moreover, they contribute to memory-associated functions [13] and modulation of anxiety [14], two functions that are disturbed in bipolar patients. Authors have suggested circRNA molecules as possible markers for the diagnostic assessment of patients with BD [6]. Zimmerman et al. have recently shown expression of circHomer1a, a neuron-associated circRNA in the frontal cortex. Notably, expression of this circRNA was decreased in both the prefrontal cortex (PFC) and induced pluripotent stem cell-originated neurons of patients with BD. CircHomer1a has been shown to regulate the expression of several splicing variants of genes participating in synaptic plasticity and psychiatric disorders. Thus, circHomer1a modulates synaptic gene activity and intellectual flexibility [15]. Table 1 and Table 2 summarize the results of studies that assessed the expression of circRNAs in BD.
Table 1

Summary of function of up-regulated circRNAs in BD.

circRNANumber of Clinical SamplesType of StudyFalse Discovery RateFunctionRef
cNEBLpostmortem human medial frontal gyrus tissues from BPD cases (n = 4) and normal subjects (n = 4)High throughput analysisFDR < 0.05-[6]
cEPHA3High throughput analysis FDR < 0.1EPHA3 participates in the neurodevelopment.
Table 2

Summary of function of down-regulated circRNAs in BD (BD: bipolar disorder, SZ: schizophrenia).

circRNANumber of Clinical SamplesTargets/Regulatorsp ValueFunctionRef
circHomer1aHuman OFC postmortem brain tissues of BD patients (n = 32) and healthy controls (n = 34)RNA-binding protein HuDp < 0.01circHomer1a is originated from HOMER1, a gene regulating neuronal excitability and synaptic plasticity. This gene is down-regulated in the OFC and stem cells-originated neurons of BD patients.[15]

3. LncRNAs and BD

Dysregulation of numerous lncRNAs has been described in peripheral blood and brain tissues of patients with BD. Hu et al. have profiled transcriptome in post-mortem brain tissues of patients with schizophrenia and BDs as well as healthy subjects. They reported differential expression of several long intergenic RNAs in various brain regions of bipolar patients. They showed that these lncRNAs have brain region-specific signatures and are mostly enriched in some pathways including immune system development and oligodendrocyte differentiation. Altered expression of these lncRNAs in patients was explained by modification of DNA methylation alteration [16]. Ji et al. have reported up-regulation of the XIST gene, the principal regulator of X chromosome inactivation (XCI) in the lymphoblastoid cells and brain tissues of female subjects with either BD or major depressive disorder. This up-regulation was accompanied by over-expression of the XCI escapee gene KDM5C. Authors have suggested that up-regulation of XIST might cause or result from delicate changes in XCI [17]. Table 3 summarizes the studies which reported up-regulation of lncRNAs in bipolar patients.
Table 3

Summary of function of up-regulated lncRNAs in BD (BD: bipolar disorder, SZ: schizophrenia).

lncRNANumber of Clinical SamplesAssessed Cell LineTargets/Regulatorsp ValueType of StudyFunctionRef
PTCSC3Whole blood sample of BD patients with manic episode (n =13)--p = 2.39 × 10−4High throughput analysisPTCSC3 gene is reported to be associated with thyroid cancer.[18]
CCAT2Peripheral blood specimens BD patients (n = 50) and healthy subjects (n = 50)--p = 0.006Candidate molecule analysisCCAT2 is an oncogenic lncRNA in numerous neoplasms that enhances cell proliferation and suppresses apoptosis.[19]
TUG1- - p < 0.001Candidate molecule analysisTUG2 is an oncogenic lncRNA in numerous neoplasms that enhances cell proliferation and suppresses apoptosis.[19]
PANDA- - p = 0.004 Candidate molecule analysisPANDA is an oncogenic lncRNA in numerous neoplasms that enhances cell proliferation and suppresses apoptosis.[19]
DISC2Peripheral blood mononuclear cells (PBMCs) of BD patients (n = 50) and controls (n = 50)-hsa-miR-92a-2-5p, hsa-miR363-5p, hsa-miR-1285-3p and hsa-miR-1268a p = 0.0015Candidate molecule analysis DISC2 may regulate DISC1 expression.[20]
XISTLymphoblastoid cells were from healthy females (n = 36) and female patients with either BD or recurrent major depression (n = 60)Lymphoblastoid cell linesTSIX, FTX, JPXp = 1 × 10−7Candidate molecule analysisXIST is the master gene for XCI.[17]
FTXLymphoblastoid cell linesXISTp < 0.1Candidate molecule analysisFTX is a positive regulator of XIST expression.[17]
Ghafelehbashi et al. have assessed the expression of IFNG-AS1 lncRNA, and IFNG and IL-1B mRNAs in peripheral blood of BD patients compared with healthy subjects. They reported down-regulation of IFNG-AS1 in patients and its correlation with IFNG expression. Moreover, expression of IL-1B was decreased in patients compared with controls. Thus, inflammatory lncRNAs might participate in the pathogenesis of BD [21]. Hu et al. have reported down-regulation of ENSG00000228794 in patients with BD. This lncRNA resides in a genomic region that is linked with BD. ENSG00000228794 is possibly implicated in calcium ion transport, thus it can modulate synaptic plasticity [16]. Table 4 summarizes the results of studies that reported down-regulation of lncRNAs in BD.
Table 4

Summary of function of down-regulated lncRNAs in BD (BD: bipolar disorder, SZ: schizophrenia).

lncRNANumber of Clinical SamplesAssessed Cell LineTargets/RegulatorsSignaling Pathwaysp ValueType of StudyFunctionRef
OIP5-AS1Peripheral blood samples of BD patients (n = 50) and healthy controls (n = 50)---p = 0.001Candidate genes analysisOIP5-AS1 is as an oncogene that enhances cell proliferation and suppresses of apoptosis.[19]
IFNG-AS1Blood samples of BD patients (n = 30) and healthy control individuals (n = 32)-IFNG-p < 0.0001High throughput analysisIFNG-AS1 facilitates IFN-γ expression through association with the WDR methyltransferases and subsequent increase in H3K4 methylation at the IFNG locus.[21]
ENSG00000228794Post-mortem brain samples of patients with SZ and BD and control subjects (n = 82)--Calcium signalingp < 0.05High throughput analysisENSG00000228794 is located in a genomic region linked with BD and partakes in calcium ion transport. [16]
TSIXLymphoblastoid cells were from healthy females (n = 36) and female patients with either BD or recurrent major depression (n = 60)Lymphoblastoid cell linesXIST-p < 0.01Candidate genes analysisTSIX is a negative regulator of XIST expression.[17]
MALAT1Peripheral blood samples of BD patients (n = 50) and healthy controls (n = 50)PBMCshsa-miR-17-5p, hsa-miR-106a-5p, hsa-miR-30c-5p, hsa-miR-20b-5p, hsa-miR-503, hsa-miR-92b-3p, hsa-miR-1224-3p-p < 0.0001Candidate molecule analysisMALAT1 takes part in the regulation of genes involved in synaptogenesis.[22]

4. miRNAs and BD

The expression profile of miRNAs has been vastly assessed in different biological sources of patients with BD including whole blood, lymphoblastoid cell lines, brain tissues or extracellular vesicles. Squassina et al. have assessed miRNAs signature in lymphoblastoid cell lines from bipolar patients who deceased by suicide and those with low risk of suicide. They reported higher miR-4286 levels while lower miR-186-5p in lymphoblastoid cell lines obtained from suicide attempters compared with the low-risk group and healthy controls. Conversely, expression of miR-4286 was reduced in postmortem brains of bipolar patients who attempted suicide compared with controls, yet it could not yield the level of significance. Exposure of human neural progenitor cells with lithium down-regulates expression of miR-4286 [23]. Lee et al. have reported abnormal expression of a number of miRNAs in the serum samples of bipolar patients. Among dysregulated miRNAs has been miR-7-5p which was up-regulated in bipolar patients [8]. Notably, miR-7 has been previously shown to suppress the healing of damaged peripheral nerves by altering the migration and proliferation of neural stem cells [8]. Moreover, this miRNA has been over-expressed in the neocortex of superior temporal lobes of patients with Alzheimer’s disease [24]. Choi et al. have extracted extracellular vesicles (EVs) from the anterior cingulate cortex. They reported over-expression of miR-149 in bipolar patients compared to controls. They also validated dysregulation of both miRNAs in EVs extracted from brains of an animal model of depressive-like manners [25]. Figure 1 shows the molecular mechanisms of participation of miR-34a in the pathogenesis of BD.
Figure 1

Expression of miR-34a is increased in BD. This miRNA binds with 3’ UTR of SHAK3 to decrease its expression. Expression of this protein is correlated with CYLD levels [26,27]. CYLD is a deubiquitinase that targets PSD-95. The latter protein participates in the maturation and function of synapses [28].

Table 5 summarizes the studies which reported up-regulation of miRNAs in BD.
Table 5

Summary of function of up-regulated miRNAs in BD (BD: bipolar disorder, SZ: schizophrenia).

microRNANumber of Clinical SamplesAssessed Cell LineTargets/RegulatorsSignaling Pathwaysp ValueType of StudyFunctionRef
miR-7-5pWhole blood samples of BD-II patients (n = 102) and controls (n = 118)-BDNFGABAergic and glutamatergic synapses and TGF-beta, Hippo, and FoxO signalingp < 0.001High throughput analysismiR-7 has a role in inhibition of the repair of peripheral nerve damage by affecting the migration and proliferation of neural stem cells.[8]
miR-142-3p-TNF-αp < 0.0001High throughput analysismiR-142-3p may modulate the BMAL1 gene and regulate circadian functions. [8]
miR-221-5p--p < 0.0001High throughput analysismiR-221 is potentially involved in atherosclerosis.[8]
miR-370-3p--p < 0.0001High throughput analysismiR-370 is reduced in brain tissue of depressed animals.[8]
miR-23b-3p--p = 0.006High throughput analysismiR-23b may have an anti-inflammatory role in central nervous system inflammation.[8]
miR-4286Lymphoblastoid cell line cultures from patients with BD who died by suicide (SC, n = 7) and with low risk of suicide (LR, n = 11) and 12, non-suicidal controlsLymphoblastoid cell lines (LCLs)PRKAB2, PTPRF, PIK3R3, CREB1, PPARGC1B, PIK3R1, CREB3L2, PTPA, PTEN RELA, PRKAG1, PTPN11, PRKCB, SOCS3, INSR, PYGB, PPARAInsulin resistance signaling pathwayp = 0.000043High throughput analysismiR-4286 might be a specific biomarker of suicide.[23]
hsa-miR-155-3pLymphoblastoid cell line cultures from BD patients excellent responders (ER, n = 12) and non-responders (NR, n = 12) to lithiumLymphoblastoid cell linesSP4-p = 0.0003High throughput analysishsa-miR-155-3p was up-regulated in ER. It partakes in inflammatory response and modulates differentiation and activation of innate and adaptive immune systems.[29]
miR-223Orbitofrontal cortex of SZ (n = 29; 20 males and 9 females), BD (n = 26; 12 males and 14 females), and unaffected controls (n = 25; 21 males and 4 females) -GRIN2B, GRIA2-p < 0.001High throughput analysismiR-223 regulates glutamate receptors. miR-223 expression is negatively correlated with levels of its targets GRIN2B and GRIA2.[30]
miR-193b-3p---p < 0.05High throughput analysismiR-193a-3p was upregulated in both BD and SZ.[30]
miR-330-3p---p < 0.05High throughput analysismiR-330-3p has been over-expressed in the blood of subjects with BD and monopolar depression.[30]
miR-28a-3p---0.05 < p <0.10High throughput analysismiR-28a-3p is in the same family as miR-708, a miRNA that is associated with risk of BD.[30]
miR-1260---p < 0.05High throughput analysis-[30]
miR-185-5pPlasma samples of patients with BD type I (n = 69; 15 depressed, 27 manic, 27 euthymic) and healthy controls (n = 41)-Tyrosine kinase receptor type 2PI3K-Aktp = 0.001High throughput analysismiR-185-5p is a target miRNA for depression.[31]
miR-29a-3pPeripheral blood of BD I patients (n = 58, 19 manic, 39 euthymic) and healthy controls (n = 51)--PI3K-Akt, TGF-beta p = 0.035Candidate analysis-[32]
miR125a-3pp = 0.014
miR-106b-5p-IL-10PI3K-Akt, TGF-betap = 0.014Candidate analysismiR-106 might be involved in immunomodulatory aspects of BD.[32]
miR-107-GRIN2A, SLC1A4PI3K-Akt, TGF-betap = 0.011Candidate analysismiR-107 is up-regulated in manic and euthymic patients.[32]
hsa-miR-150-5p, hsa-miR-25-3p, hsa-miR-451a, hsa-miR-144-3pPlasma samples from drug-free psychotic bipolar patients (n = 15) and HC (n = 9)---p < 0.01High throughput analysisThese miRNAs were upregulated in patients.[33]
hsa-miR-4516, hsa-miR-6808-5p, hsa-miR-7977, hsa-miR-1185-2-3p, hsa-miR-6791-5p, hsa-miR-3194-5p, hsa-miR-6090, hsa-miR-3135bPeripheral blood EV of BD patients (n = 20) and age- and sex-matched normal controls (n = 21)--Axon guidance mediated by netrin, endothelin signaling pathway, 5HT2 type receptor-mediated signaling, beta1 and beta2 adrenergic receptor and the androgen receptor signaling pathwaysp < 0.05High throughput data miningThese miRNAs are related to neuron development. [34]
hsa-miR-29c-3p --p = 0.010514High throughput data miningIncreased levels of miR-29c have been detected in EVs isolated from post-mortem prefrontal cortex (BA9) of patients.[34]
hsa-miR-7975 --p = 0.048192High throughput data mininghsa-miR-7975 is associated with the brain.[34]
hsa-miR-21-5p NTN1, NTNG1,-p = 0.028475High throughput data miningThe increased levels of miR-22 in EVs are supported by findings of upregulation of these miRNAs in the prefrontal cortex of patients with BD.[34]
hsa-miR-142-3p NTN3, NTNG1, NTNG2-p = 0.019266High throughput data miningNTN3, NTNG1, NTNG2 are targeted by hsa-miR-142-3p.[34]
hsa-miR-22-3p, hsa-miR-92a-3p NTN3, NTN4, NTNG1, NTNG2-p < 0.05High throughput data miningNTN3, NTN4, NTNG1, NTNG2 are targeted by hsa-miR-22-3p, hsa-miR-92a-3p. [34]
hsa-miR-1983 frontal cortex miRNA expression datasets (N for BD = 30–36 per dataset, N for controls = 28–34 per dataset) -GPX4Redox modulation pathwaysp < 0.05High throughput data miningThese are the top 10th percentile of up-regulated miRNAs that target redox modulators ranked for their ability to discriminate between BD and controls in Vladimirov dataset.[35]
hsa-miR-601-ATP2B4p < 0.05High throughput data mining[35]
hsa-miR-659-SOD2, ATP5A1p < 0.05High throughput data mining[35]
hsa-miR-192-TXN2, UQCRC2, ATP5L, PXDN, TXNIP, COX5A, TXN2p < 0.05High throughput data mining[35]
hsa-miR-346-NDUFA1, COX5Ap < 0.05High throughput data mining[35]
hsa-miR-9*-ATP5F1p < 0.05High throughput data mining[35]
hsa-miR-301a-ATP5B, COX10, TXNIP, BCL2L11, NDFUA7, TXNRD3, COX7A2, OXA1L, MGST1, PXDN, SOD2, COX5B, NDUFA5, UQCRQp < 0.05High throughput data mining[35]
hsa-miR-199a-3p-ATP5B, UQCRC2, COX10, TXNIP, BCL2L11, PTGS2, GLRX2, NDUFA2, NDUFC2, NDUFA12p < 0.05High throughput data mining[35]
hsa-miR-34a-TXNIP, NDUFS1, SOD2, PRDX5, NDUFV1p < 0.05High throughput data mining[35]
hsa-miR-145-NDUFS1, NDUFA4p < 0.05High throughput data mining[35]
hsa-miR-27a-PPA1, TXNIP, ATP2B4, ATP5SL, PRDX1, PRDX4, FOXO3, NDUFA8, CAT, PXDN, SOD1, FOXO1, NDUC2, GSTO1, ATP5G3, NDUFV3, NDUFS2, NDUFS4, NDUFV1, PRDX3, PPA1, GLRX5p < 0.05High throughput data mining[35]
hsa-miR-92a-1*-BCS1L, NDUFS1, SDHB, OXA1Lp < 0.05High throughput data mining[35]
hsa-miR-103-MGST1, TXN2, NDUFS8, ATP5B, PRDX4, ATP5A1, OXA1L, NDUFS2, NOS3, COX5A, TXNRD3p < 0.05High throughput data mining[35]
hsa-miR-196b-ATP5G3, MT-ATP6, BCL2L2, BCL2L12, ATP2B4, GLRX3, NDUFC2, OXA1L, NDUFV3p < 0.05High throughput data mining[35]
hsa-miR-449a-ATP5H, TXNIP, FOXO1, BCL2L11, ATP6V0A2, NDUFS1p < 0.05High throughput data mining[35]
hsa-miR-196a-GPX1, ATP5G3, UQCRC2, TXR1, MTATP8, MT-ATP6, BCL2L12, ATP2B4, GLRX3, FOXO1, OXA1L, NDUFV3, NDUFC2, GSTK1p < 0.05High throughput data mining [35]
hsa-miR-675-SOD2, PXDNp < 0.05High throughput data mining [35]
hsa-miR-184 -BCL2A1p < 0.05High throughput data mining [35]
hsa-miR-200c -MT-ATP6, MGST1p < 0.05High throughput data mining [35]
hsa-miR-200b -BCL2, GLRX5p < 0.05High throughput data mining [35]
miR-149Extracellular vesicles (EVs) extracted from Human Postmortem Anterior Cingulate Cortices (BA24) Diagnosed With BD (n = 4) and Non-Psychiatric Control Cases (n = 6)Neuronal and glial cells-AKT1p = 0.0046Candidate analysismiR-149 suppresses glial proliferation. [25]
miR-30d-5pBlood samples of MD patienst (n = 20) and BD patienst (n =20, 10 type I and 10 type II) and healthy controls (n = 20, 15 females, 5 males)---p = 0.028High throughput analysisThe blood expression of miR-30d-5p was increased also in MD patients after AD treatment.[36]
miR140-3p---p = 0.027High throughput analysisThe blood expression of miR140-3p was increased also in MD patients after AD treatment.[36]
miR-330-5p-HTR2C, MAOA, DRD1, CAMKK2, NTRK3, CLOCK, CREB1, GABRA2, CNR1, MTHFR-p = 0.030High throughput analysismiR-330-5p regulates many targets participating in neuronal plasticity and neurodevelopment.[36]
miR-21-3p---p = 0.043High throughput analysismiR-21-3p is decreased in MD fibroblast cultures.[36]
miR-378a-5p---p = 0.042High throughput analysismiR-378a-5p is mainly involved in lipid and metabolism homeostasis.[36]
hsa-miR-345-5p-HTR2C, MAOA, DRD1, CAMKK2, NTRK3, CLOCK, CREB1, GABRA2, CNR1, MTHFR-p = 0.010High throughput analysismiR-345- 5p is predicted to regulate several target genes with a putative role in the shared pathogenetic mechanisms between MD and BD.[36]
miR-15bBlood of unaffected individuals at higher genetic risk of developing a mood disorder (n = 34) and control subjects (n = 46)--PI3K/Akt, PTENp = 0.0166Candidate gene analysis (20 miRNAs)miR-15b was over-expressed in the high-risk persons. It is involved in metabolism, angiogenesis, stress response, cancer, cardiovascular disease and neurodegenerative conditions.[37]
miR-132--PI3K/Aktp = 0.0249Candidate gene analysis (20 miRNAs)miR-132 was over-expressed in the high-risk persons. miR-132 is transcribed from a cluster of miRNAs that partake in neuronal development and function.[37]
miR-652-GABARB2, GABARB3, 5-HT1D, DISC1-p = 0.01076Candidate gene analysis (20 miRNAs)miR-652 was up-regulated in the high-risk individuals. miR-652 plays a central role in myeloid development.[37]
miR-34aPostmortem human brain samples from the cerebellum (lateral cerebellar hemisphere; 34 control and 29 BD samples)-ANK3, CACNB3, DDN, SHANK3WNT, cadherinp < 0.01Candidate analysismiR-34a expression is inversely associated with expression of ANK3 and CACNB3.[27,38]
miR-17-5p Human prefrontal cortex (Brodmann area 10) of 15 SZ, 15 MDD, 15 BD, and 15 controls---p = 0.0028High throughput analysis-[39]
miR29c-3pp = 0.049
miR-106b-5pp = 0.021
miR-579p = 0.0092
miR-29cPostmortem Human Prefrontal Cortex (Brodmann area 9, BA9) 8 SZ, 9 BD, and 13 controls--Wntp = 0.0237High throughput analysismiR29c is induced by canonical Wnt signaling.[40]
hsa-miR-188-5p, hsa-miR-196b, hsa-miR-32*, hsa-miR-187, hsa-miR-383, hsa-miR-297, hsa-miR-876-3p, hsa-miR-490-5p, hsa-miR-449b, hsa-miR-513-5p Dorsolateral prefrontal cortex tissue of control (n = 34), bipolar (n = 31), and schizophrenic (SZ, n = 35) subjects---p < 0.05High throughput analysis-[41]
hsa-miR-504Postmortem DLPFC sections from 35 cases with schizophrenia 35 cases with BD---p = 0.00003High throughput analysis-[42]
hsa-miR-145*p = 0.00080
hsa-miR-22*p = 0.00106
hsa-miR-145p = 0.00177
hsa-miR-133bp = 0.00190
hsa-miR-154*p = 0.00195
hsa-miR-889p = 0.00321
miR-34a 20 LCLs derived from bipolar I disorder (BPI) family members with and without LiCl treatment in cultureLymphoblastoid cell lines (LCLs)AP2A1, AP2S1, CD2AP, EIF1, and VCL-p = 0.023917Candidate analysis (13 miRNAs)miR-34a, miR-152, miR-155, and miR-221 were consistently up-regulated at treatment time point day 4 and day 16. [43]
miR-152p = 0.000405
miR-155p = 0.012045
miR-221p = 0.000073
miR-195-5p,Skin biopsies of 3 control and 3 BP patient Pluripotent Stem Cell-derived neuronsAXIN2, BDNF, CACNA1E, MIB1, NLGN1 and RELNAxon guidance, Mapk, Ras, Hippo, Neurotrophin and Wnt signaling pathwayp < 0.05Candidate molecule analysis(58 miRNAs)-[44]
miR-382-5pSYT4
miR-128-3p, miR-138-2-3p, miR-487b-3p, miR-744-3p-
Pisanu et al. have assessed miRNA profile in lymphoblastoid cell lines from BD patients who responded to lithium versus non-responders. They described differential expression of 31 miRNAs between these groups, among them were miR-320a and miR-155-3p. Expression of hsa-miR-320a was significantly lower in responders. Notably, targets of this miRNA participate in neuronal survival and differentiation, apoptosis, and plasticity of synapses [29]. Zhang et al. have demonstrated deceased circulating levels of miR-134 in bipolar patients as well as patients with schizophrenia or major depressive disorder compared with normal controls. Yet, the most significant downregulation of this miRNA has been described in major depressive disorder [45]. Table 6 summarizes the list of down-regulated miRNAs in BD.
Table 6

Summary of function of down-regulated miRNAs in BD (BP: bipolar disorder, SZ: schizophrenia).

microRNANumber of Clinical SamplesAssessed Cell LineTargets/RegulatorsSignaling Pathwaysp ValueType of StudyFunctionRef
miR-320aBD patients (excellent responders, n = 12; non-responders, n = 12) to lithiumLymphoblastoid cell lines CAPNS1-p < 0.0001High throughput analysisParticipates in response to lithium[29]
miR-134Whole blood samples of BD (n = 50) and controls (n = 50)-cAMP response element-binding protein (CREB)-p = 2.25 × 10−5Candidate molecule analysismiR-134 regulates dendritic spine development and plasticity.[45]
miR-186–5pLCLs from patients with BD who deceased by suicide (SC, n = 7) and with low risk of suicide (LR, n = 11) and 12, non-suicidal controls Lymphoblastoid cell lines (LCLs)--p = 0.032High throughput analysismiR-186–5p was lower in lithium-treated LCLs from SC compared to controls.[23]
miR-484Plasma samples of patients with BD type I and healthy controls (n = 41)--PI3K-Aktp < 0.001High throughput analysismiR-484 is linked with neurogenesis, mitochondrial network and redox modulations[31]
miR-142-3p--PI3K-Aktp = 0.001High throughput analysismiR-142-3p regulates signaling pathways during embryonic development and homeostasis.[31]
miR-652-3p--PI3K-Aktp < 0.001High throughput analysismiR-652 is linked with immune system and oxidative stress.[31]
hsa-miR-363-3p, hsa-miR-4454 + has-miR-7975, hsa-miR-873-3p, hsa-miR-548al, hsa-miR-598-3p, hsa-miR-4443, hsa-miR-551a, hsa-miR-6721-5pPlasma samples from drug-free psychotic BD cases (n = 15) and HC (n = 9)---p < 0.01High throughput analysisThese miRNAs were downregulated in patients.[33]
hsa-miR-1281, hsa-miR-6068, hsa-miR-8060, hsa-miR-4433a-5p, hsa-miR-1268b, hsa-miR-1238-3p, hsa-miR-188-5p, hsa-miR-6775-5p, hsa-miR-6800-3p, hsa-miR-3620-5p, hsa-miR-451a, hsa-miR-1227-5p, hsa-miR-7108-5p, hsa-miR-671-5p, hsa-miR-6727-5p, hsa-miR-6125, hsa-miR-6821-5p Peripheral blood EVs from BD patients (n = 20) and age- and sex matched normal subjects (n = 21)--Axon guidance mediated by netrin, endothelin signaling, 5HT2 type receptor-mediated signaling, beta1 and beta2 adrenergic receptor pathways, and the androgen receptor signaling pathwayp < 0.05High throughput analysisThese miRNAs were nominally downregulated between patients and controls. Pathway analyses identified some brain-relevant mechanisms enriched in these miRNAs, including axon guidance by netrin and the serotonin receptor pathway.[34]
hsa-miR-5739---p = 0.024667High throughput analysismiR-5739 is suggested to be highly associated with the brain.[34]
hsa-miR-133a-3pPeripheral blood EVs from BD type I (n = 20) and age- and sex matched healthy controls (n = 21)-NTN1, NTN3, NTNG1, NTNG2-p < 0.05High throughput data mining-[35]
hsa-miR-299-5p3 frontal cortex miRNA expression datasets -SOD2, GPX4Redox modulation pathwaysp < 0.05High throughput data miningThese are the top 10th percentile of decreased miRNAs that target redox modulators ranked for their ability to discriminate between BD and controls in Miller dataset.[35]
hsa-miR-197-SOD1, GCLC, TXN, COX8A, ATP2B4p < 0.05High throughput data mining[35]
hsa-miR-23a-NDUFA2, PPA1, GCLM, PTGS1, SOD2, PRDX4, PXDN, TTN, UQCRQ, NDUFV1, PRDX3, NDUFA3, TXNIP, ATP5O, TXNRD1p < 0.05High throughput data mining[35]
hsa-miR-450a-GCLC, NDUFA10,ATP5C1p < 0.05High throughput data mining[35]
hsa-miR-17-ATP5B, TXN, NDUFA10, TXNIP, MTATP6, BCL2L11, NDUFS1, OXA1L, ATP2B4, BCl2L13, TXN2, SOD2, SDHB, PXDN, FOXO1, BCL2, UQCRFS1, RXNRD2, GPX2, TXNRD2p < 0.05High throughput data mining[35]
hsa-miR-944-FOXO1p < 0.05High throughput data mining[35]
hsa-miR-19b-GCLC, ATP2B4, NDUFB2, COX6A1, FOXO3, PXDN, NDUFS3, COX10, NDUFB2p < 0.05High throughput data mining[35]
hsa-miR-503-COX10, NDUFS1,PXDNp < 0.05High throughput data mining[35]
hsa-miR-7-NDUFA4, SDHC, ATP5S, FOXO6, NDUFS1, GCLM, COX4I1, ATP2B4, TXN2, GSR, ATP5F1, SDHB, NDUFC2, PPA1, PRDX1p < 0.05High throughput data mining[35]
hsa-miR-199a-5p-NDUFA13, MGST2p < 0.05High throughput data mining [35]
hsa-miR-484-NOS3, PRDX1, COX7A2L, UQCRQ, GSTO1, UQCRFS1, ATP5J, BCL2L1, COX8A, PRDX1, MTATP6, PRDX4, COX5A, UQCRQp < 0.05High throughput data mining [35]
hsa-miR-424 -NDUFS1, COX7A2L, BCL2L11, UQCRHp < 0.05High throughput data mining [35]
miR-499Peripheral blood of adult women only, 17 UP (age: 50 ± 17) and 15 BP (age: 33 ± 13) patients---p = 0.008Candidate molecule analysismiR-499 is down-regulated in depression episodes of the BD patients compared with remission phase.[46]
miR-708---p = 0.02Candidate molecule analysismiR-708 is down-regulated in depression episodes of the BD patients compared with remission phase.[46]
miR-1908-KLC2-p = 0.004Candidate molecule analysismiR-1908 is down-regulated in depression episodes of the BD patients compared with remission phase. It is involved in lipid metabolism. Overexpression of miR-1908 in multipotent adipose-derived stem cells suppressed adipogenic differentiation and increased cell proliferation.[46]
miR-1908-5pTwo human NPC lines derived from dermal fibroblasts of either a control or a BD subject, treated with vehicle or 1 mM lithium or valproate for a weekHuman neural progenitor cells (NPCs)DLGAP4, GRIN1, STX1A, CLSTN1, GRM4NF-kappaBp < 0.05Candidate molecule analysismiR-1908 is an intronic miRNA of the fatty acid desaturase 1 (FADS1) gene.[47]
miR-132Human post-mortem anterior cingulate cortex (AnCg) tissue. (n = 8, BP; n = 15, MDD; n = 14, Control)---p < 0.05Candidate molecule analysis (29 miRNAs)-[48]
miR-133a---p < 0.05Candidate molecule analysis (29 miRNAs)While miR-133b levels did not change, miR-133a was differentially expressed in the AnCg of cohort of BP patients. [48]
miR-212---p < 0.05Candidate molecule analysis (29 miRNAs)miR-132 and miR-212 have been previously identified as differentially expressed in the DLPFC of SZ patients. [48]
miR-34a-NCOA1, PDE4B-p < 0.05Candidate molecule analysis (29 miRNAs)miR-34a expression is dysregulated in SZ and BP patients. miR-34a has been linked to acute responses to stress.[48]
miR-145-5p Human prefrontal cortex (Brodmann area 10) of 15 SZ, 15 MDD, 15 BD, and 15 controls---p = 0.0069High throughput-[39]
miR-485-5pp = 0.036
miR-370p = 0.041
miR-500a-5pp = 0.041
miR-34a-5pp = 0.048
hsa-miR-454*Postmortem DLPFC tissues of individuals with schizophrenia (SZ, n= 35) and BD (n = 35)---p = 0.00004High throughput-[42]
hsa-miR-29ap = 0.00005
hsa-miR-520c-3p p = 0.00018
hsa-miR-140-3pp = 0.00053
hsa-miR-767-5pp = 0.00102
hsa-miR-874p = 0.00181
hsa-miR-32p = 0.00209
hsa-miR-573p = 0.00227
miR-134Plasma sample of drug-free bipolar I patients (14 men and 7 women) and controls (n = 21)-Limk1-p = 0.009Candidate molecule analysis miR-134 regulates dendritic spine development though Limk1, that controls synaptic development, maturation and/or plasticity.[49]
miR-346DLPFC samples of SZ patients (n = 35), BD (n = 32), normal subjects (n =34)-CSF2RA-p = 0.086Candidate molecule analysis miR-346 gene lies in intron 2 of the GRID1 gene, which has been proposed to be important in SZ susceptibility. [50]
miR-19b-3pBlood plasma from 7 UD patients, 7 BD patients, and 6 controls-MAPK1, PTEN, and PRKAA1mTOR, FoxO, and the PI3-K/Akt signaling pathwayp = 0.0462Candidate molecule analysisMiR-19b-3p is a member of the miR-17/92 cluster, which controls lymphocyte growth, activation and proliferation.[51]
miR-10b-5pSkin biopsies of 3 control and 3 BP patient Pluripotent Stem Cell-derived neuronsANK3, BDNF, CAMK2G, DLGAP2, and NFASCAxon guidance, Mapk, Ras, Hippo, Neurotrophin and Wnt signaling pathwayp < 0.05Candidate molecule analysis(58 miRNAs)-[44]
miR-10b-3p-
Lim et al. have appraised the expression of miRNAs in peripheral blood of bipolar manic patients after 12 weeks of receiving asenapine or risperidone. They reported differential expression of several miRNAs [52]. Table 7 summarizes these miRNAs.
Table 7

Altered expression of miRNAs following treatment with antipsychotic drugs.

miRNAsExpression PatternTargets/Regulatorsp ValueFunction/CommentsRef
hsa-miR-18a-5pUp-p = 0.010761These miRNAs were up-regulated in the Asenapine Group in this study. These findings suggest that candidate miRNAs might participate in the mechanism of function of both antipsychotics in bipolar mania.[52]
hsa-miR-27a-3pp = 0.000161
hsa-miR-148b-3pp = 0.005188
hsa-miR-17-3pp = 0.018034
hsa-miR-106b-5pp = 0.00445
hsa-miR-106a-5pp = 0.006898
hsa-miR-20a-5pp = 0.002247
hsa-miR-17-5pp =0.011219
hsa-miR-19b-3pUp-p = 0.013057These miRNAs were up-regulated in the Asenapine Group. miR-19b, miR145, and miR-339, were formerly shown to be dysregulated in patients with autism spectrum disorder and with Alzheimer’s disease.[52]
hsa-miR-145-5pp = 0.029543
hsa-miR-339-5pp = 0.002185
hsa-miR-15a-5pUpBDNFp = 0.002422hsa-miR-15a-5p was up-regulated in the Asenapine Group. miR-15a is reported to be involved in an interaction with brain-derived neurotrophic factor.[52]
hsa-miR-30b-5pUp-p = 0.015608hsa-miR-30b-5p was up-regulated in the Asenapine Group. MiR-30b is associated with schizophrenia, a psychiatric disorder that has been shown to share common genetic roots with BD.[52]
hsa-miR-210-3pUp-p = 0.005157hsa-miR-210-3p was up-regulated in the Asenapine Group. Overexpression of miR-210 induces angiogenesis and neurogenesis.[52]
hsa-miR-92b-5pDown-p = 0.04547These miRNAs were down-regulated in the Asenapine Group in this study.[52]
hsa-miR-1343-5pp = 0.019721
hsa-miR-664b-5pDown-p = 0.035348These miRNAs were down-regulated in the Risperidone Group in this study.[52]
hsa-miR-6778-5pp = 0.047124
hsa-miR-146b-5pDownBDNFp = 0.005919hsa-miR-146b-5p was down-regulated in the Risperidone Group. miR-146b partakes in an interaction with brain-derived neurotrophic factor.[52]

5. Discussion

Several studies have reported aberrant expression of ncRNAs in bipolar patients. Moreover, the expression of ncRNAs is influenced by drugs used for these patients. For instance, a combination of drugs including lithium, valproate, lamotrigine and quetiapine has been shown to alter the expression of several genes including miRNAs in cultured human neurons. Among the differentially expressed genes have been miR-128 and miR-378 whose targets are enriched in neuron projection development and axonogenesis [53]. Thus, ncRNAs not only are involved in the pathogenesis of BD but also they might participate in the determination of response to prescribed drugs. NcRNA profiling has revealed specific alterations in certain lncRNAs and miRNAs in the manic state indicating a possible role of these transcripts in the determination of disease status [18]. Notably, lncRNAs have been the largest group of differentially expressed ncRNAs [18]. Such state-specific transcript signature potentiates ncRNAs as preferable biomarkers for early diagnosis of BD. Next generation sequencing technique has facilitated the identification of putative biomarkers for discrimination of bipolar patients from healthy subjects. A representative of this kind of experiment is the study conducted by Lee et al. which identified over-expression of miR-7-5p, miR-23b-3p, miR-142-3p, miR-221-5p, and miR-370-3p in bipolar patients compared with healthy individuals. The diagnostic accuracy of this panel of miRNAs was estimated to be 0.907 [8]. Dysregulated ncRNAs in bipolar patients have been enriched in several neuron-related pathways such as GABAergic and glutamatergic synapses, morphine addiction pathway, redox modulation as well as TGF-β, Wnt, Akt/PI3K, Hippo and FoxO pathways. Significance of a number of these pathways such as GABAergic and glutamatergic synapses signaling and TGF-β, Hippo and FoxO pathways have been recognized in the pathogenesis of BD [54,55]. The relevance of other pathways with this disorder should be appraised in future studies. Another functional annotation analysis of the differentially expressed coding and non-coding genes between patients with BD and healthy controls has shown remarkable enrichments of cellular pathways associated with angiogenesis and vascular system evolution [6]. The largest GWAS conducted in BD has reported that the most significant loci have been related to ion channels, neurotransmitter transporters and synaptic components. Yet, this study has not reported any indication for involvement of angiogenesis or vascular related loci in BD [56]. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion, circadian rhythm, and endocannabinoid signaling [56]. Notably, insulin resistance signaling pathway and circadian rhythm have been among the related pathways with dysregulated miRNAs in BD [8,23]. Finally, top genes existing in these pathways have been shown to encode Ca2+ and K+ channel subunits, MAPK and GABA-A receptor subunits [56], the latter being recognized as one of the most important pathways enriched among dysregulated ncRNAs in BD [8]. However, different studies have indicated abnormal activity of various signaling pathways in BD including immune response pathways [57], neuroplasticity, circadian rhythms and GTPase binding [58] and G protein-receptor dysregulation [59]. Such a heterogeneous range of biological pathways involved in BD might be related to distinct brain areas assessed in these investigations. Imminent investigations integrating particularly large sample sizes of patients with BD and comparison of transcriptome of coding and ncRNAs in different parts of the brain are required to find the most relevant pathways. Dysregulation of ncRNAs has been reported in other brain disorders as well. For instance, assessment of lncRNA signature using high-throughput sequencing has led to the recognition of aberrantly expressed lncRNAs in acute ischemic stroke. ENSG00000226482 has been among up-regulated lncRNAs. This lncRNA has a potential role in activation of the adipocytokine signaling [60]. Moreover, another experiment in the animal model of blast traumatic brain injury has shown elevation of plasma amounts of a brain-enriched miRNA, namely miR-127. This study has concluded that levels of sphingolipids, miR-128, and the let-7 family can show the presence of could blast traumatic brain injury. Moreover, a number of other miRNAs have been shown to serve as markers for a global level of damage after blast injury [61]. Moreover, miRNAs have been shown to serve as diagnostic markers for cognitive impairment. Certain panels of miRNAs have high sensitivity and specificity values in this regard [62]. Notably, several dysregulated ncRNAs in BD, are also dysregulated in other neuropsychiatric conditions such as schizophrenia or Alzheimer’s disease. Although this observation supports their potential roles in synaptic plasticity or neurodevelopment, it complicates the design of disease-specific diagnostic panels for BD. Among dysregulated miRNAs in peripheral blood of patients with BD have been miR-128, miR-133b, miR-29a, miR-370, miR-451, miR-874 and miR-9* which have been recognized as brain-enriched miRNAs [63]. Taken together, circRNAs, lncRNAs and miRNAs are regarded as potential contributors in the pathology of BD and putative biomarkers for diagnosis of this disorder. Their participation in the response of patients to the prescribed medications and their potential as therapeutic targets have been less studied. Thus, these research areas should be explored in future studies. NcRNAs are superior to transcripts of standard genes in the field of biomarker study as they represent the final step of function of the gene. As transcripts of standard genes should be translated to proteins to exert their function, the transcript level might not reflect the final level of the functional molecule. Moreover, miRNAs represent important regulators of gene expression as they can target several transcripts. Finally, studies reporting dysregulation of ncRNAs in BD have some limitations. For instance, they often suffer from various confounding factors. This is especially true for postmortem brain studies. Moreover, most of the studies reviewed in this manuscript may not have sufficient statistical power due to their small sample sizes. Analysis and interpretation of differences between data of postmortem brains and blood samples, differences between expression data on ncRNA and protein coding genes, and matching with GWAS-identified loci are other research fields that should be explored in future studies.

6. Conclusions

NcRNAs are potential markers for neurological disorders such as BD. Several ncRNAs have been found to be dysregulated in blood samples of bipolar patients. Molecular studies for identification of the mechanism of dysregulation of these transcripts in bipolar patients would facilitate the development of new therapeutic strategies.
  61 in total

1.  miR-149 and miR-29c as candidates for bipolar disorder biomarkers.

Authors:  Jason L Choi; Patricia F Kao; Elena Itriago; Yougen Zhan; James A Kozubek; Andrew G Hoss; Meredith G Banigan; Charles R Vanderburg; Amir H Rezvani; Jeanne C Latourelle; Howard Cabral; Ivana Delalle
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2017-02-12       Impact factor: 3.568

2.  Preliminary investigation of peripheral extracellular vesicles' microRNAs in bipolar disorder.

Authors:  Gabriel R Fries; Camila N C Lima; Samira S Valvassori; Giovana Zunta-Soares; Jair C Soares; Joao Quevedo
Journal:  J Affect Disord       Date:  2019-05-14       Impact factor: 4.839

3.  MicroRNA dysregulation in manic and euthymic patients with bipolar disorder.

Authors:  Mehmet Akif Camkurt; İbrahim Fatih Karababa; Mehmet Emin Erdal; Sultan Basmacı Kandemir; Gabriel R Fries; Hüseyin Bayazıt; Mustafa Ertan Ay; Hasan Kandemir; Özlem Izci Ay; Salih Coşkun; Erdinç Çiçek; Salih Selek
Journal:  J Affect Disord       Date:  2019-09-12       Impact factor: 4.839

4.  A MicroRNA gene is hosted in an intron of a schizophrenia-susceptibility gene.

Authors:  Yanglong Zhu; Ted Kalbfleisch; Mark D Brennan; Yong Li
Journal:  Schizophr Res       Date:  2009-03-04       Impact factor: 4.939

5.  Over-expression of XIST, the Master Gene for X Chromosome Inactivation, in Females With Major Affective Disorders.

Authors:  Baohu Ji; Kerin K Higa; John R Kelsoe; Xianjin Zhou
Journal:  EBioMedicine       Date:  2015-06-14       Impact factor: 8.143

Review 6.  A systematic review and meta-analysis of premature mortality in bipolar affective disorder.

Authors:  J F Hayes; J Miles; K Walters; M King; D P J Osborn
Journal:  Acta Psychiatr Scand       Date:  2015-03-03       Impact factor: 6.392

7.  Genome-wide association study identifies 30 loci associated with bipolar disorder.

Authors:  Eli A Stahl; Gerome Breen; Andreas J Forstner; Andrew McQuillin; Stephan Ripke; Vassily Trubetskoy; Manuel Mattheisen; Yunpeng Wang; Jonathan R I Coleman; Héléna A Gaspar; Christiaan A de Leeuw; Stacy Steinberg; Jennifer M Whitehead Pavlides; Maciej Trzaskowski; Enda M Byrne; Tune H Pers; Peter A Holmans; Alexander L Richards; Liam Abbott; Esben Agerbo; Huda Akil; Diego Albani; Ney Alliey-Rodriguez; Thomas D Als; Adebayo Anjorin; Verneri Antilla; Swapnil Awasthi; Judith A Badner; Marie Bækvad-Hansen; Jack D Barchas; Nicholas Bass; Michael Bauer; Richard Belliveau; Sarah E Bergen; Carsten Bøcker Pedersen; Erlend Bøen; Marco P Boks; James Boocock; Monika Budde; William Bunney; Margit Burmeister; Jonas Bybjerg-Grauholm; William Byerley; Miquel Casas; Felecia Cerrato; Pablo Cervantes; Kimberly Chambert; Alexander W Charney; Danfeng Chen; Claire Churchhouse; Toni-Kim Clarke; William Coryell; David W Craig; Cristiana Cruceanu; David Curtis; Piotr M Czerski; Anders M Dale; Simone de Jong; Franziska Degenhardt; Jurgen Del-Favero; J Raymond DePaulo; Srdjan Djurovic; Amanda L Dobbyn; Ashley Dumont; Torbjørn Elvsåshagen; Valentina Escott-Price; Chun Chieh Fan; Sascha B Fischer; Matthew Flickinger; Tatiana M Foroud; Liz Forty; Josef Frank; Christine Fraser; Nelson B Freimer; Louise Frisén; Katrin Gade; Diane Gage; Julie Garnham; Claudia Giambartolomei; Marianne Giørtz Pedersen; Jaqueline Goldstein; Scott D Gordon; Katherine Gordon-Smith; Elaine K Green; Melissa J Green; Tiffany A Greenwood; Jakob Grove; Weihua Guan; José Guzman-Parra; Marian L Hamshere; Martin Hautzinger; Urs Heilbronner; Stefan Herms; Maria Hipolito; Per Hoffmann; Dominic Holland; Laura Huckins; Stéphane Jamain; Jessica S Johnson; Anders Juréus; Radhika Kandaswamy; Robert Karlsson; James L Kennedy; Sarah Kittel-Schneider; James A Knowles; Manolis Kogevinas; Anna C Koller; Ralph Kupka; Catharina Lavebratt; Jacob Lawrence; William B Lawson; Markus Leber; Phil H Lee; Shawn E Levy; Jun Z Li; Chunyu Liu; Susanne Lucae; Anna Maaser; Donald J MacIntyre; Pamela B Mahon; Wolfgang Maier; Lina Martinsson; Steve McCarroll; Peter McGuffin; Melvin G McInnis; James D McKay; Helena Medeiros; Sarah E Medland; Fan Meng; Lili Milani; Grant W Montgomery; Derek W Morris; Thomas W Mühleisen; Niamh Mullins; Hoang Nguyen; Caroline M Nievergelt; Annelie Nordin Adolfsson; Evaristus A Nwulia; Claire O'Donovan; Loes M Olde Loohuis; Anil P S Ori; Lilijana Oruc; Urban Ösby; Roy H Perlis; Amy Perry; Andrea Pfennig; James B Potash; Shaun M Purcell; Eline J Regeer; Andreas Reif; Céline S Reinbold; John P Rice; Fabio Rivas; Margarita Rivera; Panos Roussos; Douglas M Ruderfer; Euijung Ryu; Cristina Sánchez-Mora; Alan F Schatzberg; William A Scheftner; Nicholas J Schork; Cynthia Shannon Weickert; Tatyana Shehktman; Paul D Shilling; Engilbert Sigurdsson; Claire Slaney; Olav B Smeland; Janet L Sobell; Christine Søholm Hansen; Anne T Spijker; David St Clair; Michael Steffens; John S Strauss; Fabian Streit; Jana Strohmaier; Szabolcs Szelinger; Robert C Thompson; Thorgeir E Thorgeirsson; Jens Treutlein; Helmut Vedder; Weiqing Wang; Stanley J Watson; Thomas W Weickert; Stephanie H Witt; Simon Xi; Wei Xu; Allan H Young; Peter Zandi; Peng Zhang; Sebastian Zöllner; Rolf Adolfsson; Ingrid Agartz; Martin Alda; Lena Backlund; Bernhard T Baune; Frank Bellivier; Wade H Berrettini; Joanna M Biernacka; Douglas H R Blackwood; Michael Boehnke; Anders D Børglum; Aiden Corvin; Nicholas Craddock; Mark J Daly; Udo Dannlowski; Tõnu Esko; Bruno Etain; Mark Frye; Janice M Fullerton; Elliot S Gershon; Michael Gill; Fernando Goes; Maria Grigoroiu-Serbanescu; Joanna Hauser; David M Hougaard; Christina M Hultman; Ian Jones; Lisa A Jones; René S Kahn; George Kirov; Mikael Landén; Marion Leboyer; Cathryn M Lewis; Qingqin S Li; Jolanta Lissowska; Nicholas G Martin; Fermin Mayoral; Susan L McElroy; Andrew M McIntosh; Francis J McMahon; Ingrid Melle; Andres Metspalu; Philip B Mitchell; Gunnar Morken; Ole Mors; Preben Bo Mortensen; Bertram Müller-Myhsok; Richard M Myers; Benjamin M Neale; Vishwajit Nimgaonkar; Merete Nordentoft; Markus M Nöthen; Michael C O'Donovan; Ketil J Oedegaard; Michael J Owen; Sara A Paciga; Carlos Pato; Michele T Pato; Danielle Posthuma; Josep Antoni Ramos-Quiroga; Marta Ribasés; Marcella Rietschel; Guy A Rouleau; Martin Schalling; Peter R Schofield; Thomas G Schulze; Alessandro Serretti; Jordan W Smoller; Hreinn Stefansson; Kari Stefansson; Eystein Stordal; Patrick F Sullivan; Gustavo Turecki; Arne E Vaaler; Eduard Vieta; John B Vincent; Thomas Werge; John I Nurnberger; Naomi R Wray; Arianna Di Florio; Howard J Edenberg; Sven Cichon; Roel A Ophoff; Laura J Scott; Ole A Andreassen; John Kelsoe; Pamela Sklar
Journal:  Nat Genet       Date:  2019-05-01       Impact factor: 38.330

8.  Whole Genome Expression Analyses of miRNAs and mRNAs Suggest the Involvement of miR-320a and miR-155-3p and their Targeted Genes in Lithium Response in Bipolar Disorder.

Authors:  Claudia Pisanu; Eleni Merkouri Papadima; Carla Melis; Donatella Congiu; Annalisa Loizedda; Nicola Orrù; Stefano Calza; Sandro Orrù; Carlo Carcassi; Giovanni Severino; Raffaella Ardau; Caterina Chillotti; Maria Del Zompo; Alessio Squassina
Journal:  Int J Mol Sci       Date:  2019-11-30       Impact factor: 5.923

9.  Systematically characterizing dysfunctional long intergenic non-coding RNAs in multiple brain regions of major psychosis.

Authors:  Jing Hu; Jinyuan Xu; Lin Pang; Hongying Zhao; Feng Li; Yulan Deng; Ling Liu; Yujia Lan; Xinxin Zhang; Tingting Zhao; Chaohan Xu; Chun Xu; Yun Xiao; Xia Li
Journal:  Oncotarget       Date:  2016-11-01

10.  Circulating microRNA 134 sheds light on the diagnosis of major depressive disorder.

Authors:  Han-Ping Zhang; Xiao-Lei Liu; Jian-Jun Chen; Ke Cheng; Shun-Jie Bai; Peng Zheng; Chan-Juan Zhou; Wei Wang; Hai-Yang Wang; Lian-Mei Zhong; Peng Xie
Journal:  Transl Psychiatry       Date:  2020-03-16       Impact factor: 6.222

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  5 in total

1.  LncRNAs in neuropsychiatric disorders and computational insights for their prediction.

Authors:  Cinmoyee Baruah; Prangan Nath; Pankaj Barah
Journal:  Mol Biol Rep       Date:  2022-09-12       Impact factor: 2.742

2.  Significant reduction of long non-coding RNAs expression in bipolar disorder.

Authors:  Zahra Maloum; Mohammad Taheri; Soudeh Ghafouri-Fard; Zeinab Shirvani-Farsani
Journal:  BMC Psychiatry       Date:  2022-04-12       Impact factor: 3.630

3.  Downregulation of long non-coding RNAs in patients with bipolar disorder.

Authors:  Zahra Maloum; Sahar Ramezani; Mohammad Taheri; Soudeh Ghafouri-Fard; Zeinab Shirvani-Farsani
Journal:  Sci Rep       Date:  2022-05-06       Impact factor: 4.996

Review 4.  The emerging role of long non-coding RNAs in schizophrenia.

Authors:  Guangxian Wu; Xinzhe Du; Zexuan Li; Yanhong Du; Jinzhi Lv; Xinrong Li; Yong Xu; Sha Liu
Journal:  Front Psychiatry       Date:  2022-09-26       Impact factor: 5.435

5.  Abnormal pattern of vitamin D receptor-associated genes and lncRNAs in patients with bipolar disorder.

Authors:  Reyhane Eghtedarian; Soudeh Ghafouri-Fard; Hamid Bouraghi; Bashdar Mahmud Hussen; Shahram Arsang-Jang; Mohammad Taheri
Journal:  BMC Psychiatry       Date:  2022-03-12       Impact factor: 3.630

  5 in total

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