Tanja Heger

Time- and frequency-domain parameters of heart rate variability and sympathetic skin response in Parkinson's disease

The autonomic nervous system (ANS) is regularly affected in Parkinson’s disease (PD). Information on autonomic dysfunction can be derived from e.g. altered heart rate variability (HRV) and sympathetic skin response (SSR). Such parameters can be quantified easily and measured repeatedly which might be helpful for evaluating disease progression and therapeutic outcome. In this 2-center study, HRV and SSR of 45 PD patients and 26 controls were recorded. HRV was measured during supine metronomic breathing and analyzed in time- and frequency-domains. SSR was evoked by repetitive auditory stimulation. Various ANS parameters were compared (1) between patients and healthy controls, (2) to clinical scales (Unified Parkinson’s disease rating scale, Mini-Mental State Examination, Becks Depression Inventory), and (3) to disease duration. Root mean square of successive differences (RMSSD) and low frequency/high frequency (LF/HF) ratio differed significantly between PD and controls. Both, HRV and SSR parameters showed low or no association with clinical scores. Time-domain parameters tended to be affected already at early PD stages but did not consistently change with longer disease duration. In contrast, frequency-domain parameters were not altered in early PD phases but tended to be lower (LF, LF/HF ratio), respectively higher (HF) with increasing disease duration. This report confirms previous results of altered ANS parameters in PD. In addition, it suggests that (1) these ANS parameters are not relevantly associated with motor, behavioral, and cognitive changes in PD, (2) time-domain parameters are useful for the assessment of early PD, and (3) frequency-domain parameters are more closely associated with disease duration.

Quantitative timed-up-and-go parameters in relation to cognitive parameters and health- related quality of life in mild-to-moderate Parkinson's disease

Introduction The instrumented-Timed-Up-and-Go test (iTUG) provides detailed information about the following movement patterns: sit-to-walk (siwa), straight walking, turning and walk-to-sit (wasi). We were interested in the relative contributions of respective iTUG sub-phases to specific clinical deficits most relevant for daily life in Parkinson’s disease (PD). More specifically, we investigated which condition–fast speed (FS) or convenient speed (CS)–differentiates best between mild- to moderate-stage PD patients and controls, which parameters of the iTUG sub-phases are significantly different between PD patients and controls, and how the iTUG parameters associate with cognitive parameters (with particular focus on cognitive flexibility and working memory) and Health-Related-Quality of Life (HRQoL). Methods Twenty-eight PD participants (65.1±7.1 years, H&Y stage 1–3, medication OFF state) and 20 controls (66.1±7.5 years) performed an iTUG (DynaPort®, McRoberts BV, The Netherlands) under CS and FS conditions. The PD Questionnaire 39 (PDQ-39) was employed to assess HRQoL. General cognitive and executive functions were assessed using the Montreal Cognitive Assessment and the Trail Making Test. Results The total iTUG duration and sub-phases durations under FS condition differentiated PD patients slightly better from controls, compared to the CS condition. The following sub-phases were responsible for the observed longer total duration PD patients needed to perform the iTUG: siwa, turn and wasi. None of the iTUG parameters correlated relevantly with general cognitive function. Turning duration and wasi maximum flexion velocity correlated strongest with executive function. Walking back duration correlated strongest with HRQoL. Discussion This study confirms that mild- to moderate-stage PD patients need more time to perform the iTUG than controls, and adds the following aspects to current literature: FS may be more powerful than CS to delineate subtle movement deficits in mild- to moderate-stage PD patients; correlation levels of intra-individual siwa and wasi parameters may be interesting surrogate markers for the level of automaticity of performed movements; and sub-phases and kinematic parameters of the iTUG may have the potential to reflect executive functioning and HRQoL aspects of PD patients.

Algorithm for Turning Detection and Analysis Validated under Home-Like Conditions in Patients with Parkinson’s Disease and Older Adults using a 6 Degree-of-Freedom Inertial Measurement Unit at the Lower Back

Introduction Aging and age-associated disorders such as Parkinson’s disease (PD) are often associated with turning difficulties, which can lead to falls and fractures. Valid assessment of turning and turning deficits specifically in non-standardized environments may foster specific treatment and prevention of consequences. Methods Relative orientation, obtained from 3D-accelerometer and 3D-gyroscope data of a sensor worn at the lower back, was used to develop an algorithm for turning detection and qualitative analysis in PD patients and controls in non-standardized environments. The algorithm was validated with a total of 2,304 turns ≥90° extracted from an independent dataset of 20 PD patients during medication ON- and OFF-conditions and 13 older adults. Video observation by two independent clinical observers served as gold standard. Results In PD patients under medication OFF, the algorithm detected turns with a sensitivity of 0.92, a specificity of 0.89, and an accuracy of 0.92. During medication ON, values were 0.92, 0.78, and 0.83. In older adults, the algorithm reached validation values of 0.94, 0.89, and 0.92. Turning magnitude (difference, 0.06°; SEM, 0.14°) and duration (difference, 0.004 s; SEM, 0.005 s) yielded high correlation values with gold standard. Overall accuracy for direction of turning was 0.995. Intra class correlation of the clinical observers was 0.92. Conclusion This wearable sensor- and relative orientation-based algorithm yields very high agreement with clinical observation for the detection and evaluation of ≥90° turns under non-standardized conditions in PD patients and older adults. It can be suggested for the assessment of turning in daily life.

Insulin-Like Growth Factor 1 (IGF-1) in Parkinson's Disease: Potential as Trait-, Progression- and Prediction Marker and Confounding Factors.

Introduction Biomarkers indicating trait, progression and prediction of pathology and symptoms in Parkinsons disease (PD) often lack specificity or reliability. Investigating biomarker variance between individuals and over time and the effect of confounding factors is essential for the evaluation of biomarkers in PD, such as insulin-like growth factor 1 (IGF-1). Materials and Methods IGF-1 serum levels were investigated in up to 8 biannual visits in 37 PD patients and 22 healthy controls (HC) in the longitudinal MODEP study. IGF-1 baseline levels and annual changes in IGF-1 were compared between PD patients and HC while accounting for baseline disease duration (19 early stage: ≤3.5 years; 18 moderate stage: >4 years), age, sex, body mass index (BMI) and common medical factors putatively modulating IGF-1. In addition, associations of baseline IGF-1 with annual changes of motor, cognitive and depressive symptoms and medication dose were investigated. Results PD patients in moderate (130±26 ng/mL; p = .004), but not early stages (115±19, p>.1), showed significantly increased baseline IGF-1 levels compared with HC (106±24 ng/mL; p = .017). Age had a significant negative correlation with IGF-1 levels in HC (r = -.47, p = .028) and no correlation in PD patients (r = -.06, p>.1). BMI was negatively correlated in the overall group (r = -.28, p = .034). The annual changes in IGF-1 did not differ significantly between groups and were not correlated with disease duration. Baseline IGF-1 levels were not associated with annual changes of clinical parameters. Discussion Elevated IGF-1 in serum might differentiate between patients in moderate PD stages and HC. However, the value of serum IGF-1 as a trait-, progression- and prediction marker in PD is limited as IGF-1 showed large inter- and intraindividual variability and may be modulated by several confounders.

Validation of a Step Detection Algorithm during Straight Walking and Turning in Patients with Parkinson’s Disease and Older Adults using an Inertial Measurement Unit at the Lower Back

Introduction Inertial measurement units (IMUs) positioned on various body locations allow detailed gait analysis even under unconstrained conditions. From a medical perspective, the assessment of vulnerable populations is of particular relevance, especially in the daily-life environment. Gait analysis algorithms need thorough validation, as many chronic diseases show specific and even unique gait patterns. The aim of this study was therefore to validate an acceleration-based step detection algorithm for patients with Parkinson’s disease (PD) and older adults in both a lab-based and home-like environment. Methods In this prospective observational study, data were captured from a single 6-degrees of freedom IMU (APDM) (3DOF accelerometer and 3DOF gyroscope) worn on the lower back. Detection of heel strike (HS) and toe off (TO) on a treadmill was validated against an optoelectronic system (Vicon) (11 PD patients and 12 older adults). A second independent validation study in the home-like environment was performed against video observation (20 PD patients and 12 older adults) and included step counting during turning and non-turning, defined with a previously published algorithm. Results A continuous wavelet transform (cwt)-based algorithm was developed for step detection with very high agreement with the optoelectronic system. HS detection in PD patients/older adults, respectively, reached 99/99% accuracy. Similar results were obtained for TO (99/100%). In HS detection, Bland–Altman plots showed a mean difference of 0.002 s [95% confidence interval (CI) −0.09 to 0.10] between the algorithm and the optoelectronic system. The Bland–Altman plot for TO detection showed mean differences of 0.00 s (95% CI −0.12 to 0.12). In the home-like assessment, the algorithm for detection of occurrence of steps during turning reached 90% (PD patients)/90% (older adults) sensitivity, 83/88% specificity, and 88/89% accuracy. The detection of steps during non-turning phases reached 91/91% sensitivity, 90/90% specificity, and 91/91% accuracy. Conclusion This cwt-based algorithm for step detection measured at the lower back is in high agreement with the optoelectronic system in both PD patients and older adults. This approach and algorithm thus could provide a valuable tool for future research on home-based gait analysis in these vulnerable cohorts.

Limited Effect of Dopaminergic Medication on Straight Walking and Turning in Early-to-Moderate Parkinson’s Disease during Single and Dual Tasking

Background In Parkinson’s disease (PD), the effects of dopaminergic medication on straight walking and turning were mainly investigated under single tasking (ST) conditions. However, multitasking situations are considered more daily relevant. Methods Thirty-nine early-to-moderate PD patients performed the following standardized ST and dual tasks as fast as possible for 1 min during On- and Off-medication while wearing inertial sensors: straight walking and turning, checking boxes, and subtracting serial 7s. Quantitative gait parameters as well as velocity of the secondary tasks were analyzed. Results The following parameters improved significantly in On-medication during ST: gait velocity during straight walking (p = 0.03); step duration (p = 0.048) and peak velocity (p = 0.04) during turning; velocity of checking boxes during ST (p = 0.04) and DT (p = 0.04). Velocity of checking boxes was the only parameter that also improved during DT. Conclusion These results suggest that dopaminergic medication does not relevantly influence straight walking and turning in early-to-moderate PD during DT.

Neurodegenerative CSF markers in genetic and sporadic PD: Classification and prediction in a longitudinal study

BACKGROUND Parkinsons disease (PD) patients show a large phenotypic variability probably reflecting inter-individual pathologic heterogeneity. Next to typical Lewy-body pathology, β-amyloid (Aβ) and tau pathology have been found at autopsy and several studies have reported altered CSF levels of Aβ1-42, total-Tau (t-Tau) and phosphorylated-Tau (p-Tau). OBJECTIVES To evaluate whether CSF levels of neurodegenerative markers are influenced by genetics and whether specific subgroups of PD are more prone to a concomitant pathology possibly reflecting aspects of disease progression. METHODS In an explorative study we assessed CSF profiles of Aβ1-42, t-Tau, and p-Tau longitudinally in PD patients carrying LRRK2 (n = 5) or GBA mutations (n = 12), sporadic PD patients (n = 30) and healthy controls (n = 16). RESULTS Compared to healthy controls, all three PD cohorts showed lower levels of Aβ1-42. Moreover, sporadic PD and GBA-PD patients presented with lower levels of t-Tau and p-Tau whereas this phenomenon was not seen in LRRK2-PD patients. Regression analyses revealed an association between higher levels of Baseline p-Tau with more accelerated cognitive deterioration over time in LRRK2-PD and GBA-PD patients, but not in sporadic PD. CONCLUSION PD patients present with disease-specific CSF profiles of Aβ1-42, t-Tau and p-Tau arguing in favor of an involvement of these proteins in PD pathogenesis in both sporadic and genetic forms. Moreover, we found first hints for differences in these CSF profiles between genetically determined PD cohorts but that CSF constellations which tend to predict aspects of disease progression such as cognitive decline seem similar across subgroups of PD.

Progression markers of motor deficits in Parkinson's disease: A biannual 4-year prospective study

Progressive neurodegeneration is a core characteristic of Parkinson’s disease (PD). However, the lack of reliable progression FIG. 1. (a) Adaptive DBS (aDBS) testing in a chronically implanted Parkinson’s patient. Upper channel shows the averaged beta power over 400millisecond episodes (moving average). The black line demarcates the threshold for applying stimulation. The middle channel shows the LFP filtered around the dominant beta frequency (20 6 3 Hz). The bottom channel shows the stimulation copy that starts and ends with a 250-milliseconds ramping period. The dotted blue lines illustrate the relation between the increase in beta power and the start of stimulation. (b) Average dwell time on a tablet tapping task during nostimulation, continuous DBS (cDBS), and aDBS. [Color figure can be viewed at wileyonlinelibrary.com]

P171. The relationship between quantitative parameters of the Timed-up-and-Go phases, and health-related quality of life in Parkinson’s disease

Introduction Health related quality of life (HRQoL) is widely accepted as the most important factor for patients living with chronic diseases, and therefore as the most important factor to evaluate (success of) treatment. The downside of the parameter is that evaluation is qualitative, imprecise and prone to bias. To overcome these shortcomings, quantitative and objective assessment tools may be useful that have some potential to serve as a kind of “surrogate marker” for HRQoL. The Timed-Up-and-Go-Test (TUG) is a short test which provides information about important movement patterns, i.e. transfer (sit-to-walk, walk-to-sit), walking and turning. The total time needed to perform the TUG has already been shown to be associated with lower HRQoL in a chronic disease (Parkinson’s disease, PD) however, to the best of our knowledge, no study is currently available which investigated sub-phases of the TUG based on quantitative wearable sensors, and their association with HRQoL in a chronic disease. Objective To identify TUG sub-phases quantitatively that are associated with HRQoL. Methods Thirty-seven PD participants (H&Y stage I-III, ‘off’ state) performed an instrumented TUG (Dynaport®, McRoberts BV, The Netherlands) in four conditions (convenient and fast speed, turning to the left and to the right). The PD Questionnaire 39 (PDQ-39) was used to assess HRQoL. Pearson’s correlation analyses were performed to identify correlations between TUG sub-phases and HRQoL. Results TUG total time correlated well with the PDQ-39 measures. This observation was largely independent of different assessment conditions. From all sub-phases investigated, the walking forth time had the strongest association with the HRQoL questionnaire, followed by the turning phases. Again, these associations were widely independent of the assessment condition. Transfer times did only weakly or even not correlate with the HRQoL measures. Details are provided in Table 1 . Discussion, conclusion Our data confirm previous findings of a relatively strong association of TUG total time with HRQoL in PD. The duration of sub-phases seem not relevantly add to this finding. Interestingly, the sit-to-walk and walk-to-sit times correlated least with the PDQ-39. As the proper execution of transfers is a relevant prerequisite for performing daily activities, this result needs further investigation. Future work – also in our group – will therefore focus on more detailed analysis of sub-phases, considering qualitative aspects of the specific movements.