Clinical Psychopharmacology and Neuroscience 2017; 15(4): 313-319
Peripheral Signatures of Psychiatric Disorders: MicroRNAs
Mehmet Akif Camkurt1, Serkan Güneş2, Salih Coşkun3, and Ebru Fındıklı4
1Department of Psychiatry, Afşin State Hospital, Afşin, Kahramanmaraş, Turkey, 2Department of Child and Adolescent Pscyhiatry, Faculty of Medicine, Mersin University, Mersin, Turkey, 3Department of Medical Genetics, Faculty of Medicine, Dicle Univesity, Diyarbakır, Turkey, 4Department of Psychiatry, Faculty of Medicine, Kahramanmaraş Sütçü İmam University, Kahramanmaraş, Turkey
Correspondence to: Mehmet Akif Camkurt, MD, Department of Psychiatry, Afşin State Hospital, Yeşilyurt Mah., Kemal Ertekin Caddesi., 46500, Afşin/Kahramanmaraş, Turkey, Tel: +90-506-440-44-00, Fax: +90-344-511-29-66, E-mail:
Received: March 21, 2016; Revised: April 11, 2016; Accepted: April 13, 2016; Published online: November 30, 2017.
© The Korean College of Neuropsychopharmacology. All rights reserved.

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

MicroRNAs (miRNAs) are 22 nucleotide long RNA transcripts, their synthesis starts in nucleus and continues in cytoplasm. As being critical for post-transcriptional regulators of gene expression they have been investigated in psychiatric disorders. There are numerous studies performed in peripheral tissues for psychiatric disorders. Here in this article, we aimed to review some common miRNAs denoted significant in at least two studies and their relevance to psychiatric research. We focused on miR-320, miR-106, miR-34, miR-223, miR-107, and miR-134.

Keywords: MicroRNA, Psychiatry, Blood, Plasma, Serum, Biomarker

Diagnosis of psychiatric disorders depends on clinical observations and the subjective experiences of patients. Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD) are the most common classification systems for diagnosis. On the other hand, same clinical manifestations may be defined as a different disorder in different classification systems. Also, classification systems may give different names to same clinical manifestations over the years. In addition, the neurobiology of any psychiatric disorders has not yet been determined exactly. In this context, many biomarker studies have been made in recent years to determine both diagnosis and prognosis of psychiatric disorders. Aims of these studies are making diagnosis, determining prognosis, predicting treatment response, evaluating mental and emotional capacity.1)

Many studies have been conducted in peripheral tissues so far. In these studies, oxidative stress parameters, anti-oxidant enzyme levels, interleukins and brain derived neurotrophic factor (BDNF) have been studied.25) However, a certain biomarker has not been determined yet.


MicroRNA (miRNA) Systhesis

The synthesis of miRNAs starts in the nucleus. RNA polymerase II synthesizes 100–1,000 nucleotide long primiRNAs in the nucleus, these primiRNAs contain 5′ cap and 3′ polyA tail.6) Drosha (which is a nuclear RNase III), its co-factor DiGeorge syndrome critical region protein 8 and several enzymes remove 5′ cap and 3′ polyA tail from primiRNAs, and form premiRNAs in the nucleus.7) The transport of premiRNAs is performed by exportin 5/RanGTP.8) The maturation of miRNAs continues in the cytoplasm. Dicer and its co-factor trans-activator RNA binding protein (TRBP) synthesize mature miRNAs (miRNA duplex) consisted of 20 bp (Dicer clevage).9) Mature miRNAs incorporate to RNA-induced silencing complex (RISC) for gene regulation.10) miRNAs usually point mRNAs to degrade or prevents them from translation.11) With this mechanism increase of miRNAs usually results with decreased expression of target gene. In rare cases miRNAs may increase gene expression. In this way, miRNAs are thought to be capable of affecting the expressions of over 10,000 genes (Figs. 1, 2).12)

Role of miRNAs in Neural Development and Maintenance

miRNAs take part in almost every biological function in our body, especialy in brain. A zebrafish study pointed out mature miRNA injection is beneficial for correcting improper brain development.13) Furthermore, miR-133b is essential for proper development of dopaminergic neurons.14) Transform of stem cells into mature neurons require repression of Sox9 by miR-124 and miR-137 found to be important in development of neural stem cells into mature neurons.15,16) miRNAs are important for not only neurodevelopment but also for maintenance of functioning of neurons. Missing of Dicer was associated with death of neurons.17) The RISC pathway is crucial for synaptic plasticity.18) Increased expression miR-132—which is related to BDNF—has facilitating effects on migration of neurons and dendritic maturation.19,20) For detailed information about the synthesis and functions of miRNAs, the importance of miRNAs for synaptic plasticity and neurogenesis please check reviews by Dwivedi21) and O’Connor et al.22)

miRNAs and Treatment

Limited data exist about therapeutic potential of miRNAs in various diseases. Current focus depends on antagomir-based knock down.23) Although miRNA based treatment approach found beneficial for viral infections there are several challenges in transportation of miRNAs (or nucleic acids) to central nervous system. An oral taken drug should pass through gastrointestinal system without deterioration, cross the blood-brain barrier, reach to target region of the brain without causing a toxic effect. The blood brain barrier is consisted of tight junctions and it is somehow impossible for nucleic acids to cross.24,25) On the other hand, brain itself contains many kind of cells and it has a heterogeneous nature.26) To overcome this issue viral or non-viral vectors may be beneficial with specific advantages and disadvantages. Viral vectors integrates host chromosome well but safety is a major issue.27) In spite of being more safe, non-viral vectors don’t have the ability to cross many barriers to reach out the brain.28)

miRNAs are more stable than mRNAs and their stability makes them as potential diagnostic markers for diseases. Although source of circulating miRNAs isn’t clear, they are considered to be functioning in the communication between cells. This feature of miRNAs increase their likelihood as a biomarker.29) In this review, we are going to discuss some miRNAs and their importance that have been found significant in psychiatric disorders and in peripheral tissue studies (Table 1). We used Google Scholar and PubMed databases to find relevant articles for our review. Main criterion for selection of miRNAs is being significantly dysregulated (up or down) in at least two studies performed in peripheral tissues.


Four studies have been showed differences in the expressions of miR-320 family in psychiatric disorders so far. One of these studies was made by Mundalil Vasu et al.,30) which compared serum miRNA expressions of 55 autistic children with 55 healthy controls. In this study 8 miRNA levels, including miR-320, were found to be decreased compared to the control group, and 5 miRNAs were found to be increased. Moreover, Talebizadeh et al.31) investigated 470 miRNAs including miR-320 in lymphoblastoid cell lines (LCL) of autism patients. They found miR-320 was dysregulated in LCL of autism patients and they propound MECP2, NLGN3, PTEN, AUTS2, TSC1, SLITRK3, SLITRK5, SNRPN as related pathways to miR-320.

In another study comparing the differences of plasma miRNA levels of 16 depressed patients with 14 healthy controls, miR-320d was higher in depression group.32) Study of Camkurt et al.33) including 50 patients with depression and 41 healthy individuals reported that miR-320a levels were significantly lower in patient group. All these results suggest that miR-320 family may be important as a peripheral biomarker in psychiatric disorders. Another important feature of miR-320a is affecting GRIN2A and DISC1 genes that are known to be significant in the etiology of major depression.33)


miR-106 family has been studied quite extensively in psychiatric disorders. In an autism study we mentioned above, miR-320a was found to be decreased, but miR-106-5p showed higher expression in patients with autism.30) Liu et al.32) reported that miR-106a-5p was higher in patients with major depression than in control group. In another study, children with attention deficit hyperactivity disorder showed lower miR-106b-5p levels than healthy controls.34) In the study of Camkurt et al.35) comparing 16 schizophrenia patients with 16 healthy individuals, miR-106b-5p was higher in the schizophrenia group. At this point, giving some information about miR-106 may be useful. As known, interleukin (IL) levels have been studied in psychiatric disorders so far. IL-10 has anti-inflammatory properties, and it has been studied intensively in psychiatric disorders. According to a meta-analysis study, IL-10 has been found to be increased in bipolar disorder. Consistently, it has been showed that miR-106 has post-transcriptional regulatory effects for IL-10.36)

ABCA1 (member 1 of human transporter sub-family ABCA) is a protein that plays a significant role in taking out cholesterol from cells, and it is inhibited by miR-106b. Levels of pregnenolone and dehydroepiandrosterone, which are important in cholesterol metabolism, have been showed to be higher in some psychiatric disorders.37) All of these findings show that miR-106 family is very important for psychiatric disorders, and it is necessary to investigate miR-106 family in detail in future studies.


miR-34 family is probably the most intensely researched group of miRNAs in psychiatric disorders. In a study made by Bocchio-Chiavetto et al.,38) beginning of treatment and 12 weeks of escitalopram treatment were compared for miRNA levels in peripheral blood, and miR-34c-5p was shown to be decreased. In another study, lymphoblastoid cells were exposed to lithium for 16 days, and as a result, miR-34a expression was altered.39)

In a study comparing schizophrenia patients’ miRNA levels with healthy individuals, plasma miR-34 levels were higher than the control group.40) Moreover, miRNA expression levels in mononuclear leukocytes in patients with schizophrenia were evaluated, and miR-34 and other miRNAs were presented as peripheral biomarkers. Further important feature of this study is application of neuro-cognitive tests for phenotyping patients.41) A recent study investigated miR-34b-5p and miR-34c-5p in peripheral blood leukocytes of 32 major depressive disorder (MDD) patients and 32 healthy controls. They found the miR-34b-5p and miR-34c-5p were significantly higher in depressed patients, and Notch1 gene were significantly lower in MDD patients. They draw a conclusion as following; miR-34b-5p and miR-34c-5p levels in peripheral blood leukocytes were closely related to suicide idea and cognitive function and this may serve as biomarkers for the diagnosis of MDD.42)

A study performed for the detection of clinical bio-markers in patients with schizophrenia by Sun et al.43) investigated 10 miRNAs, including miR-34a. Combination of 5 microRNAs including miR-34a revealed a diagnostic specificity of 90.2%, and these 5 miRNAs were suggested to be useful in terms of diagnosis. Likewise miR-34a was determined to be increased in Alzheimer’s patients’ mononuclear cells.44) Besides, miR-34a was observed to be decreased in plasma and cerebrospinal fluid of Alzheimer’s patients.45)

In their study investigating miR-34c as a peripheral bio-marker in plasma for Alzheimer’s disease, Bhatnagar et al.46) showed that the area under the curve was 0.99 in receiver operating characteristic (ROC) analysis, and the r value was 0.7 in correlation analysis. In conclusion, they revealed that miR-34c levels and mini-mental examination showed inverse correlation, and miR-34c might be a good biomarker.

miR-34 family is one of the best examples for understanding the etiology of psychiatric disorders. Peripheral and other biomarker studies suggest that miR-34 family frequently shows expression changes in peripheral tissues, and they are the targets of mood stabilizing drugs.

This intensive knowledge about the miR-34 family probably lead the study of Bavamian et al.47) They showed higher miR-34a expressions in brains of patients with bipolar disorder. Along with the investigation of post-mortem brain tissues, on the other hand they used stem cell modeling to identify the role of miR-34a. They suggest that miR34-a is critical for bipolar disorder in terms of neurodevelopment. Evaluation of their results with peripheral data, it is a clear demonstration of importance of miRNAs for psychiatric disorders and probable correlation between brain and peripheral tissue.


Two studies showed the significance of miR-223 family in peripheral tissues. The first is the previously mentioned study including 50 depressed patients and 41 healthy controls. In this study, miR-223-3p levels were reported to be significantly higher in patients than in controls.33) In another study examining the value of miRNAs as a peripheral biomarker in posttraumatic stress disorder, Balakathiresan et al.48) investigated miRNA changes in amigdala and peripheral blood of animal experiments with fear and stress. Results of this study suggested that 9 miRNAs, including miR-223, could be a potential biomarker.


Wang et al.49) investigated the relationship between miR-107 and BACE1 mRNA gene expressions in plasma for clinical diagnosis of amnestic mild cognitive impairment. They reported that miR-107 expressions in plasma had a high capability to distinguish individuals with amnestic mild cognitive impairment from healthy controls. Furthermore, a study performed in peripheral leukocytes of depressed patients by Sun et al.42) found a positive correlation between N1, P2 latency of P300 and miR-107.


Sheinerman et al.50) evaluated the feasibility of using pairs of brain-enriched plasma miRNA, at least one of which is enriched in synapses and neurites, as biomarkers that could discriminate between patients with mild cognitive impairment and age-matched controls. The identified biomarker pairs fall into two sets: the miR-132 family and the miR-134 family. The area under the curve was 0.91–0.95 in ROC analysis, with sensitivity and specificity at 79–100% (miR-132 family) and 79–95% (miR-134 family), and p<0.001. In a separate study, these miRNA bio-marker pairs successfully detected mild cognitive impairment in most of the patients at asymptomatic stage.50) Rong et al.51) evaluated miR-134 levels before and after treatment for bipolar manic episode, their conclusion was decreased miR-134 level was directly associated with bipolar disorder and miR-134 level was significantly increased after treatment.


The field of miRNA research is constantly getting stronger and expanded. As being epigenetic regulators of gene expression, deeper investigation of miRNAs will probably be promising. Our current knowledge points out miR-34 family as a promising peripheral marker. However there are some points, limitations and obstacles, which need to be overcome in this research field. First, miRNA levels are very sensitive to external factors like diet, exercise, drug use, acute-chronic medical conditions. While including patients, providing homogenous groups is crucial. Moreover, for psychiatric investigations phenotyping of patients according to rating scales, imaging methods or symptomatology may help researchers to acquire better results. Especially, studies focusing on neuro-imaging techniques and association of peripheral miRNA levels in peripheral tissue could be a novel research topic in this regard. Further issue seems to be tissue type. There are diverse peripheral tissue types like mononuclear leukocytes, lymphocytes, plasma and serum. As is known, same miRNA tends to express diversely between tissues or different parts of the same tissue. Future studies should investigate same miRNAs in different peripheral tissue types simultaneously to clarify inter-tissue expression differences. Another point is the source of peripheral circulating miRNAs in plasma or sera of patients. The source of circulating miRNAs is known to be secretion of different tissues.29,52) Although obtaining serum or plasma is feasible, variety of secreting tissues decreases reliability of the results. On the other hand, exosomal circulating miRNA investigations may be helpful to outface this problem.53)

Currently, there are two techniques in miRNA research. One of them is identifying few miRNAs and investigating them in study samples. Limited number of investigated miRNAs is the major limitation for this method.54) Other technique is array method. In this method researcher can study tens or hundreds of miRNAs in one panel. However, some arrays prevent researchers from selecting specific miRNAs to study and that is a limitation. On the other arm, there are some arrays focusing on disease pathways, which we think more reliable to use in research.55)

Before starting a research, miRNA databases should be deeply investigated to detect the most important miRNAs and target genes. There are “validated targets” and “predicted targets” for each miRNA. Although the number of validated targets is very low, researchers may also draw conclusions according to predicted targets, see Table 2 for databases. One more issue is epistatic interactions, which is associated with complexity.56) In general the regulation of miRNAs-genes is not like one miRNA-one gene interaction. In fact, one single miRNA can regulate several genes, and one gene may be target for several miRNAs, check databases mentioned in Table 2.

The types or miRNAs still keep increasing and subtypes are evolving continuously. The more miRNA types increase the more research we will need in this field.

Fig. 1. The synthesis of microRNAs (miRNAs) starts in the nucleus. RNA polymerase II synthesizes primiRNAs with 5′ cap and 3′ polyA tail. Drosha and its co-factor DiGeorge syndrome critical region protein 8 (DGCR8) remove 5′ cap and 3′ polyA tail and form premiRNAs. PremiRNAs are transported by exportin 5/Ran GTP system.
Fig. 2. The maturation of microRNAs (miRNAs) in the cytoplasm. Dicer and its co-factor trans-activator RNA binding protein (TRBP) perform cleavage. Mature miRNAs incorporate to RNA-induced silencing complex (RISC). miRNAs usually point mRNAs 1) to degrade or 2) prevents them from translation. In rare cases miRNAs may 3) increase gene expression.

Importance of microRNAs subject to this review

MicroRNAPsychiatric disorderImportance
miR-320Major depressionmiR-320 family may be important as a peripheral biomarker
AutismmiR-320 was dysregulated in lymphoblastoid cell lines of autism patients
miR-106Major depressionmiR-106a-5p levels was higher in depressed patients
SchizophreniamiR-106b-5p levels was higher in schizophrenia patients
Attention deficit hyperactivity disorderLower miR-106b-5p levels were determined in the control group
AutismmiR-106-5p showed higher expression in autism
miR-34Major depressionmiR-34b-5p and miR-34c-5p levels in peripheral blood leukocytes were closely related to suicide idea and cognitive function
SchizophreniamiR-34 were presented as peripheral biomarkers
Bipolar disordermiR34-a may be critical for bipolar disorder in terms of neurodevelopment
Alzheimer’s diseasemiR-34a was observed to be decreased in plasma and cerebrospinal fluid according to the control group
miR-223Major depressionmiR-223-3p levels were reported to be significantly higher in patients than in controls
Posttraumatic stress disordermiR-223 could be a potential biomarker
miR-107Amnestic mild cognitive impairmentmiR107 expressions in plasma had a high capability to distinguish individuals with amnestic mild cognitive impairment from healthy controls
Major depressionPositive correlation between N1, P2latency of P300 and miR-107 in depressed patients
miR-134Mild cognitive impairmentmiRNA biomarker pairs successfully detected MCI in most of the patients at asymptomatic stage
Bipolar disorderDecreased miR-134 level was directly associated with bipolar disorder

Target detection databases for miRNAs

Database nameWebsite

*Guideline website for detection;

predicted target detection databases;

validated target detection databases.

  1. Singh, I, and Rose, N (2009). Biomarkers in psychiatry. Nature. 460, 202-207.
    Pubmed CrossRef
  2. Nurjono, M, Lee, J, and Chong, SA (2012). A review of brain-derived neurotrophic factor as a candidate biomarker in schizophrenia. Clin Psychopharmacol Neurosci. 10, 61-70.
  3. Neelamekam, S, Nurjono, M, and Lee, J (2014). Regulation of inter-leukin-6 and leptin in schizophrenia patients: a preliminary analysis. Clin Psychopharmacol Neurosci. 12, 209-214.
  4. Ma, SL, and Lam, LC (2011). Panel of genetic variations as a potential non-invasive biomarker for early diagnosis of alzheimer’s disease. Clin Psychopharmacol Neurosci. 9, 54-66.
    Pubmed KoreaMed CrossRef
  5. Camkurt, MA, Fındıklı, E, İzci, F, Kurutaş, EB, and Tuman, TC (2016). Evaluation of malondialdehyde, superoxide dismutase and catalase activity and their diagnostic value in drug naïve, first episode, non-smoker major depression patients and healthy controls. Psychiatry Res. 238, 81-85.
    Pubmed CrossRef
  6. Davis, BN, and Hata, A (2009). Regulation of MicroRNA biogenesis: A miRiad of mechanisms. Cell Commun Signal. 7, 18.
    Pubmed KoreaMed CrossRef
  7. Winter, J, Jung, S, Keller, S, Gregory, RI, and Diederichs, S (2009). Many roads to maturity: microRNA biogenesis pathways and their regulation. Nat Cell Biol. 11, 228-234.
    Pubmed CrossRef
  8. Yi, R, Qin, Y, Macara, IG, and Cullen, BR (2003). Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs. Genes Dev. 17, 3011-3016.
    Pubmed KoreaMed CrossRef
  9. Hutvágner, G, McLachlan, J, Pasquinelli, AE, Bálint, E, Tuschl, T, and Zamore, PD (2001). A cellular function for the RNA-interference enzyme dicer in the maturation of the let-7 small temporal RNA. Science. 293, 834-838.
    Pubmed CrossRef
  10. Gregory, RI, Chendrimada, TP, Cooch, N, and Shiekhattar, R (2005). Human RISC couples microRNA biogenesis and posttranscriptional gene silencing. Cell. 123, 631-640.
    Pubmed CrossRef
  11. Camkurt, MA (2015). MicroRNAs as a new hope for depression. J Mood Disord. 5, 23-30.
  12. Zhang, J, Liu, Q, Zhang, W, Li, J, Li, Z, and Tang, Z (2010). Comparative profiling of genes and miRNAs expressed in the newborn, young adult, and aged human epididymides. Acta Biochim Biophys Sin (Shanghai). 42, 145-153.
  13. Giraldez, AJ, Cinalli, RM, Glasner, ME, Enright, AJ, Thomson, JM, and Baskerville, S (2005). MicroRNAs regulate brain morphogenesis in zebrafish. Science. 308, 833-838.
    Pubmed CrossRef
  14. Kim, J, Inoue, K, Ishii, J, Vanti, WB, Voronov, SV, and Murchison, E (2007). A MicroRNA feedback circuit in midbrain dopamine neurons. Science. 317, 1220-1224.
    Pubmed KoreaMed CrossRef
  15. Cheng, LC, Pastrana, E, Tavazoie, M, and Doetsch, F (2009). miR-124 regulates adult neurogenesis in the subventricular zone stem cell niche. Nat Neurosci. 12, 399-408.
    Pubmed KoreaMed CrossRef
  16. Szulwach, KE, Li, X, Smrt, RD, Li, Y, Luo, Y, and Lin, L (2010). Cross talk between microRNA and epigenetic regulation in adult neurogenesis. J Cell Biol. 189, 127-141.
    Pubmed KoreaMed CrossRef
  17. Schaefer, A, O’Carroll, D, Tan, CL, Hillman, D, Sugimori, M, and Llinas, R (2007). Cerebellar neurodegeneration in the absence of microRNAs. J Exp Med. 204, 1553-1558.
    Pubmed KoreaMed CrossRef
  18. Ashraf, SI, McLoon, AL, Sclarsic, SM, and Kunes, S (2006). Synaptic protein synthesis associated with memory is regulated by the RISC pathway in Drosophila. Cell. 124, 191-205.
    Pubmed CrossRef
  19. Wayman, GA, Davare, M, Ando, H, Fortin, D, Varlamova, O, and Cheng, HY (2008). An activity-regulated microRNA controls dendritic plasticity by down-regulating p250GAP. Proc Natl Acad Sci U S A. 105, 9093-9098.
    Pubmed KoreaMed CrossRef
  20. Vo, N, Klein, ME, Varlamova, O, Keller, DM, Yamamoto, T, and Goodman, RH (2005). A cAMP-response element binding protein-induced microRNA regulates neuronal morphogenesis. Proc Natl Acad Sci U S A. 102, 16426-16431.
    Pubmed KoreaMed CrossRef
  21. Dwivedi, Y (2011). Evidence demonstrating role of microRNAs in the etiopathology of major depression. J Chem Neuroanat. 42, 142-156.
    Pubmed KoreaMed CrossRef
  22. O’Connor, RM, Dinan, TG, and Cryan, JF (2012). Little things on which happiness depends: microRNAs as novel therapeutic targets for the treatment of anxiety and depression. Mol Psychiatry. 17, 359-376.
  23. Lanford, RE, Hildebrandt-Eriksen, ES, Petri, A, Persson, R, Lindow, M, and Munk, ME (2010). Therapeutic silencing of microRNA-122 in primates with chronic hepatitis C virus infection. Science. 327, 198-201.
  24. Braasch, DA, Paroo, Z, Constantinescu, A, Ren, G, Oz, OK, and Mason, RP (2004). Biodistribution of phosphodiester and phosphorothioate siRNA. Bioorg Med Chem Lett. 14, 1139-1143.
    Pubmed CrossRef
  25. O’Brien, FE, Dinan, TG, Griffin, BT, and Cryan, JF (2012). Interactions between antidepressants and P-glycoprotein at the blood-brain barrier: clinical significance of in vitro and in vivo findings. Br J Pharmacol. 165, 289-312.
  26. Thakker, DR, Hoyer, D, and Cryan, JF (2006). Interfering with the brain: use of RNA interference for understanding the pathophysiology of psychiatric and neurological disorders. Pharmacol Ther. 109, 413-438.
  27. Thomas, CE, Ehrhardt, A, and Kay, MA (2003). Progress and problems with the use of viral vectors for gene therapy. Nat Rev Genet. 4, 346-358.
    Pubmed CrossRef
  28. Gao, K, and Huang, L (2009). Nonviral methods for siRNA delivery. Mol Pharm. 6, 651-658.
    Pubmed KoreaMed CrossRef
  29. Etheridge, A, Lee, I, Hood, L, Galas, D, and Wang, K (2011). Extracellular microRNA: a new source of biomarkers. Mutat Res. 717, 85-90.
    Pubmed KoreaMed CrossRef
  30. Mundalil Vasu, M, Anitha, A, Thanseem, I, Suzuki, K, Yamada, K, and Takahashi, T (2014). Serum microRNA profiles in children with autism. Mol Autism. 5, 40.
    Pubmed KoreaMed CrossRef
  31. Talebizadeh, Z, Butler, MG, and Theodoro, MF (2008). Feasibility and relevance of examining lymphoblastoid cell lines to study role of microRNAs in autism. Autism Res. 1, 240-250.
  32. Liu, X, Zhang, L, Cheng, K, Wang, X, Ren, G, and Xie, P (2014). Identification of suitable plasma-based reference genes for miRNAome analysis of major depressive disorder. J Affect Disord. 163, 133-139.
    Pubmed CrossRef
  33. Camkurt, MA, Acar, Ş, Coşkun, S, Güneş, M, Güneş, S, and Yılmaz, MF (2015). Comparison of plasma MicroRNA levels in drug naive, first episode depressed patients and healthy controls. J Psychiatr Res. 69, 67-71.
    Pubmed CrossRef
  34. Kandemir, H, Erdal, ME, Selek, S, Ay, Öİ, Karababa, IF, and Kandemir, SB (2014). Evaluation of several micro RNA (miRNA) levels in children and adolescents with attention deficit hyperactivity disorder. Neurosci Lett. 580, 158-162.
    Pubmed CrossRef
  35. Camkurt, MA, Karababa, İF, Erdal, ME, Bayazıt, H, Kandemir, S, and Kandemir, H (2016). Investigation of dysregulation of several microRNAs in peripheral blood of schizophrenia patients. Clin Psychopharmacol Neurosci. 14, 256-260.
    Pubmed KoreaMed CrossRef
  36. Sharma, A, Kumar, M, Aich, J, Hariharan, M, Brahmachari, SK, and Agrawal, A (2009). Posttranscriptional regulation of interleukin-10 expression by hsa-miR-106a. Proc Natl Acad Sci U S A. 106, 5761-5766.
    Pubmed KoreaMed CrossRef
  37. Marx, CE, Trost, WT, Shampine, LJ, Stevens, RD, Hulette, CM, and Steffens, DC (2006). The neurosteroid allopregnanolone is reduced in prefrontal cortex in Alzheimer’s disease. Biol Psychiatry. 60, 1287-1294.
    Pubmed CrossRef
  38. Bocchio-Chiavetto, L, Maffioletti, E, Bettinsoli, P, Giovannini, C, Bignotti, S, and Tardito, D (2013). Blood microRNA changes in depressed patients during antidepressant treatment. Eur Neuropsychopharmacol. 23, 602-611.
  39. Chen, H, Wang, N, Burmeister, M, and McInnis, MG (2009). MicroRNA expression changes in lymphoblastoid cell lines in response to lithium treatment. Int J Neuropsychopharmacol. 12, 975-981.
    Pubmed KoreaMed CrossRef
  40. Song, HT, Sun, XY, Zhang, L, Zhao, L, Guo, ZM, and Fan, HM (2014). A preliminary analysis of association between the down-regulation of microRNA-181b expression and symptomatology improvement in schizophrenia patients before and after antipsychotic treatment. J Psychiatr Res. 54, 134-140.
    Pubmed CrossRef
  41. Lai, CY, Yu, SL, Hsieh, MH, Chen, CH, Chen, HY, and Wen, CC (2011). MicroRNA expression aberration as potential peripheral blood biomarkers for schizophrenia. PLoS One. 6, e21635.
    Pubmed KoreaMed CrossRef
  42. Sun, N, Lei, L, Wang, Y, Yang, C, Liu, Z, and Li, X (2016). Preliminary comparison of plasma notch-associated microRNA-34b and -34c levels in drug naive, first episode depressed patients and healthy controls. J Affect Disord. 194, 109-114.
    Pubmed CrossRef
  43. Sun, XY, Zhang, J, Niu, W, Guo, W, Song, HT, and Li, HY (2015). A preliminary analysis of microRNA as potential clinical biomarker for schizophrenia. Am J Med Genet B Neuropsychiatr Genet. 168B, 170-178.
    Pubmed CrossRef
  44. Schipper, HM, Maes, OC, Chertkow, HM, and Wang, E (2007). MicroRNA expression in Alzheimer blood mononuclear cells. Gene Regul Syst Bio. 1, 263-274.
    Pubmed KoreaMed
  45. Kiko, T, Nakagawa, K, Tsuduki, T, Furukawa, K, Arai, H, and Miyazawa, T (2014). MicroRNAs in plasma and cerebrospinal fluid as potential markers for Alzheimer’s disease. J Alzheimers Dis. 39, 253-259.
  46. Bhatnagar, S, Chertkow, H, Schipper, HM, Yuan, Z, Shetty, V, and Jenkins, S (2014). Increased microRNA-34c abundance in Alzheimer’s disease circulating blood plasma. Front Mol Neurosci. 7, 2.
  47. Bavamian, S, Mellios, N, Lalonde, J, Fass, DM, Wang, J, and Sheridan, SD (2015). Dysregulation of miR-34a links neuronal development to genetic risk factors for bipolar disorder. Mol Psychiatry. 20, 573-584.
    Pubmed KoreaMed CrossRef
  48. Balakathiresan, NS, Chandran, R, Bhomia, M, Jia, M, Li, H, and Maheshwari, RK (2014). Serum and amygdala microRNA signatures of posttraumatic stress: fear correlation and biomarker potential. J Psychiatr Res. 57, 65-73.
    Pubmed CrossRef
  49. Wang, T, Chen, K, Li, H, Dong, S, Su, N, and Liu, Y (2015). The feasibility of utilizing plasma miRNA107 and BACE1 messenger RNA gene expression for clinical diagnosis of amnestic mild cognitive impairment. J Clin Psychiatry. 76, 135-141.
    Pubmed CrossRef
  50. Sheinerman, KS, Tsivinsky, VG, Crawford, F, Mullan, MJ, Abdullah, L, and Umansky, SR (2012). Plasma microRNA biomarkers for detection of mild cognitive impairment. Aging (Albany NY). 4, 590-605.
  51. Rong, H, Liu, TB, Yang, KJ, Yang, HC, Wu, DH, and Liao, CP (2011). MicroRNA-134 plasma levels before and after treatment for bipolar mania. J Psychiatr Res. 45, 92-95.
  52. De Rosa, S, Fichtlscherer, S, Lehmann, R, Assmus, B, Dimmeler, S, and Zeiher, AM (2011). Transcoronary concentration gradients of circulating microRNAs. Circulation. 124, 1936-1944.
    Pubmed CrossRef
  53. Zhang, J, Li, S, Li, L, Li, M, Guo, C, and Yao, J (2015). Exosome and exosomal microRNA: trafficking, sorting, and function. Genomics Proteomics Bioinformatics. 13, 17-24.
    Pubmed KoreaMed CrossRef
  54. Yang, SW, and Vosch, T (2011). Rapid detection of microRNA by a silver nanocluster DNA probe. Anal Chem. 83, 6935-6939.
    Pubmed CrossRef
  55. Miska, EA, Alvarez-Saavedra, E, Townsend, M, Yoshii, A, Sestan, N, and Rakic, P (2004). Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol. 5, R68.
    Pubmed KoreaMed CrossRef
  56. Phillips, PC (2008). Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems. Nat Rev Genet. 9, 855-867.
    Pubmed KoreaMed CrossRef

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