Skip to main content

REVIEW article

Front. Neurol., 02 June 2023
Sec. Multiple Sclerosis and Neuroimmunology
This article is part of the Research Topic Aging in multiple sclerosis: from childhood to old age, in women and men View all 13 articles

Aging in multiple sclerosis: from childhood to old age, etiopathogenesis, and unmet needs: a narrative review

Nicola Capasso,&#x;Nicola Capasso1,2Eleonora Virgilio&#x;Eleonora Virgilio3Antonio CovelliAntonio Covelli4Beatrice GiovanniniBeatrice Giovannini5Matteo Foschi,Matteo Foschi6,7Federico MontiniFederico Montini8Martina NaselloMartina Nasello9Annacarmen NiloAnnacarmen Nilo10Elio PrestipinoElio Prestipino11Giuseppe SchirGiuseppe Schirò12Silvia SperandeiSilvia Sperandei13Marinella Clerico&#x;Marinella Clerico14Roberta Lanzillo,
&#x;Roberta Lanzillo1,2*
  • 1Department of Neuroscience, Reproductive Sciences and Odontostomatology, Federico II University of Naples, Naples, Italy
  • 2Multiple Sclerosis Unit, Policlinico Federico II University Hospital, Naples, Italy
  • 3Neurology Unit, Department of Translational Medicine, AOU Maggiore della Carità Novara, University of Eastern Piedmont, Novara, Italy
  • 4Department of Neurology, Santi Antonio e Biagio e Cesare Arrigo Hospital, Alessandria, Italy
  • 5Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
  • 6Department of Neuroscience, MS Center, S. Maria delle Croci Hospital, AUSL Romagna, Ravenna, Italy
  • 7Department of Biotechnological and Applied Clinical Sciences (DISCAB), University of L’Aquila, L’Aquila, Italy
  • 8Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
  • 9Neurology Unit, Department of Neurosciences, Mental Health and Sensory organs (NESMOS), Sapienza University of Rome, Rome, Italy
  • 10Clinical Neurology Unit, Department of Head, Neck and Neurosciences, Santa Maria della Misericordia University Hospital, Udine, Italy
  • 11UOSC Neuro-Stroke Unit, AORN Antonio Cardarelli, Naples, Italy
  • 12Section of Neurology, Department of Biomedicine, Neurosciences and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy
  • 13Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
  • 14Department of Clinical and Biological Sciences, University of Turin, Turin, Italy

Multiple sclerosis (MS) primarily affects adult females. However, in the last decades, rising incidence and prevalence have been observed for demographic extremes, such as pediatric-onset MS (POMS; occurring before 18 years of age) and late-onset MS (corresponding to an onset above 50 years). These categories show peculiar clinical-pathogenetic characteristics, aging processes and disease courses, therapeutic options, and unmet needs. Nonetheless, several open questions are still pending. POMS patients display an important contribution of multiple genetic and environmental factors such as EBV, while in LOMS, hormonal changes and pollution may represent disease triggers. In both categories, immunosenescence emerges as a pathogenic driver of the disease, particularly for LOMS. In both populations, patient and caregiver engagement are essential from the diagnosis communication to early treatment of disease-modifying therapy (DMTs), which in the elderly population appears more complex and less proven in terms of efficacy and safety. Digital technologies (e.g., exergames and e-training) have recently emerged with promising results, particularly in treating and following motor and cognitive deficits. However, this offer seems more feasible for POMS, being LOMS less familiar with digital technology. In this narrative review, we discuss how the aging process influences the pathogenesis, disease course, and therapeutic options of both POMS and LOMS. Finally, we evaluate the impact of new digital communication tools, which greatly interest the current and future management of POMS and LOMS patients.

1. Introduction

Multiple Sclerosis (MS) is a chronic, inflammatory, immune-mediated disease of the central nervous system disease (106). MS is one of the most relevant causes of neurological disability in young people, with an important social and economic impact (38). An early diagnosis is crucial for managing MS evolution and reducing morbidity and long-term effects (103). MS has a multifactorial etiology; young females are the most affected population (with a peak incidence between 20 and 40 years old). However, MS can emerge in all age groups, including pediatric patients (pediatric-onset MS, POMS), corresponding to children before 18 years of age (2–10% of total cases), and after 50 years of age (late-onset MS, LOMS; with a prevalence ranging from 1.1–21.3% of cases depending from cut-offs and diagnostic methods considered) (82). These demographic extremes present different clinical and pathogenetic characteristics (71).

The clinical phenotype of POMS differs from adult patients. POMS patients generally experience a more aggressive disease onset with disabling clinical symptoms, a polyfocal presentation at disease onset, and a higher relapse rate early in the disease course (60). In recent decades, evidence confirmed that early axonal damage in MS patients contributes to clinical disability and progression from early disease stages (113). In POMS, acute axonal injury following inflammatory demyelinating lesions is more pronounced than in the adult counterparts (89). In contrast, LOMS patients are more likely to convert in secondary progressive phases, suggesting that they may experience a more evident chronic axonal loss associated with physiological aging (1, 111). Children are less likely to develop primary or secondary progressive MS, and 98% of POMS present with a relapsing–remitting (RR) course, compared with 84% of adult patients and 50% of LOMS (3).

POMS and LOMS are also challenging during the diagnostic workup. For POMS, it is essential to rule out other disorders that may mimic MS and demyelinating syndromes that can occur more likely than MS in childhood, such as mog-associated disease (MOGAD) and acute disseminated encephalomyelitis (ADEM) (10). POMS must not only be differentiated from acute ADEM or MOGAD, but there is also an extensive list of other disorders that can mimic MS, which need to be excluded. Such diseases include neuromyelitis optica spectrum disorder (NMOSD), systemic lupus erythematosus (SLE), neurosarcoidosis, Sjögren syndrome, leukodystrophies, hereditary metabolic diseases, and encephalitic or meningoencephalitis infectious etiologies. Inflammation of the brain during critical developmental periods, including myelinogenesis in adolescence, may irreparably damage neural networks involved in cognition. This damage may also lead to the reduced brain and deep gray matter volumes in adulthood reported in POMS relative to sex- and age-matched patients with AOMS independent of disease duration (73). Several studies have demonstrated that individuals with POMS have slower disease progression than their adult-onset counterparts, particularly during the early stages of the disease. This discrepancy may suggest greater plasticity, less neurodegeneration, and potentially more repair and remyelination in the younger nervous system (4).

In the last decades, the average age of MS patients has progressively increased, as well as the number of patients with LOMS or very late onset MS (VLOMS, onset after 60 years of age) (13, 71, 102, 112). The yearly incidence of LOMS and VLOMS represents 3.4–4.8 and 0.5% of all new diagnoses (50, 91, 112). Moreover, an increasing number of young MS patients are getting older, along with the general population trend (71, 112). Better diagnostic accuracy, longer life expectancy, and the introduction of specific disease-modifying treatments (DMTs) are among the factors leading to the growing number of older MS patients (112).

The management of older MS patients represents a clinical and therapeutic challenge, and the risk of misdiagnosis is higher than in younger patients. This is mainly due to the higher prevalence of comorbidities and immunosenescence. Indeed, the clinical onset of older MS patients is generally characterized by motor symptoms (101) potentially sharing similar features with deficits from other neurological disorders (i.e., cerebrovascular diseases) prevalent in older age. In addition, LOMS patients are more frequently male and tend to have a progressive form of the disease (8, 68). Moreover, long disease duration is associated with a worse prognosis in old MS patients (85). Some radiological and laboratory biomarkers such as spine involvement (usually spared in vascular diseases), the presence of lesions in the septum callosum (typical of MS), and the presence of oligoclonal bands in cerebrospinal fluid could be helpful to support MS diagnosis in older patients (20).

Finally, demographic extremes, POMS and LOMS, have different clinical, pathogenic, and prognostic characteristics, with 16% of LOMS reaching a score of 6 in the Expanded Disability Status Scale (EDSS), compared to the 15% of POMS (82). Thus, the clinical management, therapeutic approach, and social engagement of these two groups of patients are completely different.

Here we present a narrative review discussing how the aging process influences the pathogenesis, disease course, and therapeutic options of both POMS and LOMS. Finally, we evaluate the impact of new digital communication tools, which greatly interest the current and future management of POMS and LOMS patients.

2. Pediatric-onset multiple sclerosis patients

2.1. Genetic background

Several pieces of evidence support the contribution of genetic factors in the onset of POMS (Figure 1). Moreover, some of the variants identified as possible genetic risk factors increase the susceptibility to the onset of the disease during the pediatric age and to the onset in adulthood, suggesting that the two forms of MS share similar and superimposable biological processes (42). Human leukocyte antigen (HLA) genetic variants and non-HLA variants extend the risk of developing MS in childhood (42). However, mainly the HLA molecules, among these, those of class II, confer a greater genetic susceptibility. Not surprisingly, the polymorphisms of the classic risk factor for adult MS HLA–DRB1*15:01 are also associated with an increased risk of developing the disease in childhood, although a greater association is described for adult-onset MS (7). The HLA-DRB1*03 allele was also identified - for the first time in a population of pediatric MS patients of Greek origin - as a genetic risk factor compared to healthy controls and adult MS patients. In particular, its presence identifies patients with greater inflammatory disease activity and more relapses, mainly with the involvement of the thoracic spinal cord (43). The HLA-DP alleles, although less studied than HLA-DR alleles, seem involved in the pathogenetic mechanisms of the disease. In particular, HLA-DPB1*03 allele, already known as allele risk for adult MS, plays a role also for pediatric MS, while the HLA-DPB1*04 allele has shown a protective role for the onset of the disease in both adults and children (6). Furthermore, it is unclear whether the known genetic susceptibility factors for disease onset may also influence the relapse rate. A genotyping analysis by Graves and collaborators on 181 patients from two pediatric MS centers in the United States found no association between the number of relapses and genetic risk score for non-HLA genes. Instead, HLA-DRB1*15 was found to modify the association of vitamin D status with relapse rate (44). It should be noted that many of the biological processes that play a decisive role in the onset of MS, including pediatric MS, result from complex gene–environment interactions. According to this view, the disease emerges from genetic susceptibility under the impulse of one or more environmental exposure factors. For example, the risk of pediatric MS associated with high levels of environmental pollutants in the air appears to be greater in patients carrying the GG genotypic variant of the single nucleotide polymorphism rs928264 (G/A) within CD86 or in patients with HLA polymorphisms DRB1*15:01 (119).

FIGURE 1
www.frontiersin.org

Figure 1. Multiple Sclerosis (MS) incidence and effects of risk factors according to the age of onset. MS incidence gradually increases from childhood, peaking between the second and the fourth decade. Subsequently, a gradual decrease is seen with aging. Several risk factors have been associated mainly with POMS (MS onset <18 years), although their effect persists even in older ages (i.e., obesity, low blood vitamin D levels, viral infections, especially EBV). Other risk factors have been mainly associated with LOMS (MS onset >50 years), including air pollution, oxidative damage, chronic inflammation and hormonal changes. Although impacting on MS risk since childhood, the exposure to these factors may imply a longer time to increase the risk of developing MS. Lastly, genetic background influences MS risk throughout the lifetime.

In conclusion, although several genetic variants have been identified as susceptibility factors for the onset of MS, each of these individually plays a marginal role in the development of the disease, and perhaps more genes participate together in increasing the risk of the disease. This would lead to considering both pediatric and adult-onset MS as a polygenic disease. Furthermore, the final expression of the disease is also the result of a complex interaction with environmental factors, whose phases and exact mechanisms are not yet fully known, and any future treatments should also consider this aspect.

2.2. Environmental factors

The environmental risk factors involved in the etiopathogenesis of pediatric MS are many, but for some of them, the data collected so far in the literature are few. Childhood obesity has often been proposed as an environmental risk factor in pediatric MS. A high BMI is associated with a higher risk of prepubertal and postpubertal pediatric MS in both boys and girls (26), and with a higher risk of MS onset in both females aged 7–13 years and in males between 8 and 10 years of age (80). A key role in the pathogenesis seems to be linked to increased leptin and pro-inflammatory cytokines (IL-2, IL-6, IFN-γ, and TNF-α) and reduced adiponectin levels in patients compared to controls (54, 84). Furthermore, obesity, through the dysregulation of Th17 and T-reg cell activity, could change the intestinal microbiome favoring the development of a pro-inflammatory environment (108). Furthermore, POMS may be less likely to consume sufficient iron compared to controls (87). Therefore, the promotion of a healthy diet and good weight control allows a modulation of the immune response in the pediatric age, potentially preventing chronic inflammatory diseases such as MS. Breastfeeding seems to constitute a protective factor for the development of pediatric MS in the perinatal period, data suggest a potential reduction of autoimmune dysregulation and an increase in the activity of the immune system against pathogens. In this regard, proposing early breastfeeding, especially to women of gestational age with a family history of MS, would constitute a potential preventive therapy against the development of pediatric MS (46). In adults, low levels of vitamin D, due to a low sun exposure, which in its active form works by inhibiting the activity of inflammatory cells involving both vitamin D and non-vitamin D pathways, may increase susceptibility to MS, a finding not yet confirmed in children, although vitamin D levels are lower than the normal range in most pediatric MS patients (48, 79). Spending more time in the sun during summer may be strongly protective against developing POMS (100). In a previous meta-analysis, it was reported strong evidence for a casual and independent association between low serum concentrations of vitamin D and increased BMI and risk of POMS (41). Recent metagenomic analyses show an altered gut microbiome-related metabolic potential in POMS patients compared to controls, including higher breakdown of lipopolysaccharide molecules, higher prevalence of a methane producing pathway from Archaea and depletion of the lactate fermentation pathway, but lower resistant starch metabolism (76, 77). In a recent USA case–control study gut microbiota diversity was similar for POMS and controls, however at the gut-community-network level differences were observed, in particular POMS patients exhibited an overrepresentation of highly connected opportunistic pathogens, suggesting a possible contribute to MS pathogenesis (109).

Very recent works, using data from millions of US military recruits monitored over 20 years, proposes EBV as the leading cause of MS, showing that the risk increases approximately 32-fold after infection with EBV but does not appear to increase after infection with other viruses, even with a transmission mechanism similar to CMV (16). About that, EBV negative to positive seroconversion generally increases with age with a major incidence peak in early childhood and a second peak, especially for females, around puberty, coinciding with the approximate age of mononucleosis and with the highest female prevalence in MS (28, 34, 35, 63, 66, 81, 98). EBV infection is related to pediatric MS, and generally, all children with MS are EBV seropositive, whereas the positivity rate is considerably lower in healthy children (11, 15, 69, 86, 90). French authors in 2006 demonstrated an absence of correlation between an increased risk of the onset of MS after administration of the vaccine against the hepatitis B virus (HBV), nor between an increase in the relapse rate in a patient with a first episode of demyelinating disease of the CNS after HBV vaccination (74). The same authors then speculated on the risk of MS onset in childhood concerning exposure to secondhand smoke, which seems to be doubled compared to patients whose family members do not smoke and to be even higher in case of prolonged exposure aged 10 years or older (75). In the past, an increased susceptibility to MS has been described in patients with type I diabetes mellitus (DM). Data from American case–control studies show a 3- to 10-fold increased risk of developing MS in children of mothers with diabetes mellitus, particularly mothers who have had diabetes during pregnancy (44). Furthermore, a recent cohort study of newborns in Denmark from 1978 to 2008 observed a doubled risk of MS in children of mothers with pre-gestational diabetes compared with children of non-diabetic mothers (83). These data underline the importance of the anamnestic moment as an early opportunity to obtain such information even before conception so as to intercept the possibility of developing pediatric MS in this category of patients as soon as possible. However, it is still unclear today whether a common cause underlies both pathologies. However, there are no studies able to better define the intricate pathway involving OPN, Th17 cells and dendritic cells, which seems to link MS and type I DM.

2.3. Treatments for POMS

In POMS, relapse treatment is similar to the adult form of MS, consisting of high-dose steroids. Due to the high relapse rate and the improved recovery from relapses of POMS, early DMTs start is strongly recommended (23, 27). Low-efficacy DMTs available for POMS are interferon-β and glatiramer acetate. Although no randomized trials have been conducted, these drugs have shown adult-like efficacy and tolerance in various retrospective studies, and they have been at the base of treatment in pediatric patients for years (32). In case of failure or poor tolerability, high-efficacy DMTs should be considered. Several oral treatments are available in adult patients: Fingolimod, teriflunomide, and dimethyl fumarate. In US a multicenter study showed that initial treatment of POMS with this newer DMTs led to better disease activity control compared to injectables, supporting a greater effectiveness. However long-term safety data are still lacking (61). In POMS, the randomized trial PARADIGMS demonstrated an 81.9% efficacy of Fingolimod in reducing the annualized recurrence rate compared with IFNs and at least a 53% reduction in the annualized rate of new lesions on MRI (24). Furthermore, the greater efficacy of this drug has been highlighted in children than in adults, probably due to a greater inflammatory component of the juvenile form (29). Teriflunomide has been approved as a treatment in patients from 10 to 17 years old thanks to the data from the phase III, trial, TERIKIDS: the drug was well tolerated and had an excellent safety profile in this population (25). The two trials, FOCUS and CONNECTED, showed similar long-term safety and efficacy of dimethyl fumarate similar to the adult population, demonstrating that pediatric patients can benefit from this treatment (5). Natalizumab can be used in the case of very active diseases. Although not officially approved, various studies have shown excellent efficacy. Unfortunately, the risk of PML in children is not estimated due to the small samples that have been treated (40, 59). Clinical trials are currently underway on other highly effective drugs, including Ocrelizumab, Ofatumumab (anti-CD20) and Alemtuzumab (anti-CD52, LemKids trial) (52).

2.4. Engagement in POMS

In the management of POMS, it is essential an active involvement of the patient, the so-called “patient engagement,” and his caregivers, usually represented by the parents. This main goal has to be pursued from the very first visits and at the communication of the diagnosis (2, 67). The days after MS diagnosis represents a time of great stress for families, and an overload of information could create confusion, misunderstandings, or false expectations. Therefore it is necessary to provide adequate personalized advice, easily understandable and exhaustive, for example, iconographic stories. A better comprehension of the disease facilitates patient involvement (107). Due to the enormous impact of the disease, a multidisciplinary team composed of a neurologist, psychologist, and nurse who can meet the needs of patients and caregivers is essential. Adequate psychological support will be needed in dealing with the disruption of social life and family relationships. Therefore, it is important to encourage meetings between patients of the same age and between families of patients. Doctors must go beyond the simple medical care role by becoming a motivator. The young patient should feel part of a team that aims to fight the disease. The main weapons available are DMTs. In the past, injection therapy was the mainstay of treatment, with known and limited side effects. Otherwise, new, more effective, potentially dangerous oral drugs are now available. Therefore, the neurologist must debate the risk–benefit ratio with the patient and family members, encouraging their involvement in the decision-making process to choose the best treatment. Overcoming fear of therapy allows for avoiding harmful coping mechanisms in the future, encouraging better therapeutic adherence even in adulthood.

2.5. New communications tools: the digital

Our lifestyles and cognitive systems have changed throughout our evolutionary history, alongside human inventions, such as primitive tools, spoken language, writing, and arithmetics. Since the 1970s the Internet and the subsequent technological revolution have led to profound transformations of the human mind, thoughts and our way of life. In recent years the technological revolution has predictably reached the medical field as well, for example, in the field of cardiology, with FDA-approved devices to detect cardiac arrhythmias (95). Moreover, the current COVID-19 pandemic has further accelerated the technological transition in medicine and the role of telemedicine (78). Digital innovation is also emerging to monitor disease courses among patients with MS. A recent review (31) showed that digital technology has become part of clinical trials and was used to provide psychotherapy and motor rehabilitation with exergames, e-training, and robot-assisted exercises. Digital technology is particularly useful to standardize previously existing outcome measures, with automated acquisitions, reduced inconsistencies, and improved symptom detection (e.g., electronic recording of motor performance). Other clinical trials have used digital technology to monitor otherwise difficult-to-detect symptoms (e.g., fatigue, balance), to measure treatment adherence and side effects, and for self-assessment purposes. The collection of outcome measures is gradually shifting from on-site paper collection to Internet-based and, in the future, home-based Internet-based collection, with the detection of clinical and treatment characteristics that would otherwise have remained invisible. Similarly, remote interventions offer new possibilities for motor and cognitive rehabilitation. The role of technology in the therapeutic armamentarium to support MS patients appears to be of greater interest to pediatric patients, as they are more familiar than older patients with this latter. Examples included a recent trial that demonstrated the efficacy of an app in reducing stress and anxiety in POMS (22). Moreover, several studies explored the usefulness of digital technologies in POMS for motor exercise training program (114), physical activity and cognitive interventions (i.e., social-cognitive theory based) (70, 105).

2.6. Unmet needs: fears and confusions of POMS

POMS can be considered an “orphan” disease to all intents and purposes. Several studies have shown that there are still many unmet needs reported by children and adolescents affected by POMS, resulting not only from the physical and psychological effects of the disease in this specific age group but also from a lower availability of diagnostic and therapeutic information compared to the adult population (39). A recent meta-analysis analyzed 26 studies, including over 2,000 patients with POMS highlighting a profound negative impact on domains such as school performance, sociability and physical performance (39). Specifically, the lack of adequate knowledge of the disease has been reported as one of the main barriers experienced by patients with POMS in carrying out their daily activities, with important repercussions on the possibility of social integration. Several innovative ways have been proposed to improve communication between neurologists and caregivers to counter the sense of isolation that children and adolescents with MS often experience concerning the incorrect perception of being “different” from their peers due to illness. POMS patients, healthcare professionals and family members must adopt open communication, providing information in an age-appropriate and simple way. Taking the time to clearly explain the procedures, upcoming tests and treatments is essential to develop a comprehensive knowledge of MS, minimizing the risk of feeling confused and scared. From this point of view, modern technologies (i.e., telemedicine, online support groups) can represent a tool for sharing one’s experiences and clarifying doubts and perplexities about symptoms, fears and personal expectations (65). Furthermore, constant psychological support, also aimed at family members, can reduce the negative impact of the pathology on the quality of life of patients with POMS and redefine a new balance in family relationships, especially in the months next to the diagnosis.

3. Late-onset multiple sclerosis patients

3.1. Genetic background and environmental factors

LOMS and VLOMS patients remain relatively under-investigated in the literature (92). The same risk factors for the adult MS population are probably responsible for the late forms. The duration and the onset of exposure to environmental factors could possibly influence the age at onset in MS patients (i.e., air pollution with exposure to PM10, PM2.5, and O3 or cigarette smoke later in life; Figure 1) (55, 57). However, these assumptions need further confirmation. MS is more frequent in adult females than males, but this gender difference appears less marked in LOMS patients (56), possibly related to hormonal variations. A study by Baroncini et al. highlighted a greater risk of disability progression after menopause (14), probably concerning age-related neurodegeneration phenomena (19). Since patients with LOMS have a greater chance of presenting a progressive phenotype and a lower relapse rate (30), it is possible to hypothesize that hormonal variation may influence the age at onset. However, specific literature in this regard is not currently available. Furthermore, a greater relapse risk for women in the puerperium is known in the literature; a reduced birth rate could also be associated with a “delay” in time to the first clinical episode, thus postponing the clinical onset of the disease (57, 58). Some studies would then have indicated an increased risk of MS in men with low testosterone levels (117). Although age-related hormonal variations in men are not precocious and stereotyped, immunosenescence and hormonal factors may explain late onset in the male population. This area certainly deserves further investigation in the future. In contrast, the type of premorbid diet and the subsequent risk of developing LOMS was not shown to be associated in a large Danish registry study (92). Elderly patients also present numerous comorbidities more typical of the elderly subject, such as hypertension, dyslipidemia, and atherosclerotic processes with phenomena of chronic inflammation and oxidative stress, which could further influence the later onset of MS (64). The presence of such comorbidities might delay MS diagnosis in elderly patients; plus, evidence suggest that patients with vascular comorbidities will experience a faster progression. Finally, from a genetic point of view, while various studies have highlighted an earlier age of onset in association with several HLA alleles (for example, carriers of the HLA-DRB1*15 allele develop the disease earlier than non-carriers), few data are instead present for the patient LOMS and VLOMS (104). In an Australian study, the HLA-DRB1 *0801 allele was overrepresented in patients with LOMS, indicating a possible different genetic substrate even in late-onset patients (94).

3.2. Immunosenescence

Aging is a physiological process, typically occurring with the passing of the years, characterized by the progressive decline of bodily biological functions. This process is a major contributor to several comorbidities that frequently arise in the elderly (33). When this functional decline concerns the immune system, it is called immunosenescence. Modified proliferation and maturation of immune cells characterize immunosenescence and hempen the ability to develop an appropriate immune response. This leads to increased susceptibility to infection, improved autoimmune processes, and a worse response to vaccination (33). On the other hand, a compromised immune system causes a chronic inflammatory state, called “inflamm-aging,” with an increased level of inflammatory cytokines, which increases the risk of morbidity in the elderly population (12, 96). Chronic infections, such as Epstein–Barr virus (EBV), and accumulated senescent cells are responsible for inflammation and increase inflammatory cytokines, growth factors, and autoreactive antibody levels.

The age-related changes in the immune system mainly involve the adaptive immune system compared to the innate immune system. Indeed, a lower number of T, NK, and B naïve cells and an altered balance between pro- and anti-inflammatory molecules are typical features of immune system aging (33). Moreover, telomerase activity is generally reduced, leading to cellular senescence, interrupted proliferation, and a higher level of cell death (96). On the other hand, less effective phagocytosis, degranulation, and production of reactive oxygen species (ROS) characterize the senescent innate immune system and are responsible for higher susceptibility to viral and bacterial infections.

3.2.1. Immunosenescence and MS

MS etiology is not fully known (80). Autoreactive CD4+ T lymphocytes, crossing the blood–brain barrier (BBB), infiltrating the CNS, and recognizing myelin antigens as not-self seems one of the pathogenetic determinants of MS. This process activates microglia and astrocytes, induces oligodendrocytes’ apoptosis, and leads to demyelination and axonal loss (37). All MS patients, including POMS, are characterized by an early immunosenescence since disease onset, with shorter telomerase, thymic dysfunction, increased CD4+/CD28- T Lymphocytes and memory T cells levels, reduced number of naïve T cells, and less functional regulatory T cells (9). The immune system’s premature senescence seems essential for the onset of MS and its progression (33). The evolution of the disease towards progressive forms and the progression independent of relapse activity (PIRA) is more tightly associated with immunosenescence and early neurodegeneration than with disease duration and patients’ age (33). Moreover, sex has been reported to influence immunosenescence based on genetic, epigenetic, lifestyle, environmental, and social differences (19). For instance, the adaptive immune system tends to reduce its efficacy earlier in men (51). Hormonal changes are also important in MS progression (i.e., protective role in the third trimester of pregnancy and higher relapse risk in postpartum), as in immunosenescence. Estrogens, in fact, show neuroprotective effects in animal models of autoimmune encephalitis, binding beta receptors, activating oligodendrocytes, macrophages, and dendritic cells, and supporting remyelination and recovery from axonal loss (14). Thus, reduced estrogens level in menopause leads to reproductive, neurological, and immunological changes in MS women in the direction of a worsening of disease and disability (19).

3.2.2. Immunosenescence and elderly MS population

In the last decades, the number of LOMS and VLOMS has been growing, in line with the prevalence of elderly MS patients (17). Reduced cerebral plasticity and growth factor levels are typical of this population and lead to incomplete recovery from demyelination and diffuse axonal degeneration. Moreover, in the aging BBB, permeability increases, leading to a higher degree of inflammatory cells infiltrating CNS and facilitating astrocyte proliferation and glial scars development. This phenomenon contributes to incomplete recovery from demyelination and myelin debris clearance. The prevalence of progressive forms of MS is higher with increasing age (110). A higher number of B memory and plasma cells are typical of these forms and form lymphatic follicles. Increased numbers of memory B cells and plasma cells are characteristic of these forms and organize into meningeal ectopic follicles. In addition, with the transition to progressive MS, BBB permeability gradually decreases, leading to the compartmentalization of disease activity and significantly dampening therapeutic efficacy. Oxidative processes also increase and phagocytosis becomes much less efficient with aging. These mechanisms are responsible for progressive iron accumulation in the brain and in active chronic lesions called “smoldering lesions” (1, 62). These slowly expanding lesions are typical of elderly patients and are more frequent in long-term disease (1). Histologically, these are characterized by a central astrocyte scar and a peripheral rim of active macrophages full of iron and increased oxidative processes. Other radiological features of LOMS are global and regional cerebral atrophy (typical of grey matter), white matter lesion load atrophy (especially of periventricular lesions, responsible for the accumulation of cerebrospinal fluid) and increased cortical lesions number (connected to higher cognitive disability) (20).

In summary, immunosenescence results in such biological and immune changes in LOMS that it can be considered a major determinant of increased disability in this population.

3.3. Treatments in LOMS and elderly patients: safety, discontinuation, and engagement

There is a lack of data on the safety and efficiency of DMTs in older people with MS (112). Patients over 55 are usually excluded from clinical trials (112). Therefore, it is very difficult to determine whether the treatments available for older people are safe and effective. Consequently, the decision to initiate DMTs in elderly patients should be carefully considered, considering the risks associated with the therapy and its limited efficacy. An Italian study on natalizumab-related Progressive Multifocal Leukoencephalopathy (PML) showed that older age at natalizumab (NTZ) start might be a risk factor for developing PML before 24 infusions (93). PML risk is probably related to a major susceptibility secondary to the immunosenescence process.

Regarding other DMTs, Fingolimod has recently been associated with cases of PML, and these also seem to have an age-dependent trend (45). Furthermore, PML in elderly patients appears to have a worse outcome in various studies: in fact, most fatal cases of PML are in elderly patients (99). Age-associated changes in humoral immunity reduce the ability to mount an effective antibody response, suggesting that age may represent an additional stratified risk for PML in patients treated with MS therapy (45). Higher age is also a risk factor for other types of infections: for example, a higher risk of VZV reactivation was seen in older patients receiving Fingolimod, Cladribine, Natalizumab, and Alemtuzumab (47). Cryptococcal meningitis also appears to have the same age-related trend in patients receiving Fingolimod (115).

Nevertheless, due to the wide clinical variation in this group of patients, it is essential to individualize the treatment. Schweitzer et al. (99) suggested that the benefits of high-efficacy DMTs could decrease with age. Weideman et al. (115, 116) also found that the efficacy of DMTs was negatively correlated with age. In another work, age over 53 predicted no efficacy of DMTs (88). Older patients present significant pharmacokinetic and pharmacodynamic differences compared to younger patients.

Moreover, in advanced ages, progressive forms are more prevalent than RRMS. Despite expanding the therapeutic arsenal in MS, only one drug is approved for treating the primary progressive forms (Ocrelizumab). This drug showed a 24% reduction in the risk of disability progression compared to the placebo (36). Mitoxantrone and Siponimod have shown positive results in secondary progressive forms (53, 72, 118), although evidence suggests that the benefit is most evident in patients with persistent inflammatory activity (72).

Another important factor to consider before starting a DMT is the risk of developing cancer in ancient people: actually, most of the studies on the current DMTs have not shown a real correlation between their use and a greater risk of developing tumors; however, due to the increased cancer risks in individuals of advancing age, the interactions of age, immunosenescence, and DMTs use needs further study (99).

An Italian study on naïve RR LOMS patients did not show statistical differences between injective and oral treatment regarding time to the first relapse, risk of disability, and treatment withdrawal (118). Another problem to discuss is the treatment discontinuation in light of the decreased efficiency and increased risk of DMT in elderly patients. Another important factor to consider in this type of patient is the treatment discontinuation problem. A recent study (53) highlighted how discontinuation of treatment in elderly and previously stable patients results in possible new worsening/progression of the disease. These findings are very interesting, considering the growing number of older patients with MS in recent years and the many uncertainties about how to treat them. As previously reported, it’s generally accepted that older patients will benefit less from currently available DMTs. However, most studies involved ancient therapies; today, DMTs with better efficacy and safety profiles are available. The study, which involved adult patients of all ages, also found that disease worsening and progression resulting from therapy discontinuation were independent of patient age. The type of MS (RR versus progressive) also did not seem to influence disease progression. Notably, up to 40% of previously stable progressive patients showed worsening in disability after drug discontinuation. Recently, the ongoing DISCO-MS study evaluated discontinuation of DMT in participants aged 55 years or older, clinically stable (no relapses) for at least 5 years, and radiologically stable for three or more years. The study is probably the largest controlled study for DMTs conducted in MS patients older than 55. There is not a significant difference between treated and untreated patients regarding clinical activity and clinical worsening. Clinical relapses were particularly rare. An increase in the number of MRI lesions was highlighted in the group that stopped therapy: however, MRI changes involved a reduced number of new lesions (1 or 2 lesions), and numerous observational studies have shown that 1–2 new brain lesions on MRI scan after 1 year of therapy, are not associated with a significant risk of disability progression in the following 5–10 years. On the other hand, a higher number of lesions (3 or more new lesions), an active lesion or new relapses appear to correlate with significant disability progression. Thus, minimal evidence of new disease activity may be functionally acceptable in elderly patients after DMTs suspension. Therapy discontinuation is also a minor risk factor for elderly patients (over 55 years) with moderate disabilities. Interruption of therapy should be considered in patients with secondary progressive (SP) disease due to the poor therapeutic efficacy of most drugs in this disease stage. A retrospective study in patients with SPMS demonstrated that after discontinuation of INFβ or glatiramer acetate therapy, the rate of relapse and progression of disability remained similar to treated patients (18). In this context, it is now clear how it is essential to maintain a direct and one-to-one relationship between patient and neurologist in the therapeutic management of a chronic and complex pathology such as multiple sclerosis. It is known that older adults with MS are more likely to have a reduced health-related quality of life as a consequence of increased social isolation, the development of cognitive impairment, which, together with a physical disability, multiple comorbidities, and therefore to polytherapy, lead to a greater sense of dependence and “uselessness” (21).

Based on these considerations, an increasing number of Patient Health Engagement projects is emerging to guarantee shared treatment management (drug start and stop) and socioeconomic and work aspects. One of the main challenges of the last years is increasing the patient’s awareness of being a central point in the process of therapeutic decision. The active involvement of the MS patient should occur at any age through educational, listening, and empowerment programs. The purpose of these programs is to allow greater trust between doctor and patient and, consequently, greater autonomy and proactivity of the patient in the management of own lifestyle, health and care (97). The availability of new drugs, with their advantages and disadvantages, necessarily requires sharing the therapeutic choice, whether to start, continue or discontinue a drug, based on the single patient and needs. Several experts have reported how patients of MS appreciate direct and sincere communication, even when medical data are uncertain, resulting in better satisfaction of healthcare and so, greater adherence to the treatment (49).

Finally, in the elderly patient, it is essential to start a concomitant process of active involvement of caregivers (Caregiver Engagement), who play a fundamental and complementary role in the therapeutic, rehabilitative and social management of these patients.

4. Final remarks and conclusion

POMS and LOMS are two demographic extremes with different pathogenesis, clinical management, therapeutic approach, and social engagement. Both forms are the result of a complex gene–environment interaction, whereby the disease would emerge from a condition of genetic susceptibility under the impulse of one or more factors of environmental exposure. In this regard, both in POMS and above all in LOMS, immunosenescence could play an important role. There are many therapeutic challenges in these categories of patients and there is a lack of data on the safety and efficiency of DMTs especially in LOMS. However early DMTs start is strongly recommended and a multidisciplinary team that can meet the individual needs of the patient and caregivers is essential. A current challenge is the role of digital innovation in supporting the patient, especially POMS, not only in psychological and rehabilitation monitoring and support, but also in improving communication between the neurologist and the patient/family members, in a process of active involvement of patients and caregivers.

Author contributions

RL and MC contributed to conception, design of the study, and contributed in writing—review and editing the original draft. NC and EV organized the search literature. AC, BG, MF, EP, AN, FM, MN, GS, SS, NC, and EV wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by Merck Serono S.p.A., Rome, Italy, an affiliate of Merck (CrossRef Funder ID: 10.13039/100009945). Merck had no influence in the design, interpretation of the data, or content of the manuscript. No payments were made to the authors for the writing of this manuscript. Editorial assistance was provided by Ethos, and supported by an independent medical writing grant from Merck Serono S.p.A., Rome, Italy.

Conflict of interest

RL and MC received financial compensation for attendance to expert meetings as part of an educational programme by Merck Serono S.p.A., Rome, Italy, an affiliate of Merck.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Absinta, M, Sati, P, Masuzzo, F, Nair, G, Sethi, V, Kolb, H, et al. Association of chronic active multiple sclerosis lesions with disability in vivo. JAMA Neurol. (2019) 76:1474–83. doi: 10.1001/jamaneurol.2019.2399

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Allen, D, Gillen, E, and Rixson, L. The effectiveness of integrated care pathways for adults and children in health care settings: a systematic review. JBI Libr Syst Rev. (2009) 7:80–129. doi: 10.11124/jbisrir-2009-182

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Alroughani, R, Akhtar, S, Ahmed, S, Behbehani, R, and Al-Hashel, J. Is time to reach EDSS 6.0 faster in patients with late-onset versus young-onset multiple sclerosis? PLoS One. (2016) 11:e0165846. doi: 10.1371/journal.pone.0165846

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Alroughani, R, and Boyko, A. Pediatric multiple sclerosis: a review. BMC Neurol. (2018) 18:27. doi: 10.1186/s12883-018-1026-3

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Alroughani, R, Huppke, P, Mazurkiewicz-Beldzinska, M, Blaschek, A, Valis, M, Aaen, G, et al. Delayed-release dimethyl fumarate safety and efficacy in pediatric patients with relapsing-remitting multiple sclerosis. Front Neurol. (2020) 11:606418. doi: 10.3389/fneur.2020.606418

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Anagnostouli, M, Artemiadis, A, Gontika, M, Skarlis, C, Markoglou, N, Katsavos, S, et al. HLA-DPB1*03 as risk allele and HLA-DPB1*04 as protective allele for both early- and adult-onset multiple sclerosis in a Hellenic cohort. Brain Sci. (2020) 10:374. doi: 10.3390/brainsci10060374

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Anagnostouli, MC, and Manouseli, A. HLA-DRB1* allele frequencies in pediatric, adolescent and adult-onset multiple sclerosis patients, in a Hellenic sample. Evidence for new and established associations. J Mult Scler. (2014) 1:104. doi: 10.4172/2376-0389.1000104

CrossRef Full Text | Google Scholar

8. Andersen, MA, Buron, MD, and Magyari, M. Late-onset MS is associated with an increased rate of reaching disability milestones. J Neurol. (2021) 268:3352–60. doi: 10.1007/s00415-021-10490-0

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Balint, B, Haas, J, Schwarz, A, Jarius, S, Fürwentsches, A, Engelhardt, K, et al. T-cell homeostasis in pediatric multiple sclerosis: old cells in young patients. Neurology. (2013) 81:784–92. doi: 10.1212/WNL.0b013e3182a2ce0e

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Banwell, B, Bennett, JL, Marignier, R, Kim, HJ, Brilot, F, Flanagan, EP, et al. Diagnosis of myelin oligodendrocyte glycoprotein antibody-associated disease: international MOGAD panel proposed criteria. Lancet Neurol. (2023) 22:268–82. doi: 10.1016/S1474-4422(22)00431-8

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Banwell, B, Krupp, L, Kennedy, J, Tellier, R, Tenembaum, S, Ness, J, et al. Clinical features and viral serologies in children with multiple sclerosis: a multinational observational study. Lancet Neurol. (2007) 6:773–81. doi: 10.1016/S1474-4422(07)70196-5

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Barbé-Tuana, F, Funchal, G, Schmitz, CRR, Maurmann, RM, and Bauer, ME. The interplay between immunosenescence and age-related diseases. Semin Immunopathol. (2020) 42:545–57. doi: 10.1007/s00281-020-00806-z

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Barnett, MH, Williams, DB, Day, S, Macaskill, P, and McLeod, JG. Progressive increase in incidence and prevalence of multiple sclerosis in Newcastle, Australia: a 35-year study. J Neurol Sci. (2003) 213:1–6. doi: 10.1016/s0022-510x(03)00122-9

CrossRef Full Text | Google Scholar

14. Baroncini, D, Annovazzi, PO, De Rossi, N, Mallucci, G, Torri Clerici, V, Tonietti, S, et al. Impact of natural menopause on multiple sclerosis: a multicentre study. J Neurol Neurosurg Psychiatry. (2019) 90:1201–6. doi: 10.1136/jnnp-2019-320587

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Bar-Or, A, Pender, MP, Khanna, R, Steinman, L, Hartung, HP, Maniar, T, et al. Epstein-Barr virus in multiple sclerosis: theory and emerging immunotherapies. Trends Mol Med. (2020) 26:296–310. doi: 10.1016/j.molmed.2019.11.003

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Bjornevik, K, Cortese, M, Healy, BC, Kuhle, J, Mina, MJ, Leng, Y, et al. Longitudinal analysis reveals high prevalence of Epstein-Barr virus associated with multiple sclerosis. Science. (2022) 375:296–301. doi: 10.1126/science.abj8222

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Bolton, C, and Smith, PA. The influence and impact of ageing and immunosenescence (ISC) on adaptive immunity during multiple sclerosis (MS) and the animal counterpart experimental autoimmune encephalomyelitis (EAE). Ageing Res Rev. (2018) 41:64–81. doi: 10.1016/j.arr.2017.10.005

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Bonenfant, J, Bajeux, E, Deburghgraeve, V, Le Page, E, Edan, G, and Kerbrat, A. Can we stop immunomodulatory treatments in secondary progressive multiple sclerosis? Eur J Neurol. (2017) 24:237–44. doi: 10.1111/ene.13181

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Bove, R, Okai, A, Houtchens, M, Elias-Hamp, B, Lugaresi, A, Hellwig, K, et al. Effects of menopause in women with multiple sclerosis: an evidence-based review. Front Neurol. (2021) 12:554375. doi: 10.3389/fneur.2021.554375

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Brownlee, WJ, Hardy, TA, Fazekas, F, and Miller, DH. Diagnosis of multiple sclerosis: progress and challenges. Lancet. (2017) 389:1336–46. doi: 10.1016/S0140-6736(16)30959-X

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Buhse, M. The elderly person with multiple sclerosis: clinical implications for the increasing life-span. J Neurosci Nurs. (2015) 47:333–9; quiz E1. doi: 10.1097/JNN.0000000000000172

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Charvet, L, George, A, Cho, H, Krupp, LB, and Dennis-Tiwary, TA. Mobile attention Bias modification training is a digital health solution for managing distress in multiple sclerosis: a pilot study in pediatric onset. Front Neurol. (2021) 12:719090. doi: 10.3389/fneur.2021.719090

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Chitnis, T, Aaen, G, Belman, A, Benson, L, Gorman, M, Goyal, MS, et al. Improved relapse recovery in paediatric compared to adult multiple sclerosis. Brain. (2020) 143:2733–41. doi: 10.1093/brain/awaa199

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Chitnis, T, Arnold, DL, Banwell, B, Brück, W, Ghezzi, A, Giovannoni, G, et al. Trial of Fingolimod versus interferon beta-1a in pediatric multiple sclerosis. N Engl J Med. (2018) 379:1017–27. doi: 10.1056/NEJMoa1800149

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Chitnis, T, Banwell, B, Kappos, L, Arnold, DL, Gücüyener, K, Deiva, K, et al. Safety and efficacy of teriflunomide in paediatric multiple sclerosis (TERIKIDS): a multicentre, double-blind, phase 3, randomised, placebo-controlled trial. Lancet Neurol. (2021) 20:1001–11. doi: 10.1016/S1474-4422(21)00364-1

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Chitnis, T, Graves, J, Weinstock-Guttman, B, Belman, A, Olsen, C, Misra, M, et al. Distinct effects of obesity and puberty on risk and age at onset of pediatric MS. Ann Clin Transl Neurol. (2016) 3:897–907. doi: 10.1002/acn3.365

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Chitnis, T, Tenembaum, S, Banwell, B, Krupp, L, Pohl, D, Rostasy, K, et al. Consensus statement: evaluation of new and existing therapeutics for pediatric multiple sclerosis. Mult Scler. (2012) 18:116–27. doi: 10.1177/1352458511430704

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Choi, A, Marcus, K, Pohl, D, Eyck, PT, Balfour, H Jr, and Jackson, JB. Epstein-Barr virus infection status among first year undergraduate university students. J Am Coll Heal. (2022) 70:22–5. doi: 10.1080/07448481.2020.1726927

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Cohen, JA, Barkhof, F, Comi, G, Hartung, HP, Khatri, BO, Montalban, X, et al. Oral fingolimod or intramuscular interferon for relapsing multiple sclerosis. N Engl J Med. (2010) 362:402–15. doi: 10.1056/NEJMoa0907839

PubMed Abstract | CrossRef Full Text | Google Scholar

30. D'Amico, E, Patti, F, Zanghì, A, Chisari, CG, Lo Fermo, S, and Zappia, M. Late-onset and young-onset relapsing-remitting multiple sclerosis: evidence from a retrospective long-term follow-up study. Eur J Neurol. (2018) 25:1425–31. doi: 10.1111/ene.13745

PubMed Abstract | CrossRef Full Text | Google Scholar

31. De Angelis, M, Lavorgna, L, Carotenuto, A, Petruzzo, M, Lanzillo, R, Brescia Morra, V, et al. Digital Technology in Clinical Trials for multiple sclerosis: systematic review. J Clin Med. (2021) 10:2328. doi: 10.3390/jcm10112328

PubMed Abstract | CrossRef Full Text | Google Scholar

32. de Chalus, A, Taveira, M, and Deiva, K. Pediatric onset multiple sclerosis: future challenge for early diagnosis and treatment. Presse Med. (2021) 50:104069. doi: 10.1016/j.lpm.2021.104069

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Dema, M, Eixarch, H, Villar, LM, Montalban, X, and Espejo, C. Immunosenescence in multiple sclerosis: the identification of new therapeutic targets. Autoimmun Rev. (2021) 20:102893. doi: 10.1016/j.autrev.2021.102893

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Dunmire, SK, Verghese, PS, and Balfour, HH Jr. Primary Epstein-Barr virus infection. J Clin Virol. (2018) 102:84–92. doi: 10.1016/j.jcv.2018.03.001

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Fisher, KS, Cuascut, FX, Rivera, VM, and Hutton, GJ. Current advances in pediatric onset multiple sclerosis. Biomedicine. (2020) 8:71. doi: 10.3390/biomedicines8040071

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Fox, EJ, Markowitz, C, Applebee, A, Montalban, X, Wolinsky, JS, Belachew, S, et al. Ocrelizumab reduces progression of upper extremity impairment in patients with primary progressive multiple sclerosis: findings from the phase III randomized ORATORIO trial. Mult Scler. (2018) 24:1862–70. doi: 10.1177/1352458518808189

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Frischer, JM, Bramow, S, Dal-Bianco, A, Lucchinetti, CF, Rauschka, H, Schmidbauer, M, et al. The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain. (2009) 132:1175–89. doi: 10.1093/brain/awp070

PubMed Abstract | CrossRef Full Text | Google Scholar

38. GBD 2016 Neurology Collaborators. Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. (2019) 18:459–80. doi: 10.1016/S1474-4422(18)30499-X

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Ghai, S, Kasilingam, E, Lanzillo, R, Malenica, M, van Pesch, V, Burke, NC, et al. Needs and experiences of children and adolescents with pediatric multiple sclerosis and their caregivers: a systematic review. Children (Basel). (2021) 8:445. doi: 10.3390/children8060445

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Ghezzi, A, Pozzilli, C, Grimaldi, LM, Brescia Morra, V, Bortolon, F, Capra, R, et al. Safety and efficacy of natalizumab in children with multiple sclerosis. Neurology. (2010) 75:912–7. doi: 10.1212/WNL.0b013e3181f11daf

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Gianfrancesco, MA, Stridh, P, Rhead, B, Shao, X, Xu, E, Graves, JS, et al. Evidence for a causal relationship between low vitamin D, high BMI, and pediatric-onset MS. Neurology. (2017) 88:1623–9. doi: 10.1212/WNL.0000000000003849

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Gianfrancesco, MA, Stridh, P, Shao, X, Rhead, B, Graves, JS, Chitnis, T, et al. Genetic risk factors for pediatric-onset multiple sclerosis. Mult Scler. (2018) 24:1825–34. doi: 10.1177/1352458517733551

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Gontika, M, Skarlis, C, Artemiadis, A, Pons, R, Mastroyianni, S, Vartzelis, G, et al. HLA-DRB1 allele impact on pediatric multiple sclerosis in a Hellenic cohort. Mult Scler J Exp Transl Clin. (2020) 6:2055217320908046. doi: 10.1177/2055217320908046

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Graves, JS, Chitnis, T, Weinstock-Guttman, B, Rubin, J, Zelikovitch, AS, Nourbakhsh, B, et al. Maternal and perinatal exposures are associated with risk for pediatric-onset multiple sclerosis. Pediatrics. (2017) 139:e20162838. doi: 10.1542/peds.2016-2838

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Grebenciucova, E, and Berger, JR. Immunosenescence: the role of aging in the predisposition to neuro-infectious complications arising from the treatment of multiple sclerosis. Curr Neurol Neurosci Rep. (2017) 17:61. doi: 10.1007/s11910-017-0771-9

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Hardy, D, Chitnis, T, Waubant, E, and Banwell, B. Preventing multiple sclerosis: the pediatric perspective. Front Neurol. (2022) 13:802380. doi: 10.3389/fneur.2022.802380

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Havla, J, Warnke, C, Derfuss, T, Kappos, L, Hartung, HP, and Hohlfeld, R. Interdisciplinary risk management in the treatment of multiple sclerosis. Dtsch Arztebl Int. (2016) 113:879–86. doi: 10.3238/arztebl.2016.0879

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Hedström, AK, Olsson, T, Kockum, I, Hillert, J, and Alfredsson, L. Low sun exposure increases multiple sclerosis risk both directly and indirectly. J Neurol. (2020) 267:1045–52. doi: 10.1007/s00415-019-09677-3

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Heesen, C, Solari, A, Giordano, A, Kasper, J, and Köpke, S. Decisions on multiple sclerosis immunotherapy: new treatment complexities urge patient engagement. J Neurol Sci. (2011) 306:192–7. doi: 10.1016/j.jns.2010.09.012

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Hooge, JP, and Redekop, WK. Multiple sclerosis with very late onset. Neurology. (1992) 42:1907–10. doi: 10.1212/WNL.42.10.1907

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Huang, Z, Chen, B, Liu, X, Li, H, Xie, L, Gao, Y, et al. Effects of sex and aging on the immune cell landscape as assessed by single-cell transcriptomic analysis. Proc Natl Acad Sci U S A. (2021) 118:e2023216118. doi: 10.1073/pnas.2023216118

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Jakimovski, D, Awan, S, Eckert, SP, Farooq, O, and Weinstock-Guttman, B. Multiple sclerosis in children: differential diagnosis, prognosis, and disease-modifying treatment. CNS Drugs. (2022) 36:45–59. doi: 10.1007/s40263-021-00887-w

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Jakimovski, D, Kavak, KS, Vaughn, CB, Goodman, AD, Coyle, PK, Krupp, L, et al. Discontinuation of disease modifying therapies is associated with disability progression regardless of prior stable disease and age. Mult Scler Relat Disord. (2022) 57:103406. doi: 10.1016/j.msard.2021.103406

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Keyhanian, K, Saxena, S, Gombolay, G, Healy, BC, Misra, M, and Chitnis, T. Adipokines are associated with pediatric multiple sclerosis risk and course. Mult Scler Relat Disord. (2019) 36:101384. doi: 10.1016/j.msard.2019.101384

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Khreis, H, Bredell, C, Wai Fung, K, Hong, L, Szybka, M, Phillips, V, et al. Impact of long-term air pollution exposure on incidence of neurodegenerative diseases: a protocol for a systematic review and exposure-response meta-analysis. Environ Int. (2022) 170:107596. doi: 10.1016/j.envint.2022.107596

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Kis, B, Rumberg, B, and Berlit, P. Clinical characteristics of patients with late-onset multiple sclerosis. J Neurol. (2008) 255:697–702. doi: 10.1007/s00415-008-0778-x

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Koch-Henriksen, N, and Sørensen, PS. The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol. (2010) 9:520–32. doi: 10.1016/S1474-4422(10)70064-8

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Koch-Henriksen, N, Thygesen, LC, Stenager, E, Laursen, B, and Magyari, M. Incidence of MS has increased markedly over six decades in Denmark particularly with late onset and in women. Neurology. (2018) 90:e1954–63. doi: 10.1212/WNL.0000000000005612

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Kornek, B, Aboul-Enein, F, Rostasy, K, Milos, RI, Steiner, I, Penzien, J, et al. Natalizumab therapy for highly active pediatric multiple sclerosis. JAMA Neurol. (2013) 70:469–75. doi: 10.1001/jamaneurol.2013.923

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Krupp, LB, Tardieu, M, Amato, MP, Banwell, B, Chitnis, T, Dale, RC, et al. International Pediatric Multiple Sclerosis Study Group criteria for pediatric multiple sclerosis and immune-mediated central nervous system demyelinating disorders: revisions to the 2007 definitions. Mult Scler. (2013) 19:1261–7. doi: 10.1177/1352458513484547

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Krysko, KM, Graves, JS, Rensel, M, Weinstock-Guttman, B, Rutatangwa, A, Aaen, G, et al. Real-world effectiveness of initial disease-modifying therapies in pediatric multiple sclerosis. Ann Neurol. (2020) 88:42–55. doi: 10.1002/ana.25737

PubMed Abstract | CrossRef Full Text | Google Scholar

62. Kuhlmann, T, Ludwin, S, Prat, A, Antel, J, Brück, W, and Lassmann, H. An updated histological classification system for multiple sclerosis lesions. Acta Neuropathol. (2017) 133:13–24. doi: 10.1007/s00401-016-1653-y

PubMed Abstract | CrossRef Full Text | Google Scholar

63. Kuri, A, Jacobs, BM, Vickaryous, N, Pakpoor, J, Middeldorp, J, Giovannoni, G, et al. Epidemiology of Epstein-Barr virus infection and infectious mononucleosis in the United Kingdom. BMC Public Health. (2020) 20:912. doi: 10.1186/s12889-020-09049-x

PubMed Abstract | CrossRef Full Text | Google Scholar

64. Laman, JD, De Boer, M, and Hart, BA. CD40 in clinical inflammation: from multiple sclerosis to atherosclerosis. Dev Immunol. (1998) 6:215–22. doi: 10.1155/1998/69628

PubMed Abstract | CrossRef Full Text | Google Scholar

65. Landi, D, Ponzano, M, Nicoletti, CG, Cola, G, Cecchi, G, Grimaldi, A, et al. Patient's point of view on the use of telemedicine in multiple sclerosis: a web-based survey. Neurol Sci. (2022) 43:1197–205. doi: 10.1007/s10072-021-05398-6

PubMed Abstract | CrossRef Full Text | Google Scholar

66. Langille, MM, Rutatangwa, A, and Francisco, C. Pediatric multiple sclerosis: a review. Adv Pediatr Infect Dis. (2019) 66:209–29. doi: 10.1016/j.yapd.2019.03.003

PubMed Abstract | CrossRef Full Text | Google Scholar

67. Lorefice, L, Mura, G, Coni, G, Fenu, G, Sardu, C, Frau, J, et al. What do multiple sclerosis patients and their caregivers perceive as unmet needs? BMC Neurol. (2013) 13:177. doi: 10.1186/1471-2377-13-177

CrossRef Full Text | Google Scholar

68. Lotti, CBDC, Oliveira, ASB, Bichuetti, DB, Castro, ID, and Oliveira, EML. Late onset multiple sclerosis: concerns in aging patients. Arq Neuropsiquiatr. (2017) 75:451–6. doi: 10.1590/0004-282x20170070

PubMed Abstract | CrossRef Full Text | Google Scholar

69. Lünemann, JD, Huppke, P, Roberts, S, Brück, W, Gärtner, J, and Münz, C. Broadened and elevated humoral immune response to EBNA1 in pediatric multiple sclerosis. Neurology. (2008) 71:1033–5. doi: 10.1212/01.wnl.0000326576.91097.87

PubMed Abstract | CrossRef Full Text | Google Scholar

70. Ly, M, Stephens, S, Iruthayanathan, R, Motl, R, Finlayson, M, and Yeh, EA. Physical activity in youth with multiple sclerosis receiving the ATOMIC intervention: social connectedness above all else. Mult Scler Relat Disord. (2021) 49:102795. doi: 10.1016/j.msard.2021.102795

PubMed Abstract | CrossRef Full Text | Google Scholar

71. Marrie, RA, Yu, N, Blanchard, J, Leung, S, and Elliott, L. The rising prevalence and changing age distribution of multiple sclerosis in Manitoba. Neurology. (2010) 74:465–71. doi: 10.1212/WNL.0b013e3181cf6ec0

PubMed Abstract | CrossRef Full Text | Google Scholar

72. Martinelli Boneschi, F, Vacchi, L, Rovaris, M, Capra, R, and Comi, G. Mitoxantrone for multiple sclerosis. Cochrane Database Syst Rev. (2013) 5:Cd002127. doi: 10.1002/14651858.CD002127.pub3

CrossRef Full Text | Google Scholar

73. McKay, KA, Manouchehrinia, A, Berrigan, L, Fisk, JD, Olsson, T, and Hillert, J. Long-term cognitive outcomes in patients with pediatric-onset vs adult-onset multiple sclerosis. JAMA Neurol. (2019) 76:1028–34. doi: 10.1001/jamaneurol.2019.1546

PubMed Abstract | CrossRef Full Text | Google Scholar

74. Mikaeloff, Y, Caridade, G, Assi, S, Tardieu, M, and Suissa, S. Hepatitis B vaccine and risk of relapse after a first childhood episode of CNS inflammatory demyelination. Brain. (2007) 130:1105–10. doi: 10.1093/brain/awl368

PubMed Abstract | CrossRef Full Text | Google Scholar

75. Mikaeloff, Y, Caridade, G, Suissa, S, and Tardieu, M. Hepatitis B vaccine and the risk of CNS inflammatory demyelination in childhood. Neurology. (2009) 72:873–80. doi: 10.1212/01.wnl.0000335762.42177.07

PubMed Abstract | CrossRef Full Text | Google Scholar

76. Mirza, AI, Zhu, F, Knox, N, Forbes, JD, Bonner, C, Van Domselaar, G, et al. The metabolic potential of the paediatric-onset multiple sclerosis gut microbiome. Mult Scler Relat Disord. (2022) 63:103829. doi: 10.1016/j.msard.2022.103829

PubMed Abstract | CrossRef Full Text | Google Scholar

77. Mirza, AI, Zhu, F, Knox, N, Forbes, JD, Van Domselaar, G, Bernstein, CN, et al. Metagenomic analysis of the pediatric-onset multiple sclerosis gut microbiome. Neurology. (2022) 98:e1050–63. doi: 10.1212/WNL.0000000000013245

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Monaghesh, E, and Hajizadeh, A. The role of telehealth during COVID-19 outbreak: a systematic review based on current evidence. BMC Public Health. (2020) 20:1193. doi: 10.1186/s12889-020-09301-4

PubMed Abstract | CrossRef Full Text | Google Scholar

79. Mowry, EM, Krupp, LB, Milazzo, M, Chabas, D, Strober, JB, Belman, AL, et al. Vitamin D status is associated with relapse rate in pediatric-onset multiple sclerosis. Ann Neurol. (2010) 67:618–24. doi: 10.1002/ana.21972

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Munger, KL, Bentzen, J, Laursen, B, Stenager, E, Koch-Henriksen, N, Sørensen, TI, et al. Childhood body mass index and multiple sclerosis risk: a long-term cohort study. Mult Scler. (2013) 19:1323–9. doi: 10.1177/1352458513483889

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Münz, C. EBV infection of mice with reconstituted human immune system components. Curr Top Microbiol Immunol. (2015) 391:407–23. doi: 10.1007/978-3-319-22834-1_14

PubMed Abstract | CrossRef Full Text | Google Scholar

82. Naseri, A, Nasiri, E, Sahraian, MA, Daneshvar, S, and Talebi, M. Clinical features of late-onset multiple sclerosis: a systematic review and Meta-analysis. Mult Scler Relat Disord. (2021) 50:102816. doi: 10.1016/j.msard.2021.102816

PubMed Abstract | CrossRef Full Text | Google Scholar

83. Nielsen, NM, Gørtz, S, Hjalgrim, H, Rostgaard, K, Munger, KL, Ascherio, A, et al. Maternal diabetes and risk of multiple sclerosis in the offspring: a Danish nationwide register-based cohort study. Mult Scler. (2021) 27:1686–94. doi: 10.1177/1352458520977120

PubMed Abstract | CrossRef Full Text | Google Scholar

84. Nyirenda, MH, Fadda, G, Healy, LM, Mexhitaj, I, Poliquin-Lasnier, L, Hanwell, H, et al. Pro-inflammatory adiponectin in pediatric-onset multiple sclerosis. Mult Scler. (2021) 27:1948–59. doi: 10.1177/1352458521989090

PubMed Abstract | CrossRef Full Text | Google Scholar

85. Ostolaza, A, Corroza, J, and Ayuso, T. Multiple sclerosis and aging: comorbidity and treatment challenges. Mult Scler Relat Disord. (2021) 50:102815. doi: 10.1016/j.msard.2021.102815

PubMed Abstract | CrossRef Full Text | Google Scholar

86. Pakpoor, J, Disanto, G, Gerber, JE, Dobson, R, Meier, UC, Giovannoni, G, et al. The risk of developing multiple sclerosis in individuals seronegative for Epstein-Barr virus: a meta-analysis. Mult Scler. (2013) 19:162–6. doi: 10.1177/1352458512449682

PubMed Abstract | CrossRef Full Text | Google Scholar

87. Pakpoor, J, Seminatore, B, Graves, JS, Schreiner, T, Waldman, AT, Lotze, TE, et al. Dietary factors and pediatric multiple sclerosis: a case-control study. Mult Scler. (2018) 24:1067–76. doi: 10.1177/1352458517713343

PubMed Abstract | CrossRef Full Text | Google Scholar

88. Perdaens, O, and van Pesch, V. Molecular mechanisms of immunosenescene and inflammaging: relevance to the immunopathogenesis and treatment of multiple sclerosis. Front Neurol. (2021) 12:811518. doi: 10.3389/fneur.2021.811518

PubMed Abstract | CrossRef Full Text | Google Scholar

89. Pfeifenbring, S, Bunyan, RF, Metz, I, Röver, C, Huppke, P, Gärtner, J, et al. Extensive acute axonal damage in pediatric multiple sclerosis lesions. Ann Neurol. (2015) 77:655–67. doi: 10.1002/ana.24364

PubMed Abstract | CrossRef Full Text | Google Scholar

90. Pohl, D, Krone, B, Rostasy, K, Kahler, E, Brunner, E, Lehnert, M, et al. High seroprevalence of Epstein-Barr virus in children with multiple sclerosis. Neurology. (2006) 67:2063–5. doi: 10.1212/01.wnl.0000247665.94088.8d

PubMed Abstract | CrossRef Full Text | Google Scholar

91. Polliack, ML, Barak, Y, and Achiron, A. Late-onset multiple sclerosis. J Am Geriatr Soc. (2001) 49:168–71. doi: 10.1046/j.1532-5415.2001.49038.x

CrossRef Full Text | Google Scholar

92. Pommerich, UM, Nielsen, R, Overvad, K, Dahm, CC, Tjønneland, A, Olsen, A, et al. Diet quality is not associated with late-onset multiple sclerosis risk-a Danish cohort study. Mult Scler Relat Disord. (2020) 40:101968. doi: 10.1016/j.msard.2020.101968

PubMed Abstract | CrossRef Full Text | Google Scholar

93. Prosperini, L, de Rossi, N, Scarpazza, C, Moiola, L, Cosottini, M, Gerevini, S, et al. Natalizumab-related progressive multifocal leukoencephalopathy in multiple sclerosis: findings from an Italian independent registry. PLoS One. (2016) 11:e0168376. doi: 10.1371/journal.pone.0168376

PubMed Abstract | CrossRef Full Text | Google Scholar

94. Qiu, W, Wu, JS, Castley, A, James, I, Joseph, J, Christiansen, FT, et al. Clinical profile and HLA-DRB1 genotype of late onset multiple sclerosis in Western Australia. J Clin Neurosci. (2010) 17:1009–13. doi: 10.1016/j.jocn.2009.12.011

PubMed Abstract | CrossRef Full Text | Google Scholar

95. Raja, JM, Elsakr, C, Roman, S, Cave, B, Pour-Ghaz, I, Nanda, A, et al. Apple watch, wearables, and heart rhythm: where do we stand? Ann Transl Med. (2019) 7:417. doi: 10.21037/atm.2019.06.79

PubMed Abstract | CrossRef Full Text | Google Scholar

96. Ray, D, and Yung, R. Immune senescence, epigenetics and autoimmunity. Clin Immunol. (2018) 196:59–63. doi: 10.1016/j.clim.2018.04.002

PubMed Abstract | CrossRef Full Text | Google Scholar

97. Rieckmann, P, Boyko, A, Centonze, D, Elovaara, I, Giovannoni, G, Havrdová, E, et al. Achieving patient engagement in multiple sclerosis: a perspective from the multiple sclerosis in the 21st century steering group. Mult Scler Relat Disord. (2015) 4:202–18. doi: 10.1016/j.msard.2015.02.005

PubMed Abstract | CrossRef Full Text | Google Scholar

98. Rostgaard, K, Balfour, HH Jr, Jarrett, R, Erikstrup, C, Pedersen, O, Ullum, H, et al. Primary Epstein-Barr virus infection with and without infectious mononucleosis. PLoS One. (2019) 14:e0226436. doi: 10.1371/journal.pone.0226436

PubMed Abstract | CrossRef Full Text | Google Scholar

99. Schweitzer, F, Laurent, S, Fink, GR, Barnett, MH, Reddel, S, Hartung, HP, et al. Age and the risks of high-efficacy disease modifying drugs in multiple sclerosis. Curr Opin Neurol. (2019) 32:305–12. doi: 10.1097/WCO.0000000000000701

PubMed Abstract | CrossRef Full Text | Google Scholar

100. Sebastian, P, Cherbuin, N, Barcellos, LF, Roalstad, S, Casper, C, Hart, J, et al. Association between time spent outdoors and risk of multiple sclerosis. Neurology. (2022) 98:e267–78. doi: 10.1212/WNL.0000000000013045

PubMed Abstract | CrossRef Full Text | Google Scholar

101. Shirani, A, Zhao, Y, Petkau, J, Gustafson, P, Karim, ME, Evans, C, et al. Multiple sclerosis in older adults: the clinical profile and impact of interferon Beta treatment. Biomed Res Int. (2015) 2015:451912. doi: 10.1155/2015/451912

PubMed Abstract | CrossRef Full Text | Google Scholar

102. Solaro, C, Ponzio, M, Moran, E, Tanganelli, P, Pizio, R, Ribizzi, G, et al. The changing face of multiple sclerosis: prevalence and incidence in an aging population. Mult Scler. (2015) 21:1244–50. doi: 10.1177/1352458514561904

PubMed Abstract | CrossRef Full Text | Google Scholar

103. Solomon, AJ. Diagnosis, differential diagnosis, and misdiagnosis of multiple sclerosis. Continuum (Minneap Minn). (2019) 25:611–35. doi: 10.1212/CON.0000000000000728

PubMed Abstract | CrossRef Full Text | Google Scholar

104. Song, J, Westerlind, H, McKay, KA, Almqvist, C, Stridh, P, Kockum, I, et al. Familial risk of early- and late-onset multiple sclerosis: a Swedish nationwide study. J Neurol. (2019) 266:481–6. doi: 10.1007/s00415-018-9163-6

PubMed Abstract | CrossRef Full Text | Google Scholar

105. Stephens, S, Schneiderman, JE, Finlayson, M, Berenbaum, T, Motl, RW, and Yeh, EA. Feasibility of a theory-informed mobile app for changing physical activity in youth with multiple sclerosis. Mult Scler Relat Disord. (2022) 58:103467. doi: 10.1016/j.msard.2021.103467

PubMed Abstract | CrossRef Full Text | Google Scholar

106. Thompson, AJ, Banwell, BL, Barkhof, F, Carroll, WM, Coetzee, T, Comi, G, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. (2018) 17:162–73. doi: 10.1016/S1474-4422(17)30470-2

PubMed Abstract | CrossRef Full Text | Google Scholar

107. Tindall, T, Topcu, G, Thomas, S, Bale, C, Evangelou, N, Drummond, A, et al. Developing a patient care pathway for emotional support around the point of multiple sclerosis diagnosis: a stakeholder engagement study. Health Expect. (2023) 26:858–68. doi: 10.1111/hex.13711

PubMed Abstract | CrossRef Full Text | Google Scholar

108. Tremlett, H, Fadrosh, DW, Faruqi, AA, Hart, J, Roalstad, S, Graves, J, et al. Associations between the gut microbiota and host immune markers in pediatric multiple sclerosis and controls. BMC Neurol. (2016) 16:182. doi: 10.1186/s12883-016-0703-3

PubMed Abstract | CrossRef Full Text | Google Scholar

109. Tremlett, H, Zhu, F, Arnold, D, Bar-Or, A, Bernstein, CN, Bonner, C, et al. The gut microbiota in pediatric multiple sclerosis and demyelinating syndromes. Ann Clin Transl Neurol. (2021) 8:2252–69. doi: 10.1002/acn3.51476

PubMed Abstract | CrossRef Full Text | Google Scholar

110. Tutuncu, M, Tang, J, Zeid, NA, Kale, N, Crusan, DJ, Atkinson, EJ, et al. Onset of progressive phase is an age-dependent clinical milestone in multiple sclerosis. Mult Scler. (2013) 19:188–98. doi: 10.1177/1352458512451510

PubMed Abstract | CrossRef Full Text | Google Scholar

111. Valentino, P, Marnetto, F, Martire, S, Malucchi, S, Bava, CI, Popovic, M, et al. Serum neurofilament light chain levels in healthy individuals: a proposal of cut-off values for use in multiple sclerosis clinical practice. Mult Scler Relat Disord. (2021) 54:103090. doi: 10.1016/j.msard.2021.103090

PubMed Abstract | CrossRef Full Text | Google Scholar

112. Vaughn, CB, Jakimovski, D, Kavak, KS, Ramanathan, M, Benedict, RHB, Zivadinov, R, et al. Epidemiology and treatment of multiple sclerosis in elderly populations. Nat Rev Neurol. (2019) 15:329–42. doi: 10.1038/s41582-019-0183-3

PubMed Abstract | CrossRef Full Text | Google Scholar

113. Virgilio, E, Vecchio, D, Crespi, I, Serino, R, Cantello, R, Dianzani, U, et al. Cerebrospinal tau levels as a predictor of early disability in multiple sclerosis. Mult Scler Relat Disord. (2021) 56:103231. doi: 10.1016/j.msard.2021.103231

PubMed Abstract | CrossRef Full Text | Google Scholar

114. Vural, P, Zenginler Yazgan, Y, Tarakci, E, Guler, S, and Saltik, S. The effects of online exercise training on physical functions and quality of life in patients with pediatric-onset multiple sclerosis. Mult Scler Relat Disord. (2023) 74:104710. doi: 10.1016/j.msard.2023.104710

PubMed Abstract | CrossRef Full Text | Google Scholar

115. Weideman, AM, Barbour, C, Tapia-Maltos, MA, Tran, T, Jackson, K, Kosa, P, et al. New multiple sclerosis disease severity scale predicts future accumulation of disability. Front Neurol. (2017) 8:598. doi: 10.3389/fneur.2017.00598

PubMed Abstract | CrossRef Full Text | Google Scholar

116. Weideman, AM, Tapia-Maltos, MA, Johnson, K, Greenwood, M, and Bielekova, B. Meta-analysis of the age-dependent efficacy of multiple sclerosis treatments. Front Neurol. (2017) 8:577. doi: 10.3389/fneur.2017.00577

PubMed Abstract | CrossRef Full Text | Google Scholar

117. Ysrraelit, MC, and Correale, J. Impact of Andropause on multiple sclerosis. Front Neurol. (2021) 12:766308. doi: 10.3389/fneur.2021.766308

PubMed Abstract | CrossRef Full Text | Google Scholar

118. Zanghì, A, Avolio, C, Amato, MP, Filippi, M, Trojano, M, Patti, F, et al. First-line therapies in late-onset multiple sclerosis: an Italian registry study. Eur J Neurol. (2021) 28:4117–23. doi: 10.1111/ene.15006

PubMed Abstract | CrossRef Full Text | Google Scholar

119. Ziaei, A, Lavery, AM, Shao, XM, Adams, C, Casper, TC, Rose, J, et al. Gene-environment interactions increase the risk of pediatric-onset multiple sclerosis associated with ozone pollution. Mult Scler. (2022) 28:1330–9. doi: 10.1177/13524585211069926

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: multiple sclerosis, aging, pediatric-onset, late-onset, immunosenescence, risk factors, unmet need, engagement

Citation: Capasso N, Virgilio E, Covelli A, Giovannini B, Foschi M, Montini F, Nasello M, Nilo A, Prestipino E, Schirò G, Sperandei S, Clerico M and Lanzillo R (2023) Aging in multiple sclerosis: from childhood to old age, etiopathogenesis, and unmet needs: a narrative review. Front. Neurol. 14:1207617. doi: 10.3389/fneur.2023.1207617

Received: 17 April 2023; Accepted: 15 May 2023;
Published: 02 June 2023.

Edited by:

Vilija Jokubaitis, Monash University, Australia

Reviewed by:

Timothy Coetzee, National Multiple Sclerosis Society, United States
Bianca Weinstock-Guttman, University at Buffalo, United States

Copyright © 2023 Capasso, Virgilio, Covelli, Giovannini, Foschi, Montini, Nasello, Nilo, Prestipino, Schirò, Sperandei, Clerico and Lanzillo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Roberta Lanzillo, cm9iZXJ0YS5sYW56aWxsb0B1bmluYS5pdA==

These authors have contributed equally to this work and share first authorship

These authors have contributed equally to this work and share last authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.