1. Introduction
Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS) [
1]. The incidence and prevalence rates of this disease are increasing worldwide. According to the Atlas of MS, 3rd edition, prepared by the Multiple Sclerosis International Federation, approximately 2.8 million people worldwide have MS. Lithuania belongs to the region of high prevalence and morbidity of MS (prevalence per 100,000 people is 101–200) [
2]. MS is most commonly diagnosed in people between 20 and 40 years of age. Less commonly, it occurs in childhood (less than 1%) and after the age of 50 (about 2–10%) [
3]. Moreover, MS is 2 to 3 times more common in women than in men [
4]. MS is a multifactorial disease whose development is influenced by genetic and environmental factors [
5]. Several pathological processes contribute to the development of MS, including blood–brain barrier (BBB) damage, multifocal inflammatory responses, demyelination, oligodendrocyte death, reactivated gliosis, and axonal degeneration [
6].
According to recent studies, cellular senescence caused by telomere shortening may contribute to the development of MS [
5]. To maintain the integrity of the genome, telomeres protect chromosomes from end fusion and degradation by exonucleases. Telomeres are specialized structures located at the ends of eukaryotic chromosomes, and are composed of tandem nucleotide repeats (TTAGGG) and proteins [
7]. When telomeric DNA regions are critically shortened, they can signal replicative senescence of somatic cells and chromosome instability [
8]. Telomerase is a ribonucleoprotein enzyme critical for replicating telomeric sequences in chromosomal DNA. The enzyme complex includes several components, including the telomerase RNA component (TERC), telomerase reverse transcriptase (TERT), dyskerin, and other accessory proteins such as TEP1 [
8,
9].
TERC binds to the 3′ end of chromosomes and provides a template sequence for reverse transcription catalysed by TERT [
10]. According to recent studies, TERC inhibits apoptosis in immune cells, protects neurons from oxidative stress, and enhances cellular inflammatory responses [
11]. TERC has been shown to increase the expression and release of inflammatory cytokines by directly binding to the promoters of the
LIN37,
TPRG1L,
TYROBP, and
USP16 genes. These four genes encode proteins involved in the activation of the transcription factor nuclear factor κB (NF-κB) [
11,
12]. Inflammatory responses lead to the progressive shortening of telomeres, which has been linked to the development of age-related diseases [
13]. It has been observed that naive CD4
+ T cells from patients with rheumatoid arthritis exhibit increased telomerase inhibition, resulting in shortened telomeres due to decreased expression of TERT and TERC. For this reason, T cell subset aging is accelerated, and autoimmunity is activated [
14]. TERC levels have been shown to be increased in individuals with MS or type II diabetes. It should be noted that these two diseases are associated with inflammatory responses [
12].
The
TERC gene is located on the long arm of chromosome 3 at position 26.2 (3q26.2) [
15].
TERC is responsible for regulating telomere length [
16]. Studies in mice have shown that
TERC is involved in neural progenitor cell (NPC) proliferation. It has been observed that, in mice in which the
TERC gene is knocked out, there is a statistically significant decrease in the proliferation of NPC. It has also been found that neurons cannot fully mature when the
TERC gene is knocked out in NPC [
17]. In addition, studies have shown that
TERC gene polymorphisms influence the development of Alzheimer’s disease [
18]. Since a relationship between
TERC and MS has been established in the scientific literature, we decided to analyse the SNP rs12696304 and rs35073794 of the
TERC gene. Polymorphisms in the
TERC gene have been associated with changes in telomere length due to altered telomerase activity [
19,
20,
21]. The SNP rs12696304 C > G is located in the downstream region of the
TERC gene, i.e., 1.5 kb away from the transcription start nucleotide [
21]. The rs35073794 A > G SNP is also located in the downstream region of the
TERC gene [
20]. Thus, polymorphisms in the
TERC gene may promote cellular senescence by altering the stability of the telomerase complex or directly affecting the enzymatic activity of telomerase [
18].
TEP1 is responsible for RNA and protein binding and is involved in the regulation of telomere length [
22,
23].
TEP1 is thought to function as a structural protein by binding to
TERC and acting as a regulatory subunit to mediate the interaction of telomerase with other molecules [
24]. In addition,
TEP1 and dyskerin are responsible for stabilizing the structure of telomerase [
25]. In addition,
TEP1 directly interacts with the BLM protein of Bloom syndrome and regulates its helicase activity. Thus, it can be assumed that
TEP1 is involved in telomere lengthening [
26].
The
TEP1 gene is located on the long arm of chromosome 14 at position 11.2 (14q11.2) [
27]. According to NCBI, the
TEP1 gene consists of 55 exons [
28]. This gene is responsible for telomere elongation and prevents neuron development due to DNA damage. Ren et al. found that
TEP1 is associated with white matter microstructure abnormality in schizophrenia [
29]. Using whole-exome sequencing, Sebate and colleagues discovered that pathogenic mutations in the
TEP1 gene contribute to the neurodegenerative disease known as Parkinson’s [
30]. According to the available data, there have been no studies investigating the association between
TEP1 and MS. Based on previous studies on neurological disorders, it can be assumed that the
TEP1 gene is involved in MS. In this study, we aimed to determine the influence of the
TEP1 gene SNP rs1760904 and rs1713418 on the occurrence of MS. The SNP rs1760904 A > G is located in the exon region of the
TEP1 gene [
23,
26]. Rs1760904 is a nonsynonymous SNP that causes a proline-to-serine substitution (Ser1195Pro) that may affect the
TEP1 structure and telomerase [
26]. Rs1713418 A > G SNP is located in the 3′UTR region of the
TEP1 gene [
26]. SNP in the 3′UTR alters the ability of miRNA to bind to the target gene, which affects gene regulation and increases the risk of MS [
31].
The selected polymorphisms were chosen based on their potential relevance to our research topic. These specific genetic variants have previously been associated with biological processes related to telomere length in various studies [
18,
19,
20,
21]. By investigating the selected SNPs (rs1760904, rs1713418, rs12696304, and rs35073794), we aim to explore their potential contributions to the occurrence of multiple sclerosis. As mentioned above, each polymorphism is located within genes or regions that play crucial roles in telomere length regulation. As such, variations in these genetic loci may have functional consequences that interest us for our study. Therefore, this study aimed to determine the associations of
TEP1 rs1760904, rs1713418 and
TERC rs12696304 and rs35073794 polymorphisms with occurrence in MS patients.
2. Materials and Methods
The study was performed at the Department of Neurology, Lithuanian University of Health Sciences and in the Ophthalmology laboratory, Neuroscience Institute, Lithuanian University of Health Sciences. Ethical approval for this study was obtained from the Kaunas Regional Biomedical Research Ethics Committee (No. BE-2-102, issued 14 November 2019). Each study participant signed the informed consent form. The subjects were divided into two groups:
Patients were excluded if they had other systemic illnesses (diabetes mellitus, oncological diseases, systemic tissue disorders, chronic infectious diseases, autoimmune diseases, conditions after organ or tissue transplantation), eye optic system obscuration, or poor fundus photography quality.
The demographic factors of the patients in the study’s MS group and the control group, i.e., age and gender, were evaluated in this study. The subjects were divided into <44 years old and ≥44 years old.
2.1. DNA Extraction and Genotyping
Genomic DNA was extracted from peripheral blood leukocytes by a salting-out method. Genotyping of TEP1 rs1760904, rs1713418 and TERC rs12696304, rs35073794 was performed by real-time polymerase chain reaction (RT-PCR). To determine SNPs, we used TaqMan® genotyping assays (Applied Biosystems, New York, NY, USA; Thermo Fisher Scientific, Inc., Waltham, MA, USA) according to the manufacturer’s recommendations. The assay IDs were C___1772362_20 (TEP1 rs1760904), C___8921332_10 (TEP1 rs1713418), C____407063_10 (TERC rs12696304), and C__58097851_10 (TERC rs35073794).
2.2. Statistical Analysis
The statistical analysis of the scientific work was carried out using “IBM SPSS Statistics 29.0.”. This study used Kolmogorov–Smirnov and Shapiro–Wilk tests to evaluate the hypothesis regarding the normal distribution of the measured trait values. Because the subjects’ characteristics did not meet the requirements of a normal distribution, the following descriptive statistics were used: median and interquartile range (IQR).
The χ2-test and Fisher’s exact test were used to compare the homogeneity of the genotypes and allele distributions of the TEP1 rs1760904, rs1713418, TERC rs12696304, and rs35073794 gene polymorphisms. In addition, binary logistic regression was performed to evaluate the influence of genotypes and alleles on the occurrence of MS. Considering inheritance models and genotype combinations, the odds ratio (OR) was determined with a 95% confidence interval (CI). According to the Akaike Information Criterion (AIC), the model with the lowest value is the most appropriate inheritance model. As part of the analysis, the program “SNPStats” was also used to analyse the haplotypes. An evaluation of the linkage disequilibrium between the studied gene polymorphisms was performed. The deviation between the expected haplotype frequency and the observed frequency (D’) was calculated, and the square of the correlation coefficient of the haplotype frequency (r2) was evaluated.
4. Discussion
In our study, we analysed the polymorphisms of the
TEP1 gene rs1760904, rs1713418, and the
TERC gene rs12696304 and rs35073794 in 200 MS patients and 230 healthy individuals, because the SNPs we selected have not been studied in scientific research on the pathogenesis and development of MS. It should be noted that aging and genetic variants affecting telomere length, telomerase activation, and telomeric protein configuration can cause functional changes in cells [
26,
34]. Bühring, along with co-authors, prepared a meta-analysis which found seven studies on telomere length in MS indicating shorter telomeres in MS patients compared to controls, linked to increased disability and disease progression. This suggests a connection between aging, inflammation, and MS. TL assessment may be a disease progression biomarker. However, further research, including cell-specific analysis, is needed in order to understand MS’s pathophysiology and fully develop targeted therapies [
35].
Sipos and co-authors found that TEP1 expression increases in ulcerative colitis during mild inflammation [
36]. Gu and co-authors found that
TEP1 rs1713418 AG + AA genotypes were associated with 1.3-fold increased odds of prostate cancer in individuals younger than 69 years compared with the AA genotype (OR: 1.32, (95% CI: 1.02–1.70),
p = 0.034). However, the AG + GG genotype of the same polymorphism was associated with 1.4-fold lower odds of prostate cancer in individuals older than >69 years compared to the AA genotype (OR: 0.71, (95% CI: 0.55–0.92),
p = 0.010) [
26]. Sun et al. found that
TEP1 rs1713418 was associated with 1.3-fold increased odds of ovarian cancer occurrence (OR: 1.33, (95% CI: 1.08–1.65),
p = 0.009) [
37]. It should be noted that excessive or persistent inflammation contributes to carcinogenesis and tumour progression through the activation of inflammatory molecules and signals [
38]. Our study found that the
TEP1 rs1713418 GG genotype was associated with 2.2-fold increased odds of MS occurrence in individuals older than 44 years compared with the AG and AA genotypes (OR: 2.191, (95% CI: 1.020–4.708),
p = 0.044).
Chan and co-authors performed a haplotype analysis and found that the
TEP1 haplotype, consisting of the SNP allele variants rs1713418, rs2104978, rs17211355, rs2297615, rs2228041, rs2228026, and rs1713440, was associated with 2.2-fold increased odds of bladder cancer occurrence (OR: 2.23, (95% CI: 1.13–4.60),
p = 0.022) [
39]. This study revealed that chronic inflammation may play a role in the development of malignancies, including bladder cancer [
38]. Our haplotype analysis revealed that the rs1760904-G—rs1713418-A haplotype was statistically significantly associated with a 1.7-fold increased likelihood of developing MS (OR: 1.740, (95% CI: 1.180–2.560),
p = 0.006). The rs1760904-A—rs1713418-G haplotype was statistically significantly associated with a 1.9-fold increased probability of the occurrence of MS (OR: 1.920, (95% CI: 1.140–3.240),
p = 0.014).
Liu et al. found that TERC expression was increased more significantly in MS patients than in healthy individuals (
p < 0.01) [
12]. Scarabino and co-authors found that the
TERC rs12696304 GG genotype correlated with the occurrence of Alzheimer’s disease [
18]. In addition, the results of a study conducted by Sun and co-authors suggested that the
TERC gene rs12696304 G allele and GG genotype were statistically significantly associated with 1.6-fold increased odds of developing chronic kidney disease (OR: 1.555, (95% CI: 1.215–1.990),
p = 0.001; OR: 1.634, (95% CI: 1.201–2.234),
p = 0.002, respectively). In addition, the researchers found that the G allele of the same polymorphism was associated with 1.8-fold increased odds of developing chronic kidney disease in the female group (OR:1.816, (95% CI: 1.248–2.641),
p = 0.002), and the GG genotype was associated with 2-fold increased odds of developing chronic kidney disease in the female group (OR: 1.959, (95% CI: 1.233–3.114),
p = 0.006). The authors also found that the rs12696304 G allele could contribute to a host autoimmune response targeting glomerular tissues by activating the NF-κB pathway via TERC [
14]. It is known that secretory renal dysfunction (decreased synthesis of vitamin D, erythropoietin, and Klotho protein) may contribute to brain dysfunction in MS patients [
40]. According to the results of Al Khaldu and co-authors, the genotype of
TERC gene rs12696304 GG was associated with a 1.6-fold increased probability of developing type 2 diabetes (OR: 1.6, (95% CI: 1.5–1.9),
p = 0.005) [
41]. It should be noted that diabetes, like MS, is associated with increased oxidative stress and inflammatory responses, which may accelerate telomere shortening and associated cellular senescence [
42].
After performing binary logistic regression, we found that the
TERC gene rs12696304 G allele was associated with a 1.4-fold decrease in the likelihood of the occurrence of MS (OR: 0.703, (95% CI: 0.506–0.976),
p = 0.035).
TERC rs12696304 was associated with a decreased probability of the occurrence of MS in males according to the codominant, dominant, and additive models (5.5-fold (OR: 0.182, (95% CI: 0.037–0.894),
p = 0.036), 2-fold (OR =0.507, (95% CI: 0.284–0.903),
p = 0.021), and 1.9-fold (OR: 0.515, (95% CI: 0.314–0.845),
p = 0.009). However, we found no statistically significant associations between these polymorphisms and MS risk in females. It is well-known that genetic factors contributing to disease susceptibility can vary between genders [
43]. This phenomenon can arise due to hormonal differences or gender-specific gene expression. Hormones such as oestrogen and testosterone can influence immune responses, interact with genetic factors, and might affect the risk of autoimmune diseases like MS [
44].
Wu and co-authors found that
TERC rs35073794 was associated with 2.4-fold increased odds of renal cell carcinoma (RCC) occurrence in an allele model (A/G) (OR =2.39, 95% CI = 0.99–5.80,
p = 0.047). The authors also found that the rs35073794 AG genotype is associated with a 2.6-fold increased odds of RCC risk with adjustment for gender, age and BMI (OR =2.61, 95% CI = 1.01–6.76,
p = 0.045) [
20]. We found that
TERC rs35073794 is associated with about 2.4-fold decreased odds of MS development under the codominant, dominant, overdominant, and additive models (OR: 0.408, (95% CI: 0.275–0.603),
p < 0.001; OR: 0.412 (95% CI: 0.279–0.610),
p < 0.001; OR: 0.404 (95% CI: 0.273–0.598),
p < 0.001; OR: 0.427 (95% CI: 0.289–0.629),
p < 0.001, respectively).
TERC rs35073794 is associated with about 4.4-fold decreased odds of MS occurrence in men according to the codominant, dominant, and overdominant models (OR: 0.228, (95% CI: 0.124–0.417),
p < 0.001; OR: 0.233 (95% CI: 0.128–0.427),
p < 0.001; OR: 0.224 (95% CI: 0.122–0.410),
p < 0.001, respectively). Furthermore, for
TERC rs35073794, each A allele was associated with 3.9-fold decreased odds of MS occurrence (OR: 0.256, (95% CI: 0.141–0.462),
p < 0.001).
TERC rs35073794 was associated with about 3.4-fold decreased odds of subjects younger than 44 years of age developing MS according to the dominant, overdominant, and additive models (OR: 0.295, (95% CI: 0.173–0.503),
p < 0.001; OR: 0.295 (95% CI: 0.173–0.503),
p < 0.001; OR: 0.295 (95% CI: 0.173–0.503),
p < 0.001, respectively).
Based on haplotype analysis, Maubaret and colleagues found that the
TERC rs12696304-G-rs10936601-T-rs16847897-C haplotype was statistically significantly associated with a 1.35-fold reduction in the risk of developing type 2 diabetes (OR: 0.74, (95% CI: 0.61–0.91),
p = 0.004) [
45]. According to our haplotype analysis, the rs12696304-C-rs35073794-A haplotype was associated with a twofold reduction in the likelihood of developing MS (OR: 0.51, (95% CI: 0.32–0.84),
p = 0.008). In addition, we discovered that the rs12696304-G-rs35073794-A haplotype was associated with a 5.3-fold reduction in the probability of MS occurrence (OR: 0.19, (95% CI: 0.08–0.49),
p < 0.001).
In our study, we acknowledge several limitations. It is important to note that genetic determinants of telomere length may exhibit variations across different racial and ethnic groups. Our study was conducted exclusively among Lithuanian participants, which may limit the generalizability of our findings to more diverse populations. Future research should consider including a more ethnically and racially diverse sample in order to better understand the potential variability in genetic associations with telomere length. Also, for more accurate results, the sample size should be increased.
The study exhibits strengths in its rigorous methodology, which is characterized by clear objectives, appropriate sample sizes, and robust data collection. These elements significantly enhance the reliability and validity of our study’s findings. Additionally, the study adhered to standardized protocols and procedures, enabling the potential for replication and facilitating comparability with other studies.
There is evidence that telomere-related genes play a critical role in carcinogenesis. However, it is still unclear whether alterations in telomere-related genes may contribute to the progression and occurrence of MS [
26]. Therefore, this study warrants further research to explain the pathogenesis of MS and the impact of telomere-related gene alterations on its development.