• Users Online: 616
  • Print this page
  • Email this page

Table of Contents
Year : 2021  |  Volume : 35  |  Issue : 3  |  Page : 140-144

Isobaric tags for relative and absolute quantitation in identifying proteins for clozapine treatment response in patients with schizophrenia: A preliminary study

1 Departments of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
2 Department of Chemistry, National Sun Yat-Sen University, Kaohsiung, Taiwan
3 Departments of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine; Department of Medical Research, Genomic and Proteomic Core Laboratory, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan

Date of Submission21-Apr-2021
Date of Decision06-May-2021
Date of Acceptance08-May-2021
Date of Web Publication24-Sep-2021

Correspondence Address:
Tiao- Lai Huang
123, Ta-Pei Road, Niao-Sung District, Kaohsiung 833
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/TPSY.TPSY_27_21

Rights and Permissions

Objective: Schizophrenia is a mental disorder characterized by reduced social engagement, abnormal emotional expression, and a lack of motivation. Isobaric tags for relative and absolute quantitation (iTRAQ) are a novel proteomic technique. In this study, we intended to identify potential biomarkers for predicting clozapine treatment response using iTRAQ. Methods: We identified patients with schizophrenia that responded to a four-week treatment with clozapine. Patient's peripheral blood mononuclear cells (PBMC) were collected before and after treatment. iTRAQ-based proteomics analysis was done to identify differentially expressed proteins in PBMC before and after treatment. STRING analysis map was built, and a target protein was selected. Western blot validation was then done. Results: In 10 identified clozapine treatment-responsive patients, we screened 2,735 proteins. Nine downregulated proteins and 11 upregulated proteins were differentially expressed by 1.5-fold after clozapine treatment. STRING network analysis revealed a series of apolipoproteins, and only apolipoprotein A4 (APOA-IV) was selected for validation. Western blot validations showed that protein levels of APOA-IV were significantly most downregulated in the patient after clozapine treatment (p = 0.05). Conclusion: In this study, we integrated clinical observation data, bioinformational protein interaction analysis, and iTRAQ labeling to study proteomics in patients with schizophrenia successfully treated with clozapine. We suggest that APOA-IV protein can be a biomarker for predicting clozapine treatment response in patients with schizophrenia. But these results in this study need a larger sample size to be validated.

Keywords: apolipoprotein A-IV, biomarker, iTRAQ labeling, protein-protein interaction analysis

How to cite this article:
Lin CC, Su H, Shiea J, Huang TL. Isobaric tags for relative and absolute quantitation in identifying proteins for clozapine treatment response in patients with schizophrenia: A preliminary study. Taiwan J Psychiatry 2021;35:140-4

How to cite this URL:
Lin CC, Su H, Shiea J, Huang TL. Isobaric tags for relative and absolute quantitation in identifying proteins for clozapine treatment response in patients with schizophrenia: A preliminary study. Taiwan J Psychiatry [serial online] 2021 [cited 2022 Jun 27];35:140-4. Available from: http://www.e-tjp.org/text.asp?2021/35/3/140/326577

  Introduction Top

At present, the global population of patients with schizophrenia is 1% of the world [1], but the disease is a chronic disease requiring long-term medical treatment. Schizophrenia is a chronic disease that causes the affected patients unable to concentrate on work and to increase social and economic costs [2]. Patients with schizophrenia have some psychiatric symptoms, such as delusions and hallucinations. In addition, they have negative symptoms such as decreased social ability, slow speech, and low mood [3]. If these psychiatric symptoms persist, the patients will have cognitive decline and loss of living ability. Inevitably, patients with schizophrenia will cause an increase in social and economic costs, which is also a serious problem for future social security problems.

Two-dimensional gel electrophoresis (2-DE) is the most common analytic technique used in proteomics research. But this technique is time-consuming, usually requiring a relatively large amount of samples. When proteins have extreme molecular mass or isoelectric points, 2-DE has difficulties separating proteins. Isobaric tags for relative and absolute quantitation (iTRAQ) are an isobaric labeling and mass spectrometry-based method for quantitative biomarkers study [4]. In a study by Wang et al.'s group, iTRAQ labeling was used to quickly identify 472 proteins, of which 154 have been found to differ in control and depression in human serum [5]. In another study [6], Ren et al. have used iTRAQ labeling to identify plasma biomarkers for distinguishing bipolar depression from major depressive disorder. Therefore, iTRAQ is a fast technic and is widely screened for differences in clinical samples.

In this study, we intended to use iTRAQ labeling to find the biomarker in potential treatment response-associated protein in patients with schizophrenia after they were successfully treated with clozapine. We also used bioinformational protein–protein interaction analysis and Western blot validation for checking the study results.

  Methods Top


The patients were recruited from a tertiary medical center over two years. Their age was between 20 and 65 years old, and they had no systemic diseases such as diabetes, hypertension, and hyperthyroidism. They also had no smoking or alcohol addiction. All study participants could sign the informed consent, after the investigators thoroughly explained the details of the study. The diagnosis of schizophrenia was established by the same senior psychiatrist, according to the diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Patients were free of antipsychotic drugs or other medications for at least one month before entering the study. The severity of schizophrenia was assessed using positive and negative syndrome scale (PANSS) [7],[8]. All patients received a course of a four-week clozapine treatment. Treatment response was defined by the reduced PANSS score being greater than 50%. We also collected patients' peripheral blood mononuclear cells (PBMC) in the morning, after their six-hour fasting, before and after four weeks of clozapine treatment. We analyzed only those patients who showed treatment response [9],[10],[11]. The institutional review board (IRB) of Chang Gung Memorial Hospital approved the study design (protocol number = IRB 201601169B0, date of approval = October 11, 2016; IRB 201601169B0C101, and date of approval = October 06, 2017) with the need to obtain signed informed consent from the patients.

Isobaric tags for relative and absolute quantification (iTRAQ) labeling

Before labeling, we quantified the protein and mix in six groups of samples before and after treatment. Briefly, we took out the pooled sample the protein (100 μg) in each reduced sample, blocked on cysteine, alkylation, and subsequently digested with trypsin overnight at 37°C before the iTRAQ tag.

Peptide fractionation

After mixing the samples, peptides labeled with different channels of iTRAQ and desalted using a Sep-Pak C18 column (Waters). The peptides were vacuum dryer, and dissolution in 0.5% trifluoroacetic acid, and subsequently fractionated by high pH conditions reverse phase C18 under (Pierce High pH Reversed-Phase Peptide Fractionation Kit, Thermo Fisher Scientific, Waltham, Massachusetts, USA). The mixed peptides were eluted in a 1% ammonia solution containing different concentrations of acetonitrile (5-50%) to obtain 10 fractions. Each eluted fraction was vacuum and redissolved in 0.1% formic acid solution for liquid chromatography, tandem mass spectrometry (LC-MS / MS) analysis.

Tandem mass spectrometry-based protein identification

Tandem mass spectrometry analysis was performed on Q ExactiveTM HF mass spectrometer (Thermo Fisher Scientific, San Jose, California, USA) in combination with a Thermo ScientificTM UltiMateTM 3000 RSLCnano HPLC system. The peptide mixtures were directly loaded onto a 50-cm analytic column (EASY-Spray™ C18 Column), and separated by a gradient with gradually increased of buffer B (80% acetonitrile in 0.1% formic acid) at a flow rate of 250 nL/min over about 165 minutes. We obtained the peptide profile in positive ion mode with data acquisition. The top 15 rich precursor ions were dynamically selected for further fragmentation in the 375-1,400 m/z scan range in high-collision dissociation (HCD) mode, where the normalized collision energy was set to 33 ± 1. In a full MS scan, the resolution is 60,000 m/z, the AGC target is 3e6, and the maximum injection time is 50 ms. In the MS/MS scan, the resolution is 15,000, the AGC target is 5e4, and the maximum injection time is 100 ms. The release of dynamic exclusion of the selected precursor ions was set to 20 seconds.

MS-based proteomics data analysis by proteome discoverer software and Mascot search engine

The MS raw file was uploaded to Proteome Discoverer (version 2.1, Thermo Scientific, Waltham, Massachusetts, USA) and the Swiss-Prot Human Protein Data Library Mascot Search Algorithm (version 2.5, Matrix Science Inc., Boston, Massachusetts, USA). For protein identification, the following parameteres were used for database search: carbamidomethylation at Cys as the fixed modification, oxidation at Met, acetylation at protein N-terminus, iTRAQ-labeled at peptide N-terminus and K residue as dynamic modifications, maximum missing cleavage sites with 2, 10 ppm for MS tolerance, and 0.02 Da for MS/MS tolerance. Peptide and protein identification with a false discovery rate of less than 1% can be accepted. We increased confidence and considered using at least two unique peptides for protein identification and quantification.

Western blotting

PBMC samples were used to quantify the proteins. The proteins were denatured at 95°C for 10 min. Samples were loaded of 20 μg protein in each lane with 10% sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS-PAGE) gels. Running was SDS-PAGE, subsequently transferred to PVDF membranes. After blocking in 2% BSA in PBST for 1 hr at room temperature, the PVDF membrane was incubated for 10 h at 4°C with the following primary antibodies: Human/Mouse Apolipoprotein A-IV/ApoA4 Antibody (APOA-IV) (1: 1000; R & D) and anticytochrome C oxidase antibody (COX IV) (1: 1,000; cell signaling). After washes 5 min of three time with PBST, the membrane was incubated with antigoat or antirabbit secondary antibody (1: 10,000) at room temperature for 1 h, and then the membrane was washed 5 min of five times with PBST. The relative intensity of each protein was calculated with ImageJ software (National Institutes of Health, Bethesda, Maryland, USA).

Statistical analysis

We described the study data as mean ± standard deviation. Paired t-test was used to compare the protein changes in Western blot validation.

Data analysis was done using Statistical Package for the Social Science software version 19 (SPSS, Inc., Chicago, Illinois, USA). The differences between the groups were considered significant if p-values were smaller than 0.05.

  Results Top

PBMC analysis by iTRAQ-based quantitative proteomics

Ten clozapine treatment-responsive patients were identified [Table 1]. A total of 2,735 proteins were screened. Nine downregulated proteins and 11 upregulated proteins were differentially expressed by 1.5-fold after clozapine treatment [Table 2]. Using bioinformational protein–protein interaction analysis, the differentially expressed proteins were analyzed and protein interaction networks were established by STRING. From the protein-protein interaction network, a series of apolipoproteins containing apolipoprotein A4 (APOA-IV), apolipoprotein C2, apolipoprotein C3, and apolipoprotein C4 were identified [Figure 1].
Table 1: Demographic data of clozapine-responsive patients

Click here to view
Table 2: Differential proteins found in isobaric tags for relative and absolute quantitation

Click here to view
Figure 1: The differentially expressed proteins in STRING analysis. Apoa4, apolipoprotein A-IV; Apoc2, apolipoprotein C-II; Apoc3, apolipoprotein C-III; Apoc4, apolipoprotein C-IV.

Click here to view

Western blotting validation for differential proteins

Western blot validations showed that protein levels of APOA-IV in peripheral blood mononuclear cells (PBMCs) samples were mostly downregulated in patient after clozapine treatment [Figure 2] and [Figure 3], although no significance was found (p = 0.05).
Figure 2: Western blot validations of APOA-IV in clozapine-responsive patients with schizophrenia APOA-IV, apolipoprotein A-IV; COX-IV, cytochrome C oxidase subunit 4.

Click here to view
Figure 3: APOA-IV expression intensities quantified with ImageJ software.

Click here to view

  Discussion Top

In this study, we found that APOA-IV protein could be a biomarker for predicting clozapine treatment response in patients with schizophrenia, using an investigative method combining iTRAQ labeling and bioinformational protein–protein interaction analysis. Western blot validation showed that in most patients, decreased expressions of APOA-IV protein were found after successful clozapine treatment, though no statistical significance was found. Using bioinformational protein–protein interaction analysis, a series of apolipoproteins were identified [Figure 1]. Those apolipoproteins are mainly proteins that bind lipids such as fat and cholesterol to form lipoproteins, and apolipoprotein can also act as an enzyme cofactor for specific enzymes involved in lipoprotein metabolism [12],[13]. Many of those apolipoprotein genes are located on the same gene cluster of chromosome 11q23 [14]. Whether individual differences result in increased post-treatment performance or are affected by SNP sites on the APOA-IV gene [15]. Numerous studies at home and abroad have found that polymorphisms in the APOA-IV gene are associated with levels of blood glucose, plasma lipoproteins, cholesterol, and triglycerides [16]. Defects in the APOA-IV gene directly lead to decreased activity of APOA-IV in plasma, resulting in elevated lipoproteins and cholesterol, which greatly increases the risk of hyperlipoproteinemia and coronary heart disease [17]. In addition, studies have found that Alzheimer's disease is associated with APOA-IV, in which patients with lower performance are lower than normal [18].

Patients with schizophrenia treated with antipsychotic drugs have high metabolic rate and metabolic syndrome-related drugs such as clozapine and olanzapine [19]. Antipsychotic drugs can induce dyslipidemia and metabolic problems, finally leading to induced myocarditis [20], increased cardiovascular mortality rate, and premature death in patients with schizophrenia [21]. Although clozapine is the best choice for patients with schizophrenia, the drug has the worst metabolic characteristics. In addition, various cardiovascular diseases can induce dyslipidemia and cause high cholesterol and obesity [22]. In our clinical observation data, schizophrenia after treatment with clozapine almost gained weight after clozapine treatment. Those results are consistent with our proteomic data. In the literature survey, it is found that schizophrenia may be caused by an inflammatory reaction, and the concentration of APOA-IV in the blood increases when inflammation occurs, which in turn causes inflammation. After treatment with antipsychotic drugs (clozapine), the concentration of APOA-IV in PBMCs decreased and the inhibition of inflammatory reaction reached an effective therapeutic effect. It is speculated that the clozapine treatment pathway may achieve effective treatment by reducing the performance of APOA-IV. But the decrease in APOA-IV level may lead to a decrease in antioxidant capacity and an increase in the risk of atherosclerosis. However, since antipsychotic drugs need to be taken for a long time without interruption, the risk of concurrent diseases may increase. Therefore, while clozapine could keep psychosis in check, it inevitably reduces APOA-IV levels, which triggers other metabolic risks. Perhaps regulating the level of APOA-IV can prevent the occurences of metabloic complications. Our preliminary findings required further investigations to verify the results.

Study limitations

The readers are warned against overinterpretation of our study results because this study has three limitations:

  • The sample size was relatively small.
  • iTRAQ showed 1.608-fold increase of APOA-IV expression, but statistical significance on margin was found in the Western blot validation, probably also due to small sample size.
  • The study sample was focused on clozapine-responsive patients only. If we could have used the data with patients who were resistant to clozapine treatment as a comparative group, we would strengthen the study results.


In this study, we integrated clinical observation data, bioinformational protein interaction analysis, and iTRAQ labeling to study proteomics in patients with schizophrenia successfully treated with clozapine. We suggest that APOA-IV protein can be a biomarker for predicting clozapine treatment response in patients with schizophrenia.

  Financial Support and Sponsorship Top

This work was supported by the clinical research grants CMRPG8F1461, CMRPG8F1462, CMRPG8H0231, CMRPG8I0301, CMRPG8H0232, and CMRPG8J1511 from Kaohsiung Chang Gung Memorial Hospital in Taiwan, as well as MOST 107-2314-B-182A-130, MOST 107-2314-B-182A-123, and MOST 108-2314-B-182A-072 from Ministry of Science and Technology of Taiwan. The mass spectrometry-based proteomics analysis was done through the Clinical Proteomics Core Laboratory of Chang Gung Memorial Hospital at Linkou, Taiwan.

  Conflicts of Interest Top

Tiao-Lai Huang, a member of domestic advisory board at the Taiwanese Journal of Psychiatry, had no rôle in the peer review process or decision to publish this article.

  References Top

Saha S, Chant D, Welham J, et al.: A systematic review of the prevalence of schizophrenia. PLoS Med 2005; 2: e141.  Back to cited text no. 1
Knapp M, Mangalore R, Simon J: The global costs of schizophrenia. Schizophr Bull 2004; 30: 279-93.  Back to cited text no. 2
Strauss JS, Carpenter WT Jr, Bartko JJ: The diagnosis and understanding of schizophrenia. part III. speculations on the processes that underlie schizophrenic symptoms and signs. Schizophr Bull 1974; 11: 61-9.   Back to cited text no. 3
Moulder R, Bhosale SD, Goodlett DR, et al.: Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling. Mass Spectrom Rev 2018; 37: 583-606.  Back to cited text no. 4
Wang Q, Su X, Jiang X, et al.: iTRAQ technology-based identification of human peripheral serum proteins associated with depression. Neuroscience 2016; 330: 291-325.  Back to cited text no. 5
Ren J, Zhao G, Sun X, et al.: Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis. Psychoneuroendocrinology 2017; 86: 17-24.  Back to cited text no. 6
Kay SR, Fiszbein A, Opler LA: The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull 1987; 13: 261-76.  Back to cited text no. 7
Kay SR, Opler LA, Lindenmayer JP: Reliability and validity of the positive and negative syndrome scale for schizophrenics. Psychiatry Res 1988; 23: 99-110.  Back to cited text no. 8
Beck AT, Kovacs M, Weissman A: Assessment of suicidal intention: the Scale for Suicide Ideation. J Consult Clin Psychol 1979; 47: 343-52.  Back to cited text no. 9
Butler AM, Malone K: Attempted suicide v. non-suicidal self-injury: behaviour, syndrome or diagnosis? Br J Psychiatry 2013; 202: 324-5.  Back to cited text no. 10
Kageyama Y, Kasahara T, Morishita H, et al.: Search for plasma biomarkers in drug-free patients with bipolar disorder and schizophrenia using metabolome analysis. Psychiatry Clin Neurosci 2017; 71: 115-23.  Back to cited text no. 11
Ramasamy I: Recent advances in physiological lipoprotein metabolism. Clin Chem Lab Med 2014; 52: 1695-727.  Back to cited text no. 12
Wang F, Kohan AB, Lo CM, et al.: Apolipoprotein A-IV: a protein intimately involved in metabolism. J Lipid Res 2015; 56: 1403-18.  Back to cited text no. 13
Karathanasis SK: Apolipoprotein multigene family: tandem organization of human apolipoprotein AI, CIII, and AIV genes. Proc Natl Acad Sci U S A 1985; 82: 6374-8.  Back to cited text no. 14
Lamina C, Friedel S, Coassin S, et al.: A genome-wide association meta-analysis on apolipoprotein A-IV concentrations. Hum Mol Genet 2016; 25: 3635-46.  Back to cited text no. 15
Herron KL, Lofgren IE, Adiconis X, et al.: Associations between plasma lipid parameters and APOC3 and APOA4 genotypes in a healthy population are independent of dietary cholesterol intake. Atherosclerosis 2006; 184: 113-20.  Back to cited text no. 16
VerHague MA, Cheng D, Weinberg RB, et al.: Apolipoprotein A-IV expression in mouse liver enhances triglyceride secretion and reduces hepatic lipid content by promoting very low density lipoprotein particle expansion. Arterioscler Thromb Vasc Biol 2013; 33: 2501-8.  Back to cited text no. 17
Lin Q, Cao Y, Gao J: Decreased expression of the APOA1-APOC3-APOA4 gene cluster is associated with risk of Alzheimer's disease. Drug Des Devel Ther 2015; 9: 5421-31.  Back to cited text no. 18
Kristof E, Doan-Xuan QM, Sarvari AK, et al.: Clozapine modifies the differentiation program of human adipocytes inducing browning. Transl Psychiatry 2016; 6: e963.  Back to cited text no. 19
Otsuka Y, Idemoto K, Hosoda Y, et al.: Clozapine-induced myocarditis: follow-up for 3.5 years after successful retrial. J Gen Fam Med 2019; 20: 114-7.  Back to cited text no. 20
Blanco Mejia S, Kendall CW, Viguiliouk E, et al.: Effect of tree nuts on metabolic syndrome criteria: a systematic review and meta-analysis of randomised controlled trials. BMJ Open 2014; 4: e004660.  Back to cited text no. 21
McNamara RK, Jandacek R, Rider T, et al.: Atypical antipsychotic medications increase postprandial triglyceride and glucose levels in male rats: relationship with stearoyl-CoA desaturase activity. Schizophr Res 2011; 129: 66-73.  Back to cited text no. 22


  [Figure 1], [Figure 2], [Figure 3]

  [Table 1], [Table 2]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
   Financial Suppor...
   Conflicts of Int...
   Article Figures
   Article Tables

 Article Access Statistics
    PDF Downloaded110    
    Comments [Add]    

Recommend this journal