Анализ иммунологической памяти Джона Каннингема о мексиканском населении пациентов с множественным склерозом под лечением.

1. Introduction

Multiple sclerosis (MS) is a chronic, progressive, immune-mediated disease characterized by demyelination and axonal damage of the central nervous system (CNS). It mainly affects women between 20 and 40 years of age [ 1 ]; its incidence varies from 2 to 9.6 per 100,000 inhabitants per year; the prevalence in the USA in 2010 was 309.2/100,000 inhabitants; and the female–male ratio was 2.8:1. In 2017, the prevalence increased by 9% compared to 2010 (338/100,000 inhabitants) [ 2 ].

MS is considered to have a complex, polygenic, and multifactorial etiology. More than 200 susceptibility variants have been proposed at the MHC-encoding loci 6p21.3 [ 3 ]. The HLA-DRB1*1501 allele is the variant most associated with the risk of developing MS in different populations, with heritability being ~30% in Northern Europe, 15% in Italy, and 6% in France. This trend represents the impact of the environment on a genetically predisposed host [ 4 ]. This predisposition is confirmed by the discrepancy in the risk of MS in the general population of 0.3% and its tenfold increase in first-degree relatives [ 1 ].

Inflammation in MS is a prominent phenomenon and is attributed to the adaptive autoimmune response mediated by T and B lymphocytes against the CNS [ 5 ]. Neuroaxonal degeneration is probably the main biological target of progression; however, chronic inflammation contributes to tissue loss and disability [ 6 ]. In the last 30 years, so-called disease-modifying therapies (DMTs) have been developed, with the main purpose to reduce early disease activity and thus reduce long-term disability [ 7 ].

Among the DMTs, monoclonal antibodies (mAbs) are known as highly effective treatments (HETs) [ 8 ]; however, they have the highest risks [ 9 ]. Natalizumaf, a recombinant humanized IgG4κ antibody selective for α4-integrin (VLA-4) that prevents leukocyte migration through the blood–brain barrier (BBB) [ 10 ], reduces relapses by 67%, reduces new MRI lesions by 83%, and limits confirmed disability progression (DRP) by 42%. It is used as a monotherapy for MS; however, among the serious adverse effects is the increased risk of developing progressive multifocal leukoencephalopathy (PML), where the estimates vary widely from 1 in 90 [ 11 ] to 0.7/1000 treated patients. What remains consistent is that the risk increases up to 2.7 times if the host has antibodies for the John Cunningham virus (JCV) [ 12 ]. Other mAbs have been reported to be associated with the development of PML, such as rituximab, daclizumab, alemtuzumab, efalizumab, and ofatumumab [ 13 ], and non-mAb DMTs such as dimethyl fumarate [ 14 ] and fingolimod [ 15 , 16 ]. The common denominator of these HETs is a decrease in immune response.

PML is a rare, demyelinating, inflammatory, subacute CNS disease related to JCV infection, with a mortality rate of 30% [ 17 ]. JCV is a polyomavirus that causes asymptomatic infection in the early stages of life in immunocompetent populations and remains latent throughout the life of the host; when JCV is reactivated, it is because of immunological deterioration and produces a neurological condition characterized by cognitive and behavioral changes, language disorders, weakness, and visual deficits. In Mexico, our group published the only report on progressive multifocal leukoencephalopathy (PML) in a patient with multiple sclerosis (MS) treated with natalizumab [ 18 ].

Based on what has been described, the hypothesis of this study is that the prevalence of immunological memory for the JC virus (JCV) in Mexican MS patients treated with natalizumab is either equal to or higher than that in underdeveloped countries (60%) and is positively correlated with factors such as disease duration and type of treatment. The aim of this research was to assess, determine, and analyze the immunological memory for JCV in a population of Mexican MS patients undergoing treatment.

2. Materials and Methods

This was an analytical study carried out on patients treated at a reference hospital center for MS patients in Mexico City. The protocol was submitted and approved by the center’s research, biosafety research, and ethics committees. All participants signed a written informed consent letter authorizing their participation and received a privacy notice. The cases were Mexican patients diagnosed with MS according to the 2017 McDonald criteria [ 19 ], which consider clinical relapses, MRI findings demonstrating dissemination in space (lesions in at least two regions: periventricular, juxtacortical, infratentorial, or medullary) and time (new or simultaneous enhancing and non-enhancing lesions), as well as the presence of oligoclonal bands in the cerebrospinal fluid (CSF).

The patients were under treatment, of both sexes, and aged 12 years or older. All participants underwent a complete medical history, Expanded Disability Status Scale (EDSS) classification, and neurological evaluation. Once they met the selection criteria, they were given a structured questionnaire, and a 10 mL venous blood sample was taken from the forearm of their non-dominant side to determine the level of anti-JCV antibodies using a two-step ELISA or double-ELISA (screening and confirmatory) assay. This determination was carried out at the Virological Analysis and Reference Unit (UARVI). The results were stratified according to the UARVI specifications in accordance with the Kit: positive (anti-JCV antibody index > 0.4); negative (anti-JCV antibody index < 0.2); and indeterminate (anti-JCV antibody index between >0.2 and <0.4).

The socio-demographic and clinical data were obtained from the electronic medical record available to the researchers who participated in the study.

The participants were divided into three groups according to the result of the anti-JCV antibody index (negative, indeterminate, and positive). Descriptive statistics were performed to understand the behavior of the cohort and inferential statistics appropriate to the type of variable. Those that did not describe a normal curve were standardized using the statistical package according to their distribution and the presence or absence of values equal to or less than 0. p < 0.05 was accepted as a significant difference. The analysis was performed with the SPSS-25 program.

3. Results

Samples from 121 MS patients were analyzed: 76 women (62.8%) and 45 (37.2%) men. The mean age was 42.28 ± 10.62. The socio-demographic characteristics are described in Table 1 .

The analysis of the clinical characteristics of the patients determined the distribution by clinical type of the disease as follows: 81% presented with RRMS (Relapsing–Remitting MS) (67.34% women and 32.65% men, with an average age of 30.68 ± 9.65 years, median 30 years (max. 50–min. 12)); 17.35% with SPMS (Secondary Progressive MS) (47.61% women and 52.38% men, with a mean age of 33.62 ± 11.27, median 32 years (max. 59–min. 17), average duration of evolution of MS of 176 ± 87 months, median 168 (max. 360–min. 24)); and two patients with PPMS (Primarily Progressive MS) (both men aged 19 and 30 and with a duration of 96 and 180 months) ( Table 2 ). Additionally, we observed a marked difference in the EDSS of the different clinical types of MS that the patients presented ( Figure 1 ). EDSS is a disability scale for MS. RRMS has a lower range of EDSS (median close to 2). This reflects relatively less disability. On the other hand, SPMS has a higher EDSS (median near 6), which is clinically consistent, as SPMS represents a more advanced phase with greater accumulated disability. Significant differences in disability between RRMS and SPMS ( p = 0.0001) were confirmed by statistical analyses such as the Chi-squared and Kruskal–Wallis tests, consistent with the natural history of the disease. These analyses establish a statistical relationship between clinical severity and type of MS, indicating that RRMS is less disabling than SPMS in function.

The HETs received during the study were natalizumab in 67.76% of patients, teriflunomide in 11.57%, fingolimod in 9.09%, glatiramer acetate in 2.47%; cladribine and ocrelizumab in 1.65% each; and azathioprine, immunoglobulin G, and interferons in 0.826% each ( Table 3 , Table 4 and Table 5 ).

The JCV index was determined in all participants, and they were classified into three groups, as described in the Materials and Methods section. The first group (negative) consisted of 31 patients, 21 (67.74%) women and 10 (32.25%) men: 26 (83.9%) patients under treatment with natalizumab; 2 (5.45%) with teriflunomide; and 1 each with ocrelizumab, azathioprine, and interferon ( Table 3 ).

The second group (intermediate), composed of patients with an index between 0.2 and less than 0.4, consisted of 14 patients, 10 (71.42%) women and 4 (28.57%) men: 12 (85.7%) patients were treated with natalizumab, 1 with fingolimod, and another with glatiramer acetate ( Table 4 ).

The third group, classified as positive, consisted of 76 patients with MS and whose antibody index against JCV was 0.4 or higher; 46 (60.52%) were women and 30 (39.47%) men. The treatment they were receiving at the time of the study was as follows: 2 (2.62%) patients were receiving treatment with glatiramer acetate, 4 (5.26%) received alemtuzumab, 2 (2.62%) received cladribine, 10 (13.15%) received fingolimod, 44 (57.89%) patients received natalizumab, 12 patients received teriflunomide, and 1 patient each received ocrelizumab and immunoglobulin G ( Table 5 ). It is important to note that the treatments with azathioprine and immunoglobulin G used in this group of patients were administered off-label for MS. These decisions reflect the clinical judgment of the treating physician, informed by available evidence in specific cases. According to the type of MS, within these group, 75% of patients presented with RRMS, 22.36% of patients with SPMS, and 2.63% of the patients with PPMS. In this group, the therapies administered include natalizumab, alemtuzumab, and fingolimod, all of which are classified as HETs according to the literature [ 20 ]. In contrast, treatments such as glatiramer acetate, interferons, and teriflunomide are not classified as HETs but may be used in specific cases based on the individual clinical needs of the patient.

In the association tests, we found significant relationships between IgG positivity and certain clinical conditions: cognitive impairment, history of depression, and absence of other neurological diseases. A correlation analysis showed that the JCV antibody index was correlated with a history of depression and the duration of fingolimod use ( Table 6 ). These associations suggest that the existence of antibodies against JCV could impact inflammation or neurodegenerative mechanisms in the brain, thereby exacerbating cognitive and emotional disorders. Virus-induced neuroinflammation, in addition to the immunologic effects of the treatments (i.e., natalizumab), may contribute to these clinical conditions. Additionally, the JCV antibody index was significantly associated with the clinical form of MS, particularly between RRMS and SPMS and between RRMS and PPMS ( Figure 2 ). This may reflect an increased susceptibility to viral reactivation and immune changes in patients with more progressive disease, with implications for therapy selection and clinical monitoring. These analyses highlight the relevance of JCV seropositivity not only for PML risk but also for the clinical parameters of MS course.

4. Discussion

MS remains a disease that faces many challenges, and despite the significant progress in treatment with encouraging response rates of around 70% with DMTs [ 21 ], some limitations and complications of these treatments have been identified.

Additionally, viruses in MS have been identified at different stages of the disease from development to evolution and treatment of the disease, for example, the Epstein–Barr virus (EBV), whose infection increases the risk of developing MS by 26.5% (95% CI: 3.7–191.6) [ 22 ]. It is speculated that, after acute infection, EBV remains quiescent in peripheral blood B lymphocytes and lymph nodes [ 23 ], which in turn present antigens like myelin and, by interacting with T lymphocytes, enters the CNS with subsequent immune attacks and inflammation [ 24 ]. In addition, EBV infection bound to transcription factors confers a higher risk of developing autoimmune diseases [ 25 ].

JCV appeared on the MS scene from the use of DMTs, particularly mAc. JVC causes an asymptomatic primary infection in the early stages of life. Its access is through the digestive or respiratory tract until it reaches epithelial cells of the kidney, bone marrow, spleen, and lymphocytes cells, where it remains throughout the life of the host [ 26 ]. Although first contact with JCV usually occurs in childhood, it can also happen in adulthood, so seropositivity increases with age. It has been estimated that each year, 3% of the seronegative population becomes positive [ 27 ].

Under immunosuppressive conditions, JCV causes a disease known as PML, described by Åström in 1958, although the virus was not identified until 1971 [ 28 ]. PML is a multifocal and progressive white matter disease of the CNS where the host suffers from severe suppression of cellular immunity during its development. Primary infection is caused by the “archetype” virus, whose non-coding region or hypervariable regulatory region [ 29 ] does not replicate effectively in the brain; however, in immunosuppressed individuals, active viral replication is observed with rearrangements in the viral genome that generate neurotropic variants that actively replicate in glial cells. When JCV reaches the CNS, it lytically infects glial cells, particularly oligodendrocytes [ 30 ].

With the advent of DMTs, particularly the use of mAb, the presence of immunological memory for JCV and viruses are of interest in MS patients due to the risk of developing PML; in our cohort, we found that the positivity of immunological memory for JCV was 62.8%. Paz et al. [ 31 ], in their systematic review of 1664 articles, which included Eurasia, Canada, and the USA, observed in a total of 29,319 patients with MS and Neuromyelitis Optica an average of 57.1% seropositivity, slightly lower than that observed in the present study. In this systematic review, two Portuguese, two Austrian, one German, one Belgian, one Korean, one Dutch, and one Turkish study showed prevalences of 60% or more, and it is worth noting that the sociodemographic heterogeneity of these countries is striking. However, seropositivity for anti-JCV antibodies and its association with the use of natalizumab were not consistent across the studies reviewed. This variability may indicate a potential bias, as it is not typically observed in larger samples, and in our case, it was not identified.

In another meta-analysis of 17 independent cohorts, where 1221 patients with MS were treated with natalizumab, it was observed that on average, 10.80% of JCV-seronegative patients became positive one year after treatment. When this conversion is at low index values, there is a high probability of reversion over time, but patients with high index values almost never experience reversion, so the conversion rate by natalizumab is estimated to be three to four times higher than the biological conversion by age [ 32 ].

In a German cohort of 803 MS patients [ 33 ], the prevalence of anti-JCV antibody positivity was 67.9%. The male–female ratio was 81.7% and 64%, respectively ( p < 0.001, OR = 2.51; CI: 1.65–3), which we did not determine in our study. Those who lived in cold regions had a significantly higher prevalence of positivity ( p = 0.043 and OR = 1.86; IC 1.02–3.39) [ 32 ]. Additionally, they found no differences with the type of MS, dose and duration of immunosuppressive drugs used, and positivity of anti-JCV antibodies or the index. Unlike Germany, Mexico has few cold areas, which are located in the north of the country; moreover, the patients studied were mostly residents of the center of the country, which is characterized by warm temperatures, so this variable was not considered. In the German cohort, they observed that, among those whose MS onset was between 28 and 37 years of age, there was more positivity compared with in those whose onset was between 18 and 27 years of age ( p = 0.02; OR = 1.85; CI: 1.09–3.14). In contrast, in another study, age at disease onset was not associated with JCV positivity, but the age of the patients was, suggesting that exposure to a wild-type virus is the underlying phenomenon for seroconversion in this study group and perhaps in central Mexico [ 34 ].

A Brazilian study [ 35 ] where 1501 blood samples from 1102 MS patients with various treatment regimens were analyzed for five years, 76% were women, with a median age of 38 years. The initial seropositivity was 55.3%, the disease was more common among men ( p = 0.001), and age did not influence the result (r = 0.115). Seroconversion occurred in 18.5%, over a mean period of 22 months (0.84% per month and 10.09% per year), and an overall seropositivity of 57.1% was achieved, with no difference from the baseline seropositivity ( p = 0.09). This increase was significantly higher than that estimated by Schwab et al., ~0.48%/year [ 32 ], perhaps because the Brazilian population has more exposure to JCV. The Brazilian population might share more socioeconomic similarities with our cohort, however, and the distance in positivity between 55.3% and 62.8% could be explained by population or geographic differences, highlighting that the patients in the present study are significantly younger (30 vs. 38 years), so we would expect a higher prevalence in Brazilians. Auer et al. [ 26 ] estimated an increase of 3% per year; based on this estimate, for our cohort, if there is no change in the rate of increase, we would expect 4.7 patients to acquire MS per year, which equates to 38 patients in 8 years, and a seropositivity of 94% would be reached, which opens up an area of research for this population difference. In Brazil, Fragoso et al. [ 36 ] studied 168 patients with MS based on type of MS and treatment with natalizumab for JVC using PCR and found positivity in 51.2%, a very concerning figure that deserves to be studied.

Bozice et al. [ 37 ] observed in 7724 patients with MS from 10 countries in Europe, Canada, and Austria (median age of 43 years, 71% women, 94% white population, with various treatments and all forms of the disease) an overall prevalence of anti-JCV antibodies of 57.1%, which was associated with increasing age, being male, and living in Australia, Norway, and Portugal ( p < 0.0001). There was no difference with disease duration, type of MS, number of relapses, treatments, and treatment duration.

Olson et al. [ 38 ] found in 378 patients with RRMS a mean prevalence of anti-JCV antibodies of 57.6%, and it was associated with older age ( p = 0.030) and with treatment with natalizumab ( p < 0.001); in our cohort, prevalence of anti-JCV antibodies was also associated with older age of the patients, but we did not find any association with the various treatments.

Bhan et al. [ 39 ] recruited 4198 MS patients from Quebec, Ontario, the Atlantic provinces (Nova Scotia, New Brunswick, and Newfoundland), the western provinces (Manitoba, Saskatchewan, Alberta, and British Columbia), and the rest of Canada. Seropositivity was determined by ELISA (two steps). Overall seropositivity was 56.3%, associated with age ( p = 0.0001), being male ( p = 0.005), and residing in Quebec ( p = 0.005). No differences were observed between populations, type, and duration of MS.

Sá et al. [ 40 ] analyzed 655 MS patients in Portugal, and the overall seroprevalence of anti-JCV antibodies was 60.8% and was associated with older age ( p = 0.030); it was surprisingly lower in patients treated with natalizumab 48.4% vs. 68.3% ( p < 0.001), a finding that the researchers attributed to a selection bias, since patients with a positive result do not usually receive natalizumab.

A multicenter study in five regions of Poland included 1405 MS patients whose positivity for JVC Ab was 65.8% [ 41 ]; these authors found that there was a correlation of the JCV Ab index within the forms of SPMS and PPMS compared to RRMS patients, a finding also observed in our study and whose explanation is not clear. As expected, more than half of patients with PML are seropositive for JCV before the onset of the disease, but it is relevant that higher levels of antibodies have been detected before the diagnosis of PML compared to those who do not develop it, and in patients treated with natalizumab, an increase in antibodies has been observed shortly before or coinciding with the development of PML attributed to JCV reactivation [ 29 ]. However, the function and interpretation of anti-JCV antibodies in the evolution of the disease remain to be elucidated.

Regarding the significant association between a positive index and a history of depression, various investigations have confirmed the important role that glia plays in the development of depression. There is evidence that suggests that the development of depression may be strongly related to viral infections (herpes simplex-1, varicella zoster, and Epstein–Barr virus, among others [ 42 ]) that usually generates damage to glial cells (astrocytes, oligodendrocytes, and microglia), which causes alterations in neurotransmission; decreases the synthesis of monoamines; and increases the level of cytokines, the consequent neuroinflammation and mitochondrial damage, excitotoxicity, and oxidative stress that eventually results in depression [ 43 ]. Along with direct cell infection, other mechanisms of viral infection-induced depression have been proposed, including immune imbalance. This is carried out through chronic or excessive inflammation, driven by the stimulation of a robust production of cytokines and chemokines. This response can become dysregulated, leading to an altered hypothalamic–pituitary–adrenal axis, activation of microglia and astrocytes, and modification of metabolic pathways that changes the neurotransmitter system and synaptic function. All these mechanisms ultimately contribute to and play a crucial role in mood regulation [ 44 ].

Based on the close relationship between the different types of viruses and depression, we could consider positivity for JCV in the list of associated viruses. It was very relevant that the correlation between the JCV Ab index and depression was negative, which suggests that it is more related to the primary infection than to the magnitude of the host response.

Finally, it is possible that the behavior of JCV in people with MS differs and that this difference increases with the use of treatment, particularly highly effective disease-modifying treatments, whose common denominator is a reduction in the immune response.

Our study was limited by the sample size, so in the future, it would be interesting not only to increase the sample size but also to provide long-term follow-up to determine seroconversion and its relationship with the treatments that patients receive and additionally add studies that determine JCV infection at the time of treatment. Other limitations to consider are that control treatments were not performed, since this is a third-level hospital and this type of treatment is only given to people with MS. Moreover, the study population was taken from the center of the country, which limits the representation of regions with other climates or where the prevalence of the JCV may vary; therefore, not including these populations may have impacted the possible generalization of the findings. This was a cross-sectional study, which limits the evaluation of changes in antibody levels and disease progression in the people who participated. Other viruses that may contribute to the pathogenesis of MS such as Epstein–Barr virus were also not considered.

5. Conclusions

The seropositivity was 62.8%, and in this group, the average duration of disease evolution was 152.33 ± 93.37 months. Natalizumab was the most used HET, and despite this, only a positive association between a positive JCV antibody index with duration of fingolimod and history of depression was found. Also, a positive correlation of the JCV Ab index within the forms of SPMS and PPMS compared to RRMS was observed. No differences were observed between populations, type, and duration of MS.

Author Contributions

Conceptualization, S.G., A.G.-M., S.Q.-A., S.S.-S. and S.L.A.-E.; methodology, S.G., A.G.-M., C.G.T.-L., P.M.T. and S.L.A.-E.; formal analysis. S.G., M.A.T.G., G.G.-C., J.A.S.-C., C.G.T.-L., P.M.T. and S.L.A.-E.; investigation, S.G., A.G.-M., S.Q.-A., S.S.-S. and S.L.A.-E.; writing—original draft preparation, S.G., A.G.-M., M.A.T.G., G.G.-C., J.A.S.-C. and S.L.A.-E.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The project was approved by the ethics, research, and biosafety committees of the Centro Médico Nacional 20 de Noviembre at the Instituto de Seguridad and Servicios Sociales de los Trabajadores del Estado (ISSSTE; approval no. 277.2021).

Informed Consent Statement

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

Data Availability Statement

The original contributions presented in this study are included in the article; further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding Statement

This research received no external funding.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

References

1. Baskaran A.B., Grebenciucova E., Shoemaker T., Graham E.L. Current Updates on the Diagnosis and Management of Multiple Sclerosis for the General Neurologist. J. Clin. Neurol. 2023;19:217–229. doi: 10.3988/jcn.2022.0208.

2. Wallin M.T., Culpepper W.J., Campbell J.D., Nelson L.M., Langer-Gould A., Marrie R.A., Cutter G.R., Kaye W.E., Wagner L., Tremlett H., et al. The prevalence of MS in the United States: A population-based estimate using health claims data. Neurology. 2019;92:e1029–e1040. doi: 10.1212/WNL.0000000000007915. Erratum in Neurology 2019, 93, 688.

3. Shams H., Shao X., Santaniello A., Kirkish G., Harroud A., Ma Q., Isobe N., Alexander J., Bove R., Baranzini S., et al. Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans. Brain. 2023;146:645–656. doi: 10.1093/brain/awac092.

4. Bar-Or A., Pender M.P., Khanna R., Steinman L., Hartung H.P., Maniar T., Croze E., Aftab B.T., Giovannoni G., Joshi M.A. Epstein-Barr Virus in Multiple Sclerosis: Theory and Emerging Immunotherapies. Trends Mol. Med. 2020;26:296–310. doi: 10.1016/j.molmed.2021.01.004. Erratum in Trends Mol. Med. 2021, 27, 410–411.

5. Weiner H.L. The challenge of multiple sclerosis: How do we cure a chronic heterogeneous disease? Ann. Neurol. 2009;65:239–248. doi: 10.1002/ana.21640.

6. Elliott C., Wolinsky J.S., Hauser S.L., Kappos L., Barkhof F., Bernasconi C., Wei W., Belachew S., Arnold D.L. Slowly expanding/evolving lesions as a magnetic resonance imaging marker of chronic active multiple sclerosis lesions. Mult. Scler. J. 2019;25:1915–1925. doi: 10.1177/1352458518814117.

7. Freedman M.S., Devonshire V., Duquette P., Giacomini P.S., Giuliani F., Levin M.C., Montalban X., Morrow S.A., Oh J., Rotstein D., et al. Treatment Optimization in Multiple Sclerosis: Canadian MS Working Group Recommendations. Can. J. Neurol. Sci. 2020;47:437–455. doi: 10.1017/cjn.2020.66.

8. Amin M., Hersh C.M. Updates and advances in multiple sclerosis neurotherapeutics. Neurodegener. Dis. Manag. 2023;13:47–70. doi: 10.2217/nmt-2021-0058.

9. Graf J., Aktas O., Rejdak K., Hartung H.P. Monoclonal Antibodies for Multiple Sclerosis: An Update. BioDrugs. 2019;33:61–78. doi: 10.1007/s40259-018-0327-9.

10. Morrow S.A., Clift F., Devonshire V., Lapointe E., Schneider R., Stefanelli M., Vosoughi R. Use of natalizumab in persons with multiple sclerosis: 2022 update. Mult. Scler. Relat. Disord. 2022;65:103995. doi: 10.1016/j.msard.2022.103995.

11. Bloomgren G., Richman S., Hotermans C., Subramanyam M., Goelz S., Natarajan A., Lee S., Plavina T., Scanlon J.V., Sandrock A., et al. Risk of natalizumab-associated progressive multifocal leukoencephalopathy. N. Engl. J. Med. 2012;366:1870–1880. doi: 10.1056/NEJMoa1107829.

12. Ho P.R., Koendgen H., Campbell N., Haddock B., Richman S., Chang I. Risk of natalizumab-associated progressive multifocal leukoencephalopathy in patients with multiple sclerosis: A retrospective analysis of data from four clinical studies. Lancet Neurol. 2017;16:925–933. doi: 10.1016/S1474-4422(17)30282-X.

13. Sharma K., Tolaymat S., Yu H., Elkhooly M., Jaiswal S., Jena A., Kakara M., Sriwastava S. Progressive multifocal leukoencephalopathy in anti-CD20 and other monoclonal antibody (mAb) therapies used in multiple sclerosis: A review. J. Neurol. Sci. 2022;443:120459. doi: 10.1016/j.jns.2022.120459.

14. Jordan A.L., Yang J., Fisher C.J., Racke M.K., Mao-Draayer Y. Progressive multifocal leukoencephalopathy in dimethyl fumarate-treated multiple sclerosis patients. Mult. Scler. J. 2022;28:7–15. doi: 10.1177/1352458520949158.

15. Lombardo-Del Toro P., Bragado-Trigo I., Arroyo P., Tena-Cucala R., Bau L., Matas E., Muñoz-Vendrell A., Simó M., Pons-Escoda A., Martínez-Yélamos A., et al. Fingolimod-associated progressive multifocal leukoencephalopathy in a multiple sclerosis patient with a good response to filgrastim. J. Neurol. 2023;270:5196–5200. doi: 10.1007/s00415-023-11865-1.

16. Rindi L.V., Zaçe D., Braccialarghe N., Massa B., Barchi V., Iannazzo R., Fato I., De Maria F., Kontogiannis D., Malagnino V., et al. Drug-Induced Progressive Multifocal Leukoencephalopathy (PML): A Systematic Review and Meta-Analysis. Drug Saf. 2024;47:333–354. doi: 10.1007/s40264-023-01383-4.

17. Kowalec K., Carleton B., Tremlett H. The potential role of pharmacogenomics in the prevention of serious adverse drug reactions in multiple sclerosis. Mult. Scler. Relat. Disord. 2013;2:183–192. doi: 10.1016/j.msard.2012.11.003.

18. Quiñones-Aguilar S., Sauri-Suárez S., Alcaraz-Estrada S., García S. Progressive Multifocal Leukoencephalopathy associated to treatment with natalizumab in Mexican patient Multiple Sclerosis. Case report, analysis and update. Neuro Endocrinol. Lett. 2019;40:222–226.

19. Lara R.A.C. McDonald and MAGNIMS criteria in multiple sclerosis. Neurol. Neurocir. Psiquiatr. 2023;51:44–45.

20. Merkel B., Butzkueven H., Traboulsee A.L., Havrdova E., Kalincik T. Timing of high-efficacy therapy in relapsing-remitting multiple sclerosis: A systematic review. Autoimmun. Rev. 2017;16:658–665. doi: 10.1016/j.autrev.2017.04.010.

21. Selmaj K., Cree B.A.C., Barnett M., Thompson A., Hartung H.P. Multiple sclerosis: Time for early treatment with high-efficacy drugs. J. Neurol. 2024;271:105–115. doi: 10.1007/s00415-023-11969-8.

22. Bjornevik K., Cortese M., Healy B.C., Kuhle J., Mina M.J., Leng Y., Elledge S.J., Niebuhr D.W., Scher A.I., Munge A.L. Longitudinal analysis reveals high prevalence of Epstein-Barr virus associated with multiple sclerosis. Science. 2022;375:296–301. doi: 10.1126/science.abj8222.

23. Thorley-Lawson D.A. Epstein-Barr virus: Exploiting the immune system. Nat. Rev. Immunol. 2001;1:75–82. doi: 10.1038/35095584.

24. Soldan S.S., Lieberman P.M. Epstein-Barr virus and multiple sclerosis. Nat. Rev. Microbiol. 2023;21:51–64. doi: 10.1038/s41579-022-00770-5.

25. Harley J.B., Chen X., Pujato M., Miller D., Maddox A., Forney A., Magnusen A.F., Lynch A., Chetal K., Yukawa M., et al. Transcription factors operate across disease loci, with EBNA2 implicated in autoimmunity. Nat. Genet. 2018;50:699–707. doi: 10.1038/s41588-018-0102-3.

26. Kartau M., Sipilä J.O., Auvinen E., Palomäki M., Verkkoniemi-Ahola A. Progressive Multifocal Leukoencephalopathy: Current Insights. Degener. Neurol. Neuromuscul. Dis. 2019;9:109–121. doi: 10.2147/DNND.S203405.

27. Auer M., Hegen H., Sellner J., Oppermann K., Bsteh G., Di Pauli F., Berger T., Deisenhammer F. Conversion and reversion of anti-John Cunningham virus antibody serostatus: A prospective study. Brain Behav. 2019;9:e01332. doi: 10.1002/brb3.1332.

28. Ferenczy M.W., Marshall L.J., Nelson C.D., Atwood W.J., Nath A., Khalili K., Major E.O. Molecular biology, epidemiology, and pathogenesis of progressive multifocal leukoencephalopathy, the JC virus-induced demyelinating disease of the human brain. Clin. Microbiol. Rev. 2012;25:471–506. doi: 10.1128/CMR.05031-11.

29. Trampe A.K., Hemmelmann C., Stroet A., Haghikia A., Hellwig K., Wiendl H., Goelz S., Ziegler A., Gold R., Chan A. Anti-JC virus antibodies in a large German natalizumab-treated multiple sclerosis cohort. Neurology. 2012;78:1736–1742. doi: 10.1212/WNL.0b013e3182583022.

30. Brew B.J., Davies N.W.S., Cinque P., Clifford D.B., Nath A. Progressive multifocal leukoencephalopathy and other forms of JC virus disease. Nat. Rev. Neurol. 2010;6:667–679. doi: 10.1038/nrneurol.2010.164.

31. Paz S.P.C., Branco L., Pereira M.A.C., Spessotto C., Fragoso Y.D. Systematic review of the published data on the worldwide prevalence of John Cunningham virus in patients with multiple sclerosis and neuromyelitis optica. Epidemiol. Health. 2018;40:e2018001. doi: 10.4178/epih.e2018001.

32. Schwab N., Schneider-Hohendorf T., Hoyt T., Gross C.C., Meuth S.G., Klotz L., Foley J.F., Wiendl H. Anti-JCV serology during natalizumab treatment: Review and meta-analysis of 17 independent patient cohorts analyzing anti-John Cunningham polyoma virus sero-conversion rates under natalizumab treatment and differences between technical and biological sero-converters. Mult. Scler. J. 2018;24:563–573. doi: 10.1177/1352458517728814.

33. Koolaji S., Allahabadi N.S., Ahmadi A., Eskandarieh S., Moghadasi A.N., Azimi A.R., Sahraian M.A. Anti-JC virus antibody sera positivity and index value among patients with multiple sclerosis may be correlated with age, sex, and area of residence. J. Neurovirol. 2018;24:570–576. doi: 10.1007/s13365-018-0646-0.

34. Pietropaolo V., Prezioso C., Bagnato F., Antonelli G. John Cunningham virus: An overview on biology and disease of the etiological agent of the progressive multifocal leukoencephalopathy. New Microbiol. 2018;41:179–186.

35. Branco L.P., Adoni T., Apostolos-Pereira S.L., Brooks J.B.B., Correa E.C., Damasceno C.A., Eboni A.C.B., Fezer L., Gama P.D.D., Goncalves M.V.M., et al. Serological profile of John Cunningham virus (JCV) in patients with multiple sclerosis. Arq. Neuropsiquiatr. 2018;76:588–591. doi: 10.1590/0004-282x20180083.

36. Fragoso Y.D., Mendes M.F., Arruda W.O., Becker J., Brooks J.B., Carvalho Mde J., Comini-Frota E.R., Domingues R.B., Ferreira M.L., Finkelsztejn A., et al. Nearly one-half of Brazilian patients with multiple sclerosis using natalizumab are DNA-JC virus positive. Arq. Neuropsiquiatr. 2013;71:780–782. doi: 10.1590/0004-282X20130121.

37. Bozic C., Subramanyam M., Richman S., Plavina T., Zhang A., Ticho B. Anti-JC virus (JCV) antibody prevalence in the JCV Epidemiology in MS (JEMS) trial. Eur. J. Neurol. 2014;21:299–304. doi: 10.1590/0004-282X20130121.

38. Olsson T., Achiron A., Alfredsson L., Berger T., Brassat D., Chan A., Comi G., Eraksoy M., Hegen H., Hillert J., et al. Anti-JC virus antibody prevalence in a multinational multiple sclerosis cohort. Mult. Scler. J. 2013;19:1533–1538. doi: 10.1177/1352458513477925.

39. Bhan V., Lapierre Y., Freedman M.S., Duquette P., Selchen D., Migounov V., Walt L., Zhang A. Anti-JC Virus Antibody Prevalence in Canadian MS Patients. Can. J. Neurol. Sci. 2014;41:748–752. doi: 10.1017/cjn.2014.32.

40. Sá M.J., Nunes C.C., da Silva A.M., Mota P., Pinto-Marques J., on behalf of the JUSTIFY Investigators JC virus antibodies in Portuguese multiple sclerosis patients: JUSTIFY study results. J. Neurol. Sci. 2019;406:116426. doi: 10.1016/j.jns.2019.116426.

41. Bonek R., Guenter W., Jałowiński R., Karbicka A., Litwin A., Maciejowski M., Zajdel R., Zajdel K., Petit V., Rejdak K. JC Virus Seroprevalence and JCVAb Index in Polish Multiple Sclerosis Patients Treated with Immunomodulating or Immunosuppressive Therapies. J. Clin. Med. 2021;10:1998. doi: 10.3390/jcm10091998.

42. Wang X., Zhang L., Lei Y., Liu X., Zhou X., Liu Y., Wang M., Yang L., Zhang L., Fan S., et al. Meta-analysis of infectious agents and depression. Sci. Rep. 2014;4:4530. doi: 10.1038/srep04530.

43. Yu X., Wang S., Wu W., Chang H., Shan P., Yang L., Zhang W., Wang X. Exploring New Mechanism of Depression from the Effects of Virus on Nerve Cells. Cells. 2023;12:1767. doi: 10.3390/cells12131767.

44. Park E.S., Shin C.Y., Jeon S.J., Ham B.J. Is There such a Thing as Post-Viral Depression?: Implications for Precision Medicine. Biomol. Ther. 2024;32:659. doi: 10.4062/biomolther.2024.170.

Associated Data

Data Availability Statement

The original contributions presented in this study are included in the article; further inquiries can be directed to the corresponding author.