Analysis of STAT1,STAT2 and STAT3 mRNA expression levels in the blood of patients with multiple sclerosis

Abstract

BACKGROUND:

Multiple sclerosis (MS) is the most common chronic, inflammatory, autoimmune disease of the central nervous system (CNS) maintained by the secretion of a large number of cytokines [1]. The signal transducer and activator of transcription (STAT) family has an essential role in transmitting many of the cytokine-mediated signals and failure in the signaling process contributes to the etiopathogenesis of MS.

METHODS:

This study aimed to assess STAT1, STAT2 and STAT3 gene expression in the blood of 50 relapsing-remitting MS (RR-MS) patients and 50 healthy controls by TaqMan Quantitative Real-Time PCR.

RESULTS:

The results showed that STAT1 gene expression was significantly up-regulated ( $p=$ 0.023), whereas STAT2 gene expression was significantly down-regulated ( $p<$ 0.0001) in MS patients compared to controls. On the other hand, there was no significant difference between MS patients and controls for STAT3 gene expression ( $p=$ 0.837). In addition, there was no significant correlation between the expression of STAT1, STAT2, STAT3 genes and clinical findings, such as the level of physical disability in MS patients (according to the Kurtzke Expanded Disability Status Scale (EDSS) criterion) and disease duration.

CONCLUSION:

A significant positive correlation was demonstrated between STAT1 and STAT2 and also between STAT1 and STAT3. This study shows for the first time that a comparison of the relative quantitative expression of three different STAT genes in the blood cells of MS patients compared to controls revealed marked differences in the expression of the STAT family genes that might reflect their different roles in the pathogenesis of MS. These transcripts might be useful biomarkers for evaluating the efficacy of IFN treatment of the MS patients.

Keywords

Multiple sclerosis STAT1 STAT2 STAT3

1. Introduction

Multiple sclerosis (MS) is a chronic, progressive, inflammatory T-Cell – mediated autoimmune disease in thecentral nervous system (CNS) in which some autoimmunityresponses against myelin sheaths lead to plaques [1]. There is increasing recognition that genetics and environmental factors have specific effects on MS susceptibility as they do with many other autoimmune disease [2, 3]. Cytokines and their receptors are critical to the functioning of both innate and adaptive immune responses and play a vital role in the development of the immune system [4].

Because IFN-beta treatment is known to reduce the relapse rate in MS [5], and because IFNs activate the classical Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) signaling pathway, we have focused on this pathway as a possible biomarker of MS remission and response to IFN treatment. The JAK/STAT signaling pathway is one of a handful of pleiotropic cascades utilized by numerous cytokines and is critical for initiating innate immunity, orchestrating adaptive immune systems, and ultimately constraining inflammatory and immune responses [6, 7]. This signaling pathway consists of three main components, a cell surface receptor, a Janus kinase (JAK) and two Signal Transducer and Activator of Transcription (STAT) proteins, that transmit information from extracellular chemical signals to the nucleus resulting in DNA transcription and expression of genes involved in diverse biologic processes including differentiation, apoptosis, cell growth, transformation, inflammation, and immune response [8]. The cell surface receptor is activated by a signal from interferon, interleukin, growth factors, or other chemical messengers. This action activates associated JAKs, increasing their kinase activity. The activated JAK then phosphorylates target tyrosine on the receptor. The phosphotyrosine residues on the receptor proteins are binding sites for other SH2 domain-containing signaling molecules such as the STAT proteins [9]. When STAT binds to the receptor it brings it into a position where it can be phosphorylated by JAK. Once phosphorylated, two STATs can then form hetero- or homodimers (each STAT molecule binds to the phosphotyrosine of the other phosphorylated STAT). The STAT dimer, as an active transcription factor, translocates into the cell nucleus where it binds to DNA and promotes transcription of genes responsive to STAT [10].

The JAK-STAT pathway is expressed in the white blood cells and dysregulation of the pathway can result in immune deficiency and autoimmune diseases such as MS [7, 11]. Excessive production of cytokines, significant enrichment of genes encoding components of the JAK/STAT pathway and loss of expression of negative regulators may contribute to an aberrant activity in the JAK/STAT pathway in MS [6, 12, 13]. There are seven STAT proteins in mammalian cells, Stat1, Stat2, Stat3, Stat4, Stat5a, Stat5b and Stat6, that are encoded by separate genes [8, 14]. Previous studies reported finding changes in the expression of the STAT genes and in the amount of STAT proteins in various inflammatory and autoimmune diseases, such as experimental autoimmune encephalomyelitis (EAE) [10, 15, 16, 17]. Therefore, since the JAK/STAT pathway is a therapeutic target in inflammation, autoimmune diseases, tumors and rejection [7, 18], a more detailed investigation of the expression of the genes involved in this pathway might help to reveal whether they have a role in the etiology of MS [19]. To date, there are few or no published studies on the expression of STAT genes in the peripheral circulation of MS patients or their role in the disease.

The purpose of the present study was to investigate the correlation between the mRNA expression levels of STAT1, STAT2, and STAT3 as biomarkers of MS in a case-control study of 50 patients and fifty controls recruited in Iran. Moreover, we analyzed the correlation between expression of STAT1, STAT2, and STAT3 with Kurtzke Expanded Disability Status Scale (EDSS) and disease duration.

Table 1
Demographic and clinical features of MS patients and healthy controls

Variables	MS patient	Control
Female/Male [no. (%)]	40 (80%)/	29 (55%)/
	10 (20%)	21 (42%)
Age (mean $\pm$ SD, Y)	36.2 $\pm$ 2.9	35.3 $\pm$ 2.1
Age range (Y)	17–55	22–60
Age of onset (mean $\pm$ SD, Y)	31.41 $\pm$ 2.8	–
Relapsing-remitting	100 (100%)	–
course (no. %)
Duration (mean $\pm$ SD, Y)	4.58 $\pm$ 3.2	–
EDSS (mean $\pm$ SD)	3.07 $\pm$ 2.7	–

Table 2

Sequences of the primers and probes used for Real Time PCR

Gene name	Primer sequence	Probe sequence
STAT1	Forward: GAGCACAGTGATGTTAGA	Fam-CATTGGTCTCGTGTTCTCTGTTCT-TAMRA
	Reverse: GCTGTTCTTGTTTCTGATC
STAT2	Forward: GAGCCTTTGTGGTAGAAA	Fam-AGTGACTCATTGCCTTCCTGG-TAMRA
	Reverse: CCTGTCAATGGAGACTTC
STAT3	Forward: CCTTCCTGCTAAGATTCA	Fam-CGCTGATGTCCTTCTCCACC-TAMRA
	Reverse: GACTGGATCTGGGTCTTA
HPRT	Forward: TATATCCAACACTTCG	Fam-AAGCTTGCGACCTTGA-TAMRA
	Reverse: CTTTCCTTGGTCAGG

2. Materials and methods

2.1 Patients and controls

This was a case-control study of 50 Relapsing-Remitting MS (RR-MS) patients (40 females and 10 males, mean age: 35.3 $\pm$ 3.2, age of onset: 28.36 $\pm$ 2.4, duration of disease: 7.2 $\pm$ 3.1, EDSS: 2.98 $\pm$ 3.1) and 50 age and gender matched healthy controls (29 females and 21 males, mean age: 34.8 $\pm$ 2.1). All the patients taking part in this study were HLA-DRB1*15 negative [20], clinically stable in the remission phase, and responsive to interferon-beta. They were prescribed Cinnovex™ as a general treatment strategy [21]. MRI (Magnetic Resonance Imaging) was used to identify MS in RRMS patients based on McDonald criteria [22, 23]. Table 1 provides more details on the MS patients and healthy controls. This study was approved by the local Ethics Committee of Shahid Beheshti University of Medical Science. All the individuals in this study provided written consent forms and the blood samples were collected at Iran’s MS Society Clinic.

2.2 Blood sampling

In this study 5 cc sample of peripheral blood were taken from each individual in both control and disease groups. RNA extraction and cDNA synthesis were done immediately after blood sampling.

2.3 Quantitative Real Time-PCR

Total RNA was extracted from whole blood using GeneAll Hybrid-R ${}^{\text{TM}}$ blood RNA extraction kit (cat No.305-101), according to manufacturer’s instruction. RNA concentration, integrity and quality were verified by spectrophotometry (Eppendorf Biophotometer Plus) and 1% agarose gel electrophoresis. The first-strand cDNA was synthesized from 2 $\mu$ g of total RNA by using the Biosystems High-Capacity cDNA Reverse Transcription Kit (PN: 4375575). The software program allele ID 7 (Premier Biosoft, Palo Alto, USA) was used to design the specific probes and primers for the STAT1, STAT2 and STAT3 sequences (Table 2). Gene expression levels for each sample were normalized to the expression level of the reference gene hypoxanthine phosphoribosyltransferase (HPRT1) that was amplified using specific primers and probe of the HPRT1 sequence (Table 2). Real-time Quantitative PCR was performed with the Corbett Rotor Gene 6000 machine (Corbett Life Science) and the Biosystems TaqMan ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ , Universal PCR Master Mix (PN: 4304449).

2.4 Statistical methods

The expression levels in the case and control groups were compared using an independent t-test. P values and CI 95 % for mean differences were estimated by bootstrapping. Pearson correlation coefficient was applied to identify the level of correlation between the variables under study. The level of significance was set at a p value of $\leqslant$ 0.05. The analyses were performed using SPSS version 18, serving as Windows statistical package (Chicago, IL, USA).

Table 3
STAT1 expression levels in RR-MS patients compared with control group, based on age and sex of the participants

STAT1 expression		Control no.	RR-MS patient no.	p value	Expression ratio	Std.error	95% CI
Total		50	50	0.023	1.631	0.45	$-$ 1.934–	$-$ 0.144
Male		21	10	0.067	2.091	0.83	$-$ 3.3–	$-$ 0.597
Female		29	40	0.212	1.361	0.532	$-$ 1.733–	0.391
$<$ 30	Male	13	2	0.81	1.337	1.81	$-$ 2.58–	1.7
	Female	17	13	0.575	1.247	0.805	$-$ 2.05–	1.101
30–40	Male	4	4	0.13	5.488	1.85	$-$ 8.5–	$-$ 1.044
	Female	9	17	0.589	1.169	0.942	$-$ 2.37–	1.42
$>$ 40	Male	4	4	0.9	1.069	1.609	$-$ 3.21–	3.04
	Female	3	10	0.536	0.797	0.719	$-$ 0.77–	1.95

Table 4

STAT 2 expression levels in RR-MS patients compared with control group, based on age and sex of the participants

STAT2 expression		Control no.	RR-MS patient no.	p value	Expression ratio	Std.error	95% CI
Total		50	50	$<$ 0.0001	0.409	0.579	$-$ 3.914–	$-$ 1.6
Male		21	10	0.082	0.382	1.43	$-$ 5.27–	0.051
Female		29	40	0.002	0.515	0.617	$-$ 3.9–	$-$ 1.444
$<$ 30	Male	13	2	0.711	2.091	4.98	$-$ 5.06–	9.52
	Female	17	13	0.099	0.808	1.015	$-$ 3.51–	0.361
30–40	Male	4	4	0.022	0.308	1.07	$-$ 8.47–	$-$ 4.28
	Female	9	17	0.017	0.411	0.942	$-$ 5.2–	$-$ 1.464
$>$ 40	Male	4	4	0.456	1.051	1.32	$-$ 4.05–	0.99
	Female	3	10	0.028	0.367	0.957	$-$ 4.53–	$-$ 0.947

Table 5

STAT3 expression levels in RR-MS patients compared with control group, based on age and sex of the participants

STAT3 expression		Control no.	RR-MS patient no.	p value	Expression ratio	Std.error	95% CI
Total		50	50	0.837	1.04	0.61	$-$ 1.35–	1.099
Male		21	10	0.692	1.303	1.8	$-$ 4.58–	2.58
Female		29	40	0.992	0.984	0.639	$-$ 1.282–	1.27
$<$ 30	Male	3	2	0.931	0.778	3.96	$-$ 6.08–	6.63
	Female	17	13	0.847	0.944	0.778	$-$ 1.39–	1.68
30–40	Male	4	4	0.644	1.146	1.026	$-$ 2.61–	1.3
	Female	9	17	0.751	0.773	1.163	$-$ 1.89–	2.85
$>$ 40	Male	4	4	0.856	0.67	4	$-$ 7.67–	6.65
	Female	3	10	0.453	1.986	1.66	$-$ 3.99–	2.22

3. Results

3.1 Patients and controls

In this study, the study samples were divided into (a) the total number of participants (regardless of age and sex) and (b) two subgroups (based on participants’ sex and age ( $<$ 30, 30–40, 40 $<$ years). Separate computations were carried out for the total numbers in each group and for each of the subgroups. TaqMan Real-Time-PCR was used to compare the expression level of STAT1, STAT2, and STAT3 genes between the RR-MS patients and a group of normal individuals.

3.2 Expression levels of the STAT genes

Table 3 shows the results of the total STAT1 expression level in RR-MS patients compared with control group as well as those based on age and sex of the participants. Statistical analysis revealed a significant up-regulation in the expression of STAT1 gene in MS patients versus healthy controls ( $P=$ 0.023). This up-regulation was 1.63 times higher than the control group. Up-regulation was limited to the overall total (i.e. all the participants together, regardless of sex and age). Sex and age linked computations showed an increase in STAT1 expression as well, but the increase was not statistically significant.

Table 4 shows the results of the total STAT2 expression level in RR-MS patients compared with control group as well as those based on age and sex of the participants. STAT2 mRNA levels were significantly down-regulated in the RR-MS patients in comparison with the controls ( $P=$ 0.0001). The STAT2 mRNA levels were down-regulated in all categories (i.e. the total and two subgroups), but only in the subgroup of patients between 30–40 and females over 40 years were significant.

Table 5 shows the results of the total STAT3 expression level in RR-MS patients compared with control group as well as those based on age and sex of the participants. Compared to normal individuals, STAT3 expression level in MS patients showed a slight increase in all categories (i.e. the total and two subgroups), but the increase was not statistically significant.

3.3 STAT genes expression level among RR-MS patient based on age and sex

No significant association was demonstrated between male and female patients in the STAT genes expression levels (Supplementary Table 1).

3.4 Correlation between STAT1, STAT2, and STAT3 gene expression levels with EDSS or disease duration

To find a possible correlation between the expression of STAT1, STAT2 and STAT3 gene expression with EDSS and disease duration among the RR-MS patients Pearson correlation was performed. As can be seen in Supplementary Fig. 1 that there is no significant linear correlation between the variables under study, neither in STAT1, STAT2 nor the STAT3 gene. Similarly, Supplementary Fig. 2 shows no significant correlation between expression status and duration of the disease for the three STAT genes.

3.5 Correlation among STAT genes expression

Correlation between STAT1 and STAT2, STAT1 and STAT3 and STAT2 and STAT3 expression level in patient group are shown in Supplementary Fig. 3. Positive correlations between STAT1 and STAT2 and also STAT1 and STAT3 were demonstrated ( $p=$ 0.039, $R^{2}=$ 0.049; $p=<$ 0.0001, $R^{2}=$ 0.299, respectively).

4. Discussion

The aim of the present study was to investigate the correlation between the expression levels of STAT1, STAT2, STAT3 genes and risk of MS. Our results showed that the STAT1 expression level was significantly up-regulated, whereas the STAT2 expression level was significantly down-regulated in MS patient versus controls. On the other hand, there was no significant difference in the STAT3 gene expression between patients and controls ( $P$ value $=$ 0.837). To the best of our knowledge, there are no previous reports about STAT gene expression profiling in human MS patients to directly compare with our results and provide comparative conclusions. Thus, the reasons for and the exact mechanisms underlying the up-regulation of STAT1 and down-regulation of STAT2 in blood of MS patients is not well understood, although other studies point towards important mechanisms such as the complex cross-talk between cytokines secreted by cells of the adaptive system, cytokines secreted by innate immune cells [6, 10, 16], and the vital role of the STAT protein family in Th1 and Th17 cell proliferation and differentiation [24, 25, 26, 27, 28]. Various cytokines including type I and type II IFNs utilize the STAT pathways, and the roles of different JAKs and STATs in immunoregulation and immunopathology provide an opportunity to study how dysregulation of STAT pathways might contribute to autoimmune diseases such as MS [10, 29, 30, 31]. Thus, different cytokines and biochemical pathways in cytokine signaling that are involved in immune mediated diseases, now supported by GWAS data, are attractive pharmacological targets for developing treatments [32].

A complicating factor in the present study is that the MS patients under investigation were in remission and receiving IFN-b treatment. The effectiveness of IFN-b therapy is difficult to monitor [33] and the clinical response to IFN-b therapy may exhibit considerable variability in the number and types of MS relapsed cases [34]. Moreover, the effectiveness of IFN therapy can vary between men and women because of the marked physiological differences between the genders in their immune response [35]. For example, IFN treatment is sensitive to the regulation of the female hormone, estrogen [36], and estrogen affects all the major cells of the immune system including T and B cells, macrophages, dendritic cells and natural killer cells [33, 35, 36, 37]. In this regard, it is interesting that the down-regulation of STAT2 gene expression in the patients with MS was more significant in the women than in the men who were over forty years of age (Table 4). Moreover, IFNs are known to induce STAT gene expression (REFS) and their positive or negative responsiveness to IFN treatment might indicate defects in the signaling pathway or an autocrine or refractory effect that may have consequences in disease pathogenesis. Thus, further studies are need to determine whether the changes in STAT mRNA blood levels might be used to predict relapses in patients diagnosed with MS or as biological markers for monitoring the effectiveness of IFN-b therapy.

A possible explanation for the increased expression of STAT1 in the blood cells is the increased expression of inflammatory cytokines including IL-12, IFN- $\gamma$ , IL-6, IL-21, and IL-23. Considerable research has described a number of negative regulators of the JaK-STAT signaling pathway, including suppressors of cytokine signaling (SOCSs), tyrosine phosphatases and protein inhibitors of activated STAT (PIASs) [37, 38]. An increase or decrease in the expression of any of these regulators might then affect the expression of the STAT genes. This is possibly due to other molecules like chaperones and noncoding RNAs (microRNA, long noncoding RNA), which seem to be important effectors of the JAK/STAT pathway [39, 40, 41]. The changes in expression of STAT1 and STAT2 that we observed in this study indicate a role for these genes in MS disease. However, it is not clear whether the up-regulation and down-regulation of these two genes are causes of MS or whether they simply reflect the changing aspects of the disease. Further studies are required to resolve this question.

IL-12 and interferon-gamma (IFN- $\gamma$ ) are known to be involved in the pathogenesis of immune disorders of the CNS [42, 43]. It has been well established that STAT1 and STAT2 play an obligatory role in IFN- $\gamma$ and IL-12 biological responses [30, 44]. Multiple sclerosis and EAE are similar autoimmune diseases in that they are closely linked with IL-12 and IFN- $\gamma$ in the development of type 1 cellular immune responses [45, 46, 47]. Our result for the up-regulation of STAT1 is in line with the observations of Maier et al. [48] in their EAE model of symptomatic transgenic mice, but in disagreement with the observed changes in STAT2 gene expression. Smita Zaheer et al. [49] also observed significant up-regulation in the expression of STAT1, STAT2, STAT3 and STAT4 in the brains and spinal cords of wild type mice exhibiting EAE symptoms and in the whole blood of MS patients, and the components of JAK/STAT pathway were found to be activated in various other models of EAE [13, 50, 51, 52, 53, 54, 55]. In contrast, Holcar et al. [56] found a significantly lower expression of total STAT1 protein in CD4+ T cells of adolescents that was associated with the increase in activated Treg. While we cannot make a direct comparison between the results of these animal studies and our results of the MS case-control study, the varying results among the different studies illustrate the complexity of the factors, signals, and responses that need to be taken into account when considering the interactions of the immunomodulatory cytokines in different types of autoimmune disease. Furthermore, variations in STAT gene expression in blood samples of individuals with MS might be expected because no two people have exactly the same symptoms or respond to treatment in the same way. In this regard, longitudinal studies of individuals treated with IFN for MS might help to reveal the serial changes in STAT gene expression and effectiveness of IFN treatment.

A limitation in our study that can be improved in future was the low sample number of MS patients. Although we could not find a significant correlation between EDSS and duration of the disease and STAT expression, the use of a greater number of MS patients in future studies might help to better partition the patients and improve the statistical analysis. Since these results were obtained for the first time in MS disease, we recommend further studies using a larger sample pool to further investigate the results reported in the current work. Our data is still preliminary and additional studies in other populations could help to better define the profile of STAT expression and the role of STATs in MS.

5. Conclusion

Our study has shown that STAT1 was up-regulated and STAT2 was down-regulated in RR-MS patients with no significant difference in the STAT3 gene expression between patients and controls. There was a positive correlation between STAT1 and STAT2 and between STAT1 and STAT3, and these changes in STAT gene expression may be useful for monitoring the effectiveness of IFN-b treatment of MS.

Footnotes

Acknowledgments

The present article is financially supported by “Research Department of Medicine School, Shahid Beheshti University of Medical Sciences (Grant No.: sbmu.REC.1393.597)”.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary data

The supplementary files are available to download from https://dx-doi-org.web.bisu.edu.cn/10.3233/HAB-180352.

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Analysis of STAT1,STAT2 and STAT3 mRNA expression levels in the blood of patients with multiple sclerosis

Abstract

BACKGROUND:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

Table 1 Demographic and clinical features of MS patients and healthy controls

2.1 Patients and controls

2.2 Blood sampling

2.3 Quantitative Real Time-PCR

2.4 Statistical methods

Table 3 STAT1 expression levels in RR-MS patients compared with control group, based on age and sex of the participants

3.1 Patients and controls

3.2 Expression levels of the STAT genes

3.3 STAT genes expression level among RR-MS patient based on age and sex

3.4 Correlation between STAT1, STAT2, and STAT3 gene expression levels with EDSS or disease duration

3.5 Correlation among STAT genes expression

4. Discussion

5. Conclusion

Footnotes

Acknowledgments

Conflict of interest

Supplementary data

References

Table 1
Demographic and clinical features of MS patients and healthy controls

Table 3
STAT1 expression levels in RR-MS patients compared with control group, based on age and sex of the participants