Next Article in Journal
Increased Levels of Plasma Alzheimer’s Disease Biomarkers and Their Associations with Brain Structural Changes and Carotid Intima-Media Thickness in Cognitively Normal Obstructive Sleep Apnea Patients
Next Article in Special Issue
MiRNAs in Lung Cancer: Diagnostic, Prognostic, and Therapeutic Potential
Previous Article in Journal
Genomic Breakpoints’ Characterization of a Large CHEK2 Duplication in an Italian Family with Hereditary Breast Cancer
Previous Article in Special Issue
The Profile of MicroRNA Expression in Bone Marrow in Non-Hodgkin’s Lymphomas
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diagnostics
Volume 12
Issue 7
10.3390/diagnostics12071521
diagnostics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genes of the Glutamatergic System and Tardive Dyskinesia in Patients with Schizophrenia

by
Olga Yu. Fedorenko
1,
Diana Z. Paderina
1,
Elena G. Kornetova
1,2,
Evgeniya G. Poltavskaya
1,
Ivan V. Pozhidaev
1,
Anastasiia A. Goncharova
1,
Maxim B. Freidin
3,4,
Anna V. Bocharova
3,
Nikolay A. Bokhan
1,2,
Anton J. M. Loonen
5,* and
Svetlana A. Ivanova
1,2
1
Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634014 Tomsk, Russia
2
Department of Psychiatry, Addictology and Psychotherapy, Siberian State Medical University, 634050 Tomsk, Russia
3
Research Institute of Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia
4
School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK
5
Unit of PharmacoTherapy, Epidemiology & Economics, Groningen Research Institute of Pharmacy, University of Groningen, 9713 AV Groningen, The Netherlands
*
Author to whom correspondence should be addressed.
Diagnostics 2022, 12(7), 1521; https://doi.org/10.3390/diagnostics12071521
Submission received: 26 May 2022 / Revised: 16 June 2022 / Accepted: 20 June 2022 / Published: 22 June 2022
(This article belongs to the Special Issue MicroRNA in Diagnosis and Prognosis)
Versions Notes

Abstract

:
Background: Tardive dyskinesia (TD) is an extrapyramidal side effect of the long-term use of antipsychotics. In the present study, the role of glutamatergic system genes in the pathogenesis of total TD, as well as two phenotypic forms, orofacial TD and limb-truncal TD, was studied. Methods: A set of 46 SNPs of the glutamatergic system genes (GRIN2A, GRIN2B, GRIK4, GRM3, GRM7, GRM8, SLC1A2, SLC1A3, SLC17A7) was studied in a population of 704 Caucasian patients with schizophrenia. Genotyping was performed using the MassARRAY Analyzer 4 (Agena Bioscience™). Logistic regression analysis was performed to test for the association of TD with the SNPs while adjusting for confounders. Results: No statistically significant associations between the SNPs and TD were found after adjusting for multiple testing. Since three SNPs of the SLC1A2 gene demonstrated nominally significant associations, we carried out a haplotype analysis for these SNPs. This analysis identified a risk haplotype for TD comprising CAT alleles of the SLC1A2 gene SNPs rs1042113, rs10768121, and rs12361171. Nominally significant associations were identified for SLC1A3 rs2229894 and orofacial TD, as well as for GRIN2A rs7192557 and limb-truncal TD. Conclusions: Genes encoding for mGlu3, EAAT2, and EAAT1 may be involved in the development of TD in schizophrenia patients.

1. Introduction

Schizophrenia is one of the most severe polymorphic mental disorders and is characterized by positive and negative symptoms, as well as behavioral and cognitive impairments [1,2,3]. According to a systematic review of 129 individual data sources, the global age-standardized point prevalence of schizophrenia in 2016 was estimated to be 0.28% (95% uncertainty interval (UI): 0.24–0.31) [4]. The main components of the genesis of schizophrenia are a combination of genetic predisposition factors and exposure to adverse environmental factors [5]. Schizophrenia is a highly polygenic disorder with a complex array of risk loci [6,7,8].
The treatment of schizophrenia still relies primarily on patients having to use antipsychotics. However, due to long-term treatment with typical and atypical antipsychotics, various adverse events may occur, such as neuroendocrine, metabolic, and extrapyramidal side effects [9,10,11,12]. Tardive dyskinesia is a severe motor side effect of antipsychotic drugs characterized by involuntary rapid muscle contractions and athetoid movements of the trunk, limbs, and orofacial muscles [13,14,15]. The exact mechanism of TD is still unknown, but we previously presented evidence that it could be related to the impairment of the GABAergic medium spiny projection neurons (MSNs) of the indirect extrapyramidal pathway [16]. In the establishment of this damage, oxidative stress, due to intracellular excess dopamine (due to a dopamine D2 receptor blockade) and glutamatergic excitotoxicity, may play a mechanistic role [16]. In addition to dopamine receptors, serotonin receptors can also be associated with the occurrence of TD [17]. Already in one of the first studies of our group, we found evidence that different genetic factors contribute to the development of orofacial/classical TD in comparison to limb-truncal/peripheral dyskinesia [18]. This may be related to the fact that orofacial movements are associated with phylogenetically older brain structures than those of the limbs [19,20]. Motor side effects of antipsychotic therapy remain understudied despite their prevalence [21].
Glutamate is the major excitatory amino acid neurotransmitter in the mammalian central nervous system [22]. It plays an important role in numerous physiological functions, including learning and memory, sensory perception, the development of synaptic plasticity, motor control, respiration, and the regulation of cardiovascular function. Glutamate realizes its action through two types of glutamate receptors; ionotropic receptors mediate fast synaptic transmission and metabotropic G-protein coupled receptors mediate slow synaptic transmission [23]. Both types of receptors are associated with the development of TD [24]. However, the possible association between the genetic variants of the genes encoding (parts of) these receptors were studied almost exclusively for the NR2A and NR2B subunits of the ionotropic glutamate N-methyl-D-aspartate (NMDA) receptor [19].
Ionotropic glutamate receptors can be divided into three families, of which several subtypes exist: α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), kainate, and N-methyl-D-aspartate (NMDA) receptors [25,26,27]. These subunits form tetramers with each other, which act as ion channels that depolarize the membrane. Thus, the NMDA ion channels are also permeable to Ca2+ ions and therefore capable of the long-term potentiation of synaptic excitation.
The tetrameric NMDA receptor is composed of subunits, which exist in different forms: GluN1 (product of GRIN1), GluN2 (GRIN2A, GRIN2B, GRIN2C, and GRIN2D), and GluN3 (GRIN3A and GRIN3B) [25,26,27]. Most NMDA receptors consist of two GluN1 subunits (to which glycine can bind) and two GluN2 subunits (to which glutamate can). GRIN2A is located on chromosome 16p13.2 and codes for a polypeptide of 1464 amino acid residues, GluN2A (also called NR2A) [25]. GRIN2B is located on chromosome 12p12 and codes for a polypeptide of 1484 amino acid residues, GluN2B or NR2B [25]. These genes have been investigated for possible involvement in the pathophysiology of TD in patients with schizophrenia, but the results of the studies are inconsistent [28,29,30].
The kainate receptor is also composed of four peptide molecules, of which a total of five different variants exist, named GluK1 (or GRIK1) to GluK5 (or GRIK5). The GRIK4 gene encoding the protein product KA1, 956 amino acid residues in size, is located on chromosome 11q22.3. To our knowledge, the possible existence of an association of genetic variants of this gene was investigated for the pathophysiology of schizophrenia [31] but not for TD.
The metabotropic glutamate (mGlu) receptors include eight different G-protein coupled receptors, which are divided into three groups based on the homology of their amino acid sequences: Group I (mGluR1 and mGluR5), Group II (mGluR2 and mGluR3), and Group III (mGluR4, mGluR6, mGluR7, and mGluR8) [32,33]. mGluR3, mGluR7, and mGluR8 are linked to a Gi/o protein for signal transducing. The GRM3, GRM7, and GRM8 genes encoding the metabotropic glutamate receptors mGluR3, mGluR7, and mGluR8, respectively, are located on chromosomes 7q21.11-q21.12, 3p26.1, and 7q31.33-q32.1, respectively. They have been studied for a possible association with schizophrenia [34,35,36], but we found no pharmacogenetic studies on the possible role of these genes in the development of extrapyramidal side effects [19].
To function as a neurotransmitter, glutamate must be removed from the synaptic cleft after its release by (re)uptake by surrounding neurons and glia cells and then stored in presynaptic storage vesicles or metabolized. The former is done by excitatory amino acid transporters (EAATs), of which 5 variant polypeptides exist in humans in the range of 500–600 amino acid residues; EAAT1 to EAAT5 [37,38]. The SLC1A2 gene is localized on chromosome 11p13 and encodes for the brain’s main glutamate transporter; the excitatory amino acid transporter 2 (EAAT2). Recently, an association of a genetic variant of this gene with schizophrenia was found [39], and a relationship between EAAT2 functioning and schizophrenia and mood disorders was also previously suggested [40]. The SLC1A3 encodes for EAAT1 and is localized in chromosome 5p13.2. Mutations of this gene are thought to be responsible for the development of certain forms of episodic ataxias [41,42]. Three subtypes of the vesicular glutamate transporter exist of approximately 600 amino acid residues in size (VGLUTs 1, 2, and 3) [38]. The SLC17A7 gene on chromosome 19q13.33 encodes the VGLUT1 protein, which, in humans, consists of 560 amino acids [43]. VGLUT1 is mainly expressed by glutamatergic terminals in the cerebral cortex, hippocampus, and basolateral amygdala [44].
The present study aimed to investigate the role of polymorphic variants of the genes for ionotropic receptors (GRIN2A, GRIN2B, GRIK4), metabotropic receptors (GRM3, GRM7, GRM8), and glutamate transporters (SLC1A2, SLC1A3, SLC17A7) in the development of tardive dyskinesia and its subtypes in patients with schizophrenia.

2. Materials and Methods

2.1. Patients

The study was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki 1975, as revised in Fortaleza, Brazil, 2013). The protocol of this study was submitted to and approved by the Bioethics Committee of the Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Sciences (protocol No. 142, approved on 14 May 2021). The study group consisted of a total of 944 patients with schizophrenia treated at the clinics of the Mental Health Research Institute of the Tomsk National Research Medical Center, the Tomsk Clinical Psychiatric Hospital, and the Kemerovo Regional Clinical Psychiatric Hospital. Informed consent was obtained from all subjects involved in the study.
The inclusion criteria for the study were a verified clinical diagnosis of schizophrenia in accordance with the International Classification of Diseases, 10th revision (ICD-10) criteria [45], age 18–65 years, the absence of organic, certain neurological, and severe somatic pathology, and the presence of a signed informed consent form for the study. The examined patients are residents of the Siberian Region, of White clinical appearance, and not related by blood to each other.
The exclusion criteria included the presence of pharmacological withdrawal symptoms, as well as comorbid neurological, organic, and somatic diseases that would make it difficult to objectively assess the clinical condition due to the underlying disease.
The patients studied had been taking antipsychotic treatment with typical and/or atypical antipsychotics for a long time. In the study, chlorpromazine equivalent (CPZeq) was used to standardize the dose, efficacy, and side effects of antipsychotics [46]. To determine the presence and severity of dyskinesia, patients were examined with the Abnormal Involuntary Movement Scale (AIMS) [13,14,15,47].

2.2. Genetic Analysis

Antecubital venous blood for research was taken into BD Vacutainer tubes with EDTA anticoagulant. DNA extraction was carried out by the standard phenol-chloroform method. DNA concentration measurements were performed on a Thermo Scientific NanoDrop 8000 UV–Vis Spectrophotometer.
Genotyping of 46 single nucleotide polymorphisms of the genes of the glutamatergic system was performed: GRIN2A (rs11644461, rs11646587, rs11866328, rs7190619, rs7192557, rs7196095, rs7206256, rs9788936, rs9989388, rs1345423, rs4782039, rs8057394), GRIN2B (rs10772715, rs10845838, rs12300851, rs12827536, rs1805481, rs220599, rs2300242, rs7313149, rs2192970, rs890), GRIK4 (rs1954787), GRM3 (rs1468412, rs2237562, rs6465084, rs2299225), GRM7 (rs1396409, rs3749380, rs12491620, rs1450099, rs17031835), GRM8 (rs2237748, rs2299472), SLC1A2 (rs1042113, rs10768121, rs12361171, rs3829280, rs10742338, rs11033046, rs12294045, rs3088168, rs3812778, rs7936950, SLC1A3 (rs2229894), and SLC17A7 (rs62126236). SNPs that were mentioned in the previous genetic studies mentioned in the introduction and had a minor allele frequency (MAF) of >5% were studied. The basic information on these SNPs is described in Table 1.
Genotyping was performed on a mass spectrometer MassARRAY® Analyzer 4 (Agena Bioscience™, San Diego, CA, USA) using the set Consumables iPLEX Gold 96 on The Core Facility “Medical Genomics” base, Tomsk NRMC.

2.3. Statistical Analysis

Statistical analysis was performed in the R 4.0.4 software environment using basic functions and the “haplo.stats” package. The Hardy–Weinberg equilibrium (HWE) of genotypic frequencies was tested using the χ2 test. Logistic regression was applied to test the association between tardive dyskinesia and genetic variants (additive model) while correcting for age and sex. Bonferroni correction was applied after calculating the number of independent tests, following the approach described by Li and Li [48] and after excluding the SNPs that were different from the HWE. Associations were considered statistically significant at p < 0.05 after correction for multiple testing.

3. Results

A total of 944 patients (435 females and 509 males) receiving long-term antipsychotic therapy were examined. Table 2 presents the main demographic and clinical parameters of the studied patient groups.
Tardive dyskinesia was diagnosed in 229 patients (24.3%). The median age of patients with tardive dyskinesia was statistically significantly higher than in the comparison group (p < 0.001). As not unexpected in relation to this, the duration of illness was also longer in the group of patients with tardive dyskinesia (p < 0.001).
Out of the total group of 944 patients with schizophrenia, we genotyped a smaller representative sample of 704 patients (Table 3).
An analysis of the allelic variants of the studied genes showed that the observed distribution of the genotype frequencies corresponded to that expected at the Hardy–Weinberg equilibrium. The exceptions were two polymorphic variants, SLC1A2 rs10742338 and GRM3 rs6465084, which were excluded from the following statistical analysis.
A total of 33 independent SNPs were estimated following the procedure described in [48]. Thus, for the analysis of associations, the significance level after Bonferroni correction was set as 0.05/33 = 0.0015.
No statistically significant associations between the SNPs and TD were found after adjusting for multiple testing (Table 4).
It has been noted that three SNPs of the SLC1A2 gene demonstrated nominally significant associations; therefore, we carried out haplotype analysis for these SNPs. This analysis identified a risk haplotype for TD comprising the CAT alleles of the SLC1A2 gene SNPs rs1042113, rs10768121, and rs12361171 (Table 5).
The same statistical analysis was also performed on subgroups of patients with various phenotypic forms of tardive dyskinesia: orofacial and limb-truncal. Nominally significant associations were identified for rs2229894 of SLC1A3 and orofacial TD (β = −0.4566 ± 0.1855, p = 0.0138) as well as for rs7192557 of GRIN2A and limb-truncal TD (β = 0.4385 ± 0.1958, p = 0.0251).

4. Discussion

In this article, we present the results of a study on the possible association of 44 polymorphisms of genes involved in glutamatergic neurotransmission with the prevalence of classical, peripheral, and total tardive dyskinesia in 704 out of 944 patients with schizophrenia from clinics in Western Siberia in the Russian Federation. For six SNPs (GRM3 rs2237562 and rs1468412; SLC1A2 rs1042113, rs10768121, and rs12361171; and SLC1A3 rs2229894), we found a nominally significant association with TD, but none of them survived Bonferroni correction for multiple testing. Haplotype analysis for SCL1A2 rs1042113, rs10768121, and rs12361171 identified a risk haplotype for TD comprising CAT alleles. In addition, logistic regression analysis revealed nominally significant associations for SLC1A3 rs2229894 and orofacial TD, as well as for GRIN2A rs7192557 and limb-truncal TD.
Glutamate is the main excitatory neurotransmitter of the central nervous system, and its neurons are widely distributed in the brain. Therefore, the dysfunction of this system can lead to a wide range of neuropsychiatric symptoms. Excitatory transmission is achieved through the activation of ion-channel or G protein-coupled glutamate receptors. The intensity of receptor interaction is determined in part by the removal of glutamate from the synaptic cleft and by neurotransmitter storage in the presynaptic vesicles. In addition to direct neurotransmission, glutamate is also important for inducing neuroplastic changes and causing excitotoxicity [49]. Within the extrapyramidal system, striatal MSNs, among others, are innervated by glutamatergic corticostriatal and thalamostriatal neurons [19]. Glutamatergic neurons from all parts of the cerebral cortex terminate in ‘striatal spine module’ of matrix MSNs of the extrapyramidal cortical–striatal–thalamic–cortical (CSTC) circuits, while projection neurons from the prefrontal cortex and corticoid amygdala terminate in the striosomal compartment of the striatum [19]. The latter neurons finally regulate the activity of the ascending dopaminergic pathway systems originating within the midbrain. Glutamatergic corticostriatal neurons targeting both compartments may play a role in the development of tardive dyskinesia. Excessive glutamatergic activity in striatal spine modules may result in damage to the MSNs of the indirect pathway. This may also be due to an excessive release of dopamine from mesostriatal neurons, which increases oxidative stress in the MSNs of the indirect pathway along that pathway. The MSNs of the indirect pathway are more susceptible to damage than those of the direct pathway [16,19].
We already investigated the possible association of polymorphisms of GRIN2A and GRIN2B in a previous study in a smaller patient population [29] and compared our findings with those of 168 Dutch White patients by Bakker and others [50]. The results hardly agreed. Only for rs1345423 in GRIN2A was a significant association with TD found in both populations. The GRIN2A variants rs7192557 (rs1969060) and rs8057394 were associated with the age of onset of dyskinesia in Huntington’s disease [51,52,53]. Ivanova et al. observed a relationship between these genetic variants and levodopa-induced dyskinesia but not with TD [28]. The various findings are confirmed in the presently studied patient population, suggesting that the NMDA receptor plays, at most, a minor role in the development of TD. However, it is at least notable that the polymorphism rs7192557, which has been associated with the onset of dyskinesia in Huntington’s disease [51,52,53] as well as with levodopa-induced dyskinesia [28], shows some association with peripheral TD in the present study.
Neuroplasticity and excitotoxicity are usually associated mainly with the properties of NMDA receptors, but the kainate receptor is, at least theoretically, also a good candidate. Kainic acid is best known for its excitotoxic effect [54,55] and is used in a classical model for HD [56,57] and epilepsy [58,59]. A certain GRIK2 variant was associated with the age of onset of HD, but this has been later contradicted [52,60]. The GRIK4 kainate receptor was strongly associated with excitotoxic neurodegeneration (in the hippocampus) [61], but nothing is known about its relation to movement disorders. Our results also do not point in the direction of a possible link.
In addition to the ionotropic glutamate receptors, the metabotropic (mGlu) receptors are also associated with processes of neurodegeneration/neuroprotection [62,63]. Because the various mGlu receptors are also localized in the extrapyramidal system [63,64,65], the value of drugs with an affinity for mGlu receptors was also investigated in Parkinson’s disease [65]. This led to the development of many new drugs that may be of value in the prevention and treatment of LID [65]. Unfortunately, the clinical results of substances targeting mGlu4 and mGlu5 were rather disappointing [66]. In our study, we found a nominally significant influence of variants of mGlu3. Apart from the axons of neurons, mGlu3 receptors are also found on reactive astrocytes [64] and microglia [67]. Through these receptors, mGlu3 receptors mediate the bringing of microglia into an anti-inflammatory state, which has a significant protective effect against neurodegenerative processes [68].
The vesicular glutamate transporter (VGLUT) plays a role in concentrating glutamate in its presynaptic vesicles, which is a prerequisite for glutamatergic neurotransmission. Of the three forms that exist of this transporter, VGLUT1 and VGLUT2 are the most abundant but complementary in the central nervous system [38,69]. VGLUT1 is used as a biomarker for corticostriatal glutamatergic neurons, whereas VGLUT2 is mainly present in thalamostriatal glutamatergic neurons [70]. The involvement of VGLUT1 in the pathogenesis of CNS disorders has not actually been investigated very thoroughly [71]. There is some evidence for a possible role in Parkinson’s disease and schizophrenia, but this appears to be primarily cognitive in nature [71].
The solute carrier family 1 member 2 (SLC1A2) gene codes for the excitatory amino acid transporter 2 (EAAT2) protein, and the solute carrier family 1 member 3 (SLC1A3) for the EAAT1 protein. Excitatory amino acid transporter 1 is mainly found in glia cells in the cerebellum but is also present in glia cells throughout the CNS [72]. EAAT2, which is also predominantly present in glial cells, is widespread and abundant in the forebrain, cerebellum, and spinal cord, and accounts for more than 90% of the total glutamate intake [38,72]. Both astrocytes [73,74] and (activated) microglia [75,76,77,78] carry EAAT1 and EAAT2 proteins and, to a much lesser extent, neurons [72,79]. Significance was attributed to EAAT1 and EAAT2 in the development of symptoms of various mental illnesses [79]. We also consider it significant that astrocytes are an important part of the striatal spinal modules [19] and regulate extracellular glutamate concentrations by their uptake [38, 40]. However, it is somewhat illogical to assume that this mechanism contributes to the development of (classical) TD, as interference with glutamatergic neurotransmission appears to have little effect, as reflected by the absence of other associations. One might also consider a mechanism influencing neurotransmission in the habenular complex, where astrocytes and the immunocompetent microglia also play an important regulatory role [79].

Limitations

Although our genotyped population counted a substantial 704 patients, only 158 people (28.9%) had TD. We used a good reliable variant of the AIMS to evaluate the presence of TD, but a limitation remains with the one-time cross-sectional assessment. Patients with TD were significantly older and sicker than individuals without TD, so the exposure to antipsychotics probably lasted longer. This may mean that the group without TD probably also includes individuals who would have exhibited TD on longer exposure. We do not have sufficient information about this medication history and have to accept that this may have resulted in a bias. However, it is unlikely that this bias is very large because the interference of antipsychotics with glutamatergic neurotransmission is, at best, modest and usually absent.

5. Conclusions

The results of our study point to the involvement of excitatory amino acid transporter 1 (EAAT1) and 2 (EAAT2), as well as metabotropic glutamate receptor 3 (mGlu3) in the development of TD. The possibility should be considered and explored that this is primarily via the role of glutamate in glial cell function (particularly considering neuroglia in the habenula). The possible role of microglia in the development of TD warrants further investigation. Hence, glutamate plays a role in the development of TD but probably not through glutamatergic neuronal fibers (as, for example, corticostriatal and thalamostriatal inputs to striatal MSNs). The possibility should be considered and explored that this is primarily via the role of glutamate in (neuro)glial cell function.

Author Contributions

Conceptualization, O.Y.F., A.J.M.L. and S.A.I.; methodology, O.Y.F. and S.A.I.; validation, O.Y.F., E.G.K. and A.V.B.; statistical analysis, I.V.P. and M.B.F.; investigation, O.Y.F., D.Z.P., E.G.P., I.V.P., A.A.G. and A.V.B.; resources, O.Y.F. and S.A.I.; data curation, O.Y.F. and E.G.K.; writing—original draft preparation, O.Y.F., D.Z.P. and A.J.M.L.; writing—review and editing, O.Y.F., E.G.K., M.B.F., N.A.B., A.J.M.L. and S.A.I.; visualization, O.Y.F. and A.J.M.L.; supervision, N.A.B. and S.A.I.; project administration, O.Y.F. and S.A.I.; funding acquisition, O.Y.F. and S.A.I. All authors have read and agreed to the published version of the manuscript.

Funding

This work was conducted with the support of the Russian Science Foundation (project No. 21-15-00212).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Bioethical Committee of the Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Sciences (Protocol 142, approved on 14 May 2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated for this study will not be made publicly available, but they are available upon reasonable request to S.A.I. ([email protected]) following the approval of the Board of Directors of the MHRI, in line with the local guidelines and regulations.

Acknowledgments

Dutch universities have suspended all forms of cooperation with Russian educational and research institutions due to the conflict with Russia over the borders of Ukraine. The Board of the Faculty of Science and Engineering of the University of Groningen exempted the manuscript of this article because the data collection was already complete and the results were described in a report.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Owen, M.J.; Sawa, A.; Mortensen, P.B. Schizophrenia. Lancet 2016, 388, 86–97. [Google Scholar] [CrossRef] [Green Version]
  2. Cao, X.; Chen, S.; Xu, H.; Wang, Q.; Xie, S.; Zhang, Y. Global functioning, cognitive function, psychopathological symptoms in untreated patients with first-episode schizophrenia: A cross-sectional study. Psychiatry Res. 2022, 313, 114616. [Google Scholar] [CrossRef]
  3. Wu, Q.; Wang, X.; Wang, Y.; Long, Y.J.; Zhao, J.P.; Wu, R.R. Developments in Biological Mechanisms and Treatments for Negative Symptoms and Cognitive Dysfunction of Schizophrenia. Neurosci. Bull. 2021, 37, 1609–1624. [Google Scholar] [CrossRef]
  4. Charlson, F.J.; Ferrari, A.J.; Santomauro, D.F.; Diminic, S.; Stockings, E.; Scott, J.G.; McGrath, J.J.; Whiteford, H.A. Global Epidemiology and Burden of Schizophrenia: Findings from the Global Burden of Disease Study 2016. Schizophr. Bull. 2018, 44, 1195–1203. [Google Scholar] [CrossRef] [PubMed]
  5. Moran, P.; Stokes, J.; Marr, J.; Bock, G.; Desbonnet, L.; Waddington, J.; O’Tuathaigh, C. Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models. Neural Plast. 2016, 2016, 2173748. [Google Scholar] [CrossRef] [Green Version]
  6. Ripke, S.; O’Dushlaine, C.; Chambert, K.; Moran, J.L.; Kähler, A.K.; Akterin, S.; Bergen, S.E.; Collins, A.L.; Crowley, J.J.; Fromer, M.; et al. Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nat. Genet. 2013, 45, 1150–1159. [Google Scholar] [CrossRef] [PubMed]
  7. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014, 511, 421–427. [Google Scholar] [CrossRef] [Green Version]
  8. Harrison, P.J. Recent genetic findings in schizophrenia and their therapeutic relevance. J. Psychopharmacol. 2015, 29, 85–96. [Google Scholar] [CrossRef]
  9. Ivanova, S.A.; Osmanova, D.Z.; Freidin, M.B.; Fedorenko, O.Y.; Boiko, A.S.; Pozhidaev, I.V.; Semke, A.V.; Bokhan, N.A.; Agarkov, A.A.; Wilffert, B.; et al. Identification of 5-hydroxytryptamine receptor gene polymorphisms modulating hyperprolactinaemia in antipsychotic drug-treated patients with schizophrenia. World J. Biol. Psychiatry 2017, 18, 239–246. [Google Scholar] [CrossRef] [Green Version]
  10. Stroup, T.S.; Gray, N. Management of common adverse effects of antipsychotic medications. World Psychiatry 2018, 17, 341–356. [Google Scholar] [CrossRef]
  11. Kornetova, E.G.; Kornetov, A.N.; Mednova, I.A.; Goncharova, A.A.; Gerasimova, V.I.; Pozhidaev, I.V.; Boiko, A.S.; Semke, A.V.; Loonen, A.J.M.; Bokhan, N.A.; et al. Comparative Characteristics of the Metabolic Syndrome Prevalence in Patients with Schizophrenia in Three Western Siberia Psychiatric Hospitals. Front. Psychiatry 2021, 12, 661174. [Google Scholar] [CrossRef] [PubMed]
  12. Guo, K.; Feng, Z.; Chen, S.; Yan, Z.; Jiao, Z.; Feng, D. Safety Profile of Antipsychotic Drugs: Analysis Based on a Provincial Spontaneous Reporting Systems Database. Front. Pharmacol. 2022, 13, 848472. [Google Scholar] [CrossRef] [PubMed]
  13. Loonen, A.J.M.; Doorschot, C.H.; van Hemert, D.A.; Oostelbos, M.C.; Sijben, A.E. The Schedule for the Assessment of Drug-Induced Movement Disorders (SADIMoD): Test-retest reliability and concurrent validity. Int. J. Neuropsychopharmacol. 2000, 3, 285–296. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Loonen, A.J.M.; Doorschot, C.H.; van Hemert, D.A.; Oostelbos, M.C.; Sijben, A.E. The schedule for the assessment of drug-induced movement disorders (SADIMoD): Inter-rater reliability and construct validity. Int. J. Neuropsychopharmacol. 2001, 4, 347–360. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Loonen, A.J.M.; van Praag, H.M. Measuring movement disorders in antipsychotic drug trials: The need to define a new standard. J. Clin. Psychopharmacol. 2007, 27, 423–430. [Google Scholar] [CrossRef]
  16. Loonen, A.J.M.; Ivanova, S.A. New insights into the mechanism of drug-induced dyskinesia. CNS Spectr. 2013, 18, 15–20. [Google Scholar] [CrossRef]
  17. Pozhidaev, I.V.; Paderina, D.Z.; Fedorenko, O.Y.; Kornetova, E.G.; Semke, A.V.; Loonen, A.J.M.; Bokhan, N.A.; Wilffert, B.; Ivanova, S.A. 5-Hydroxytryptamine Receptors and Tardive Dyskinesia in Schizophrenia. Front. Mol. Neurosci. 2020, 13, 63. [Google Scholar] [CrossRef] [Green Version]
  18. Al Hadithy, A.F.; Ivanova, S.A.; Pechlivanoglou, P.; Semke, A.; Fedorenko, O.; Kornetova, E.; Ryadovaya, L.; Brouwers, J.R.B.J.; Wilffert, B.; Bruggeman, R.; et al. Tardive dyskinesia and DRD3, HTR2A and HTR2C gene polymorphisms in Russian psychiatric inpatients from Siberia. Prog. Neuropsychopharmacol. Biol. Psychiatry 2009, 33, 475–481. [Google Scholar] [CrossRef]
  19. Loonen, A.J.M.; Wilffert, B.; Ivanova, S.A. Putative role of pharmacogenetics to elucidate the mechanism of tardive dyskinesia in schizophrenia. Pharmacogenomics 2019, 20, 1199–1223. [Google Scholar] [CrossRef] [Green Version]
  20. Loonen, A.J.M.; Ivanova, S.A. Neurobiological mechanisms associated with antipsychotic drug-induced dystonia. J. Psychopharmacol. 2021, 35, 3–14. [Google Scholar] [CrossRef]
  21. Sienaert, P.; van Harten, P.; Rhebergen, D. The psychopharmacology of catatonia, neuroleptic malignant syndrome, akathisia, tardive dyskinesia, and dystonia. Handb. Clin. Neurol. 2019, 165, 415–428. [Google Scholar] [CrossRef] [PubMed]
  22. Brosnan, J.T.; Brosnan, M.E. Glutamate: A truly functional amino acid. Amino Acids 2013, 45, 413–418. [Google Scholar] [CrossRef] [PubMed]
  23. Collingridge, G.L.; Abraham, W.C. Glutamate receptors and synaptic plasticity: The impact of Evans and Watkins. Neuropharmacology 2022, 206, 108922. [Google Scholar] [CrossRef] [PubMed]
  24. Szota, A.M.; Scheel-Krüger, J. The role of glutamate receptors and their interactions with dopamine and other neurotransmitters in the development of tardive dyskinesia: Preclinical and clinical results. Behav. Pharmacol. 2020, 31, 511–523. [Google Scholar] [CrossRef]
  25. Traynelis, S.F.; Wollmuth, L.P.; McBain, C.J.; Menniti, F.S.; Vance, K.M.; Ogden, K.K.; Hansen, K.B.; Yuan, H.; Myers, S.J.; Dingledine, R. Glutamate receptor ion channels: Structure, regulation, and function. Pharmacol. Rev. 2010, 62, 405–496. [Google Scholar] [CrossRef] [Green Version]
  26. Greger, I.H.; Mayer, M.L. Structural biology of glutamate receptor ion channels: Towards an understanding of mechanism. Curr. Opin. Struct. Biol. 2019, 57, 185–195. [Google Scholar] [CrossRef]
  27. Hansen, K.B.; Wollmuth, L.P.; Bowie, D.; Furukawa, H.; Menniti, F.S.; Sobolevsky, A.I.; Swanson, G.T.; Swanger, S.A.; Greger, I.H.; Nakagawa, T.; et al. Structure, Function, and Pharmacology of Glutamate Receptor Ion Channels. Pharmacol. Rev. 2021, 73, 298–487. [Google Scholar] [CrossRef]
  28. Ivanova, S.A.; Loonen, A.J.M.; Pechlivanoglou, P.; Freidin, M.B.; Al Hadithy, A.F.; Rudikov, E.V.; Zhukova, I.A.; Govorin, N.V.; Sorokina, V.A.; Fedorenko, O.Y.; et al. NMDA receptor genotypes associated with the vulnerability to develop dyskinesia. Transl. Psychiatry 2012, 2, e67. [Google Scholar] [CrossRef]
  29. Ivanova, S.A.; Loonen, A.J.M.; Bakker, P.R.; Freidin, M.B.; Ter Woerds, N.J.; Al Hadithy, A.F.; Semke, A.V.; Fedorenko, O.Y.; Brouwers, J.R.B.J.; Bokhan, N.A.; et al. Likelihood of mechanistic roles for dopaminergic, serotonergic and glutamatergic receptors in tardive dyskinesia: A comparison of genetic variants in two independent patient populations. SAGE Open Med. 2016, 4, 2050312116643673. [Google Scholar] [CrossRef]
  30. Lim, K.; Lam, M.; Zai, C.; Tay, J.; Karlsson, N.; Deshpande, S.N.; Thelma, B.K.; Ozaki, N.; Inada, T.; Sim, K.; et al. Genome wide study of tardive dyskinesia in schizophrenia. Transl. Psychiatry 2021, 11, 351. [Google Scholar] [CrossRef]
  31. Greenwood, T.A.; Lazzeroni, L.C.; Calkins, M.E.; Freedman, R.; Green, M.F.; Gur, R.E.; Gur, R.C.; Light, G.A.; Nuechterlein, K.H.; Olincy, A.; et al. Genetic assessment of additional endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study. Schizophr. Res. 2016, 170, 30–40. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Conn, P.J.; Pin, J.P. Pharmacology and functions of metabotropic glutamate receptors. Annu. Rev. Pharmacol. Toxicol. 1997, 37, 205–237. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Gerber, U.; Gee, C.E.; Benquet, P. Metabotropic glutamate receptors: Intracellular signaling pathways. Curr. Opin. Pharmacol. 2007, 7, 56–61. [Google Scholar] [CrossRef] [PubMed]
  34. Shibata, H.; Tani, A.; Chikuhara, T.; Kikuta, R.; Sakai, M.; Ninomiya, H.; Tashiro, N.; Iwata, N.; Ozaki, N.; Fukumaki, Y. Association study of polymorphisms in the group III metabotropic glutamate receptor genes, GRM4 and GRM7, with schizophrenia. Psychiatry Res. 2009, 167, 88–96. [Google Scholar] [CrossRef]
  35. Saini, S.M.; Mancuso, S.G.; Mostaid, M.S.; Liu, C.; Pantelis, C.; Everall, I.P.; Bousman, C.A. Meta-analysis supports GWAS-implicated link between GRM3 and schizophrenia risk. Transl. Psychiatry 2017, 7, e1196. [Google Scholar] [CrossRef] [Green Version]
  36. Liang, W.; Yu, H.; Su, Y.; Lu, T.; Yan, H.; Yue, W.; Zhang, D. Variants of GRM7 as risk factor and response to antipsychotic therapy in schizophrenia. Transl. Psychiatry 2020, 10, 83. [Google Scholar] [CrossRef] [Green Version]
  37. Kovermann, P.; Engels, M.; Müller, F.; Fahlke, C. Cellular Physiology and Pathophysiology of EAAT Anion Channels. Front. Cell Neurosci. 2022, 15, 815279. [Google Scholar] [CrossRef]
  38. Shigeri, Y.; Seal, R.P.; Shimamoto, K. Molecular pharmacology of glutamate transporters, EAATs and VGLUTs. Brain Res. Brain Res. Rev. 2004, 45, 250–265. [Google Scholar] [CrossRef]
  39. Wang, L.; Ma, T.; Qiao, D.; Cui, K.; Bi, X.; Han, C.; Yang, L.; Sun, M.; Liu, L. Polymorphism of rs12294045 in EAAT2 gene is potentially associated with schizophrenia in Chinese Han population. BMC Psychiatry 2022, 22, 171. [Google Scholar] [CrossRef]
  40. Parkin, G.M.; Udawela, M.; Gibbons, A.; Dean, B. Glutamate transporters, EAAT1 and EAAT2, are potentially important in the pathophysiology and treatment of schizophrenia and affective disorders. World J. Psychiatry 2018, 8, 51–63. [Google Scholar] [CrossRef]
  41. Giunti, P.; Mantuano, E.; Frontali, M. Episodic Ataxias: Faux or Real? Int. J. Mol. Sci. 2020, 21, 6472. [Google Scholar] [CrossRef] [PubMed]
  42. Amadori, E.; Pellino, G.; Bansal, L.; Mazzone, S.; Møller, R.S.; Rubboli, G.; Striano, P.; Russo, A. Genetic paroxysmal neurological disorders featuring episodic ataxia and epilepsy. Eur. J. Med. Genet. 2022, 65, 104450. [Google Scholar] [CrossRef] [PubMed]
  43. Almqvist, J.; Huang, Y.; Laaksonen, A.; Wang, D.N.; Hovmöller, S. Docking and homology modeling explain inhibition of the human vesicular glutamate transporters. Protein Sci. 2007, 16, 1819–1829. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Fremeau, R.T., Jr.; Voglmaier, S.; Seal, R.P.; Edwards, R.H. VGLUTs define subsets of excitatory neurons and suggest novel roles for glutamate. Trends Neurosci. 2004, 27, 98–103. [Google Scholar] [CrossRef]
  45. World Health Organization. International Statistical Classification of Diseases and Health Related Problems ICD-10; World Health Organization: Geneva, Switzerland, 2004. [Google Scholar]
  46. Andreasen, N.C.; Pressler, M.; Nopoulos, P.; Miller, D.; Ho, B.C. Antipsychotic dose equivalents and dose-years: A standardized method for comparing exposure to different drugs. Biol. Psychiatry 2010, 67, 255–262. [Google Scholar] [CrossRef] [Green Version]
  47. Loonen, A.J.M.; Doorschot, C.H. Abnormal Involuntary Movement Scale (AIMS) (Sadimod Adaptation). Available online: https://sadimod.nl/AIMS-form-Sadimod (accessed on 23 May 2022).
  48. Li, J.; Ji, L. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 2005, 95, 221–227. [Google Scholar] [CrossRef] [Green Version]
  49. Loonen, A.J.M. Het Beweeglijke Brein. De Neurowetenschappelijke Achtergronden van de Psychische Functies, 3rd ed.; Uitgeverij Mension: Haarlem, The Netherlands, 2021; pp. 149–174. ISBN 978-90-77322-58-1. [Google Scholar]
  50. Bakker, P.R.; Al Hadithy, A.F.; Amin, N.; van Duijn, C.M.; van Os, J.; van Harten, P.N. Antipsychotic-induced movement disorders in long-stay psychiatric patients and 45 tag SNPs in 7 candidate genes: A prospective study. PLoS ONE 2012, 7, e50970. [Google Scholar] [CrossRef] [Green Version]
  51. Arning, L.; Kraus, P.H.; Valentin, S.; Saft, C.; Andrich, J.; Epplen, J.T. NR2A and NR2B receptor gene variations modify age at onset in Huntington disease. Neurogenetics 2005, 6, 25–28. [Google Scholar] [CrossRef]
  52. Andresen, J.M.; Gayán, J.; Cherny, S.S.; Brocklebank, D.; Alkorta-Aranburu, G.; Addis, E.A.; US-Venezuela Collaborative Research Group; Cardon, L.R.; Housman, D.E.; Wexler, N.S. Replication of twelve association studies for Huntington’s disease residual age of onset in large Venezuelan kindreds. J. Med. Genet. 2007, 44, 44–50. [Google Scholar] [CrossRef] [Green Version]
  53. Arning, L.; Saft, C.; Wieczorek, S.; Andrich, J.; Kraus, P.H.; Epplen, J.T. NR2A and NR2B receptor gene variations modify age at onset in Huntington disease in a sex-specific manner. Hum. Genet. 2007, 122, 175–182. [Google Scholar] [CrossRef]
  54. McGeer, P.L.; McGeer, E.G. Kainic acid: The neurotoxic breakthrough. Crit. Rev. Toxicol. 1982, 10, 1–26. [Google Scholar] [CrossRef] [PubMed]
  55. Coyle, J.T. Kainic acid: Insights into excitatory mechanisms causing selective neuronal degeneration. Ciba Found Symp. 1987, 126, 186–203. [Google Scholar] [CrossRef] [PubMed]
  56. Coyle, J.T.; Schwarcz, R. Lesion of striatal neurones with kainic acid provides a model for Huntington’s chorea. Nature 1976, 263, 244–246. [Google Scholar] [CrossRef] [PubMed]
  57. Sanberg, P.R.; Johnston, G.A. Glutamate and Huntington’s disease. Med. J. Aust. 1981, 2, 460–465. [Google Scholar] [CrossRef] [PubMed]
  58. Levin, S.L.; Sytinskiĭ, I.A. Toksicheskoe deĭstvie kainovoĭ kisloty kak model’ khorei Gentingtona i épilepsii (obzor) [Toxic action of kainic acid as a model of Huntington chorea and epilepsy (review)]. Korsakov’s J. Neurol. Psychiatry 1983, 83, 754–763. [Google Scholar]
  59. Rusina, E.; Bernard, C.; Williamson, A. The Kainic Acid Models of Temporal Lobe Epilepsy. eNeuro 2021, 8, ENEURO.0337-20.2021. [Google Scholar] [CrossRef]
  60. Lee, J.H.; Lee, J.M.; Ramos, E.M.; Gillis, T.; Mysore, J.S.; Kishikawa, S.; Hadzi, T.; Hendricks, A.E.; Hayden, M.R.; Morrison, P.J.; et al. TAA repeat variation in the GRIK2 gene does not influence age at onset in Huntington’s disease. Biochem. Biophys. Res. Commun. 2012, 424, 404–408. [Google Scholar] [CrossRef] [Green Version]
  61. Lowry, E.R.; Kruyer, A.; Norris, E.H.; Cederroth, C.R.; Strickland, S. The GluK4 kainate receptor subunit regulates memory, mood, and excitotoxic neurodegeneration. Neuroscience 2013, 235, 215–225. [Google Scholar] [CrossRef] [Green Version]
  62. Caraci, F.; Battaglia, G.; Sortino, M.A.; Spampinato, S.; Molinaro, G.; Copani, A.; Nicoletti, F.; Bruno, V. Metabotropic glutamate receptors in neurodegeneration/neuroprotection: Still a hot topic? Neurochem. Int. 2012, 61, 559–565. [Google Scholar] [CrossRef]
  63. Nickols, H.H.; Conn, P.J. Development of allosteric modulators of GPCRs for treatment of CNS disorders. Neurobiol. Dis. 2014, 61, 55–71. [Google Scholar] [CrossRef] [Green Version]
  64. Amalric, M. Targeting metabotropic glutamate receptors (mGluRs) in Parkinson’s disease. Curr. Opin. Pharmacol. 2015, 20, 29–34. [Google Scholar] [CrossRef] [PubMed]
  65. Sebastianutto, I.; Cenci, M.A. mGlu receptors in the treatment of Parkinson’s disease and L-DOPA-induced dyskinesia. Curr. Opin. Pharmacol. 2018, 38, 81–89. [Google Scholar] [CrossRef] [PubMed]
  66. Frouni, I.; Huot, P. Glutamate modulation for the treatment of levodopa induced dyskinesia: A brief review of the drugs tested in the clinic. Neurodegener. Dis. Manag. 2022. [Google Scholar] [CrossRef] [PubMed]
  67. Mead, E.L.; Mosley, A.; Eaton, S.; Dobson, L.; Heales, S.J.; Pocock, J.M. Microglial neurotransmitter receptors trigger superoxide production in microglia; consequences for microglial-neuronal interactions. J. Neurochem. 2012, 121, 287–301. [Google Scholar] [CrossRef]
  68. Mastroiacovo, F.; Zinni, M.; Mascio, G.; Bruno, V.; Battaglia, G.; Pansiot, J.; Imbriglio, T.; Mairesse, J.; Baud, O.; Nicoletti, F. Genetic Deletion of mGlu3 Metabotropic Glutamate Receptors Amplifies Ischemic Brain Damage and Associated Neuroinflammation in Mice. Front. Neurol. 2021, 12, 668877. [Google Scholar] [CrossRef]
  69. Takamori, S. VGLUTs: ‘exciting’ times for glutamatergic research? Neurosci. Res. 2006, 55, 343–351. [Google Scholar] [CrossRef]
  70. Smith, Y.; Galvan, A.; Ellender, T.J.; Doig, N.; Villalba, R.M.; Huerta-Ocampo, I.; Wichmann, T.; Bolam, J.P. The thalamostriatal system in normal and diseased states. Front. Syst. Neurosci. 2014, 8, 5. [Google Scholar] [CrossRef]
  71. Du, X.; Li, J.; Li, M.; Yang, X.; Qi, Z.; Xu, B.; Liu, W.; Xu, Z.; Deng, Y. Research progress on the role of type I vesicular glutamate transporter (VGLUT1) in nervous system diseases. Cell Biosci. 2020, 10, 26. [Google Scholar] [CrossRef] [Green Version]
  72. O’Shea, R.D. Roles and regulation of glutamate transporters in the central nervous system. Clin. Exp. Pharmacol. Physiol. 2002, 29, 1018–1023. [Google Scholar] [CrossRef]
  73. Milton, I.D.; Banner, S.J.; Ince, P.G.; Piggott, N.H.; Fray, A.E.; Thatcher, N.; Horne, C.H.; Shaw, P.J. Expression of the glial glutamate transporter EAAT2 in the human CNS: An immunohistochemical study. Brain Res. Mol. Brain Res. 1997, 52, 17–31. [Google Scholar] [CrossRef]
  74. Banner, S.J.; Fray, A.E.; Ince, P.G.; Steward, M.; Cookson, M.R.; Shaw, P.J. The expression of the glutamate re-uptake transporter excitatory amino acid transporter 1 (EAAT1) in the normal human CNS and in motor neurone disease: An immunohistochemical study. Neuroscience 2002, 109, 27–44. [Google Scholar] [CrossRef]
  75. Gras, G.; Chrétien, F.; Vallat-Decouvelaere, A.V.; Le Pavec, G.; Porcheray, F.; Bossuet, C.; Léone, C.; Mialocq, P.; Dereuddre-Bosquet, N.; Clayette, P.; et al. Regulated expression of sodium-dependent glutamate transporters and synthetase: A neuroprotective role for activated microglia and macrophages in HIV infection? Brain Pathol. 2003, 13, 211–222. [Google Scholar] [CrossRef] [PubMed]
  76. Vallat-Decouvelaere, A.V.; Chrétien, F.; Gras, G.; Le Pavec, G.; Dormont, D.; Gray, F. Expression of excitatory amino acid transporter-1 in brain macrophages and microglia of HIV-infected patients. A neuroprotective role for activated microglia? J. Neuropathol. Exp. Neurol. 2003, 62, 475–485. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. López-Redondo, F.; Nakajima, K.; Honda, S.; Kohsaka, S. Glutamate transporter GLT-1 is highly expressed in activated microglia following facial nerve axotomy. Brain Res. Mol. Brain Res. 2000, 76, 429–435. [Google Scholar] [CrossRef]
  78. Nakajima, K.; Tohyama, Y.; Kohsaka, S.; Kurihara, T. Ability of rat microglia to uptake extracellular glutamate. Neurosci. Lett. 2001, 307, 171–174. [Google Scholar] [CrossRef]
  79. Loonen, A.J.M.; Ivanova, S.A. Circuits Regulating Pleasure and Happiness—Focus on Potential Biomarkers for Circuitry including the Habenuloid Complex. Acta Neuropsychiatr. 2022, 1–36. [Google Scholar] [CrossRef]
Table
Table 1. The basic information of analyzed polymorphic variants.
Table 1. The basic information of analyzed polymorphic variants.
GeneSNPChromosome: LocationLocation RegionAllelesMAFχ2p-Value
GRIN2Ars1164446116:10027033intron variantT/C0.23 (C)0.6860.408
rs1164658716:9779462intron variantG/A0.29 (A)0.3730.541
rs1186632816:9768699intron variantG/T0.31 (T)01
rs134542316:10154207intron variantG/A/C/T0.32 (G)0.2410.624
rs478203916:9913110intron variantT/C0.22 (C)0.6590.417
rs719061916:9985267intron variantG/A0.07 (A)0.6650.415
rs719255716:10029612intron variantG/A/C/T0.32 (A)0.2800.597
rs719609516:9791975intron variantT/C/G0.30 (C)0.1100.740
rs720625616:10103066intron variantA/G/T0.44 (G)0.4170.518
rs805739416:10021631intron variantC/G0.43 (C)0.3540.552
rs978893616:10011603intron variantT/C0.24 (C)0.0140.906
rs998938816:9872282intron variantC/T0.19 (T)0.2550.614
GRIN2Brs1077271512:13885069intron variantG/A0.43 (A)0.0060.938
rs1084583812:13741462intron variantG/A0.38 (A)0.4820.487
rs1230085112:13815471intron variantT/A/C0.10 (C)0.0660.798
rs1282753612:13943223intron variantC/T0.22 (T)0.9120.340
rs180548112:13610521intron variantA/C0.43 (C)0.8320.362
rs219297012:13683379intron variantG/A0.11 (A)0.1950.659
rs22059912:13822364intron variantG/A0.44 (A)2.6640.103
rs230024212:13687363intron variantA/T0.48 (T)0.6040.437
rs731314912:13675353intron variantT/A/C/G0.21 (C)1.8750.171
rs89012:135623743 prime UTR variantA/C/G0.28 (C)0.6000.438
GRIK4rs195478711:120792654intron variantT/C0.50 (T)0.0520.819
SLC1A2rs104211311:35286822synonymous variantT/C0.23 (C)0.0810.777
rs1074233811:352555413 prime UTR variantT/A/C0.10 (T)4.3120.038 *
rs1076812111:352581093 prime UTR variantA/C/G0.35 (C)1.4110.235
rs1103304611:352533863 prime UTR variantT/A0.36 (A)0.7630.382
rs1229404511:352577543 prime UTR variantC/G/T0.20 (T)0.0150.904
rs1236117111:352567863 prime UTR variantT/A/C0.36 (A)2.5750.109
rs308816811:352517213 prime UTR variantT/C0.36 (C)0.7780.378
rs381277811:352557233 prime UTR variantG/A0.10 (A)2.5470.110
rs382928011:352551763 prime UTR variantA/C/T0.13 (T)2.9160.088
rs793695011:352574123 prime UTR variantC/A/G/T0.10 (C)3.4880.062
SLC1A3rs22298945:366863023 prime UTR variantG/A/C0.430.5520.457
SLC17A7rs6212623619:49441696intron variantT/C0.19 (C)0.4580.499
GRM3rs14684127:86804135intron variantA/T0.38 (T)01
rs22375627:86792916intron variantT/C0.39 (C)0.5870.444
rs22992257:86818264intron variantT/G0.03 (G)1.2470.264
rs64650847:86774159intron variantA/G0.23 (G)4.1000.043 *
GRM7rs124916203:7352646intron variantC/G0.18 (G)3.2150.073
rs13964093:7261220intron variantG/A/C/T0.34 (A)0.0960.757
rs14500993:7496689intron variantT/G0.38 (T)0.0990.752
rs170318353:6880071intron variantC/T0.10 (T)0.0390.844
rs37493803:6861610missense variantC/G/T0.42 (T)0.2990.585
GRM8rs22377487:126638809intron variantC/T0.32 (T)01
rs22994727:126580415intron variantC/A/G0.32 (A)0.0620.803
Notes: MAF—minor allele frequency; HWE χ2 and HWE p—chi-square and p-value statistics, respectively, to test the frequency distribution according to the Hardy–Weinberg equilibrium. * and in bold: significant at p < 0.05.
Table
Table 2. Demographic and clinical parameters of the total group of patients with schizophrenia depending on the presence or absence of tardive dyskinesia.
Table 2. Demographic and clinical parameters of the total group of patients with schizophrenia depending on the presence or absence of tardive dyskinesia.
Patients without TDPatients with TDp-Value
Total sample size715229-
Gender, n (%)Male—375 (52.45%)Male—134 (58.51%)0.109
Female—340 (47.55%)Female—95 (41.49%)
Age, years
Me (Q1; Q3)		37 (30; 48)45 (34.75; 56.25)<0.001
Age of onset, years
Me (Q1; Q3)		24 (20; 29)24 (19; 31.25)0.558
Duration of illness, years
Me (Q1; Q3)		11.5 (5; 20)18 (8.75; 27.25)<0.001
CPZeq, dose Me (Q1; Q3)450 (225; 750)500 (300; 758.7)0.187
Notes: Me (Q1; Q3)—median and quartiles (first and third); TD—tardive dyskinesia; CPZeq—chlorpromazine equivalent (according to [46]).
Table
Table 3. Demographic and clinical parameters of the representative group of patients genotyped.
Table 3. Demographic and clinical parameters of the representative group of patients genotyped.
Patients without TDPatients with TDp-Value
Total sample size546158-
Orofacial TD—86
Limb-truncal TD—77
Gender, n (%)Male—282 (51.65%)Male—88 (55.70%)0.109
Female—264 (48.35%)Female—70 (44.30%)
Age, years
Me (Q1; Q3)		38 (31; 48)45 (34; 57)<0.001
Age of onset, years
Me (Q1; Q3)		24 (20; 30)24 (19.5; 31.5)0.558
Duration of illness, years
Me (Q1; Q3)		12 (6; 21)18 (9; 27)<0.001
CPZeq, dose Me (Q1; Q3)430 (225; 779.95)500 (300; 758.7)0.294
Notes: Me (Q1; Q3)—median and quartiles (first and third); TD—tardive dyskinesia; CPZeq—chlorpromazine equivalent (calculated according to [46]).
Table
Table 4. Results of regression analysis of association between genetic markers and tardive dyskinesia.
Table 4. Results of regression analysis of association between genetic markers and tardive dyskinesia.
GeneSNPEstimateStandard Errorp-Value
GRM3rs22375620.38840.14000.0055
GRM3rs14684120.33110.14000.0180
SLC1A2rs10421130.38460.14340.0073
SLC1A2rs10768121−0.29630.13520.0284
SLC1A2rs12361171−0.29630.13580.0291
SLC1A3rs2229894−0.33270.14010.0175
Notes: Additive genetic model was tested using logistic regression adjusting for age and sex. Only nominally significant associations are shown.
Table
Table 5. Results of regression analysis of association between haplotypes of SLC1A2 gene (SNPs rs1042113, rs10768121, and rs12361171) and tardive dyskinesia.
Table 5. Results of regression analysis of association between haplotypes of SLC1A2 gene (SNPs rs1042113, rs10768121, and rs12361171) and tardive dyskinesia.
HaplotypeFrequencyOR95% CIp-Values
TCA0.38051.00 (Ref.)
CAT0.27311.571.15–2.140.0048
TAT0.33111.160.84–1.600.3570
Rare0.01520.740.21–2.540.6296
Notes: Adjustments were made for age and sex; rare haplotypes with frequency < 0.01 are combined.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Fedorenko, O.Y.; Paderina, D.Z.; Kornetova, E.G.; Poltavskaya, E.G.; Pozhidaev, I.V.; Goncharova, A.A.; Freidin, M.B.; Bocharova, A.V.; Bokhan, N.A.; Loonen, A.J.M.; et al. Genes of the Glutamatergic System and Tardive Dyskinesia in Patients with Schizophrenia. Diagnostics 2022, 12, 1521. https://doi.org/10.3390/diagnostics12071521

AMA Style

Fedorenko OY, Paderina DZ, Kornetova EG, Poltavskaya EG, Pozhidaev IV, Goncharova AA, Freidin MB, Bocharova AV, Bokhan NA, Loonen AJM, et al. Genes of the Glutamatergic System and Tardive Dyskinesia in Patients with Schizophrenia. Diagnostics. 2022; 12(7):1521. https://doi.org/10.3390/diagnostics12071521

Chicago/Turabian Style

Fedorenko, Olga Yu., Diana Z. Paderina, Elena G. Kornetova, Evgeniya G. Poltavskaya, Ivan V. Pozhidaev, Anastasiia A. Goncharova, Maxim B. Freidin, Anna V. Bocharova, Nikolay A. Bokhan, Anton J. M. Loonen, and et al. 2022. "Genes of the Glutamatergic System and Tardive Dyskinesia in Patients with Schizophrenia" Diagnostics 12, no. 7: 1521. https://doi.org/10.3390/diagnostics12071521

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop