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

Jules M. Janssen Daalen, Robin van den Bergh, Eva M. Prins, Mahshid Sadat Chenarani Moghadam, Rudie van den Heuvel, J.VanDer Veen, Soania Mathur, Hannie Meijerink, Anat Mirelman, Sirwan K.L. Darweesh,

npj Digital Medicine · 2024 · 39 citations · 153 references

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TL;DR

Digital biomarkers that remotely monitor symptoms could transform Parkinson’s disease trials by enabling objective, repeated assessments in patients’ homes, yet while motor features are rapidly advanced, the non‑motor domain remains underdeveloped. The review systematically evaluates emerging digital biomarkers for Parkinson’s disease non‑motor symptoms, assessing their technological readiness, potential to track disease progression across stages, and future trial deployment. The authors conduct a systematic review of digital biomarkers for PD non‑motor symptoms, including cross‑field developments, and assess their technological readiness and suitability for tracking disease progression. Wearables show promise for autonomic, constipation, and sleep metrics, including REM sleep behavior disorder, but neuropsychiatric biomarkers are less mature; most have not been validated in PD, and their ability to detect disease progression, especially in prodromal stages, remains untested, underscoring the need for real‑world validation in large longitudinal cohorts.

Abstract

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.

References

153