Modeling multiple sclerosis using mobile and wearable sensor data.

Multiple sclerosis (MS) is a neurological disease of the central nervous system that is the leading cause of non-traumatic disability in young adults. Clinical laboratory tests and neuroimaging studies are the standard methods to diagnose and monitor MS. However, due to infrequent clinic visits, it is fundamental to identify remote and frequent approaches for monitoring MS, which enable timely diagnosis, early access to treatment, and slowing down disease progression. In this work, we investigate the most reliable, clinically useful, and available features derived from mobile and wearable devices as well as their ability to distinguish people with MS (PwMS) from healthy controls, recognize MS disability and fatigue levels. To this end, we formalize clinical knowledge and derive behavioral markers to characterize MS. We evaluate our approach on a dataset we collected from 55 PwMS and 24 healthy controls for a total of 489 days conducted in free-living conditions. The dataset contains wearable sensor data - e.g., heart rate - collected using an arm-worn device, smartphone data - e.g., phone locks - collected through a mobile application, patient health records - e.g., MS type - obtained from the hospital, and self-reports - e.g., fatigue level - collected using validated questionnaires administered via the mobile application. Our results demonstrate the feasibility of using features derived from mobile and wearable sensors to monitor MS. Our findings open up opportunities for continuous monitoring of MS in free-living conditions and can be used to evaluate and guide the effectiveness of treatments, manage the disease, and identify participants for clinical trials.

HLA Associations of Intrathecal IgG Production against Specific Viruses in Multiple Sclerosis.

OBJECTIVE: Specific human leucocyte antigen (HLA) alleles are not only associated with higher risk to develop multiple sclerosis (MS) and other autoimmune diseases, but also with the severity of various viral and bacterial infections. Here, we analyzed the most specific biomarker for MS, that is, the polyspecific intrathecal IgG antibody production against measles, rubella, and varicella zoster virus (MRZ reaction), for possible HLA associations in MS. METHODS: We assessed MRZ reaction from 184 Swiss patients with MS and clinically isolated syndrome (CIS) and 89 Swiss non-MS/non-CIS control patients, and performed HLA sequence-based typing, to check for associations of positive MRZ reaction with the most prevalent HLA alleles. We used a cohort of 176 Swedish MS/CIS patients to replicate significant findings. RESULTS: Whereas positive MRZ reaction showed a prevalence of 38.0% in MS/CIS patients, it was highly specific (97.7%) for MS/CIS. We identified HLA-DRB1*15:01 and other tightly linked alleles of the HLA-DR15 haplotype as the strongest HLA-encoded risk factors for a positive MRZ reaction in Swiss MS/CIS (odds ratio [OR], 3.90, 95% confidence interval [CI] 2.05-7.46, padjusted = 0.0004) and replicated these findings in Swedish MS/CIS patients (OR 2.18, 95%-CI 1.16-4.02, padjusted = 0.028). In addition, female MS/CIS patients had a significantly higher probability for a positive MRZ reaction than male patients in both cohorts combined (padjusted <0.005). INTERPRETATION: HLA-DRB1*15:01, the strongest genetic risk factor for MS, and female sex, 1 of the most prominent demographic risk factors for developing MS, predispose in MS/CIS patients for a positive MRZ reaction, the most specific CSF biomarker for MS. ANN NEUROL 2024;95:1112-1126.

Meaningful digital biomarkers derived from wearable sensors to predict daily fatigue in multiple sclerosis patients and healthy controls.

Fatigue is the most common symptom among multiple sclerosis (MS) patients and severely affects the quality of life. We investigate how perceived fatigue can be predicted using biomarkers collected from an arm-worn wearable sensor for MS patients (n = 51) and a healthy control group (n = 23) at an unprecedented time resolution of more than five times per day. On average, during our two-week study, participants reported their level of fatigue 51 times totaling more than 3,700 data points. Using interpretable generalized additive models, we find that increased physical activity, heart rate, sympathetic activity, and parasympathetic activity while awake and asleep relate to perceived fatigue throughout the day-partly affected by dysfunction of the ANS. We believe our analysis opens up new research opportunities for fine-grained modeling of perceived fatigue based on passively collected physiological signals using wearables-for MS patients and healthy controls alike.

Basic CSF parameters and MRZ reaction help in differentiating MOG antibody-associated autoimmune disease versus multiple sclerosis.

Background: Myelin oligodendrocyte glycoprotein antibody-associated autoimmune disease (MOGAD) is a rare monophasic or relapsing inflammatory demyelinating disease of the central nervous system (CNS) and can mimic multiple sclerosis (MS). The variable availability of live cell-based MOG-antibody assays and difficulties in interpreting low-positive antibody titers can complicate diagnosis. Literature on cerebrospinal fluid (CSF) profiles in MOGAD versus MS, one of the most common differential diagnoses, is scarce. We here analyzed the value of basic CSF parameters to i) distinguish different clinical MOGAD manifestations and ii) differentiate MOGAD from MS. Methods: This is retrospective, single-center analysis of clinical and laboratory data of 30 adult MOGAD patients and 189 adult patients with relapsing-remitting multiple sclerosis. Basic CSF parameters included CSF white cell count (WCC) and differentiation, CSF/serum albumin ratio (QAlb), intrathecal production of immunoglobulins, CSF-restricted oligoclonal bands (OCB) and MRZ reaction, defined as intrathecal production of IgG reactive against at least 2 of the 3 viruses measles (M), rubella (R) and varicella zoster virus (Z). Results: MOGAD patients with myelitis were more likely to have a pleocytosis, a QAlb elevation and a higher WCC than those with optic neuritis, and, after review and combined analysis of our and published cases, they also showed a higher frequency of intrathecal IgM synthesis. Compared to MS, MOGAD patients had significantly more frequently neutrophils in CSF and WCC>30/µl, QAlb>10×10-3, as well as higher mean QAlb values, but significantly less frequently CSF plasma cells and CSF-restricted OCB. A positive MRZ reaction was present in 35.4% of MS patients but absent in all MOGAD patients. Despite these associations, the only CSF parameters with relevant positive likelihood ratios (PLR) indicating MOGAD were QAlb>10×10-3 (PLR 12.60) and absence of CSF-restricted OCB (PLR 14.32), whereas the only relevant negative likelihood ratio (NLR) was absence of positive MRZ reaction (NLR 0.00). Conclusion: Basic CSF parameters vary considerably in different clinical phenotypes of MOGAD, but QAlb>10×10-3 and absence of CSF-restricted OCB are highly useful to differentiate MOGAD from MS. A positive MRZ reaction is confirmed as the strongest CSF rule-out parameter in MOGAD and could be useful to complement the recently proposed diagnostic criteria.

Differentiating neurosarcoidosis from multiple sclerosis using combined analysis of basic CSF parameters and MRZ reaction.

Background: Neurosarcodosis is one of the most frequent differential diagnoses of multiple sclerosis (MS) and requires central nervous system (CNS) biopsy to establish definite diagnosis according to the latest consensus diagnostic criteria. We here analyzed diagnostic values of basic cerebrospinal fluid (CSF) parameters to distinguish neurosarcoidosis from MS without CNS biopsy. Methods: We retrospectively assessed clinical, radiological and laboratory data of 27 patients with neurosarcoidosis treated at our center and compared following CSF parameters with those of 138 patients with relapsing-remitting MS: CSF white cell count (WCC), CSF/serum albumin quotient (Qalb), intrathecal production of immunoglobulins including oligoclonal bands (OCB), MRZ reaction, defined as a polyspecific intrathecal production of IgG reactive against ≥2 of 3 the viruses measles (M), rubella (R), and zoster (Z) virus, and CSF lactate levels. Additional inflammatory biomarkers in serum and/or CSF such as neopterin, soluble interleukin-2 receptor (sIL-2R) and C-reactive protein (CRP) were assessed. Results: There was no significant difference in the frequency of CSF pleocytosis, but a CSF WCC > 30/µl was more frequent in patients with neurosarcoidosis. Compared to MS, patients with neurosarcoidosis showed more frequently an increased Qalb and CSF lactate levels as well as increased serum and CSF levels of sIL-2R, but a lower frequency of intrathecal IgG synthesis and positive MRZ reaction. Positive likelihood ratio (PLR) of single CSF parameters indicating neurosarcoidosis was highest, if (a) CSF WCC was >30/µl (PLR 7.2), (b) Qalb was >10 × 10-3 (PLR 66.4), (c) CSF-specific OCB were absent (PLR 11.5), (d) CSF lactate was elevated (PLR 23.0) or (e) sIL-2R was elevated (PLR>8.0). The combination of (a) one of three following basic CSF parameters, i.e., (a.1.) CSF WCC >30/ul, or (a.2.) QAlb >10 × 10-3, or (a.3.) absence of CSF-specific OCB, and (b) absence of positive MRZ reaction showed the best diagnostic accuracy (sensitivity and specificity each >92%; PLR 12.8 and NLR 0.08). Conclusion: Combined evaluation of basic CSF parameters and MRZ reaction is powerful in differentiating neurosarcoidosis from MS, with moderate to severe pleocytosis and QAlb elevation and absence of intrathecal IgG synthesis as useful rule-in parameters and positive MRZ reaction as a rule-out parameter for neurosarcoidosis.

Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis.

Background: Fatigue is a common symptom of many diseases, including multiple sclerosis. It manifests as a cognitive or physical condition. Fatigue is poorly understood, and effective therapies are missing. Furthermore, there is a lack of methods to measure fatigue objectively. Fatigability, the measurable decline in performance during a task, has been suggested as a complementary method to quantify fatigue. Objective: To develop a new and objective measurement of cognitive fatigability and investigate its association with perceived fatigue. Methods: We introduced the cognitive fatigability assessment test (cFAST), a novel smartphone-based test to quantify cognitive fatigability. Forty-two people with multiple sclerosis (23 fatigued and 19 non-fatigued, defined by the Fatigue Scale for Motor and Cognitive Functions) took part in our validation study. Patients completed cFAST twice. We used t-tests, Monte Carlo sampling, and area under the receiver operating characteristic curves to evaluate our approach using two sets of proposed metrics. Results: When classifying fatigue, our fatigability metric Δresponse time has a mean area under the receiver operating characteristic curve of 0.74 (95% CI 0.64-0.84), making it the best performing metric for this task. Furthermore, Δresponse time shows a statistically significant difference between the fatigued and non-fatigued groups (t = 2.27, P = .03). Particularly, cognitively-fatigued patients decline in performance, while non-fatigued patients do not. Conclusions: We introduce cFAST, a new instrument to quantify cognitive fatigability. Our pilot study provides evidence that cognitive fatigability assessment test produces a quantifiable drop in cognitive performance in a short period. Furthermore, our results indicate that cFAST may have the potential to serve as a surrogate for subjective cognitive fatigue. cFAST is significantly shorter than the existing fatigability assessments and does not require specialized equipment. Thus, it could enable frequent and remote monitoring, which could substantially aid clinicians in better understanding and treating fatigue.

Continuous monitoring with wearables in multiple sclerosis reveals an association of cardiac autonomic dysfunction with disease severity.

Background: Dysfunction of the autonomic nervous system is common in multiple sclerosis patients, and probably present years before diagnosis, but its role in the disease is poorly understood. Objectives: To study the autonomic nervous system in patients with multiple sclerosis using cardiac autonomic regulation measured with a wearable. Methods: In a two-week study, we present a method to standardize the measurement of heart rate variability using a wearable sensor that allows the investigation of circadian trends. Using this method, we investigate the relationship of cardiac autonomic dysfunction with clinical hallmarks and subjective burden of fatigue and autonomic symptoms. Results: In 55 patients with multiple sclerosis and 24 healthy age- and gender-matched controls, we assessed the cumulative circadian heart-rate variability trend of two weeks. The trend analysis revealed an effect of inflammation (P = 0.0490, SMD = -0.5466) and progressive neurodegeneration (P = 0.0016, SMD = 1.1491) on cardiac autonomic function. No association with subjective symptoms could be found. Conclusions: Trend-based heart rate variability measured with a wearable provides the opportunity for unobtrusive long-term assessment of autonomic functions in patients with multiple sclerosis. It revealed a general dysregulation in patients with multiple sclerosis.