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Feb 8, 2017 - There are day/night and seasonal changes in biological markers such as melatonin and cortisol. Controversial changes in serum S100B ...
Progress in Neuro-Psychopharmacology & Biological Psychiatry 75 (2017) 207–212

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Day/night changes in serum S100B protein concentrations in acute paranoid schizophrenia Armando L. Morera-Fumero a,b,⁎, Estefanía Díaz-Mesa c, Pedro Abreu-Gonzalez d, Lourdes Fernandez-Lopez a,e, Maria del Rosario Cejas-Mendez c a

Departamento de Medicina Interna, Dermatología y Psiquiatría, Facultad de Ciencias de la Salud, Universidad de la Laguna (ULL), La Laguna, Santa Cruz de Tenerife, Spain Consultoria Psiquiátrica SC, Santa Cruz de Tenerife, Spain Servicio de Psiquiatría, Hospital Universitario de Canarias, La Laguna, Santa Cruz de Tenerife, Spain d Departamento de Ciencias Médicas Básicas: Unidad de Fisiología, Facultad de Ciencias de la Salud, Universidad de la Laguna (ULL), La Laguna, Santa Cruz de Tenerife, Spain e Sociedad para la Investigación y Asistencia en Salud Mental, Santa Cruz de Tenerife, Spain b c

a r t i c l e

i n f o

Article history: Received 16 December 2016 Received in revised form 4 February 2017 Accepted 6 February 2017 Available online 8 February 2017

a b s t r a c t There are day/night and seasonal changes in biological markers such as melatonin and cortisol. Controversial changes in serum S100B protein levels have been described in schizophrenia. We aim studying whether serum S100B levels present day/night variations in schizophrenia patients and whether S100B levels are related to psychopathology. Sixty-five paranoid schizophrenic inpatients participated in the study. Psychopathology was assessed with the Positive and Negative Syndrome Scale (PANSS) at admission and discharge. Blood was drawn at 12:00 (midday) and 00:00 (midnight) hours at admission and discharge. Sixty-five healthy subjects matched by age, gender and season acted as control group. At admission and discharge patients had significantly higher serum S100B concentrations at midday and midnight than healthy subjects. At admission, patients showed a day/night variation of S100B levels, with higher S100B levels at 12:00 than at 00:00 h (143.7 ± 26.3 pg/ml vs. 96.9 ± 16.6 pg/ml). This day/night difference was not present in the control group. Midday and midnight S100B at admission decreased when compared to S100B at discharge (midday, 143.7 ± 26.3 vs. 83.0 ± 12, midnight 96.9 ± 16.6 vs. 68.6 ± 14.5). There was a positive correlation between the PANSS positive subscale and S100B concentrations at admission. This correlation was not present at discharge. Conclusions: acute paranoid schizophrenia inpatients present a day/night change of S100B serum levels at admission that disappears at discharge. The correlation between serum S100B concentrations and the PANSS positive scores at admission as well as the decrease of S100B at discharge may be interpreted as an acute biological response to the clinical state of the patients. © 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

1. Introduction Schizophrenia is a chronic mental disorder characterized by delusions, hallucinations, disorganized speech and behavior, and other symptoms that cause social or occupational dysfunction (American Psychiatric Association, 2013). The aetiology of the disease is multifactorial and still it is not clearly understood. Several aetiological hypotheses, such as the dopamine (Howes et al., 2012), glutamate (Hu et al., 2015), neurodevelopmental (Fatemi and Folsom, 2009), and viral (Crow, 1988), among others, have been proposed. Neuroinflammation is one of the latest pathophysiological factors involved in the aetiology of schizophrenia (Monji et al., 2013). ⁎ Corresponding author at: Departamento de Medicina Interna, Dermatología y Psiquiatría, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), 38071, La Laguna, Santa Cruz de Tenerife, Islas Canarias, Spain. E-mail address: [email protected] (A.L. Morera-Fumero).

Several clinical studies point to the positive clinical response to antiinflammatory drugs as adjuvant treatment in schizophrenic patients (Laan et al., 2006; Muller et al., 2010). Additionally, the anti-inflammatory properties of some antipsychotics point to the same pathophysiological ground (Kato et al., 2011). In the last two decades, the study of the S100B protein has made its own room as a peripheral marker of brain inflammation (Studahl et al., 2009), till the point that it has led to some authors to consider the S100B protein as the C-reactive protein of the brain (Sen and Belli, 2007). The utility of the S100B protein as a potential neurochemical biomarker in different neurological, psychiatric and neurosurgical disorders has recently been reviewed (Wainwright et al., 2009; Yelmo-Cruz et al., 2013). With respect to psychiatric disorders, S100B blood levels have mainly been used as a marker of mood disorders and schizophrenia (Arolt et al., 2003; Morera et al., 2009). Reports on S100B blood levels in schizophrenia patients are controversial; having been reported no differences (Hendouei et al., 2016;

http://dx.doi.org/10.1016/j.pnpbp.2017.02.007 0278-5846/© 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Uzbay et al., 2013), increased (Milleit et al., 2016; Wiesmann et al., 1999) or decreased (Gattaz et al., 2000) levels compared to controls. Two recent meta-analysis have reported that blood S100B concentrations are higher in schizophrenic patients than in healthy subjects (Aleksovska et al., 2014; Schumberg et al., 2016). Some biological variables such as melatonin, malondialdehyde, temperature and cortisol (Klerman et al., 2002; Morera and Abreu, 2007; Morera et al., 2009) among others, have been reported to have circadian and seasonal changes. Circadian rhythms of S100B blood levels have been reported as inexistent in healthy subjects (Ikeda and Umemura, 2005; Morera-Fumero et al., 2013). It is not known whether or not, patients with schizophrenia show circadian oscillations in blood S100B concentrations. On the other hand, the relationships between psychopathology and blood S100B levels are also controversial. Positive correlations (Ling et al., 2007; Rothermundt et al., 2001), negative correlations (Rothermundt et al., 2004b; Schmitt et al., 2005) or absence of correlations (Hendouei et al., 2016; Lara et al., 2001; Qi et al., 2009; Rothermundt et al., 2007; Schroeter et al., 2009; Steiner et al., 2006, 2009) between S100B levels and negative psychopathology have been previously reported. Furthermore, a positive (Schroeter et al., 2003) and an absence (Lara et al., 2001; Ling et al., 2007; Qi et al., 2009; Rothermundt et al., 2007; Schmitt et al., 2005; Schroeter et al., 2009; Steiner et al., 2006, 2009) of correlation between positive psychopathology and S100B levels have also been reported. The aims of this research are studying whether serum S100B levels have a day/night change and whether serum S100B concentrations are related to psychopathology. 2. Methods 2.1. Subjects Sixty-five Caucasian (Ben-Abdesselam et al., 2003) paranoid schizophrenic inpatients meeting DSM-IV criteria participated in the study. All patients were independently diagnosed by consensus of two experienced clinical psychiatrists based on the Structured Clinical Interview for the DSM-IV. Patients were recruited from the psychiatric ward of the Canary Islands University Hospital. They were hospitalized because of an acute psychotic relapse. A sample of 65 healthy controls, matched by age and gender, without personal and family psychiatric antecedents was recruited between the acquaintances by the researchers. Any subject with alcohol abuse/dependence, substance abuse, physical illness, pregnancy, severe trauma, taking anti-inflammatories or immunosuppressant, mental retardation and physical agitation was excluded. Physical healthiness of the control group was ascertained by a short medical history and a general laboratory test. Mental healthiness was assessed informally by asking the subjects if they had received psychiatric treatment in the past or were receiving treatment at present or if any first-degree relative was in the past or present receiving psychiatric treatment. Psychological treatment was considered as well as receiving psychiatric treatment.

of the patients in order to match the patients for the S100B seasonal change (Morera-Fumero et al., 2013). Samples were collected at 12:00 and 00:00 h in order to interfere the minimum with the hospitalization routines and because midday (light period) and midnight (dark period) represent two opposite times along of day. Subjects were in bed one hour before blood extraction in order to reduce the physical and psychological stress (Gazzolo et al., 2010). After extraction, samples were placed in vacutainer tubes without anticoagulant and allow to clot, then they were centrifuged at 3000 rpm during 5 min. After that, serum was separated, aliquoted in Eppendorf tubes and stored frozen at −70 °C until analysis. The study protocol was carried out following the Helsinki Declaration and all the subjects gave written informed consent before inclusion. The protocol was approved by the Ethics and Investigation Committee of the Canary Islands University Hospital. 2.4. Serum S100B measurements Serum S100B levels were determined with an enzyme-linked immunoassay (ELISA) kit according to the manufacturer instructions (BioVendor, Candler, USA). The BioVendor Human S100B ELISA uses a polyclonal anti-cow S100B coated in microtitration wells. The absorbance of the resulting yellow colour product was measured spectrophotometrically at 450 nm in a microplate spectrophotometer reader (Benchmark Plus, Bio-Rad, Hercules, CA, USA). In this ELISA, the lowest detection limit was 10.8 pg/ml. Coefficients of variation were 3.92% and 5.03% for intra- and inter-assay variabilities, respectively. To minimize the assay variance all serum samples were analyzed the same day with the same laboratory batch and by the same analyst. The analyst was blind at all times with respect to the samples pertaining to admission/discharge, day/night or patient/control groups. In order to know the possible effect of the typical and atypical antipsychotics on serum S100B concentrations we tried to group patients according to the treatment received. Because most patients received a combination of typical and atypical antipsychotics and there were no more than five cases in each group, all antipsychotic treatments were transformed into chlorpromazine antipsychotic equivalent doses (CAED) (Woods, 2003). 2.5. Statistical analysis Data were analyzed using the 21st version of the Statistical Package for the Social Sciences (SPSS, Chicago, Illinois, USA). Night/day and admission/discharge serum S100B differences in patients were analyzed by means of an ANOVA for repeated measures. Patient/control serum S100B differences were analyzed by an ANOVA for independent measures. Bonferroni's post hoc comparisons are carried out if ANOVA results are statistically significant. Pearson correlations were applied to study the relationships between quantitative variables while the statistic chi-square was applied to study the association between qualitative variables. All statistical tests were two-tailed. Statistical significance level was set at 0.05. Quantitative data are presented as mean ± SD.

2.2. Psychopathological assessment

3. Results

At admission and discharge, psychopathology was assessed with the Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). Two clinical psychiatrists measured the psychopathology. They had simultaneously attended a training session in the use of the PANSS. After PANSS training repeated assessments for the PANSS scores maintained an inter-rater correlation coefficient N 0.8.

3.1. Results of patients at admission and control group

2.3. Study protocol Blood samples were collected the day after admission and the day before discharge in the patients group while blood of healthy controls was collected in any day between the period of admission and discharge

Serum S100B concentrations, demographic and clinical characteristic of both samples are summarized in Table 1. Both samples are comparable by age, gender and distribution of normal/overweight-obese variables. Patients had significantly higher BMI than healthy subjects. In order to control the possible effect of BMI on S100B, BMI was added as a covariate variable in the statistical analysis. The comparison of patient and control subjects' serum S100B concentrations at 12:00 and 00:00 h was carried out through a MANCOVA test, acting BMI as covariate. The result of the MANCOVA was significant for the group of subjects (F = 4.98, p b 0.03) and time of the day that

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Table 1 Serum S100B concentrations, demographic and clinical characteristics of both samples. Quantitative variable is given as mean ± SD. NPA = number of previous admissions. CAED: chlorpromazine antipsychotic equivalent dose. Variables

Patients

Controls

P

Age (years) Gender (male/female) Body mass index Normal/overweight + obese Illness onset (years) Illness duration (years) NPA CAED (mg/day) Days of hospitalization

36.7 ± 10.2 36/29 28.3 ± 6.6 33/32 23.9 ± 7.5 12.3 ± 10.0 4.1 ± 3.3 757.7 ± 400.0 21.4 ± 10.8 Admission 19.9 ± 4.9 13.8 ± 5.1 24.1 ± 4.1 12:00 143.7 ± 210.7

39.6 ± 9.8 46/19 25.5 ± 4.1 30/35 − − − − −

0.1 0.35 0.02 0.72 − − − − −

− − − 12:00 47.3 ± 23.9

− − −

PANSS positive PANSS negative PANSS general Time S100B (ng/ml)

00:00 96.9 ± 132.7

Discharge 11.1 ± 4.1 11.1 ± 3.4 20.5 ± 3.2 12:00 83.0 ± 96.3

blood was sampled (F = 4.66, p b 0.04). BMI covariation was not significant. Post-hoc comparisons revealed that patients had significantly higher serum S100B levels at 12:00 and 00:00 h (p b 0.05, Table 1) than controls. Patients had significantly higher S100B levels at 12:00 than 00:00 h (p b 0.05, Fig. 1). Control subjects had similar S100B levels at 12:00 and 00:00 h (Fig. 1).

00:00 68.6 ± 116.4

00:00 49.0 ± 22.0



between the PANSS positive subscale and the diurnal and nocturnal S100B protein level at admission (Table 2). Furthermore, this correlation was not present at discharge. The rest of correlations did not show statistical significance. Table 3 shows that there are no significant correlations between any of the serum S100B measures and the clinical variables (age of illness onset, years of illness duration, CAED, hospitalization days and number of previous admissions).

3.2. Changes between admission and discharge 4. Discussion The comparison of the different PANSS subscales scores between admission and discharge was significant (p b 0.01). There was a significant decrease in the three PANSS subscales scores (Table 1). The comparison of serum S100B concentrations between admission and discharge at 12:00 and 00:00 h was carried out through a MANCOVA, acting BMI as covariate. The result of the MANCOVA was significant for the admission/discharge period (F = 4.68, p b 0.04) as well as for the time of the day that blood was sampled (F = 4.71, p b 0.04). BMI covariation was not significant. Post-hoc comparisons showed that serum 12:00 h S100B levels decreased significantly at admission compared to serum 12:00 h S100B levels at discharge (p b 0.05, Table 1). Serum S100B levels at 00:00 h also decreased significantly between admission and discharge (p b 0.05, Table 1). The comparison of midday and midnight S100B serum levels at discharge revealed that S100B midday levels were similar to midnight levels (p = ns) (Fig. 1), the same day/night pattern that healthy subjects had but with different absolute values. 3.3. Relations between S100B and psychopathological and clinical variables Correlations between serum S100B protein levels and the different PANSS scores elicited only two positive and significant correlations,

Fig. 1. Comparison of midday and midnight S100B in patients and healthy subjects at midday and midnight.

4.1. Patients at admission and control group To our knowledge, this is the first time that a day/night variation, with significantly higher levels at midday than midnight, of serum S100B concentration has been described in schizophrenia inpatients when admitted to hospitalization because of an acute relapse. As far as we know, there is none study in the literature that has investigated the day/night change in schizophrenia S100B protein concentrations. We have not found day/night changes in S100B concentrations in our control group. There are two studies in which serum day/night changes in S100B concentrations have been studied in healthy subjects (Ikeda and Umemura, 2005; Morera-Fumero et al., 2013). Both studies confirm that serum S100B did not show day/night changes. Our patients had higher serum S100B levels than the healthy controls at 12:00 and 00:00 h. Previous researches have been carried out sampling patients once and most investigations have reported that patients had higher S100B levels than controls (Chen et al., 2017; Hong et al., 2016; Lara et al., 2001; Milleit et al., 2016; Qi et al., 2009; Rothermundt et al., 2004a, 2007; Schmitt et al., 2005; Schroeter et al., Table 2 Correlations between S100B concentrations at admission and discharge and subscales of the Positive and Negative Syndrome Scale. r = Pearson coefficient, p = significance level.

Positive scale admission Positive scale discharge Negative scale admission Negative scale discharge General scale admission General scale discharge

r p r p r p r p r p r p

S100B 12:00 admission

S100B 00:00 admission

S100B 12:00 discharge

S100B 00:00 discharge

0.354 0.050 −0.215 0.245 0.047 0.849 −0.015 0.938 0.004 0.983 −0.102 0.578

0.462 0.009 −0.180 0.332 −0.136 0.579 −0.131 0.490 0.069 0.737 −0.118 0.521

−0.024 0.897 0.084 0.653 0.152 0.535 0.224 0.235 −0.158 0.440 −0.052 0.779

0.275 0.134 −0.152 0.414 −0.058 0.814 −0.004 0.982 0.280 0.166 0.014 0.940

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Table 3 Correlations between S100B concentrations at admission and discharge and clinical variables. r = Pearson coefficient, p = significance level. CAED: chlorpromazine antipsychotic equivalent dose. NPA: number of previous admissions.

Illness onset Illness duration CAED Hospitalization days NPA

r p r p r p r p r p

S100B12:00 admission

S100B00:00 admission

S100B12:00 discharge

S100B00:00 discharge

0.187 0.305 −0.011 0.951 0.013 0.943 0.073 0.700 −0.068 0.713

0.077 0.674 −0.124 0.499 −0.125 0.497 0.237 0.207 −0.161 0.377

0.298 0.098 −0.118 0.521 0.102 0.578 −0.272 0.146 −0.064 0.729

0.073 0.690 0.105 0.568 −0.141 0.442 0.139 0.464 −0.202 0.268

2003; Wiesmann et al., 1999; Zhang et al., 2010a, 2010b). Our admission results are confirmed by those researches. Three researches have reported different results. The paper of Gattaz et al. (2000) reported that schizophrenic patients had significantly lower S100B levels than healthy subjects while the paper of Uzbay et al. (2013) and Hendouei et al. (2016) reported no significant differences between patients and healthy controls. Two differences may explain the discrepancy of the results in the case of Gattaz et al. (2000). First, their sample were outpatients, while our sample are acutely relapsed inpatients, so we can assume that the patients of Gattaz et al. (2000) had less severe symptoms that our patients. Second, it is not mentioned in the paper if the authors controlled the stress of the patients. It is known that medical patients are subject to higher stress than healthy controls (Morera-Fumero and Gonzalez de Rivera, 1983). In the case of Uzbay et al. (2013) four differences may explain the discrepancy with our results. First, the sample of patients was ambulatory patients. Second, the control group was comprised by relatives of the patients. Third, patients sample of Uzbay et al. (2013) are older than our patients sample. Fourth, it is not known if the authors controlled the stress of the patients. In the study of Hendouei et al. (2016) the patient sample was mainly comprised by undifferentiated schizophrenia while in our case the whole sample was comprised by paranoid schizophrenia patients.

Schroeter et al. (2009) measured the S100B level at admission and approximately six weeks later at discharge. They found that S100B levels were higher at admission and discharge than the S100B level of the control group but S100B levels did not change between admission and discharge. Steiner et al. (2009) studied inpatient at admission and six weeks later after reconvalescence. They found that patients had significantly higher S100B levels than healthy subjects at admission but at week six patients had decreased significantly the S100B levels compared to admission and those levels were similar to those of the control group. Hendouei et al. (2016) did not find differences in S100B levels between patients at admission and six weeks later and control subjects. Additionally, S100B levels did not decrease significantly between admission and six weeks later despite that the clinical picture of the patients improved. In our case, patients S100B figures between admission and discharge have decreased significantly but S100B levels at discharge were still significantly higher in patients than controls. Ling et al. (2007) measured plasma S100B levels at admission and after 12 weeks of treatment. They found that at admission and after 12 weeks of treatment patients had higher levels of S100B than controls but between admission and discharge S100B had decreased significantly. Apart from the time difference between the first and second measurement (3 weeks in our study vs 12 weeks) the studies have found the same result. Rothermundt et al. (2004b) studied outpatients at basal, 12 and 24 weeks. S100B levels did not change between basal time, 12 and 24 weeks, but S100B levels were higher at the three time points than the S100B levels of the control group. In this case the authors do not find decreases in S100B levels after 24 weeks of treatment and S100B were significantly higher than the S100B levels of the control group. There are two main differences with our research. First, patients were outpatients, so we can assume with less severe symptoms than our patients. Second, patients were selected with considerable negative symptoms and our sample was comprised by acutely relapsed patients, so it possible that our sample presented more positive symptoms than the sample of Rothermundt et al. (2004b). It is known that negative symptoms are less responsive to psychopharmacological treatment than positive symptoms (Kinon et al., 2010).

4.2. Changes between admission and discharge

4.3. Relationships between S100B and psychopathology and clinical variables

S100B levels decreased significantly between admission and discharge at 12:00 and 00:00 h. The day-night change that was present at admission was not present at discharge, despite that the S100B levels had significantly decreased between admission and discharge. Clinical improvement of the patients is confirmed by the significant reduction of the PANSS scores. We have found seven longitudinal studies to which compare our morning results (Hendouei et al., 2016; Ling et al., 2007; Rothermundt et al., 2001, 2004b, Sarandol et al., 2007; Schroeter et al., 2009; Steiner et al., 2009). Five papers (Hendouei et al., 2016; Rothermundt et al., 2001, Sarandol et al., 2007; Schroeter et al., 2009; Steiner et al., 2009) studied patients at basal time and then six weeks later, one paper (Ling et al., 2007) studied the patients at basal and 12 weeks later and finally, one paper (Rothermundt et al., 2004b) studied the patients at basal, 12 and 24 weeks later. Rothermundt et al. (2001) measured serum S100B levels in schizophrenic inpatients at admission and after six weeks of treatment. They found that patients had significantly higher S100B levels than controls at admission but this difference was not present after six weeks of treatment. Sarandol et al. (2007) measured S100B in inpatients and outpatients at basal time and six weeks later. Patients had significantly higher S100B at basal time than control subjects but only patients with negative symptoms had reduced significantly the level of S100B at week six.

Another interesting result is related to the positive correlation between S100B serum concentration at midday and midnight and the PANSS positive subscale scores at admission. As far as we know, this is the first time that this finding is reported. None of the previous reports that have used the PANSS to measure psychopathology have found the same result and this is reasonable because none measured S100B at night. Two investigations found similar results to our midday results. Schroeter et al. (2003) found a positive correlation between the third BPRS subscore (thought disturbance) and the concentration of S100B at 08:00 h. Chen et al. (2017) reported a positive correlation between S100B and the PANSS positive symptom score in drug-naïve but not in drug-free patients. Rothermundt et al. (2004b) reported a positive correlation between the total PANSS score and S100B levels. The authors do not report the correlations between S100B levels and PANSS subscales, so we do not know whether the positive correlation is due to any of the PANSS subscales scores. The same group (Rothermundt et al., 2004a) reported a negative correlation between S100B levels and PANSS negative scores. The patients of this study were selected with prominent negative symptoms, so this bias may explain the results. Ling et al. (2007) reported a positive correlation of S100B plasma levels and PANSS total score at admission, but this correlation mainly existed between S100B levels and the PANSS negative subscores.

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Ling et al. (2007) heparinised blood samples before measuring S100B levels. Tort et al. (2003) have reported a significant increase of S100B plasma level when blood was treated with heparin. No correlations between S100B levels and PANSS total, positive, negative and general scores have also been reported (Hendouei et al., 2016; Pedersen et al., 2008; Qi et al., 2009; Steiner et al., 2009; Zhang et al., 2010a). Hong et al. (2016) reported a negative correlation between S100B and PANSS total score and general score with no significant correlations between S100B and the positive and negative subscales. A recent meta-regression analysis (Schumberg et al., 2016) have reported a positive correlation between S100B and PANSS total, positive and general scores but not with the negative scores. The most plausible explanation for such range of different results may be the differences in methodologies. Our results point to an independence between serum S100B concentrations and illness duration, age of illness onset, CAED, hospitalization days and number of previous admissions. Illness duration and age of illness onset have been reported not to be related to S100B levels (Chen et al., 2017; Gattaz et al., 2000; Qi et al., 2009; Rothermundt et al., 2001; Sarandol et al., 2007; Schroeter et al., 2003; Schroeter et al., 2009; Schumberg et al., 2016; Steiner et al., 2006; Wiesmann et al., 1999). Our results point to the same direction. One paper reported a negative correlation between illness duration and S100B levels (Lara et al., 2001) while the meta-regression analysis of Schumberg et al. (2016) found a positive correlation between S100B concentrations and illness duration. We did not study individual antipsychotics, because we would need at least five subjects in each cell to make comparisons, that is the reason why all antipsychotic treatments were converted into CAED. We did not find correlations between S100B concentrations and CAED. Two recent meta-analysis did not find differences in S100B concentrations between medicated and non-medicated patients (Aleksovska et al., 2014; Schumberg et al., 2016). We did not find relationships between serum S100B levels and hospitalization days and number of previous admissions. Several papers have reported an absence of relation between S100B concentrations and the number of episodes that patients had suffered (Gattaz et al., 2000; Qi et al., 2009; Schroeter et al., 2003; Schroeter et al., 2009). Zhang et al. (2010b) did not find correlation between S100B levels and length of hospitalization as we have found.

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4.5. Limitations and strengths Our research has some limitations. First, the number of patients is not big enough. One of the disadvantages of studying circadian rhythms in humans is that it requires taking several biological measures (Morera-Fumero and Abreu-Gonzalez, 2013) and because of the clinical characteristics of the patients (acutely relapsed) and the setting (hospitalized), this is a difficult task to perform. Second, the effect of individual antipsychotics was not analyzed because of the number of subjects that were treated with one antipsychotic was small; this is the reason why we converted all antipsychotic doses into CAED. Third, we do not include drug-free patients because of the difficulty of recruiting such patients and for ethical reasons. Four, our S100B data on patients must be considered preliminary, because replication studies are necessary to confirm that acute paranoid schizophrenic patients present a day/ night change when acutely relapsed. Fifth, more long-term studies are needed because despite that after three weeks of treatment S100B levels decreased significantly, serum S100B levels still were significantly increased compared to the S100B levels of healthy subjects. On the other hand, our research also has some strengths worth pointing out. First, the sample of patients studied at admission and discharge is comprised by the same group of subjects, so the interindividual variability is low. Second, despite the relatively short period of time that patients were hospitalized, they have a good clinical improvement. 4.6. Conclusions Acute paranoid schizophrenia inpatients present a day/night change of S100B serum levels at admission. This change is absent at discharge. The positive correlation between serum S100B concentrations and the PANSS positive scores at admission as well as the significant decrease of S100B levels at discharge taken together with the presence at admission and the absence at discharge of a day/night change may be interpreted as an acute biological response to the clinical state of the patients. Funding This study has been partly financed by a research grant (PI: 08/115) of the Fundación Canaria de Investigacion y Salud (FUNCIS) of the local government of the Canary Islands.

4.4. Recommendations In our opinion, some of the controversial results that are reported by the different investigations stem from the diversity of methodological strategies. In order to improve homogeneity, we would like to make the following recommendations. First, avoid the use of heparin as anticoagulant, when collecting blood samples, serum should be the biological fluid in which S100B blood concentrations should be measured. If this is not possible for clinical reasons, use EDTA that not interfere with S100B levels (Tort et al., 2003). The use of anticoagulants should always be reported. Second, in order to avoid the dispersion of psychopathological measures, PANSS, BPRS, SANS, SAPS, one scale of measure should be used. Third, the race/ethnicity is an important variable that affects S100B concentrations (BenAbdesselam et al., 2003), so, reporting of race/ethnicity should be considered. Fourth, because studying circadian rhythms in humans is a difficult task, it would be advisable that at least three time points should be measured: 09:00, 12:00, and 24:00 h (Morera-Fumero and Abreu-Gonzalez, 2013). Fifth, there is a seasonal effect on serum S100B concentrations in healthy subjects (Morera-Fumero et al., 2013). Until now, it is not known if this seasonal pattern is present in patients, so the recommendation is to match the control group for season. Sixth, when possible use quantitative analytical techniques and avoid qualitative analytical techniques.

Role of funding source The funding agencies had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; and preparation, review, or approval of the manuscript. Contributors: Dr. EDM and Dr. ALMF conceived the idea and methodology for the research. Dr. EDM, Dr. LFL and Dr. MRCM recruited the subjects and were involved in clinical and diagnostic assessments as well as the samples collections. Dr. PAG did the analytical procedures and Dr. MRCM conducted the statistical analysis. Dr. PAG, Dr. ALMF and Dr. LFL wrote the first draft. All authors contributed to the writing of the manuscript and approved the final version. Conflict of interest None. Acknowledgements We would like to thank to Dr. Aram Morera-Mesa (freelance translator) for his assistance in the translation of this article.

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