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<article article-type="review-article" dtd-version="2.3" xml:lang="EN" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1129186</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2023.1129186</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The role of microRNAs in depression</article-title>
<alt-title alt-title-type="left-running-head">Ding et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphar.2023.1129186">10.3389/fphar.2023.1129186</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Ding</surname>
<given-names>Ruidong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2148054/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Su</surname>
<given-names>Dingyuan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Qian</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1856840/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Yu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2150121/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Jia-Yi</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Lv</surname>
<given-names>Shuangyu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/726296/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Ji</surname>
<given-names>Xinying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1042654/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Institute of Molecular Medicine</institution>, <institution>Henan International Joint Laboratory for Nuclear Protein Regulation</institution>, <institution>School of Basic Medical Sciences</institution>, <institution>Henan University</institution>, <addr-line>Kaifeng</addr-line>, <addr-line>Henan</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>San-Quan College</institution>, <institution>Xinxiang Medical University</institution>, <addr-line>Xinxiang</addr-line>, <addr-line>Henan</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Kaifeng Key Laboratory for Infectious Diseases and Biosafety</institution>, <addr-line>Kaifeng</addr-line>, <addr-line>Henan</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Faculty of Basic Medical Subjects</institution>, <institution>Shu-Qing Medical College of Zhengzhou</institution>, <addr-line>Zhengzhou</addr-line>, <addr-line>Henan</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/495628/overview">Guillaume Lucas</ext-link>, INSERM U1215 Neurocentre Magendie, France</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/132112/overview">Cortney Ann Turner</ext-link>, University of Michigan, United States</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/593739/overview">Alessandro Barbon</ext-link>, University of Brescia, Italy</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Shuangyu Lv, <email>shuangyulv@163.com</email>; Xinying Ji, <email>10190096@vip.henu.edu.cn</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Neuropharmacology, a section of the journal Frontiers in Pharmacology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>29</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1129186</elocation-id>
<history>
<date date-type="received">
<day>21</day>
<month>12</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>21</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Ding, Su, Zhao, Wang, Wang, Lv and Ji.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Ding, Su, Zhao, Wang, Wang, Lv and Ji</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>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&#x2019;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.</p>
</abstract>
<kwd-group>
<kwd>microRNA</kwd>
<kwd>depression</kwd>
<kwd>brain</kwd>
<kwd>biomarker</kwd>
<kwd>MDD</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<sec id="s1-1">
<title>1.1 MicroRNAs</title>
<p>MicroRNAs (miRNAs) are short-stranded endogenous non-coding RNA molecules with a length of 19&#x2013;25 nucleotides. A single microRNA can target hundreds of mRNAs and influence the expression of many genes (<xref ref-type="bibr" rid="B28">Friedman et al., 2009</xref>; <xref ref-type="bibr" rid="B76">Lu and Rothenberg, 2018</xref>). 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, <italic>etc</italic>. 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 <italic>via</italic> 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 (<xref ref-type="bibr" rid="B140">Zurawek and Turecki, 2021</xref>). RISC binds to the 3&#x2019;untranslated region (3&#x2032;UTR) of target mRNAs to induce targeted mRNA degradation or translational repression, thereby controlling gene expression at the post-transcriptional level.</p>
</sec>
<sec id="s1-2">
<title>1.2 Molecular pathophysiology of depression</title>
<p>Major depressive disorder (MDD) is a common illness that severely limits psychosocial functioning and diminishes quality of life (<xref ref-type="bibr" rid="B78">Malhi and Mann, 2018</xref>). MDD causes emotional changes in patients, as well as depressed mood and anhedonia, and it can lead to several psychiatric symptoms, including cognitive impairment (<xref ref-type="bibr" rid="B45">Hu et al., 2017</xref>). 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 (<xref ref-type="bibr" rid="B104">Segal et al., 1974</xref>; <xref ref-type="bibr" rid="B15">Delgado et al., 1990</xref>; <xref ref-type="bibr" rid="B131">Willner et al., 2013</xref>). Hyperactivity of the HPA axis can lead to the stimulation of glucocorticoids and cortisol secretion, which may contribute to the development of depression (<xref ref-type="bibr" rid="B34">Goodyer et al., 2000</xref>; <xref ref-type="bibr" rid="B38">Harris et al., 2000</xref>). Notably, alterations of the HPA axis have also been associated with impairment of cognitive function (<xref ref-type="bibr" rid="B55">Keller et al., 2017</xref>). Stress-mediated inflammation and HPA axis dysfunction can lead to an alteration in neuroplasticity at the cellular level (<xref ref-type="bibr" rid="B20">Egeland et al., 2015</xref>). 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 (<xref ref-type="bibr" rid="B84">Molendijk et al., 2014</xref>). 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 (<xref ref-type="bibr" rid="B89">Penner-Goeke and Binder, 2019</xref>). In addition, peripheral cytokines can directly act on neurons and support cells and subsequently contribute to the development of depression (<xref ref-type="bibr" rid="B81">Miller and Raison, 2016</xref>). This hypothesis is supported by a role for some non-steroidal anti-inflammatory drugs in the treatment of depression (<xref ref-type="bibr" rid="B62">Leonard, 2018</xref>). 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&#x2019;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.</p>
<p>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 (<xref ref-type="bibr" rid="B78">Malhi and Mann, 2018</xref>). 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.</p>
</sec>
</sec>
<sec id="s2">
<title>2 Expression and regulation of microRNAs in clinical samples of depression</title>
<p>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 <xref ref-type="table" rid="T1">Table 1</xref>). 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 (<xref ref-type="table" rid="T2">Table 2</xref>). 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.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Summary of researches on the changes in the levels of microRNAs and their target genes in MDD patients.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">References</th>
<th align="left">Sample sources</th>
<th align="left">microRNA</th>
<th align="left">Regulation MDD vs. HC</th>
<th align="left">Targeted gene</th>
<th align="left">Expression of target gene</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="2" align="center">
<xref ref-type="bibr" rid="B35">Gorinski et al. (2019)</xref>
</td>
<td rowspan="2" align="left">Brodmann Area 9(BA9)</td>
<td align="left">miR-30a, miR-30e</td>
<td align="left">Up</td>
<td rowspan="2" align="left">ZDHHC21</td>
<td rowspan="2" align="left">Down</td>
</tr>
<tr>
<td align="left">miR-200a</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B132">Wingo et al. (2020)</xref>
</td>
<td align="left">Brodmann Area 9(BA9)/Brodmann Area 46(BA46)</td>
<td align="left">miR-484, miR-26b-5p, miR-30d-5p, miR-197-3</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="3" align="center">
<xref ref-type="bibr" rid="B109">Smalheiser et al. (2012)</xref>
</td>
<td rowspan="3" align="left">Brodmann Area 9(BA9)</td>
<td align="left">miR-20b, miR-20a, miR-34a, miR-34b</td>
<td align="left">Down</td>
<td align="left">VEGFA</td>
<td align="left"/>
</tr>
<tr>
<td align="left">miR-34a</td>
<td align="left">Down</td>
<td align="left">Bcl-2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">miR-148b</td>
<td align="left">Down</td>
<td align="left">DNMT3B</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B79">Maussion et al. (2012)</xref>
</td>
<td align="left">Brodmann Area 10(BA10)</td>
<td align="left">miR-185</td>
<td align="left">Up</td>
<td align="left">TrkB-T1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B110">Smalheiser et al. (2014)</xref>
</td>
<td align="left">Dorsolateral Prefrontal Cortex (BA10)</td>
<td align="left">miR-508-3p, miR-152</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="3" align="center">
<xref ref-type="bibr" rid="B125">Wang et al. (2018a)</xref>
</td>
<td rowspan="2" align="left">Dorsolateral Prefrontal Cortex (BA10)</td>
<td align="left">miR-19a-3p</td>
<td align="left">Up</td>
<td align="left">Tumor Necrosis Factor-&#x3b1;(TNF-&#x3b1;)</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">miR-20a-5p, miR-92a-1-3p</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Peripheral Blood Mononuclear Cells (PBMC)</td>
<td align="left">miR-19a-3p</td>
<td align="left">Up</td>
<td align="left">Tumor Necrosis Factor-&#x3b1;(TNF-&#x3b1;)</td>
<td align="left">Up</td>
</tr>
<tr>
<td rowspan="2" align="center">
<xref ref-type="bibr" rid="B27">Fiori et al. (2021)</xref>
</td>
<td align="left">Brodmann Area 24(BA24)</td>
<td align="left">miR-323a-3p (miR-204-5p, miR-331-3p)</td>
<td align="left">Up</td>
<td align="left">ERBB4</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">Cerebral lateral habenula</td>
<td align="left">miR-323a-3p (miR-320b-3p, miR-331-3p)</td>
<td align="left">Up</td>
<td align="left">ERBB4</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="center">
<xref ref-type="bibr" rid="B126">Wang et al. (2018b)</xref>
</td>
<td rowspan="2" align="left">Brodmann Area 44(BA44)</td>
<td rowspan="2" align="left">miR-124-3p</td>
<td rowspan="2" align="left">Down</td>
<td align="left">DDIT4</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">SP1</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B116">Torres-Berrio et al. (2017)</xref>
</td>
<td align="left">Brodmann Area 44(BA44)</td>
<td align="left">miR-218</td>
<td align="left">Down</td>
<td align="left">DCC</td>
<td align="left">Up</td>
</tr>
<tr>
<td rowspan="3" align="center">
<xref ref-type="bibr" rid="B74">Lopez et al. (2014a)</xref>
</td>
<td rowspan="3" align="left">Brodmann Area 44(BA44)</td>
<td align="left">miR-320c, miR-34c-5p</td>
<td align="left">Up</td>
<td align="left">SAT1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">miR-320c, miR-139-5p</td>
<td align="left">Up</td>
<td align="left">SMOX</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">miR-195</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="center">
<xref ref-type="bibr" rid="B101">Roy et al. (2017a)</xref>
</td>
<td align="left">Brodmann Area 46(BA46)</td>
<td align="left">miR-124-3p</td>
<td align="left">Up</td>
<td align="left">GRIA3, GRIA4, NR3C1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">Serum</td>
<td align="left">miR-124-3p</td>
<td align="left">Up</td>
<td align="left">GRIA3, GRIA4, NR3C1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B73">Lopez et al. (2017)</xref>
</td>
<td align="left">Ventrolateral Prefrontal Cortex (BA47)</td>
<td align="left">miR-146a-5p, miR-146b-5p, miR-425-3p, miR-24-3p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B75">Lopez et al. (2014b)</xref>
</td>
<td align="left">Ventrolateral Prefrontal Cortex (BA47)</td>
<td align="left">miR-1202</td>
<td align="left">Down</td>
<td align="left">GRM4</td>
<td align="left">Up</td>
</tr>
<tr>
<td rowspan="2" align="center">
<xref ref-type="bibr" rid="B135">Yoshino et al. (2020)</xref>
</td>
<td rowspan="2" align="left">Anterior Cingulate Cortex (ACC)</td>
<td align="left">117 microRNAs (4.16%)</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">54 microRNAs (2.13%)</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="3" align="center">
<xref ref-type="bibr" rid="B4">Azevedo et al. (2016)</xref>
</td>
<td rowspan="3" align="left">Anterior Cingulate Cortex (ACC)</td>
<td align="left">miR-34a</td>
<td align="left">Down</td>
<td align="left">NCOA1</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">miR-184</td>
<td align="left">Down</td>
<td align="left">NCOR2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">miR-34a, miR-184</td>
<td align="left">Down</td>
<td align="left">PDE4B</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B77">Maheu et al. (2015)</xref>
</td>
<td align="left">Basolateral Amygdala</td>
<td align="left">miR-511</td>
<td align="left">Up</td>
<td align="left">GFRA1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B100">Roy et al. (2020)</xref>
</td>
<td align="left">Cerebral Amygdala</td>
<td align="left">miR-128-3p</td>
<td align="left">Up</td>
<td align="left">DVL1, LEF1, WNT5b</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B102">Roy et al. (2017b)</xref>
</td>
<td rowspan="2" align="left">Locus Coeruleus</td>
<td align="left">miR-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-1179</td>
<td align="left">Up</td>
<td align="left">GRIK1</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">miR-409-5p, let-7g-3p, miR-1197</td>
<td align="left">Down</td>
<td align="left">RELN, GSK-3&#x3b2;, MAOA, CHRM1, PLCB1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B3">Aschrafi et al. (2016)</xref>
</td>
<td align="left">Midbrain</td>
<td align="left">miR-326</td>
<td align="left">Down</td>
<td align="left">Urocortin 1 (Ucn1)</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B50">Issler et al. (2014)</xref>
</td>
<td align="left">Raphe Nuclei (RN)/Whole Blood</td>
<td align="left">miR-135a</td>
<td align="left">Down</td>
<td align="left">Htr1a, Slc6A4</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B85">Morgunova and Flores (2021)</xref>
</td>
<td align="left">Prefrontal Cortex (PFC)</td>
<td align="left">miR-218-5p</td>
<td align="left">Down</td>
<td align="left">DCC</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B70">Liu et al. (2021c)</xref>
</td>
<td align="left">Peripheral Blood Mononuclear Cells (PBMC)</td>
<td align="left">miR-374b, miR-10a</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B49">Hung et al. (2019)</xref>
</td>
<td align="left">Peripheral Blood Mononuclear Cells (PBMC)</td>
<td align="left">let-7e, miR-21-5p, miR-146a, miR-155</td>
<td align="left">Down</td>
<td align="left">IL-6</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">Monocytes</td>
<td align="left">miR-146a, miR-155</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B113">Sun et al. (2016)</xref>
</td>
<td align="left">Peripheral Blood Mononuclear Cells (PBMC)</td>
<td align="left">miR-34b-5p, miR-34c-5p</td>
<td align="left">Up</td>
<td align="left">NOTCH1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B41">He et al. (2016)</xref>
</td>
<td align="left">Peripheral Blood Mononuclear Cells (PBMC)</td>
<td align="left">miR-124</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B119">Vaisvaser et al. (2016)</xref>
</td>
<td align="left">Peripheral Blood Mononuclear Cells (PBMC)</td>
<td align="left">miR-29c</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B29">Gecys et al. (2022)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">let-7e-5p, miR-125a-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B99">Roumans et al. (2021)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">let-7b-5p</td>
<td align="left">Down</td>
<td align="left">ERK1/2</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B115">Sundquist et al. (2021)</xref>
</td>
<td rowspan="2" align="left">Plasma</td>
<td rowspan="2" align="left">miR-144-5p</td>
<td rowspan="2" align="left">Down</td>
<td align="left">21 Inflammatory Proteins</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">15 Inflammatory Proteins</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B11">Chen et al. (2020)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">miR-19b-3p</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B137">Zhang et al. (2020a)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">miR-134</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B80">Mendes-Silva et al. (2019)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">miR-184</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B120">Van der Auwera et al. (2019)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">let-7g-5p, miR-103a-3p, miR-107, miR-142-3p</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B23">Fang et al. (2018)</xref>
</td>
<td align="left">Plasma</td>
<td align="left">miR-132, miR-124</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="3" align="left">
<xref ref-type="bibr" rid="B8">Camkurt et al. (2015)</xref>
</td>
<td rowspan="3" align="left">Plasma</td>
<td align="left">miR-451a</td>
<td align="left">Up</td>
<td align="left">SLC17A7</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">miR-320a</td>
<td align="left">Down</td>
<td align="left">GRIN2A, DISC1</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">miR-17-5p, miR-223-3p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B1">Al-Rawaf et al. (2021)</xref>
</td>
<td rowspan="2" align="left">Serum</td>
<td align="left">miR-34a-5p, miR-124</td>
<td align="left">Up</td>
<td align="left">iNOS, Cortisol</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">miR-135, miR-451-a</td>
<td align="left">Down</td>
<td align="left">SOD2, CAT,5-HT</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B72">Liu et al. (2021d)</xref>
</td>
<td align="left">Serum/Cerebrospinal Fluid</td>
<td align="left">miR-199a-5p</td>
<td align="left">Up</td>
<td align="left">WNT2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">Hippocampus</td>
<td align="left">miR-199a-5p</td>
<td align="left">Up</td>
<td align="left">WNT2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B26">Feng et al. (2019)</xref>
</td>
<td align="left">Serum</td>
<td align="left">miR-221-3p</td>
<td align="left">Up</td>
<td align="left">IRF2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B31">Gheysarzadeh et al. (2018)</xref>
</td>
<td align="left">Serum</td>
<td align="left">miR-16, miR-135a, miR-1202</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B60">Kuang et al. (2018)</xref>
</td>
<td rowspan="2" align="left">Serum</td>
<td align="left">miR-451a</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">miR-34a-5p, miR-221-3p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B40">He et al. (2021)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">miR-9</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B114">Sun et al. (2020)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">miR-34c-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B139">Zhao et al. (2019)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">pmiR-chr11</td>
<td align="left">Up</td>
<td align="left">BRPF1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B92">Qi et al. (2018)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">miR-132</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B127">Wang et al. (2018c)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">miR-155</td>
<td align="left">Up</td>
<td align="left">SIRT1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B71">Liu et al. (2016)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">miR-132</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B63">Li et al. (2021a)</xref>
</td>
<td rowspan="2" align="left">Plasma Exosome</td>
<td align="left">miR-335-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">miR-1292-3p</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B67">Liang et al. (2020)</xref>
</td>
<td align="left">Serum Exosome</td>
<td align="left">miR-139-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B133">Xian et al. (2022)</xref>
</td>
<td align="left">Serum Exosome</td>
<td align="left">miR-9-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B129">Wei et al. (2020)</xref>
</td>
<td align="left">Blood Exosome</td>
<td align="left">miR-139-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B83">Mizohata et al. (2021)</xref>
</td>
<td align="left">Neural Extracellular Vesicles (NEVs) in Blood</td>
<td align="left">miR-17-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Summary of researches on the changes in the levels of microRNAs and their target genes in experimental animals induced to develop depression.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">References</th>
<th align="left">Sample sources</th>
<th align="left">microRNA</th>
<th align="left">Regulation MDD vs. HC</th>
<th align="left">Targeted gene</th>
<th align="left">Expression of target gene</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="3" align="left">
<xref ref-type="bibr" rid="B54">Kavuran Buran et al. (2022)</xref>
</td>
<td align="left">Hippocampus</td>
<td align="left">miR-135a-5p, miR-135b-5p, miR-6334, miR-203a-3p, miR-296-5p, miR-6320</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">Prefrontal Cortex (PFC)</td>
<td align="left">miR-135a-5p, miR-135b-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">miR-484, miR-501-3p, miR-296-5p, miR-361-3p</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B57">Kim et al. (2022)</xref>
</td>
<td align="left">Prefrontal Cortex (PFC)</td>
<td align="left">miR-329, miR-362</td>
<td align="left">Up</td>
<td align="left">Baiap3</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B136">Yoshino et al. (2022)</xref>
</td>
<td align="left">Prefrontal Cortex (PFC)</td>
<td align="left">miR-218a-5p</td>
<td align="left">Up</td>
<td align="left">DTWD1, BNIP1, METTL22, SNAPC1, HDAC6</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B46">Huang et al. (2021a)</xref>
</td>
<td rowspan="2" align="left">Prefrontal Cortex (PFC)/Hippocampus</td>
<td align="left">miR-23a-5p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">miR-98-5p, miR-3968</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B35">Gorinski et al. (2019)</xref>
</td>
<td rowspan="2" align="left">Brodmann Area 9(BA9)</td>
<td align="left">miR-30a, miR-30e</td>
<td align="left">Up</td>
<td rowspan="2" align="left">ZDHHC21</td>
<td rowspan="2" align="left">Down</td>
</tr>
<tr>
<td align="left">miR-200a</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B116">Torres-Berrio et al. (2017)</xref>
</td>
<td align="left">Brodmann Area 44(BA44)</td>
<td align="left">miR-218</td>
<td align="left">Down</td>
<td align="left">DCC</td>
<td align="left">Up</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B101">Roy et al. (2017a)</xref>
</td>
<td align="left">Brodmann Area 46(BA46)</td>
<td align="left">miR-124-3p</td>
<td align="left">Up</td>
<td align="left">GRIA3, GRIA4, NR3C1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">Serum</td>
<td align="left">miR-124-3p</td>
<td align="left">Up</td>
<td align="left">GRIA3, GRIA4, NR3C1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B73">Lopez et al. (2017)</xref>
</td>
<td align="left">Ventrolateral Prefrontal Cortex (BA47)</td>
<td align="left">miR-146a-5p, miR-146b-5p, miR-425-3p, miR-24-3p</td>
<td align="left">Up</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B68">Liu et al. (2021a)</xref>
</td>
<td rowspan="2" align="left">Hippocampus</td>
<td align="left">miR-883b-3p</td>
<td align="left">Down</td>
<td align="left">Adcy1, Nr4a2</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">miR-377-3p</td>
<td align="left">Down</td>
<td align="left">Six4, Stx16, Ube3a</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B108">Si et al. (2021)</xref>
</td>
<td align="left">Peripheral Samples/Hippocampus</td>
<td align="left">miR-212</td>
<td align="left">Up</td>
<td align="left">Nuclear Factor I-A (NFIA)</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B47">Huang et al. (2021b)</xref>
</td>
<td rowspan="2" align="left">Hippocampus</td>
<td rowspan="2" align="left">miR-139-5p</td>
<td rowspan="2" align="left">Down</td>
<td align="left">Phosphodiesterase 4D (PDE4D)</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">p-CREB, BDNF</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B61">Lan et al. (2021)</xref>
</td>
<td align="left">Hippocampus</td>
<td align="left">miR-204-5p</td>
<td align="left">Down</td>
<td align="left">RGS12</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B69">Liu et al. (2021b)</xref>
</td>
<td align="left">Hippocampus</td>
<td align="left">miR-383</td>
<td align="left">Up</td>
<td align="left">WNT2</td>
<td align="left">Down</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B72">Liu et al. (2021d)</xref>
</td>
<td align="left">Serum/Cerebrospinal Fluid</td>
<td align="left">miR-199a-5p</td>
<td align="left">Up</td>
<td align="left">WNT2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">Hippocampus</td>
<td align="left">miR-199a-5p</td>
<td align="left">Up</td>
<td align="left">WNT2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B66">Li et al. (2021c)</xref>
</td>
<td align="left">Hippocampus Dentate Gyrus</td>
<td align="left">miR-26a-3p</td>
<td align="left">Up</td>
<td align="left">PTEN</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B65">Li et al. (2021b),</xref> <xref ref-type="bibr" rid="B106">Shen et al. (2021)</xref>
</td>
<td align="left">Hippocampus CA1 Region/Hippocampus Dentate Gyrus</td>
<td align="left">miR-211-5p</td>
<td align="left">Down</td>
<td align="left">Dyrk1A</td>
<td align="left">Up</td>
</tr>
<tr>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B93">Qin and Li (2022)</xref>
</td>
<td rowspan="2" align="left">Hippocampus</td>
<td rowspan="2" align="left">miR-124-3p</td>
<td rowspan="2" align="left">Up</td>
<td align="left">STAT3, Bcl-2</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">Bax</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B112">Su et al. (2022)</xref>
</td>
<td align="left">Hippocampus</td>
<td align="left">miR-139-5p</td>
<td align="left">Up</td>
<td align="left">NR3C1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B64">Li et al. (2022)</xref>
</td>
<td align="left">Hippocampus</td>
<td align="left">miR-497a-5p</td>
<td align="left">Up</td>
<td align="left">NR3C1</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B82">Mingardi et al. (2021)</xref>
</td>
<td align="left">Hippocampus</td>
<td align="left">miR-9-5p</td>
<td align="left">Down</td>
<td align="left">REST</td>
<td align="left">Up</td>
</tr>
<tr>
<td rowspan="5" align="left">
<xref ref-type="bibr" rid="B16">Ding et al. (2021)</xref>
</td>
<td align="left">Peripheral Blood</td>
<td align="left">miR-135a</td>
<td align="left">Down</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td rowspan="4" align="left">Peripheral Blood/Hippocampus</td>
<td rowspan="4" align="left">miR-135a</td>
<td rowspan="4" align="left">Down</td>
<td align="left">TLR4</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">IL-1&#x3b2;, IL-6, TNF-&#x3b1;</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">Bax Protein</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">Bcl-2 Protein</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B100">Roy et al. (2020)</xref>
</td>
<td align="left">Cerebral Amygdala</td>
<td align="left">miR-128-3p</td>
<td align="left">Up</td>
<td align="left">DVL1, LEF1, WNT5b, Snail1, Arpp21</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B122">Volk et al. (2016)</xref>
</td>
<td align="left">Cerebral Amygdala</td>
<td align="left">miR-15a</td>
<td align="left">Up</td>
<td align="left">FKBP51</td>
<td align="left">Down</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B3">Aschrafi et al. (2016)</xref>
</td>
<td align="left">Midbrain</td>
<td align="left">miR-326</td>
<td align="left">Down</td>
<td align="left">Urocortin 1 (Ucn1)</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B50">Issler et al. (2014)</xref>
</td>
<td align="left">Raphe Nuclei (RN)/Whole Blood</td>
<td align="left">miR-135a</td>
<td align="left">Down</td>
<td align="left">Htr1a, Slc6A4</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B25">Fei et al. (2020),</xref> <xref ref-type="bibr" rid="B48">Huang et al. (2022)</xref>
</td>
<td align="left">Brain Microglia</td>
<td align="left">miR-29b-3p</td>
<td align="left">Down</td>
<td align="left">MMP2</td>
<td align="left">Up</td>
</tr>
<tr>
<td align="left">
<xref ref-type="bibr" rid="B124">Wang et al. (2021)</xref>
</td>
<td align="left">Neural Stem Cells (NSC)</td>
<td align="left">miR-34a-5p</td>
<td align="left">Up</td>
<td align="left">Tia1</td>
<td align="left">Down</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3">
<title>3 Involvement of microRNAs in the pathophysiology of depression</title>
<sec id="s3-1">
<title>3.1 MicroRNAs are involved in the pathophysiology of depression induced by the dysregulation of monoamines</title>
<p>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 (<xref ref-type="bibr" rid="B21">Elias et al., 2022</xref>). The monoamine hypothesis of depression has been applied for nearly six decades ago (<xref ref-type="bibr" rid="B13">Coppen et al., 1965</xref>) and the classical doctrine holds that monoamines are depleted and chronically below normal levels in the brains of patients with MDD (<xref ref-type="bibr" rid="B105">Shaw et al., 1967</xref>). 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 (<xref ref-type="bibr" rid="B44">Hillhouse and Porter, 2015</xref>). In 1996, <xref ref-type="bibr" rid="B42">Heninger et al. (1996)</xref> 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.</p>
<p>
<xref ref-type="bibr" rid="B35">Gorinski et al. (2019)</xref> 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 <italic>Htr1a</italic> and <italic>Slc6a4</italic> genes in MDD patients (<xref ref-type="bibr" rid="B50">Issler et al., 2014</xref>) and the upregulation of the inhibitory 5HT1a receptor (5HT1AR), encoded by the <italic>Htr1a</italic> gene, and 5HT transporter (SERT), encoded by the <italic>Slc6a4</italic> gene, contributed to aberrant monoamine neurotransmitters in patients with depression (<xref ref-type="bibr" rid="B50">Issler et al., 2014</xref>). 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 (<xref ref-type="bibr" rid="B116">Torres-Berrio et al., 2017</xref>). 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 (<xref ref-type="bibr" rid="B116">Torres-Berrio et al., 2017</xref>). MiR-1202 was found to be differentially expressed in MDD patient ventrolateral prefrontal cortices, with upregulated GRM4 expression (<xref ref-type="bibr" rid="B75">Lopez et al., 2014b</xref>). GRM4 is expressed throughout the brain, with predominant expression sites at presynaptic and postsynaptic membranes, where it regulates glutamatergic, dopaminergic, GABAergic, and serotonergic neurotransmission (<xref ref-type="bibr" rid="B75">Lopez et al., 2014b</xref>). 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 (<xref ref-type="bibr" rid="B57">Kim et al., 2022</xref>). In both the central nervous system and endocrine systems, DCVs are essential for peptidergic and aminergic signaling (<xref ref-type="bibr" rid="B90">Persoon et al., 2018</xref>) (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Role of microRNAs in serotonin dysregulation. The inhibitory receptor 5HT1AR is hyperactivity or increased under the influence of miR-135a, miR-200a, miR-30a, and miR-30e, lead to the occurrence and development of depression. DCV and SERT undergo quantitative abnormalities under the influence of miR-329, miR-362 and miR-135a, causing dysregulation of monoamine transmitter secretion and reuptake. GRM4, whose transcription is increased by miR-1202 downregulation, can regulate monoamine neurotransmitter transmission (Created with <ext-link ext-link-type="uri" xlink:href="http://BioRender.com">BioRender.com</ext-link>).</p>
</caption>
<graphic xlink:href="fphar-14-1129186-g001.tif"/>
</fig>
</sec>
<sec id="s3-2">
<title>3.2 MicroRNAs are involved in the pathophysiological processes of depression related to neuroplasticity and neurogenesis abnormalities</title>
<p>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 (<xref ref-type="bibr" rid="B18">Duman, 2002</xref>). 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 (<xref ref-type="bibr" rid="B128">Wayman et al., 2006</xref>; <xref ref-type="bibr" rid="B33">Gogolla et al., 2009</xref>). The mTOR signaling pathway is involved in the pathophysiology of MDD through the P70S6K/eIF4B pathway (<xref ref-type="bibr" rid="B52">Jernigan et al., 2011</xref>). 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 (<xref ref-type="bibr" rid="B19">Duric et al., 2010</xref>; <xref ref-type="bibr" rid="B134">Yoshii and Constantine-Paton, 2010</xref>; <xref ref-type="bibr" rid="B36">Gormanns et al., 2011</xref>). MicroRNAs have an influence on depression by interfering with the stability of these signaling pathways (<xref ref-type="bibr" rid="B22">Fan et al., 2014</xref>).</p>
<p>As shown in <xref ref-type="fig" rid="F2">Figure 2</xref>. <xref ref-type="bibr" rid="B126">Wang et al. (2018b)</xref> 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. <xref ref-type="bibr" rid="B100">Roy et al. (2020)</xref> 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 (<xref ref-type="bibr" rid="B121">Voleti and Duman, 2012</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Role of microRNAs in neuroplasticity and neurogenesis abnormalities. MiR-124, miR-128, miR-139, miR-144 and others are involved in the regulation of neuroplasticity and neurogenesis through multiple pathways. These pathways mainly include Wnt/&#x3b2;-Catenin signaling pathway, mTOR signaling pathway, LTP signaling pathway, etc.</p>
</caption>
<graphic xlink:href="fphar-14-1129186-g002.tif"/>
</fig>
<p>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 (<xref ref-type="bibr" rid="B101">Roy et al., 2017a</xref>). In the basolateral amygdala of depressed patients, upregulated miR-511 downregulated the encoded GFR&#x3b1;1a specific isoform of the <italic>GFRA1</italic> gene of the receptor (<xref ref-type="bibr" rid="B77">Maheu et al., 2015</xref>). The subtypes, GFR&#x3b1;1a and GFR&#x3b1;1b elicited different downstream effects and had opposing effects in some aspects of neuroplasticity. The promotion of axonal growth by GFR&#x3b1;1a, was downregulated, while the inhibition of axonal growth by GFR&#x3b1;1b, was relatively upregulated, leading to the development of depression (<xref ref-type="bibr" rid="B77">Maheu et al., 2015</xref>). 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 (<xref ref-type="bibr" rid="B79">Maussion et al., 2012</xref>). Importantly, downregulation of TrkB-T1 in the frontal cortex might be associated with the neurobiology of suicide (<xref ref-type="bibr" rid="B79">Maussion et al., 2012</xref>).</p>
<p>In animal models, miR-139-5p regulates the cAMP/PKA/CREB/BDNF pathway to promote hippocampal neurogenesis by targeting PDE4D. <xref ref-type="bibr" rid="B47">Huang et al. (2021b)</xref> 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, <xref ref-type="bibr" rid="B82">Mingardi et al. (2021)</xref> 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.</p>
</sec>
<sec id="s3-3">
<title>3.3 Role of microRNAs in MDD caused by changes of hypothalamic-pituitary-adrenal axis</title>
<p>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 (<xref ref-type="bibr" rid="B88">Pariante and Lightman, 2008</xref>). 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 (<xref ref-type="bibr" rid="B12">Colla et al., 2007</xref>; <xref ref-type="bibr" rid="B2">Alt et al., 2010</xref>). 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 (<xref ref-type="bibr" rid="B59">Kronenberg et al., 2009</xref>; <xref ref-type="bibr" rid="B103">Schmidt et al., 2009</xref>). As observed in depressed patients, HPA axis activity is the main biochemical change in addition to monoaminergic neurotransmitter disturbances (<xref ref-type="bibr" rid="B7">Budziszewska, 2002</xref>). MicroRNAs can influence the HPA axis activity by affecting glucocorticoid related receptors or other pathways (<xref ref-type="bibr" rid="B118">Uchida et al., 2008</xref>; <xref ref-type="bibr" rid="B123">Vreugdenhil et al., 2009</xref>).</p>
<p>
<xref ref-type="bibr" rid="B101">Roy et al. (2017a)</xref> 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 (<xref ref-type="bibr" rid="B101">Roy et al., 2017a</xref>). 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 (<xref ref-type="bibr" rid="B101">Roy et al., 2017a</xref>).</p>
<p>The central nervous system responses are of greater concern regarding hyperactive HPA axis responses. <xref ref-type="bibr" rid="B1">Al-Rawaf et al. (2021)</xref> 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 (<xref ref-type="bibr" rid="B94">Rajasethupathy et al., 2009</xref>). 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 (<xref ref-type="bibr" rid="B94">Rajasethupathy et al., 2009</xref>). 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 (<xref ref-type="bibr" rid="B87">Numakawa et al., 2009</xref>; <xref ref-type="bibr" rid="B86">Numakawa et al., 2012</xref>; <xref ref-type="bibr" rid="B130">Wibrand et al., 2012</xref>).</p>
</sec>
<sec id="s3-4">
<title>3.4 MicroRNAs are involved in depression caused by abnormal inflammatory response</title>
<p>Depression and inflammation mutually contribute to the development of each other&#x2019;s pathophysiology (<xref ref-type="bibr" rid="B56">Kiecolt-Glaser et al., 2015</xref>). Since the study of T and B lymphocytes in psychiatric patients by <xref ref-type="bibr" rid="B43">Herzog et al. (1979)</xref>, the exploration of the relationship between the inflammatory response and depression has gradually unfolded (<xref ref-type="bibr" rid="B43">Herzog et al., 1979</xref>). 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 (<xref ref-type="bibr" rid="B32">Gibney and Drexhage, 2013</xref>). 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 (<xref ref-type="bibr" rid="B14">Dantzer et al., 2008</xref>). The traditional routes of communication between the periphery and the central involve neural and humoral pathways, which mainly include: neural pathways (<xref ref-type="bibr" rid="B39">Harrison et al., 2009</xref>), signaling <italic>via</italic> cerebral endothelial cells (CECs) (<xref ref-type="bibr" rid="B98">Rivest et al., 2000</xref>; <xref ref-type="bibr" rid="B58">Kobayashi, 2010</xref>), signaling <italic>via</italic> circumventricular organs (CVOs) (<xref ref-type="bibr" rid="B95">Ransohoff et al., 2003</xref>) and peripheral immune-cell-to-brain signaling (<xref ref-type="bibr" rid="B30">Geissmann et al., 2003</xref>). TNF&#x3b1;, IL-1&#x3b2; and IL-6 are the main cytokines involved in the signaling of these pathways (<xref ref-type="bibr" rid="B14">Dantzer et al., 2008</xref>; <xref ref-type="bibr" rid="B9">Capuron and Miller, 2011</xref>). Recently, communication through the gut-microbiota-to-brain rout has gained increasing attention because of its role in regulating brain function (<xref ref-type="bibr" rid="B51">Jenkins et al., 2016</xref>; <xref ref-type="bibr" rid="B107">Sherwin et al., 2016</xref>). MicroRNAs participate in the pathophysiological process of inflammation in depression by promoting the production of inflammatory factors, as shown <xref ref-type="fig" rid="F3">Figure 3</xref>. Changes in cytokine levels in patients with MDD have been identified to be associated with patient mood and volition (<xref ref-type="bibr" rid="B5">Beurel et al., 2020</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Role of microRNAs in inflammatory factors and neurotransmitters in depression. Psychiatric symptoms in humans are influenced by a variety of neurotransmitters and inflammatory factors. Among these inflammatory factors, IL-1&#x3b2;, IL-6, TNF, and IFN&#x3b1; are influenced by microRNA levels.</p>
</caption>
<graphic xlink:href="fphar-14-1129186-g003.tif"/>
</fig>
<p>
<xref ref-type="bibr" rid="B125">Wang et al. (2018a)</xref> 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-&#x3b1; by affecting the transcription of TAR-RNA binding protein (TRBP) and HuR (<xref ref-type="bibr" rid="B125">Wang et al., 2018a</xref>). The upregulation of TNF-&#x3b1; in dlPFC and PBMC was confirmed to be associated with suicidal ideation in MDD patients (<xref ref-type="bibr" rid="B125">Wang et al., 2018a</xref>). <xref ref-type="bibr" rid="B115">Sundquist et al. (2021)</xref> 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&#x2019; psychiatric symptoms (<xref ref-type="bibr" rid="B115">Sundquist et al., 2021</xref>). CircDYM, as an endogenous miR-9 sponge, is able to inhibit the activity of miR-9. <xref ref-type="bibr" rid="B138">Zhang et al. (2020b)</xref>, 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, <xref ref-type="bibr" rid="B133">Xian et al. (2022)</xref> 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 <italic>via</italic> the SOCS2-STAT3 axis. Since then, M1 subtype microglia has produced a large amount of IL-1&#x3b2;, IL-6 and TNF-&#x3b1;. 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 (<xref ref-type="bibr" rid="B6">Borre et al., 2014</xref>; <xref ref-type="bibr" rid="B17">Dubois et al., 2019</xref>; <xref ref-type="bibr" rid="B96">Rea et al., 2020</xref>). 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 <italic>via</italic> 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 (<xref ref-type="bibr" rid="B91">Petra et al., 2015</xref>; <xref ref-type="bibr" rid="B97">Rea et al., 2017</xref>; <xref ref-type="bibr" rid="B24">Farzi et al., 2018</xref>).</p>
</sec>
</sec>
<sec id="s4">
<title>4 Summary and prospect</title>
<p>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.</p>
<p>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 (<xref ref-type="bibr" rid="B111">Stokes, 1995</xref>). In addition, high levels of cortisol inducing loss of hippocampal dendrites, and neuronal plasticity is recognized as one of the causes of depression (<xref ref-type="bibr" rid="B37">Gotlib et al., 2008</xref>). In addition, miR-124 can in turn control serotonin-induced synaptic facilitation by inhibiting the transcription of CREB (<xref ref-type="bibr" rid="B94">Rajasethupathy et al., 2009</xref>). 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 (<xref ref-type="bibr" rid="B117">Troubat et al., 2021</xref>).</p>
<p>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.</p>
<p>Since the discovery of the stable presence of free microRNAs in serum in 2018 (<xref ref-type="bibr" rid="B10">Chen et al., 2008</xref>), 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.</p>
<p>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.</p>
</sec>
</body>
<back>
<sec id="s5">
<title>Author contributions</title>
<p>Conceptualization: SL and XJ Writing&#x2014;original draft: RD, DS, and QZ Writing&#x2014;review and editing: XJ, SL, RD, YW, and J-YW</p>
</sec>
<sec id="s6">
<title>Funding</title>
<p>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).</p>
</sec>
<sec sec-type="COI-statement" id="s7">
<title>Conflict of interest</title>
<p>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.</p>
</sec>
<sec sec-type="disclaimer" id="s8">
<title>Publisher&#x2019;s note</title>
<p>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.</p>
</sec>
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