Yes, there’s a lot of biomarkers related to neurodegeneration used in RBD, in particular those related to alpha-synuclein-related neurodegeneration, which are more relevant for Parkinson’s disease, dementia with Lewy bodies mainly, or autonomic markers. And so more classical biomarkers that have been used for several years include cognition, neurophysiological markers, olfactory disturbances...
Yes, there’s a lot of biomarkers related to neurodegeneration used in RBD, in particular those related to alpha-synuclein-related neurodegeneration, which are more relevant for Parkinson’s disease, dementia with Lewy bodies mainly, or autonomic markers. And so more classical biomarkers that have been used for several years include cognition, neurophysiological markers, olfactory disturbances. And there are a lot of new markers being developed lately using, for example, wearable devices or applying advanced artificial intelligence methods, machine learning to any kind of different biomarkers that you can imagine, not only the wearable ones, but also like polysomnography and other biomarkers that have been used in the past, but have now been revisited in a new way using artificial intelligence. There is probably some, there is for sure some clinical utility in them, but at the moment, actually, they are used more in the research field. We know that some of them can, for example, indicate that patients are at higher risk of phenoconverting to overt neurodegeneration in a shorter term, or they can suggest if patients are going to develop Parkinson’s disease or dementia. But this works in a research project on a group level. It’s difficult still to apply this information for the single patient, in clinical practice, to use this information to tell a single patient which is exactly his or her risk to go on into neurodegeneration in the next one or three years, for example.
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