Older adults with multiple sclerosis (MS) face unique issues related to the combined effects of MS and age-related changes, which often present with overlapping symptoms that complicate assessment and treatment decisions. In this review, based on the Consortium of MS Centers’ Aging and MS Consensus Statement committee meeting in 2024, we address the contributions of aging in MS by focusing on direct, biological aging effects on MS pathology and comorbid age-related changes in physical and cognitive function. Features of biological aging include cellular senescence and immune dysregulation, which may drive disease progression in MS through a variety of proinflammatory mediators that may maintain low levels of chronic inflammation in the immune and central nervous system compartments and offset regulatory processes, ultimately impairing remyelination and increasing neurodegeneration. Measuring biological aging in MS may help identify individuals at risk of worse MS outcomes and support gerotherapeutic treatments that target aging mechanisms. Compounding any direct effects of aging on MS pathology, aging-related impairments in neuromuscular function and cognition can worsen functional outcomes in people with MS. Characteristics of cognitive impairments in MS affecting attention and processing speed occur early in the disease course and are distinct from other age-associated neurodegenerative disorders, such as Alzheimer disease, that commonly affect language and executive function domains. As MS clinicians care for growing numbers of older adults with MS, a more comprehensive understanding of the interplay between aging and MS-related changes can improve the timing and modality of treatments to optimize MS neurogeriatric care.

From the Division of MS/Neuroimmunology, The Ohio State University, Wexner Medical Center, Columbus, OH (YZ); UCHealth Yampa Valley Medical Center, Steamboat Springs, CO (PB); Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (SAM); Department of Neurology, Georgetown University Medical Center, Washington, DC, (JW); Departments of Medicine and Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada (RAM); Nova Scotia Health, Halifax, Nova Scotia, Canada (RAM); Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, Department of Neurology, University of Colorado Anschutz School of Medicine, Aurora, CO (JB); Department of Neurological Sciences, University of Nebraska, Omaha, NE (RStewart); Independence Care System, Brooklyn, NY (RStacom); private practice, Greensboro, NC (MDB); Departments of Internal Medicine and Geriatrics, University of Nebraska Medical Center, Omaha, NE (MTC); Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY (FWF); Multiple Sclerosis Center, Holy Name Medical Center, Teaneck, NJ (FWF); Department of Neurology, University of Colorado Anschutz School of Medicine, Aurora, CO (JRC); Department of Clinical Neurology, Johns Hopkins School of Medicine, Baltimore, MD (SDN); Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV (LHH); Department of Neurosciences, University of California San Diego, San Diego, CA (JSG). 

Yinan Zhang, MD, 395 West 12th Ave, 7th Floor, Columbus, OH 43210; 

This manuscript stems from presentations and discussions at the Consortium of Multiple Sclerosis Centers (CMSC) Aging and Multiple Sclerosis Consensus Conference held June 1-2, 2024, and is based on the CMSC publication “MS and Aging: A Summary Statement From a CMSC Consensus Conference.”

 Jeffrey Wilken, PhD, has been a speaker for Biogen, EMD Serono, and Sanofi; a paid consultant for Bayer and Sanofi; and has received research funding from Biogen and Sanofi. Ruth Ann Marrie, PhD, MD, receives research funding from the Arthritis Society, the Canadian Institutes of Health Research, Children’s Hospital Research Institute of Manitoba, Consortium of Multiple Sclerosis Centers, Crohn’s and Colitis Canada, Manitoba Medical Service Foundation, MS Canada, National Multiple Sclerosis Society, Pfizer Foundation, Public Health Agency of Canada, and the US Department of Defense. She is a coinvestigator on studies receiving funding from Biogen Idec and Roche Canada, and holds the Multiple Sclerosis Clinical Research Chair at Dalhousie University. Jacquelyn Bainbridge, PharmD, has served on advisory boards for EMD Serono, Novartis, and TG Therapeutics. Renee Stewart, APRN-DNP, has been on an advisory board for Genentech. Rachael Stacom, NP, has served on advisory boards for Genentech and TG Therapeutics. Frederick W. Foley, PhD, has been on advisory boards for Bayer and Biogen; has been a paid consultant for Biogen; and has been a speaker for EMD Serono and Sanofi. John R. Corboy, MD, MA, has received compensation as the medical director of the Rocky Mountain MS Center and associate editor of the 

. He has received research support from EMD Serono, the National Institute of Health via the Immune Tolerance Network, and the National Multiple Sclerosis Society. Le H. Hua, MD, has received personal fees for speaking, consulting, and advisory board activities from Alexion, EMD Serono, Genentech, Genzyme, Horizon, Novartis, and TG Therapeutics, and has had research support paid to her institution from Genentech outside the submitted work. Authors Yinan Zhang, MD; Patty Bobryk, MHS, PT, MSCS, ATP; Sarah A. Morrow, MD, FRCPC, MS; Mona D. Bostick, RDN; Maureen T. Choman, MD; Scott D. Newsome, DO; and Jennifer S. Graves, MD, PhD, MAS, have nothing to disclose.

Yinan Zhang, MD

Patty Bobryk, MHS, PT, MSCS, AT

Sarah A. Morrow, MD, MS, FRCPC

Jeffrey Wilken, PhD

Ruth Ann Marrie, MD, PhD, FRCPC

Jacquelyn Bainbridge, PharmD

Renee Stewart, APRN-DNP

Rachael Stacom, NP

Mona D. Bostick, RDN, LDN

Maureen T. Choman, MD

Frederick W. Foley, Ph.D.

John R. Corboy, MD, MA

Scott D. Newsome, DO, MSCS

Le H. Hua, MD

Jennifer S. Graves, MD, PhD, MAS

Understanding age-related changes in multiple sclerosis (MS) may help inform treatment decisions that address normal aging and MS-related aging processes.

Clinicians should recognize and assess for earlier and more severe onset of age-related decline in physical function, compounding MS-induced neurological deficits.

Cognitive domains, such as processing speed and attention, are more commonly affected in MS compared with other neurodegenerative disorders such as Alzheimer disease, which can affect language skills and executive function.

Disease activity in multiple sclerosis (MS) diminishes with age, with fewer relapses and decreased new T2 lesion formation on brain and spine MRI.

 Concurrently, age increases the risk and rate of developing nonrelapse-related disability accumulation.

 Age strongly correlates with declines in physical and cognitive function in MS, and there is overlap between MS progression and non-MS age-related changes. Older adults experience the combined effects of MS and age-related changes (

). Providers and patients often face challenges in distinguishing whether neurological symptoms are due to aging, MS-specific decline, or an interaction of the two. In this review, we discuss pathophysiological changes and biomarkers of aging in MS and describe age-related changes in physical and cognitive function in people with MS. Understanding aging processes and their role in the MS disease course may lead to improved markers of disease progression and uncover new targets for therapy.

Mechanisms and Changes Related to MS and Aging

Pathophysiological Changes of Aging and MS

Although chronological age is the greatest risk factor for MS disease progression, the age at which people experience progression or reach disability milestones varies. Individual differences in biological age may explain this variation. Biological age reflects the cellular, molecular, and genetic mechanisms of aging, and emerging evidence suggests accelerated biological aging in people with MS.

 Aging mechanisms are related to damage accumulation, response to damage, and loss of reserve and compensatory ability, which collectively drive the irreversible decline in function from accumulation of cellular and molecular damage over time.

Aging is associated with cellular senescence and age-related immune exhaustion and dysregulation, referred to as immunosenescence.

 When cells permanently exit the cell cycle and become senescent in response to damage and stressors, the accumulation of senescent cells produces mediators of inflammation through the senescence-associated secretory phenotype (SASP).

 SASP mediators hinder remyelination and contribute to neurodegeneration and functional decline.

 In MS, particularly in progressive MS, senescent cells are in the tertiary lymphoid aggregates within the brain meninges and contribute to widespread microglial activation and SASP expression.

 In postmortem MS brain tissues, there is elevated expression of the senescence marker 

 in MS lesions compared with normal white matter.

 One senotherapeutic approach is to try to remove senescent cells using senolytic agents that disrupt their antiapoptotic pathways. Studies in experimental autoimmune encephalomyelitis, the widely used animal model of MS, have shown that some senolytics lead to improved function and survival.

 A clinical trial of senolytics in MS is underway (NCT07270120).

Immunosenescence in MS results in a shift of immune cells toward terminally differentiated lymphocytes and activated microglia.

 Thymic involution occurs with aging and results in decreased naive T cells and increased memory T cells, which leads to decreased T-cell receptor repertoire and impaired antigen recognition.

 Compared with controls, people with MS tend to have a lower frequency of naive T cells and a higher frequency of terminally differentiated effector memory T cells.

 B cells also decline with age, with a decrease in naive B cells and an increase in dysfunctional antigen-experienced B cells.

 Microglia are activated in chronic active MS lesions and drive neuroinflammation by secreting SASP mediators.

Other aging processes also play a role in MS progression. Aging-induced oxidative stress drives cellular senescence and mitochondrial dysfunction that damage neurons.

 Increased production of reactive oxygen species promotes oxidative stress and hinders energy production.

 Age-associated increases in gastrointestinal permeability lead to gut dysbiosis, resulting in the release of pathogen-associated molecular patterns, which are central nervous system penetrant and contribute to microglial activation.

 Aging also alters the gut microbiome, which may also contribute to MS progression.

Aging biomarkers reflect mechanisms of aging and provide insights into the processes that drive the onset and progression of age-related diseases. There are a variety of biomarkers reflecting the different hallmarks of aging, and several have been studied in people with MS. Multiple studies have measured telomere length in people with MS, where the progressive shortening of the protective endcaps of genomic DNA contributes to genomic instability and the DNA damage response and, ultimately, to replicative senescence.

 Several studies, but not all, have found shorter telomere lengths in people with MS compared with a control group, and there appears to be an association between shorter telomere length and greater disability in MS.

Aging has also been associated with epigenetic alterations. Epigenetic clocks have been derived from differential methylation patterns to predict life span (mortality) or health span–based outcomes.

 In people with MS, epigenetic age acceleration can be seen in both adults and children.

 As clinically accessible tools, composite biomarkers such as the National Health and Nutrition Examination Survey Biological Age Index (NHANES BAI), comprised of a 10-item clinical index of physiological measures and routine lab tests, may also be useful. The NHANES BAI has been shown to be elevated in people with MS compared with controls.

 Reproductive aging, marked by age-related decline in sex steroid hormones, has been shown to contribute to disability accumulation in women with MS, as measured by levels of anti-Müllerian hormone.

Although the precise mechanisms by which biological aging drives MS disease activity and progression are unclear, measuring biological aging in MS may advance clinical practice by informing clinical trial design of drugs that target processes, referred to as gerotherapeutics, which are studied in age-related diseases. Aging biomarkers also have the potential to stratify disease severity in MS if strong associations can be determined between biological aging and MS disease outcomes.

MS impacts overall physical function, neuromuscular performance, and physical activity levels, but there is only a modest understanding of the contribution of normal aging processes to these measures in older populations. Aging leads to reduced physiological reserve and performance,

 and there is overlap between MS disease-specific mechanisms and age-related health changes. The ability to identify and understand the similarities and distinctions between aging and the impact of MS on physical functioning may enable appropriate, targeted, and timely clinical interventions.

Physical function is divided into basic activities that are essential for independent living and complex activities that are discretionary and not required for independent living, but may affect quality of life.

 Many factors contribute to overall physical functioning beyond the presence or absence of disease, including perceptual, environmental, and behavioral considerations. The Short Physical Performance Battery (SPPB) is a tool that measures physical function and mobility in older adults.

 It includes assessments of balance, gait speed, and lower extremity strength, with a higher summary score indicating greater functional ability. The SPPB score typically declines with age in the general population.

 This tool has also been validated as a measure of lower-extremity physical function in people with MS across the life span.

 In a study that compared 345 people with MS and 174 controls across 6 age groups, SPPB scores declined along the life span in people with MS to a greater extent than those of controls.

 Strength was a robust component of physical functioning across most age groups.

Further support for the amplified decline of physical functioning in people with MS was demonstrated in a study that included 698 people with MS (aged 29-71 years) and 226 controls (aged 18-72 years).

 Performance tests were administered, including ambulation (Timed 25-Foot Walk Test) and upper extremity function (9-Hole Peg Test). The progression of motor decline increased synergistically in individuals with MS as they aged.

Accelerated decline in physical functioning during middle age was observed in people with MS in a longitudinal study. The 10-Item Physical Functioning Scale (PF-10) was used to assess various aspects of physical functioning in 733 women with MS over the course of 25 years.

 PF-10 scores declined in both the controls and in people with MS, but the decline was 3 to 4 times faster in midlife for those with MS. Specifically, a 45-year-old woman with MS exhibited physical function levels comparable to those of a 75-year-old woman without MS, suggesting a 30-year acceleration in functional decline due to the disease.

Physical activity declines with age in the general population, but this decline is more pronounced in people with MS.

 Recent study data confirm that older adults with MS are much less physically active than age-matched individuals without MS, and this can lead to compounding deleterious effects on physical function and worsening overall health.

 Older adults with MS exhibited lower step counts and greater sedentary time compared with controls without MS, despite adjusting for age, sex, and comorbidities. These differences may reflect not only the impact of aging but also MS-specific factors such as fatigue, balance issues, and reduced motor function.

Frailty is an age-related state characterized by decreased physiological reserve and increased vulnerability to adverse health outcomes. Common frailty measurements include the frailty phenotype, which assesses the presence of 3 or more out of 5 clinical manifestations, including weight loss, slow walking speed, low physical activity, exhaustion, and weak grip strength, and the Frailty Index, which evaluates the accumulation of deficits across a list of health-related variables that can be customized to the relevant clinical or research setting.

 In people with MS, frailty is associated with high disability, disease duration, and progressive MS.

 Although frailty may overlap with neurological disability in MS, its additional elements help capture the clinical complexity in MS and guide management and prognosis.

Muscle performance naturally declines with age due to physiological changes, such as decreased muscle mass, strength, and endurance.

 Neuromuscular function is the muscle’s ability to generate force and power, including the underlying neural and muscular determinants (such as voluntary activation and contractile properties). The combination of neural function (central) and muscular properties (peripheral) provides neuromuscular function, which then yields physical function and health-related outcomes, such as quality of life. In MS, age and the disease itself combine to reduce neuromuscular function.

 The rate of force development, which represents the ability to rapidly generate muscle force at the start of a maximal contraction, was up to 70% lower in people with MS than in controls across age groups. This becomes important in functional skills, where speed of contraction is essential, for example, a quick balance correction to prevent a fall.

 The study data also revealed that this decline begins early in the disease course and accelerates through middle age, with the most pronounced reductions seen in older adults with MS. An additional study investigated muscle power (work over time) and found a similar pattern of loss that was most evident in early to middle age, where changes in controls occurred later in the life span.

The authors suggest that this should be an area of targeted therapy early in the disease trajectory.

People with MS experience more pronounced and complex alterations in muscle function. Research has shown that people with MS exhibit substantial impairment compared with controls in isometric and dynamic muscle strength, particularly in knee extensors and plantar flexors, with deficits ranging from 18% to 38%.

 Plantar flexors of the ankle were preferentially affected in people with MS vs age-matched controls, and these deficits are linked to limitations in walking and stair climbing. In addition, people with MS demonstrate an altered muscle oxidative mechanism, leading to impaired exercise tolerance at the muscle level.

Aging is associated with worsening cognition, specifically in executive function, prospective memory, learning and retrieval, information processing speed, shifting attention, and visuoperceptual judgment.

 Cognitive impairment (CI) in people with MS most commonly involves slowed cognitive processing speed and deficits in episodic memory, executive function, and verbal fluency.

 Visuospatial ability is affected less frequently.

 Aging results in increased prevalence of CI in people with MS, which, in one study, was seen in 77.4% of adults over age 55 compared with 42.8% of younger patients,

 and CI was found in 48% of people with MS who had 3 decades of disease duration.

Only a few studies have directly examined the interaction between aging and cognitive decline in MS. For the most part, these studies have not demonstrated accelerated cognitive worsening or an interaction between the aging process and cognition in older people with MS.

 However, in late-onset MS, working memory and visuospatial memory (learning and recall) were more frequently and severely impaired than in people with earlier-onset MS, suggesting that MS-associated cognitive changes may be exacerbated by age-related brain changes, leading to reduced reserve and accelerated cognitive decline.

CI usually presents differently in older people with MS than in people with other degenerative diseases, such as amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD). Studies have found there may be a similar decrease in semantic fluency in people with MS and people with aMCI.

 However, people with aMCI typically perform much worse on delayed memory measures than people with MS. In addition, people with progressive MS have greater deficits in attention, episodic memory, and information processing speed, whereas people with AD have impaired learning, memory, and verbal skills.

 CI in older people with MS, as well as the potential overlap with other neurogenerative diseases such as AD, is still understudied and poorly understood. Other age-related conditions, such as vascular comorbidities, further contribute to CI in MS.

 There is still much to learn regarding the impact of aging on the MS disease course, the risk of other causes of cognitive impairment in people with MS, and the impact of other common comorbidities.

With improved disease management and increased life span, more individuals with MS are entering older age and are experiencing the dual burden of MS-related impairments and age-related decline. MS introduces disease-specific impairments that often result in functional limitations earlier and more severely than those seen in typical aging. As the MS population ages, clinicians must consider the interaction between age and MS-related decline and incorporate assessments and interventions that address both processes.

Trojano M, Liguori M, Bosco Zimatore G, et al. Age-related disability in multiple sclerosis. 

. 2002;51(4):475-480. doi:10.1002/ana.10147

Confavreux C, Vukusic S. Age at disability milestones in multiple sclerosis. 

2006;129(pt 3):595-605. doi:10.1093/brain/awh714

Scalfari A, Neuhaus A, Daumer M, Ebers GC, Muraro PA. Age and disability accumulation in multiple sclerosis. 

2011;77(13):1246-1252. doi:10.1212/WNL.0b013e318230a17d

Scalfari A, Lederer C, Daumer M, Nicholas R, Ebers GC, Muraro PA. The relationship of age with the clinical phenotype in multiple sclerosis. 

2016;22(13):1750-1758. doi:10.1177/1352458516630396

Weinshenker BG, Bass B, Rice GP, et al. The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability. 

 1989;112 (pt 1):133-146. doi:10.1093/brain/112.1.133

Zhang Y, Atkinson J, Burd CE, Graves J, Segal BM. Biological aging in multiple sclerosis. 

 2023;29(14):1701-1708. doi:10.1177/13524585231204122

Graves JS, Krysko KM, Hua LH, Absinta M, Franklin RJM, Segal BM. Ageing and multiple sclerosis. 

 2023;22(1):66-77. doi:10.1016/S1474
-4422(22)00184-3

Kuhlmann T, Moccia M, Coetzee T, et al; International Advisory Committee on Clinical Trials in Multiple Sclerosis. Multiple sclerosis progression: time for a new mechanism-driven framework. 

 2023;22(1):78-88. doi:10.1016/S1474-4422(22)00289-7

López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. Hallmarks of aging: an expanding universe. 

 2023;186(2):243-278. doi:10.1016/j.cell.2022.11.001

Suryadevara V, Hudgins AD, Rajesh A, et al. SenNet recommendations for detecting senescent cells in different tissues. 

 2024;25(12):1001-1023. doi:10.1038/s41580-024-00738-8

Acosta JC, Banito A, Wuestefeld T, et al. A complex secretory program orchestrated by the inflammasome controls paracrine senescence. 

Muñoz-Espín D, Serrano M. Cellular senescence: from physiology to pathology. 

Nicaise AM, Wagstaff LJ, Willis CM, et al. Cellular senescence in progenitor cells contributes to diminished remyelination potential in progressive multiple sclerosis. 

 2019;116(18):9030-9039. doi:10.1073/pnas
.1818348116

Sethi V, Nair G, Absinta M, et al. Slowly eroding lesions in multiple sclerosis. 

. 2017;23(3):464-472. doi:10.1177/1352458516655403

Lassmann H, van Horssen J, Mahad D. Progressive multiple sclerosis: pathology and pathogenesis. 

 2012;8(11):647-656. doi:10.1038/nrneurol.2012.168

LaPak KM, Burd CE. The molecular balancing act of p16(INK4a) in cancer and aging. 

 2014;12(2):167-183. doi:10.1158/1541-7786.MCR-13-0350

Liu Y, Sanoff HK, Cho H, et al. Expression of p16

 in peripheral blood T-cells is a biomarker of human aging. 

 2009;8(4):439-448. doi:10.1111/j.1474-9726.2009.00489.x

Atkinson J, Dokiburra A, Groover H, Godbout JP, Segal BM, Zhang Y. Targeting senescent microglia in progressive multiple sclerosis: a geroscience-informed approach. 

2025;16:1681724. doi:10.3389/fimmu.2025.1681724

Liu Z, Liang Q, Ren Y, et al. Immunosenescence: molecular mechanisms and diseases. 

 2023;8(1):200. doi:10.1038/s41392-023-01451-2

Palmer DB. The effect of age on thymic function. 

 2013;4:316. doi:10.3389/fimmu.2013.00316

Pawelec G. Hallmarks of human “immunosenescence”: adaptation or dysregulation? 

 2012;9(1):15. doi:10.1186/1742-4933-9-15

Zuroff L, Rezk A, Shinoda K, et al. Immune aging in multiple sclerosis is characterized by abnormal CD4 T cell activation and increased frequencies of cytotoxic CD4 T cells with advancing age. 

 2022;82:104179. doi:10.1016/j.ebiom.2022.104179

de Mol J, Kuiper J, Tsiantoulas D, Foks AC. The dynamics of B cell aging in health and disease. 

 2021;12:733566. doi:10.3389/fimmu.2021.733566

Muzio L, Viotti A, Martino G. Microglia in neuroinflammation and neurodegeneration: from understanding to therapy. 

. 2021;15:742065. doi:10.3389/fnins.2021.742065

Holmström KM, Finkel T. Cellular mechanisms and physiological consequences of redox-dependent signalling. 

. 2014;15(6):411-421. doi:10.1038/nrm3801

Lin MT, Beal MF. Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. 

2006;443(7113):787-795. doi:10.1038/nature05292

Giorgi C, Marchi S, Simoes ICM, et al. Mitochondria and reactive oxygen species in aging and age-related diseases. 

. 2018;340:209-344. doi:10.1016/bs.ircmb.2018.05.006

Fernández A, Quintana E, Velasco P, et al. Senescent accelerated prone 8 (SAMP8) mice as a model of age dependent neuroinflammation. 

2021;18(1):75. doi:10.1186/s12974-021-02104-3

Fettig NM, Pu A, Osborne LC, Gommerman JL. The influence of aging and the microbiome in multiple sclerosis and other neurologic diseases. 

2024;325(1):166-189. doi:10.1111/imr.13361

Bühring J, Hecker M, Fitzner B, Zettl UK. Systematic review of studies on telomere length in patients with multiple sclerosis. 

 2021;12(5):1272-1286. doi:10.14336/AD.2021.0106

Krysko KM, Henry RG, Cree BAC, et al. Telomere length is associated with disability progression in multiple sclerosis. 

 2019;86(5):671-682. doi:10.1002/ana.25592

Hecker M, Fitzner B, Jäger K, et al. Leukocyte telomere length in patients with multiple sclerosis and its association with clinical phenotypes. 

2021;58(6):2886-2896. doi:10.1007/s12035-021-02315-yy

Habib R, Ocklenburg S, Hoffjan S, Haghikia A, Epplen JT, Arning L. Association between shorter leukocyte telomeres and multiple sclerosis. 

2020;341:577187. doi:10.1016/j.jneuroim.2020.577187

Horvath S, Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. 

. 2018;19(6):371-384. doi:10.1038/s41576-018-0004-3

Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. 

. 2018;10(4):573-591. doi:10.18632/aging.101414

Theodoropoulou E, Alfredsson L, Piehl F, Marabita F, Jagodic M. Different epigenetic clocks reflect distinct pathophysiological features of multiple sclerosis. 

2019;11(12):1429-1439. doi:10.2217/epi-2019-0102

Maltby V, Xavier A, Ewing E, et al. Evaluation of cell-specific epigenetic age acceleration in people with multiple sclerosis. 

 2023;101(7):e679-e689. doi:10.1212/WNL.0000000000207489

Goyne C, Fair AE, Yilmaz D, et al; US Network of Pediatric MS Centers. Epigenetic aging in pediatric-onset multiple sclerosis. 

 2025;104(12):e213673. doi:10.1212/WNL.0000000000213673

Miner AE, Yang JH, Kinkel RP, Graves JS. The NHANES Biological Age Index demonstrates accelerated aging in MS patients. 

2023;77:104859. doi:10.1016/j.msard.2023.104859

Graves JS, Henry RG, Cree BAC, et al. Ovarian aging is associated with gray matter volume and disability in women with MS. 

2018;90(3):e254-e260. doi:10.1212/WNL.0000000000004843

Khan SS, Singer BD, Vaughan DE. Molecular and physiological manifestations and measurement of aging in humans. 

 2017;16(4):624-633. doi:10.1111/acel.12601

Painter P, Stewart AL, Carey S. Physical functioning: definitions, measurement, and expectations. 

 1999;6(2):110-123. doi:10.1016/s1073
-4449(99)70028-2

Dugan SA, Gabriel KP, Lange-Maia BS, Karvonen-Gutierrez C. Physical activity and physical function: moving and aging. 

2018;45(4):723-736. doi:10.1016/j.ogc.2018.07.009

Guralnik JM, Simonsick EM, Ferrucci L, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. 

 1994;49(2):M85-M94. doi:10.1093/geronj/49.2.m85

de Fátima Ribeiro Silva C, Ohara DG, Matos AP, Pinto ACPN, Pegorari MS. Short Physical Performance Battery as a measure of physical performance and mortality predictor in older adults: a comprehensive literature review. 

. 2021;18(20):10612. doi:10.3390/ijerph182010612

Motl RW, Learmonth YC, Wójcicki TR, et al. Preliminary validation of the short physical performance battery in older adults with multiple sclerosis: secondary data analysis. 

. 2015;15:157. doi:10.1186/s12877-015-0156-3

Jeng B, Šilić P, Bollaert RE, Sandroff BM, Motl RW. Physical function across the lifespan in adults with multiple sclerosis: an application of the Short Physical Performance Battery. 

. 2023;73:104624. doi:10.1016/j.msard.2023.104624

Roy S, Frndak S, Drake AS, et al. Differential effects of aging on motor and cognitive functioning in multiple sclerosis. 

 2017;23(10):1385-1393. doi:10.1177/1352458516679036

Cortese M, Bjornevik K, Chitnis T, Ascherio A, Munger KL. Aging with multiple sclerosis: a longitudinal study of physical function, mental health, and memory in two cohorts of US women. 

. 2022;28(1):121-131. doi:10.1177/13524585211007739

Milanović Z, Pantelić S, Trajković N, Sporiš G, Kostić R, James N. Age-related decrease in physical activity and functional fitness among elderly men and women. 

Klaren RE, Motl RW, Dlugonski D, Sandroff BM, Pilutti LA. Objectively quantified physical activity in persons with multiple sclerosis. 

2013;94(12):2342-2348. doi:10.1016/j.apmr.2013.07.011

Bollaert RE, Motl RW. Physical and cognitive functions, physical activity, and sedentary behavior in older adults with multiple sclerosis. 

2019;42(4):304-312. doi:10.1519/JPT.0000000000000163

Fried LP, Tangen CM, Walston J, et al; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. 

. 2001;56(3):M146-M156. doi:10.1093/gerona/56.3.m146

Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. 

2013;381(9868):752-762. doi:10.1016/S0140-6736(12)62167-9

Al Worikat N, Molaei F, Zanotto A, et al. Frailty in multiple sclerosis: a scoping review. 

 2024;92:106157. doi:10.1016/j.msard.2024.106157

Volume 27, Issue Theme II

Age-Related Changes in Multiple Sclerosis Pathophysiology and Clinical Function

From Disability to Capability: Trajectory of Healthy Aging From the Perspective of People With Multiple Sclerosis

Long-Term Changes in Patient-Reported Outcome Measures in People With Multiple Sclerosis 55 Years and Older: Analysis From the New York State Multiple Sclerosis Consortium

Letter From the Guest Editors - Volume 27, Theme II