Context
Mood disturbances are associated with an activated inflammatory response system.
Objective
To identify a discriminating and coherent expression pattern of proinflammatory genes in monocytes of patients with bipolar disorder.
Design
A quantitative polymerase chain reaction (Q-PCR) case-control gene expression study on purified monocytes of bipolar patients, the offspring of bipolar patients, and healthy control participants after having selected 22 discriminating inflammatory genes using whole genome analyses.
Setting
Academic research setting in the Netherlands.
Patients
Forty-two bipolar patients with 25 healthy controls, 54 offspring of a bipolar parent (13 had a mood disorder and 3 developed one during follow-up), and 70 healthy children underwent Q-PCR.
Main Outcome Measure
Inflammatory gene expression levels in monocytes.
Results
We detected in the monocytes of bipolar patients a coherent mutually correlating set (signature) of 19 aberrantly expressed (P < .01) messenger RNAs of inflammatory (PDE4B, IL1B, IL6, TNF, TNFAIP3, PTGS2, and PTX3), trafficking (CCL2, CCL7, CCL20, CXCL2, CCR2, and CDC42), survival (BCL2A1 and EMP1), and mitogen-activated protein kinase pathway (MAPK6, DUSP2, NAB2, and ATF3) genes. Twenty-three of 42 bipolar patients (55%) had a positive signature test result vs 7 of 38 healthy controls (18%)
(positive test result: positivity for PDE4B, ie, a messenger RNA 1 SD higher than the mean level found in healthy controls, plus 25% of the other genes with similar positive findings).
Positive signature test results were also present in 11 of 13 offspring with a mood disorder (85%), 3 of 3 offspring developing a mood disorder (100%), and 17 of 38 euthymic offspring (45%) vs 13 of 70 healthy children (19%). Lithium carbonate and antipsychotic treatment downregulated the gene expression of most inflammatory genes.
Conclusions
The monocytes of a large proportion of bipolar patients and offspring of bipolar parents showed an inflammatory gene expression signature. This coherent set of genes opens new avenues for biomarker development with possibilities for disease prediction in individuals genetically at risk and for the subclassification of bipolar patients who could possibly benefit from anti-inflammatory treatment.
The macrophage–T-cell theory of depression1,2 postulates an activated inflammatory response system in mood disorders and considers this activated inflammatory response system to be a driving force behind the illness, because proinflammatory cytokines are capable of destabilizing brain function.
This makes the brain vulnerable to stress and unknown endogenous factors such that major mood disturbances are the consequence. In animal models,
the behavioral changes induced by proinflammatory cytokines (sickness behavior) are comparable to the symptoms of depression as seen in humans.3Also in humans, low intravenous doses of endotoxin increase the level of these cytokines and induce depressive symptoms.4,5 Furthermore, depressive symptoms and mania can be precipitated by interferon alpha treatment,6 whereas anti–tumor necrosis factor (TNF) therapy given for psoriasis resulted in a markedly improved mood.7 Last, in patients with mood disorders, increased serum, saliva,
and cerebral spinal fluid levels of several proinflammatory compounds have been found, such as interleukin 6 (IL-6), IL-1β, TNF-α,
prostaglandin E2 (PGE2), and chemokine ligand 2 (CCL2),5,8-11 although other studies have reported negative findings.12 In addition, there have been reports on high serum levels of positive acute-phase proteins (eg, haptoglobin, α1-antitrypsin, ceruloplasmin, and C-reactive protein) and low levels of negative acute-phase proteins (eg, albumin and retinal-binding protein) in patients with mood disorders, indicating that mood disorders are accompanied by an acute-phase response.13-15
We herein report outcomes of a quantitative polymerase chain reaction (Q-PCR) study on monocytes of patients with bipolar disorder (hereinafter referred to as bipolar patients) in whom we found 19
aberrantly expressed genes involved in inflammation and inflammation-related processes after having identified and selected 21 such proinflammatory genes in whole-genome gene expression profiling (Affymetrix, Santa Clara, California) on purified CD14+ monocytes of a limited set of bipolar patients. The expression levels of the inflammatory and inflammation-related genes were mutually strongly correlated in 4 functional pathways, forming a monocyte gene expression signature.
To investigate whether this set of aberrantly expressed genes exists before disease, we also tested the monocytes of 54 children of bipolar parents; of these 54 children, 13 had a mood disorder and 3 were found to have a mood disorder within 2 to 3 years after blood sample collection.16
Patients and healthy control participants
Outpatients with DSM-IV bipolar I or II disorder were recruited from the following 2 studies: the Dutch site of the Stanley Foundation Bipolar Network (SFBN), an international multicenter research program described elsewhere in detail17,18 (n = 19 for the gene profiling analysis studies and n = 19 for Q-PCR verification),
and an ongoing Dutch twin study on bipolar disorder described in detail in Vonk et al19 (n = 23
index cases for Q-PCR studies). Clinical characteristics of the bipolar patients used for Q-PCR are shown in Table 1.
Offspring of a Bipolar Patient
The offspring of bipolar patients described herein belong to an ongoing prospective study among the adolescent offspring of a bipolar patient in the Netherlands. The children were not related to the bipolar patient group mentioned in the previous subsection. The study design,
recruitment procedure, and study population have been described elsewhere in detail.16,20,21 In brief,
86 bipolar patients and their spouses and 140 offspring aged 12 to 21 years were examined between November 1, 1997, and March 31, 1999
(time 1). Fourteen months after the first assessment, 132 offspring aged 13 to 23 years were available for reassessment (time 2). At time 2, we were able to collect immune cells for our study from 54 offspring (26 male and 28 female subjects). At the third assessment (time 3),
41 months after time 2, 129 offspring (aged 16-26 years) belonging to 80 families were still participating.16 Further characteristics of the bipolar offspring are given in Table 2.
A DSM-IV diagnosis of bipolar disorder was made by means of the Structured Clinical Interview for DSM-IV Axis I in the bipolar patients of the SFBN,
in the bipolar patients of the twin study, and in the bipolar offspring study at time 3 or by means of the Schedule for Affective Disorders and Schizophrenia, Children's Version in the bipolar offspring study at times 1 and 2. The bipolar patients of the SFBN underwent assessment at monthly follow-up visits by means of the Young Mania Rating Scale,
the Inventory of Depressive Symptomatology, and the Clinical Global Impressions Scale–Bipolar Version.
Adult healthy controls were recruited via the enrolling laboratory,
medical staff, and medical students. The offspring study controls were healthy Dutch high school students. The inclusion criteria for the control groups were an absence of psychiatric disorders such as psychosis, mood disorders, and anxiety disorders, and also of the medical disorders chronic fatigue syndrome and fibromyalgia, and a history free of these disorders in first-degree family members. Healthy controls had to be in self-proclaimed good health and free of any obvious medical illness for at least 2 weeks before the blood withdrawal,
including acute infections and allergic reactions. Healthy controls did not use any psychotropic or other medication.
The Medical Ethical Review Committee of the University Medical Center Utrecht approved the studies. Written informed consent was obtained from all participants after a complete description of the study was given.
Blood Collection and Preparation
Blood was collected in a clotting tube for serum preparation (frozen and stored at −80°C) and in tubes containing heparin sodium for immune cell preparation. From the heparinized blood samples,
peripheral blood mononuclear cell (PBMC) suspensions were prepared via low-density gradient centrifugation as described in detail elsewhere22 within 5 hours for all samples to avoid activation of the monocytes. The PBMCs were frozen in 10% dimethyl sulfoxide and stored in liquid nitrogen. This enabled us to test patient and control immune cells in the same series of experiments at appropriate times.
On the day of testing, stored PBMC suspensions were quickly thawed and directly diluted in RPMI 1640 medium with Ultraglutamine 1 and 25mM Hepes (BioWhittaker brand; Lonza, Verviers, Belgium) to wash out the dimethyl sulfoxide. The viability of the cells was invariably more than 90% (trypan blue exclusion staining). Monocytes were prepared from the PBMC suspensions by a magnetic cell sorting system for CD14
separation (MACS; Miltenyi Biotec, Auburn, California) according to the manufacturer's recommendations. Purity of the monocytes was routinely determined for each sample by morphological screening of the wet preparation after trypan blue staining. In addition, purity was determined by routine flow cytometry analysis (FACSCalibur [Becton Dickinson, Amsterdam,
the Netherlands] and antibody CD14 APC [BD Pharmingen, San Diego,
California]) on randomly chosen samples.
Affymetrix Whole Genome Gene Expression Profiling
The RNA was isolated from the purified monocytes using minipreparation columns (RNeasy; Qiagen, Hilden, Germany) as described by the manufacturer and previously.23 The RNA was first converted into complementary DNA (cDNA) and subsequently into complementary RNA (cRNA). Fragmented cRNA was hybridized to U95Av2 microarrays (Affymetrix,
according to the manufacturer's protocol). For all experiments reported herein, the 5′ to 3′ ratios of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were 2 or less (usually 0.9-1.1).
All raw data obtained via whole genome gene expression profiling are available as MIAMExpress submission E-MEXP-1275 (http://www.ebi.ac.uk/miamexpress/).
The RNA was isolated from monocytes using minipreparation columns (RNeasy) per the manufacturer's protocol. After extraction, the RNA concentration was determined and RNA was stored at 80°C until use.
To obtain cDNA for the Q-PCR, we used the optimized extensively described Biomed-1 protocol.24 One microgram of RNA was reverse transcribed using a commercial reverse transcriptase kit (SuperscriptII; Invitrogen, Carlsbad, California)
and random hexamers (Amersham Biosciences, Roosendaal, the Netherlands)
for 50 minutes at 42°C.
Quantitative PCR was performed with a commercially available mix (TaqMan Universal PCR Master Mix; Applied Biosystems, Foster City, California). All TaqMan probes and consensus primers were preformulated and designed by the manufacturer (Assays-on-Demand; Applied Biosystems) on the basis of the detected transcript clusters of the bipolar discriminating genes detected in the Affymetrix analysis (available in eTable 1 and the “Results” section). The PCR conditions were 2 minutes at 50°C and 10 minutes at 95°C, followed by 40 cycles of 15 seconds at 95°C, and finally 1 minute at 60°C.
The PCR amplification of the housekeeping gene ABL (see eTable 1 for all gene accession numbers) was performed for each sample to allow normalization between the samples. We chose ABL as the housekeeping gene because it was previously shown that ABL was the most consistently expressed housekeeping gene in hematopoietic cells.25 Data were expressed as cycle threshold (CT)
values corrected to ABL (ΔCT values,
described in eTable 2 and eTable 3) and as fold change values determined via the ΔΔCT method (User Bulletin 2; Applied Biosystems) (Table 3 and Table 4). To correct for interassay variance we set the mean of the studied genes found in the healthy control groups in the same assay for each gene to 1, and the fold change values of the genes in patient monocytes were expressed relative to this set mean of 1 of the healthy controls for the given values.
Using the aberrantly expressed genes in the monocytes of the patients, various signatures could be defined. The definitions depend on the percentage of positive genes, with positivity defined as a messenger RNA (mRNA) expression 1 SD higher than the mean level found in the healthy controls.
Bioinformatics and statistics
Scanned microarray images were analyzed using commercially available software (Microarray Suite 4.2; Affymetrix). Further analysis was performed using Rosetta Resolver (http://www.rosettabio.com) biosoftware. The genes were classified with Ingenuity Systems software (http://www.ingenuity.com). Statistical analysis of the data was performed using the SPSS 11.0 statistical software package for Windows (SPSS Inc, Chicago, Illinois). Data were tested for normal distribution using the Kolmogorov-Smirnov test. Depending on the distribution pattern and the total number of subjects, parametric (normal distribution,
≥ 50 subjects) or nonparametric tests (skewed distribution,
< 50 subjects) were used. Differences in means between groups were determined using the Mann-Whitney test, or the Kruskal-Wallis test for more than 2 groups. Correlations were determined via Pearson or Spearman correlation coefficients, linear regression, and univariate analyses of variance and covariance. Frequencies were compared using the χ2 test. The specific tests used are indicated in the legends of the figures and tables.
Search for potential inflammatory biomarker genes via affymetrix analysis
Affymetrix analysis was performed on the MACS-purified pooled monocytes from 5 non–lithium carbonate–treated bipolar patients (aged 12-36 years; mean age, 22 years; 3 female and 2 male patients) and 6 healthy controls (aged 12-39 years; mean age, 20 years;
3 female and 3 male patients) with the aim to search in particular for inflammation-related genes. The 11 cell files are available as MIAMExpress submission E-MEXP-1275 (http://www.ebi.ac.uk/miamexpress/). We analyzed the data using the Rosetta Resolver program and considered for further study only genes with a statistically significant differential expression of more than 2-fold (P < .01)
between the bipolar patients and control group. This resulted in 71
discriminating genes for non–lithium-treated bipolar patients (64 upregulated and 7 downregulated). Major functional networks found to be involved in Ingenuity Systems analysis were indeed inflammation and cell movement but also cellular growth and differentiation. Pathways involved were the mitogen-activated protein kinase (MAPK) pathway,
the IL-6 signaling pathway, and the apoptosis pathway. To select for genes that could serve as potential monocyte biomarkers for the bipolar inflammatory condition, we took the top 7 genes from the list (ie, PDE4B, ATF3, MAPK6, DUSP2, TNFAIP3, CXCL2, and BCL2A1) and 6 genes with a statistically significant differential expression of more than 2-fold with a well-known involvement in inflammation, the MAPK and IL-6 pathways, and cell movement (ie, IL1B, IL6, TNF, PTGS2, PTX3, and CCL20).
In addition, we analyzed the pooled monocytes, purified by the magnetic cell sorting system, of lithium-treated bipolar patients and healthy controls. Cell pools were mainly used to limit costs and to avoid interindividual differences. One pool consisted of monocytes of 7 lithium-treated bipolar patients (1 man and 6 women; mean age,
39 years; age range, 27-57 years) compared with a pool of healthy control monocytes (1 man and 6 women; mean age, 40 years; age range,
24-56 years); the other pool consisted of 7 lithium-treated bipolar patients (4 men and 3 women; mean age, 44 years; age range, 37-57
years) compared with a pool of healthy control monocytes (4 men and 3 women; mean age, 45 years; age range, 39-53 years). The raw data of the 4 pools are also available as MIAMExpress submission E-MEXP-1275
(http://www.ebi.ac.uk/miamexpress/). After Rosetta Resolver analysis, we found 187 discriminating genes (114 upregulated and 73
downregulated) between lithium-treated bipolar patients and healthy controls (2-fold difference). Ingenuity Systems analysis showed that lithium treatment downregulated genes involved in inflammation but induced the de novo expression of genes involved in cell growth, differentiation,
survival, and apoptosis. Because we were searching for potential inflammatory biomarkers, we selected in this set of genes those well known to be involved in inflammation, the MAPK and IL-6 pathways, and cell movement,
that is, HSPA1A, NAB2, CDC42, ADAM17, CCL2, CCR2, CCL7, CX3CR1, and EMP1. The 22 Affymetrix-selected genes were further validated using Q-PCR.
Q-pcr analysis of monocytes of bipolar patients
Table 3 (column A) shows that, of the 22 mRNAs tested, 19 could be verified in Q-PCR to be significantly differentially expressed (P ≤ .01) in the monocytes of a series of 42 newly selected bipolar patients compared with 25 healthy controls (see eTable 2 for ΔCT values). These were the inflammatory genes PDE4B, IL1B, IL6, TNF, TNFAIP3, PTGS2, and PTX3; the chemokinesis/motility genes CCL2, CCL7, CCL20, CXCL2, CCR2, and CDC42; the MAPK pathway genes MAPK6, DUSP2, NAB2, and ATF3; and the cell survival/apoptosis genes BCL2A1 and EMP1. All were overexpressed in the monocytes of bipolar patients, except for CCR2.
Table 5 shows that the actual mood status of the patients is related to the inflammatory gene expression. During a manic episode, the mRNA expression of MAPK6 and CCL2 was significantly increased in monocytes of manic vs euthymic bipolar patients; during depressive episodes, expression of these mRNAs was raised in addition to that of IL6, PTX3, EMP1, and BCL2A1. Although active disease thus is related to the mRNA expression of these molecules, almost all 19 mRNAs were still significantly higher in euthymic bipolar patients compared with healthy controls, except for CCL2 and EMP1.
Table 6 shows that lithium and antipsychotic treatment reduced the expression of PDE4B and TNF. We therefore analyzed the Q-PCR monocyte data for bipolar patients without lithium or antipsychotic treatment separately from the data of those receiving lithium and/or antipsychotic treatment (Table 3, columns B and C). Results of this analysis clearly indicated that,
in non–lithium- and non–antipsychotic-treated bipolar patients, the gene expressions of PDE4B, IL1B, IL6, TNF, TNFAIP3, PTGS2, PTX3, CCL20, CXCL2, BCL2A1, and DUSP2 were at particularly high levels, which were reduced by lithium and antipsychotic treatment. Expression of CCL2, CCL7, CDC42, CCR2, ATF3, NAB2, and MAPK6 were not affected by lithium and/or antipsychotic treatment. Expression of EMP1 was not raised in bipolar patients off lithium and/or antipsychotics, whereas lithium treatment had a significantly stimulating effect on EMP1 expression (Tables 3 and 6). The Q-PCR data thus verify the limited Affymetrix data, showing a decrease in inflammatory genes and a rise in apoptotic genes in monocytes of lithium-treated bipolar patients.
Expression of EMP1 was also influenced by other medications; a higher level of expression was found with carbamazepine,
whereas a lower expression was found with valproate sodium (Table 6).
The other variables for which we tested (age, sex, body mass index, age at disease onset, duration of illness, and duration of lithium use) (via linear regression) lacked any significant effect on the aberrant mRNA expressions.
An inflammatory gene expression signature in bipolar patients
The expression levels of the 19 mRNAs were virtually all mutually strongly correlated in expression (see the eFigure [http://archgenpsychiatry.com]). The strongest correlations were found between PDE4B and the other mRNAs,
and PDE4B was the gene most consistently overexpressed. There are reasons to consider PDE4B as a key molecule in the proinflammatory state of the bipolar monocytes (discussed in the “Comment” section). We therefore tried out various definitions for the presence or absence of a PDE4B-associated proinflammatory mRNA signature (Table 7 and Table 8). The definitions given depend on the percentage of positive findings among the 19 genes, with positivity defined as an mRNA expression 1 SD higher than the mean level found in the healthy controls (Tables 7 and 8). In all definitions, PDE4B demonstrated positive findings. Using these definitions, it is evident that a PDE4B positivity in monocytes combined with a positivity for the other signature genes of up to 50% discriminates bipolar patients from healthy controls and that a proportion of up to 60% of bipolar patients is characterized by a PDE4B-associated proinflammatory, chemokinesis,
cell survival mRNA signature (depending on the signature definition).
It is also clear in this analysis that lithium and/or antipsychotic treatment downregulated the signature expression (Tables 7 and 8).
Inflammatory gene expression signature in offspring of bipolar patients
Table 4 demonstrates that the 13 bipolar offspring with a lifetime diagnosis of a mood disorder showed a raised level of expression of the mRNAs for all 18 signature genes tested (CCR2 was not tested) at time 2 (the time of monocyte testing) (for ΔCT values, see eTable 3). When expressed as signature positivity (Table 9 and Table 10), 11 of the 13 offspring with a lifetime diagnosis of a mood disorder at time 2 were positive for the proinflammatory signature if it was defined as positive findings for PDE4B plus 25% of the 19 genes. Four of those 13 offspring had a lifetime diagnosis of bipolar disorder; all 4 were positive for the signature. The other 9 children had a lifetime diagnosis of depression, and 7 of them had a proinflammatory signature. There was no relationship of positivity and negativity for this signature and the precise psychiatric diagnosis of the unipolar mood disorder (major depressed, dysthymia, or depression not otherwise specified).
Three offspring who were healthy at the time of blood collection at time 2 developed depression 41 months later at time 3. All 3 of these subjects had monocytes with the proinflammatory signature at time 2 (Tables 4, 9, and 10).
One offspring who had a lifetime diagnosis of depression at time 2 underwent conversion to a lifetime diagnosis of bipolar disorder at time 3; this subject had a full-blown proinflammatory signature (defined as positivity for PDE4B plus 100%
of the 18 genes) at time 2 (data not shown).
Table 4 additionally shows that healthy offspring of a bipolar parent (ie, no lifetime mood disorder at any time point tested) demonstrated aberrancies in the expression of the 19 proinflammatory, chemokinesis, and cell survival genes in their monocytes. The inflammatory gene signature defined as positive for PDE4B plus 25% or greater of the genes was found in 45% of them vs 19% in healthy young adults (Tables 9 and 10). However, expression levels of the proinflammatory genes IL6, TNF, TNFAIP3, PTX3, PTGS2, CCL7, CCL20, and CXCL2, and the MAPK pathway genes DUSP2 and ATF3 in particular were significantly higher in offspring with a mood disorder than in healthy euthymic offspring (Table 4).
EXPRESSION AT THE PROTEIN LEVEL OF ABERRANTLY EXPRESSED MONOCYTE SIGNATURE mRNAs
We measured (via standard commercially available enzyme-linked immunosorbent assays) the protein expression levels of the signature genes IL1B, IL6, CCL2, and CCL7 in bipolar patients and healthy controls described in Table 1. Although the serum levels of all 4 cytokines were higher in the bipolar patients, only that of IL-1β was statistically significantly raised (2 times higher in bipolar patients vs healthy controls, Figure 1A). The serum level of IL-1β was not influenced by mood (P = .58, Kruskal-Wallis test) or by treatment with lithium, antipsychotics, or any other drug.
There was no effect of age, sex, or body mass index on the levels of the cytokines.
We also measured the expression of CCR2, the receptor for CCL2, on monocytes via standard flow cytometry analysis and found that CCR2 was mainly expressed on the mature CD14+CD16+ set of monocytes (Figure 1B). Expression of CCR2 was not significantly different between monocytes of bipolar patients and healthy controls.
Levels of CCR2 expression were independent of mood status and use of medication.
We herein show that the monocytes of most bipolar patients and bipolar offspring (particularly those who later develop a mood disorder)
have an altered mRNA expression of genes involved in inflammation and inflammation-related processes.26-47 Owing to the coherent and mutually strongly correlating aberrant expression, the mRNAs form an mRNA signature representing a set of proinflammatory genes that discriminate bipolar patients from healthy controls.
Based on the literature, an interaction model of the aberrantly expressed genes can be constructed (Figure 2). This model illustrates the mutual interdependency of the molecules. The expression of positive and negative signals in the network is an indication that in the aberrant monocytes of bipolar patients regulation is operative. For inflammatory cytokines, mRNA and protein levels often do not correlate. Indeed, the approximately 6-fold- raised expression of IL1B at the monocyte mRNA level was reflected only in a 2-fold-raised protein level in the serum of bipolar patients, whereas CCL2, CCL7, IL-6,
and CCR2 protein expression were not significantly different. Clearly,
a regulation at the protein transcription level is operative in the monocytes of bipolar patients to ensure a close-to-normal function,
and the question thus arises concerning which environmental or endogenous condition will create a failure of the monocyte to keep control over its aberrant gene expression, avoiding a higher protein production of the proinflammatory compounds. Psychological stress (both acute and chronic) might be such a condition (via adrenaline and glucocorticoid signaling),48 and indeed stressors have an upregulating effect of IL-1β and IL-6.49 In addition, stressful life events triggered the onset of mood disorder episodes in the offspring of bipolar patients described herein,50 showing a possible interaction between the existence of an aberrant monocyte proinflammatory gene expression signature and environmental stress factors. A cofactor playing a role in this stress-induced immune activation might be a relative resistance of immune cells to glucocorticoids, which has been reported in patients with bipolar disorder.22 Such decreased glucocorticoid sensitivity has also been thought to be the mechanism behind the well-known hypothalamic-pituitary-adrenal axis disturbances in patients with mood disorders,51-53 and these disturbances have led to the concept that impaired glucocorticoid receptor signaling is a crucial factor in the pathogenesis of mood disorders.54
The overexpression of proinflammatory cytokines, mediators,
and chemokines in the monocytes of bipolar patients was in particular correlated with the overexpression of phosphodiesterase type 4B (PDE4B),
a cyclic adenosine monophosphate (cAMP)–degrading enzyme. It is tempting to speculate that this molecule acts as a key molecule in the proinflammatory state of bipolar monocytes apart from the fact that it was the most consistently overexpressed gene, because (1)
cAMP is known to be inhibitory for inflammatory cells55; (2) of the cAMP-specific isoenzymes, PDE4
is expressed in all the inflammatory and immunomodulating cells40; (3) high activity of PDE4B leads to a proinflammatory state40,41; (4) the PDE4B gene is crucial for the proinflammatory action of monocytes in gene knockout studies42; (5) the in vitro differentiation of monocytes to inflammatory macrophages leads to upregulation of PDE4B43; and (6) PDE4 inhibitors broadly inhibiting functions of inflammatory cells40,41 are in a far stage of development.
Using such medication not only results in anti-inflammatory effects such as reduction of TNF-α production42,45 but also in antidepressive effects when tested in animal models47 and clinical trials.56
Our findings also suggest that an assessment of the monocyte gene signature might be useful for prognostic purposes. In a previous report on the offspring of bipolar patients, we confirmed that bipolar disorder is more prevalent in such offspring and is preceded by 1
or more episodes of (until then unipolar) depressive episodes.20 Herein we showed that bipolar offspring with a lifetime diagnosis of bipolar or (still) unipolar depressive disorder were positive for the mRNA signature (similar to our adult bipolar patients). More importantly, all 3 offspring who were psychiatrically healthy at the time of first monocyte testing but had developed depression 3 years later had a positive monocyte gene signature. This suggests that a positive gene signature precedes the onset of the first mood episode in individuals at risk and is not the consequence of the psychiatric condition. Also, a large proportion of the still healthy euthymic offspring showed an aberrant gene signature. We hypothesize that these signature-positive offspring in particular are at risk for the development of depression and, eventually, possible bipolar mood disorder. We are currently planning a 10-year follow-up of our offspring study and hope to validate the signature test as a potential inflammatory biomarker set linked to mood disorders.
Our data on a raised expression of the genes for proinflammatory cytokines and related compounds support the macrophage–T-cell theory of mood disorders.57-59 However,
other reports refute a high level of cytokine production from immune cells in mood disorders,60,61 and our finding of a discrepancy between mRNA and protein levels of cytokines may in part explain this controversy. Our finding also underscores the superiority of gene expression over protein detection in diagnosing the activated inflammatory response system of bipolar patients.
We also found PTGS2 (cyclooxygenase 2 [COX-2], involved in the production of PGE262) and PTX3 to be part of the proinflammatory gene expression signature. Increased PGE2 levels have been described in the saliva,11 serum,63 and cerebrospinal fluid10 of depressed patients, and PGE2 seems to be directly involved in the sickness behavior of animals.64 An in vitro study reported an increased PGE2 secretion from blood cells of depressed patients,65 and a COX-2 inhibitor has been reported to enhance the therapeutic effects of reboxetine in patients with a major depressive disorder.66 Cells of the monocyte-macrophage lineage exposed to a variety of inflammatory signals, including IL-6,38 express and release PTX3, which has a nonredundant role in resistance to selected microbial agents,39 is also expressed in the brain and involved in neuronal plasticity and degeneration,67 and has been found to be overexpressed in the fibroblasts of melancholic patients.68
With regard to a genetic background for the aberrant proinflammatory gene signature in mood disorder, gene polymorphisms in important signature genes (ie, IL1B, TNF, and CCL2) have been described as being linked to the presence or treatment response of the disorders.69-71 However,
the inflammatory program is also activated in response to infection.
Because bipolar disorder has been linked to infection by viral and intracellular pathogens,72-74 a simple explanation for the inflammatory signature could be that the monocytes are reacting to infection.
Most of our bipolar patients used various psychotropic medications that influenced the expression level of the signature genes. The strongest effects were for lithium and antipsychotics. Extensive literature describes the immunomodulating effects of antipsychotics and lithium.75-77 With regard to proinflammatory cytokine production, reports are inconsistent.60,78-80 In our in vivo study, the mRNA levels for important inflammatory cytokines/compounds were reduced in monocytes by lithium and/or antipsychotic treatment but did not completely normalize to the level found in healthy controls.
Lithium also has profound effects on the MAPK system.81,82 In the rat brain, it stimulates phosphorylation of signaling molecules in the extracellular signal-regulated kinase (ERK) branch of the MAPK route81 and influences the expression of the ERK pathway–regulated apoptosis molecule B-cell leukemia/lymphoma 2–related protein A1 (BCL2A1).82 In our bipolar patients with already raised mRNA levels of the MAPK pathway genes and of BCL2A1, we could not find a stimulating effect of lithium on MAPK pathway genes or on BCL2A1 in the monocytes.
We herein described an inflammatory monocyte gene expression signature in patients with bipolar disorder reflecting their activated inflammatory response system. This signature is also present in bipolar offspring, particularly in those who later develop a mood disorder.
Correspondence: Hemmo A. Drexhage,
MD, PhD, Department of Immunology, Erasmus Medical Center, PO Box 1738, 3000 DR Rotterdam, the Netherlands (h.drexhage@erasmusmc.nl).
Submitted for Publication: June 4, 2007; final revision received December 5, 2007; accepted December 5, 2007.
Author Contributions: Dr Drexhage had full access to all data in the study and takes responsibility for the integrity of the data and the accuracy of the analysis. Drs Padmos and Hillegers share equal first authorship.
Financial Disclosure: None reported.
Funding/Support: This study was supported in part by a grant from the Stanley Medical Research Institute.
Additional Contributions: Harm J. de Wit, BSc, provided technical assistance. Christa Walgaard, MD, ran the CCR2 expression levels on bipolar monocytes.
Tar van Os helped in the design of the Figures. Caspar Looman, MSc,
provided guidance for the statistical analyses.
2.Leonard
BE The immune system, depression and the action of antidepressants.
Prog Neuropsychopharmacol Biol Psychiatry 2001;25
(4)
767- 780
PubMedGoogle ScholarCrossref 3.Dunn
AJSwiergiel
AHde Beaurepaire
R Cytokines as mediators of depression: what can we learn from animal studies?
Neurosci Biobehav Rev 2005;29
(4-5)
891- 909
PubMedGoogle ScholarCrossref 4.Yirmiya
RPollak
YMorag
MReichenberg
ABarak
OAvitsur
RShavit
YOvadia
HWeidenfeld
JMorag
ANewman
MEPollmacher
T Illness, cytokines, and depression.
Ann N Y Acad Sci 2000;917478- 487
PubMedGoogle ScholarCrossref 5.Suarez
ECKrishnan
RRLewis
JG The relation of severity of depressive symptoms to monocyte-associated proinflammatory cytokines and chemokines in apparently healthy men.
Psychosom Med 2003;65
(3)
362- 368
PubMedGoogle ScholarCrossref 6.Greenberg
DBJonasch
EGadd
MARyan
BFEverett
JRSober
AJMihm
MATanabe
KKOtt
MHaluska
FG Adjuvant therapy of melanoma with interferon-alpha-2b is associated with mania and bipolar syndromes.
Cancer 2000;89
(2)
356- 362
PubMedGoogle ScholarCrossref 7.Tyring
SGottlieb
APapp
KGordon
KLeonardi
CWang
ALalla
DWoolley
MJahreis
AZitnik
RCella
DKrishnan
R Etanercept and clinical outcomes, fatigue, and depression in psoriasis: double-blind placebo-controlled randomised phase III trial.
Lancet 2006;367
(9504)
29- 35
PubMedGoogle ScholarCrossref 8.Maes
MScharpe
SMeltzer
HYBosmans
ESuy
ECalabrese
JCosyns
P Relationships between interleukin-6 activity, acute phase proteins,
and function of the hypothalamic-pituitary-adrenal axis in severe depression.
Psychiatry Res 1993;49
(1)
11- 27
PubMedGoogle ScholarCrossref 9.Motivala
SJSarfatti
AOlmos
LIrwin
MR Inflammatory markers and sleep disturbance in major depression.
Psychosom Med 2005;67
(2)
187- 194
PubMedGoogle ScholarCrossref 10.Linnoila
MWhorton
ARRubinow
DRCowdry
RWNinan
PTWaters
RN CSF prostaglandin levels in depressed and schizophrenic patients.
Arch Gen Psychiatry 1983;40
(4)
405- 406
PubMedGoogle ScholarCrossref 11.Ohishi
KUeno
RNishino
SSakai
THayaishi
O Increased level of salivary prostaglandins in patients with major depression.
Biol Psychiatry 1988;23
(4)
326- 334
PubMedGoogle ScholarCrossref 12.Stübner
SSchon
TPadberg
FTeipel
SJSchwarz
MJHaslinger
ABuch
KDukoff
RLasser
RMuller
NSunderland
TRapoport
SIMoller
HJHampel
H Interleukin-6 and the soluble IL-6 receptor are decreased in cerebrospinal fluid of geriatric patients with major depression: no alteration of soluble gp130.
Neurosci Lett 1999;259
(3)
145- 148
PubMedGoogle ScholarCrossref 13.Maes
MScharpe
SVan Grootel
LUyttenbroeck
WCooreman
WCosyns
PSuy
E Higher alpha 1-antitrypsin, haptoglobin, ceruloplasmin and lower retinol binding protein plasma levels during depression: further evidence for the existence of an inflammatory response during that illness.
J Affect Disord 1992;24
(3)
183- 192
PubMedGoogle ScholarCrossref 14.Song
CDinan
TLeonard
BE Changes in immunoglobulin, complement and acute phase protein levels in the depressed patients and normal controls.
J Affect Disord 1994;30
(4)
283- 288
PubMedGoogle ScholarCrossref 15.Sluzewska
ASobieska
MRybakowski
JK Changes in acute-phase proteins during lithium potentiation of antidepressants in refractory depression.
Neuropsychobiology 1997;35
(3)
123- 127
PubMedGoogle ScholarCrossref 16.Reichart
CGWals
MHillegers
MHOrmel
JNolen
WAVerhulst
FC Psychopathology in the adolescent offspring of bipolar parents.
J Affect Disord 2004;78
(1)
67- 71
PubMedGoogle ScholarCrossref 17.Leverich
GSNolen
WARush
AJ McElroy
SLKeck
PEDenicoff
KDSuppes
TAltshuler
LLKupka
RKramlinger
KGPost
RM The Stanley Foundation Bipolar Treatment Outcome Network, I:
longitudinal methodology.
J Affect Disord 2001;67
(1-3)
33- 44
PubMedGoogle ScholarCrossref 18.Suppes
TLeverich
GSKeck
PENolen
WADenicoff
KDAltshuler
LL McElroy
SLRush
AJKupka
RFrye
MABickel
MPost
RM The Stanley Foundation Bipolar Treatment Outcome Network, II:
demographics and illness characteristics of the first 261 patients.
J Affect Disord 2001;67
(1-3)
45- 59
PubMedGoogle ScholarCrossref 19.Vonk
RSchot
ACKahn
RSNolen
WADrexhage
HA Is autoimmune thyroiditis part of the genetic vulnerability (or an endophenotype) for bipolar disorder?
Biol Psychiatry 2007;62
(2)
135- 140
PubMedGoogle ScholarCrossref 20.Hillegers
MHReichart
CGWals
MVerhulst
FCOrmel
JNolen
WA Five-year prospective outcome of psychopathology in the adolescent offspring of bipolar parents.
Bipolar Disord 2005;7
(4)
344- 350
PubMedGoogle ScholarCrossref 21.Hillegers
MHReichart
CGWals
MVerhulst
FCOrmel
JNolen
WADrexhage
HA Signs of a higher prevalence of autoimmune thyroiditis in female offspring of bipolar parents.
Eur Neuropsychopharmacol 2007;17
(6-7)
394- 399
PubMedGoogle ScholarCrossref 22.Knijff
EMBreunis
MNvan Geest
MCKupka
RWRuwhof
Cde Wit
HJNolen
WADrexhage
HA A relative resistance of T cells to dexamethasone in bipolar disorder.
Bipolar Disord 2006;8
(6)
740- 750
PubMedGoogle ScholarCrossref 23.Staal
FJWeerkamp
FBaert
MRvan den Burg
CMvan Noort
Mde Haas
EFvan Dongen
JJ Wnt target genes identified by DNA microarrays in immature CD34
+ thymocytes regulate proliferation and cell adhesion.
J Immunol 2004;172
(2)
1099- 1108
PubMedGoogle ScholarCrossref 24.Gabert
JBeillard
Evan der Velden
VHBi
WGrimwade
DPallisgaard
NBarbany
GCazzaniga
GCayuela
JMCave
HPane
FAerts
JLDe Micheli
DThirion
XPradel
VGonzalez
MViehmann
SMalec
MSaglio
Gvan Dongen
JJ Standardization and quality control studies of “real-time”
quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia: a Europe Against Cancer program.
Leukemia 2003;17
(12)
2318- 2357
PubMedGoogle ScholarCrossref 25.Beillard
EPallisgaard
Nvan der Velden
VHBi
WDee
Rvan der Schoot
EDelabesse
EMacintyre
EGottardi
ESaglio
GWatzinger
FLion
Tvan Dongen
JJHokland
PGabert
J Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using “real-time”
quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR):
a Europe Against Cancer program.
Leukemia 2003;17
(12)
2474- 2486
PubMedGoogle ScholarCrossref 27.Inoue
KZama
TKamimoto
TAoki
RIkeda
YKimura
HHagiwara
M TNFα-induced ATF3 expression is bidirectionally regulated by the JNK and ERK pathways in vascular endothelial cells.
Genes Cells 2004;9
(1)
59- 70
PubMedGoogle ScholarCrossref 28.Jeffrey
KLBrummer
TRolph
MSLiu
SMCallejas
NAGrumont
RJGillieron
CMackay
FGrey
SCamps
MRommel
CGerondakis
SDMackay
CR Positive regulation of immune cell function and inflammatory responses by phosphatase PAC-1.
Nat Immunol 2006;7
(3)
274- 283
PubMedGoogle ScholarCrossref 29.Camps
MNichols
AArkinstall
S Dual specificity phosphatases: a gene family for control of MAP kinase function.
FASEB J 2000;14
(1)
6- 16
PubMedGoogle Scholar 30.Wittmann
TWaterman-Storer
CM Cell motility: can Rho GTPases and microtubules point the way?
J Cell Sci 2001;114
(pt 21)
3795- 3803
PubMedGoogle Scholar 32.Ehrengruber
MUMuhlebach
SGSohrman
SLeutenegger
CMLester
HADavidson
N Modulation of early growth response (EGR) transcription factor–dependent gene expression by using recombinant adenovirus.
Gene 2000;258
(1-2)
63- 69
PubMedGoogle ScholarCrossref 35.Lee
HSSherley
JLChen
JJChiu
CCChiou
LLLiang
JDYang
PCHuang
GTSheu
JC EMP-1 is a junctional protein in a liver stem cell line and in the liver.
Biochem Biophys Res Commun 2005;334
(4)
996- 1003
PubMedGoogle ScholarCrossref 36.Jain
ATindell
CALaux
IHunter
JBCurran
JGalkin
AAfar
DEAronson
NShak
SNatale
RBAgus
DB Epithelial membrane protein-1 is a biomarker of gefitinib resistance.
Proc Natl Acad Sci U S A 2005;102
(33)
11858- 11863
PubMedGoogle ScholarCrossref 38.Alles
VVBottazzi
BPeri
GGolay
JIntrona
MMantovani
A Inducible expression of PTX3, a new member of the pentraxin family, in human mononuclear phagocytes.
Blood 1994;84
(10)
3483- 3493
PubMedGoogle Scholar 39.Garlanda
CHirsch
EBozza
SSalustri
ADe Acetis
MNota
RMaccagno
ARiva
FBottazzi
BPeri
GDoni
AVago
LBotto
MDe Santis
RCarminati
PSiracusa
GAltruda
FVecchi
ARomani
LMantovani
A Non-redundant role of the long pentraxin PTX3 in anti-fungal innate immune response.
Nature 2002;420
(6912)
182- 186
PubMedGoogle ScholarCrossref 40.Dal Piaz
VGiovannoni
MP Phosphodiesterase 4 inhibitors, structurally unrelated to rolipram,
as promising agents for the treatment of asthma and other pathologies.
Eur J Med Chem 2000;35
(5)
463- 480
PubMedGoogle ScholarCrossref 41.Giembycz
MA Cilomilast: a second generation phosphodiesterase 4 inhibitor for asthma and chronic obstructive pulmonary disease.
Expert Opin Investig Drugs 2001;10
(7)
1361- 1379
PubMedGoogle ScholarCrossref 42.Jin
SLConti
M Induction of the cyclic nucleotide phosphodiesterase PDE4B is essential for LPS-activated TNF-α responses.
Proc Natl Acad Sci U S A 2002;99
(11)
7628- 7633
PubMedGoogle ScholarCrossref 43.Shepherd
MCBaillie
GSStirling
DIHouslay
MD Remodelling of the PDE4 cAMP phosphodiesterase isoform profile upon monocyte-macrophage differentiation of human U937 cells.
Br J Pharmacol 2004;142
(2)
339- 351
PubMedGoogle ScholarCrossref 44.Houslay
MDBaillie
GS The role of ERK2 docking and phosphorylation of PDE4 cAMP phosphodiesterase isoforms in mediating cross-talk between the cAMP and ERK signalling pathways.
Biochem Soc Trans 2003;31
(pt 6)
1186- 1190
PubMedGoogle ScholarCrossref 45.Beshay
ECroze
FPrud’homme
GJ The phosphodiesterase inhibitors pentoxifylline and rolipram suppress macrophage activation and nitric oxide production in vitro and in vivo.
Clin Immunol 2001;98
(2)
272- 279
PubMedGoogle ScholarCrossref 46.Fleming
YMFrame
MCHouslay
MD PDE4-regulated cAMP degradation controls the assembly of integrin-dependent actin adhesion structures and REF52 cell migration.
J Cell Sci 2004;117
(Pt 11)
2377- 2388
PubMedGoogle ScholarCrossref 47.Itoh
TTokumura
MAbe
K Effects of rolipram, a phosphodiesterase 4 inhibitor, in combination with imipramine on depressive behavior, CRE-binding activity and BDNF level in learned helplessness rats.
Eur J Pharmacol 2004;498
(1-3)
135- 142
PubMedGoogle ScholarCrossref 48.Delgado
MFernandez-Alfonso
MSFuentes
A Effect of adrenaline and glucocorticoids on monocyte cAMP-specific phosphodiesterase (PDE4) in a monocytic cell line.
Arch Dermatol Res 2002;294
(4)
190- 197
PubMedGoogle ScholarCrossref 49.Segerstrom
SCMiller
GE Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry.
Psychol Bull 2004;130
(4)
601- 630
PubMedGoogle ScholarCrossref 50.Wals
MHillegers
MHReichart
CGVerhulst
FCNolen
WAOrmel
J Stressful life events and onset of mood disorders in children of bipolar parents during 14-month follow-up.
J Affect Disord 2005;87
(2-3)
253- 263
PubMedGoogle ScholarCrossref 51.Rush
AJGiles
DESchlesser
MAOrsulak
PJParker
CR
JrWeissenburger
JECrowley
GTKhatami
MVasavada
N The dexamethasone suppression test in patients with mood disorders.
J Clin Psychiatry 1996;57
(10)
470- 484
PubMedGoogle ScholarCrossref 52.Watson
SGallagher
PRitchie
JCFerrier
INYoung
AH Hypothalamic-pituitary-adrenal axis function in patients with bipolar disorder.
Br J Psychiatry 2004;184496- 502
PubMedGoogle ScholarCrossref 53.Daban
CVieta
EMackin
PYoung
AH Hypothalamic-pituitary-adrenal axis and bipolar disorder.
Psychiatr Clin North Am 2005;28
(2)
469- 480
PubMedGoogle ScholarCrossref 55.Diamantstein
TUlmer
A The antagonistic action of cyclic GMP and cyclic AMP on proliferation of B and T lymphocytes.
Immunology 1975;28
(1)
113- 119
PubMedGoogle Scholar 56.Hebenstreit
GFFellerer
KFichte
KFischer
GGeyer
NMeya
USastre-y-Hernandez
MSchony
WSchratzer
MSoukop
W Rolipram in major depressive disorder: results of a double-blind comparative study with imipramine.
Pharmacopsychiatry 1989;22
(4)
156- 160
PubMedGoogle ScholarCrossref 57.Maes
MBosmans
ECalabrese
JSmith
RMeltzer
HY Interleukin-2 and interleukin-6 in schizophrenia and mania:
effects of neuroleptics and mood stabilizers.
J Psychiatr Res 1995;29
(2)
141- 152
PubMedGoogle ScholarCrossref 58.Rapaport
MHGuylai
LWhybrow
P Immune parameters in rapid cycling bipolar patients before and after lithium treatment.
J Psychiatr Res 1999;33
(4)
335- 340
PubMedGoogle ScholarCrossref 59.Liu
HCYang
YYChou
YMChen
KPShen
WWLeu
SJ Immunologic variables in acute mania of bipolar disorder.
J Neuroimmunol 2004;150
(1-2)
116- 122
PubMedGoogle ScholarCrossref 60.Hornig
MGoodman
DBKamoun
MAmsterdam
JD Positive and negative acute phase proteins in affective subtypes.
J Affect Disord 1998;49
(1)
9- 18
PubMedGoogle ScholarCrossref 61.Haack
MHinze-Selch
DFenzel
TKraus
TKuhn
MSchuld
APollmacher
T Plasma levels of cytokines and soluble cytokine receptors in psychiatric patients upon hospital admission: effects of confounding factors and diagnosis.
J Psychiatr Res 1999;33
(5)
407- 418
PubMedGoogle ScholarCrossref 62.James
MJPenglis
PSCaughey
GEDemasi
MCleland
LG Eicosanoid production by human monocytes: does COX-2 contribute to a self-limiting inflammatory response?
Inflamm Res 2001;50
(5)
249- 253
PubMedGoogle ScholarCrossref 63.Calabrese
JRSkwerer
RGBarna
BGulledge
ADValenzuela
RButkus
ASubichin
SKrupp
NE Depression, immunocompetence, and prostaglandins of the E series.
Psychiatry Res 1986;17
(1)
41- 47
PubMedGoogle ScholarCrossref 64.Yirmiya
RBarak
OAvitsur
RGallily
RWeidenfeld
J Intracerebral administration of
Mycoplasma fermentans produces sickness behavior: role of prostaglandins.
Brain Res 1997;749
(1)
71- 81
PubMedGoogle ScholarCrossref 65.Song
CLin
ABonaccorso
SHeide
CVerkerk
RKenis
GBosmans
EScharpe
SWhelan
ACosyns
Pde Jongh
RMaes
M The inflammatory response system and the availability of plasma tryptophan in patients with primary sleep disorders and major depression.
J Affect Disord 1998;49
(3)
211- 219
PubMedGoogle ScholarCrossref 66.Müller
NSchwarz
MJDehning
SDouhe
ACerovecki
AGoldstein-Muller
BSpellmann
IHetzel
GMaino
KKleindienst
NMoller
HJArolt
VRiedel
M The cyclooxygenase-2 inhibitor celecoxib has therapeutic effects in major depression: results of a double-blind, randomized, placebo controlled, add-on pilot study to reboxetine.
Mol Psychiatry 2006;11
(7)
680- 684
PubMedGoogle ScholarCrossref 67.Garlanda
CBottazzi
BBastone
AMantovani
A Pentraxins at the crossroads between innate immunity, inflammation,
matrix deposition, and female fertility.
Annu Rev Immunol 2005;23337- 366
PubMedGoogle ScholarCrossref 68.Shelton
RCLiang
SLiang
PChakrabarti
AManier
DHSulser
F Differential expression of pentraxin 3 in fibroblasts from patients with major depression.
Neuropsychopharmacology 2004;29
(1)
126- 132
PubMedGoogle ScholarCrossref 69.Pae
CUYu
HSKim
TSLee
CULee
SJJun
TYLee
CSerretti
APaik
IH Monocyte chemoattractant protein-1 (MCP1) promoter–2518
polymorphism may confer a susceptibility to major depressive disorder in the Korean population.
Psychiatry Res 2004;127
(3)
279- 281
PubMedGoogle ScholarCrossref 70.Jun
TYPae
CUHoon
HChae
JHBahk
WMKim
KSSerretti
A Possible association between −G308A tumour necrosis factor-α
gene polymorphism and major depressive disorder in the Korean population.
Psychiatr Genet 2003;13
(3)
179- 181
PubMedGoogle ScholarCrossref 71.Yu
YWChen
TJHong
CJChen
HMTsai
SJ Association study of the interleukin-1beta (C-511T) genetic polymorphism with major depressive disorder, associated symptomatology,
and antidepressant response.
Neuropsychopharmacology 2003;28
(6)
1182- 1185
PubMedGoogle Scholar 72.Dickerson
FBBoronow
JJStallings
COrigoni
AECole
SKrivogorsky
BYolken
RH Infection with herpes simplex virus type 1 is associated with cognitive deficits in bipolar disorder.
Biol Psychiatry 2004;55
(6)
588- 593
PubMedGoogle ScholarCrossref 73.Yolken
RHTorrey
EF Viruses, schizophrenia, and bipolar disorder.
Clin Microbiol Rev 1995;8
(1)
131- 145
PubMedGoogle Scholar 74.Ferszt
RSeverus
EBode
LBrehm
MKuhl
KPBerzewski
HLudwig
H Activated Borna disease virus in affective disorders.
Pharmacopsychiatry 1999;32
(3)
93- 98
PubMedGoogle ScholarCrossref 75.Rybakowski
JK Antiviral and immunomodulatory effect of lithium.
Pharmacopsychiatry 2000;33
(5)
159- 164
PubMedGoogle Scholar 76.Drzyzga
LObuchowicz
EMarcinowska
AHerman
ZS Cytokines in schizophrenia and the effects of antipsychotic drugs.
Brain Behav Immun 2006;20
(6)
532- 545
PubMedGoogle ScholarCrossref 77.Pollmächer
THaack
MSchuld
AKraus
THinze-Selch
D Effects of antipsychotic drugs on cytokine networks.
J Psychiatr Res 2000;34
(6)
369- 382
PubMedGoogle ScholarCrossref 78.Himmerich
HKoethe
DSchuld
AYassouridis
APollmacher
T Plasma levels of leptin and endogenous immune modulators during treatment with carbamazepine or lithium.
Psychopharmacology (Berl) 2005;179
(2)
447- 451
PubMedGoogle ScholarCrossref 79.Maes
MSong
CLin
AHPioli
RKenis
GKubera
MBosmans
E In vitro immunoregulatory effects of lithium in healthy volunteers.
Psychopharmacology (Berl) 1999;143
(4)
401- 407
PubMedGoogle ScholarCrossref 80.Boufidou
FNikolaou
CAlevizos
BLiappas
IAChristodoulou
GN Cytokine production in bipolar affective disorder patients under lithium treatment.
J Affect Disord 2004;82
(2)
309- 313
PubMedGoogle ScholarCrossref 81.Einat
HYuan
PGould
TDLi
JDu
JZhang
LManji
HKChen
G The role of the extracellular signal-regulated kinase signaling pathway in mood modulation.
J Neurosci 2003;23
(19)
7311- 7316
PubMedGoogle Scholar 82.Manji
HKChen
G PKC, MAP kinases and the bcl-2 family of proteins as long-term targets for mood stabilizers.
Mol Psychiatry 2002;7
((suppl 1))
S46- S56
PubMedGoogle ScholarCrossref