TYPE Original Research PUBLISHED 06 April 2023 DOI 10.3389/fphys.2023.1145818 Autonomic response to walk OPEN ACCESS tests is useful for assessing EDITED BY Mario Habek, University of Zagreb, Croatia outcome measures in people REVIEWED BY Magdalena Krbot Skoric, with multiple sclerosis University Hospital Centre Zagreb, Croatia Łukasz Rzepiński, Spyridon Kontaxis 1,2*, Estela Laporta 1,2, Esther Garcia 2,3, 10th Military Research Hospital and Polyclinic, Poland Ana Isabel Guerrero 4, Ana Zabalza 4, Martinis Matteo 5, Ivan Adamec, Roselli Lucia 5, Sara Simblett 6, Janice Weyer 7, Matthew Hotopf 6, University Hospital Centre Zagreb, Croatia Vaibhav A. Narayan 8, Zulqarnain Rashid 9, Amos A. Folarin 9,10, *CORRESPONDENCE Richard J. B. Dobson 9,10, Mathias Due Buron 11, Letizia Leocani 5, Spyridon Kontaxis, sikontax@gmail.com Nicholas Cummins 9, Srinivasan Vairavan 8, Gloria Dalla Costa 5, SPECIALTY SECTION Melinda Magyari 11, Per Soelberg Sørensen 11, Carlos Nos 4, This article was submitted to Raquel Bailón 1,2, Giancarlo Comi 5,12 and the RADAR-CNS Physio-logging, a section of the journal Frontiers in Physiology Consortium 13 RECEIVED 16January 2023 1 Laboratory of Biomedical Signal Interpretation and Computational Simulation (BSICoS), University of ACCEPTED 15 March 2023 Zaragoza, Zaragoza, Spain, 2 Biomedical Research Networking Center in Bioengineering, Biomaterials PUBLISHED 06 April 2023 and Nanomedicine (CIBER-BBN), Barcelona, Spain, 3 Department of Microelectronics and Electronic Systems, Autonomous University of Barcelona, Barcelona, Spain, 4 Multiple Sclerosis Centre of CITATION Catalonia (CEMCAT), Department of Neurology/Neuroimmunology, Hospital Universitari Vall Kontaxis S, Laporta E, Garcia E, Guerrero D’Hebron, Universitat Autónoma de Barcelona, Barcelona, Spain, 5 Faculty of Medicine and Surgery, AI, Zabalza A, Matteo M, Lucia R, Simblett Vita Salute San Raffaele University, Milan, Italy, 6 Institute of Psychiatry, Psychology and Neuroscience, S, Weyer J, Hotopf M, Narayan VA, King’s College London, London, United Kingdom, 7 RADAR-CNS Patient Advisory Board, London, Rashid Z, Folarin AA, Dobson RJB, Buron United Kingdom, 8 Research and Development Information Technology, London, United Kingdom, MD, Leocani L, Cummins N, Vairavan S, 9 Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Costa GD, Magyari M, Sørensen PS, Nos Neuroscience, King’s College London, London, United Kingdom, 10 Institute of Health Informatics, C, Bailón R, Comi G and the RADAR-CNS University College London, London, United Kingdom, 11 Danish Multiple Sclerosis Centre, Department Consortium (2023), Autonomic response of Neurology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark, 12 Casa di Cura to walk tests is useful for assessing del Policlinico, Milan, Italy, 13 The RADAR-CNS Consortium, London, United Kingdom outcome measures in people with multiple sclerosis. Front. Physiol. 14:1145818. doi: 10.3389/fphys.2023.1145818 COPYRIGHT Objective: The aim of this study was to evaluate the association between © 2023 Kontaxis, Laporta, Garcia, changes in the autonomic control of cardiorespiratory system induced by walk Guerrero, Zabalza, Matteo, Lucia, Simblett, Weyer, Hotopf, Narayan, tests and outcome measures in people with Multiple Sclerosis (pwMS). Rashid, Folarin, Dobson, Buron, Leocani, Cummins, Vairavan, Costa, Magyari, Methods: Electrocardiogram (ECG) recordings of 148 people with Relapsing- Sørensen, Nos, Bailón, Comi and the Remitting MS (RRMS) and 58 with Secondary Progressive MS (SPMS) were RADAR-CNS Consortium. This is an acquired using a wearable device before, during, and after walk test performance open-access article distributed under the terms of the Creative Commons from a total of 386 periodical clinical visits. A subset of 90 participants repeated Attribution License (CC BY). The use, a walk test at home. Various MS-related symptoms, including fatigue, disability, distribution or reproduction in other and walking capacity were evaluated at each clinical visit, while heart rate forums is permitted, provided the original author(s) and the copyright variability (HRV) and ECG-derived respiration (EDR) were analyzed to assess owner(s) are credited and that the autonomic nervous system (ANS) function. Statistical tests were conducted original publication in this journal is to assess differences in ANS control between pwMS grouped based on the cited, in accordance with accepted academic practice. No use, distribution phenotype or the severity of MS-related symptoms. Furthermore, correlation or reproduction is permitted which does coefficients (r) were calculated to assess the association between the most not comply with these terms. significant ANS parameters and MS-outcome measures. Results: People with SPMS, compared to RRMS, reached higher mean heart rate (HRM) values during walk test, and larger sympathovagal balance after Frontiers in Physiology 01 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 test performance. Furthermore, pwMS who were able to adjust their HRM and ventilatory values, such as respiratory rate and standard deviation of the ECG- derived respiration, were associated with better clinical outcomes. Correlation analyses showed weak associations between ANS parameters and clinical outcomes when the Multiple Sclerosis phenotype is not taken into account. Blunted autonomic response, in particular HRM reactivity, was related with worse walking capacity, yielding r = 0.36 r = 0.29 (RRMS) and r > 0.5 (SPMS). A positive strong correlation r > 0.7 r > 0.65 between cardiorespiratory parameters derived at hospital and at home was also found. Conclusion: Autonomic function, as measured by HRV, differs according to MS phenotype. Autonomic response to walk tests may be useful for assessing clinical outcomes, mainly in the progressive stage of MS. Participants with larger changes in HRM are able to walk longer distance, while reduced ventilatory function during and after walk test performance is associated with higher fatigue and disability severity scores. Monitoring of disorder severity could also be feasible using ECG-derived cardiac and respiratory parameters recorded with a wearable device at home. KEYWORDS autonomic nervous system, heart rate variability, ECG-derived respiration, relapsing- remitting multiple sclerosis, secondary progressive multiple sclerosis, fatigue, disability, walking capacity 1 Introduction a vicious neuroinflammatory cycle that amplifies tissue damage (Findling et al., 2020). Multiple Sclerosis (MS) is a chronic inflammatory disorder Dysfunction of the ANS is being increasingly recognized characterized by demyelination of the nerve fibers in the human as an important aspect of MS, with an estimated prevalence Central Nervous System (CNS) (Faissner et al., 2019). Progressive of 45%–84% (Racosta and Kimpinski, 2016). The main clinical neurodegeneration owing to chronic demyelination causes varied manifestations of autonomic disturbances are associated with neurological deficits, which may considerably reduce the quality abnormal cardiovascular control (Findling et al., 2020), aberrant of life in people with MS (pwMS) (McGinley et al., 2021). The thermoregulation (Christogianni et al., 2018), gastrointestinal high prevalence of MS (2.8 million people in 2020) together with symptoms (Aghaz et al., 2018), and pelvic organ dysfunction the relatively young onset age (between 20 and 40 years) have a (Aharony et al., 2017). Retrospective studies have shown that significant impact on personal and societal costs (Wallin et al., 2019; autonomic symptoms may be a key player in both prodromal phase Walton et al., 2020). and development of clinically established MS (Disanto et al., 2018; Although the exact cause of MS remains uncertain, it Almeida et al., 2019; Skorić et al., 2019). Autonomic dysregulation is considered an inflammatory autoimmune disorder that is is also implicated in other common MS-related symptoms, such influenced by both genetic and environmental risk factors (Baecher- as fatigue (Ayache and Chalah, 2017; Capone et al., 2020), sleep Allan et al., 2018). A general consensus is that the disorder begins disturbances (Hensen et al., 2018; Sakkas et al., 2019), and clinical with inflammatory lesions (known as focal plaques) due to the depression (Gold et al., 2005; Morris et al., 2018). Therefore, dysregulation of the Blood-Brain Barrier (BBB) (Mahad et al., these findings highlight the importance of monitoring the ANS 2015). The disruption of the BBB increases the trans-endothelial dysfunction in people with MS. migration of activated leukocytes into the CNS, which can The functionality of the ANS is often assessed based on changes initiate inflammatory responses by releasing pro-inflammatory in cardiovascular parameters during diagnostic tests including, cytokines (Ortiz et al., 2014). Furthermore, the sympathetic and Valsalva maneuver, deep breathing, and tilt-table test (Ziemssen parasympathetic branches of the Autonomic Nervous System (ANS) and Siepmann, 2019). The variation in ANS activity, which is play a key role in the bidirectional communication between the known as autonomic reactivity, is particularly important since it immune system and the CNS (Racosta and Kimpinski, 2016). reflects the ability of an individual to cope with a challenging Sympathetic influence on immune response can be direct, via situation (Carnevali et al., 2018; Kontaxis et al., 2020). In order adrenoceptors on immune cells, or indirect, through innervation homeostasis to be maintained, cardiovascular parameters, such as of major immune organs (Pongratz and Straub, 2014). The Heart Rate (HR), are constantly changing. Short-term and long- parasympathetic division of the ANS, through the activation of term variations of HR, the so-called Heart Rate Variability (HRV), the efferent vagus nerve, inhibits pro-inflammatory cytokine release have emerged as the most valuable non-invasive measure of ANS and protects against systemic inflammation (Pavlov and Tracey, function (Billman, 2011). Reduced contribution of the ANS to 2012). Impairment of the ANS can either trigger inflammatory cardiac regulation, reflected as lower HRV, signifies pathological states or may fail to activate anti-inflammatory mechanisms, causing changes associated with autonomic dysfunction (Ernst, 2017). Frontiers in Physiology 02 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 Reduced HRV in pwMS, compared to healthy subjects, has been methods and the influence of respiration in the estimation of HRV reported in numerous studies (Racosta and Kimpinski, 2016; indices. Changes in respiratory parameters, such as respiration rate Findling et al., 2020). Moreover, the severity of HRV deficit appears and tidal volume, can confound the relationship between ANS to be associated with the progression of the disorder (Studer et al., function and HRV indices (Grossman and Taylor, 2007). To the 2017; Adamec et al., 2018). It has been hypothesized that autonomic best of the authors’ knowledge, none of the previous studies has imbalance towards a sympathetic dominance may have a pathogenic taken into account the effect of respiration on HRV in pwMS. role in the development of MS, while parasympathetic dysfunction Recent studies suggest that besides monitoring respiration when correlates with the progression of the disorder (Pintér et al., 2015; analyzing HRV indices, there is an increasing awareness of the need Racosta and Kimpinski, 2016). to include respiration parameters in MS (Rzepiński et al., 2022). However, there is no consensus regarding the presence Previous studies in pwMS have shown that autonomic imbalance of relation between HRV and the most common disorder could influence breathing control and upper airway muscle activity characteristics, such as disability and fatigue. The most widely used (Hensen et al., 2018). In (Heine et al., 2016), a significant association disability rating scale in MS is the Expanded Disability Status Scale between disorder severity and cardiopulmonary fitness was found. (EDSS) (Inojosa et al., 2020b), while the Fatigue Severity Scale (FSS) Respiratory dysfunction frequently occurs in people with advanced is one of the most well-known questionnaires evaluating the fatigue MS contributing significantly to morbidity and mortality (Tzelepis severity in pwMS (Krupp et al., 1989). The EDSS is mainly based and McCool, 2015). on the evaluation of functional systems including ambulation, i.e., In order to monitor deterioration in pwMS, a continuous the maximal walking distance without rest, and several functional monitoring of clinical state is required. Remote measurement systems such as visual, sensory, and cerebral, among others (Kurtzke, technologies (RMT), including a variety of sensors, can actively and 1983). The FSS evaluates both physical and cognitive aspects of passively collect numerous data that can assess symptom severity fatigue and their interference in daily living (Beckerman et al., and progression, or response to treatment (White et al., 2022). With 2020). Previous studies have shown a significant positive relation the advances in RMT over the last few decades, it could be now between EDSS scores and HRV parameters reflecting sympathetic possible to provide real-time objective multidimensional indications dominance (Studer et al., 2017; Zawadka-Kunikowska et al., 2020), of patients’ clinical symptoms (Malasinghe et al., 2019). A growing while in (Damla et al., 2018), no significant association between number of studies have explored the feasibility and potential HRV and EDSS was found. Although HRV tended to be different in effectiveness of RMTs in measuring a variety of physiological pwMS with and without fatigue, no significant correlation with FSS parameters among pwMS (Bradshaw et al., 2017; Alexander et al., scores has been observed (Flachenecker et al., 2003; Sander et al., 2020). The vast majority of RMTs are employed for non-invasive 2019). The absence of consensus regarding the relation of HRV measurement of physical activity, while wearable sensors measuring with these MS-related symptoms could be partially explained cardiac activity still require further research before being included by the subjective nature of the questionnaires (van Munster and as tools for assessing autonomic dysfunction among pwMS Uitdehaag, 2017). For instance, the EDSS assessment is subjective to (Fuller et al., 2020; Xiang and Bernard, 2021). the examining neurologist (Inojosa et al., 2020a), while perception In this study, changes in HRV and respiratory parameters of fatigue in pwMS can be increased by comorbid conditions such derived from the ECG induced by walk tests are analyzed for as sleeping disturbances and depression (Sternberg, 2017). assessing clinical outcomes in pwMS. Correlation analyses with Among the most common MS-related characteristics are also clinical markers of disorder severity and progression are performed. walking limitations that can be used to complement other less The main hypothesis tested here is that stress response to walk objective clinical measures (Bethoux and Bennett, 2011; Kieseier tests quantified by autonomic reactivity indices and respiratory and Pozzilli, 2012). The 6-Minute Walk Test (6 MWT), which parameters are useful for assessing clinical outcomes. This study also records the maximum distance a patient walks in 6 min, has been explores the feasibility and acceptability of home-based monitoring the most commonly applied measure of walking capacity in MS in pwMS. (Cederberg et al., 2019). In routine clinical assessment, the 2-Minute Walk Test (2 MWT) can be considered a practical replacement for the 6 MWT, which often tends to be more burdensome for 2 Materials and methods individuals with MS (Andersen et al., 2016; Scalzitti et al., 2018). Current research on the walking assessments is focused only 2.1 Dataset on changes in the HR profile rather than fluctuations in HRV parameters. Emerging evidence suggests that, in pwMS, a lower The data used in this study were collected as part of the increase in the HR induced by walking is associated with higher Remote Assessment of Disease and Relapse-Central Nervous System levels of disability (Bosnak-Guclu et al., 2012; Dalgas et al., 2014). (RADAR-CNS) research programme1 . RADAR-CNS is an IMI2 Although blunted autonomic reactivity to endurance exercise or tilt- project that aims to develop new ways of measuring disorders related up table test has been previously reported in pwMS (Studer et al., to CNS, such as MS, using remote monitoring technologies, i.e., 2017; Zawadka-Kunikowska et al., 2020; Gerasimova-Meigal et al., wearable devices and mobile sensors. The MS work package of 2021), no relationship between reactivity indices and disability or RADAR-CNS, which consists of multiple clinical sites spread across fatigue scores was found (Gervasoni et al., 2018; Rampichini et al., several European countries, started recruiting participants in June 2020). A possible explanation for the lack of consensus regarding the potential use of HRV may also be the heterogeneity of the applied 1 https://www.radar-cns.org/ Frontiers in Physiology 03 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 2018. Since then, active (questionnaires and physical tests), and TABLE 1 Mean ± standard deviation of demographic data and baseline passive monitoring strategies (wearable and smartwatch devices) clinical data. have been in place by three sites: Ospedale San Raffaele in Milan, RRMS SPMS Italy, Vall d’Hebron Institut de Recerca in Barcelona, Spain, and Number of subjects n 148 58 the University Hospital Copenhagen, Rigshospitalet in Copenhagen, Denmark (Ranjan et al., 2019). Outcome measures in pwMS were Sex (female/male) 94/54 33/25 assessed every 3 months during clinical visits in the hospital, while Age, years 45.5 ± 9.8 49.4 ± 9.3 the phenotype of the disorder, i.e., either relapsing-remitting MS BMI, kg/m2 24.3 ± 4.9 25.3 ± 4.6 (RRMS) or secondary progressive MS (SPMS), was assessed at the first clinical visit. In each clinical visit, participants underwent an MS duration, years 14.9 ± 7.9 19.8 ± 10.5 experimental protocol that consists of three stages: (a) a Basal stage MS progression, years 4.8 ± 3.8 (B) where the subjects were instructed to relax without speaking FSS (n) 4.4 ± 1.7 (135) 4.8 ± 1.3 (55) during 5 min, (b) a Test stage (T ) during which, the individuals EDSS (n) 2.9 ± 1.1 (140) 4.0 ± 1.2 (56) were performing the 2 MW T, and (c) a Recovery stage (R) where the subjects were supposed to achieve a resting state remaining 2MWT, m (n) 123.8 ± 22.8 (101) 100.5 ± 26.1 (29) silent during 5 min. During the whole protocol, an ECG signal 6MWT, m (n) 402.1 ± 66.6 (143) 350.3 ± 90.7 (57) was continuously recorded at a sampling frequency of 125 Hz for MS medication n (%) each participant using the wearable device Bittium Faros 1802 . Note that other physical tests (6 MW T), and the filling of questionnaires Fingolimod 24 (16%) 9 (15%) either by the clinicians (EDSS) or the pwMS (FSS), were conducted Natalizumab 12 (8%) 10 (17%) before attaching the wearable device. Teriflunomide 20 (13%) 7 (12%) As of 1 November 2021, 206 pwMS had been enrolled in the RADAR-MS study, and a total of 384 clinical visits had been Interferon-beta 22 (15%) 5 (8%) conducted (99, 58, 34, 9, 5, and 1 patient(s) had one to six clinical Glatiramer acetate 17 (11%) 5 (8%) visits, respectively). Although ECG data during the 2 MW T (T ) Other 38 (25%) 14 (24%) were available in all participants, 5min of ECG data during B and R were available in about 70% for each one of them. From all Co-morbidities n (%) participants, 90 performed again a 2MWT wearing Faros at home Depression 6 (4%) 6 (10%) the day after the clinical visit. Table 1 shows the demographic Blood pressure disorders 5 (3%) 4 (7%) data and baseline clinical data for all participants. Approval of Thyroid disorder 5 (3%) 3 (5%) the protocol was obtained from hospitals’ ethical committees and informed consent obtained from all participants. This study was co- Heart diseases 2 (1%) 2 (3%) developed with service users in our Patient Advisory Board, who Statistically significant differences are indicated in bold text. were involved in the choice of measures, the timing and issues MS, multiple sclerosis; RRMS, Relapsing–Remitting Multiple Sclerosis; SPMS, secondary progressive multiple sclerosis; BMI, body mass index; FSS, fatigue severity scale; EDSS, of engagement. The inclusion criteria for this study were an age expanded disability status scale; 2MWT, 2-Minute Walk Test; 6MWT, 6-Minute Walk Test. 18 or over, diagnosis of MS according to 2010 revisions to the McDonald criteria, RRMS or SPMS phenotypes, EDSS from 2 to 6, the ability to give informed consent for participation, the willingness and ability to complete self-reported assessments via smartphone, with cut-off frequency of 0.5 Hz. To reduce the effect of jitter into existing ownership of android smartphone, while exclusion criteria HRV parameters, the ECG was up-sampled from 125 to 1,000 Hz were the presence of any condition (physical, mental, or social) that (Malik et al., 1996). Then, a wavelet-based detector was applied is likely to affect the subject’s ability to comply with the protocol, and to identify the position of the QRS-complexes (Martínez et al., female subjects who are currently pregnant. For further information 2004). HRV was generated from the beat occurrence time series on the MS study and assessment schemes the interested reader is based on the integral pulse frequency modulation (IPFM) model, referred to (Dalla Costa et al., 2020). which accounts for misdetections and the presence of ectopic beats (Bailón et al., 2010). The IPFM model assumes that ANS modulation on the sinoatrial node can be represented by a band- 2.2 Heart rate variability and respiration limited signal. To derive spectral parameters, the modulating signal indices was sampled at 4 Hz, and the power spectral density was obtained by applying Welch’s periodogram in segments of length 5 min. In this section the estimation of ECG-derived cardiorespiratory A Hamming window of 100 s (50% overlap), which offers high parameters that reflect ANS function is described. However, surface temporal resolution and it allows the robust estimation of the lowest measurements of heart activity may include various types of noise, frequency of interest (4 periods for 0.04 Hz), was selected. and thus ECG should be first preprocessed. To remove the baseline From short-term recordings, two main spectral components are wander, the ECG signal was filtered using a forward-backward filter distinguished in the low-frequency (LF) band ([0.04, 0.15] Hz) and in the high-frequency (HF) band ([0.15, 0.4] Hz). HF spectral power is considered a measure of parasympathetic nervous system activity, 2 https://www.bittium.com/medical/bittium-faros mainly due to the respiratory sinus arrhythmia, while LF fluctuations Frontiers in Physiology 04 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 FIGURE 1 HRV analysis during the 2MWT (A) HRV signal, (B) EDR signal, (C) HR profile, and (D) HRV spectrum. in HRV have been suggested to represent both sympathetic and by averaging first measurements across multiple visits for each parasympathetic modulations (Malik et al., 1996). Note that in order subject. Statistical analysis is conducted to assess differences in HF spectral power to reflect parasympathetic activity, respiratory ANS regulation between groups of pwMS with different clinical rate must lay in the HF band. However, sometimes during exercise outcomes. First of all, ANS function in pwMS with different respiratory rate may be higher than the upper limit of the HF band. phenotype (RRMS or SPMS) is considered. Participants with Hence, the extended HF band (eHF), which goes up to half the low (FSS < 4) or high (FSS ≥ 4) fatigue scores (FSSL or FSSH , mean HR ( fHR ), i.e., the Nyquist frequency for HRV signals, is respectively), and with low (EDSS ≤ 2.5) or high (EDSS ≥ 4.5) preferred (Bailón et al., 2007). Thus, the normalized LF power, i.e., disability scores (EDSSL or EDSSH , respectively), consist in groups the relative value of the LF power in proportion to the total (LF of interest (Krupp et al., 1989; Manouchehrinia et al., 2017). Since and eHF) power, is calculated for estimating sympathovagal balance there is no cut-off value for grouping pwMS based on 6MWT or (SB). Note that for the correct estimation of SB, respiratory rate 2MWT scores, the lower and upper quartiles are used. Participants must not lay in the LF band. In this study, since no respiration are grouped into low or high 6MWT (6MWTL or 6MWTH ). signal was recorded, respiratory parameters are estimated from the For separating pwMS based on statistical distribution, the 6MWT ECG. The ECG-derived respiration (EDR) signal, named slope range is selected as it has a higher completeness (97%) compared (Kontaxis et al., 2019), is used to obtain the mean respiratory rate to 2MWT (63%), see Table 1. Statistically significant group ( fr ) from EDR spectra, and the standard deviation of the EDR differences (RRMS vs. SPMS, FSSL vs. FSSH , EDSSL vs. EDSSH , and signal (σr ), is used as surrogate of tidal volume (Varon et al., 2020). 6MWTL vs. 6MWTH ) are assessed with the two-sample t-test for It should be noted that a median absolute deviation-based rule independent samples, and the Mann-Whitney U non-parametric was implemented to remove outliers from the EDR signal before test when appropriate. Shapiro-Wilk and the two-sample F-test parameter estimation (Bailón et al., 2006). are conducted for ensuring normality and equality of variances, Besides HRM (HRMS ), sympathovagal balance (SBS ), and respectively. Differences in baseline demographic data are also respiratory parameters ( f Sr , σSr ) that are calculated for each stage S evaluated. (S = [B, T , R]), HRM is also estimated during the first (HRMT1 ) Regression models based on a clinical measure (Phenotype, and second minute (HRMT2 ) of the 2MWT in order to study the FSS, EDSS, 6MWT, 2MWT) with demographic variables (Sex, HR profile. The intra-subject difference between HRM parameters Age, BMI) as covariates are also used in order to determine during test (HRMT , HRMT1 , HRMT2 ) and either basal (HRMB ) significant predictors for autonomic variables. Partial correlation or recovery stage (HRMR ) are considered autonomic reactivity (Pearson r) analyses controlling for demographic variables (Sex, S indices. The reactivity indices, denoted Δ(HRM)S2 , are calculated by Age, BMI) are carried out for testing bivariate associations 1 subtracting the value of the HRM in S1 = [B, R] from that in S2 = between the most significant ANS parameters and clinical [T , T1 , T2 ]. Figure 1 illustrates an example of HRV analysis during outcomes. Since ANS function might differ according to the the 2MWT. phenotype of the disorder, correlation analyses are also conducted separately for the populations of RRMS and SPMS. Finally, correlation coefficients between ANS parameters derived at 2.3 Statistical analysis hospital and at home are calculated to test the feasibility of RMT to monitor disorder severity in pwMS outside clinical Since a small percentage of subjects has measurements for settings. The significance threshold in this study is set to more than two clinical visits, the statistical analysis is performed p < 0.05. Frontiers in Physiology 05 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 FIGURE 2 Boxplots of HRV and respiratory parameters for different groups of pwMS. Groups based on (A–D) phenotype, (E–H) fatigue severity, (I–L) disability level, and (M–P) walking capacity. Statistically significant group differences are denoted with an asterisk. TABLE 2 Regression models to determine ANS parameters by clinical features. Dependent variables Independent variables BETA (β) SE t p-value SBR Phenotype 0.05 0.02 2.34 <0.05 R = 0.75; R2 = 0.56 Age −0.003 0.001 −2.64 <0.01 F(4) = 3.66; p < 0.01 σT r FSS −0.49 0.14 −3.44 <0.001 R = 0.75; R2 = 0.56 Sex −1.55 0.48 −3.44 <0.01 F(4) = 8.59; p < 0.001 T Δ(HRM)R2 2MWT 0.08 0.03 2.66 <0.01 R = 0.77; R2 = 0.59 F(4) = 3.63; p < 0.01 T Δ(HRM)R2 6MWT 0.04 0.01 4.52 <0.001 R = 0.80; R2 = 0.64 F(4) = 7.48; p < 0.001 FSS, fatigue severity scale; 2MWT, 2-Minute Walk Test; 6MWT, 6-Minute Walk Test; SBR , sympathovagal balance at recovery phase; σT r , standard deviation of EDR signal during walk test; T Δ(HRM)R2 , change in HRM from second minute of 2MWT to recovery phase; R, the correlation between the predictor and the response variable; R2 , coefficient of determination; F, F-test statistic, BETA (β), the slope of regression line; SE, standard error between the points and the regression line; t, t-test statistic. Frontiers in Physiology 06 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 TABLE 3 Partial correlation coefficient r between ANS parameters and clinical outcomes. MS RRMS SPMS FSS EDSS 2MWT 6MWT FSS EDSS 2MWT 6MWT FSS EDSS 2MWT 6MWT HRMT −0.22 n.s n.s 0.24 −0.21 n.s n.s 0.31 −0.34 −0.20 n.s 0.33 SBR n.s n.s n.s n.s n.s n.s 0.29 0.21 n.s n.s n.s n.s σT r −0.25 n.s n.s n.s −0.22 n.s n.s n.s −0.45 n.s n.s n.s fR r n.s n.s n.s n.s n.s n.s n.s n.s n.s n.s 0.40 0.29 T Δ(HRM)R1 n.s n.s 0.24 0.32 n.s n.s n.s 0.35 n.s n.s 0.50 0.38 T Δ(HRM)R2 n.s n.s n.s 0.36 n.s n.s n.s 0.36 n.s −0.31 0.51 0.50 a n.s., not statistically significant correlation value. MS, multiple sclerosis; RRMS, Relapsing–Remitting MS; SPMS, Secondary Progressive MS; FSS, fatigue severity scale; EDSS, expanded disability status scale; 2MWT, 2-Minute Walk Test; 6MWT, 6-Minute Walk Test; HRMT , heart rate mean during walk test; SBR , sympathovagal balance at recovery phase; σT R r , standard deviation of EDR signal during walk test; f r , respiratory T T frequency at recovery phase; Δ(HRM)R1 , change in HRM from first minute of 2MWT to recovery phase; Δ(HRM)R2 , change in HRM from second minute of 2MWT to recovery phase. FIGURE 3 Scatter plots of the most significant ANS parameters for each clinical outcome measure (A) FSS, (B) EDSS, (C) 2MWT, and (D) 6MWT. A blue and red line are fitted to the data of RRMS and SPMS group, respectively, while a black line is fitted to the data without taking into account the phenotype of the disorder. 3 Results (Figure 2O). Sympathetic dominance was statistically significant higher in 6MWTH group during recovery period (Figure 2N). Figure 2 illustrates the boxplots of HRV and respiratory Furthermore, reactivity indices (not shown) were found to be parameters for different groups of pwMS. Groups based on statistically different between the groups of 6MWT, with higher phenotype consist of 148 and 58 subjects for RRMS and SPMS reactivity to be associated with pwMS who were able to walk longer group, respectively, while the groups of (low, high) scores for FSS, distance. It should be also noted that only a small percentage of EDSS, and 6MWT, consist of (64, 131), (70, 35), and (51, 51) about 3% of SB at each stage was excluded from the analysis because subjects, respectively. Regarding phenotype, SPMS group, compared respiratory rate was laying in the LF band. to RRMS, shows statistically significant higher HRM during walk Significant predictors of ANS parameters in pwMS are presented test (Figure 2A) and increased sympathovagal balance after test in Table 2. Regression analysis results confirm that MS phenotype is execution (Figure 2B). Participants with low fatigue scores reached an independent predictor for SBR besides the significant effect of higher HRM level during T and respiratory rate during R than those age on sympathovagal balance. The FSS score, and the sex variable, with higher fatigue scores (Figures 2E, G). In relation to disability, were identified as independent predictors for σT r , while 2MWT, EDSSL group, compared to EDSSH , exhibits also higher HRM during and 6MWT scores were statistically significant predictors for HRM T test execution (Figure 2I), as well as higher f Tr (Figure 2K) σr R reactivity measured with Δ(HRM)R2 . (Figure 2L), suggesting that exercise may induce significant changes Results of partial correlation analyses are summarized in in respiratory system. Finally, pwMS who were able to walk longer Table 3. It can be seen that, analyzing all pwMS without taking distance (6MWTH ) show higher HRMT and σT r (Figure 2M,P), into account the phenotype of the disorder, there is a weak that implies a greater cardiopulmonary effort compared to pwMS association between ANS parameters and outcome measures. In in 6MWTL group. The same holds for the respiratory rate that particular, a moderate positive correlation between 6MWT and remained higher in 6MWTH group even after task execution reactivity indices of HRM, implies that higher autonomic reactivity Frontiers in Physiology 07 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 FIGURE 4 Scatter plots of the most significant ANS parameters derived during 2MWT performed at hospital and at home. (A) σT r , (B) HRMT , (C) HRMT1 , and (D) HRMT2 . is associated with pwMS who were able to walk longer distance. The fatigue severity, disability level, and walking capacity, are evaluated increase of HRM during the last minute of the 2MWT with respect with rating scales and walk tests performed during periodical T to recovery stage (Δ(HRM)R2 ) shows the best results (r = 0.36) clinical visits. The feasibility of ANS parameters to provide a home- (r = 0.32). Regarding EDSS, no significant association was found, based monitoring of clinical markers is also explored. while less-fatigued pwMS show a larger cardiopulmonary effort HRV analysis can be used to assess the dynamic balance during the walk test (HRMT , σT r ). However, differences in ANS between the sympathetic and parasympathetic systems, allowing to regulation between people with RRMS and SPMS may blur the infer the autonomic function. Results show that HRV parameters association of ANS parameters with the clinical markers. Taking into differ among participants depending on the MS phenotype. account the phenotype of the disorder, results show a strong positive People with SPMS, compared to RRMS, show higher HRM correlation in people with SPMS between reactivity indices of while performing walk tests and larger SB after test performance T HRM (Δ(HRM)R2 ) and 6MWT or 2MWT scores, yielding r = 0.50 (Figures 2A,B). Further statistical analyses revealed that the and r = 0.51 (r = 0.51and r = 0.60), respectively. Moreover, a higher phenotype of MS was a significant predictor of sympathovagal respiratory rate after test execution ( f R r ) was associated with better balance (Table 2). Increased sympathetic dominance is associated walking capacity, yielding r = 0.40 (2MWT) and r = 0.29 (6MWT) with autonomic imbalance, which is often reported to be more (r = 0.48 (2MWT) and r = 0.33 (6MWT). A negative correlation pronounced in the progressive variant of the MS (Zawadka- between σT r and FSS (r = −0.45) (r = 0.50) suggests a higher tidal Kunikowska et al., 2020; Gerasimova-Meigal et al., 2021). These volume during walking in less-fatigued people with SPMS. Only results are in agreement with previous studies which found that for SPMS group there is significant correlation between autonomic pwMS exhibit higher HR levels during exercise compared to healthy reactivity and EDSS scores (r = −0.31) (r = 0.35). On the contrary, a subjects (Savci et al., 2005), and more prominent differences in weak positive relationship between sympathovagal balance (SBR ) autonomic tone during recovery phase (Gervasoni et al., 2018). and walk test scores was only found in RRMS group. Figure 3 Anticipatory stress dynamics prior to test execution could be illustrates the scatter plots of the most significant ANS parameters implicated in the absence of significant differences between MS for each outcome measure. subgroups during basal conditions (Juster et al., 2012; Adamec et al., Finally, ANS parameters derived at home and at clinical visit 2018; Reynders et al., 2020). while participants were performing the 2MWT, including σT r , Autonomic dysregulation, besides the key role it plays in HRMT , HRMT1 , and HRMT2 , showed a significant association, the progression of the disorder, it is also involved in the vast yielding r = 0.74, r = 0.71, r = 0.70, and r = 0.70 r = 0.69, r = 0.68, majority of MS-related symptoms (Findling et al., 2020). Results r = 0.67, and r = 0.70, respectively (Figure 4). This strong correlation show that pwMS with low FSS and EDSS scores reach higher implies that RMT could be used for monitoring disorder severity HRM values during walk tests (Figures 2E,I). Greater fatigue in pwMS, complementing thus, periodic evaluations performed at and disability severity in pwMS may be associated with loss in hospital. the capacity to increase cardiovascular output during exercise (Capone et al., 2020). Lower HR in moderate compared to mild disability group of pwMS at the end of walk tests was also observed in 4 Discussion (Bosnak-Guclu et al., 2012). Similar to patients with chronic fatigue syndrome, HR was lower during exercise tests relative to control In this study the association between ANS response to walk subjects (De Becker et al., 2000; Nelson et al., 2019). Furthermore, tests and outcome measures in pwMS is investigated. Autonomic reduced cardiovascular output can lead to less ventilatory efficiency function is assessed with HRV and respiratory parameters derived (Inbar et al., 2001; Javierre et al., 2010). This is in accordance with from a wearable device, while MS-related symptoms, including the lower respiratory rates ( f R T r , f r ) attained by pwMS with higher Frontiers in Physiology 08 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 fatigue and disability severity scores (Figures 2G,K). Furthermore, RRMS group there is a significant correlation between SB and walk a higher FSS score was a significant predictor of decreased standard test scores. deviation of the EDR signal measured with σT r (Table 2). Inconsistencies regarding the link between disorder severity and Abnormalities in cardiac and/or ventilatory function can SB can be muddled by changes in respiration, since the beat-to- limit exercise performance capacity in pwMS (Wens et al., 2016). beat fluctuation in HR at the frequency of the respiratory cycle, Participants who were able to walk longer distance (6MWTH ) which is known as the respiratory sinus arrhythmia component, is exhibit higher HRMT , f T T r , and σr values during walk tests mediated by the parasympathetic branch of the ANS (Billman et al., (Figure 2M,O,P), implying a greater cardiopulmonary effort than 2015; Ziemssen and Siepmann, 2019). In this study, the influence pwMS in 6MWTL group. An increased respiratory rate and of respiration on SB estimation is taken into account by tracking sympathetic dominance in 6MWTH group is also observed after test the respiratory rate and by modifying the classical HF band in execution (Figure 2N,O). A significantly shorter distance walked HRV analysis. Beyond the heterogeneity of the applied methods, by pwMS compared to healthy individuals was previously reported the assessment of ANS functionality using different autonomic in (Savci et al., 2005), while cumulative evidence supports that tests could lead to discrepancies regarding the role of autonomic changes in cardiorespiratory fitness outcomes during exercise are reactivity in MS. For instance, contradictory results have been the most sensitive to detect worsening in pwMS (Paltamaa et al., reported about autonomic responses to mental and orthostatic 2008; Heine et al., 2016; Madsen et al., 2019). These data thus seem stress (Studer et al., 2017; Vlcek et al., 2018; Imrich et al., 2021), to indicate that the cardiorespiratory system is stressed when a walk while walk tests and deep breathing protocols may enhance test is performed by pwMS (Dalgas et al., 2014). differences in ANS regulation between pwMS and healthy subjects Autonomic response to stress can provide valuable information (Paltamaa et al., 2008; Wens et al., 2016; Gerasimova-Meigal et al., regarding the monitoring of clinical outcomes in MS (Briones- 2021). Buixassa et al., 2015; Rzepiński et al., 2022). Besides changes from Walk tests may be one of the most straightforward procedures baseline to stress exposure, the length and persistence of stress for inducing autonomic changes, not only in clinical settings but reactions following the demanding challenge should be considered also at home (Singh et al., 2014). With the development of RMTs, (Juster et al., 2012). The findings of this study reveal that walked such as, smartphones, wearable sensors or home-based devices, ANS distance and HRM reactivity indices have a positive relationship parameters can be monitored remotely Malasinghe et al. (2019). (Table 3). The increment of HRM during the last minute of the Strong correlation between ANS parameters derived at home and 2MWT with respect to recovery stage shows the best performance at clinical visits during the performance of walk tests (Figure 4) (r = 0.36) (r = 0.32) in pwMS (RRMS and SPMS). Furthermore, implies that RMTs can be used for home-based monitoring of 2MWT and 6MWT scores were found as significant predictors disorder severity in pwMS. Aside from complementing clinical T of increased HRM reactivity measured with Δ(HRM)R2 (Table 2). assessments, reducing clinic contact allows also pwMS who would These results imply that pwMS with larger autonomic reactivity were not normally engage in studies to participate (Owens, 2020). able to walk longer distance. Reduced autonomic reactivity in pwMS, Furthermore, the feasibility of RMT to detect small changes in compared to healthy subjects, has been previously documented impairment or functional improvement on a more regular basis (Gerasimova-Meigal et al., 2021). Moreover, blunted autonomic could accurately represent long-term changes in the clinical state of reactivity was found to be related with incomplete recovery from pwMS (Alexander et al., 2020). relapses (Studer et al., 2017). However, no relationship between Although RMTs offer a lot of potential for research, they do reactivity indices and disability and/or fatigue severity scores is have important limitations. Many technologies have a high initial usually reported (Flachenecker et al., 2003; Gervasoni et al., 2018; engagement level that fades quickly if usage is not constantly Sander et al., 2019; Rampichini et al., 2020). monitored after the initial enthusiasm and commitment of users The weak associations between outcome measures and ANS (Dorsey et al., 2017). In this study, only a small subset of subjects parameters might be attributed to differences in autonomic (about 60%) performed walk tests at home. Unintentional walk regulation between people with RRMS and SPMS (Adamec et al., testing, which does not modify casual activity habits, may increase 2018). Correlation analyses show better results taking into account the number of pwMS who are less motivated to perform such tests the phenotype of the disorder (Figure 3). Reactivity indices of HRM for extended periods. According to a recent study, unintentional and walk test scores, in particular, show a strong positive association walk testing has been shown to be practical and useful for assessing in people with SPMS, yielding (r = 0.50 and r = 0.51) (r = 0.51 and walking capacity in free-living activities (Sokas et al., 2021). Another r = 0.6) for 6MWT and 2MWT scores, respectively (Table 3). In important limitation is the interpretation of SB during walk test. (Hansen et al., 2013), walking capacity in pwMS was also found to Despite vagal withdrawal, hyperpnea could entail a significant be highly correlated with the impairment in adapting HR. Moreover, increase in HF power due to the mechanical effect of respiration on results show that pwMS who were able to walk longer distance reach HRV (Cottin et al., 2008). Hence, a rise in sympathetic tone, and higher respiratory rate during recovery, while less-fatigued pwMS consequently in SB, might be blurred when respiratory rate and show a larger cardiopulmonary effort during walk test (HRMT , σT r ). respiratory pattern are not taken into account. A better assessment Previous studies reported that ventilatory dysfunction in pwMS was of the SB could be achieved by removing respiratory influences from related to worse exercise tolerance (Hansen et al., 2015). Regarding HRV (Varon et al., 2018). disability, pwMS with lower EDSS values show higher reactivity Apart from monitoring respiration while assessing HRV indices, indices of HRM, while other studies have reported a significant the need of evaluating respiratory function in pwMS is becoming association with SB (Shirbani et al., 2018). In this study, only for increasingly apparent. Recent studies suggest that pwMS are at Frontiers in Physiology 09 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 increased risk for sleep disturbances (Braley and Boudreau, 2016; patients/participants provided their written informed consent to Sakkas et al., 2019). Intermittent hypoxia produced by apneas participate in this study. during the night might enhance oxidative stress and aggravate MS neurodegeneration (Hensen et al., 2018). In addition to being a trigger for an acute MS exacerbation, sleep disorders contribute Author contributions significantly to fatigue and other chronic MS symptoms (Braley and Boudreau, 2016; Sahraian et al., 2017). Thus, respiratory SK, EL, EG, NC, SV, and RB contributed to the study design. function should be assessed early in the illness course so that SK, EL, and RB contributed to the data analysis and manuscript rehabilitation can be planned to prevent respiratory complications writing. AG, AZ, MM, RL, MB, LL, and GC contributed to the data and improve quality of life in pwMS (Muhtaroglu et al., 2020). It collection. VN, SS, ZR, AF, and RD contributed to the administrative should be also noted that autonomic tests assessing respiratory and technical support of the study. JW, LL, GC, MM, PS, CN, function (e.g., deep breathing test) (Rzepiński et al., 2022), could and GC contributed to the clinical support of the study. MH (PI be more suitable instead of walk tests to quantify autonomic of RADAR-CNS) contributed to funding and oversight of data response in people with SPMS who often suffer from limited collection. All authors contributed to the critical revision of the ambulation (Wens et al., 2016). Screening for both ventilatory manuscript. and cardiac function could open a window of opportunities for the early diagnosis of the progressive stage of MS that is often established retrospectively and delayed (Inojosa et al., 2021). Funding Finally, confirming findings of previous studies, both clinical outcomes and demographic characteristics (Table 2) may be also The RADAR-CNS project has received funding from the considered as significant predictors of autonomic function in pwMS Innovative Medicines Initiative 2 Joint Undertaking under grant Rzepiński et al. (2019). Thus, further research should be conducted agreement No 115902. This Joint Undertaking receives support for people with primary progressive MS, including a healthy control from the European Union’s Horizon 2020 research and innovation group as well, taking into account differences in more demographic programme and EFPIA (www.imi.europa.eu). This communication predictors (e.g., fitness levels), and changes in medication or reflects the views of the RADAR-CNS Consortium and neither IMI other disease modifying treatments (e.g., haematopoietic stem cell nor the European Union and EFPIA are liable for any use that transplantation). may be made of the information contained herein. Morover, the In conclusion, the findings of this study show that autonomic work was supported by the Grant TED2021-131106B-I00 funded by function as measured by HRV differs according to MS phenotype, MCIN/AEI/ 10.13039/501100011033 and by the “European Union with sympathetic dominance to be more pronounced in SPMS NextGenerationEU/PRTR”. compared to RRMS. Autonomic response to walk tests quantified by autonomic reactivity indices and respiratory parameters are useful for assessing clinical outcomes mainly in the progressive stage of Acknowledgments MS. Moreover, pwMS with larger autonomic reactivity, in particular, are able to walk longer distance, while reduced ventilatory function We thank all the members of the RADAR-CNS patient advisory during and after walk test performance is associated with higher board for their contribution to the device selection procedures, fatigue and disability severity scores. Finally, this study demonstrates and their invaluable advice throughout the study protocol that monitoring of disorder severity could be feasible using ECG- design. derived cardiac and respiratory parameters recorded with a wearable device at home. Conflict of interest Data availability statement MB has received speaker honoraria from Novartis. The remaining authors declare that the research was conducted The datasets presented in this article are not readily available in the absence of any commercial or financial relationships that because of ethic requirements. Requests to access the datasets should could be construed as a potential conflict of interest. be directed to the RADAR-CNS consortium and will be subject to local ethics clearances. Please email the corresponding author for details. Publisher’s note All claims expressed in this article are solely those Ethics statement of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, The studies involving human participants were reviewed and the editors and the reviewers. Any product that may be approved by Casa di Cura del Policlinico, Hospital Universitari evaluated in this article, or claim that may be made by its Vall d’Hebron, Copenhagen University Hospital Rigshospitalet. The manufacturer, is not guaranteed or endorsed by the publisher. Frontiers in Physiology 10 frontiersin.org Kontaxis et al. 10.3389/fphys.2023.1145818 References Adamec, I., Crnošija, L., Junaković, A., Skorić, M. K., and Habek, M. 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