PREdictive Risk Factors of Conversion Into Idiopathic RBD. Italian Study

Study Overview
=================
Brief Summary
-----------------
REM Sleep Behavior Disorder (RBD) is a REM sleep parasomnia first described in 1986 and characterized by the loss of physiological muscle atonia typical of REM sleep and by the presence of abnormal, sometimes violent, motor activity often related to dream content The observed motor behaviors are often associated to vivid dreams, characterized by an aggressive-defensive content, even if pleasant dreams have been described, resulting in non-violent behaviors. Diagnosis of RBD requires video-polysomnographic recording (vPSG) at a Sleep Center, essential to identify and quantify the complete or intermittent loss of physiological muscle atonia during REM sleep (REM sleep without atonia, RSWA) and record any related motor behaviors. The exact prevalence of RBD in the general population is not known and it seems underrated, but is estimated to be 0.3-1.15%. RBD is defined as idiopathic or isolated (iRBD) when it is not associated with other neurological diseases. The so-called symptomatic RBD, on the other hand, can occur in association with neurodegenerative diseases of the spectrum of alpha-synucleinopathies which include Parkinson's Disease (PD), Multiple System Atrophy (AMS), and Lewy Body Dementia (DLB). In recent years, several follow-up studies on large cohorts of iRBD patients have shown that the idiopathic form evolves towards a symptomatic form in most cases. More precisely, the risk of developing an alpha-synucleinopathies increases over time, with a conversion rate of up to 90% in some studies at 14 years. RBD represents an early marker of neurodegeneration, like a unique open window on the initial, pre-symptomatic phase of alpha-synucleinopathies, which could allow the use of neuroprotective therapies, as soon as they are available. Several longitudinal studies indicated older age, presence of hyposmia, abnormal color vision, minimal extrapyramidal motor signs, mild cognitive impairment, autonomic disturbances, and severity of loss of RSWA as risk factors for neurodegeneration. However, most studies investigated biomarkers separately, with retrospective study designs, in small cohorts or without a rigorous harmonization between centers in the case of multicenter studies. To date, however, there is no reliable pool of biomarkers that predict the phenoconversion into α-synucleinopathy, the timing in which this can occur, and the phenotype of α-synucleinopathy. Furthermore, despite clinical and research evidence suggesting that iRBD is a heterogeneous disorder little attention was paid to different iRBD phenotypes and currently, there are no relevant data on the impact of iRBD on quality of life. Actually, through neural network analysis approaches, it is possible to find out complex correlations between data from different sources (i.e., clinical examinations, questionnaires, biological data, imaging and neurophysiological techniques, etc.) and to identify subgroups of patients sharing the same substantial characteristics. Identifying different iRBD phenotypes through established as well as innovative biomarkers and standardized measures of wellbeing is crucial to better understanding alpha-synucleinopathies, developing targeted interventions, and reducing the disease burden. To this aim, clinical, biological, neurophysiological, neuropsychological and imaging biomarkers need to be prospectively collected, according to standardized and harmonized procedures. This would significantly increase our understanding of the physiopathological processes of alpha-synucleinopathy from the prodromal phase. Indeed, identifying phenotype clusters with both consolidated and innovative biomarkers may lay the groundwork for a reliable characterization of iRBD patients, likely providing the basis for an efficient stratification of patients longitudinally followed. Several disease-modifying therapies are now in development, including but not limited to monoclonal antibodies against alpha-synucleinopathy. Prodromal synucleinopathy patients, such as those with iRBD, are the ideal target to test disease-modifying therapies because the neurodegeneration is still in an early stage and the likelihood to rescue both brain structures and function is higher. The last aim of the FarPResto study is to have a trial-ready cohort of iRBD patients, collected with standardized and harmonized procedures, to be enrolled in upcoming disease-modifying trials. The FARPRESTO project is endorsed by the Italian Association of Sleep Medicine (AIMS) and by The RBD_Patients society (www.sonnomed.it)

Official Title
-----------------
Redictive Risk Factors of Conversion Into Idiopathic RBD. Italian Study [FAttori di Rischio PREdittivi di Conversione Nell'RBD Idiopatico. STudio ItalianO

Conditions
-----------------
REM Sleep Behavior Disorder

Participation Criteria
=================
Eligibility Criteria
-----------------
Inclusion Criteria: Age: major of 18 years old iRBD diagnosis, according to diagnostic criteria of the ICSD second and third edition Exclusion Criteria: Impossibility to provide or withdraw informed consent and inability to read, write and understand the purpose and modality of the study.

Ages Eligible for Study
-----------------
Minimum Age: 18 Years

Sexes Eligible for Study
-----------------
All

Accepts Healthy Volunteers
-----------------
No

Study Plan
=================
How is the study designed?
-----------------
What is the study measuring?
-----------------
Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Identification of predictive risk factors of phenoconversion in patients with iRBD | In order to increase our understanding on the physiopathological processes of alpha-synucleinopathy from the prodromal phase clinical, biological, neurophysiological, neuropsychological and imaging biomarkers need to be prospectively collected, according to standardized and harmonized procedures. Moreover, identifying phenotype clusters with both consolidated and innovative biomakers may lay the groundwork for a reliable characterization of iRBD patients, likely providing the basis for an efficient stratification of patients to be longitudinally followed. | May 25, 2020 - January 31, 2035 | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Description of the socio-demographic and clinical characteristics of patients diagnosed with iRBD | Data on socio-demographic and clinical characteristics of patients diagnosed with iRBD will be collected and analyzed. | May 25, 2020 - January 31, 2035 | 
| Collection of longitudinal data about the development of alpha-synucleinopathies and estimation of the conversion rate at 3, 5, 7, and 10 years | Information about the conversion rate at 3, 5, 7, and 10 years to neurodegenerative pathologies of the spectrum of alpha-synucleinopathies (Parkinson's Disease, Multiple System Atrophy and Lewy Body Dementia) will be collected and evaluated. | May 25, 2020 - January 31, 2035 | 
| Evaluation of the impact of iRBD on the quality of life and sleep | The impact of iRBD on the quality of life and sleep will be assessed through the administration of validated questionnaires. | May 25, 2020 - January 31, 2035 | 
| Assessment of the correlation between phenoconversion, cognitive performance and loss of normal muscle atony during REM sleep | The results of cognitive performance tests, video-polysomnographic recording and their connection with phenoconversion will be investigated | May 25, 2020 - January 31, 2035 | 
| Identification of RBD phenotypes through different biomarkers | RBD phenotypes will be identified evaluating clinical, biological,neurophysiological, neuropsychological and imaging biomarkers. | May 25, 2020 - January 31, 2035 | 
| Validation of vPSG criteria for RBD diagnosis | vPSG criteria for RBD diagnosis will be validated | May 25, 2020 - January 31, 2035 | 

 Terms related to the study
=================
Keywords Provided by Centre Hospitalier Valida
-----------------
atonia, neurodegeneration