Changes in DNMT1 expression as a marker of epigenetic regulation disturbanses in multiple sclerosis patients

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Abbreviations

DNMTs, DNA methyltransferases; MS, multiple sclerosis; MTHFR, methylenetetetrahydrofolate reductase; MTR, methionine synthase; MTRR, methionine synthase reductase; PCR, polymerase chain reaction; MS-HRM, methyl-sensitive high-resolution melting curve analysis; EDSS, expanded disability status scale.

Background

Disruption of epigenetic regulation represents a crucial link in the pathogenesis of multifactorial diseases by mediating the interaction of environmental factors and genetic predisposition [1, 2]. DNA methylation, the transfer of a methyl group from the universal methyl donor S-adenosine methionine to cytosine, which is part of CpG dinucleotides, was the first to be discovered and is the most studied mechanism of epigenetic control [3]. This reaction is catalyzed by enzymes of the DNA methyltransferase family (DNMTs) [4, 5]. The DNMT1 gene product provides stability of methylation patterns during cell division as it has affinity primarily for half-methylated DNA. Methyltransferases DNMT3a and DNMT3b perform de novo methylation and are expressed primarily in undifferentiated embryonic cells [6].

The activity of methyltransferases is altered in several pathological processes, including tumor growth, neurodegenerative diseases, and autoimmune pathology. For several malignant neoplasms, there is a correlation between the suppression of oncosuppressor gene production and hyperactivation of DNMTs at both the transcriptional and translational levels [7–9]. Furthermore, alterations in the activity of DNA methyltransferases, in conjunction with alterations in the genome-wide methylation levels and activation or inactivation of specific genes involved in the pathogenesis of numerous diseases of the central nervous system, have been demonstrated. Particularly, low DNMT1 expression in patients with Alzheimer’s disease correlates with high production of presynilin, whereas dysregulation of α-synuclein expression, DNMT1 translocation, and hyperproduction of genes involved in its pathogenesis have been associated with Parkinson’s disease [10–12]. There is a correlation between the formation of pathological protein aggregates, reduced FUS gene expression, and DNMT1 overexpression in patients with one of the variants of familial amyotrophic lateral sclerosis [13].

Multiple sclerosis (MS) is a progressive demyelinating autoimmune disease characterized by a chronic course with increasing neurological deficits [14]. Significant changes in DNA methylation profiles occur in MS, including hypomethylation of promoters of genes associated with the control of myelination, T-lymphocyte differentiation, and inflammatory reactions (PAD2, FOXP3, and IL-17A) [15–18]. As a notable decline in DNMT1 mRNA expression is observed in MS patients [19], it can be hypothesized that the suppression of DNMT1 activity contributes to the formation of aberrant methylation patterns and dysregulation of gene expression. Thus, it is of interest to compare DNMT1 gene expression levels in patients at the onset of MS and during the long-term course of the disease. Moreover, it is necessary to ascertain whether the suppression of DNMT1 expression is associated with alterations in the degree of methylation of the promoter region of the gene, or whether this reduction is because of other mechanisms. Particularly, the regulation of methylation processes is closely associated with the functioning of the folate cycle and activity of enzymes controlling the metabolism of homocysteine and methionine and formation of methyl donors [20, 21]. Excessive accumulation of homocysteine because of its slow conversion into methionine is accompanied by a decrease in the production of S-adenosine methionine, a deficiency of methyl groups, and a decrease in the ratio of S-adenosine methionine/S-adenosine homocysteine [22]. S-adenosine homocysteine, a byproduct of the methylation reaction, functions as a competitive inhibitor of DNMTs [23]. Consequently, the peculiarities of folate metabolism and homocysteine metabolism may be affected by both insufficient intake of micronutrients, especially B vitamins, which are coenzymes of the folic acid cycle, and genetically determined decreases in the activity of key genes of the folate cycle, including methylenetetrahydrofolate reductase (MTHFR), methionine synthase (MTR), and methionine synthase reductase (MTRR).

The aim of this study was to assess the level of DNMT1 mRNA expression and degree of DNMT1 promoter methylation in MS patients with various disease durations, and to determine the relationship between DNMT1 gene activity and the presence of folate cycle gene polymorphisms.

Materials and methods

An experimental group of 98 patients with MS, diagnosed according to the McDonald criteria [24], and a control group of 32 healthy volunteers without neurologic pathology were obtained for the study (Table 1). The patients included in the study were under outpatient observation at the clinic of the Institute of Experimental Medicine and the Almazov National Medical Research Center. Venous blood samples for molecular biological studies were obtained from patients and healthy volunteers after they signed a voluntary informed consent form.

 

Table 1 / Таблица 1

Demographic characteristics of control subjects and multiple sclerosis patients. Data are presented as: median [1rd quartile; 3rd quartile]

Демографические характеристики контрольной группы и пациентов с рассеянным склерозом. Данные представлены в виде: медиана [1-й квартиль; 3-й квартиль]

Indicators	Control group, n = 32	Patients with multiple sclerosis, n = 99
Gender (W : M)	24 : 8	71 : 28
Age (years)	37,0 [31, 5; 47, 0]	40,0 [32, 0; 48, 0]
Age of MS onset (years)	–	31,0 [24, 0; 37, 0]
EDSS score	–	3,8 [2, 0; 5, 1]

Note: EDSS, expanded disability status scale.

 

Genetic testing was conducted to detect polymorphisms of folate cycle genes, including MTHFR, MTR, and MTRR, in all participants. A group of 30 individuals were selected from the total sample to assess DNMT1 expression.

Genotyping for polymorphisms C677T and A1298C of the MTHFR gene, A2756G of the MTR gene, and A66G of the MTRR gene

Venous blood samples were collected in vacuum tubes containing an anticoagulant (ethylenediaminetetracetic acid) for subsequent molecular biological and genetic analyses. Nuclear DNA was isolated from whole blood according to standard protocols using the DNA Sorb B reagent kit (Next-Bio LLC, St. Petersburg) for genotyping. Genotypes were determined by polymerase chain reaction (PCR) using specific oligonucleotide primers and allele-specific LNA-modified fluorescent probes for the following polymorphisms: C677T and A1298C of the MTHFR gene (SNP rs1801133 and rs1801131), A2756G of the MTR gene (SNP rs1805087) and A66G of the MTRR gene (SNP rs1801394). The primers and probes were synthesized from DNA Synthesis LLC.

Analysis of expression level and evaluation of methylation of DNMT1 gene promoter

Three groups consisting of ten patients diagnosed with MS (disease duration of >1year), ten patients in the MS onset (disease duration of no more than 6 months), and ten healthy volunteers of an appropriate age, were selected for determining DNMT1 expression.

The mRNA expression levels and degree of methylation of the promoter region of the DNMT1 gene were assessed using peripheral blood mononuclear cells isolated by gradient centrifugation with the Proba-Ficoll reagent kit (DNA-Technology LLC, Russia) according to the manufacturer’s instructions.

Extraction of mRNA and evaluation of DNMT1 gene expression level

Total mRNA was isolated from peripheral blood mononuclear cells using the Extract-RNA reagent (Evrogen, Russia). The mRNA expression level of the DNMT1 gene was assessed by reverse transcription followed by PCR using specific oligonucleotide primers and TaqMan fluorescent probes, with real-time recording of the results. The expression level of DNMT1 was calculated using the ΔΔCt method relative to the expression level of the β-glucuronidase beta (GUSB) gene. The stability of its expression level and validity of its use as an internal control in the study of gene expression in human peripheral blood mononuclear cells were demonstrated previously [25].

Extraction of genomic DNA and determination of the degree of methylation of the promoter of the DNMT1 gene

Genomic DNA was isolated from peripheral mononuclear cell samples using the sorbent extraction method (DNA-Technology Ltd.), following the manufacturer’s instructions. The concentration of the extracted genomic DNA was determined using spectrophotometer at a wavelength of 260 nm on a NanoDrop LITE instrument (ThermoFisher Scientific, USA), according to the manufacturer’s instructions. The absorbance ratio at 260 and 280 nm wavelengths (A260/280) was used to assess the purity of the preparation.

At least 100 ng of DNA from each sample was subjected to bisulfite conversion using the BisQuick reagent kit (Evrogen, Moscow) to convert unmethylated cytosines to uracil. All samples (including samples of methylated and unmethylated control DNA, whose algorithm is described below) were processed simultaneously to avoid potential batch effects.

The efficiency of bisulfite conversion was assessed using an artificial sample of completely unmethylated human DNA in the form of a PCR-amplified product including a 638-bp region in the promoter region of the DNMT1 gene. The primers used for amplification were as follows: forward (638_F): 5՛-GGGAATCCACGGTCCATTT-3՛ and reverse (638_R): 5՛-GGGCTTCTTCTCGCTGCTGCTGCTTTAT3՛.

Assessment of methylation of the promoter region of the DNMT1 gene

Fluorescent PCR followed by methyl-sensitive high-resolution melting curve analysis (MS-HRM) was used to determine the extent of methylation of the DNMT1 promoter. The high-resolution melting curve analysis technique, initially developed for genotyping, was adapted to assess site-specific methylation. The data obtained by quantitative assessment of methylation using MS-HRM analysis are comparable to those obtained by pyrosequencing, which validates the method [26].

The website https://www.ebi.ac.uk/Tools/seqstats/emboss_cpgplot/ was used to identify sites within the promoter region of the DNMT1 gene exhibiting a high content of CpG dinucleotides and to select specific primers. When estimating the degree of methylation using HRM analysis, we selected primers that allowed us to avoid errors associated with preferential amplification of unmethylated and/or incompletely converted DNA [27, 28]. Additionally, the alterations that occur during bisulfite conversion were detected according to the criteria delineated in the manual accessible at https://zymoresearch.eu/pages/bisulfite-beginner-guide. Two variants of methylation-independent primers proposed by F. Coppedè et al. [29] for analyzing the methylation level of the promoter region of the DNMT1 gene were used. The primer sequences are presented in Table 2 and the position of the primers on the sequence is schematically depicted in Fig. 1.

 

Table 2 / Таблица 2

The sequences of oligonucleotide primers for bisulfite-converted DNA used to analyze the level of methylation of the DNMT1 promoter region using the MS-HRM method

Последовательности олигонуклеотидных праймеров для конвертированной бисульфитом ДНК, использованные для анализа уровня метилирования промоторной области гена DNMT1 методом MS-HRM

Sequence 5´–3´	Fragment length	CpG sites (n)	Region relative to TSS	Positions on a chromosome
DNMT1_F GCGTTTTGTTTGTTTTTT	106	9	47–151	10194773–10194878 NC_000019.10
DNMT1_R CCCAAATACCCACACTAA
DNMT1_F2 ACGGTTAGTGTGGGTATT	155	21	–87–67	10194857–10195012 NC_000019.10
DNMT1_R2 CCAAACTAAAATAATAAA
DNMT1_F3 GGTATCGTGTTTATTTTTTAGTAA	114	9	–263÷–149	10195084–10195187 NC_000019.10
DNMT1_R3 ACGAAACCAACCATACCCAA

 

Fig. 1. Schematic representation of the DNMT1 promoter region and the positions of the primers used to amplify the promoter region. Cross lines indicate the position of CpG dinucleotides (double lines correspond to CGCG regions). The numbers indicate positions on the chromosome for the sequence NC_000019.10 located in the NCBI

 

The DNMT1 promoter region was amplified using the Roche LightCycler 96 platform (Roche AppliedScience, Laval, PQ, Canada). A previously described protocol [30] was used for PCR and subsequent melting curve analysis. Protocol parameters for all staging conditions were as follows: 1 cycle of 95°C for 12 min, 60 cycles of 95°C for 30 s, 63°C for 30 s, and 72°C for 45 s; followed by HRM 95°C for 10 s and 50°C for 1 min, 65°C for 15 s, and continuous measurement to 95°C with one measurement at 0.2°C. PCR was conducted in a final volume of 50 μl using hot-start TaqM polymerase (AlkorBio LLC), 20 pmol of each primer, and 10 ng of bisulfite-modified DNA matrix. All reactions were performed in triplicate.

Samples with various percentages of methylation were prepared from 100% methylated and unmethylated human DNA control in appropriate ratios and used for calibration. Fully methylated DNA was obtained by reaction with the enzyme CpG-methylase M.SSI (SibEnzyme LLC) from genomic DNA of the human cell line Raji (Evrogen JSC). The amplified PCR product corresponding to the investigated DNMT1 promoter region was used as a sample of fully unmethylated DNA.

The control and test DNA samples were simultaneously subjected to bisulfite conversion. The effective DNA concentration was normalized by pre-PCR to ensure that the difference in Ct threshold cycles for methylated and unmethylated DNA did not exceed two cycles. The procedure involved preparing standard samples (calibrators) with a specified percentage of methylation, ranging from 0% to 100%. Calibrators were included in each run, and the values obtained from them were used to construct standard curves and determine the methylation level for each of the samples under study.

Post-processing of MS-HRM data

The selection of the postprocessing method for MS-HRM data was informed by approaches used in previous studies. The chosen calculation method involves calculation of the Area Under Curve (AUC), which is a derivative of the HRM curve, and comparing AUC values from calibrators with known methylation levels and methylation levels of the samples under study. This method aligns with the study objectives [31].

Melting curves were normalized using the Roche LightCycler 96 software. Difference plots were generated for each normalized melting curve relative to the baseline melting curve, which corresponded to the plot for the 100% methylated control sample. When multiple baseline samples were selected, the data from these curves were averaged and the resulting values were used as reference values for subtraction. After normalization of the difference plot, each curve was displayed as it appears when the AUC value for the baseline is subtracted.

The difference plots for calibrators and test samples were imported into Excel (Microsoft Office 2021) as a text file containing the fluorescence signal measurements data from each point along the temperature gradient. Further calculations were performed using the protocol proposed in Ref. [31] and available at https://dx.doi.org/10.17504/protocols.io.n2bvj6yjxlk5/v1.

Data were analyzed using the Statistica 10.0 software package. Frequencies of alleles and genotypes of the studied polymorphic variants were determined by direct counting and compared between groups using the χ² method and Fisher’s exact test (for groups of <5). The Pearson correlation coefficient was used to test for correlation between DNMT1 mRNA expression level and blood homocysteine content. One-factor analysis of variance (ANOVA) was used to test for significant differences in DNMT1 mRNA levels between the studied groups and to ascertain the impact of genotypes for the studied polymorphisms on DNMT1 expression. Multivariate ANOVA was used to discern the collective influence of multiple independent variables. The data were tested for conformity to the normal distribution using the Kolmogorov–Smirnov test to assess if they met statistical assumptions.

Results

DNMT1 mRNA expression levels were significantly different across the experimental groups (ANOVA, F = 17.5935, p = 0.0003) (Fig. 2). Post-hoc analysis revealed a significant decrease in DNMT1 mRNA levels in patients at MS onset (p = 0.001) and patients with a prolonged disease course (p = 0.013) relative to the control group.

 

Fig. 2. The changes in the DNMT1 mRNA expression level in peripheral blood mononuclear cells in patients with multiple sclerosis (MS). Data are presented as means and the error of the mean; * significant differences between groups according to the results of post-hoc analysis, p < 0.05 (Tukey’s test for unequal samples)

 

These findings are consistent with the data of a previously published study that demonstrated a twofold decrease in the level of DNMT1 mRNA expression in peripheral mononuclear blood cells of MS patients [19]. Furthermore, our study revealed that a significant suppression of DNMT1 expression at the stage of disease onset.

There were no significant difference in degree of methylation of the promoter region of the DNMT1 gene between samples obtained from healthy participants (control) and samples from MS patients. Values of percentage of methylation were 0%–2% in samples from the control group, and 0%–3.5% in samples from MS patients. However, there was a tendency toward a higher percentage of methylation in MS patients than in healthy participants (median 1.94 vs. 1.20). Figure 3 depicts the melting curves for calibration samples spanning 0%–100%. Furthermore, it includes a sample from cells of the HeLa tumor line with a methylation level of approximately 5% (used as a standard with an unknown percentage of methylation) and one of the tested samples.

 

Fig. 3. Normalized melting curves for amplified DNMT1 promoter fragments. Blue lines correspond to melting curves for calibration samples with known percentage of methylation; green line — melting curve for a sample obtained from the HeLa tumor cell line (calculated percentage of methylation 5.5%); orange line — sample obtained from peripheral blood mononuclear cells of a patient with multiple sclerosis (calculated percentage of methylation 1.15%)

 

There was a significant and strong positive correlation between the level of DNMT1 mRNA expression and serum homocysteine content in patients with a disease duration of >1year (Table 3). No correlation between these parameters was observed in patients at the stage of MS onset and in the control group. In the group of patients with a disease duration of >1year, the disease duration was 4–15 years, with a median and interquartile range of 9 years and 7–12 years, respectively. There was no significant correlation between DNMT1 mRNA expression level and disease duration in patients in this group (r = –0.034; p = 0.931). The observed patterns may reflect the interrelation of abnormalities in regulating methylation processes and changes in the functioning of folic acid metabolism and the methionine–homocysteine cycle in the development of the disease.

 

Table 3 / Таблица 3

The data of correlation analysis to assess the relationship between the level of relative expression of DNMT1 mRNA and the content of homocysteine in the blood

Данные корреляционного анализа для оценки взаимосвязи между уровнем относительной экспрессии мРНК DNMT1 и содержанием гомоцистеина в крови

Group	Homocysteine / DNMT1 mRNA
Control group (n = 10)	r = 0.294; p = 0.442
Multiple sclerosis, onset (n = 10)	r = 0.388; p = 0.268
Multiple sclerosis (n = 10)	r = 0.733; p = 0.025

Note: r is Pearson’s correlation coefficient; p is the p value at 5% significance level.

 

The influence of genotypes for MTHFR, MTR, and MTRR gene polymorphisms on DNMT1 expression level was analyzed to determine the potential contribution of folate cycle gene polymorphisms to the mechanisms of epigenetic disturbances in MS. None of the four polymorphic variants studied (C677T, A1298C, A2756G, and A66G) demonstrated an isolated effect of genotype on DNMT1 expression. However, a significant combined effect of genotypes at polymorphisms A2756G of the MTR gene and C677T of the MTHFR gene was observed on DNMT1 mRNA expression level (ANOVA, F = 4.516; p = 0.044) (Fig. 4). A post-hoc analysis revealed significant differences in DNMT1 mRNA expression levels between participants with the CC_C677T/AA_A2756G and those with CC_C677T/AG,GG_A2756G genotypes (p = 0.017, Fisher’s criterion). The CC_C677T/AA_A2756G genotype exhibited the lower DNMT1 expression values.

 

Fig. 4. The combined effect of genotypes for polymorphisms C677T of the MTHFR gene and A2756G of the MTR gene on the level of DNMT1 expression in control group subjects and patients with multiple sclerosis

 

A comparison of the distribution of genotypes for these polymorphic variants in the control group and in the group of MS patients (regardless of disease duration) revealed significant differences (χ² = 10.73; p = 0.014). It turned out that CC_C677T/AG,GG_A2756G genotype was significantly less frequent among MS patients than in the control group (15% and 35%, respectively). So, proportion of combinations of polymorphic variants with the highest values of relative DNMT1 expression was reduced in MS patients. Additionally, the frequency of allele A for the A2756G polymorphism of the MTR gene was significantly higher in the MS patient group than in the control group (χ² = 4.655; p = 0.031).

The observed patterns suggest that the risk of developing disorders associated with reduced DNMT1 expression may be determined, at least partly, by genotype for the A2756G polymorphisms of the MTR gene and the C677T polymorphism of the MTHFR gene.

Discussion

MS is the most common demyelinating diseases. Whole genome analysis revealed significant differences in DNA methylation profiles between MS patients and healthy individuals [32]. These differences affect various genes involved in the regulation of immune cell activity, processes of oligodendrocyte maturation and differentiation, and formation of myelin structure [33–35]. Evidence of decreased expression (at the mRNA and protein levels) of DNMT1 and TET2, enzymes that control DNA methylation and demethylation is crucial for understanding the mechanisms of epigenetic dysregulation in MS. A twofold decrease in DNMT1 mRNA expression in peripheral mononuclear cells from MS patients has been reported in a previous study [19]. Our data are consistent with those of previous studies and further demonstrate that changes in DNMT1 expression are characteristic of patients at the onset of MS.

Targeting the activity of methyltransferases with demethylating drugs is a possible approach for treating MS and other neurodegenerative diseases [36, 37]. Following the discovery of epigenetic changes specific to the pathogenesis of a number of neurodegenerative diseases, the possibility of targeted editing of methylation patterns is also being investigated [38]. Modification of folate metabolism, which is directly related to the regulation of methylation processes, can be considered an alternative and possibly a safer method. The folate cycle and methionine–homocysteine cycle are coupled metabolic pathways that ensure the formation of one-carbon fragments (methyl groups) necessary for the synthesis of DNA, amino acids, and methylation reactions [21]. Experimental studies reported that artificially induced deficiency of nutrients, primarily B vitamins, led to accumulation of homocysteine, a decrease in the rate of its conversion to methionine, deficiency of S-adenosine methionine, and changes in the activity of DNA methyltransferases [39, 40]. Furthermore, the presence of polymorphisms in genes encoding MTR and MTHFR has been reported to be associated with global or gene-specific changes in DNA methylation [41, 42]. The presence of polymorphisms in key genes of the folate cycle can affect the degree of methylation of the promoter region of the DNMT1 gene in peripheral blood mononuclear cells [29]. Particularly, the study demonstrated an increase in the level of DNMT1 promoter methylation in individuals carrying the minor allele G for the A2756G polymorphism of the MTR gene (rs1805087).

The findings of this study did not reveal an isolated effect of polymorphic variants of folate cycle genes on the level of DNMT1 expression. However, we demonstrated the presence of a combined effect of genotypes for polymorphisms C677T of the MTHFR gene and A2756G of the MTR gene. When genotypes CC_C677T/AG,GG_A2756G were combined, DNMT1 expression values were the highest. These findings are consistent with those of previous studies, which indicate that the T allele of the C677T polymorphism is associated with DNA hypomethylation, and the G allele of the A2756G variant of the MTR gene is associated with hypermethylation [41]. Interestingly, the cumulative effect of polymorphic variants of folate cycle genes has been reported previously [43]. For further studies, it would be beneficial to verify the assumption that the genotype CC_C677T/AA_A2756G, which exhibits the greatest reduction in DNMT1 expression levels, will be associated with a greater risk of disease development and/or progression.

Polymorphic variants, C677T and A2756G, are associated with an increased risk of hyperhomocysteinemia. The C–T substitution (C677T of the MTHFR gene) leads to the formation of a thermolabile form of the enzyme, to a decrease in its activity up to 70% in carriers of the CT genotype and up to 30% of the initial level in carriers of the TT genotype, which reduces the efficient formation of the active form of folic acid, 5-methyltetrahydrofolate, a coenzyme in the reaction of homocysteine remethylation [44]. The A2756G polymorphism impairs the function and stability of methionine synthase, encoded by the MTR gene, an enzyme that catalyzes the remethylation of homocysteine into methionine [45]. The correlation between DNMT1 expression and the content of homocysteine, a marker of folate metabolism, revealed in this study and observed only in MS patients with long disease duration, lends support to the hypothesis that folic acid metabolism disturbances contribute to the dysregulation of epigenetic processes in MS. A weak significant inverse correlation between DNMT1 promoter methylation level and homocysteine content was demonstrated previously in a cohort of healthy volunteers [29]. Considering that folate metabolism disturbances are potentially reversible, the investigating the association between epigenetic rearrangements and folic acid metabolism represents a promising avenue for identifying new markers and targets for MS therapy.

Conclusions

This study demonstrates, for the first time, that there is a reduction in DNMT1 expression in MS patients at the disease onset stage. The correlation between DNMT1 mRNA expression, blood homocysteine content, and genotype by MTHFR and MTR gene polymorphisms supports the hypothesis that changes in the metabolism of one-carbon fragments caused by the presence of polymorphic variants of folate cycle genes are involved in the pathogenesis of MS and may contribute to impaired epigenetic regulation.

Additional information

Funding source. The study was carried out with financial support from the Russian Science Foundation (grant No. 23-25-00312).

Compliance with ethical standards. The study was approved by the Local Ethics Committee of the Federal State Budgetary Institution “IEM” (protocol No. 3/23 of September 20, 2023). Before the study, voluntary informed consent was obtained from all subjects whose data are presented in the publication.

Conflict of interest. The authors declare no conflict of interest.

Authors’ contribution. All authors made significant contributions to the conception, conduct of the study and preparation of the article, and read and approved the final version before publication. The largest contribution is distributed as follows: E.A. Tsymbalova — conducting experiments, processing results; E.A. Chernyavskaya — conducting experiments, selecting literature, processing results; D.E. Ryzhkova — conducting experiments, describing, processing results; G.N. Bisaga, I.N. Abdurasulova — discussion of the results; V.I. Lyudyno — concept and management of the work, processing of results, writing the text.

About the authors

Evgenia A. Tsymbalova

Institute of Experimental Medicine

Email: evgesha.tsymbalova@mail.ru

research assistant of I.P. Pavlov Department of Physiology

Russian Federation, Saint Petersburg

Ekaterina А. Chernyavskaya

Institute of Experimental Medicine

Email: kate-chernjavskaja@yandex.ru
ORCID iD: 0009-0003-0421-9819

research assistant of I.P. Pavlov Department of Physiology

Russian Federation, Saint Petersburg

Darja Е. Ryzhkova

Institute of Experimental Medicine

Email: dashstepanova@gmail.com
ORCID iD: 0009-0004-3745-3203

specialist of I.P. Pavlov Department of Physiology

Russian Federation, Saint Petersburg

Gennady N. Bisaga

Almazov National Medical Research Center

Email: bisaga@yandex.ru
ORCID iD: 0000-0002-1848-8775
SPIN-code: 9121-7071

MD, Dr. Sci. (Med.), Professor of the Department of Neurology with the Clinic

Russian Federation, Saint Petersburg

Irina N. Abdurasulova

Institute of Experimental Medicine

Email: i_abdurasulova@mail.ru
ORCID iD: 0000-0003-1010-6768
SPIN-code: 5019-3940

Cand. Sci. (Biol.), Head of I.P. Pavlov Department of Physiology

Russian Federation, Saint Petersburg

Viktoria I. Lioudyno

Institute of Experimental Medicine

Author for correspondence.
Email: vlioudyno@mail.ru
ORCID iD: 0000-0002-1449-7754
SPIN-code: 8980-8497

Cand. Sci. (Biol.), Senior Research Associate of I.P. Pavlov Department of Physiology

Russian Federation, Saint Petersburg

References

Supplementary files