Fibroblasts from patients with major depressive disorder show distinct transcriptional response to metabolic stressors

Abstract

Major depressive disorder (MDD) is increasingly viewed as interplay of environmental stressors and genetic predisposition, and recent data suggest that the disease affects not only the brain, but the entire body. As a result, we aimed at determining whether patients with major depression have aberrant molecular responses to stress in peripheral tissues. We examined the effects of two metabolic stressors, galactose (GAL) or reduced lipids (RL), on the transcriptome and miRNome of human fibroblasts from 16 pairs of patients with MDD and matched healthy controls (CNTR). Our results demonstrate that both MDD and CNTR fibroblasts had a robust molecular response to GAL and RL challenges. Most importantly, a significant part (messenger RNAs (mRNAs): 26-33%; microRNAs (miRNAs): 81-90%) of the molecular response was only observed in MDD, but not in CNTR fibroblasts. The applied metabolic challenges uncovered mRNA and miRNA signatures, identifying responses to each stressor characteristic for the MDD fibroblasts. The distinct responses of MDD fibroblasts to GAL and RL revealed an aberrant engagement of molecular pathways, such as apoptosis, regulation of cell cycle, cell migration, metabolic control and energy production. In conclusion, the metabolic challenges evoked by GAL or RL in dermal fibroblasts exposed adaptive dysfunctions on mRNA and miRNA levels that are characteristic for MDD. This finding underscores the need to challenge biological systems to bring out disease-specific deficits, which otherwise might remain hidden under resting conditions.

OPEN

Citation: Transl Psychiatry (2015) 5, e523; doi:10.1038/tp.2015.14

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ORIGINAL ARTICLE

Fibroblasts from patients with major depressive disorder show distinct transcriptional response to metabolic stressors

KA Garbett1, A Vereczkei1,2, S Klmn1,3, L Wang4, Korade1,5, RC Shelton6 and K Mirnics1,3,5

Major depressive disorder (MDD) is increasingly viewed as interplay of environmental stressors and genetic predisposition, and recent data suggest that the disease affects not only the brain, but the entire body. As a result, we aimed at determining whether patients with major depression have aberrant molecular responses to stress in peripheral tissues. We examined the effects of two metabolic stressors, galactose (GAL) or reduced lipids (RL), on the transcriptome and miRNome of human broblasts from 16 pairs of patients with MDD and matched healthy controls (CNTR). Our results demonstrate that both MDD and CNTR broblasts had a robust molecular response to GAL and RL challenges. Most importantly, a signicant part (messenger RNAs (mRNAs): 2633%; microRNAs (miRNAs): 8190%) of the molecular response was only observed in MDD, but not in CNTR broblasts. The applied metabolic challenges uncovered mRNA and miRNA signatures, identifying responses to each stressor characteristic for the MDD broblasts. The distinct responses of MDD broblasts to GAL and RL revealed an aberrant engagement of molecular pathways, such as apoptosis, regulation of cell cycle, cell migration, metabolic control and energy production. In conclusion, the metabolic challenges evoked by GAL or RL in dermal broblasts exposed adaptive dysfunctions on mRNA and miRNA levels that are characteristic for MDD. This nding underscores the need to challenge biological systems to bring out disease-specic decits,

Translational Psychiatry (2015) 5, e523; doi:10.1038/tp.2015.14; published online 10 March 2015

INTRODUCTION

Major depressive disorder (MDD) is a mental disorder characterized by persistent depressed mood, anhedonia, sleep and appetite disturbances, and feelings of worthlessness, guilt and hopelessness. It is increasingly viewed as an illness of the body as well as of the mind.1 Both genetic and environmental factors have been associated with the etiology of the disease,2 but their interplay remains unexplained to date. Stressful life events are associated with the onset and severity of major depression;3 therefore, we speculated that aberrant adaptive responses to stressors would be also detectable at the cellular level.

Coordination of cellular responses to stress is largely accomplished by mitochondria.4 Regardless of the type of stress a cell is experiencing (for example, exposure to harmful chemicals, changes of nutrient or oxygen supplies, dangerous levels of reactive oxygen species or even pathogen invasion), mitochondria utilize a wide array of mechanisms aimed at restoring cellular homeostasis.5 Therefore, the health of these cellular organelles is critical not only for the fate of the individual cells, but for the well-being of the entire organism. Not surprisingly, abnormalities in mitochondrial functions have been implicated in neurological6 and psychiatric disorders,79 and specically in MDD.10 In addition, mitochondria are involved in multiple metabolic pathways and are the most prominent generators of energy in the cell. Energy is produced in the cytoplasm through glycolysis, or in the mitochondria through oxidative phosphorylation, also known as mitochondrial respiration. The reliance on energy produced by mitochondrial respiration, rather than glycolysis, can be

which otherwise might remain hidden under resting conditions.

experimentally shifted by changing the sugar source in the cell culture medium from glucose to galactose (GAL).11 The shift to oxidative phosphorylation can reveal mitochondrial decits intersecting control of carbohydrate metabolism and energy homeostasis. Energy production is also tightly interconnected with lipid metabolism through the key metabolite acetyl-CoA. Acetyl-CoA may remain in the mitochondria for energy production or may be exported for de novo fatty acid synthesis into the cytoplasm, depending mainly on the availability of fatty acids. This adaptive shift can be experimentally directed by limiting the fatty acid supply in the cell culture medium. Therefore, cellular adaptation to stress can be tested by simple manipulations of the carbohydrate and fatty acids source in the culture medium.

Molecular adaptation to stress in the context of mental disorders is difcult to address in the human brain. Alternatively, we used in vitro propagated peripheral cells to test the effects of metabolic stress. Dermal broblasts are an appealing cell-based model for studying peripheral events associated with brain disorders, based on the ease of establishing them from skin biopsies, and the ability to maintain in culture without additional reprograming.12 In addition, the confounding variability in human samples on the basis of patients hormones, life style or medication use, are virtually eliminated after several cell divisions. To date, skin broblast cultures have been used successfully to elucidate molecular mechanisms associated with schizophrenia13,14 and developmental disorders,15,16 and for discerning abnormalities in signal transduction pathways in MDD.12,1719 In addition, previous reports for dysregulations in

1Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; 2Department of Medical Chemistry, Molecular Biology and Pathobiochemistry, Semmelweis University, Budapest, Hungary; 3Department of Psychiatry, University of Szeged, Szeged, Hungary; 4Department of Biostatistics, Vanderbilt University, Nashville, TN, USA; 5Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, TN, USA and 6Department of Psychiatry, University of Alabama, Birmingham, AL, USA. Correspondence: Dr KA Garbett, Department of Psychiatry, Vanderbilt University, 8128 MRB III, 465 21st Avenue South, Nashville, TN 37232, USA.

E-mail: mailto:[email protected]

Web End [email protected] Received 2 October 2014; revised 12 December 2014; accepted 19 December 2014

MDD broblasts metabolic stress response KA Garbett et al

2 lipid metabolism20 and mitochondrial respiration,21 suggest abnormalities in mitochondrial function in the periphery of MDD patients. Therefore, we aimed at elucidating whether MDD broblasts would in addition exhibit molecular decits in response to metabolic stressors such as GAL and reduced lipids (RL) in the culture medium. In this manuscript, we present the experimental data gathered from metabolically challenged human dermal broblasts and discuss their relevance to MDD.

MATERIALS AND METHODS Human broblasts

This study was approved by the Vanderbilt University Institutional Review Board. Participants were diagnosed with a current major depressive episode according to the Structured Clinical Interview for DSM-IV-TR22 with

an exclusion criteria of other primary axis I DSM-IV diagnosis. Procedures for recruitment and diagnosis have been described previously.12,18 A

written informed consent was obtained from all the participants before any procedures were conducted. Sixteen healthy controls (CNTR) were matched by age, race and gender to MDD patients (Supplementary Material 1). The MDD and CNTR subject groups had similar average age (MDD = 34.9, CNTR = 35.2), representation of gender (12 female and four male) and race (12 white and four African American). Fibroblast cultures were established from skin biopsies according to a protocol previously described.12,18

Briey, broblast cultures underwent 510 passages with DMEM (Dulbeccos Modied Eagles medium; Mediatech, Manassas, VA, USA) containing 250 mM glucose and 1 mM sodium pyruvate, supplemented with 2 mM L-glutamine (Mediatech), 10% fetal bovine serum (Thermo Scientic HyClone, Logan, UT, USA) and antibiotic/antimycotic solution (Invitrogen, Carlsbad, CA, USA). Cultures were maintained at 37 C and 5% CO2. A cell line from each patient was divided into three plates (plating density 1.2 106 cells per plate) and after overnight adherence, each plate received one of the following formulations: (1) standard (STD) medium: DMEM containing 25 mM glucose; (2) galactose-containing (GAL) medium: DMEM with no glucose, supplemented with 10 mM GAL (Sigma-Aldrich, St. Louis, MO, USA); (3) RL medium: DMEM containing 25 mM glucose, supplemented with lipid-reduced fetal bovine serum (Thermo Scientic HyClone). All the cultures were grown for 7 days, refreshing the media every 2 days. The cells were collected after washing with ice-cold phosphate-buffered saline twice, and then trypsinized, pelleted (700 g for 8 min at 18 C) and stored at 80 C until RNA isolation. In all the tested cell lines, neither GAL nor RL exhibited a detectable effect on cell growth and mortality.

RNA isolation and analysesTotal RNA and small RNA fractions were isolated from frozen broblasts using mirVana microRNA (miRNA) isolation Kit (Ambion, Austin, TX, USA) according to manufacturers instruction. Both total RNA and small RNA were eluted with 100 l Elution Solution. Agilent 2100 Bioanalyzer was used to determine the quality and size of the RNA preps. Total RNA integrity number for all messenger RNA (mRNA) samples ranged from 9.4 to 10, and was similar between the MDD and CNTR groups and various conditions. The samples were stored at 80 C until further use.

The mRNA levels in each broblast culture were examined with the GeneChip HT HG-U133+ PM Array Plate (Affymetrix, Santa Clara, CA, USA). The complementary DNA synthesis from total RNA, labeling and hybridization were performed according to manufacturers protocol. The segmented images from each GeneChip were normalized and log2 transformed using GC-robust multi-array analysis.23 The average logarithmic ratio (ALR = MeanMDD MeanCNTR) was calculated for each gene probe, as an indicator for magnitude of change and Students paired and group two-tailed P-values as indicators for signicance of change. Signicance was established according to the dual criteria of |ALR|40.3785 (30%

change) and both pairwise and groupwise P 0.01. Quantitaive PCR validation of the microarray data was performed with RT2 custom Proler

PCR Arrays (Qiagen, Valencia, CA, USA), designed to test the mRNA expression level of 10 genes involved in the regulation of lipid metabolism: stearoyl-CoA desaturase (delta-9-desaturase), fatty acid binding protein 3, 7-dehydrocholesterol reductase, insulin induced gene 1, quinolinate phosphoribosyltransferase, 3-hydroxy-3-methylglutaryl-CoA reductase, 3-hydroxy-3-methylglutaryl-CoA synthase 1, low-density lipoprotein receptor, fatty acid desaturase 1, fatty acid desaturase 2. The differentially

expressed genes were subjected to a two-way hierarchical clustering analysis using GenePattern software.24 In addition, for each gene probe, we applied a linear statistical model with gene expression values as the outcome variable and group, stressor and group stressor as xed effects (groups: CNTR, MDD; stressors: GAL, RL). Data were analyzed with procedure MIXED in SAS software (version 9.3, SAS Institute, Cary, NC, USA). Gene set enrichment analysis (GSEA) based on pre-dened gene classes were carried out with the GenePattern software.25 BioCarta dened set of genes were considered signicantly overrepresented at P 0.05.

The miRNA levels were interrogated with miRNome miScript miRNA PCR Arrays (Qiagen). The complementary DNA was prepared from small RNA preps with miScript HiSpec Buffer according to miScript II RT Kit (Qiagen) instructions. The complementary DNA from each sample was quantied and proportionately combined into four pools of samples according to age and gender (Supplementary Material 1). Creating multiple sample pools from closely matched individuals allowed us a reduced work load and cost, while still retaining the ability to establish statistical signicance in the downstream analyses. However, to avoid any pooling biases and outlier effects, the outcome of these data had to be validated in the individual samples. As a result, signicantly changed miRNA levels in each individual broblast sample were examined with custom miScript miRNA PCR Arrays. (Qiagen), containing assays for the following miRNAs: miR-146b-5p, miR-550a, miR-214, miR-132*, miR-376c, miR-19a, miR-181a*, miR-486-5p, miR-424*, miR-542-3p, miR-22, miR-376b, miR-29b, miR-564. The selection of the 14 miRNA assays was based on a statistically signicant difference in response to GAL or RL in the MDD or the CNTR group. The Ct values for each miRNA from both miRNome and custom qPCR arrays were normalized to the average Ct from a set of housekeeping genes and thus Ct values were generated. At Ct 435, a miRNA level was considered non-detectable. In cases where the levels of a miRNA were non-detectable in two or more samples within a group, the miRNA was not used for further comparisons. The miRNA difference of expression between groups was measured by CtRL = MeanCtRL MeanCtSTD and CtGAL = MeanCt

GAL MeanCtSTD. A miRNA was considered differentially expressed when | Ct|40.3785 and pairwise P 0.05. Group stressor interaction was determined by the dual criteria of |Ct|40.3785 (30% difference) and groupwise P 0.05. CtGAL = CtMDDGAL CtCNTRGAL; CtRL = CtMDDRL CtCNTRRL.

RESULTSMDD broblast response to metabolic stress: mRNA changes Metabolic stress response in MDD and CNTR broblasts from 32 subjects (16 MDD and 16 CNTR) was achieved by exposure to culture media containing GAL or RL (Supplementary Material 2). Analysis of mRNA species by oligonucleotide microarrays revealed that GAL substitution of glucose in the growth medium resulted in robust changes in the transcriptome of both MDD and CNTR broblasts. Using dual criteria for establishing signicant expression differences (|ALRGAL STD| 4 0.3785 (30% change)

and both group- and pairwise P 0.01), we identied 1196 transcripts changed in GAL-treated MDD broblasts (Supplementary Material 3A). Of those, 975 were upregulated as a result of GAL treatment. According to the same criteria, 1111 probes were changed in CNTR broblasts, 733 of which were upregulated. In comparison with the CNTR broblasts, MDD broblasts revealed a distinct GAL-induced mRNA pattern; of the total number of mRNAs, 310 (26%) were only exhibited in MDD (Supplementary Material 4A).

RL treatment also resulted in pronounced mRNA changes in both MDD and CNTR cells. Differential expression in RL conditions (compared with STD media) was noted for 312 transcripts in the MDD: 262 upregulated and 50 downregulated mRNAs. Similarly, in CNTR broblast, 360 mRNA species (261 upregulated, 99 down-regulated) were differentially expressed in RL compared with STD conditions (Supplementary Material 3B). Importantly, the MDD broblasts responded to RL condition differently than CNTR; 103(33.4%) of all mRNA changes induced by RL were only exhibited in MDD (Supplementary Material 4B).

It was remarkable that both GAL and RL treatments resulted in distinct mRNA changes in MDD broblasts that were not present

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Figure 1. Disease stressor interaction mRNA signatures. (a) MDD GAL and (b) MDD RL. The ALR (MeanRL MeanSTD) of the probes with signicant disease challenge interaction were subjected to unsupervised hierarchical clustering. The colored squares represent the increase (red) or decrease (blue) of each ALR from the mean. Color intensity is proportional to magnitude of change. Clear separation of MDD and CNTR groups was observed. Furthermore, two genes (INTS4 and N4BP2L1denoted by arrows) are commonly present in both signatures. CNTR, control; GAL, galactose; MDD, major depressive disorder; mRNA, messenger RNA; RL, reduced lipid; STD, standard.

in CNTR, therefore, we further sought to identify the interaction effect between disease state and metabolic challenge (group stressor) by applying a linear statistical model. We used a dual signicance cutoff criterion of |ALR|40.3785 (30% change) and

P 0.01. We found that the characteristic MDD signature in response to GAL (MDD GAL) was dened by 28 (Figure 1a), and in response to RL (MDD RL) was dened by 20 mRNA species (Figure 1b). Two of the genes (integrator complex subunit 4; INTS4 and NEDD4 binding protein 2-like 1; N4BP2L1) overlapped in the MDD GAL and MDD RL response-dening pattern.

Custom qPCR arrays were used to validate the microarray-detected mRNA changes in response to GAL and RL. The arrays were designed to test the mRNA expression level of 10 genes involved in lipid metabolism with signicantly changed expression

in MDD and in CNTR samples in GAL vs STD and in RL vs STD conditions. The statistical signicance of the microarray-detected expression changes for all 10 genes was conrmed by qPCR (Figure 2). In addition, the microarrays ALRs had a high correlation with the qPCRs Ct in both GAL vs STD and RL vs STD comparisons.

To better understand what molecular pathways are differently engaged in MDD compared with CNTR in response to metabolic stress, we performed GSEA with predetermined gene sets by BioCarta. Signicantly enriched gene sets, representing molecular pathways, were identied for both MDD and CNTR in GAL and RL environment (Table 1, GSEA). GAL treatment induced enrichment of 21 pathways in MDD and 17 in CNTR. Nine of the 21 gene sets (43%) were only enriched in MDD and are involved in cell cycle

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Figure 2. qPCR validation of the differential mRNA expression detected with microarrays. The differential expression of 10 mRNAs, detected with microarrays, was validated with custom qPCR arrays (groups: MDD, CNTR; culture conditions: STD, GAL, RL). ALR (ALRGAL = MeanGAL

MeanSTD, blue, ALRRL = MeanRL MeanSTD, pink) was used as an estimate for the microarray expression changes and was plotted on the x axis. Ct (CtGAL = CtGAL CtSTD, blue; CtRL = CtRL CtSTD, pink) was used for a qPCR expression changes estimate and was plotted as Ct on the y axis. Note that the estimates from both analyses in each comparison were highly correlated. CNTR, control; GAL, galactose;

MDD, major depressive disorder; mRNA, messenger RNA; qPCR, quantitative PCR; RL, reduced lipid; STD, standard.

regulation (PTC1, MPR, ACAP95, ARF), apoptosis (HSP27, SET, BAD), anti-inammation (IL10) and cell survival (IL7). RL resulted in enrichment of 19 pathways in MDD and 15 in CNTR. Ten of the 19 gene sets (53%) were only enriched in MDD and are involved in cell repair (TFF), survival (TRKA), migration (ECM) and proliferation (CDMAC, SPRY), and also in regulation of metabolism (GH) and energy production (FEEDER, GLYCOLYSIS). Overall, GSEA revealed that the specic changes in MDD evoked by both metabolic stressors are represented by approximately half of all detected molecular pathways, indicating that MDD broblasts utilize different strategies for adaptation to the metabolic stressors. Moreover, challenging the MDD broblasts with GAL and RL exposed characteristic molecular signatures undetectable at STD conditions.

MDD broblast response to metabolic stress: miRNA changes The miRNAs are important regulators of mRNA function and they are heavily involved in control of metabolism and energy homeostasis.26 Therefore, we sought to identify the miRNA response to metabolic challenges in the same MDD broblasts in which differential mRNA expression patterns had been established.

The miRNA samples, isolated individually from the 16 MDD and16 CNTR broblast cultures, were pooled into four sets according to the patients age and gender (Supplementary Material 1). Human miRNome miScript miRNA PCR Arrays (Qiagen) were used to prole the expression of the 1008 most abundantly expressed miRNA species in the human miRNA genome (miRNome).

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Table 1. BioCarta GSEA enrichment of mRNA expression in response to GAL and RL challenges

Pathway Size NES P-value

Enriched in CNTR GALRACCYCD 26 1.89 0.0076 CELLCYCLE 23 1.81 0.0000 TEL [phone] SRCRPTP 11 1.72 0.0000 P53 16 1.66 0.0078 CERAMIDE 22 1.65 0.0115 CFTR 12 1.62 0.0000 CHREBP2 42 1.61 0.0275 G2 24 1.61 0.0199 ATRBRCA 21 1.58 0.0159 CARM_ER 34 1.58 0.0373 STATHMIN 19 1.56 0.0233 ATM 20 1.55 0.0492 CHEMICAL 22 1.53 0.0497 RB 13 1.53 0.0346 AKAPCENTROSOME 15 1.52 0.0471 PLCE 12 1.51 0.0299

Enriched in CNTR RLPPARA 56 1.83 0.0000 RACCYCD 26 1.71 0.0229 CHREBP2 42 1.65 0.0136 CD40 15 1.59 0.0301 ARF 17 1.57 0.0359 VIP 26 1.57 0.0169 P38MAPK 39 1.53 0.0076 HSP27 15 1.50 0.0389 BAD 26 1.50 0.0217 GCR 19 1.47 0.0360 LYM 11 1.43 0.0368 PLCE 12 1.43 0.0443 IL22BP 16 1.53 0.0300 DNAFRAGMENT 10 1.54 0.0237 AHSP 11 1.56 0.0412

Enriched in MDD GALTEL 18 1.98 0.0000 SRCRPTP 11 1.73 0.0020 PTC1 11 1.73 0.0000 G2 24 1.66 0.0021 CARM_ER 34 1.66 0.0056 HSP27 15 1.65 0.0116 RB 13 1.62 0.0062 CERAMIDE 22 1.60 0.0212 P53 16 1.58 0.0220 SET 11 1.58 0.0328 CHEMICAL 22 1.58 0.0243 ATRBRCA 21 1.57 0.0080 MPR 34 1.56 0.0413 CELLCYCLE 23 1.56 0.0305 AKAP95 12 1.56 0.0469 CHREBP2 42 1.56 0.0222 IL10 17 1.53 0.0320 ARF 17 1.50 0.0382 PLCE 12 1.47 0.0301 IL7 17 1.46 0.0258 BAD 26 1.43 0.0138

Enriched in MDD RLRACCYCD 26 1.90 0.0040 TFF 21 1.88 0.0064 CD40 15 1.78 0.0102 TRKA 12 1.74 0.0084 ECM 24 1.67 0.0234 PPARA 56 1.63 0.0066 HSP27 15 1.62 0.0176 GH 28 1.60 0.0204 GLEEVEC 23 1.58 0.0361

Table. 1. (Continued )

Pathway Size NES P-value

ARF 17 1.54 0.0463 EXTRINSIC 13 1.53 0.0140 CHREBP2 42 1.53 0.0246 CDMAC 16 1.52 0.0355 BAD 26 1.48 0.0118 SPRY 18 1.45 0.0417 FEEDER 9 1.53 0.0236 DNAFRAGMENT 10 1.54 0.0488 AHSP 11 1.56 0.0354 GLYCOLYSIS 10 1.63 0.0040

Abbreviations: CNTR, control; GAL, galactose; GSEA, gene set enrichment analysis; MDD, major depressive disorder; mRNA, messenger RNA; RL, reduced lipid. Molecular pathway enrichment of mRNA in MDD and CNTR. Pathways enriched only in one group (MDD or CNTR) are in bold.

Approximately 50% of the assayed miRNAs were detected in human cultured dermal broblasts, regardless of disease status or culture condition. Signicant expression differences in metabolic stress vs STD conditions were dened when change was larger than 30% (|Ct|40.3785) and paired t-test P 0.05. In response to GAL challenge, MDD broblasts revealed expression changes in 63 miRNAs (Supplementary Material 5A). The number of miRNAs changed by GAL challenge in CNTR samples was substantially lower, 38 miRNAs. In addition, 81% of the miRNAs changed in GAL were specic for MDD broblasts.

RL elicited much stronger miRNA response in MDD (147 miRNAs), compared with CNTR (38 miRNA) (Supplementary Material 5B), leading us to believe that MDD broblasts are experiencing the RL environment as much more stressful than CNTRs. Furthermore, 90% of the miRNA RL-response pattern was observed only in MDD, but not in CNTR.

Validation of miRNome analyses on pooled samples was performed with custom qPCR array of 14 miRNAs (SABiosciences, Qiagen) on individual samples. The Ct (CtGAL = CtGAL Ct

STD, CtRL = CtRL CtSTD) from the pooled samples for each

miRNA was correlated with the corresponding Ct from the individual samples (Figure 3). Both GAL- and RL-induced miRNA response demonstrated high correlation between pooled and individual samples with coefcients of rGAL = 0.920 and rRL = 0.785.

In addition, 85% of the miRNA changes in the individual samples were signicantly different in the predicted direction (P 0.05), providing a strong validation for the miRNome data.

In addition, in an attempt to identify the miRNA changes that characterize the specic response of MDD to each metabolic challenge, we used a group challenge linear statistical model and the dual signicance criterion of |Ct|40.3785 and

P 0.05. Thus, we derived two miRNA signatures: (1) representing MDD GAL interaction (16 miRNAs) and (2) representing MDD

RL interaction (36 miRNAs, Figure 4). It is noteworthy that miR-7, miR-382, miR-296-5p and miR-3176 were common for both signatures.

Literature search in PubMed for the roles of the MDD GAL and MDD RL signature miRNAs revealed an interesting trend toward extensive miRNA involvement in the regulation of metabolism, cell proliferation, survival and migration (Table 2). In relation to control of metabolism, we found miRNAs regulating insulin levels and secretion, obesity and starvation in both MDD GAL (38%) and MDD RL (37%) panels. In addition, eight miRNAs from the MDD RL panel: miR-3613-3p, miR-33a, miR-192, miR-26a, miR--34a, miR-370, miR-15b and miR-296-5p, have been described in the literature as regulators of lipid metabolism. With regard to cell proliferation and apoptosis, 56% of the MDD GAL and 61% of the MDD RL miRNAs are known controllers of various signaling

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Figure 3. Differential miRNA expression in pooled samples is validated in individual samples. The expression level of 14 miRNAs, detected in miRNome analyses of pooled samples, was validated with independent qPCR arrays of individual samples (groups: MDD, CNTR; culture conditions: STD, GAL, RL). The expression changes, estimated with Ct (CtGAL = CtGAL CtSTD, blue; CtRL = CtRL CtSTD, pink), from the pooled samples are plotted on the x axis, and from the individual samples on the y axis. Note that the values from each comparison were highly correlated. CNTR, control; GAL, galactose; MDD, major depressive disorder; miRNA, microRNA; qPCR, quantitative PCR; RL, reduced lipid; STD, standard.

cascades, out of which 13% (GAL) and 33% (RL) affect or are affected by the tumor suppressor protein p53. As p53 is not only a modulator of apoptosis, but is also involved in regulation of metabolism,27 some overlap between these categories is expected. Furthermore, 25% (MDD GAL) and 39% (MDD RL) of the signature miRNAs are known to regulate cell motility. Interestingly, three of them: miR-34a, miR-34b and miR-199a-3p, are recognized as regulators of the hepatocyte growth factor receptor, c-Met,28,29 a key controller of cell migration.

DISCUSSIONOur results demonstrate that the metabolic challenges evoked by substitution of glucose with GAL or reducing the abundance of lipids in the growth media of broblast cultures result in robust changes of mRNA and miRNA expression. MDD broblasts responded to the metabolic stress with alternate expression of 1196 (GAL) and 312 (RL) transcripts. A substantial fraction of these mRNA changes, 26% (GAL) and 33% (RL) were only observed in MDD, but not in CNTR. The specic response of MDD broblasts to each challenge was represented by 20 (MDD GAL) and 28 (MDD RL) mRNAs with signicant group by challenge interaction. The characteristic response of MDD broblasts to the metabolic stressors was even more pronounced on the miRNA level; 81% (GAL) and 90% (RL) of the total miRNA changes were only observed in MDD, but not in CNTR. The miRNA signature response of MDD broblasts was dened by 16 (MDD GAL) and 36 (MDD RL) miRNAs. The stress-induced changes, observed on both mRNA and miRNA level, revealed MDD-associated impairments in molecular pathways involved in the control of metabolism and energy production, cell survival, proliferation and migration. These impairments are likely to be present in all the somatic cells, and therefore are informative of the disease process. In fact, the results are consistent with our previous ndings in human postmortem brain tissue, as both studies implicated disturbances in apoptotic molecular pathways.30

Impairments in any of the detected molecular pathways could

be critical for the development and plasticity of the brain and can result in the disease state of MDD.31 In a previous study, MDD broblasts cultured in STD condition revealed decits in cell proliferation and cell motility.32 In this study, we demonstrated that molecular pathways involved in the same processes were also impaired in response to metabolic challenges with GAL and RL, and revealed previously unknown disruption of pathways regulating metabolism and energy production. Presenting metabolic challenges was instrumental for dening distinct MDD mRNA and miRNA response signatures that might also contribute to patients aberrant responses to life stressors.

GAL and RL treatments elicited common responses in MDD broblasts. The commonality was demonstrated on both mRNA and miRNA level. On mRNA level, the overlap between MDD GAL and MDD RL signatures was dened by the integrator complex subunit 4 (INTS4), and the NEDD4 binding protein 2-like 1 (N4BP2L1). The INTS4 associates with RNA polymerase II, and therefore potentially has a general effect on regulation of gene transcription and RNA processing.33 The N4BP2L1 is a paralog of N4BP2 and is likely involved in cell survival.34 Evidence for MDD impairment in the regulation of cell survival and proliferation streamed from the molecular pathway analyses as well. The HSP27, BAD and ARF molecular pathways were the commonly enriched pathways in MDD during GAL and RL challenges; all of which affect cell survival and proliferation. Furthermore, 38% (GAL) and 17% (RL) of the MDD-enriched gene sets (PTC1, MPR, ACAP95, ARF, HSP27, SET, BAD, IL7, TRKA, CDMAC, SPRY), contribute to the regulation of cell survival and proliferation. On the miRNA level, three of the commonly changed miRNAs are regulators of cell proliferation and apoptosis.3537 In addition, a striking 5661% of the miRNAs from the MDD GAL and MDD RL signatures have roles in cell cycle and survival regulation. Overall, these data provide an overwhelming support for the aberrant engagement of mechanisms regulating cell proliferation and survival by MDD broblasts when exposed to two distinct metabolic challenges. Commonality between GAL-and RL-induced responses in MDD was also detected in their respective miRNA signatures, where at least 38% (GAL) and 37% (RL) of the miRNAs were regulators of metabolism or energy homeostasis, indicating deciencies in those signaling cascades in MDD as well. In summary, the challenges presented by GAL and RL in MDD broblasts affected cellular processes, such as control of cell proliferation and survival, regulation of metabolism and energy production. The molecular machinery for regulation of these processes is located mainly in the mitochondria. Therefore, our data strongly support the disruption of mitochondrial functions in patients with MDD, as previously suggested.10

The GAL and RL treatment also evoked different responses in MDD broblasts. The number of mRNAs with changed expression in GAL was four times the number of mRNAs changed in RL. In contrast, the mRNA signatures characterizing the specic response of MDD to each stress, have similar number of mRNAs (MDD GAL = 28, MDD RL = 20). Therefore, the proportion of the specic mRNAs from the total mRNA changes (GAL = 1196, RL = 360) is in favor of RL (5.6 vs 2.3%). Consequently, we concluded that RL vs GAL environment more strongly illuminates the molecular decits of MDD. Furthermore, additional data, obtained from RL treatment, reveal abnormalities in MDD, which were not apparent in GAL. These are the eight miRNAs in the MDD RL miRNA signature known to control lipid metabolism, pointing toward the possibility of fatty acid metabolism dysregulation in patients with MDD, a phenomenon studied in many different ways during the last couple of decades.3842 Another interesting fact revealed only in RL environment is the presence of six hypoxamirs in the MDD RL miRNA signature. Hypoxamirs have been identied as miRNAs contributing to mitochondrial respiration arrest in a low oxygen environment.43 In our study, CNTR broblasts upregulated six hypoxamirs (let-7b*, miR-192, miR-26a, miR-98, miR-23a and

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Figure 4. Disease stressor interaction miRNA signatures. (a) MDD GAL and (b) MDD RL. The Cts (CtGAL = CtGAL CtSTD; CtRL = CtRL CtSTD) of the miRNAs with signicant disease challenge interaction were subjected to unsupervised hierarchical clustering. The colored squares represent the increase (red) or decrease (blue) of each Ct from the mean. Increased Ct represents reduced level of miRNA in metabolic stress compared with STD conditions. Clear separation of MDD and CNTR groups was observed. Four miRNAs (that is, miR-7, miR-382, miR-296-5p and miR-3176), denoted by arrows, are commonly present in both signatures. CNTR, control; GAL, galactose; MDD, major depressive disorder; miRNA, microRNA; RL, reduced lipid; STD, standard.

miR-7)44 in response to RL, whereas MDD broblasts down-regulated them. This particular difference in the MDD response compared with CNTR further supports the notion of mitochondrial dysfunction in MDD. The RL challenge was also very informative in uncovering abnormalities in the process of cell migration; 39% of the miRNAs in the MDD RL miRNA signature were regulators of metastasis. Also, MDD responded to RL with enrichment of ECM (extracellular matrix) pathway and TFF (Trefoil factors initiate mucosal healing) pathway; both important players in the processes of cell migration. The decit of MDD in cell migration was not as apparent during adaptation to GAL, but was observed in a previous study in STD conditions.32

An important question is whether the changes we detect in peripheral tissues are relevant to a disease process that takes place primarily in the brain. Genetic factors associated with MDD are likely to be present throughout the entire body and not just be specic to the brain. The adaptive decits detected in broblast cell lines can be linked back to the function of neurons and the brain, with multiple examples found in the mRNA and miRNA challenge-response signatures and in the altered molecular pathways. On mRNA level, such examples are presented by genes important for neurite outgrowth, neurodevelopment and synaptic

plasticity: Actin-related protein 2/3 complex, subunit 5 (ARPC5),45

ArfGAP with coiled-coil, ankyrin repeat and PH domains 2 (ACAP2)46 and Beta-1,3-glucuronyltransferase 2 (glucuronosyltransferase S, B3GAT2).47 Multiple important roles in the nervous system are associated with miRNA challenge-response signatures as well. Generally, 31% (GAL) and 47% (RL) of the miRNAs from the miRNA signatures are either regulators of molecular events in the brain or biological markers associated with psychiatric disorders in the periphery. In particular, we identied miRNAs with roles in neurite outgrowth and synapse formation: miR-7,48 miR-26a,49 miR-34a,50 miR-134 (ref. 51) and miR-132;52,53 cell cycle progression, apoptosis and specication of neurons: miR-25,54 miR-34a,55 miR-497 (ref. 56) and miR-376a;57 brain morphogenesis: miR-7,58 miR-370 (ref. 59) and myelination in the central nervous system: miR-23a.60 Furthermore, our study identied miRNAs implicated in the pathological development of schizophrenia, such as miR-132 (ref. 61) and miR-382;62 and of Alzheimers, such as miR-98.63 In addition, several of the miRNAs with aberrant challenge-response in MDD have been described as potential peripheral biomarkers for psychiatric or neurological diseases: miR-564 (ref. 64) and miR-132 for schizophrenia;65 hsa-let-7g and miR-15b for Alzheimer's;66 and miR-1285, miR-34a and miR-34b for Huntingtons

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Table 2. Experimentally established involvement of the miRNAs from MDD GAL and MDD RL signatures in cellular processes (on the basis of PubMed search)

Physiological process miRNA_ID

MDD GAL miRNAMetabolism miR-33a*, miR-7, miR-296-5p, miR-181a*, miR-497*Fatty acid metabolism miR-296-5p, miR-193a-3p

P53 miR-1208, miR-1285, miR-7Apoptosis/proliferation miR-548c-5p, miR-7, miR-382, miR-296-5p, miR-181*, miR-193a-3p, miR-1285, miR-32, miR-497* Migration/c-MET miR-548c-5p, miR-7, miR-296-5p, miR-497*Neurons/psychiatry miR-7, miR-382, miR-296-5p, miR-32, miR-497*

MDD RL miRNAMetabolism miR-33a, miR-7, miR-661, miR-1307, miR-376a, miR-26a, miR-132, miR-25, miR-98, miR-34a, miR-23a, miR-199a/b-3p, miR-296-5pFatty acid metabolism miR-3613-3p, miR-33a, miR-192, miR-26a, miR-34a, miR-370, miR-15b, miR-296-5pP53 miR-34b, miR-16-1*, miR-661, miR-192, miR-7, miR-134, miR-25, miR-98, miR-34a, miR-370, miR-15b, miR-199a/b-3p Apoptosis/proliferation miR-33a, miR-34b, miR-16-1*, miR-661, miR-192, miR-7, miR-376a, miR-382, miR-26a, miR-134, miR-379, let-7g, miR-132, miR-25, miR-98, miR-34a, miR-370, miR-15b, miR-23a, miR-199a/b-3p, miR-100, miR-296-5pMigration/c-MET miR-34b, miR-661, miR-550a, miR-7, miR-376a, miR-26a, let-7g, miR-134, miR-132, miR-25,miR-98, miR-34a, miR-100, miR-296-5pNeurons/psychiatry miR-34b, miR-7, miR-376a, miR-382, miR-26a, miR-134, miR-564, let-7g, miR-132, miR-25, miR-98, miR-34a, miR-370, miR-15b, miR-23a, miR-199a/b-3p, miR-296-5p

Abbreviations: GAL, galactose; MDD, major depressive disorder; miRNA, microRNA; RL, reduced lipid. Metabolism/fatty acid metabolism.36,63,7494 Apoptosis/

proliferation/p53.37,49,54,56,58,95118 Migration.29,54,98,99,119131 Neurons/psychiatry.4851,53,54,5658,60,61,6366,6871,98,132134

Research Foundation. We are especially grateful to Weining Xu, Senior Manager at Qiagen, for her invaluable guidance in the use of the miRNome arrays. We thank the Vantage Molecular Biology Core at Vanderbilt for their help in performing the microarray and miRNome array studies. We offer our sincere appreciation to Dr Marla Perna, who provided constructive comments on the manuscript preparation.

disease.67 This study also identied a number of miRNAs that respond to different stressors in the nervous system: miR-34b, which affects the degree of oxidative stress and survival of dopaminergic neurons;68 miR-296-5p, which responds to oxidative stress in mouse hippocampal neuronal cultures;69 miR-199a, which reacts to hypoxia in rat cortical pericytes;70 and miR-98, which is elevated in the brains of newborn rats experiencing prenatal stress.71 And last, miR-296-5p, which showed aberrant response to both RL and GAL in MDD broblasts, presents a strong connection to MDD; miR-296-5p has been identied as a regulator of inducible I kappa-B kinase,72 a gene with genetic association with MDD.73

Taken together, this information gives condence to the relevance of our observations in broblasts to the MDD disease state. This study provides a solid foundation for future experiments with human broblasts aimed at deciphering the systemic immune disturbances in MDD. Moreover, our results demonstrate that aberrant responses to stressors are indeed present in the peripheral tissues from MDD patients. These responses intersect multiple cellular processes associated with mitochondria, such as regulation of metabolism and energy production, cell proliferation, survival and motility; therefore, they strongly suggest that the stress-response impairments of MDD patients are most likely based on impaired mitochondrial functions.

CONFLICT OF INTEREST

RCS receives unrelated research support from Assurex Health; Bristol-Myers Squibb; Eli Lilly and Company; Elan Corporation; Euthymics Bioscience; Forest Pharmaceuticals; Janssen Pharmaceutica; Jazz Pharmaceuticals; Naurex; Novartis Pharmaceuticals; Otsuka Pharmaceuticals; Pamlab; Pzer; Repligen Corporation; Ridge Diagnostics; St. Jude Medical; and Takeda Pharmaceuticals and consults for Bristol-Myers Squibb Company; Cerecor; Cyberonics; Eli Lilly and Company; Forest Pharmaceuticals; Janssen Pharmaceutica; Medtronic; Naurex; Pamlab; Pzer; Ridge Diagnostics; Shire Plc; and Takeda Pharmaceuticals. The remaining authors declare no conict of interest.

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ACKNOWLEDGMENTS

KM was supported by National Institute of Mental Health Grants R01 MH067234 and R01 MH079299. RCS was supported by National Institute of Mental Health Grants MH01741, MH52339 and MH073630 and a grant from the Brain and Behavior

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