Digital Biotyping of FSHD Patients and Controls

Study Overview
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Brief Summary
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Facioscapulohumeral muscular dystrophy (FSHD) is a devastating progressive muscle dystrophy. There is no treatment. FSHD is generally characterized by asymmetrical weakness and wasting of facial, shoulder girdle and upper arm muscles followed by weakness of muscles of the trunk and lower extremities, but disease severity varies widely between patients. Relatively long periods of stability are interspersed with short periods of potentially steep decline, leading overall to a slow but unpredictable rate of progression. Different genotypes underlying FSHD have been identified, but they result in highly similar phenotypes and at the molecular level converge on undue expression of the transcription factor, DUX4, in skeletal muscle, which is thought to (ultimately) lead to muscle wasting due to inflammation, apoptosis, and oxidative stress. There is no approved treatment, although various companies are engaged in FSHD drug discovery and development aimed in particular at reducing DUX4 expression. Multiple treatment options are currently under development in both preclinical and early clinical stages. However, these efforts face significant challenges in the path to regulatory approval. Because of the slow and variable rate of progression of FSHD, evidencing a significant treatment response will be cumbersome using only the existing measurements of muscle function. The successful development of these investigative treatments for FSHD is therefore highly dependent on the availability of validated disease and treatment biomarkers to monitor disease progression and response to treatment, respectively. To date, no such validated biomarkers exist. This study is important for four reasons: 1. Clinical testing of FSHD drug candidates requires the availability of clinical biomarkers that (a) change relatively rapidly over time; (b) allow for identification of fast progressors; and (c) correlate with gold standard, but slowly changing, clinical severity and/or functional scores. This study is a first step in that direction as it seeks to explore if the investigational digital technologies described below are able to generate single or composite variables that (cross-sectionally) distinguish FSHD patients from controls. If identified, such variables will be tested as putative clinical FSHD biomarkers in a follow-up longitudinal study with FSHD patients. 2. Patient testimonies indicate that living with FSHD means living with pain, fatigue, social isolation, and anxiety about the future. This study provides the first-ever opportunity to gather objective, real-world data about the impact of FSHD on daily life. 3. Regulators have already indicated that Real-World Data (RWD) is a top strategic priority for their drug reviews. This study aims to fill this gap by gathering RWD about the physical and social activities of FSHD patients in comparison with controls. This way we aim to find (composite) scores that correlate with selected severity and functional scores and additionally distinguish FSHD patients from controls. 4. This study offers an opportunity to expand the spectrum of diseases in which RWD may be used as (a basis for) clinical outcome measures. A successful outcome of this study may support testing the MORE platform in other muscular dystrophies as well.

Official Title
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An Exploratory, Non-interventional Study to Biotype Patients With Facioscapulohumeral Muscular Dystrophy (FSHD) and Controls Using Digital Technologies

Conditions
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Muscular Dystrophy, Facioscapulohumeral

Intervention / Treatment
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* Behavioral: CHDR Monitoring Remotely (MORE)
* Behavioral: Withings Steel HR
* Behavioral: Withings Body+ scale
* Behavioral: Withings Blood Pressure Monitor


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients eligible for inclusion in this study have to fulfill all of the following criteria: Written informed consent is obtained before any assessment is performed. Males and females age 16+ years. Genetically confirmed FSHD. Symptomatic as demonstrated by Lamperti score >0. Fully functioning Android-based smartphone with Android version 5.0 or higher. Able to comply with the study procedures, prohibitions and restrictions (drug use) as specified in the protocol. Controls inclusion criteria Controls eligible for inclusion in this study have to fulfill all of the following criteria: Written informed consent is obtained before any assessment is performed. Males and females age 16+ years. Unrelated subjects without FSHD. Fully functioning Android-based smartphone with Android version 5.0 or higher. Able to comply with the study procedures, prohibitions and restrictions (drug use) as specified in the protocol. Exclusion Criteria: Patients fulfilling any of the following criteria are not eligible for inclusion in this study: Current or previously diagnosed illness or any clinical condition that, in the opinion of the investigator, might confound the results of the study. Positive urine β-human chorionic gonadotropin (β-hCG) pregnancy test at Screening in women of childbearing potential. Wearing a pacemaker or other internal medical device (e.g. Vagus nerve stimulation (VNS), Deep Brain Stimulation (DBS)). Current enrollment in an interventional study. Controls fulfilling any of the following criteria are not eligible for inclusion in this study: Current or previously diagnosed illness or any clinical condition that, in the opinion of the investigator, might confound the results of the study. Positive urine β-human chorionic gonadotropin (β-hCG) pregnancy test at Screening in women of childbearing potential. Wearing a pacemaker or other internal medical device (e.g. Vagus nerve stimulation (VNS), Deep Brain Stimulation (DBS)). Current enrollment in an interventional study.

Ages Eligible for Study
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Minimum Age: 16 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Patients with FSHD<br>CHDR Monitoring Remotely (MORE) Withings Steel HR Withings Body+ scale Withings Blood Pressure Monitor | Behavioral: CHDR Monitoring Remotely (MORE)<br>* CHDR MORE is a highly customizable platform which allows remote monitoring of patients and trial subjects, data ingestion, and data management. The current infrastructure includes an Android app to unobtrusively collect data from smartphone sensors, and a connection to the Withings Health online platform to collect wearable data. Data is stored on a secure server in a structured data scheme ensuring clear data management processes, forming a prerequisite for comprehensive data analysis. The Android app enables data collection from multiple smartphone sensors (e.g. location data, accelerometer and ambient light) as well as phone usage logs (e.g. app usage, calls and texts).<br>Behavioral: Withings Steel HR<br>* The Withings Steel HR is a commercially available smartwatch that combines various sensors to measure activity (steps, sleep, etc.) and heart rate (HR). HR is measured using a PPG (photoplethysmogram, i.e. optically obtained volumetric measurement) based on a commercially available sensor (AS7000) incorporating low-noise and high-sensitivity analogue circuitry. The manufacturer supplies the algorithm for converting the PPG signal into HR values. Data is transferred from the watch to the smartphone using the Withings Health Mate app from where it will be uploaded to the output server.<br>Behavioral: Withings Body+ scale<br>* Body composition (weight, BMI and Skeletal Muscle Mass) can be assessed with the Withings Body+ smart scale at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging.<br>Behavioral: Withings Blood Pressure Monitor<br>* Blood pressure can be assessed with the automated Withings Blood Pressure Monitor at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging<br>|
| Healthy controls<br>CHDR Monitoring Remotely (MORE) Withings Steel HR Withings Body+ scale Withings Blood Pressure Monitor | Behavioral: CHDR Monitoring Remotely (MORE)<br>* CHDR MORE is a highly customizable platform which allows remote monitoring of patients and trial subjects, data ingestion, and data management. The current infrastructure includes an Android app to unobtrusively collect data from smartphone sensors, and a connection to the Withings Health online platform to collect wearable data. Data is stored on a secure server in a structured data scheme ensuring clear data management processes, forming a prerequisite for comprehensive data analysis. The Android app enables data collection from multiple smartphone sensors (e.g. location data, accelerometer and ambient light) as well as phone usage logs (e.g. app usage, calls and texts).<br>Behavioral: Withings Steel HR<br>* The Withings Steel HR is a commercially available smartwatch that combines various sensors to measure activity (steps, sleep, etc.) and heart rate (HR). HR is measured using a PPG (photoplethysmogram, i.e. optically obtained volumetric measurement) based on a commercially available sensor (AS7000) incorporating low-noise and high-sensitivity analogue circuitry. The manufacturer supplies the algorithm for converting the PPG signal into HR values. Data is transferred from the watch to the smartphone using the Withings Health Mate app from where it will be uploaded to the output server.<br>Behavioral: Withings Body+ scale<br>* Body composition (weight, BMI and Skeletal Muscle Mass) can be assessed with the Withings Body+ smart scale at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging.<br>Behavioral: Withings Blood Pressure Monitor<br>* Blood pressure can be assessed with the automated Withings Blood Pressure Monitor at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Social activity | - Voice activation (probability of human voices in proximity) | day 1 to day 42 (+/-3 days) | 
| Social activity | - Phone (length of call, last 3 digits of phone number, number known/unknown) | day 1 to day 42 (+/-3 days) | 
| Social activity | - SMS (amount of characters, last 3 digits of phone number, number known/unknown) | day 1 to day 42 (+/-3 days) | 
| Social activity | - App usage (categories of apps, start time, running in background/foreground) | day 1 to day 42 (+/-3 days) | 
| Social activity | - Light sensor (lm) | day 1 to day 42 (+/-3 days) | 
| Physical activity | - Acceleration | day 1 to day 42 (+/-3 days) | 
| Physical activity | - Gyroscope | day 1 to day 42 (+/-3 days) | 
| Physical activity | - Magnetic field | day 1 to day 42 (+/-3 days) | 
| Physical activity | - Step count | day 1 to day 42 (+/-3 days) | 
| Physical activity | - Google Places | day 1 to day 42 (+/-3 days) | 
| Physical activity | - Relative location | day 1 to day 42 (+/-3 days) | 
| Biometric data collected using the Withings Health platform: | Withings Steel HR smartwatch - Sleep pattern (time of sleep, sleep phases) | day 1 to day 42 (+/-3 days) | 
| Biometric data collected using the Withings Health platform: | Withings Steel HR smartwatch -Heart rate data | day 1 to day 42 (+/-3 days) | 
| Biometric data collected using the Withings Health platform: | Withings Steel HR smartwatch -Physical activity (steps, walking distance) | day 1 to day 42 (+/-3 days) | 
| Withings Body+ scale | Weight (kg) | day 1 to day 42 (+/-3 days) | 
| Withings Body+ scale | Body composition (%) | day 1 to day 42 (+/-3 days) | 
| Withings Blood Pressure Monitor | Systolic blood pressure (mmHg) | day 1 to day 42 (+/-3 days) | 
| Withings Blood Pressure Monitor | Diastolic blood pressure (mmHg) | day 1 to day 42 (+/-3 days) | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Facioscapulohumeral muscular dystrophy, Biotyping