Association between trace elements in serum from bipolar disorder and schizophrenia patients considering treatment effects

Journal Pre-proof Association between trace elements in serum from bipolar disorder and schizophrenia patients considering treatment effects Elisa C. Santa Cruz, Katherine C. Madrid, Marco A.Z. Arruda, Alessandra Sussulini

PII:

S0946-672X(19)30689-3

DOI:

https://doi.org/10.1016/j.jtemb.2020.126467

Reference:

JTEMB 126467

To appear in:

Journal of Trace Elements in Medicine and Biology

Received Date:

30 October 2019

Revised Date:

3 January 2020

Accepted Date:

10 January 2020

Please cite this article as: Santa Cruz EC, Madrid KC, Arruda MAZ, Sussulini A, Association between trace elements in serum from bipolar disorder and schizophrenia patients considering treatment effects, Journal of Trace Elements in Medicine and Biology (2020), doi: https://doi.org/10.1016/j.jtemb.2020.126467

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Association between trace elements in serum from bipolar disorder and schizophrenia patients considering treatment effects

Elisa C. Santa Cruz1, Katherine C. Madrid2, Marco A. Z. Arruda2,3, Alessandra Sussulini1,3*

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Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of

P.O. Box 6154, 13083-970, Campinas, SP, Brazil 2

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Analytical Chemistry, Institute of Chemistry, University of Campinas (UNICAMP),

Spectrometry, Sample Preparation and Mechanization Group (GEPAM),

Department of Analytical Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), P.O. Box 6154, 13083-970, Campinas, SP, Brazil

National Institute of Science and Technology for Bioanalytics – INCTBio,

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13083-970, Campinas, SP, Brazil

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* Corresponding author

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Institute of Chemistry, University of Campinas (UNICAMP), P.O. Box 6154,

E-mail: [email protected]

Highlights

Elemental determination in blood serum from schizophrenia (SCZ) and

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Phone: +55 19 35213060

bipolar disorder (BD) patients. Lowest Se concentration determined for BD patients treated with Li.

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Lower Zn concentrations for SCZ and BD patients against healthy controls.

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Higher Fe concentrations in SCZ and BD not treated with Li patients against healthy controls.

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Copper: zinc ratio was significantly enhanced in SCZ patients compared to healthy individuals.

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Abstract

BACKGROUND: Imbalances in metal concentrations have been suggested to contribute to the pathophysiology of different brain disorders, such as bipolar disorder (BD) and schizophrenia (SCZ). OBJECTIVES: The aim of this exploratory study is to evaluate the association between the concentrations of macro/trace elements in serum from BD and SCZ patients considering the effects from different treatments. METHODS: Eleven subjects with SCZ, seven with BD treated with lithium (BDL)

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and eight subjects with BD treated with other medications except lithium (BDN) were recruited for the study, as well as eleven healthy controls (HC). Serum

concentrations of eleven macro/trace elements (Se, Zn, Fe, K, Ca, Mg, P, Al, Cu, Mn, and Ni) were determined using inductively coupled plasma mass spectrometry (ICP-MS).

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RESULTS: Se and Zn concentrations were significantly lower for patients with

SCZ and BD in comparison to HC by one-way ANOVA test. Moreover, serum 1)

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concentrations for Fe were significantly higher (p < 0.05) in BDN (548 ± 92 μg Land SCZ (632 ± 279 μg L-1) in comparison to HC (421 ± 121 μg L-1). A significant

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negative correlation was reported between Se and Fe in BDL group (r = -0.935, p < 0.05). In addition, a significantly higher Cu/Zn ratio was determined in SCZ group against HC (ratio = 2.4, p = 0.028).

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CONCLUSIONS: The obtained results suggest that the imbalance in Fe concentrations is an effect of BD treatment. Lithium is supposed to have an antagonist effect for Se in BDL patients. A negative correlation reported between

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Fe and BMI in SCZ group could be related to antipsychotic treatment and the Cu/Zn ratio reported could be considered as a suggesting parameter to relate

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oxidative stress to SCZ. Future studies including larger number of patients with SCZ and BD before and after treatment are necessary to confirm the investigative results presented herein.

Keywords: bipolar disorder; schizophrenia; ICP-MS; iron; selenium; zinc.

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1. Introduction

Bipolar disorder (BD) and schizophrenia (SCZ) are mental illnesses that affect approximately 1 % of the worldwide population and can be a burden to society in both social and economic aspects [1, 2]. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), these diseases are separately classified in diagnostic systems. Nevertheless, there is evidence for shared genetic factors and several medications are commonly used in the treatment of both disorders, especially atypical antipsychotics [3]. This drug class

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is particularly studied for SCZ patients and side effects, such as weight gain and glucose dysregulation, are reported [4].

Essential elements are indispensable for the appropriate functioning of

living organisms and are thus classified for being required for specific biochemical

functions. An insufficiency in these metals may result in alterations in cognition,

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immune function and development [5]. Imbalances in metal levels have been

suggested to contribute to the pathophysiology of different brain disorders [6, 7],

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including BD and SCZ [8, 9]. Five micro-trace nutrients in particular, Cu, Fe, Zn, Al, and Mg, have been studied for a variety of mental disorders, particularly SCZ

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[10]. Nevertheless, other elements such as Se, Ni, P, and Mn have not been previously or deeply investigated.

In the present study, the focus is the analysis of blood serum samples from

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healthy controls and treated BD and SCZ patients by determining Se, Zn, Fe, K, Ca, Mg, P, Al, Cu, Mn, and Ni using ICP-MS, in order to measure the alterations in their concentrations and point out differences between the disorders. The set

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of macro/trace elements was selected based on previous studies related with BD and SCZ [8, 9], [11-14]. The results herein presented are expected to

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complement metabolomics and proteomics data, thus offering a complete potential biomarker panel that can be employed for the diagnosis of these disorders in the future. To the best of our knowledge, this is the first study that compares the concentration of multiple elements in these two psychiatric disorders with healthy individuals and contemplates treatment effects.

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2. Material and methods

2.1. Study subjects Clinical diagnoses for both disorders, bipolar disorder (BD) and schizophrenia (SCZ), fulfilled the DSM-IV criteria, according to the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I). Euthymia was defined as not satisfying the criteria for any current mood episode and presenting, at the same time, Young Mania Rating Scale (YMRS) and 17-items Hamilton Depression Rating Scale (HDRS-17) scores below 8. Only patients who used

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lithium for at least 6 months were included in bipolar disorder treated with lithium

(BDL) group. The studied cohort consisted of 37 serum samples: healthy controls (n = 11), patients diagnosed with schizophrenia (n = 11), and bipolar disorder patients treated with lithium (n = 7) and with other medications except lithium (n

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= 8). Blood samples were collected at the Hospital das Clínicas (University of Campinas, Brazil). Controls were individuals without any known psychiatric

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disorder. All subjects have no diabetes, kidney failure, or other diseases. The study protocol was reviewed and approved by the Ethics Committee of the

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University of Campinas (protocol 775/2010). The study subjects were informed about the purpose of the study and written consent was obtained from each of

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them.

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2.2. Samples collection and storage

Blood was drawn into vacutainer tubes, immediately placed on ice, allowed to clot for at least 30 min, and centrifuged at 3500 g for 15 min at 4 °C. The

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obtained serum was aliquoted, transferred into polypropylene tubes containing 0.01 % (m/v) sodium azide, and stored at -80 °C until assayed. As presented in Table 1, patients were under medications such as valproate, carbamazepine, and lithium as mood stabilizers, venlafaxine and sertraline as antidepressants, olanzapine, quetiapine, aripiprazole, risperidone and clozapine as antipsychotics, and clonazepam as anxiolytic.

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2.3. Instrumentation and multi-elemental analysis

An inductively coupled plasma quadrupole mass spectrometer ICP-MS 2030 (Shimadzu, Japan), a DGT100 Plus microwave oven (Provecto Analitica, Brazil), and a certified reference solution of yttrium (89Y) as internal standard were employed in this study. Ultrapure water (18.2 MΩ cm resistivity) obtained from a Milli-Q Advanced A 10 purification system (Millipore, USA) was used for the preparation of all aqueous solutions for the experiments. Sample preparation and operational ICP-MS conditions were selected

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from the adaptation of a methodology previously developed by our group [11]. Optimization was achieved using spiked serum pool of control samples and

calculated recovery percentages of the different analytes, as presented in Supplemental Table 1. For quantification, two calibration curves were prepared,

each one composed by 7 points shown in Supplemental Table 2. The first

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calibration curve, which contained a mixture of Al, Cu, Fe, Zn, Mn, Ni, Se and Mg, was used for the quantification of samples after decomposition. The other curve

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(containing P, Ca and K) was used for the quantification of samples diluted 20 times. Each point used the respective 1000 μg L -1 standard solution. Serum

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samples were decomposed using a closed vessel DGT100 Plus microwave oven in a 1.8 mL cryogenic tubes system. 125 µL of sub-boiled distilled HNO3 and 84 µL of H2O2 (Merck) were added to 40 µL of serum. After 15 min of reaction at

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room temperature, the following program was applied: (1) 60 s at 300 W, (2) 120 s at 500 W, (3) 120 s at 800 W, and (4) 60 s at 500 W. Additionally, 10 µg L-1 of a yttrium (89Y) solution was added before decomposition as internal standard.

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After decomposition, samples were diluted to 2.0 mL with Milli Q purified water. Each sample was treated in triplicate and five technical replicates were

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measured. For K, P, and Ca quantification, samples were diluted 20 times. All ICP-MS parameters are presented in Table 2. For ICP-MS analysis, a broad m/z range was selected to cover the highest number of elements possible for the quantitative multi-elemental analysis. Limits of detection (LOD) and limits of quantification (LOQ) were calculated as: LOD = (3*SD)/m and LOQ = (10*SD)/m, where SD is the standard deviation of independent measurements of a blank sample and “m” is the slope of the calibration curve.

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2.4. Statistical analysis

The acquired data were normalized with respect to the internal standard peak intensity. Data were analysed using univariate statistic tools such as Welch’s t-test and one-way analysis of variance – ANOVA. Before correlation analysis, normalization to sample median and autoscaling was performed. Finally, Pearson’s correlation was used to calculate the correlation coefficient of macro/trace elements levels between the disorders and healthy control groups. All results were evaluated using a confidence level of 95 % and a statistical

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significance of p < 0.05.

3. Results

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3.1. Determination of macro/trace elements in serum samples

Table 3 presents the obtained mean and standard deviation (SD) for the

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determined concentrations of the 37 analyzed samples of BD and SCZ patients and HC.

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Trace elements such as Al, Ni, and Mn were not considered further because the concentrations were below the LOQ (data not shown).

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3.2. Statistical analysis

According to Table 4, one-way ANOVA indicated two elements were

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statistically different amongst the four groups and p-values from Welch’s t-test between combinations of two groups. The first two elements, Se and Zn,

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presented the lowest p-values by ANOVA. Another element that presented pvalue < 0.05 was Fe, when comparing SCZ and BDN groups against HC group. Figure 1 presents the box plot of these differential elements for a visual representation of their determined concentrations in the studied groups. In Figure 1.a, BDL, BDN and SCZ groups presented differentially lower Se concentrations than HC and, considering the patient groups, Se concentration was lower for BDL than BDN and SCZ, although there is no statistical differentiation between SCZ and BDN. In Figure 1.b, it is observed that the concentration of Zn in BDL, BDN 6

and SCZ groups are lower than in HC, but did not present statistical differentiation amongst them. Finally, in Figure 1.c, Fe shows higher concentrations for BDN and SCZ groups when comparing with HC group. Serum Cu was elevated in BDN and SCZ groups compared with the HC group; however, the difference was not statistically significant. Macro elements such as K, P, Mg, and Ca were not discriminative in the statistical analysis since they showed similar concentrations between patients and healthy individuals (Supplemental Figure 1).

3.3. Correlation of serum macro/trace element concentrations between

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patients and controls Pearson’s correlation analyses were performed to determine the

correlation of macro/trace element concentrations between patients and healthy individuals. Besides, the body mass index (BMI) of the participants was included

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as a variable. For better understanding, BDL and SCZ groups were plotted together for comparison, since BDN and HC groups presented higher similarity

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between them. Therefore, Figure 2 presents elemental concentration correlations between BDL and SCZ groups. For BDL group, all the variables

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except Fe presented positive correlation with each other and a significant negative correlation was observed between Se and Fe (r = -0.935). Whereas for SCZ group all the variables (except Cu) exhibited positive correlations with each

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other. Furthermore, a significant negative correlation was determined between Fe and Cu (r = -0.745). Figure 3 displays variable correlations between BDN and HC groups. Most of the variables (except Cu) were positively correlated with each

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other for both of the disorders. A significant negative correlation was only found between Fe and Cu in HC (r = -0.830) and BDN (r = -0.786) groups. Detailed

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results of these analyses are described in Supplemental Tables 3 and 4. Correlations related with BMI will be discussed in the following section.

4. Discussion and Conclusion

In the literature, there is no consensus regarding altered Fe, Cu and Zn concentrations in serum for recently diagnosed SCZ patients compared with HC. However, there is evidence that lower serum Se concentrations are found in SCZ 7

patients against HC [9, 15], regardless of the antipsychotic treatment [12, 13]. Since our results showed lower concentrations of Se for the treated SCZ than HC group, we support that the SCZ medication does not affect significantly Se concentration in serum. Nevertheless, antipsychotic treatment possibly has effects on pathways that involve Cu, since the concentration of this metal in our study did not differ between patients and healthy individuals, independently of the imbalance before treatment. Kaya et al. reported a trace element study comparing SCZ patients under treatment against HC and determined higher serum levels of Fe, Cu, Mg, and Al

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and lower levels of Zn and Mn [16]. These results were confirmed in the present study for Fe and Zn, but other trace elements could not be compared because

either the determined concentration was below the LOQ or the patients used a different type of medication.

In a previous study of our group, plasma samples were used to compare

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element levels in SCZ patients before and after antipsychotic treatment [11] and

Fe was reported in higher levels after six weeks of treatment. Even though the

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latter is a study using plasma samples, according to our findings, an increase of serum Fe levels in treated SCZ patients is also significant in this blood fraction.

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In another study, there are elements such as Se and Zn that presented no significant difference and higher levels of Cu in plasma were determined for treated SCZ patients versus HC [17]. Comparing these results to our findings

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(Figure 1), we may deduce that the choice of the blood fraction is relevant for the determination of these elements, since divergent results were obtained. For untreated BD patients in comparison with HC, elevated serum

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concentrations of K, P, Cu, Al, and Mn and lower Fe and Zn concentrations were reported [18]. Considering that our study involved treated BD patients, the

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medication might be associated with pathways that involve K, P, Cu, Al, and Mn, because their concentrations were not statistically different to the ones determined in the HC group. There is also evidence for lower serum Zn concentration for treated BD patients in depression phase compared to healthy volunteers [19, 20]. In our study, we determined decreased Zn concentrations for treated BD patients in comparison to HC and increased Fe concentrations. We can hypothesize that the treatment without Li somehow affected pathways related to Fe, since its concentration was increased for BDN patients. Moreover, 8

treatment with or without Li did not affect Zn serum levels since its concentration remains lower than for HC after treatment. In a previous study of our group, elevated serum levels for Fe, K, Mg, Se, and Zn for BD patients, treated with Li and other medication except Li, against HC were reported [8]. In the current study, we confirmed higher Fe concentrations in both groups of treated BD patients than HC and thus we can conclude that the medication is involved in the increase on Fe concentration. An explanation about the divergent responses for the other elements could be related to the combination of medications, including the patients treated with Li.

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The association between Se and BD has been less explored than Se and SCZ, as described before. However, for BD patients treated with Li, we reported

the lowest serum Se levels between the two groups of BD patients and this could mean that Li somehow has an antagonist effect with Se, since a significant

difference was found between BD treatments for this trace element. We have no

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extra information about studies correlating BD and low Se concentration in serum.

be interesting to confirm our results.

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A further study comparing HC with BD patients before and after treatment would

The main functions of Fe in biology are associated with its cofactor role in

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several proteins, such as oxygen transport and cellular metabolism. Commonly, Fe concentration increases with aging in different parts of the brain. Oxidative stress can play a part in a wide range of neuropsychiatric disorders, including

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SCZ and BD [21]. Moreover, there is evidence that higher levels of Fe in neurodegenerative diseases may lead to an increase in the oxidative stress due to its action with H2O2 in the Fenton reaction, which increases the production of

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·OH in the brain [22, 23]. Therefore, the higher serum Fe concentrations reported in BDN and SCZ groups might be associated with oxidative stress.

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Selenium is a component for a number of selenoproteins. In particular,

glutathione peroxidase (GPx), which has essential enzymatic functions including protection from oxidative stress and inflammation [24, 25]. Thereby, since the obtained results revealed that BD and SCZ groups have a deficiency in Se, we may relate them with a decrease of antioxidant levels, thus oxidative stress processes may be related to these disorders. A deficiency of this trace element has been involved in a variety of illnesses, such as renal disease and obesity and, as a neuromodulator role in brain, related with depression [26]. Evidence 9

reveals that Se intake in SCZ patients elevates Cu and Zn serum levels [27], which presented increasing of appetite and memory capability. Zinc deficiency is characterized by growth retardation, loss of appetite, and impaired immune function. When Zn deficiency does occur, it is usually due to insufficient Zn intake or absorption, augmented losses of Zn from the body, or increased requirements for Zn [28]. Zinc deficit can lead to various conditions, including psychiatric disturbances such as depression and anxiety [29]. Therefore, the reduction in the concentration of this trace element in our study may indicate that patients are prone to have these disturbances. Furthermore, it

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is known that Zn acts as a cofactor involved in the antioxidant defence system and has a protective role against oxidative stress in diseases, such as diabetes and chronic kidney disease [30-32]. In contrast to our findings, the low level of

this element may imply that BD and SCZ patients are undergoing oxidative stress processes in spite of the treatment.

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Copper has a role in a wide number of bodily physiological processes, such as myocardial contractility, myelination of the central nervous system,

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cholesterol and glucose metabolism, hormone synthesis, and immune function [33]. Additionally, it is also related with the etiology of mental disorders [34]. Even

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though the increased serum Cu concentration was not significant in SCZ patients, there is evidence which pinpoints a prejudicial effect of elevated levels of Cu in SCZ patients by magnifying or maintaining dopaminergic dysregulation [35].

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Trace element ratio Cu/Zn has been used as an index related to imbalance inflammation and oxidative stress in the development or progression of the disease activities [36-38]. Among the free radicals produced during oxidative

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stress, reactive oxygen species (ROS) and reactive nitrogen species (RNS) are the most related in psychiatric disorders such as SCZ and BD [39, 40].

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Guo et al. presented in a study a positive correlation between superoxide

dismutase (SOD) enzyme activity and Cu/Zn ratio [37]. SOD is one of the antioxidant enzymes that protects the cell mitigating the harmful effects of ROS. For the correct activation of this enzyme, Cu has to work together with Zn, and it is actually the ratio of these elements, rather than the absolute amount of Cu or Zn by oneself, which helps the enzyme function properly [41]. Therefore, we determined serum Cu/Zn ratios for each condition. Table 5 shows that Cu/Zn ratio is significantly higher in SCZ than HC group with p-value < 0.05 and no 10

significant differentiation between SCZ and BD groups (complete results in Supplemental Table 5). Even though the differentiation between BDL and SCZ did not shown statistical significance in this study, a greater number of subjects could disclose whether the differentiation is significant or not. Kunz et al. determined higher levels of SOD in treated SCZ patients against HC, whereas no significant difference was found when comparing control with euthymic BD patients [42]. Furthermore, Hendouei et al. reported increased SOD activity in patients treated with clozapine compared with those treated with other antipsychotics [43]. Altogether, our SCZ group were under antipsychotic

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treatment, mostly with clozapine, and with the literature mentioned, there is a positive correlation between Cu/Zn ratio and SOD. This imbalance may occur as a result of a protective and adapted mechanism development during the

treatment, and/or may be an indication of the elevated generation of ROS in SCZ patients. Hence, Cu/Zn ratio may be considered as a biomarker of oxidative

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stress. However, it is of interest to perform the evaluation of SOD and these two

elements in a further assay in order to validate the correlation. The present study

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has its limitations and does not allow us to conclude a direct association between the impaired Cu and Zn concentrations and the presence of oxidative stress in

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SCZ.

Besides the importance in evaluating the homeostasis of the elements, body mass index (BMI) may also indicate some correlations with metals [44, 45].

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Then, BMI was evaluated in such context, exhibiting positive correlation for all elements, except for Fe in SCZ and BDL groups (Figure 2), whereas for HC and BDN, presented positive correlation for all elements except for Cu. In view of

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evidence of weight gain after antipsychotic treatment [4], such as clozapine and olanzapine [46], and SCZ group has significant elevated BMI (p-value = 0.036,

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compared with HC group, Table 1). Thus, we can relate the negative correlation of Fe with antipsychotic treatment in SCZ. On the other hand, it is easy to notice in Figure 2 and Figure 3 the same

element correlation behavior among HC, BDN, and SCZ groups, although lower for the latter. However, in comparison with the other groups, BDL seems to display the inverse correlations in Cu and Fe, which might be due to Li effect in the combined treatment.

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The incorporation of mineral supplementation in the treatment might be good practice to counteract Zn and Se insufficiencies in both disorder groups, since a positive income for Se intake in SCZ patients has been reported [27]. However, we should emphasize that this is a supposition, given the limitations of the current study, which include the relatively small number of samples from local subjects and hence it does not allow us to generalize the results to the entire population. To the best of our knowledge, this is the first study that compares the concentration of multiple elements in these two psychiatric disorders with healthy

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individuals and, besides, considers treatment effects. The evaluation of patients with BD and SCZ, phenotypically different disorders, was performed in order to

explore potential elemental biomarkers for each disorder, which would be helpful to improve their diagnosis. Since there is evidence for shared genetic factors for

BD and SCZ, finding differential markers enhance the understanding of the

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pathophysiological mechanisms of both disorders and lead to advances in

translational research with the discovery of new trans-diagnostic treatments and

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drug discovery [47]. In summary, our results suggest that serum Fe, Zn, and Se concentrations are affected in treated patients diagnosed with BD and SCZ

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compared against HC. The obtained results suggest that higher serum Fe concentration is an effect of treatment for BDN group and might be associated with oxidative stress for BDN and SCZ groups. It was not possible to conclude

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whether the low concentration of Se is an effect of treatment or due to oxidative stress. However, it seems that Li has an antagonist effect to Se, as exhibited in BDL group. The lower concentration of Zn in BD and SCZ patients might denote

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an undergoing oxidative stress in spite of the treatment. Only BDL patients reported a significant negative correlation between Se and Fe. Furthermore, the

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negative correlation reported between Fe and BMI in SCZ group could be related to antipsychotic treatment. The switch of correlation patterns for Cu and Fe within BDL group, compared with the others, might be due to Li effect of the combined treatment. Moreover, we demonstrated for the first time the Cu/Zn ratio for two psychiatric disorders, which a significantly higher ratio was found in SCZ group against HC (ratio = 2.40, p = 0.028). Together with the association with ROS, it could be considered as a suggesting parameter for oxidative stress. Future

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studies including a larger number of patients with SCZ and BD before and after treatment are necessary to confirm these exploratory results.

Conflicts of interest

The authors declare that there are no conflicts of interest.

Funding

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This work was supported by the São Paulo Research Foundation (FAPESP, grant number 2018/01525-3), National Council for Scientific and

Technological Development (CNPq) and INCT of Bioanalytics (FAPESP 2014/50867-3 and CNPq 465389/2014-7 grant numbers).

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Acknowledgements

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The authors thank Claudio E. M. Banzato and Luiz F. A. Lima e Silva and other medical staff from Hospital das Clínicas for the supervised screening and

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for technical support.

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information of study participants. Luana Ferreira da Costa is also acknowledged

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Figure Caption

Figure 1. Box plot for serum metal concentration levels (mean ± SD; n = 37) and p-value from Welch’s t-test among the four groups in pairs: (a) selenium, (b) zinc, and (c) iron concentrations. BDL: Bipolar disorder patients treated with lithium, BDN: Bipolar disorder patients treated with other medications except lithium, HC: Healthy controls, SCZ: Schizophrenia patients.

Figure 2. Pearson's correlations of macro/trace element concentrations between

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SCZ and BDL groups. The lower-left corner represents the correlations of elements in SCZ group and the upper-right corner represents the correlations in BDL group.

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Figure 3. Pearson's correlations of macro/trace element concentrations between HC and BDN groups. The lower-left corner represents the correlations of elements in HC group and the upper-right corner represents the correlations in BDN group.

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Table 1. Characteristics of subjects included in the study

Parameter Age (years); mean (SD)

BDL 30 (9.5)

BDN 31 (11.0)

SCZ 33.7 (7.9)

HC 35.9 (7.0)

Gender F/M; n (%)

4/3 (57/43)

6/2 (75/25)

3/8 (27/73)

7/4 (64/36)

BMI; kg/m2; mean (SD)

43.1 (8.9)

41 (5.0)

50 (12.0)

41.8 (4.6)

28.6

25.0

18.2

9.1

Anticonvulsants

2 (28.6)

5 (62.5)

1 (9.1)

--

Mood stabilizers

7 (100)

--

--

--

Anxiolytic

1 (14.3)

--

2 (18.2)

--

Antipsychotics

6 (85.7)

5 (62.5)

--

--

Smoker, %

Antidepressants

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Treatment; n (%)

9 (81.8)

--

3 (27.3)

--

BMI: Body mass index, BDL: Bipolar disorder patients treated with lithium, BDN: Bipolar disorder patients treated with other medication except lithium, SCZ: Schizophrenia

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patients, HC: Healthy control.

Table 2. Instrumental parameters used in multi-elemental profile evaluation in serum samples by ICP-MS

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Plasma Conditions

Radio Frequency power (kW)

Values 1.2 5

Plasma Gas (L min-1)

8

Auxiliary Gas (L min-1)

1.1

Carrier Gas (L min-1)

0.7

Mixed Gas (L min-1)

0

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Sampling Depth (mm)

Cell Conditions

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Collision Gas

Cell Gas (mL min-1)

He 6

Cell Voltage (V)

-21

Energy Filter (V)

7

26

Table 3. Determined concentrations (µg L-1) for macro and trace elements in 37 human serum samples: BDL (n = 7), BDN (n = 8), HC (n = 11), and SCZ (n = 11)

Fe

66

Zn

24

Mg*

78

Se

39

K*

31

P*

44

Ca*

SCZ

Mean

893

1032

897

1089

SD

106

332

212

338

Mean

700

548

421

632

SD

396

92

121

279

Mean

516

497

589

488

SD

58

34

50

88

Mean

14.0

13.6

13.3

14.3

SD

2.7

1.4

1.6

2.6

Mean

22.1

32.2

37.6

31.8

SD

4.0

5.9

5.5

3.1

Mean

198

176

170

186

SD

30

18

28

15

Mean

112

109

115

118

SD

19

15

17

16

Mean

95

98

95

98

SD

32

23

13

19

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56

HC

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Cu

BDN

re

63

BDL

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*Concentration in µg mL-1, BDL: Bipolar disorder patients treated with lithium, BDN: Bipolar disorder patients treated with other medications

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except lithium, HC: Healthy control, SCZ: Schizophrenia patients.

27

Table 4. Statistical analysis by one-way ANOVA and Welch’s t-test p-value

p-value

p-value

p-value

p-value

p-value

BDL – BDN

HC – BDL

HC – SCZ

BDN – SCZ

HC – BDN

BDL – SCZ

ANOVA

Se

3.2E-03*

5.2E-06*

4.3E-03*

0.860

0.056

2.2E-05*

2.0E-06*

Zn

0.442

0.010*

3.0E-03*

0.785

2.2E-04*

0.464

2.7E-03*

K

0.106

0.056

0.101

0.219

0.556

0.266

0.080

Fe

0.344

0.054

0.037*

0.448

0.019*

0.695

0.120

Cu

0.339

0.963

0.132

0.730

0.306

0.177

0.329

P

0.744

0.748

0.663

0.222

0.470

0.464

0.695

Mg

0.734

0.536

0.312

0.505

0.713

0.815

0.754

Ca

0.815

0.999

0.566

0.966

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p-value

Element

0.681

0.749

0.963

* p-value < 0.05, BDL: Bipolar disorder patients treated with lithium, BDN: Bipolar disorder patients treated

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with other medications except lithium, HC: Healthy control, SCZ: Schizophrenia patients.

Table 5. Cu/Zn ratios among BDL, SCZ and HC groups Cu/Zn

re

p-value

p-value

p-value

HC

SCZ

HC-SCZ

BDL-SCZ

HC-BDL

mean

1.76

1.65

2.40

0.028*

0.084

0.669

SD

0.32

0.43

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BDL

0.68

* p-value < 0.05, SD: Standard deviation; BDL: Bipolar disorder patients

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treated with lithium; HC: Healthy control; SCZ: Schizophrenia patients.

28