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Correlation between the level of microRNA expression in peripheral blood mononuclear cells and symptomatology in patients with generalized anxiety disorder
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ScienceDirect Comprehensive Psychiatry 69 (2016) 216 – 224 www.elsevier.com/locate/comppsych
Correlation between the level of microRNA expression in peripheral blood mononuclear cells and symptomatology in patients with generalized anxiety disorder Sheng-dong Chen a, b, 1 , Xin-yang Sun c, 1 , Wei Niu d, 1 , Ling-ming Kong e , Ming-jun He e , Hui-min Fan f , Wan-shuai Li g , Ai-fang Zhong h , Li-yi Zhang e,⁎, Jim Lu g, i,⁎⁎ a
Department of Psychiatry and Psychology, Second Military Medical University, Shanghai 200433, People's Republic of China Department of Neurology, No.102 Hospital of Chinese People's Liberation Army, Changzhou, Jiangsu 213003, People's Republic of China c Department of Psychiatry and Psychology, PingAn Health Cloud Company Ltd. of China, Shanghai 200030, People's Republic of China d Department of Rehabilitation, No.102 Hospital of Chinese People's Liberation Army, Changzhou, Jiangsu 213003, People's Republic of China e Prevention and Treatment Center for Psychological Diseases, No.102 Hospital of Chinese People's Liberation Army, Changzhou 213003, Jiangsu, People's Republic of China f Cadre Ward, Chengdu Military General Hospital, Chengdu, Sichuan 610083, People's Republic of China g GoPath Diagnostic Laboratory Co. Ltd, No.801, Changwuzhong Road, Changzhou, Jiangsu 213164, People's Republic of China h Department of Laboratory, No.102 Hospital of Chinese People's Liberation Army, Changzhou, Jiangsu 213003, People's Republic of China i GoPath Laboratories LLC, 1351 Barclay Blvd, Buffalo, Grove, IL 60089, United States b
Abstract This study investigated the correlation between the level of microRNA expression in peripheral blood mononuclear cells (PBMCs) and symptomatology in patients with generalized anxiety disorder (GAD). MicroRNA array was performed in peripheral blood mononuclear cells (PBMCs) obtained from GAD patients with gender, age, ethnicity-matched healthy controls. Then real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the top 7 miRNAs with the highest fold-change values in 76 GAD patients and 39 healthy controls. It demonstrated that 5 miRNAs showed significantly differences in expression levels (P b 0.01). These 5 GAD-associated miRNAs were finally selected into our study to analyze the association between the plasma level of miRNAs expression and symptomatology scores in Hamilton Anxiety Scale (HAMA). Results showed that the level of miR-4505 and miR-663 was negatively correlated with the total HAMA scores in GAD patients (r = 0.2228, r = 0.264 P b 0.05). MiR-663 was selected into the regression equation of HAMA total scores and psychic anxiety symptomatology scores, and it could explain 5.3% of the HAMA total scores and 15.3% of the anxiety symptomatology scores. This study analyzed preliminarily possible circulating miRNAs expression changes in GAD patients, and the expression level of miR663 highly correlated with psychic anxiety symptoms, further molecular mechanism of which needs to be explored. © 2016 Elsevier Inc. All rights reserved.
⁎ Correspondence to: Li-yi Zhang, Prevention and Treatment Center for Psychological Diseases, NO.102 hospital of Chinese People's Liberation Army, North Peace Road 55, Changzhou, Jiangsu 213003, People's Republic of China. Tel.: +86 519 83064556; fax: +86 519 83064560. ⁎⁎ Correspondence to: J. Lu, GoPath Laboratories LLC, 1351 Barclay Blvd, Buffalo Grove, IL 60089, United States of America; GoPath Diagnostic Laboratory Co. Ltd, No.801, Changwuzhong Road, Changzhou, Jiangsu 213164, People's Republic of China. Toll Free: 1-855-GOPATH9. Fax: + 86 224 588 9941. E-mail addresses: [email protected] (L. Zhang), [email protected] (J. Lu). 1 These authors have contributed equally to this work and agreed to share the first authorship position together. http://dx.doi.org/10.1016/j.comppsych.2016.05.006 0010-440X/© 2016 Elsevier Inc. All rights reserved.
1. Introduction Generalized anxiety disorder (GAD) is common, distressing, and an impairing mental health problem associated with a high lifetime prevalence resulting in significant social costs [1]. Furthermore, anxiety symptoms and disorders often precede the development of other mental and physical disorders, including major depressive disorder, suicide risk, and substance use disorders [2,3]. Despite intensive efforts over several decades, the molecular and cellular mechanisms associated with GAD remain poorly understood. Currently, the diagnosis and treatment of GAD are
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based on the patient's subjective description of symptoms, psychiatrists' subjective assessment of mental status using relevant scales, and clinical behavioral observations. Epigenetic and regulatory elements, such as microRNA (miRNA), provide an additional layer of complexity to the heterogeneity of GAD [4,5]. miRNAs are a class of endogenous small noncoding RNAs that regulate diverse biological processes by negatively modulating gene expression at the posttranscriptional level [6]. miRNAs individually regulate up to several hundred genes, and may collectively regulate as much as 50–60% of the transcriptome [7,8], suggesting that miRNAs may have pleiotropic biological effects. Important roles for miRNA have been recognized in multiple biological processes associated with central nervous system (CNS) functions, such as neurogenesis, neurite outgrowth, neuronal proliferation, synaptogenesis, and synaptic plasticity [9–12]. Recent studies have demonstrated that expression of specific miRNAs can be detected in peripheral blood in many neuropsychiatric diseases [13–15]. Several investigations have also been performed to identify specific miRNAs and their pathways that may contribute to the pathomechanism of GAD [10,16,17]. Uchida et al. reported that downregulation of glucocorticoid receptor (GR) translation via miR-18a may be an important susceptibility mechanism for stress-related disorders in Fischer 344 (F344) rats [18]. Animal studies demonstrated that miR-183 and miR-134 could modify both alternative splicing and cholinergic neurotransmission under stress conditions in the brain, thus providing a link between the molecular and physiological responses of different brain regions to psychological stress [17]. A recent study suggested that miR-34c downregulates stress-related proteins, such as corticotropin releasing factor receptor type 1 (CRFR1), and assists in the stress recovery process. Such miRNAs and their targets may unveil new targets for the treatment of stress-related disorders [19]. Some miRNAs showed inconsistent changes in recent studies, highlighting the dysregulated expression of several miRNAs in experimental mice [20] and in the peripheral blood mononuclear cells (PBMCs) of human patients with Parkinson's disease, reflecting brain-related changes [21]. Some of these discrepancies can be attributed to differences among anatomical and functional regions of the brain or peripheral tissues, and also to sources of technical variation, such as tissue collection, the RNA isolation protocol (total RNA vs. small RNA enriched, electrophoresis vs. solvent extraction), amplification, array platform, chemistry, and normalization methods. Gene expression profiling and the levels of certain mRNAs in the blood were shown to be related to brain levels, which appear to be very stable [22,23]; therefore, a growing number of studies on psychiatric illness have focused on miRNAs in peripheral blood. Altered peripheral miRNA expression has been detected in some mental disorders, such as schizophrenia, bipolar disorder, major depressive disorder, and Alzheimer's disease [14,15,24,25].
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Interestingly, the results of miRNA expression profiling are closely correlated with clinical symptoms [14], suggesting that lymphocytes may reflect the metabolism of brain cells. However, it remains unclear which miRNAs in PBMCs contribute to the pathomechanism of GAD, which miRNAs have the greatest influence on the symptomatology of GAD, and whether it is possible for the expression levels of certain miRNAs to be used to predict the diversity and severity of symptomatology. Here, we hypothesized that GAD-related miRNAs could be detectable in PBMCs, and that certain miRNAs could serve as biomarkers to predict the severity of symptomatology in patients with GAD. Using miRNA microarray analysis, we examined array-based miRNA profiles in PBMCs from a set of patients with GAD and healthy controls. Then, 5 miRNAs (miR-4484, miR-4674, miR-501-3p, miR-663, and miR-4505) were selected to study the association between the PBMC levels of miRNA expression and symptomatology in 76 patients with GAD to test our hypothesis and to provide an experimental basis for the correlation between the levels of microRNA expression and symptomatology in patients with GAD. 2. Materials and methods 2.1. Patients The study population was selected from a group of patients with GAD admitted to the No.102 Hospital of the Chinese People's Liberation Army from July 2013 to May 2014. The inclusion criteria were as follows: patients aged between 18 and 65 years that fulfilled the criteria for GAD as set forth by the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV). The patients were either first-time visitors or prior to any clinical treatment, or drug-naive from any antidepressant or antianxiolytic agents for at least 3 months before enrollment in the study. The exclusion criteria were as follows: personal history of medical diseases, other psychiatric disorders, structural brain disorders, mental retardation, unstable psychiatric features, and movement disorders. Patients with brain injury causing traumatic amnesia longer than 24 h, and who had received a blood transfusion within 1 month or electroconvulsive therapy within 6 months, were excluded from the study. Clinical diagnoses were made independently by at least two psychiatrists, and were further confirmed by an additional chief psychiatrist. A total of 76 patients were enrolled, and general information (including name, gender, age, ethnicity, education level, occupation, income level, marital status, substance abuse history, and family history of psychiatric diseases) was collected from all subjects in the GAD group. All of the patients were assessed using the Hamilton Anxiety Scale (HAMA) by well-trained research assistants with backgrounds in psychology or psychiatry. In addition, 39 healthy controls without any family history of psychiatric disorders (schizophrenia, bipolar
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disorder, GAD, or major depression) were recruited. All healthy controls had no history of blood transfusion or severe traumatic events within 1 month. Patients and healthy controls were matched for gender, age, and ethnicity. The study was approved by the local ethics committee and written informed consent was obtained from the subjects. 2.2. HAMA HAMA is a 14-item test measuring the severity of anxiety symptoms, which was developed by Max Hamilton in 1959 [26]. This test provides measures of overall anxiety, psychic anxiety (mental agitation and psychological distress), and somatic anxiety (physical complaints related to anxiety), and is now widely used for measuring the severity of a patient's anxiety. Each of the 14 items includes a number of symptoms, and each group of symptoms is rated on a scale of 0–4, with 4 being the most severe. All of these scores are used to compute an overarching score that indicates a person's anxiety severity. In this study, all patients were evaluated for the HAMA total score, the 7-item HAMA psychic subscale (item 1, anxious mood; item 2,tension; item 3, fears; item 4, insomnia; item 5, intellectual; item 6, depressed mood; and item 14, behavior at interview), and the 7-item somatic anxiety subscale [item 7, somatic (muscular); item 8, somatic (sensory); item 9, cardiovascular symptoms; item 10, respiratory symptoms; item 11, gastrointestinal symptoms; item 12, genitourinary symptoms; and item 13, autonomic symptoms], as well as the individual items in each subscale. 2.3. Blood collection and RNA extraction Whole blood (5 mL) was collected from each subject using (EDTA) anticoagulant tubes and processed within 3 h. PBMCs were isolated from the blood by Ficoll density centrifugation, transferred into fresh RNase/DNase-free 2-mL microcentrifuge tubes, and stored at − 80°C until use. Total RNA was isolated from the PBMC with a mirVana ™ PARIS™ kit (P/N: AM1556; Applied Biosystems, Foster City, CA). The RNA concentration and quality were measured with a NanoDrop™ ND-2100 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE). The integrity of the RNA was assessed using an Agilent 2100 (Agilent Technologies, Atlanta, GA). To ensure robust analysis for the following procedures, samples with an RNA integrity number (RIN) b 8 were excluded [27,28]. 2.4. miRNA microarray expression profiling RNA samples from 3 patients with GAD (male, 23 years; male, 32 years; female, 29 years) and 3 controls (male, 23 years; male, 32 years; female, 29 years) were used for miRNA microarray profiling. miRNA expression was measured using an Affymetrix miRNA 3.0 Array (Affymetrix, Santa Clara, CA) containing probes for a total of 723 human miRNAs. Sample labeling, microarray hybridization, and washing were performed based on the manufacturer's
standard protocols. Briefly, total RNA was tailed with poly(A) and then labeled with biotin. The labeled RNAs were then hybridized onto the microarray. After washing and staining the slides, the arrays were scanned with an Affymetrix Scanner 3000 (Affymetrix). The scanned images were analyzed using Expression Console software (version 1.3.1; Affymetrix). 2.5. Real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR) The top 7 miRNAs with significant differential expression changes according to the microarray results were chosen for further validation with real-time qRT-PCR. Blood samples from 76 patients with GAD were used to validate the findings of the miRNA profiling. Total RNA was extracted from the purified plasma using a mirVana™ PARIS™ kit (P/N: AM1556; Applied Biosystems) for quantitative detection of miRNA. Complementary DNA was synthesized using a Reverse Transcription TaqMan® MicroRNA Reverse Transcription Kit and miRNA-specific stem–loop primers (P/N: 4,366,596; Applied Biosystems) according to the manufacturer's instructions. The RT reaction mixture consisted of 5 μL of total RNA (~ 10 ng), 0.15 μL of dNTPs with dTTP (100 mM), 1.00 μL of multiscribe RT enzyme (50 U/μL), 1.5 μL of 10 × RT buffer, 0.19 μL of RNase inhibitor (20 U/μL), 4.16 μL of nuclease-free water, and 3 μL of 5 × RT primer in a total volume of 15 μL. Reactions were performed under the following conditions: 16°C for 30 min, 42°C for 30 min, 85°C for 5 min, and held at 4°C. Real-time PCR was performed using an Applied Biosystems 7900HT Real-Time PCR System (Applied Biosystems) with 10 μL of PCR mixture that included 2 μL of cDNA, 5 μL of 2 × TaqMan® Universal PCR Master Mix II (Applied Biosystems), 0.5 μL of 20 × miRNA-specific PCR primer/probe mix (Applied Biosystems), and 2.5 μL of nuclease-free water. PCR was performed in 384-well plates at 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. Each sample was run in triplicate for analysis. The 5 × RT primers (miRNA -specific stem–loop primers) and 20 × miRNA-specific PCR primer/probe mix were supplied with the TaqMan® MicroRNA Assay (Applied Biosystems) based on the miRNA sequences obtained from the miRBase database (http://www.mirbase.org). Data were collected using SDS 2.3 software (Applied Biosystems). After normalization relative to RNU48, the expression levels of miRNAs were calculated using the 2 − ΔΔCt method [28,29]. The numbers of PCR cycles for each miRNA in qRT-PCR are shown in Table 1. 2.6. Statistical analysis Demographic variables were compared between patients and matched controls by Fisher's exact test for qualitative variables and t-tests for quantitative variables. Expression levels of miRNAs were compared between the patient and
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3.2. miRNA microarray expression profiling
Table 1 PCR cycles for each identified miRNAs in qRT-PCR. miRNA
PCR cycles
miR-4505 miR-1301 miR-432-5p miR-4484 miR-4674 miR-501-3p miR-663 RNU48
26.0 26.0 22.0 17.0 20.2 25.0 21.0 14.0
control groups using Students' t-tests. Pearson's correlation test was carried out to test the correlations of miRNA expression levels with HAMA psychic and somatic anxiety symptomatology scores, and multivariate regression analysis was performed to determine the responsibility of miRNAs levels for the diversity of symptomatology. All statistical analyses were carried out using DataAssist version 3.0 software, and SPSS version 21.0 software (SPSS, Chicago, IL). In all analyses, P b 0.05 (two-tailed) was taken to indicate statistical significance.
3. Results 3.1. Clinical characteristics of the patients As shown in Table 2, the mean ages (mean ± standard deviation [SD]) of patients in the case and control groups were 47.03 ± 13.20 and 46.06 ± 14.26 years, respectively. All of the patients and controls were of Han Chinese ethnicity, and there were no differences in age, sex, or residential locations between the patients with GAD and the healthy controls. The mean HAMA score was 24.38 ± 3.79.
Table 2 Demographic data of different groups.
Controls (n = 39)
GAD (n = 76)
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Comparisons of demographic variables between the GAD group and the control group
Using 6 blood samples (3 patients with GAD and 3 controls) for microarray profiling, 7 miRNAs were identified with significant differences in expression level between the patients with GAD and the controls (fold-change ≥ 2; P b 0.05). Of these, 5 miRNAs were upregulated and 2 were downregulated. The list of differentially expressed miRNAs identified by the microarray analysis is shown in Table 3. In unsupervised hierarchical clustering analysis, the normalized microarray expression data for the 7 miRNAs showing differential expression were used to generate a heat map. Hierarchical clustering was performed using the Euclidean metric and complete linkage rule. The samples were self-segregated into the patients with GAD and control clusters (Fig. 1). 3.3. Real-time qRT-PCR validation To validate the results of the microarray assay, the 7 miRNAs (miR-1301, miR-432-5p, miR-4484, miR-4674, miR-501-3p, miR-663, and miR-4505) with differential expression were examined in a larger sample (76 cases and 39 controls) using the qRT-PCR method. Using RNU48 as a normalization control, 5 miRNAs were upregulated in patients with GAD compared with normal controls (P b 0.05), showing the same tendency as the microarray results; 2 miRNAs (miR-1301, miR-432-5p) were also upregulated in patients with GAD, in contrast to the microarray results (Fig. 2). We selected the 5 miRNAs with significant differential expression (miR-4484, miR-4674, miR-501-3p, miR-663, and miR-4505) that were in accordance with the microarray results for further study. 3.4. Comparison of miRNA expression, symptomatology scores, and total score in patients with GAD Pearson's correlation test was carried out to test the correlations of miRNA expression levels with HAMA total scores, psychic, and somatic anxiety symptomatology scores (Figs. 3–5). The levels of miR-4505 and miR-663 expression were negatively correlated with the total HAMA scores in patients with GAD (r = 0.2228, r = 0.264, P b 0.05). We also found a significant negative correlation between all 5 miRNAs (miR-4505, miR-4484, miR-4674, miR-501-3p,
Statistics p Value Age Mean(SD) Range Media Gender Boys Girls Ethnicity Han ethnicity Educational levels Junior high and below Senior high and above
47.03 ± 13.20 46.06 ± 14.6 t = 1.56
0.349
9 30
19 57
0.005
0.856
–
76
–
–
–
40 36
–
–
Table 3 Differentially expressed microRNAs identified by microarray analysis in PBMCs from GAD patients versus controls. miRNA
Fold-change
Regulation
p Value
has-miR-1301 has-miR-432-5p has-miR-4484 has-miR-4674 has-miR-501-3p has-miR-663 has-miR-4505
2.2144198 5.777223 2.6435952 5.227357 2.5043268 3.0083036 5.30872
Down Down Up Up Up Up Up
0.044 0.029 0.028 0.033 0.020 0.030 0.014
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HAMA total scores and 15.3% of the anxiety symptomatology scores (Table 4).
4. Discussion
Fig. 1. Heatmap showing 7 miRNAs differential expression in PBMCs from GAD patients (n = 3) and controls (n = 3). Rows represent miRNAs species, and columns represent individual plasma sample. The relative miRNA expression is depicted according to the color scale. Red indicates up-regulation; green indicates downregulation. The numbers with JLZ denote GAD; numbers with NC denote normal controls.
and miR-663) and the psychic anxiety symptomatology scores (Fig. 4) (P b 0.01). 3.5. Stepwise regression analysis on miRNA expression for HAMA symptomatology Stepwise regression analysis was performed using the levels of miRNA expression (miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663) as independent variables, and the HAMA total scores, psychic, and somatic anxiety symptomatology scores as dependent variables. The results showed that miR-663 was selected into the regression equation of the HAMA total scores and the psychic anxiety symptomatology score, and could explain 5.3% of the
At present, the diagnosis of GAD is symptom-based in accordance with the DSM-IV criteria, which depend on the patient's subjective description of symptoms, psychiatrists' assessment of mental status with the HAMA scale, and clinical behavioral observations. However, there are no reliable circulating biomarkers for GAD symptom prediction, diagnosis, or outcome prediction. There is emerging evidence suggesting that numerous miRNAs are abundantly expressed in the brain [12,30] and that they play crucial roles in regulating various neurobiological processes, such as the establishment and maintenance of dendrites [31] and neurite outgrowth [32]. In previous studies, we showed that circulating miRNAs were associated with human schizophrenia and major depressive disorder [14,15]. It has been increasingly accepted that aberrant expression of certain miRNAs has a significant role in the underlying pathophysiology of GAD [33]. Investigation of gene elements, such miRNAs, in GAD is critical to understanding the genetic etiology of this disorder. However, there have been few studies focusing on the association between changes in miRNA expression and the psychic and somatic anxiety symptomatology in patients with GAD. To date, there have been few studies of miRNAs in GAD. Several researchers have attempted to identify specific miRNAs and their targets responsible for regulating synaptic function in GAD. Honda et al. examined alterations in
Fig. 2. Differentially expressed microRNAs identified by microarray analysis in PBMCs from GAD patients versus controls.
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Fig. 3. Correlation coefficients between the level of miRNAs and HAMA total scores.
miRNA profiles in peripheral blood from 25 male medical students 2 months and 2 days before the National Examination for Medical Practitioners. The levels of 7 miRNAs (miR-16, miR-20b, miR-26b, miR-29a, miR-126, miR-144, and miR-144*) were significantly elevated during the pre-examination period in association with significant downregulation of their target mRNAs (WNT4, CCM2, MAK, and FGFR1), 2 days before the examination. They concluded that a distinct group of miRNAs in peripheral
blood may participate in the integrated response to chronic academic stress in healthy young men [34]. Zhou et al. found fluctuating levels of various hippocampal miRNAs (let-7b, let-7c, miR-24a, miR-30c, miR-34a, miR-128a, miR-144, and miR-221) following chronic treatment with the mood stabilizers lithium and valproate [9]. In the present study, the levels of circulating miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663 were upregulated in the GAD group compared with the control
Fig. 4. Correlation coefficients between the level of miRNAs and psychic anxiety symptomatology scores.
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Fig. 5. Correlation coefficients between the level of miRNAs and somatic anxiety symptomatology scores.
group. All 5 of these miRNAs were negatively correlated with psychic anxiety symptomatology scores. Both miR-4505 and miR-663 were negatively correlated with the HAMA total score. The most important findings of this study were that miRNA-663 was selected into the regression equation of the HAMA total scores and psychic anxiety symptoms, and could explain 5.7% of the HAMA total scores and 15.3% of the psychic anxiety symptoms. miRNAs have been shown to play significant roles in early mammalian development. Both acute and chronic stress are connected to the development of anxiety disorders through complex mechanisms related to neural plasticity [16,35]. We found differences in the levels of miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663 between the GAD group and the control group that have not been reported previously to be involved in GAD. The reported functions of these miRNAs were mostly associated with human cancer [36–38]. However, recent studies have shown that miR-501-3p plays an important role in the processes of neurogenesis and
neuronal differentiation, suggesting that miR-501-3p may participate in regulating the development of the CNS [39]. miR-663, which is expressed in Homo sapiens and Pan troglodytes, belongs to the primate-specific miRNAs, which may be associated with vertebrate evolution, development, and neuronal differentiation, and may be involved in the etiology of numerous psychiatric disorders [40,41]. The relationship between stress-induced differences in senescence and miR-663 have been reported [42,43]. Maes et al. observed higher levels of miR-663 in both replicative and stress-induced senescence in vitro [43]. Furthermore, Hackl et al. detected higher levels of miR-663 expressed by fibroblasts and memory T cells derived from older donors compared with younger donors [44]. The precise mechanisms by which miR-663 could act in GAD and psychic anxiety symptoms remain to be explored. Recently, upregulation of miR-663 in tumor tissue was found with longer periods of ischemia, indicating that miR-663 affected the stress response through FOSB [45]. Here, we observed a
Table 4 Step-wise regression analysis on miRNA expression for symptomatology. Dependent variable HAMA total score Psychic symptoms
Model (Constant) hsa-miR-663 (Constant) hsa-miR-663
Unstandardized coefficients
Standardized coefficients
B
Std. Error
25.119 -0.237 15.037 -0.306
0.549 0.100 0.438 0.080
R2
t
p
45.788 -2.356 34.293 -3.815
b0.0001 0.021 b0.0001 0.0001
Beta -0.264 0.405
0.057 0.153
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negative correlation between the level of miR-663 and psychic anxiety symptom scores, which was likely a reflection of the variability and complexity of the GAD process. These observations support the suggestion that miR-663 may participate in the process of stress, which could contribute to the etiology of GAD psychic symptoms. We further performed bioinformatics analyses with regard to the 5 significantly upregulated miRNAs (hasmiR-4484, has-miR-4505, has-miR-4674, has-miR-501-3p, and has-miR-663) in patients with GAD, which demonstrated that these miRNAs participated in various biological processes, including nervous system development, nerve growth factor receptor signaling pathways, neuron migration, dendrite development, regulation of neuron projection development, midbrain development, regulation of excitatory postsynaptic membrane potential, gliogenesis, dendrite morphogenesis, etc. [46]. Genetics represents an important potential source of differences between patients with GAD and controls. Hanin et al. showed that miR-608 targets acetylcholinesterase (AChE) and demonstrated weakened miR-608 interaction with the rs17228616 AChE allele, which has a single-nucleotide polymorphism SNP in the 3′-untranslated region (3′UTR). They found that minor rs17228616 allele heterozygous and homozygous subjects showed elevated risks of inherited anxiety and hypertension [47]. The SNPs in the vicinity of the identified miRNAs were sought in the Web-available genome-wide association study (GWAS) datasets, and miRNA-related SNPs are listed in Supplementary table 2. Detailed bioinformatics analyses of these miRNAs are currently underway, and the molecular mechanisms by which these miRNAs participate in the pathogenesis and development of GAD must be explored. In summary, our data demonstrated significant changes in the circulating levels of miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663 in patients with GAD, suggesting that these miRNAs are potentially involved in the pathogenesis of GAD. The upregulation of miR-663 expression predicts psychic anxiety symptoms in patients with GAD and can thus serve as a therapeutic target of antianxiety drugs. Further, miR-663 likely plays significant roles in the symptomatology of patients with GAD. The specific mechanism underlying this interaction warrants further investigation.
5. Limitations Several general limitations of our study should be acknowledged. First, the sample size was relatively small for the analysis. The small number of subjects in the control group relative to the GAD group may have decreased the statistical power for comparison of miRNA expression levels between the GAD and control groups. Therefore, further validation in larger cohorts is needed to better evaluate the suitability and specificity of the 5 miRNA signatures as biomarkers. Second, we found that the upregulation of
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ScienceDirect Comprehensive Psychiatry 69 (2016) 216 – 224 www.elsevier.com/locate/comppsych
Correlation between the level of microRNA expression in peripheral blood mononuclear cells and symptomatology in patients with generalized anxiety disorder Sheng-dong Chen a, b, 1 , Xin-yang Sun c, 1 , Wei Niu d, 1 , Ling-ming Kong e , Ming-jun He e , Hui-min Fan f , Wan-shuai Li g , Ai-fang Zhong h , Li-yi Zhang e,⁎, Jim Lu g, i,⁎⁎ a
Department of Psychiatry and Psychology, Second Military Medical University, Shanghai 200433, People's Republic of China Department of Neurology, No.102 Hospital of Chinese People's Liberation Army, Changzhou, Jiangsu 213003, People's Republic of China c Department of Psychiatry and Psychology, PingAn Health Cloud Company Ltd. of China, Shanghai 200030, People's Republic of China d Department of Rehabilitation, No.102 Hospital of Chinese People's Liberation Army, Changzhou, Jiangsu 213003, People's Republic of China e Prevention and Treatment Center for Psychological Diseases, No.102 Hospital of Chinese People's Liberation Army, Changzhou 213003, Jiangsu, People's Republic of China f Cadre Ward, Chengdu Military General Hospital, Chengdu, Sichuan 610083, People's Republic of China g GoPath Diagnostic Laboratory Co. Ltd, No.801, Changwuzhong Road, Changzhou, Jiangsu 213164, People's Republic of China h Department of Laboratory, No.102 Hospital of Chinese People's Liberation Army, Changzhou, Jiangsu 213003, People's Republic of China i GoPath Laboratories LLC, 1351 Barclay Blvd, Buffalo, Grove, IL 60089, United States b
Abstract This study investigated the correlation between the level of microRNA expression in peripheral blood mononuclear cells (PBMCs) and symptomatology in patients with generalized anxiety disorder (GAD). MicroRNA array was performed in peripheral blood mononuclear cells (PBMCs) obtained from GAD patients with gender, age, ethnicity-matched healthy controls. Then real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the top 7 miRNAs with the highest fold-change values in 76 GAD patients and 39 healthy controls. It demonstrated that 5 miRNAs showed significantly differences in expression levels (P b 0.01). These 5 GAD-associated miRNAs were finally selected into our study to analyze the association between the plasma level of miRNAs expression and symptomatology scores in Hamilton Anxiety Scale (HAMA). Results showed that the level of miR-4505 and miR-663 was negatively correlated with the total HAMA scores in GAD patients (r = 0.2228, r = 0.264 P b 0.05). MiR-663 was selected into the regression equation of HAMA total scores and psychic anxiety symptomatology scores, and it could explain 5.3% of the HAMA total scores and 15.3% of the anxiety symptomatology scores. This study analyzed preliminarily possible circulating miRNAs expression changes in GAD patients, and the expression level of miR663 highly correlated with psychic anxiety symptoms, further molecular mechanism of which needs to be explored. © 2016 Elsevier Inc. All rights reserved.
⁎ Correspondence to: Li-yi Zhang, Prevention and Treatment Center for Psychological Diseases, NO.102 hospital of Chinese People's Liberation Army, North Peace Road 55, Changzhou, Jiangsu 213003, People's Republic of China. Tel.: +86 519 83064556; fax: +86 519 83064560. ⁎⁎ Correspondence to: J. Lu, GoPath Laboratories LLC, 1351 Barclay Blvd, Buffalo Grove, IL 60089, United States of America; GoPath Diagnostic Laboratory Co. Ltd, No.801, Changwuzhong Road, Changzhou, Jiangsu 213164, People's Republic of China. Toll Free: 1-855-GOPATH9. Fax: + 86 224 588 9941. E-mail addresses: [email protected] (L. Zhang), [email protected] (J. Lu). 1 These authors have contributed equally to this work and agreed to share the first authorship position together. http://dx.doi.org/10.1016/j.comppsych.2016.05.006 0010-440X/© 2016 Elsevier Inc. All rights reserved.
1. Introduction Generalized anxiety disorder (GAD) is common, distressing, and an impairing mental health problem associated with a high lifetime prevalence resulting in significant social costs [1]. Furthermore, anxiety symptoms and disorders often precede the development of other mental and physical disorders, including major depressive disorder, suicide risk, and substance use disorders [2,3]. Despite intensive efforts over several decades, the molecular and cellular mechanisms associated with GAD remain poorly understood. Currently, the diagnosis and treatment of GAD are
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based on the patient's subjective description of symptoms, psychiatrists' subjective assessment of mental status using relevant scales, and clinical behavioral observations. Epigenetic and regulatory elements, such as microRNA (miRNA), provide an additional layer of complexity to the heterogeneity of GAD [4,5]. miRNAs are a class of endogenous small noncoding RNAs that regulate diverse biological processes by negatively modulating gene expression at the posttranscriptional level [6]. miRNAs individually regulate up to several hundred genes, and may collectively regulate as much as 50–60% of the transcriptome [7,8], suggesting that miRNAs may have pleiotropic biological effects. Important roles for miRNA have been recognized in multiple biological processes associated with central nervous system (CNS) functions, such as neurogenesis, neurite outgrowth, neuronal proliferation, synaptogenesis, and synaptic plasticity [9–12]. Recent studies have demonstrated that expression of specific miRNAs can be detected in peripheral blood in many neuropsychiatric diseases [13–15]. Several investigations have also been performed to identify specific miRNAs and their pathways that may contribute to the pathomechanism of GAD [10,16,17]. Uchida et al. reported that downregulation of glucocorticoid receptor (GR) translation via miR-18a may be an important susceptibility mechanism for stress-related disorders in Fischer 344 (F344) rats [18]. Animal studies demonstrated that miR-183 and miR-134 could modify both alternative splicing and cholinergic neurotransmission under stress conditions in the brain, thus providing a link between the molecular and physiological responses of different brain regions to psychological stress [17]. A recent study suggested that miR-34c downregulates stress-related proteins, such as corticotropin releasing factor receptor type 1 (CRFR1), and assists in the stress recovery process. Such miRNAs and their targets may unveil new targets for the treatment of stress-related disorders [19]. Some miRNAs showed inconsistent changes in recent studies, highlighting the dysregulated expression of several miRNAs in experimental mice [20] and in the peripheral blood mononuclear cells (PBMCs) of human patients with Parkinson's disease, reflecting brain-related changes [21]. Some of these discrepancies can be attributed to differences among anatomical and functional regions of the brain or peripheral tissues, and also to sources of technical variation, such as tissue collection, the RNA isolation protocol (total RNA vs. small RNA enriched, electrophoresis vs. solvent extraction), amplification, array platform, chemistry, and normalization methods. Gene expression profiling and the levels of certain mRNAs in the blood were shown to be related to brain levels, which appear to be very stable [22,23]; therefore, a growing number of studies on psychiatric illness have focused on miRNAs in peripheral blood. Altered peripheral miRNA expression has been detected in some mental disorders, such as schizophrenia, bipolar disorder, major depressive disorder, and Alzheimer's disease [14,15,24,25].
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Interestingly, the results of miRNA expression profiling are closely correlated with clinical symptoms [14], suggesting that lymphocytes may reflect the metabolism of brain cells. However, it remains unclear which miRNAs in PBMCs contribute to the pathomechanism of GAD, which miRNAs have the greatest influence on the symptomatology of GAD, and whether it is possible for the expression levels of certain miRNAs to be used to predict the diversity and severity of symptomatology. Here, we hypothesized that GAD-related miRNAs could be detectable in PBMCs, and that certain miRNAs could serve as biomarkers to predict the severity of symptomatology in patients with GAD. Using miRNA microarray analysis, we examined array-based miRNA profiles in PBMCs from a set of patients with GAD and healthy controls. Then, 5 miRNAs (miR-4484, miR-4674, miR-501-3p, miR-663, and miR-4505) were selected to study the association between the PBMC levels of miRNA expression and symptomatology in 76 patients with GAD to test our hypothesis and to provide an experimental basis for the correlation between the levels of microRNA expression and symptomatology in patients with GAD. 2. Materials and methods 2.1. Patients The study population was selected from a group of patients with GAD admitted to the No.102 Hospital of the Chinese People's Liberation Army from July 2013 to May 2014. The inclusion criteria were as follows: patients aged between 18 and 65 years that fulfilled the criteria for GAD as set forth by the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV). The patients were either first-time visitors or prior to any clinical treatment, or drug-naive from any antidepressant or antianxiolytic agents for at least 3 months before enrollment in the study. The exclusion criteria were as follows: personal history of medical diseases, other psychiatric disorders, structural brain disorders, mental retardation, unstable psychiatric features, and movement disorders. Patients with brain injury causing traumatic amnesia longer than 24 h, and who had received a blood transfusion within 1 month or electroconvulsive therapy within 6 months, were excluded from the study. Clinical diagnoses were made independently by at least two psychiatrists, and were further confirmed by an additional chief psychiatrist. A total of 76 patients were enrolled, and general information (including name, gender, age, ethnicity, education level, occupation, income level, marital status, substance abuse history, and family history of psychiatric diseases) was collected from all subjects in the GAD group. All of the patients were assessed using the Hamilton Anxiety Scale (HAMA) by well-trained research assistants with backgrounds in psychology or psychiatry. In addition, 39 healthy controls without any family history of psychiatric disorders (schizophrenia, bipolar
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disorder, GAD, or major depression) were recruited. All healthy controls had no history of blood transfusion or severe traumatic events within 1 month. Patients and healthy controls were matched for gender, age, and ethnicity. The study was approved by the local ethics committee and written informed consent was obtained from the subjects. 2.2. HAMA HAMA is a 14-item test measuring the severity of anxiety symptoms, which was developed by Max Hamilton in 1959 [26]. This test provides measures of overall anxiety, psychic anxiety (mental agitation and psychological distress), and somatic anxiety (physical complaints related to anxiety), and is now widely used for measuring the severity of a patient's anxiety. Each of the 14 items includes a number of symptoms, and each group of symptoms is rated on a scale of 0–4, with 4 being the most severe. All of these scores are used to compute an overarching score that indicates a person's anxiety severity. In this study, all patients were evaluated for the HAMA total score, the 7-item HAMA psychic subscale (item 1, anxious mood; item 2,tension; item 3, fears; item 4, insomnia; item 5, intellectual; item 6, depressed mood; and item 14, behavior at interview), and the 7-item somatic anxiety subscale [item 7, somatic (muscular); item 8, somatic (sensory); item 9, cardiovascular symptoms; item 10, respiratory symptoms; item 11, gastrointestinal symptoms; item 12, genitourinary symptoms; and item 13, autonomic symptoms], as well as the individual items in each subscale. 2.3. Blood collection and RNA extraction Whole blood (5 mL) was collected from each subject using (EDTA) anticoagulant tubes and processed within 3 h. PBMCs were isolated from the blood by Ficoll density centrifugation, transferred into fresh RNase/DNase-free 2-mL microcentrifuge tubes, and stored at − 80°C until use. Total RNA was isolated from the PBMC with a mirVana ™ PARIS™ kit (P/N: AM1556; Applied Biosystems, Foster City, CA). The RNA concentration and quality were measured with a NanoDrop™ ND-2100 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE). The integrity of the RNA was assessed using an Agilent 2100 (Agilent Technologies, Atlanta, GA). To ensure robust analysis for the following procedures, samples with an RNA integrity number (RIN) b 8 were excluded [27,28]. 2.4. miRNA microarray expression profiling RNA samples from 3 patients with GAD (male, 23 years; male, 32 years; female, 29 years) and 3 controls (male, 23 years; male, 32 years; female, 29 years) were used for miRNA microarray profiling. miRNA expression was measured using an Affymetrix miRNA 3.0 Array (Affymetrix, Santa Clara, CA) containing probes for a total of 723 human miRNAs. Sample labeling, microarray hybridization, and washing were performed based on the manufacturer's
standard protocols. Briefly, total RNA was tailed with poly(A) and then labeled with biotin. The labeled RNAs were then hybridized onto the microarray. After washing and staining the slides, the arrays were scanned with an Affymetrix Scanner 3000 (Affymetrix). The scanned images were analyzed using Expression Console software (version 1.3.1; Affymetrix). 2.5. Real-time quantitative reverse-transcription polymerase chain reaction (qRT-PCR) The top 7 miRNAs with significant differential expression changes according to the microarray results were chosen for further validation with real-time qRT-PCR. Blood samples from 76 patients with GAD were used to validate the findings of the miRNA profiling. Total RNA was extracted from the purified plasma using a mirVana™ PARIS™ kit (P/N: AM1556; Applied Biosystems) for quantitative detection of miRNA. Complementary DNA was synthesized using a Reverse Transcription TaqMan® MicroRNA Reverse Transcription Kit and miRNA-specific stem–loop primers (P/N: 4,366,596; Applied Biosystems) according to the manufacturer's instructions. The RT reaction mixture consisted of 5 μL of total RNA (~ 10 ng), 0.15 μL of dNTPs with dTTP (100 mM), 1.00 μL of multiscribe RT enzyme (50 U/μL), 1.5 μL of 10 × RT buffer, 0.19 μL of RNase inhibitor (20 U/μL), 4.16 μL of nuclease-free water, and 3 μL of 5 × RT primer in a total volume of 15 μL. Reactions were performed under the following conditions: 16°C for 30 min, 42°C for 30 min, 85°C for 5 min, and held at 4°C. Real-time PCR was performed using an Applied Biosystems 7900HT Real-Time PCR System (Applied Biosystems) with 10 μL of PCR mixture that included 2 μL of cDNA, 5 μL of 2 × TaqMan® Universal PCR Master Mix II (Applied Biosystems), 0.5 μL of 20 × miRNA-specific PCR primer/probe mix (Applied Biosystems), and 2.5 μL of nuclease-free water. PCR was performed in 384-well plates at 95°C for 10 min, followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. Each sample was run in triplicate for analysis. The 5 × RT primers (miRNA -specific stem–loop primers) and 20 × miRNA-specific PCR primer/probe mix were supplied with the TaqMan® MicroRNA Assay (Applied Biosystems) based on the miRNA sequences obtained from the miRBase database (http://www.mirbase.org). Data were collected using SDS 2.3 software (Applied Biosystems). After normalization relative to RNU48, the expression levels of miRNAs were calculated using the 2 − ΔΔCt method [28,29]. The numbers of PCR cycles for each miRNA in qRT-PCR are shown in Table 1. 2.6. Statistical analysis Demographic variables were compared between patients and matched controls by Fisher's exact test for qualitative variables and t-tests for quantitative variables. Expression levels of miRNAs were compared between the patient and
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3.2. miRNA microarray expression profiling
Table 1 PCR cycles for each identified miRNAs in qRT-PCR. miRNA
PCR cycles
miR-4505 miR-1301 miR-432-5p miR-4484 miR-4674 miR-501-3p miR-663 RNU48
26.0 26.0 22.0 17.0 20.2 25.0 21.0 14.0
control groups using Students' t-tests. Pearson's correlation test was carried out to test the correlations of miRNA expression levels with HAMA psychic and somatic anxiety symptomatology scores, and multivariate regression analysis was performed to determine the responsibility of miRNAs levels for the diversity of symptomatology. All statistical analyses were carried out using DataAssist version 3.0 software, and SPSS version 21.0 software (SPSS, Chicago, IL). In all analyses, P b 0.05 (two-tailed) was taken to indicate statistical significance.
3. Results 3.1. Clinical characteristics of the patients As shown in Table 2, the mean ages (mean ± standard deviation [SD]) of patients in the case and control groups were 47.03 ± 13.20 and 46.06 ± 14.26 years, respectively. All of the patients and controls were of Han Chinese ethnicity, and there were no differences in age, sex, or residential locations between the patients with GAD and the healthy controls. The mean HAMA score was 24.38 ± 3.79.
Table 2 Demographic data of different groups.
Controls (n = 39)
GAD (n = 76)
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Comparisons of demographic variables between the GAD group and the control group
Using 6 blood samples (3 patients with GAD and 3 controls) for microarray profiling, 7 miRNAs were identified with significant differences in expression level between the patients with GAD and the controls (fold-change ≥ 2; P b 0.05). Of these, 5 miRNAs were upregulated and 2 were downregulated. The list of differentially expressed miRNAs identified by the microarray analysis is shown in Table 3. In unsupervised hierarchical clustering analysis, the normalized microarray expression data for the 7 miRNAs showing differential expression were used to generate a heat map. Hierarchical clustering was performed using the Euclidean metric and complete linkage rule. The samples were self-segregated into the patients with GAD and control clusters (Fig. 1). 3.3. Real-time qRT-PCR validation To validate the results of the microarray assay, the 7 miRNAs (miR-1301, miR-432-5p, miR-4484, miR-4674, miR-501-3p, miR-663, and miR-4505) with differential expression were examined in a larger sample (76 cases and 39 controls) using the qRT-PCR method. Using RNU48 as a normalization control, 5 miRNAs were upregulated in patients with GAD compared with normal controls (P b 0.05), showing the same tendency as the microarray results; 2 miRNAs (miR-1301, miR-432-5p) were also upregulated in patients with GAD, in contrast to the microarray results (Fig. 2). We selected the 5 miRNAs with significant differential expression (miR-4484, miR-4674, miR-501-3p, miR-663, and miR-4505) that were in accordance with the microarray results for further study. 3.4. Comparison of miRNA expression, symptomatology scores, and total score in patients with GAD Pearson's correlation test was carried out to test the correlations of miRNA expression levels with HAMA total scores, psychic, and somatic anxiety symptomatology scores (Figs. 3–5). The levels of miR-4505 and miR-663 expression were negatively correlated with the total HAMA scores in patients with GAD (r = 0.2228, r = 0.264, P b 0.05). We also found a significant negative correlation between all 5 miRNAs (miR-4505, miR-4484, miR-4674, miR-501-3p,
Statistics p Value Age Mean(SD) Range Media Gender Boys Girls Ethnicity Han ethnicity Educational levels Junior high and below Senior high and above
47.03 ± 13.20 46.06 ± 14.6 t = 1.56
0.349
9 30
19 57
0.005
0.856
–
76
–
–
–
40 36
–
–
Table 3 Differentially expressed microRNAs identified by microarray analysis in PBMCs from GAD patients versus controls. miRNA
Fold-change
Regulation
p Value
has-miR-1301 has-miR-432-5p has-miR-4484 has-miR-4674 has-miR-501-3p has-miR-663 has-miR-4505
2.2144198 5.777223 2.6435952 5.227357 2.5043268 3.0083036 5.30872
Down Down Up Up Up Up Up
0.044 0.029 0.028 0.033 0.020 0.030 0.014
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HAMA total scores and 15.3% of the anxiety symptomatology scores (Table 4).
4. Discussion
Fig. 1. Heatmap showing 7 miRNAs differential expression in PBMCs from GAD patients (n = 3) and controls (n = 3). Rows represent miRNAs species, and columns represent individual plasma sample. The relative miRNA expression is depicted according to the color scale. Red indicates up-regulation; green indicates downregulation. The numbers with JLZ denote GAD; numbers with NC denote normal controls.
and miR-663) and the psychic anxiety symptomatology scores (Fig. 4) (P b 0.01). 3.5. Stepwise regression analysis on miRNA expression for HAMA symptomatology Stepwise regression analysis was performed using the levels of miRNA expression (miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663) as independent variables, and the HAMA total scores, psychic, and somatic anxiety symptomatology scores as dependent variables. The results showed that miR-663 was selected into the regression equation of the HAMA total scores and the psychic anxiety symptomatology score, and could explain 5.3% of the
At present, the diagnosis of GAD is symptom-based in accordance with the DSM-IV criteria, which depend on the patient's subjective description of symptoms, psychiatrists' assessment of mental status with the HAMA scale, and clinical behavioral observations. However, there are no reliable circulating biomarkers for GAD symptom prediction, diagnosis, or outcome prediction. There is emerging evidence suggesting that numerous miRNAs are abundantly expressed in the brain [12,30] and that they play crucial roles in regulating various neurobiological processes, such as the establishment and maintenance of dendrites [31] and neurite outgrowth [32]. In previous studies, we showed that circulating miRNAs were associated with human schizophrenia and major depressive disorder [14,15]. It has been increasingly accepted that aberrant expression of certain miRNAs has a significant role in the underlying pathophysiology of GAD [33]. Investigation of gene elements, such miRNAs, in GAD is critical to understanding the genetic etiology of this disorder. However, there have been few studies focusing on the association between changes in miRNA expression and the psychic and somatic anxiety symptomatology in patients with GAD. To date, there have been few studies of miRNAs in GAD. Several researchers have attempted to identify specific miRNAs and their targets responsible for regulating synaptic function in GAD. Honda et al. examined alterations in
Fig. 2. Differentially expressed microRNAs identified by microarray analysis in PBMCs from GAD patients versus controls.
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Fig. 3. Correlation coefficients between the level of miRNAs and HAMA total scores.
miRNA profiles in peripheral blood from 25 male medical students 2 months and 2 days before the National Examination for Medical Practitioners. The levels of 7 miRNAs (miR-16, miR-20b, miR-26b, miR-29a, miR-126, miR-144, and miR-144*) were significantly elevated during the pre-examination period in association with significant downregulation of their target mRNAs (WNT4, CCM2, MAK, and FGFR1), 2 days before the examination. They concluded that a distinct group of miRNAs in peripheral
blood may participate in the integrated response to chronic academic stress in healthy young men [34]. Zhou et al. found fluctuating levels of various hippocampal miRNAs (let-7b, let-7c, miR-24a, miR-30c, miR-34a, miR-128a, miR-144, and miR-221) following chronic treatment with the mood stabilizers lithium and valproate [9]. In the present study, the levels of circulating miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663 were upregulated in the GAD group compared with the control
Fig. 4. Correlation coefficients between the level of miRNAs and psychic anxiety symptomatology scores.
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Fig. 5. Correlation coefficients between the level of miRNAs and somatic anxiety symptomatology scores.
group. All 5 of these miRNAs were negatively correlated with psychic anxiety symptomatology scores. Both miR-4505 and miR-663 were negatively correlated with the HAMA total score. The most important findings of this study were that miRNA-663 was selected into the regression equation of the HAMA total scores and psychic anxiety symptoms, and could explain 5.7% of the HAMA total scores and 15.3% of the psychic anxiety symptoms. miRNAs have been shown to play significant roles in early mammalian development. Both acute and chronic stress are connected to the development of anxiety disorders through complex mechanisms related to neural plasticity [16,35]. We found differences in the levels of miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663 between the GAD group and the control group that have not been reported previously to be involved in GAD. The reported functions of these miRNAs were mostly associated with human cancer [36–38]. However, recent studies have shown that miR-501-3p plays an important role in the processes of neurogenesis and
neuronal differentiation, suggesting that miR-501-3p may participate in regulating the development of the CNS [39]. miR-663, which is expressed in Homo sapiens and Pan troglodytes, belongs to the primate-specific miRNAs, which may be associated with vertebrate evolution, development, and neuronal differentiation, and may be involved in the etiology of numerous psychiatric disorders [40,41]. The relationship between stress-induced differences in senescence and miR-663 have been reported [42,43]. Maes et al. observed higher levels of miR-663 in both replicative and stress-induced senescence in vitro [43]. Furthermore, Hackl et al. detected higher levels of miR-663 expressed by fibroblasts and memory T cells derived from older donors compared with younger donors [44]. The precise mechanisms by which miR-663 could act in GAD and psychic anxiety symptoms remain to be explored. Recently, upregulation of miR-663 in tumor tissue was found with longer periods of ischemia, indicating that miR-663 affected the stress response through FOSB [45]. Here, we observed a
Table 4 Step-wise regression analysis on miRNA expression for symptomatology. Dependent variable HAMA total score Psychic symptoms
Model (Constant) hsa-miR-663 (Constant) hsa-miR-663
Unstandardized coefficients
Standardized coefficients
B
Std. Error
25.119 -0.237 15.037 -0.306
0.549 0.100 0.438 0.080
R2
t
p
45.788 -2.356 34.293 -3.815
b0.0001 0.021 b0.0001 0.0001
Beta -0.264 0.405
0.057 0.153
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negative correlation between the level of miR-663 and psychic anxiety symptom scores, which was likely a reflection of the variability and complexity of the GAD process. These observations support the suggestion that miR-663 may participate in the process of stress, which could contribute to the etiology of GAD psychic symptoms. We further performed bioinformatics analyses with regard to the 5 significantly upregulated miRNAs (hasmiR-4484, has-miR-4505, has-miR-4674, has-miR-501-3p, and has-miR-663) in patients with GAD, which demonstrated that these miRNAs participated in various biological processes, including nervous system development, nerve growth factor receptor signaling pathways, neuron migration, dendrite development, regulation of neuron projection development, midbrain development, regulation of excitatory postsynaptic membrane potential, gliogenesis, dendrite morphogenesis, etc. [46]. Genetics represents an important potential source of differences between patients with GAD and controls. Hanin et al. showed that miR-608 targets acetylcholinesterase (AChE) and demonstrated weakened miR-608 interaction with the rs17228616 AChE allele, which has a single-nucleotide polymorphism SNP in the 3′-untranslated region (3′UTR). They found that minor rs17228616 allele heterozygous and homozygous subjects showed elevated risks of inherited anxiety and hypertension [47]. The SNPs in the vicinity of the identified miRNAs were sought in the Web-available genome-wide association study (GWAS) datasets, and miRNA-related SNPs are listed in Supplementary table 2. Detailed bioinformatics analyses of these miRNAs are currently underway, and the molecular mechanisms by which these miRNAs participate in the pathogenesis and development of GAD must be explored. In summary, our data demonstrated significant changes in the circulating levels of miR-4505, miR-4484, miR-4674, miR-501-3p, and miR-663 in patients with GAD, suggesting that these miRNAs are potentially involved in the pathogenesis of GAD. The upregulation of miR-663 expression predicts psychic anxiety symptoms in patients with GAD and can thus serve as a therapeutic target of antianxiety drugs. Further, miR-663 likely plays significant roles in the symptomatology of patients with GAD. The specific mechanism underlying this interaction warrants further investigation.
5. Limitations Several general limitations of our study should be acknowledged. First, the sample size was relatively small for the analysis. The small number of subjects in the control group relative to the GAD group may have decreased the statistical power for comparison of miRNA expression levels between the GAD and control groups. Therefore, further validation in larger cohorts is needed to better evaluate the suitability and specificity of the 5 miRNA signatures as biomarkers. Second, we found that the upregulation of
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