Mitchell Miglis, MD, Stanford University, Palo Alto, CA, discusses a project that focuses on identifying biomarkers in isolated REM sleep behavior disorder (iRBD). The relevance of iRBD as early phase α-synucleinopathy has become increasingly evident in the last few years, providing the rationale for the development of reliable biomarkers that may allow for improved monitoring of the development of α-synucleinopathies. Dr Miglis first talks on iRBD as a strong predictor for the development of diseases such as Parkinson’s, Lewy Body Dementia (LBD), and multiple system atrophy (MSA). Dr Miglis then explains how challenging it is to assemble biomarkers due to their different roles and how they may progress differently over time, making it difficult to quantify which ones are the most appropriate to monitor. To conclude, Dr Miglis highlights some of the future goals in biomarker detection, including the aim of the NAPS study (NCT03623672) and the need to improve methods of identifying biomarkers from easily obtainable samples. This interview took place during the World Sleep Congress 2022 in Rome, Italy.
Transcript (edited for clarity)
So this publication project was a very exciting collaboration with members of the international RBD study group from all around the world and specifically a biomarker section of that study group. And we know in sleep and in neurology that isolated RBD meaning RBD without other signs of manifest neurodegenerative disease is a very strong predictor of developing these neurodegenerative diseases over time, sometimes decades in the future...
So this publication project was a very exciting collaboration with members of the international RBD study group from all around the world and specifically a biomarker section of that study group. And we know in sleep and in neurology that isolated RBD meaning RBD without other signs of manifest neurodegenerative disease is a very strong predictor of developing these neurodegenerative diseases over time, sometimes decades in the future. So it’s a very powerful window into the future, and it gives an opportunity to employ disease modifying treatments, to possibly slow or prevent the progression of these diseases. You know, of course like Parkinson’s, Lewy body dementia, multiple system atrophy, but the challenge is we don’t really understand which markers to follow, which biomarkers that actually predict the speed of conversion to the manifest disease. So this publication was one attempt to sort of quantify the biomarkers we know, and hopefully define those for future drug trials.
And I just want to mention that this is not specifically my work. This is the work of many, many accomplished researchers, more accomplished than myself that have devoted much of their careers to this. And there have been many other publications on this as well, but I think what we realized in trying to assemble all of these biomarkers, it’s not as simple as originally thought. It’s very complex. The biomarkers have different roles, potentially. Some may be more helpful in diagnosis. Others may be more helpful in prognosis. Then others might be more useful when combined with other biomarkers. So this concept of like multimodal or combined biomarkers is probably the way of the future to think about these.
For instance, if we do imaging with dopamine DaTscan imaging, that’s more powerful when combined with say cognitive testing or smell testing. Some biomarkers like smell loss, they appear very early, but then they don’t seem to progress over time. So it doesn’t really help in the prognosis. Whereas some biomarkers like motor function appear later in the disease and very close to that time of conversion. So those are more helpful in predicting sort of the proximity to conversion. So trying to quantify all this and create a grading scale, that’s the next project. And I know that’s something that the North American prodromal study, the NAPS study’s interested in creating sort of rating scale that kind of quantifies these different types of markers. I think the challenges and we try to get at this in the review article is identifying biomarkers that are available that are not too expensive, so they can be widely employed, but also of course, very sensitive and specific.
And I think the future will be trying to analyze these markers in very easily obtainable samples, like blood sample. They can do spinal fluid analysis or RT-QuIC. And this is very exciting, but it’s not so easy to do one more puncture on everybody. So either blood sampling, skin biopsy, salivary sampling, very minimally invasive things. I think that’s really the future. And being able to demonstrate that these markers change over time and they track with the disease. So if we enroll patients in a trial, if we give them disease modifying agent, we can repeat the biomarker and demonstrate the efficacy of the drug using these potential tissue analyses.