A novel super-resolution microscopy platform for cutaneous alpha-synuclein detection in Parkinson's disease.

Alpha-synuclein (aSyn) aggregates in the central nervous system are the main pathological hallmark of Parkinson's disease (PD). ASyn aggregates have also been detected in many peripheral tissues, including the skin, thus providing a novel and accessible target tissue for the detection of PD pathology. Still, a well-established validated quantitative biomarker for early diagnosis of PD that also allows for tracking of disease progression remains lacking. The main goal of this research was to characterize aSyn aggregates in skin biopsies as a comparative and quantitative measure for PD pathology. Using direct stochastic optical reconstruction microscopy (dSTORM) and computational tools, we imaged total and phosphorylated-aSyn at the single molecule level in sweat glands and nerve bundles of skin biopsies from healthy controls (HCs) and PD patients. We developed a user-friendly analysis platform that offers a comprehensive toolkit for researchers that combines analysis algorithms and applies a series of cluster analysis algorithms (i.e., DBSCAN and FOCAL) onto dSTORM images. Using this platform, we found a significant decrease in the ratio of the numbers of neuronal marker molecules to phosphorylated-aSyn molecules, suggesting the existence of damaged nerve cells in fibers highly enriched with phosphorylated-aSyn molecules. Furthermore, our analysis found a higher number of aSyn aggregates in PD subjects than in HC subjects, with differences in aggregate size, density, and number of molecules per aggregate. On average, aSyn aggregate radii ranged between 40 and 200 nm and presented an average density of 0.001-0.1 molecules/nm2. Our dSTORM analysis thus highlights the potential of our platform for identifying quantitative characteristics of aSyn distribution in skin biopsies not previously described for PD patients while offering valuable insight into PD pathology by elucidating patient aSyn aggregation status.

Getting oriented: Redefining attention deficits in Parkinson's disease.

OBJECTIVE: Parkinson's disease (PD) may affect not only motor functions, but also cognitive processes such as attention. While past research has examined PD impact on spatial attention, it has not addressed how the key functions of attentional orienting and alerting in PD are mediated by cueing format, an ecologically relevant parameter. We assessed how exogenous and endogenous orienting cue modes affect PD patients' visuospatial attention expressed as dorsal attention network orienting benefits, ventral attention network reorienting costs, and alerting abilities. METHOD: Ninety PD patients and 72 healthy comparison participants performed a spatial attention task in an engaging game format which required selection of a target location without prior cueing, or with temporal, valid spatial, or invalid spatial exogenous or endogenous cueing. RESULTS: PD patients differed from healthy participants only in response time benefits in orienting under endogenous probabilistically predictive cue processing. They did not exhibit greater reorienting costs, differences in inhibition of return, or alerting deficits, irrespective of modes of cueing. CONCLUSION: These results suggest that fundamental orienting and alerting functions might be intact in PD, with challenges emerging only if additional cognitive processes, including those related to motor preparation, are required to utilize cue information. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Levodopa-carbidopa intestinal gel for advanced Parkinson's disease: Impact of LRRK2 and GBA1 mutations.

BACKGROUND: Advanced Parkinson's disease (PD) can be treated with Levodopa-Carbidopa Intestinal Gel (LCIG). OBJECTIVE: To compare descriptive data of LCIG treatment in GBA1-PD and LRRK2-PD. METHODS: This multicenter retrospective study compared clinical data obtained from electronic medical records of PD patients treated with LCIG. Patients were grouped based on their genetic status. RESULTS: Fifty-two iPD, 15 LRRK2-PD and 23 GBA1-PD were included in this study. No difference in daily dose of LCIG or levodopa equivalent daily dose were detected. GBA1-PD had significantly shorter disease duration at LCIG initiation (p = 0.01) and experienced more hallucinations (p = 0.03) compared with LRRK2-PD and iPD. LRRK2-PD and iPD had significantly longer duration of LCIG treatment compared with GBA1-PD (p < 0.01). CONCLUSION: Overall, LCIG treatment was well tolerated in LRRK2-PD and GBA1-PD. GBA1-PD required LCIG earlier in their course of their disease and had higher frequencies of hallucinations during treatment, attesting to a more severe disease course.

Effect of GBA1 Mutations and APOE Polymorphisms on Survival and Progression Among Ashkenazi Jews with Dementia with Lewy Bodies.

BACKGROUND: Glucocerebrosidase 1 (GBA1) mutations are associated with reduced survival in Parkinson's disease but their effect on survival in dementia with Lewy bodies (DLB) is unclear. OBJECTIVE: To assess the impact of GBA1 mutations on survival among Ashkenazi Jews with DLB, while controlling for APOE status. METHODS: One hundred and forty participants from Tel Aviv Medical Center, Israel were genotyped for GBA1 mutations and APOE polymorphisms. Survival rates and follow-up cognitive screening scores were analyzed. RESULTS: GBA1 mutation carriers had a two-fold increased risk of death (HR = 1.999), while APOE status did not independently affect survival. In a subset of patients with available clinical data (N = 63), carriers of the APOE ε4 allele showed faster cognitive deterioration, while GBA1 mutation carriers also declined more rapidly albeit not significantly. CONCLUSION: Understanding the genetic effects on survival and progression is crucial for patient counseling and inclusion in clinical trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art.

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

White matter abnormalities in healthy E200K carriers may serve as an early biomarker for genetic Creutzfeldt-Jakob disease (gCJD).

BACKGROUND: MRI is an important tool for disease diagnosis of Creutzfeldt-Jakob disease (CJD), yet its role in identifying preclinical stages of disease remains unclear. Here, we explored subtle white matter (WM) alterations in genetic CJD (gCJD) patients and in asymptomatic E200K mutation carriers using MRI, depending on total tau protein (t-tau) levels in CSF. METHODS: Six symptomatic gCJD patients and N=60 healthy relatives of gCJD patients were included. Participants underwent genetic testing for the E200K mutation, MRI scans at 3T and a lumbar puncture (LP) for t-tau. Diffusion tensor imaging (DTI) metrics were calculated along WM tracts. RESULTS: gCJD patients demonstrated higher mean diffusivity (MD), radial diffusivity (RD) and lower fractional anisotropy (FA) values compared with healthy relatives in several WM tracts (p<0.05). Out of the healthy relatives, 50% (N=30) were found to be carriers of the E200K mutation. T-tau levels in cerebrospinal fluid (CSF) were above the normal range (>290 pg/mL) in N=8 out of 23 carriers who underwent an LP. No significant differences in FA, MD, axial diffusivity (AD) and RD were detected between healthy mutation carriers (HMC) and healthy non-carriers within the WM tracts. Finally, significantly higher FA and lower MD, RD and AD along several WM tracts were found in HMC with elevated t-tau compared with HMC with normal t-tau (p<0.05). CONCLUSIONS: DTI abnormalities along WM tracts were found in healthy E200K mutation carriers with elevated t-tau in CSF. Longer follow-up is required to determine whether these subtle WM alterations are predictive of future conversion to symptomatic gCJD. TRIAL REGISTRATION NUMBER: NCT05746715.

Mild cognitive impairment among LRRK2 and GBA1 patients with Parkinson's disease.

BACKGROUND: Mild cognitive impairment (MCI) is common in Parkinson's disease (PD). We aimed to assess the incidence of MCI among patients with PD, carriers of mutations in LRRK2 and GBA1 genes, based on the movement disorder society (MDS) criteria for the diagnosis of MCI in early-stage PD. METHODS: Patients with PD were included if they scored ≤2 on the Hoehn and Yahr and ≤6 years since motor symptom onset. A group of age and gender matched healthy adults served as controls. A neuropsychological cognitive battery was used covering five cognitive domains (executive functions, working memory, memory, visuospatial and language). MCI was explored while applying two methods (level I and II). Frequency of MCI was assessed in comparison between groups. RESULTS: 70 patients with idiopathic PD (iPD) (68 % males), 42 patients with LRRK2-PD (61 % males), 83 patients with GBA1-PD (63 % males) and 132 age and gender matched controls (61 % males), participated in this study. PD groups were similar in clinical characteristics. Level I criteria were positive in 57.5 % of iPD, 43 % of LRRK2-PD and 63.4 % of the GBA1-PD (p = 0.071). Level II criteria was met by 39 % of iPD, 14 % LRRK2-PD and 41 % of GBA1-PD (p < 0.001), when using a 2 standard-deviation (SD) threshold. GBA1-PD and iPD showed impairments on multiple domains even in the more conservative 2 SD, reflecting MCI. CONCLUSIONS: The majority of our PD cohort was classified as MCI when assessed with strict criteria. GBA1-PD and iPD showed a more widespread pattern of MCI compared with LRRK2-PD.

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders.

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a single lower-back inertial measurement unit worn by 472 young and older adults with different neurological conditions, including Parkinson's disease and healthy controls. Studying more than 80,000 steps, the best model showed high accuracy for a single step (root mean square error, RMSE = 6.08 cm, ICC(2,1) = 0.89) and higher accuracy when averaged over ten consecutive steps (RMSE = 4.79 cm, ICC(2,1) = 0.93), successfully reaching the predefined goal of an RMSE below 5 cm (often considered the minimal-clinically-important-difference). Combining machine-learning with a single, wearable sensor generates accurate step length measures, even in patients with neurologic disease. Additional research may be needed to further reduce the errors in certain conditions.

Validity of the Short Weekly Calendar Planning Activity in patients with Parkinson disease and nonmanifesting LRRK2 and GBA carriers.

BACKGROUND AND PURPOSE: Subtle executive dysfunction is common in people newly diagnosed with Parkinson disease (PD), even when general cognitive abilities are intact. This study examined the Short Weekly Calendar Planning Activity (WCPA-10)'s known-group construct validity, comparing persons with PD to healthy controls (HCs) and nonmanifesting carriers of LRRK2 and GBA gene mutations to HCs. Additionally, convergent and ecological validity was examined. METHODS: The study included 73 participants: 22 with idiopathic PD (iPD) who do not carry any of the founder GBA mutations or LRRK2-G2019S, 29 nonmanifesting carriers of the G2019S-LRRK2 (n = 14) and GBA (n = 15) mutations, and 22 HCs. Known-group validity was determined using the WCPA-10, convergent validity by also using the Montreal Cognitive Assessment (MoCA) and Color Trails Test (CTT), and ecological validity by using the WCPA-10, Schwab and England Activities of Daily Living Scale (SE ADL), and Physical Activity Scale for the Elderly (PASE). RESULTS: Known-group validity of the WCPA-10 was established for the iPD group only; they followed fewer rules (p = 0.020), were slower (p = 0.003) and less efficient (p = 0.001), used more strategies (p = 0.017) on the WCPA-10, and achieved significantly lower CTT scores (p < 0.001) than the HCs. The nonmanifesting carriers and HCs were similar on all cognitive tests. Convergent and ecological validity of the WCPA-10 were partially established, with few correlations between WCPA-10 outcome measures and the MoCA (r = 0.50, r = 0.41), CTT-2 (r = 0.43), SE ADL (r = 0.41), and PASE (r = 0.54, r = 0.46, r = 0.31). CONCLUSIONS: This study affirms the known-group validity for most (four) WCPA-10 scores and partially confirms its convergent and ecological validity for PD.

Identifying Subtle Motor Deficits Before Parkinson's Disease is Diagnosed: What to Look for?

Motor deficits typical of Parkinson's disease (PD), such as gait and balance disturbances, tremor, reduced arm swing and finger movement, and voice and breathing changes, are believed to manifest several years prior to clinical diagnosis. Here we describe the evidence for the presence and progression of motor deficits in this pre-diagnostic phase in order to provide suggestions for the design of future observational studies for an effective, quantitatively oriented investigation. On the one hand, these future studies must detect these motor deficits in as large (potentially, population-based) cohorts as possible with high sensitivity and specificity. On the other hand, they must describe the progression of these motor deficits in the pre-diagnostic phase as accurately as possible, to support the testing of the effect of pharmacological and non-pharmacological interventions. Digital technologies and artificial intelligence can substantially accelerate this process.

Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease.

BACKGROUND: Real-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to disease progression. OBJECTIVES: The aim was to identify real-world mobility measures that reflect PD severity and show discriminant ability and sensitivity to disease progression, compared to the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scale. METHODS: Multicenter real-world continuous (24/7) digital mobility data from 587 persons with PD and 68 matched healthy controls were collected using an accelerometer adhered to the lower back. Machine learning feature selection and regression algorithms evaluated associations of the digital measures using the MDS-UPDRS (I-III). Binary logistic regression assessed discriminatory value using controls, and longitudinal observational data from a subgroup (n = 33) evaluated sensitivity to change over time. RESULTS: Digital measures were only moderately correlated with the MDS-UPDRS (part II-r = 0.60 and parts I and III-r = 0.50). Most associated measures reflected activity quantity and distribution patterns. A model with 14 digital measures accurately distinguished recently diagnosed persons with PD from healthy controls (81.1%, area under the curve: 0.87); digital measures showed larger effect sizes (Cohen's d: [0.19-0.66]), for change over time than any of the MDS-UPDRS parts (Cohen's d: [0.04-0.12]). CONCLUSIONS: Real-world mobility measures are moderately associated with clinical assessments, suggesting that they capture different aspects of motor capacity and function. Digital mobility measures are sensitive to early-stage disease and to disease progression, to a larger degree than conventional clinical assessments, demonstrating their utility, primarily for clinical trials but ultimately also for clinical care. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Overnight Distribution of REM Sleep Features in People with Parkinson's Disease (PD) and Non-PD Controls.

BACKGROUND: Rapid eye movement (REM) sleep behavior disorder (RBD) is a leading predictor of Parkinson's disease (PD). Diagnosis is performed in the sleep laboratory by detecting pathological REM sleep without atonia (RSWA). The evidence on the overnight distribution of RSWA% is conflicting. OBJECTIVE: To investigate the temporal distribution of the number of ocular movements per REM sleep minute (REM density), and RSWA% in people with PD and non-PD controls. METHODS: All participants underwent a single overnight evaluation in a sleep laboratory. Clinical evaluation was performed on a separate day. REM density and RSWA% were compared between PD and controls both across four sleep periods and individual REM cycles. RESULTS: A total of 51 participants with recorded RSWA in polysomnography laboratory were included, 28 with PD aged 64±9 years with a disease duration of 3.3±2.9 years, and 23 controls aged 55±8 years. People with PD had lower REM density and higher RSWA% compared to controls. As expected, REM density was higher towards the morning. In contrast, RSWA% was equally distributed across the night, for both PD and controls. CONCLUSIONS: PD pathology affects REM sleep features, but not the overnight distribution of those features. While REM density increased towards the end of the night, RSWA% was equally distributed across the night for both PD and controls. Our findings have clinical implications for diagnosing RBD, as quantification of RSWA% in any sleep cycle is sufficient for reliably evaluating total RSWA% and reduced REM density may be a marker of PD.

Differences in EEG Event-Related Potentials during Dual Task in Parkinson's Disease Carriers and Non-Carriers of the G2019S-LRRK2 Mutation.

BACKGROUND: The G2019S-LRRK2 gene mutation is a common cause of hereditary Parkinson's disease (PD), associated with a higher frequency of the postural instability gait difficulty (PIGD) motor phenotype yet with preserved cognition. This study investigated neurophysiological changes during motor and cognitive tasks in PD patients with and without the G2019S-LRRK2 mutation. METHODS: 33 iPD patients and 22 LRRK2-PD patients performed the visual Go/NoGo task (VGNG) during sitting (single-task) and walking (dual-task) while wearing a 64-channel EEG cap. Event-related potentials (ERP) from Fz and Pz, specifically N200 and P300, were extracted and analyzed to quantify brain activity patterns. RESULTS: The LRRK2-PD group performed better in the VGNG than the iPD group (group*task; p = 0.05). During Go, the iPD group showed reduced N2 amplitude and prolonged N2 latency during walking, whereas the LRRK2-PD group showed only shorter latency (group*task p = 0.027). During NoGo, opposite patterns emerged; the iPD group showed reduced N2 and increased P3 amplitudes during walking while the LRRK2-PD group demonstrated increased N2 and reduced P3 (N2: group*task, p = 0.010, P3: group*task, p = 0.012). CONCLUSIONS: The LRRK2-PD group showed efficient early cognitive processes, reflected by N2, resulting in greater neural synchronization and prominent ERPs. These processes are possibly the underlying mechanisms for the observed better cognitive performance as compared to the iPD group. As such, future applications of intelligent medical sensing should be capable of capturing these electrophysiological patterns in order to enhance motor-cognitive functions.

Imaging Markers in Genetic Forms of Parkinson's Disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity, and resting tremor. While the majority of PD cases are sporadic, approximately 15-20% of cases have a genetic component. Advances in neuroimaging techniques have provided valuable insights into the pathophysiology of PD, including the different genetic forms of the disease. This literature review aims to summarize the current state of knowledge regarding neuroimaging findings in genetic PD, focusing on the most prevalent known genetic forms: mutations in the GBA1, LRRK2, and Parkin genes. In this review, we will highlight the contributions of various neuroimaging modalities, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI), in elucidating the underlying pathophysiological mechanisms and potentially identifying candidate biomarkers for genetic forms of PD.

Bio-potential noise of dry printed electrodes: physiology versus the skin-electrode impedance.

Objective. To explore noise characteristics and the effect physiological activity has on the link between impedance and noise.Approach. Dry-printed electrodes are emerging as a new and exciting technology for skin electro-physiology. Such electrode arrays offer many advantages including user convenience, quick placement, and high resolution. Here we analyze extensive electro-physiological data recorded from the arm and the face to study and quantify the noise of dry electrodes, and to characterize the link between noise and impedance. In particular, we studied the effect of the physiological state of the subject (e.g. rapid eye movement sleep) on noise.Main results. We show that baseline noise values extracted from dry electrodes in the arm are in agreement with the Nyquist equation. In the face, on the other hand, the measured noise values were higher than the values predicted by the Nyquist equation. In addition, we studied how different electrode properties affect performances, including electrode size, shape, and material properties.Significance. Altogether, the results presented here provide a basis for understanding dry electrode performances and substantiate their great potential in electro-physiological investigations.

Task-Related Reorganization of Cognitive Network in Parkinson's Disease Using Electrophysiology.

BACKGROUND: Cognitive deficits in Parkinson's disease (PD) patients are well described, however, their underlying neural mechanisms as assessed by electrophysiology are not clear. OBJECTIVES: To reveal specific neural network alterations during the performance of cognitive tasks in PD patients using electroencephalography (EEG). METHODS: Ninety participants, 60 PD patients and 30 controls underwent EEG recording while performing a GO/NOGO task. Source localization of 16 regions of interest known to play a pivotal role in GO/NOGO task was performed to assess power density and connectivity within this cognitive network. The connectivity matrices were evaluated using a graph-theory approach that included measures of cluster-coefficient, degree, and global-efficiency. A mixed-model analysis, corrected for age and levodopa equivalent daily dose was performed to examine neural changes between PD patients and controls. RESULTS: PD patients performed worse in the GO/NOGO task (P < 0.001). The power density was higher in δ and θ bands, but lower in α and ß bands in PD patients compared to controls (interaction group × band: P < 0.001), indicating a general slowness within the network. Patients had more connections within the network (P < 0.034) than controls and these were used for graph-theory analysis. Differences between groups in graph-theory measures were found only in cluster-coefficient, which was higher in PD compared to controls (interaction group × band: P < 0.001). CONCLUSIONS: Cognitive deficits in PD are underlined by alterations at the brain network level, including higher δ and θ activity, lower α and ß activity, increased connectivity, and segregated network organization. These findings may have important implications on future adaptive deep brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Decreased aperiodic neural activity in Parkinson's disease and dementia with Lewy bodies.

Neural oscillations and signal complexity have been widely studied in neurodegenerative diseases, whereas aperiodic activity has not been explored yet in those disorders. Here, we assessed whether the study of aperiodic activity brings new insights relating to disease as compared to the conventional spectral and complexity analyses. Eyes-closed resting-state electroencephalography (EEG) was recorded in 21 patients with dementia with Lewy bodies (DLB), 28 patients with Parkinson's disease (PD), 27 patients with mild cognitive impairment (MCI) and 22 age-matched healthy controls. Spectral power was differentiated into its oscillatory and aperiodic components using the Irregularly Resampled Auto-Spectral Analysis. Signal complexity was explored using the Lempel-Ziv algorithm (LZC). We found that DLB patients showed steeper slopes of the aperiodic power component with large effect sizes compared to the controls and MCI and with a moderate effect size compared to PD. PD patients showed steeper slopes with a moderate effect size compared to controls and MCI. Oscillatory power and LZC differentiated only between DLB and other study groups and were not sensitive enough to detect differences between PD, MCI, and controls. In conclusion, both DLB and PD are characterized by alterations in aperiodic dynamics, which are more sensitive in detecting disease-related neural changes than the traditional spectral and complexity analyses. Our findings suggest that steeper aperiodic slopes may serve as a marker of network dysfunction in DLB and PD features.

Association Between Frailty and Free-Living Walking Performance in People With Multiple Sclerosis.

OBJECTIVE: The purpose of this study was to examine the association between frailty and the quantity and quality of free-living walking and the mediating effect of frailty on the relationship between disability and walking performance in people with multiple sclerosis (MS). METHODS: Ninety-nine people with relapsing-remitting MS (mean age = 49.3 [SD = 9.8] years; 73.7% women; Expanded Disability Status Scale [EDSS] score range = 2.0-6.0) wore a triaxial accelerometer for 7 days. Recorded measures reflected the quantity (daily step counts, number of 30-second walking bouts, and signal vector magnitude [SVM]) and quality (gait speed, step cadence, step and stride regularity, and sample entropy) of walking. For each walking quality measure, the typical (median), best (90th percentile), and worst (10th percentile) values were calculated. Frailty was evaluated through a 38-item frailty index. RESULTS: Participants were classified as not frail (n = 31), moderately frail (n = 34), and severely frail (n = 34) on the basis of established procedures. Patients who were moderately and severely frail exhibited poorer performance in all measures of walking quantity and quality, except for sample entropy, than individuals who were not frail. No differences in free-living walking performance were observed between the moderately and severely frail groups. Frailty did not mediate the relationship between disability (EDSS) and measures of walking quality. Conversely, frailty had a significant mediating effect on the relationship between disability and measures of walking quantity, such as daily step counts (indirect effect: b = -220.42, 95% CI = -452.03 to -19.65) and SVM (indirect effect: b = -1.00, 95% CI = -1.86 to -0.30). CONCLUSION: Frailty is associated with poorer free-living walking performance in people with MS. The study findings suggest that frailty, rather than disability, may be primarily responsible for the lower amount of physical activity performed by people with MS in the real world. IMPACT: The observation that frailty and disability are differently related to measures of walking quality and quantity underscores the importance of a targeted approach to rehabilitation in people with MS.