The World Journal of Biological Psychiatry, 2014; Early Online: 1–8

ORIGINAL INVESTIGATION

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Elevated levels of cerebrospinal fluid neuron-specific enolase (NSE), but not S100B in major depressive disorder

FRANK MARTIN SCHMIDT1, ROLAND MERGL1, BARBARA STACH2, INA JAHN1 & PETER SCHÖNKNECHT1 1Department

of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany, and 2Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany

Abstract Objectives. Alterations in neuronal and glial integrity are considered to be of pathogenic impact on major depressive disorder (MDD). For MDD, data on cerebrospinal fluid (CSF) levels of neuron-specific enolase (NSE) are lacking and scarce for glial protein S100B. Methods. We measured CSF levels of NSE and S100B in 31 patients with MDD and 32 mentally healthy controls using electrochemiluminescence immunoassays (ECLIA). Results. Adjusted means of NSE were significantly elevated in the MDD patients (11.73 ng/ml (9.95–13.52 95% CI) compared to the controls (6.17 ng/ml (4.55–7.78), F ⫽ 9.037, P ⫽ 0.004. Effect size for adjusted mean group difference of 5.57 ng/ml was found invariably high (Cohen’s d ⫽ 1.23). Differentiating MDD from controls, a NSE cut-off of 7.94 ng/ml showed sensitivity of 81% (95% CI 63.7–90.8) and specificity of 75% (95% CI 57.9–86.7). Adjusted levels of S100B did not differ significantly between the two groups (1.12 ng/ml (0.77–1.48) in MDD, 0.97 ng/ml (0.64–1.30) in controls). Conclusions. Our results of elevated CSF-NSE levels support neuronal pathology in MDD and the potential use of CSF-NSE as marker in clinical diagnostics. Missing group differences in S100B do not promote a specific glial pathology in depressive disorders. Key words: major depressive disorder, neuronal biomarker, neuron specific enolase, NSE, S100B

Introduction Major depressive disorder (MDD) is the leading global cause of years of health lost to disease in both men and women (WHO 2014), belongs to the most common mental disorders with lifetime prevalence of up to 20% (Kessler et al. 2005) and shows high mortality rates of 10% (Wulsin et al. 1999). Effort on the knowledge of the neurobiology and improvement in treatment efficiency in MDD has led to the detection of various molecular and structural changes within the brain (Kern et al. 2012; Sacher et al. 2012; Schindler et al. 2012; Lichtblau et al. 2013). Both neuronal and glial alterations are regarded to have pathogenic impact on the onset and course of the disorder (Rajkowska 2000; Rajkowska and Stockmeier, 2013). Uniquely located in the cytoplasm of neurons, the glycolytic enzyme neuron-specific enolase (NSE) has regulatory impact on both neuronal metabolism and neurotrophy and is clinically applied as a marker for

changes in neuronal integrity (Kaiser et al. 1989; Cooper 1999; Pollak et al. 2003; Hein et al. 2008; Böhmer et al. 2011; Ahmad et al. 2012; Duan et al. 2012). Whereas, to the authors’ knowledge, NSE has not been determined in the CSF in MDD to date, investigations on serum levels of NSE have presented conflicting results with reduced levels in MDD and bipolar patients (Machado-Vieira et al. 2007; Wiener et al. 2013) or missing differences between MDD patients and healthy subjects (Schroeter et al. 2008). Serving as marker for glia cell activity, S100beta (S100B) is a calcium-binding protein specifically found in astrocytes and oligodendrocytes, with proinflammatory and neurotrophic properties on serotonergic neurons, with changes in S100B levels resulting from short-term trauma and long-term degeneration (Steiner et al. 2007; Hein et al. 2008; Shapiro et al. 2010; Böhmer et al. 2011; Ahmad et al. 2012; Michetti et al. 2012). Findings of elevated

Correspondence: Frank M. Schmidt, MD, University Hospital Leipzig, Department of Psychiatry and Psychotherapy, Semmelweisstr. 10, D-04103 Leipzig, Germany. Tel: ⫹ 49-341-9725036. Fax: ⫹ 49-341-9724448. E-mail: [email protected] (Received 2 April 2014 ; accepted 5 August 2014 ) ISSN 1562-2975 print/ISSN 1814-1412 online © 2014 Informa Healthcare DOI: 10.3109/15622975.2014.952776

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S100B levels in MDD from the yet solitary study on CSF levels (Grabe et al. 2001) and studies on serum levels in MDD (Jang et al. 2008; Yang et al. 2008; Schroeter et al. 2011) give support for the hypotheses of a glial pathology in depression (Rajkowska 2000; Rajkowska and Stockmeier, 2013). In bipolar disorder, a recent investigation on a large cohort of patients with missing alterations in CSF-S100B levels gives evidence rather for axonal than glial damage in affective disorder (Jakobsson et al. 2014).

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Aims of the study To demonstrate surrogate markers of either neuronal or glial pathology, or both, in MDD, CSF-NSE and CSF-S100B levels were compared between patients suffering from MDD and mentally healthy controls. Methods Subjects A total of 31 patients with MDD and 32 controls without any psychiatric or neurological disorders were consecutively recruited to participate in the study and were included into the final analyses. Three depressed patients at first agreed upon participation, but later withdrew consent without providing explanations. All patients and controls were admitted to hospital as inpatients. Patients with MDD were recruited from the Department of Psychiatry and Psychotherapy, University Hospital Leipzig, where they were admitted for diagnosis and treatment. MDD was diagnosed by a senior specialist in psychiatry according to DSM-IV criteria. Assessment of severities was supported by performance of the 17-item Hamilton Rating Scale for Depression (HAMD-17; Hamilton 1960). Patients were only included when no psychiatric comorbidities, current neurological disorders or symptoms were diagnosed by clinical and laboratory investigations and no history of neurological disorder existed. Eight of 31 patients were drug-naïve for ⬎ 14 days prior to lumbar puncture. The other 23 patients received: citalopram (n ⫽ 9), mirtazapine (n ⫽ 8), sertraline (n ⫽ 2), amitriptyline (n ⫽ 2), reboxetine (n ⫽ 1), duloxetine (n ⫽ 1), lithium (n ⫽ 3), valproic acid (n ⫽ 2), olanzapine (n ⫽ 1), promethazine (n ⫽ 3). Controls were recruited from the Department of Anaesthesiology and Intensive Care Medicine, University Hospital Leipzig, prior to elective abdominal or urological surgery. The interventions were made necessary due to benign prostatic hyperplasia (n ⫽ 13), urinary calculus (n ⫽ 8), hernia inguinalis (n ⫽ 3), haemorrhoids (n ⫽ 2), stress incontinence (n ⫽ 2), bilestone (n ⫽ 2), varicocele (n ⫽ 1), hepatic haemangioma (n ⫽ 1). Controls showing any signs of neurological or

psychiatric disorder in clinical and laboratory investigation or with a history of either or were excluded from the study. In order to further survey exclusion criteria, the Structured Clinical Interview Axis I Disorder (SCID; First et al. 1997) and HAMD-17 were performed. Participants with medical conditions potentially affecting levels of NSE and S100B were excluded from participation. These included suspected or confirmed pulmonary microcytoma, neuroblastoma, neuroendocrine tumours, leukoencephalopathy, present or history of head trauma and disruptions of the blood–brain barrier (BBB). Only subjects with normal ranges of CSF-lactate, CSFglucose, quotient of CSF-serum albumin, cell count, and no dysfunction of the blood–cerebrospinal fluid barrier, were included into the study.Written informed consent was obtained from all subjects in accordance with the guidelines laid down in the current version of the Declaration of Helsinki.This study was approved by Leipzig University and Saxony Medical Ethics Committee. Lumbar puncture procedure and neuropeptide assays Lumbar puncture was performed similarly within both groups as laid down in the guidelines of the Deutsche Gesellschaft für Neurologie (DGN; http://www.dgn.org/leitlinien-online-2012/inhaltenach-kapitel/2424-ll-84-2012-diagnostischeliquorpunktion.html). All lumbar punctures were performed in a time slot between 12:30 p.m. and 1:30 p.m. After this, samples were immediately aliquoted in non-absorbing 300-μl polypropylene tubes and probes were shock-frozen in fluid N2 and stored in freezers at –80°C until further measurements (n ⫽ 56), or were instantly measured (n ⫽ 7). For the measurement of NSE we used an electrochemiluminescence immunoassay (ECLIA) with a linear measuring range between 0.050 and 370 ng/ml (Elecsys, Roche Diagnostics). For the measurement of S100B we used an ECLIA with a linear measuring range between 0.005 and 39 μg/ml (Elecsys). Statistical analysis The IBM Statistical Package for the Social Sciences (SPSS) program version 20.0 for Windows was used for all statistical analyses. Graphs were drawn with GraphPad Prism 6. The significance level was set at P ⬍ 0.05. Independent samples t-test was applied for group differences in NSE levels, following normal distribution of NSE values according to Kolmogorov–Smirnov testing. For examination of group differences in S100B levels, Mann–Whitney U-test was performed following non-Gaussian distribution. One-way analyses of covariance (ANCOVA) were performed with

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CSF-NSE and S100B in major depressive disorder 3 CSF-NSE as well as CSF-S100B as the dependent variables, with group, sex, psychotropic medication yes/no, storage vs. instant measure as independent variables and age as well as duration of storage as covariates. Effect size for NSE and S100B between groups was calculated using Cohen’s d (Cohen 1988). In the case of an ANCOVA, Cohen’s d was estimated by using the following formula: d ⫽ mean difference between the contrasts/square root of the mean square computed for errors in the model. To assess the accuracy rates of NSE, receiver operating characteristic (ROC) analyses resulting in area under the curve values (AUCs) were performed. Sensitivity and specificity were computed for different cut-off scores. The Youden index was used to select optimal cut-off scores (Youden 1950). Group differences in age were analysed with an independent samples t-test, HAMD-17 differences with a Mann–Whitney U-test and differences in gender distribution by using a Chi2-test. For correlation analyses between NSE and S100B, and age at onset of MDD and duration of the disorder, Spearman rank correlation was used. For correlation analyses between the respective parameters and age and HAMD-17-scores, Pearson and Spearman correlations were performed, respectively.

Results In the present study, 31 MDD patients and 32 controls were included. Subjects’ socio-demography and clinical characteristics are depicted in Table I. Means of CSF-NSE were found significantly elevated in the MDD patients compared to controls (F ⫽ 9.037, P ⫽ 0.004), whereas none of the factors or covariates were shown to have a significant impact on group differences (all P ⬎ 0.05). In contrast, S100B did not differ between the two groups (F ⫽ 0.007, P ⫽ 0.549) (see Figures 1 and 2).

The effect sizes for the mean group differences in CSF-NSE values were found invariably high for patients with MDD whereas no effect could be found for S100B (see Table II). For the differentiation between MDD and HC, ROC analyses for non-adjusted NSE values resulted in AUC ⫽ 0.820 (95% CI 0.718– 0.922). According to the Youden index of 0.56, an optimal cut-off of 7.94 ng/ml had highest sensitivity of 81% (95% CI 63.7– 90.8) and specificity of 75% (95% CI 57.9–86.7). NSE and S100B were found to significantly correlate in the total group (rho ⫽ 0.367, P ⫽ 0.004) and in the MDD group (rho ⫽ 0.489, P ⫽ 0.005), but missed significance in the control group (rho ⫽ 0.343, P ⫽ 0.064). NSE and S100B did not correlate significantly with age or BMI in the total group and did not differ between sexes in the total group. NSE and S100 also did not correlate with HAMD-17 scores in the MDD patients (NSE: r ⫽ 0.178, P ⫽ 0.371; S100B: rho ⫽ –0.218, P ⫽ 0.274) nor controls (NSE: r ⫽ 0.47, P ⫽ 0.800; S100B: rho ⫽ 0.79, P ⫽ 0.679). Within the MDD patients, levels of both NSE (P ⫽ 0.434) and S100B (P ⫽ 0.306) did not differ between patients with first versus recurrent depressive episodes. NSE and S100B did not correlate significantly with age at onset of MDD (NSE: r ⫽ 0.044, P ⫽ 0.828; S100B: r ⫽ 0.206, P ⫽ 0.303) nor total duration of the disorder (NSE: r ⫽ 0.093, P ⫽ 0.643; S100B: r ⫽ –0.096, P ⫽ 0.634).

Discussion In this first study on CSF-NSE and the first study combining CSF-NSE and CSF-S100B in MDD, we could demonstrate that neuronal NSE, but not glial S100B levels were significantly elevated in the MDD patients. For NSE, high effect size and reasonably high accuracy rates to distinguish MDD from

Table I. Socio-demographic and clinical characteristics.

Age, years (⫾SD) Gender, male/female BMI, kg/m2 (⫾SD) HAMD-17, sum score (⫾SD) Episode, first/recurrent Age at onset MDD, years (⫾SD) Duration of MDD, years (⫾SD) Psychotropic medication no/yes Antidepressants Mood stabilizer Neuroleptics aIndependent

MDD patients (N ⫽ 31)

Controls (N ⫽ 32)

P

49.81 (⫾ 16.50) 14/17 25.12 (⫾ 4.12) 17.86 (⫾ 8.27) 11/20 41.56 (⫾ 16.70) 8.37 (⫾ 11.41) 8/23 23 6 3

50.75 (⫾ 16.50) 18/14 27.44 (⫾ 5.76) 0.9 (⫾ 0.75) – – – 32/0 – – –

⫽ 0.881a ⫽ 0.379b ⫽ 0.113a ⬍ 0.001c NA NA NA ⬍ 0.001b NA NA NA

samples t-test, bChi2-test, cMann–Whitney U-test. BMI, Body mass index; HAMD-17, Hamilton Depression Rating Scale, 17-item version; MDD, Major depressive disorder; NA, not applicable; SD, standard deviation.

– 5.57* [1.23] 1.12 (0.77–1.48) 0.97 (0.64–1.30) 1.18 (1.14) 0.96 (0.50) *P ⫽ 0.004; SD, standard deviation; CI, confidence interval.

0.91 (0.39) 0.92 (0.34) MDD patients Controls

11.73 (9.95–13.52) 6.17 (4.55–7.78) 12.19 (5.30) 6.43 (4.10)

Group

Adjusted mean values in ng/ml (95% CI)

S100B medians in ng/ml (IQR)

Means in ng/ml (⫾SD)

Adjusted mean values in ng/ml (95% CI)

NSE Adjusted mean differences (95% CI) [effect size] MDD Figure 2. CSF-S100B in patients with major depressive disorder (MDD) and healthy subjects.

NSE means in ng/ml (⫾SD)

controls further support a neuron-based neuropathology in depressive disorders. Since neuronal loss is described for specific brain regions in MDD (Sacher et al. 2012; Schindler et al. 2012) and NSE is found nearly ubiquitous throughout the brain, elevations of NSE in the CSF may result from a release from neuronal cytoplasms following neuronal cell death, as seen for stroke or haemorrhage (Böhmer et al. 2011; Ahmad et al. 2012). In contrast, since NSE was found to have neurotrophic and neuroprotective properties, elevations could, on the other hand, display or be part of a counter-regulation against neuronal depletion,

Table II. Pairwise comparisons and effect size of CSF-NSE and CSF-S100B between MDD patients and controls.

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Figure 1. CSF-NSE in patients with major depressive disorder (MDD) and healthy subjects.

– 0.22 [0.26]

F.M. Schmidt et al. S100B Adjusted mean differences (95% CI) [effect size] MDD

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CSF-NSE and S100B in major depressive disorder 5 e.g., by accelerating glucose metabolism within the neurons (Takei et al. 1991; Hattori et al. 1995). Likewise, findings of elevated expression of NSE and NSE-mRNA in the serotonergic dorsal raphe nucleus of rats responding to chronic social stress was assumed to display a protective mechanism exerted by neurons in response to stress and antidepressant treatment (Abumaria et al. 2007). Similar to the specific relationship between neurotrophic factors, such as BDNF and NGF, and brain structures impaired in MDD patients (Frodl et al. 2008; Banerjee et al. 2013; Savitz et al. 2013; Kuhn et al. 2014), we hypothesize that changes in NSE levels in MDD are related to impaired cerebral structures involved in the pathogenesis of depression. Specifically for the amygdala, a region with grey matter reductions and impaired functional connectivity found in MDD (Sacher et al. 2012; Song et al. 2014) MRI-grey matter densities were found to relate reciprocally to serum-NSE levels in healthy subjects (Streitbürger et al. 2012). Secondly, slight decreases of NSE levels were found post mortem in the frontal cortex in MDD patients (Yuan et al., 2010). However, translational studies combining NSE-measurement and imaging in MDD patients are lacking to date. Whereas our results of no association between CSF-NSE levels and clinical variables of severity and course of the disorder do not portend a statedependency of NSE, the high effect size and accuracy rates to differentiate MDD from HC may point towards CSF-NSE as a trait marker for MDD. This would prompt further investigation of the sensitivity and specificity of NSE in distinguishing different forms of affective disorder, e.g., between melancholic and non-melancholic depressive subtypes, major depression and adjustment disorders, or uni- and bipolar depression. Concerning the literature on NSE in MDD, our results contradict a recent investigation reporting reduced levels of serum-NSE in subjects with a depressive syndrome (Wiener et al. 2013). Comparisons with our results face several limitations since: (1) CSF and serum concentrations of NSE in general are not adequately related to each other (Nygaard et al. 1998; Casmiro et al. 2005), (2) the depressed subjects included in the other study were not diagnosed clinically, but on a population-based survey, and (3) psychiatric comorbidities were not excluded. In a second study on serum levels between MDD and HC, the authors themselves suggest the low sample size as a limitation for finding missing group differences (Schroeter et al. 2008). Our finding of no significant differences in S100B between groups needs to be critically compared with

the literature. In the sole study on CSF-S100B in MDD patients which found elevated levels in a much smaller MDD sample (n ⫽ 11), statistical analyses between the groups were performed with a paired t-test (Grabe et al. 2001). In neurological patients, CSF levels negatively correlated with self-reported depressive scores, suggesting a symptom- and severitydependency of S100B levels (Uher et al. 2012). For serum, the body of literature presents high effect sizes which we could not confirm for CSF (Schroeter et al. 2008). Exploring the discrepancies between our results and the literature on serum levels, it should be considered that serum S100B does not exclusively reflect central processes, but extracerebral expression mainly comes from adipocytes, as well as chondrocytes, melanocytes, skeletal muscles and myocardium (Parker et al. 1998; Gonçalves et al. 2010). Controlled for covariates like BMI or presence of inflammation and cardiac diseases, the insulin- and adipocyte-dependency of S100B has recently been acknowledged as an important covariate when interpreting S100B in schizophrenia (Steiner et al. 2010) and should be included in further MDD studies likewise. Further, concentrations of S100B are in strong relation to the functioning of the BBB (Kanner et al. 2003). Immunological processes with cytokine release, a consistent finding for MDD, as well as S100B itself due to its central and peripheral proinflammatory properties, can affect the BBB and should also be considered as a covariate (Sen et al. 2007; Lichtblau et al. 2013; Fujiya et al. 2014; Schmidt et al. 2014). When interpreting our results, we need to consider the limitation that the majority of depressed patients had received antidepressants. An influence of medication on levels of both NSE and S100B may not fully be ruled out. Preclinical investigations suggest an increment of S100B during antidepressant therapy. In that way, the selective serotonin reuptake inhibitor fluoxetine increased the expression of S100B in mice (Akhisaroglu et al. 2003). In rats, the administration of fluoxetine reversed a decrease of hippocampal and CSF-S100B concentrations which had followed chronic mild stress (Rong et al. 2010). In another investigation, exposure to fluoxetine reduced S100B concentrations within the hippocampus, whereas, intriguingly, serotonin had antagonizing effects on S100B release (Tramontina et al. 2008). The authors suggest that other molecular targets than serotonin, such as protein kinase A, are responsible for an involvement of S100B in depression. For NSE, one study showed increased levels of NSE-mRNA and protein levels within the dorsal raphe nucleus in rats following the administration of citalopram (Abumaria et al. 2007). In human serum, however, concentrations of NSE did not change, and concentrations of S100B only decreased in a few studies

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during treatment (Schroeter et al. 2008). As suggested above (Uher et al. 2012), the authors postulate a relationship between S100B, severity of acute depression and reduction of symptoms with correlations of effect sizes of HAMD and S100B reductions, rather than an overall and course-independent effect of medication over time. Further, the heterogeneity of our sample consisting of both first and recurrent depressive episode, with variances in duration of the disorder and age at onset, may have an impact on both NSE and S100B levels. Also, the study sample was small and, even though effect size, sensitivity and specificity were high for NSE, conclusions can only be regarded as preliminary. A follow-up investigation on conditions of health or relapse into depression would give some information on intra-individual stability and state and/or trait-properties of the respective markers. A larger sample with a longitudinal follow-up design and the inclusion of other psychiatric disorders clinically more difficult to separate from depression than mentally healthy subjects are therefore recommended for future investigations. By excluding psychiatric or somatic comorbidities, we have investigated a sample free from confounder possibly impacting on CSF levels that does not fully depict conditions in clinical routine. At the same time, this selection meets the demand of reducing the possibility of associated conditions to bias our results and increases the likelihood that the NSE levels may serve as a putative diagnostic biomarker in MDD. Also, the exclusion of subjects with contraindications to lumbar puncture may have biased the composition of the MDD sample. The heterogeneity of the literature with partly contradictory results to the presented study demands further research on glial and neuronal pathophysiology in depression, potentially including combined CSF, serum, genetic and structural investigations. Lumbar puncture is a highly applicable method to exclude neurologic-somatic causes for depression and to deepen our understanding of the pathophysiology of depressive disorder. However, a critical light needs to be shed on the diagnostic value of lumbar puncture. Though sensitivity and specificity in this investigation were good for NSE, clinical investigations, rather than any potential biomarker, lead to diagnosis and therapeutic decision making within depression. Also, the adverse, sometimes severe, effects of lumbar puncture, and the time- and cost-consuming requirements before conducting the procedure, and poor applicability outside a hospital environment, need to be considered. In conclusion, in this first study on CSF-NSE in MDD, we could show that NSE levels were markedly increased in the MDD compared to controls. This

elevation may either result from neuronal cell loss or depict a counter-regulation against alterations in neuronal integrity. In contrast, missing differences in CSF-S100B in this clinically heterogeneous sample of MDD patients do not promote the hypothesis of a specific glial pathology in MDD which was previously supported by findings of elevated S100B levels in serum.

Acknowledgements None. Statement of Interest None to declare.

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Elevated levels of cerebrospinal fluid neuron-specific enolase (NSE), but not S100B in major depressive disorder.

Alterations in neuronal and glial integrity are considered to be of pathogenic impact on major depressive disorder (MDD). For MDD, data on cerebrospin...
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