REVIEW article

Front. Pharmacol., 29 March 2023

Sec. Neuropharmacology

Volume 14 - 2023 | https://doi.org/10.3389/fphar.2023.1129186

The role of microRNAs in depression

  • 1. Institute of Molecular Medicine, Henan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng, Henan, China

  • 2. San-Quan College, Xinxiang Medical University, Xinxiang, Henan, China

  • 3. Kaifeng Key Laboratory for Infectious Diseases and Biosafety, Kaifeng, Henan, China

  • 4. Faculty of Basic Medical Subjects, Shu-Qing Medical College of Zhengzhou, Zhengzhou, Henan, China

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Abstract

Major depressive disorder (MDD) is a psychiatric disorder with increasing prevalence worldwide. It is a leading cause of disability and suicide, severely affecting physical and mental health. However, the study of depression remains at an exploratory stage in terms of diagnostics and treatment due to the complexity of its pathogenesis. MicroRNAs are endogenous short-stranded non-coding RNAs capable of binding to the 3’untranslated region of mRNAs. Because of their ability to repress translation process of genes and are found at high levels in brain tissues, investigation of their role in depression has gradually increased recently. This article summarizes recent research progress on the relationship between microRNAs and depression. The microRNAs play a regulatory role in the pathophysiology of depression, involving dysregulation of monoamines, abnormalities in neuroplasticity and neurogenesis, hyperactivity of the HPA axis, and dysregulation of inflammatory responses. These microRNAs might provide new clue for the diagnosis and treatment of MDD, and the development of antidepressant drugs.

1 Introduction

1.1 MicroRNAs

MicroRNAs (miRNAs) are short-stranded endogenous non-coding RNA molecules with a length of 19–25 nucleotides. A single microRNA can target hundreds of mRNAs and influence the expression of many genes (Friedman et al., 2009; Lu and Rothenberg, 2018). It is now established that about 70% of the known microRNAs are expressed in the brain and play critical roles in brain development through key signaling pathways involving synapse formation, neuronal plasticity, nerve growth, etc. MicroRNAs are endogenously encoded in the mammalian genome and are transcribed in the nucleus as primary transcripts (pri-miRNAs) which are hundreds of nucleotides in length. Pri-miRNAs are then trimmed into precursor microRNAs (pre-miRNAs) within the nucleus by DiGeorge syndrome critical region 8 (DGCR8) and Drosha. After processing in the nucleus, pre-miRNA transcripts are transported to the cytoplasm via the transporter Exportin-5 (XPO5). Pre-miRNAs are further processed in the cytoplasm by the enzyme Dicer into approximately 22 nucleotide-long RNA duplexes. The RNA duplexes are incorporated into the RNA-induced gene silencing complex (RISC), and further processed to form mature microRNAs (Zurawek and Turecki, 2021). RISC binds to the 3’untranslated region (3′UTR) of target mRNAs to induce targeted mRNA degradation or translational repression, thereby controlling gene expression at the post-transcriptional level.

1.2 Molecular pathophysiology of depression

Major depressive disorder (MDD) is a common illness that severely limits psychosocial functioning and diminishes quality of life (Malhi and Mann, 2018). MDD causes emotional changes in patients, as well as depressed mood and anhedonia, and it can lead to several psychiatric symptoms, including cognitive impairment (Hu et al., 2017). Although, there has been considerable research looking at the pathophysiology of major depressive disorder (MDD), no single mechanism can satisfactorily and completely explain all aspects of the disorder. There are several hypotheses regarding the molecular mechanisms involved in depression, including the monoamine hypothesis, hypothalamic-pituitary-adrenal (HPA) axis, neuroplasticity and neurogenesis, epigenetics, and inflammation. The monoamine hypothesis reveals that the pathophysiological basis leading to depression is due mostly to a decrease in monoamine neurotransmitters (e.g., serotonin). Evidence from clinical trials of some tricyclic antidepressants and monoamine oxidase inhibitors (MAOIs) have provided the basis for this hypothesis (Segal et al., 1974; Delgado et al., 1990; Willner et al., 2013). Hyperactivity of the HPA axis can lead to the stimulation of glucocorticoids and cortisol secretion, which may contribute to the development of depression (Goodyer et al., 2000; Harris et al., 2000). Notably, alterations of the HPA axis have also been associated with impairment of cognitive function (Keller et al., 2017). Stress-mediated inflammation and HPA axis dysfunction can lead to an alteration in neuroplasticity at the cellular level (Egeland et al., 2015). The neurogenesis process is controlled by regulatory proteins, such as brain-derived neurotrophic factor (BDNF), and peripheral BDNF has been found to be downregulated in patients with MDD (Molendijk et al., 2014). Epigenetics, the interaction of genes and the environment, plays a role in the alteration of brain neurobiology, and the effect of epigenetics can set the stage for the development of MDD (Penner-Goeke and Binder, 2019). In addition, peripheral cytokines can directly act on neurons and support cells and subsequently contribute to the development of depression (Miller and Raison, 2016). This hypothesis is supported by a role for some non-steroidal anti-inflammatory drugs in the treatment of depression (Leonard, 2018). Patients with autoimmune diseases and severe infections both have persistent activation of the immune system, causing high levels of cytokine production in the periphery. Such changes will cause changes in the patient’s central nervous system function, which in turn will lead to the occurrence and development of depression. This mechanism may explain why individuals with autoimmune diseases and severe infections are more likely to become depressed.

Up to now, first-line antidepressant drugs and other selected drugs in the clinic have low effectiveness, variable tolerance, adverse effects, and other disadvantages. Furthermore, large variations in therapeutic effects exist among individual drugs (Malhi and Mann, 2018). Our current understanding of microRNAs is continuing to increase partly, because of their high expression levels in the brain and their role in the regulation of neuronal plasticity and other functions. Recently, researchers focused on a role for microRNAs in the etiology of MDD. In this review, we have summarized the roles and mechanisms of microRNAs-mediated gene expression in the pathophysiological process of MDD. The role of each microRNA implicated in depression will be described as it relates to the different hypotheses of depression. In addition, this review could provide an attractive clue and potential targets to help diagnose and treat depression, as well as to assist in antidepressant drug development.

2 Expression and regulation of microRNAs in clinical samples of depression

Many studies have confirmed that the level of microRNAs expression is associated with the onset of depression. These studies include both human and animal experiments. Postmortem human experiments were carried out to examine the expression levels of microRNAs in the prefrontal cortex, amygdala and other regions, as well as the levels and identity of their downstream target genes and protein products (As shown in Table 1). These human studies also looked at peripheral whole blood, serum, exosomes, and other tissues. The animal experiments were performed to detect microRNAs, and their downstream target genes and protein expression in the hippocampus and other tissues in rodents with depression-like symptoms (Table 2). The depression-like symptoms were induced by chronic unpredictable mild stress (CUMS) and this successful animal model was confirmed using behavioral tests, including sucrose preference test, forced swim test, and elevated plus maze test. According to the literature, microRNAs such as miR-124-3p, miR-128-3p, miR-139-5p, and miR-144-5p have been shown to play a significant role in different pathophysiological mechanisms of depression, which will be described in the corresponding sections of the text according to their different roles.

TABLE 1

ReferencesSample sourcesmicroRNARegulation MDD vs. HCTargeted geneExpression of target gene
Gorinski et al. (2019)Brodmann Area 9(BA9)miR-30a, miR-30eUpZDHHC21Down
miR-200aDown
Wingo et al. (2020)Brodmann Area 9(BA9)/Brodmann Area 46(BA46)miR-484, miR-26b-5p, miR-30d-5p, miR-197-3Down
Smalheiser et al. (2012)Brodmann Area 9(BA9)miR-20b, miR-20a, miR-34a, miR-34bDownVEGFA
miR-34aDownBcl-2Down
miR-148bDownDNMT3BUp
Maussion et al. (2012)Brodmann Area 10(BA10)miR-185UpTrkB-T1Down
Smalheiser et al. (2014)Dorsolateral Prefrontal Cortex (BA10)miR-508-3p, miR-152Down
Wang et al. (2018a)Dorsolateral Prefrontal Cortex (BA10)miR-19a-3pUpTumor Necrosis Factor-α(TNF-α)Up
miR-20a-5p, miR-92a-1-3pDown
Peripheral Blood Mononuclear Cells (PBMC)miR-19a-3pUpTumor Necrosis Factor-α(TNF-α)Up
Fiori et al. (2021)Brodmann Area 24(BA24)miR-323a-3p (miR-204-5p, miR-331-3p)UpERBB4Down
Cerebral lateral habenulamiR-323a-3p (miR-320b-3p, miR-331-3p)UpERBB4Down
Wang et al. (2018b)Brodmann Area 44(BA44)miR-124-3pDownDDIT4Up
SP1Up
Torres-Berrio et al. (2017)Brodmann Area 44(BA44)miR-218DownDCCUp
Lopez et al. (2014a)Brodmann Area 44(BA44)miR-320c, miR-34c-5pUpSAT1Down
miR-320c, miR-139-5pUpSMOXDown
miR-195Up
Roy et al. (2017a)Brodmann Area 46(BA46)miR-124-3pUpGRIA3, GRIA4, NR3C1Down
SerummiR-124-3pUpGRIA3, GRIA4, NR3C1Down
Lopez et al. (2017)Ventrolateral Prefrontal Cortex (BA47)miR-146a-5p, miR-146b-5p, miR-425-3p, miR-24-3pUp
Lopez et al. (2014b)Ventrolateral Prefrontal Cortex (BA47)miR-1202DownGRM4Up
Yoshino et al. (2020)Anterior Cingulate Cortex (ACC)117 microRNAs (4.16%)Up
54 microRNAs (2.13%)Down
Azevedo et al. (2016)Anterior Cingulate Cortex (ACC)miR-34aDownNCOA1Up
miR-184DownNCOR2Down
miR-34a, miR-184DownPDE4B
Maheu et al. (2015)Basolateral AmygdalamiR-511UpGFRA1Down
Roy et al. (2020)Cerebral AmygdalamiR-128-3pUpDVL1, LEF1, WNT5bDown
Roy et al. (2017b)Locus CoeruleusmiR-17-5p, miR-20b-5p, miR-106a-5p, miR-330-3p, miR-541-3p, miR-582-5p, miR-890, miR-99-3p, miR-550-5p, miR-1179UpGRIK1Up
miR-409-5p, let-7g-3p, miR-1197DownRELN, GSK-3β, MAOA, CHRM1, PLCB1Down
Aschrafi et al. (2016)MidbrainmiR-326DownUrocortin 1 (Ucn1)Up
Issler et al. (2014)Raphe Nuclei (RN)/Whole BloodmiR-135aDownHtr1a, Slc6A4Up
Morgunova and Flores (2021)Prefrontal Cortex (PFC)miR-218-5pDownDCCUp
Liu et al. (2021c)Peripheral Blood Mononuclear Cells (PBMC)miR-374b, miR-10aDown
Hung et al. (2019)Peripheral Blood Mononuclear Cells (PBMC)let-7e, miR-21-5p, miR-146a, miR-155DownIL-6Up
MonocytesmiR-146a, miR-155Down
Sun et al. (2016)Peripheral Blood Mononuclear Cells (PBMC)miR-34b-5p, miR-34c-5pUpNOTCH1Down
He et al. (2016)Peripheral Blood Mononuclear Cells (PBMC)miR-124Up
Vaisvaser et al. (2016)Peripheral Blood Mononuclear Cells (PBMC)miR-29cUp
Gecys et al. (2022)Plasmalet-7e-5p, miR-125a-5pUp
Roumans et al. (2021)Plasmalet-7b-5pDownERK1/2Down
Sundquist et al. (2021)PlasmamiR-144-5pDown21 Inflammatory ProteinsUp
15 Inflammatory ProteinsDown
Chen et al. (2020)PlasmamiR-19b-3pDown
Zhang et al. (2020a)PlasmamiR-134Down
Mendes-Silva et al. (2019)PlasmamiR-184Down
Van der Auwera et al. (2019)Plasmalet-7g-5p, miR-103a-3p, miR-107, miR-142-3pDown
Fang et al. (2018)PlasmamiR-132, miR-124Up
Camkurt et al. (2015)PlasmamiR-451aUpSLC17A7Down
miR-320aDownGRIN2A, DISC1Up
miR-17-5p, miR-223-3pUp
Al-Rawaf et al. (2021)SerummiR-34a-5p, miR-124UpiNOS, CortisolUp
miR-135, miR-451-aDownSOD2, CAT,5-HTDown
Liu et al. (2021d)Serum/Cerebrospinal FluidmiR-199a-5pUpWNT2Down
HippocampusmiR-199a-5pUpWNT2Down
Feng et al. (2019)SerummiR-221-3pUpIRF2Down
Gheysarzadeh et al. (2018)SerummiR-16, miR-135a, miR-1202Down
Kuang et al. (2018)SerummiR-451aDown
miR-34a-5p, miR-221-3pUp
He et al. (2021)Peripheral BloodmiR-9Up
Sun et al. (2020)Peripheral BloodmiR-34c-5pUp
Zhao et al. (2019)Peripheral BloodpmiR-chr11UpBRPF1Down
Qi et al. (2018)Peripheral BloodmiR-132Up
Wang et al. (2018c)Peripheral BloodmiR-155UpSIRT1Down
Liu et al. (2016)Peripheral BloodmiR-132Up
Li et al. (2021a)Plasma ExosomemiR-335-5pUp
miR-1292-3pDown
Liang et al. (2020)Serum ExosomemiR-139-5pUp
Xian et al. (2022)Serum ExosomemiR-9-5pUp
Wei et al. (2020)Blood ExosomemiR-139-5pUp
Mizohata et al. (2021)Neural Extracellular Vesicles (NEVs) in BloodmiR-17-5pUp

Summary of researches on the changes in the levels of microRNAs and their target genes in MDD patients.

TABLE 2

ReferencesSample sourcesmicroRNARegulation MDD vs. HCTargeted geneExpression of target gene
Kavuran Buran et al. (2022)HippocampusmiR-135a-5p, miR-135b-5p, miR-6334, miR-203a-3p, miR-296-5p, miR-6320Up
Prefrontal Cortex (PFC)miR-135a-5p, miR-135b-5pUp
miR-484, miR-501-3p, miR-296-5p, miR-361-3pDown
Kim et al. (2022)Prefrontal Cortex (PFC)miR-329, miR-362UpBaiap3Down
Yoshino et al. (2022)Prefrontal Cortex (PFC)miR-218a-5pUpDTWD1, BNIP1, METTL22, SNAPC1, HDAC6Down
Huang et al. (2021a)Prefrontal Cortex (PFC)/HippocampusmiR-23a-5pUp
miR-98-5p, miR-3968Down
Gorinski et al. (2019)Brodmann Area 9(BA9)miR-30a, miR-30eUpZDHHC21Down
miR-200aDown
Torres-Berrio et al. (2017)Brodmann Area 44(BA44)miR-218DownDCCUp
Roy et al. (2017a)Brodmann Area 46(BA46)miR-124-3pUpGRIA3, GRIA4, NR3C1Down
SerummiR-124-3pUpGRIA3, GRIA4, NR3C1Down
Lopez et al. (2017)Ventrolateral Prefrontal Cortex (BA47)miR-146a-5p, miR-146b-5p, miR-425-3p, miR-24-3pUp
Liu et al. (2021a)HippocampusmiR-883b-3pDownAdcy1, Nr4a2Up
miR-377-3pDownSix4, Stx16, Ube3aUp
Si et al. (2021)Peripheral Samples/HippocampusmiR-212UpNuclear Factor I-A (NFIA)Down
Huang et al. (2021b)HippocampusmiR-139-5pDownPhosphodiesterase 4D (PDE4D)Up
p-CREB, BDNFDown
Lan et al. (2021)HippocampusmiR-204-5pDownRGS12Up
Liu et al. (2021b)HippocampusmiR-383UpWNT2Down
Liu et al. (2021d)Serum/Cerebrospinal FluidmiR-199a-5pUpWNT2Down
HippocampusmiR-199a-5pUpWNT2Down
Li et al. (2021c)Hippocampus Dentate GyrusmiR-26a-3pUpPTENDown
Li et al. (2021b),Shen et al. (2021)Hippocampus CA1 Region/Hippocampus Dentate GyrusmiR-211-5pDownDyrk1AUp
Qin and Li (2022)HippocampusmiR-124-3pUpSTAT3, Bcl-2Down
BaxUp
Su et al. (2022)HippocampusmiR-139-5pUpNR3C1Down
Li et al. (2022)HippocampusmiR-497a-5pUpNR3C1Down
Mingardi et al. (2021)HippocampusmiR-9-5pDownRESTUp
Ding et al. (2021)Peripheral BloodmiR-135aDown
Peripheral Blood/HippocampusmiR-135aDownTLR4Up
IL-1β, IL-6, TNF-αUp
Bax ProteinUp
Bcl-2 ProteinDown
Roy et al. (2020)Cerebral AmygdalamiR-128-3pUpDVL1, LEF1, WNT5b, Snail1, Arpp21Down
Volk et al. (2016)Cerebral AmygdalamiR-15aUpFKBP51Down
Aschrafi et al. (2016)MidbrainmiR-326DownUrocortin 1 (Ucn1)Up
Issler et al. (2014)Raphe Nuclei (RN)/Whole BloodmiR-135aDownHtr1a, Slc6A4Up
Fei et al. (2020),Huang et al. (2022)Brain MicrogliamiR-29b-3pDownMMP2Up
Wang et al. (2021)Neural Stem Cells (NSC)miR-34a-5pUpTia1Down

Summary of researches on the changes in the levels of microRNAs and their target genes in experimental animals induced to develop depression.

3 Involvement of microRNAs in the pathophysiology of depression

3.1 MicroRNAs are involved in the pathophysiology of depression induced by the dysregulation of monoamines

Monoamine neurotransmitter (serotonin, noradrenaline, and dopamine) dysregulation is considered the most likely cause of MDD, and most of the drugs used in the clinic for the treatment of MDD are based on this principle. Monoamine-based antidepressants were the first drugs developed for the treatment of MDD (Elias et al., 2022). The monoamine hypothesis of depression has been applied for nearly six decades ago (Coppen et al., 1965) and the classical doctrine holds that monoamines are depleted and chronically below normal levels in the brains of patients with MDD (Shaw et al., 1967). This hypothesis is corroborated by the pharmacological mechanism of action of monoamine oxidase (MAO) inhibitors, tricyclic antidepressants, and selective serotonin reuptake inhibitors in MDD patients (Hillhouse and Porter, 2015). In 1996, Heninger et al. (1996) revised the monoamine doctrine to suggest that monoamine depletion may play more of a role, thereby affecting nervous system functions, or it must be present in the environment of a stressor to cause MDD. They provided a theoretical basis for investigating the role of microRNAs in MDD.

Gorinski et al. (2019) found that a decrease in miR-200a expression or an increase in miR-30a and miR-30e expression led to a decrease of ZDHHC21 expression in humans and animal models. ZDHHC21, a palmitoyl acyltransferase, was identified as the major enzyme involved in the palmitoylation of the 5HT1AR and the decrease in the palmitoylation of 5HT1AR resulted in inhibition of adenylate cyclase and subsequent decrease of cAMP levels resulting in the occurrence of MDD. The downregulated miR-135a was shown to promote the translation of the Htr1a and Slc6a4 genes in MDD patients (Issler et al., 2014) and the upregulation of the inhibitory 5HT1a receptor (5HT1AR), encoded by the Htr1a gene, and 5HT transporter (SERT), encoded by the Slc6a4 gene, contributed to aberrant monoamine neurotransmitters in patients with depression (Issler et al., 2014). DCC (Deleted in Colorectal Cancer) drives prefrontal cortex maturity by determining DA targets early in life, for example, in rats, signaling within dopamine neurons in the juvenile VTA determines the extent of innervation of the PFC (Torres-Berrio et al., 2017). Whereas miR-218 was shown to be upregulated in BA44 in MDD patients and led to a significant decrease in DCC expression levels. In rats, who had experienced chronic social defeat stress paradigms also showed the same changes (Torres-Berrio et al., 2017). MiR-1202 was found to be differentially expressed in MDD patient ventrolateral prefrontal cortices, with upregulated GRM4 expression (Lopez et al., 2014b). GRM4 is expressed throughout the brain, with predominant expression sites at presynaptic and postsynaptic membranes, where it regulates glutamatergic, dopaminergic, GABAergic, and serotonergic neurotransmission (Lopez et al., 2014b). The increased expression of miR-329 and miR-362 in the PFC of MDD patients caused downregulation of Baiap3 (brain specific angiogenesis inhibitor 1-associated protein 3), which subsequently induced defective dense core vesicles (DCVs) transport and reduced serotonin exocytosis (Kim et al., 2022). In both the central nervous system and endocrine systems, DCVs are essential for peptidergic and aminergic signaling (Persoon et al., 2018) (Figure 1).

FIGURE 1

3.2 MicroRNAs are involved in the pathophysiological processes of depression related to neuroplasticity and neurogenesis abnormalities

Neuroplasticity is a fundamental process by which the brain acquires information and produces appropriately adaptive responses in relevant environments. Thus, dysfunction in neuroplasticity and neurogenesis may contribute to the pathophysiology of MDD (Duman, 2002). Multiple signaling pathways are involved in this process. For example, Wnt signaling pathway plays a role in neurogenesis, synapse formation, synaptic transmission, and dendritic arborization in the hippocampus (Wayman et al., 2006; Gogolla et al., 2009). The mTOR signaling pathway is involved in the pathophysiology of MDD through the P70S6K/eIF4B pathway (Jernigan et al., 2011). Abnormalities in BDNF, glutamate receptors, VEGF signaling, and long-term potentiation (LTP) pathways also contribute to the pathophysiological progression of depression by affecting neuroplasticity and neurogenesis (Duric et al., 2010; Yoshii and Constantine-Paton, 2010; Gormanns et al., 2011). MicroRNAs have an influence on depression by interfering with the stability of these signaling pathways (Fan et al., 2014).

As shown in Figure 2. Wang et al. (2018b) found that miR-124-3p was significantly downregulated in Brodmann area 44 (BA44) of patients with MDD. Downregulation of miR-124-3p abolished its inhibition of DNA damage inducible transcript 4 protein (DDIT4) and SP1 expression, and inhibited the mTOR signaling pathway. Roy et al. (2020) demonstrated that miR-128-3p was upregulated in the amygdala of MDD patients, leading to a decreased expression of Wnt5b, LEF1 and DVL1, which are genes related to the Wnt signaling pathway. Disruption of canonical Wnt/Fz/GSK3 signaling leads to abnormal neurodevelopment that is associated with neuropsychiatric disorders (Voleti and Duman, 2012).

FIGURE 2

Moreover, the downregulation of Gria3 and Gria4 receptors induced by miR-124-3p had an influence on modulation of AMPA receptor, and correlated with an impaired synaptic plasticity in patients with depression (Roy et al., 2017a). In the basolateral amygdala of depressed patients, upregulated miR-511 downregulated the encoded GFRα1a specific isoform of the GFRA1 gene of the receptor (Maheu et al., 2015). The subtypes, GFRα1a and GFRα1b elicited different downstream effects and had opposing effects in some aspects of neuroplasticity. The promotion of axonal growth by GFRα1a, was downregulated, while the inhibition of axonal growth by GFRα1b, was relatively upregulated, leading to the development of depression (Maheu et al., 2015). The upregulation of miR-185 in brain BA10 of MDD patients resulted in a decrease of TrkB-T1 expression. TrkB-T1, a BDNF receptor lacking the tyrosine kinase domain, was highly expressed in astrocytes and it regulated BDNF-evoked calcium transients (Maussion et al., 2012). Importantly, downregulation of TrkB-T1 in the frontal cortex might be associated with the neurobiology of suicide (Maussion et al., 2012).

In animal models, miR-139-5p regulates the cAMP/PKA/CREB/BDNF pathway to promote hippocampal neurogenesis by targeting PDE4D. Huang et al. (2021b) demonstrated that downregulation of miR-139-5p along with upregulation of its target gene PDE4D and downregulation of p-CREB and BDNF after inducing depression-like symptoms in CUMS mice. Such alterations show a bidirectional role for microRNAs in both protection and impairment of the neurogenesis pathways. In addition, Mingardi et al. (2021) found that miR-9-5p expression decreased in the hippocampus of rats subjected to chronic mild stress and primary hippocampal cultures. This change would cause overexpression of its downstream target protein REST, which would negatively affect neuronal dendritic morphology.

3.3 Role of microRNAs in MDD caused by changes of hypothalamic-pituitary-adrenal axis

Chronic stress has long been recognized to be a potential risk factor for depression, which is often associated with depression prevalence. The activity of the HPA axis is mediated by arginine vasopressin (AVP) and hypothalamic secretion of corticotropin releasing factor (CRF), which in turn activates the pituitary gland to secrete adrenocorticotropic hormone (ACTH), and finally stimulates the adrenal cortex to secrete glucocorticoids. Glucocorticoids then interact with receptors in multiple target tissues, where they directly exert negative feedback regulation on ACTH secreted by the pituitary as well as CRF secreted by the hypothalamus (Pariante and Lightman, 2008). Changes in glucocorticoid receptor (GR) expression, nuclear translocation, cofactor binding, and GR mediated gene transcription may play an important role in glucocorticoid resistance, which will lead to the development of HPA axis hyperactivity (Colla et al., 2007; Alt et al., 2010). Impaired GR function occurring in the periphery leads to the development of HPA axis hyperactivity. High glucocorticoid levels resulting from HPA axis hyperactivity may be involved in glucocorticoid-dependent hippocampal plasticity changes, causing hippocampal atrophy and reduced hippocampal neurogenesis, which in turn promotes the development of MDD (Kronenberg et al., 2009; Schmidt et al., 2009). As observed in depressed patients, HPA axis activity is the main biochemical change in addition to monoaminergic neurotransmitter disturbances (Budziszewska, 2002). MicroRNAs can influence the HPA axis activity by affecting glucocorticoid related receptors or other pathways (Uchida et al., 2008; Vreugdenhil et al., 2009).

Roy et al. (2017a) confirmed the effect of HPA axis hyperactivity on depression by examining the changes in miR-124-3p and its downstream target genes in PFC (BA46) and serum of mice with depression-like symptom after chronic CORT treatment. Furthermore, the detection of PFC (BA46) in post-mortem brains from depressed patients coincides with animal experiments (Roy et al., 2017a). In addition, upregulation of miR-124-3p in human and animal models was confirmed to be associated with downregulation of AMPA receptor family members Gria3 and Gria4, and glucocorticoid receptor NR3C1. MiR-124-3p mediated repression of NR3C1 may be central to the associated neuroendocrine response to stress (Roy et al., 2017a).

The central nervous system responses are of greater concern regarding hyperactive HPA axis responses. Al-Rawaf et al. (2021) demonstrated that the excessive cortisol activity induced by HPA axis hyperfunction was significantly correlated with decreased serotonin levels. A previous study has confirmed that the expression level of miR-124 was regulated by serotonin and demonstrated a significant negative correlation (Rajasethupathy et al., 2009). MiR-124 could control serotonin to induce synaptic function by repressing the transcription of cAMP response element binding protein (CREB), and conversely, CREB could further regulate miR-124 expression (Rajasethupathy et al., 2009). In addition, aberrant expression of miR-34a-5p and miR-451-a significantly reduced BDNF expression, and BDNF affected serotonin and cortisol expression by producing pro-neuroprotective signals (Numakawa et al., 2009; Numakawa et al., 2012; Wibrand et al., 2012).

3.4 MicroRNAs are involved in depression caused by abnormal inflammatory response

Depression and inflammation mutually contribute to the development of each other’s pathophysiology (Kiecolt-Glaser et al., 2015). Since the study of T and B lymphocytes in psychiatric patients by Herzog et al. (1979), the exploration of the relationship between the inflammatory response and depression has gradually unfolded (Herzog et al., 1979). Over the past four decades, accumulating evidence has shown that MDD is associated with systemic immune activation, including inflammatory markers, and changes in the number of immune cells (Gibney and Drexhage, 2013). Cytokines are one of the most important components of the immune system in depression. In response to peripheral infections, innate immune cells produce pro-inflammatory cytokines that act on the brain leading to development of neuropsychiatric disorders. When the peripheral immune system is continuously activated, immune signaling to the brain leads to exacerbation of the disease, and development of depressive symptoms in patients (Dantzer et al., 2008). The traditional routes of communication between the periphery and the central involve neural and humoral pathways, which mainly include: neural pathways (Harrison et al., 2009), signaling via cerebral endothelial cells (CECs) (Rivest et al., 2000; Kobayashi, 2010), signaling via circumventricular organs (CVOs) (Ransohoff et al., 2003) and peripheral immune-cell-to-brain signaling (Geissmann et al., 2003). TNFα, IL-1β and IL-6 are the main cytokines involved in the signaling of these pathways (Dantzer et al., 2008; Capuron and Miller, 2011). Recently, communication through the gut-microbiota-to-brain rout has gained increasing attention because of its role in regulating brain function (Jenkins et al., 2016; Sherwin et al., 2016). MicroRNAs participate in the pathophysiological process of inflammation in depression by promoting the production of inflammatory factors, as shown Figure 3. Changes in cytokine levels in patients with MDD have been identified to be associated with patient mood and volition (Beurel et al., 2020).

FIGURE 3

Wang et al. (2018a) pointed out that the upregulated expression of miR-19a-3p was detected in dlPFC and PBMC of MDD suicide completers. Gene analysis demonstrated that the elevated miR-19a-3p upregulated the expression of TNF-α by affecting the transcription of TAR-RNA binding protein (TRBP) and HuR (Wang et al., 2018a). The upregulation of TNF-α in dlPFC and PBMC was confirmed to be associated with suicidal ideation in MDD patients (Wang et al., 2018a). Sundquist et al. (2021) demonstrated that, in 178 patients with depression, anxiety, or stress and adjustment disorders, 36 inflammatory proteins with significantly different expression in peripheral blood of patients at baseline were seen, including 21 inflammatory proteins with increased levels and 15 with decreased levels, and all were associated with changes in miR-144-5p levels. In addition, the alteration in inflammatory proteins, which occurs after receiving treatment, was demonstrated to be associated with improvement in patients’ psychiatric symptoms (Sundquist et al., 2021). CircDYM, as an endogenous miR-9 sponge, is able to inhibit the activity of miR-9. Zhang et al. (2020b), by examining peripheral blood samples from MDD patients, hippocampus and plasma samples from MDD animal models, found that circDYM levels were significantly decreased. This would lead to enhanced miR-9 activity, which in turn would cause polarization of microglia. In a recent research, Xian et al. (2022) found miR-9-5p-enriched exosomes derived from PC12 cells in the serum of MDD patients. After BV2 microglia phagocytosed miR-9-5p-enriched exosomes, they were polarized to M1 subtype microglia via the SOCS2-STAT3 axis. Since then, M1 subtype microglia has produced a large amount of IL-1β, IL-6 and TNF-α. It leads to and intensifies the damage of neurons and causes the occurrence and development of MDD. Recent studies on depression triggered by microbial dysbiosis has shed new light on the role of abnormal inflammatory responses in the pathophysiology of depression (Borre et al., 2014; Dubois et al., 2019; Rea et al., 2020). This perspective explores the link between the gut microbiota and the regulation of the brain-gut axis, immune and endocrine system activity, and neurophysiological changes. Communication between the brain and the gut occurs bidirectionally via neural, endocrine, and immune pathways. Microbiota dysbiosis and an increased intestinal permeability with subsequent immune responses seem to be at the root of chronic mild inflammation associated with neuropsychiatric disorders (Petra et al., 2015; Rea et al., 2017; Farzi et al., 2018).

4 Summary and prospect

MicroRNAs are recognized as key epigenetic regulators of multiple functions in the brain and play a key role in MDD pathogenesis. As research continues to deepen, the roles of microRNAs in the pathophysiology of depression are gradually being elucidated. This review summarized recent research progress focusing on the role of microRNAs in the pathophysiology of depression, including dysregulation of monoamines, abnormalities in neuroplasticity and neurogenesis, hyperactivity of the HPA axis, and dysregulation of inflammatory responses. This suggests that an indispensable role for microRNAs occurs in these pathways. Several studies looking at changes in the levels of microRNAs and their downstream target genes before and after antidepressant treatment have confirmed a role for microRNAs in depression. Clearly, there are interactions between these different pathways and this exhibits the complexity in the pathogenesis of depression.

Based on the above four pathophysiological mechanisms of depression, it can be found that MDD, whether caused by dysregulation of monoamines or hyperactivity of the HPA, have parts that interact and influence each other. It is difficult to explain by a single pathophysiological mechanism, either from the clinical presentation of MDD patients or from changes in laboratory experiments. For example, high levels of cortisol in patients with Cushing syndrome resulted in alterations of neurotransmitter function, such as reduced serotonin synthesis. This can also be detected in MDD patients with HPA axis hyperactivity induced by long-term chronic stress (Stokes, 1995). In addition, high levels of cortisol inducing loss of hippocampal dendrites, and neuronal plasticity is recognized as one of the causes of depression (Gotlib et al., 2008). In addition, miR-124 can in turn control serotonin-induced synaptic facilitation by inhibiting the transcription of CREB (Rajasethupathy et al., 2009). Taken together, neuroinflammation could contribute to the pathogenesis of depression by interacting with the dysregulation of brain monoamines, dysregulation of the HPA axis, and alterations in hippocampal dentate gyrus neurons (Troubat et al., 2021).

It is important to note that current studies based on the role of microRNAs in depression have certain limitations, especially for the relationship between microRNAs and depression. Whether protective or injurious during the development of the disease, the levels of microRNAs in the brain tissue or peripheral tissues of patients do change when compared to normal individuals. Nevertheless, it is tough to confirm which of the varied microRNAs are responsible for the pathogenesis of MDD or that the major depressive disorder causes changes in certain microRNAs. If changes in specific microRNAs can be confirmed to contribute to the development of MDD, these microRNAs could be used as biomarkers for the diagnosis of the disease. In the same way, if it can be confirmed that MDD causes changes in the expression of microRNAs, and at the same time, alterations in these microRNAs can cause changes in the expression of downstream mRNAs and then have favorable or adverse effects on patients, this finding will be very important for the potential treatment of the disease and in stopping its development.

Since the discovery of the stable presence of free microRNAs in serum in 2018 (Chen et al., 2008), studies on the determination of microRNA levels in the serum of patients with depression have also gradually increased. However, it is undeniable that such studies have limitations as microRNAs in blood samples may not accurately reflect disease pathogenesis in the brain, because blood microRNAs are a mixture of brain-derived microRNAs and other microRNAs excreted from various tissues. The identification of microRNA within exosomes secreted by brain cells into the circulation may be able to compensate for the limitations that exist.

Finally, it is clear that microRNAs play an integral role in the pathophysiology of depression and may perhaps be able to provide a reference for the diagnostics and prognostics in depression by examining microRNA levels in relevant tissues. Moreover, promoting or inhibiting the expression of microRNAs might provide new clues for the development of antidepressant drugs.

Statements

Author contributions

Conceptualization: SL and XJ Writing—original draft: RD, DS, and QZ Writing—review and editing: XJ, SL, RD, YW, and J-YW

Funding

This work was supported by the National Natural Science Foundation of China (No. 81971280), the Program for Innovative Talents of Science and Technology in Henan Province (No. 23HASTIT043), the Natural Science Foundation of Henan Province for Excellent Young Scholars (No. 212300410026), the Medical Science and Technology Program of Henan Province (No. SBGJ202103096), and the Program for Young Key Teacher of Henan Province (No. 2020GGJS037).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Summary

Keywords

microRNA, depression, brain, biomarker, MDD

Citation

Ding R, Su D, Zhao Q, Wang Y, Wang J-Y, Lv S and Ji X (2023) The role of microRNAs in depression. Front. Pharmacol. 14:1129186. doi: 10.3389/fphar.2023.1129186

Received

21 December 2022

Accepted

21 March 2023

Published

29 March 2023

Volume

14 - 2023

Edited by

Guillaume Lucas, INSERM U1215 Neurocentre Magendie, France

Reviewed by

Cortney Ann Turner, University of Michigan, United States

Alessandro Barbon, University of Brescia, Italy

Updates

Copyright

*Correspondence: Shuangyu Lv, ; Xinying Ji,

This article was submitted to Neuropharmacology, a section of the journal Frontiers in Pharmacology

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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