Projects Funded - Diagnostic Biomarkers

IMPROVING METHODS FOR BETTER DIAGNOSIS - "BIOMARKERS"

Presently, multiple system atrophy is a clinical diagnosis, determined largely by verifying a constellation of symptoms and excluding other illnesses. Definite diagnosis is only possible after death by means of brain autopsy. The current inability to diagnose MSA accurately has severely hampered previous clinical trials of potential disease modifying drugs in MSA patients, a problem shared with Parkinson’s, Alzheimer’s, and other neurodegenerative diseases. Specific biomarkers such as blood or spinal fluid tests and brain imaging studies are needed, both to positively diagnose the illness and to monitor and understand the impact of potential therapeutic treatments.

A $10 million investment is required to develop diagnostic biomarkers and refine imaging methodologies.

To date, the MSA Coalition has invested $325,000 in 7 diagnostic biomarker projects including grants given to develop tests that might detect MSA from blood, skin or cerebrospinal fluid (CSF) samples. In addition, the MSA Coalition supported a project aimed at developing sophisticated MRI methods to diagnose MSA with greater accuracy and a clinical biomarker study utilizing wearable sensors to determine measurable changes in balance and gait between MSA and similar atypical parkinsonian disorders.

Although we currently can only invest a small amount towards this line of research, The MSA Coalition is proud of the work we have inspired. Several groundbreaking articles have been published in highly prestigious medical journals like Movement Disorders, Brain and Nature. There has also been news media coverage and our funded researchers have been given awards for excellence.

Learn more about the status of our biomarker projects by exploring the links below.

 

**AWARD WINNING** “Defining diagnostic brain MRI markers in early MSA with a novel toolbox”: Florian Krismer, MD, PhD (Innsbruck Medical University, Austria)

MSA Coalition Grant #2015-04-003 – $50,000

Multiple system atrophy (MSA) is a rare and devastating neurological condition. There is currently no therapy that can halt or slow the progression of the disease. Clinical trials with a large number of patients are required to test the efficacy of candidate agents. One of the prerequisites of clinical trials is that the patients enrolled in them should be as homogeneous as possible. In addition, potential treatments should be applied as early as possible. Hence, an early and reliable diagnosis of MSA is critical. However, it is difficult to discriminate different parkinsonian disorders at very early disease stages on clinical symptoms only. Thus, for the purpose of patient counseling and clinical research, additional investigations are inevitable.

Based on emerging findings in favor of specific sequences of brain magnetic resonance imaging (MRI) as early diagnostic markers of MSA pathology, we propose to develop a MRI toolbox that consistently separates MSA from other degenerative parkinsonian disorders.

AWARDS

1. October 3, 2020: Dr. Florian Krismer was bestowed with the JiePie Award for research for this work.

2. February 2020: Dr. Florian Krismer was bestowed with the Parkinsong Award for this research. Below is the winning abstract.

“Morphometric MRI Profiles of Multiple System Atrophy Variants and Implications for Differential Diagnosis” – Florian Krismer, MD, PhD, et al

Manual width measurements of the middle cerebellar peduncle on MRI were shown to improve the accuracy of an imaging‐guided diagnosis of multiple system atrophy (MSA). Recently, automated volume segmentation algorithms were able to reliably differentiate patients with Parkinson’s disease (PD) and the parkinsonian variant of MSA. The objective of the current study was to integrate probabilistic information of the middle cerebellar peduncle into an existing MRI atlas for automated subcortical segmentation and to evaluate the diagnostic properties of the novel atlas for the differential diagnosis of MSA (parkinsonian and cerebellar variant) versus PD.
Three Tesla MRI scans of 48 healthy individuals were used to establish an automated whole‐brain segmentation procedure that includes the volumes of the putamen, cerebellar gray and white matter, and the middle cerebellar peduncles.
Classification accuracy of segmented volumes were tested in early‐stage MSA patients (18 MSA‐parkinsonism, 13 MSA‐cerebellar) and 19 PD patients using a C4.5 classifier.
Putaminal and infratentorial atrophy were present in 77.8% and 61.1% of MSA‐parkinsonian patients, respectively. Four of 18 MSA‐parkinsonian patients (22.2%) had infratentorial atrophy without evidence of putaminal atrophy. Infratentorial atrophy was present in all MSA‐cerebellar patients, with concomitant putaminal atrophy in 46.2% of these cases. The diagnostic algorithm using putaminal and infratentorial volumetric information correctly classified all PD patients and 96.8% of MSA patients.
The middle cerebellar peduncle was successfully integrated into a subcortical segmentation atlas, and its excellent diagnostic accuracy outperformed existing volumetric MRI processing strategies in differentiating MSA patients with variable atrophy patterns from PD patients.

 

PUBLISHED ARTICLES

1. September 2020: Automated Analysis of Diffusion‐Weighted Magnetic Resonance Imaging for the Differential Diagnosis of Multiple System Atrophy from Parkinson’s Disease.

2. March 2019: Morphometric MRI profiles of multiple system atrophy variants and implications for differential diagnosis.

3. December 2018: The diagnostic accuracy of the hummingbird and morning glory sign in patients with neurodegenerative parkinsonism

4. August 2018:Abnormalities on structural MRI associate with faster disease progression in multiple system atrophy

5. January 2018: MR planimetry in neurodegenerative parkinsonism yields high diagnostic accuracy for PSP

6. December 2017: Diffusion-weighted MRI distinguishes Parkinson disease from the parkinsonian variant of multiple system atrophy: A systematic review and meta-analysis

 

REPORTS

1. Final report by Florian Krismer (April 2021)

Summary of the Work Programme

In the MRI-Innsbruck-New York (MINY) project, we proposed to study the diagnostic accuracy of MRI-based biomarkers of MSA. To this end, we suggested to screen a predefined set of MRI alterations and validate the most promising MRI markers in an independent cohort of “de novo” patients with parkinsonism.

In a first step, we exploited the Innsbruck MRI database that includes 75 MSA patients, 249 PD patients and 72 PSP patients to screen for reliable planimetric measures in T1-weighted images. One of the predefined goals was to find a MR measure that does not require advanced MRI analysis methods, i.e. finding a MRI measure that neurologists/neuroradiologists can assess manually through their regular image viewer software. The results of this study were published in Parkinsonism and Related Disorders (Mangesius et al., Parkinsonism Relat Disord. 2018;46:47-55. doi: 10.1016/j.parkreldis.2017). In summary, while we were able to discriminate PSP from MSA and PD with high diagnostic accuracy, the diagnostic accuracy of manual MR planimetry in separating MSA-P and PD was suboptimal. Despite the lack of accuracy, we were still able to demonstrate that planimetric measurements and visual inspections of MRI have a significant impact for patient counselling and the planning of future clinical trials as shown in a post-hoc analysis of the MSA-RAS (“Rasagiline for MSA”) trial. The post-hoc analysis suggests that abnormalities on MRI associate with faster disease progression in MSA patients (Krismer et al., Parkinsonism Relat Disord. 2018; epub ahead of print, doi: 10.1016/j.parkreldis.2018.08.004)

However, to achieve our initial goal, we were looking at two fallback strategies to improve the accuracy of an MRI-assisted diagnosis of MSA. (1) we performed a meta-analysis assessing the diagnostic utility of diffusion-weighted imaging (DWI). Our results suggest that DWI is helpful in separating MSA from related disorders with changes in putaminal diffusivity yielding an excellent sensitivity and specificity to distinguish clinically diagnosed patients with MSA-P from PD. The results of this study were recently published in PloS ONE (Bajaj et al., PLoS ONE 12(12): e0189897. doi: 10.1371/journal.pone.0189897). Overall, this study recommends the use of DWI for the differential diagnosis of MSA by providing level 1a evidence of its usefulness (cf. http://www.cebm.net/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/). (2) A project that we are still actively pursuing deals with automated brain segmentation/volumetry. Our group had previously described a method that reliably separated MSA, PD and PSP in mild-to-moderate disease stages through automated, volumetric analysis of T1-weighted MR images (Scherfler et al. 2016, Neurology 29;86(13):1242-9). Over the past 18 months, we refined this methodology and developed a MSA-specific segmentation atlas that focuses on brain regions known to be heavily affected by MSA pathology. A report describing the methodology and the results of the pilot study were published in the Movement Disorders Journal (Krismer et al. 2019, Mov Disord. 2019 Jul;34(7):1041-1048. doi: 10.1002/mds.27669). We are currently validating this newly developed diagnostic algorithm in an independent cohort (“New York” cohort) of patients that underwent MRI at very early disease stages when they were diagnosed of having clinically unclassifiable parkinsonism (i.e. suffering from parkinsonism but not fulfilling any diagnostic criteria yet). These patients were then followed for several years to ascertain their clinical diagnosis (i.e. assign them to one of the following diagnostic categories: MSA, PD and PSP). We expect to finish this analysis soon and will publish an additional joint publication with the team from New York University. Furthermore, we were able to develop an automated analysis stream to analyze anatomical and diffusion-weighted imaging sequences in parallel. The results of this study were published in Movement Disorders (Krismer et al. 2021, Mov. Disord. 2021; 36(1):241-245. doi: 10.1002/mds.28281).

 

Technical Summary / Key figures

Publications:

  • Mangesius et al., Parkinsonism Relat Disord. 2018;46:47-55. doi: 10.1016/j.parkreldis.2017
  • Mueller et al., Parkinsonism Relat Disord. 2018;54:90-94. doi: 10.1016/j.parkreldis.2018.04.005.
  • Krismer et al., Parkinsonism Relat Disord. 2019 Jan;58:23-27. doi: 10.1016/j.parkreldis.2018.08.004
  • Bajaj et al., PLoS ONE 12(12): e0189897. doi: 10.1371/journal.pone.0189897
  • Krismer et al., Movement Disorders Journal 2019;34(7):1041-1048. doi: 10.1002/mds.27669.
  • Krismer et al., Movement Disorders Journal 2021; 36(1):241-245. doi: 10.1002/mds.28281

 

Development of human resources

The scientific work of this project forms the foundation for two PhD theses at the Medical University Innsbruck. One PhD student with a medical background has already completed her PhD; a second PhD student is at the brink of finishing her PhD. The PhD students were responsible for analysing the brain MRI (after thorough introduction on how to perform the image analysis). In addition, we were able to recruit and fund a young PostDoc experienced in post-processing of brain MRI to develop advanced MRI analysis algorithms. Overall, this project was an important step towards an academic career at the Medical University of Innsbruck and the New York University for those involved.

Contribution to the advancement of the field (e.g. did the results contribute to increasing the importance of the field? In what way?)

The dissemination of (preliminary) study results by journal publications and poster presentations at expert conferences mounted a lively discussion on the significance of imaging in the differential diagnosis of neurodegenerative parkinsonian disorders. In fact, a working group of the International Parkinson’s disease and Movement Disorders society-endorsed MSA study group is about to conclude a systematic review on the diagnostic yield of different ancillary investigations and this review includes a dedicated chapter on imaging (Pellecchia et al., in preparation).

 

Information on the execution of the project:

Duration:

Q2, 2015 – Q1, 2021. We applied for cost-neutral extensions of the project duration due to initial difficulties in recruiting qualified PhD students and a delayed start of data analysis as well as delays in contract negotiations between the two Universities).

 

Use of personnel:

Two PhD students with a medical background and PostDoc were partially funded through the present project. The PhD students/Postdoc were responsible for MRI analyses.

Major items of equipment purchased:

None

Other significant deviations:

None

2. Research update by Florian Krismer (August 2018)

In the MRI-Innsbruck-New York (MINY) project, we proposed to study the diagnostic accuracy of MRI-based biomarkers of MSA. To this end, we suggested to screen a predefined set of MRI alterations and validate the most promising MRI markers in an independent cohort of “de novo” patients with parkinsonism.

In a first step, we exploited the Innsbruck MRI database that includes 75 MSA patients, 249 PD patients and 72 PSP patients to screen for reliable planimetric measures in T1-weighted images. One of the predefined goals was to find a MR measure that does not require advanced MRI analysis methods, i.e. finding a MRI measure that neurologists/neuroradiologists can assess manually through their regular image viewer software. The results of this study were published in Parkinsonism and Related Disorders (Mangesius et al., Parkinsonism Relat Disord. 2018;46:47-55. doi: 10.1016/j.parkreldis.2017). In summary, while we were able to discriminate PSP from MSA and PD with high diagnostic accuracy, the diagnostic accuracy of manual MR planimetry in separating MSA-P and PD was suboptimal. Despite the lack of accuracy, we were still able to demonstrate that planimetric measurements and visual inspections of MRI have a significant impact for patient counselling and the planning of future clinical trials as shown in a post-hoc analysis of the MSA-RAS (“Rasagiline for MSA”) trial. The post-hoc analysis suggests that abnormalities on MRI associate with faster disease progression in MSA patients (Krismer et al., Parkinsonism Relat Disord. 2018; epub ahead of print, doi: 10.1016/j.parkreldis.2018.08.004)

However, to achieve our initial goal, we were looking at two fallback strategies to improve the accuracy of an MRI-assisted diagnosis of MSA. (1) we performed a meta-analysis assessing the diagnostic utility of diffusion-weighted imaging (DWI). Our results suggest that DWI is helpful in separating MSA from related disorders with changes in putaminal diffusivity yielding an excellent sensitivity and specificity to distinguish clinically diagnosed patients with MSA-P from PD. The results of this study were recently published in PloS ONE (Bajaj et al., PLoS ONE 12(12): e0189897. doi: 10.1371/journal.pone.0189897). Overall, this study recommends the use of DWI for the differential diagnosis of MSA by providing level 1a evidence of its usefulness (cf. http://www.cebm.net/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/). (2) A project that we are still actively pursuing deals with automated brain segmentation/volumetry. Our group had previously described a method that reliably separated MSA, PD and PSP in mild-to-moderate disease stages through automated, volumetric analysis of T1-weighted MR images (Scherfler et al. 2016, Neurology 29;86(13):1242-9). Over the past 18 months, we refined this methodology and developed a MSA-specific segmentation atlas that focuses on brain regions known to be heavily affected by MSA pathology. A report describing the methodology and the results of the pilot study were recently submitted to the Movement Disorders Journal and the results will also be presented at the International Parkinson’s disease and Movement Disorders Congress later this year. We are currently validating this newly developed diagnostic algorithm in two independent cohorts (an Innsbruck and a New York cohort) of patients that underwent MRI at very early disease stages when they were diagnosed of having clinically unclassifiable parkinsonism (i.e. suffering from parkinsonism but not fulfilling any diagnostic criteria yet). These patients were then followed for several years to ascertain their clinical diagnosis (i.e. assign them to one of the following diagnostic categories: MSA, PD and PSP). We expect to finish this analysis over the course of the next year. Hence, we propose a cost-neutral one year extension of the project. The remaining funds will be used to fund a part-time employee who is already trained in imaging analysis.

Summary / Key figures

Publications (until August 2018):

  • Mangesius et al., Parkinsonism Relat Disord. 2018;46:47-55. doi: 10.1016/j.parkreldis.2017
  • Krismer et al., Parkinsonism Relat Disord. 2018; epub ahead of print, doi: 10.1016/j.parkreldis.2018.08.004
  • Bajaj et al., PLoS ONE 12(12): e0189897. doi: 10.1371/journal.pone.0189897
  • Krismer et al., Movement Disorders Journal, submitted.

Development of human resources

The scientific work of this project forms the basis for two Ph.D. theses.

3. Research Update by Florian Krismer (September 2017)

In the MRI-Innsbruck-New York project, we proposed to study the diagnostic accuracy of R-based biomarkers of MSA. To this end, we suggested to screen a predefined set of MRI alterations and validate the most promising MRI markers in an independent cohort of “de novo” patients with parkinsonism.

In a first step, we exploited the Innsbruck MRI database that includes 75 MSA patients, 249 PD patients and 72 PSP patients to screen for reliable planimetric measures in T1-weighted images. One of the predefined goals was to find a MR measure that does not require advanced MRI analysis methods, i.e. finding a MRI measure that neurologists/neuroradiologists can assess manually through their regular image viewer software. The results of this study are currently under revision at Parkinsonism and Related Disorders. In summary, while we were able to discriminate PSP from MSA and PD with a high diagnostic accuracy, the diagnostic accuracy of manual MR planimetry in separating MSA-P and PD was suboptimal.

Given this lack of accuracy, we are currently pursuing two additional projects that – we believe – will significantly advance the field:

(1) our group has previously described a method that reliably separated MSA, PD and PSP in mild-to-moderate disease stages through automated, volumetric analysis of T1-weighted MR images (Scherfler et al. 2016, Neurology 29;86(13):1242-9). We are currently validating this diagnostic algorithm in two independent cohorts (an Innsbruck and a New York cohort) of patients that underwent MRI at very early disease stages when they were diagnosed of having clinically unclassifiable parkinsonism (i.e. suffering from parkinsonism but not fulfilling any diagnostic criteria yet). These patients were then followed for a several years to ascertain their clinical diagnosis (assign them to one of the following diagnostic categories: MSA, PD and PSP). We expect to finish the analysis later this year.

(2) Several previous studies assessed the diagnostic utility of diffusion-weighted imaging (DWI) suggesting that DWI may be helpful in separating MSA from related disorders. We recently completed a systematic literature search and performed a meta-analysis. We were able to demonstrate that putaminal diffusivity yields excellent sensitivity and specificity to distinguish clinically diagnosed patients with MSA-P from PD. This study recommends the use of DWI for the differential diagnosis of MSA by providing level 1a evidence of its usefulness (cf. http://www.cebm.net/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/). The results of this study are currently under peer review at PLoS ONE.

 

**UPDATED RESULTS** “Inside the gait – a new era on the horizon for atypical parkinsonian disorders”: Gregor K. Wenning, MD, PhD (Medical University of Innsbruck, Austria)

MSA Coalition Grant #2016-09-008 – $50,000

Multiple system atrophy (MSA) and Progressive Supranuclear Palsy (PSP) are rare and devastating neurological conditions. There is currently no therapy that can halt or slow the progression of these diseases. Clinical trials with a large number of patients are urgently needed to test the efficacy of therapeutic agents. In addition, an early and reliable diagnosis of MSA and PSP and the discrimination of these diseases from the more benign idiopathic Parkinson’s disease can be a challenge for the neurologist, especially at early stages.

Emerging data show that instrumented gait analysis using wearable sensors can provide a great amount of clinically relevant information which could help to better characterize these diseases and to quantify their progression characteristics and rates in an objective, rater-independent way. Moreover, new findings show that these sensors may be able to detect risk-of-fall associated gait parameters. This is particularly relevant in the clinical assessment and in the follow-up of patients with atypical parkinsonian disorders where the gait impairment and the risk of fall are even more prominent compared to idiopathic Parkinson’s disease.

Based on emerging findings in favor of the feasibility of wearable sensors in the clinical practice, we aim to propose a new objective tool in the diagnostic workup, individualized progression assessment, and therapeutic response of atypical parkinsonian disorder patients.

RESULTS

A research grant from the MSA Coalition helped support this trial, the results of which show that “physiotherapy is feasible, safe and improves gait performance in patients with multiple system atrophy”.

 

We are happy to be able to share this link with permission from the research team where you may download the exercises that proved helpful. Please feel free to share this protocol with your own physical therapists.

2. Presentation (June 2019): The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism

3. Published Article (May 2019): Gait and postural disorders in parkinsonism: a clinical approach

4. Published Article (January 2019): The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations

5. Published Article (June 2018): Sensor-based gait analysis in atypical parkinsonian disorders.

6. Conclusions and Outlook (View Full Final Report – December 2018)

Our study addressed the primary research question whether MSA patients can benefit from a standardized physiotherapy based on guidelines for PD. Additionally, the study aimed to investigate whether physiotherapy effects are sustainable. The most important clinically relevant finding was that gait of MSA patients is improving after an intensive in-hospital in-patient physiotherapy program. Thinking further, this finding after such a short treatment duration is even surprising in relation to the motor impairment of MSA patients. Still, most of these therapeutic effects were not significantly worsening after a low-dose unsupervised in-home training program. However, our data indicate a
tendency not to maintain the same improvement levels showed after an intensive physiotherapy in-hospital. Therefore, an intensive in-patient in-hospital physiotherapy seems to be a more effective intervention than a low-dose in-home training. There are several possible explanations for this result. Firstly, it may be hypothesized that patients at home without supervision of an expert are not
performing the training program properly. Secondly, it may reflect that patients do not have enough time during the 5-day long in-hospital physiotherapy to learn properly the training program and being able to reproduce it correctly at home. Another possible explanation is the lack of compliance and adherence to the training plan.

The current study was the first-ever assessment of physiotherapy in MSA patients. Further studies are needed to confirm and implement our results. For patients with PD, there is strong evidence that the introduction of an activity coach in the intervention plan, who guides patients towards a more active lifestyle through periodic coaching sessions enhances patients´ motivation and promotes
physical activity [15]. Therefore, an activity coach may educate patients about the benefits and the importance of physical activity, may help to overcome any perceived barriers to engaging in physical activity and set systemic goals, therefore improving patients´ motivation, well-being and levels of independence.

 

**AWARD WINNING** “Biomarker Development in MSA”: Roy Freeman, MD (Beth Israel Deaconess Medical Center MA)

MSA Coalition Grant #2013-12-005 – $25,000

There is currently an unmet need for a biomarker in Multiple System Atrophy. A reliable biomarker could contribute to the diagnosis, treatment and disease modification of MSA by improving diagnostic accuracy, defining disease progression and providing an objective measure of the response to disease modifying interventions. Successful development of a biomarker for MSA would therefore assist in the evaluation and enhance the efficacy of drugs or other interventions that have neuroprotective qualities and offer the possibility of slowing, halting or reversing the rapid progression of MSA. This study in human subjects, will determine whether alpha-synuclein deposits in cutaneous autonomic nerves is a valid biomarker for multiple system atrophy.

RESULTS

1. May 2019: MSA Coalition Funded Research Honored as “Abstract of Distinction” at the American Academy of Neurology Annual Meeting.

The abstract entitled “Cutaneous Alpha-Synuclein Deposition in Multiple System Atrophy” has been identified as a 2019 Abstract of Distinction by the American Academy of Neurology at this year’s Annual Meeting. The Abstracts of Distinction program recognizes the top scientific achievement in each abstract topic area and is awarded to only a small number of superior abstracts. There are 24 Abstracts of Distinction this year that were carefully selected from the 3000+ abstracts submitted for the 2019 Annual Meeting in Philadelphia, PA.

This MSA Coalition funded work, led by MSA Coalition grantee, Dr. Roy Freeman, MD, Beth Israel Deaconess Medical Center, Boston, MA seeks to fill an unmet need for a biomarker in multiple system atrophy by way of skin sample testing for levels of the protein alpha-synuclein in MSA patients, Parkinson Disease patients, and healthy controls. A reliable biomarker could contribute to the diagnosis, treatment and disease modification of MSA by: (1) improving diagnostic accuracy; (2) increasing cohort homogeneity in clinical trails; (3) promoting early diagnosis, ideally in the pre-motor state; (4) defining disease progression and (5) providing an objective measure of the response to disease modifying interventions. Successful development of a biomarker for MSA would assist in the evaluation and enhance the efficacy of drugs or other interventions that have neuroprotective qualities and offer the possibility of slowing, halting or reversing the rapid progression of MSA.

2. NIH Grant (July 2016): Dr. Roy Freeman obtained a grant from NIH ($252,643) to continue this study

3. BIDMC Newsletter article (Summer 2014): Below the surface

 

**UPDATED RESULTS** “Detection of pathological alpha-synuclein aggregates in CSF by qRT-QuIC”: Armin Giese, MD (Ludwig-Maximilians-University, Munich, Germany)

MSA Coalition Grant #2015-04-005 – $48,190

Reliable molecular biomarkers for early diagnosis and monitoring the disease progression in MSA are urgently needed, but are lacking to date. Deposits of aggregated alpha-synuclein (aSyn) are the pathological hallmark of MSA. However, reliable tools for the quantification of pathological aSyn in body fluids such as cerebrospinal fluid (CSF) are currently missing. We have established a rapid and reliable tool, qRT-QuIC (quantitative real-time quaking-induced conversion), to be able to sensitively and specifically detect and quantify even minute amounts of pathological protein aggregates, which we now want to apply to CSF samples of MSA patients.

PROJECT DESCRIPTION

(1) We will optimize the existing assay to detect pathological aSyn aggregates with high accuracy: This requires the adjustment of the assay conditions and its subsequent testing using recombinant and brain derived pathological aggregates as seeds.

(2) In a second step, validation of the assay will be carried out by analyzing patient CSF-samples from MSA patients (n=50), PD patients (n=50), and controls (n=100) including an independent cohort validation.

(3) Finally, we will further standardize and automate the assay resulting in a routine method for clinical diagnostics.

ANTICIPATED OUTCOME

The results of this study will be of crucial importance to find a reliable biomarker for MSA. If successful, this method would allow for precise early diagnosis and could be a powerful tool to track disease progression and to monitor therapeutic effects of novel therapeutics in MSA as well as in other synucleinopathies.

RESULTS

1. Published article (May 2020): Potential sources of interference with the highly sensitive detection and quantification of alpha‐synuclein seeds by qRT‐QuIC

2. Research update by Armin Giese (December 2015):

With financial support of the MSA Coalition grant, we were able to purchase the necessary hardware, a BMG FLUOstar Omega multiwell plate reader, for establishing qRT-QuIC for the detection of alpha-synuclein aggregation. Primary instrument settings were adjusted and quality controls were carefully performed. Recombinant monomeric alpha-synuclein, which is used as a substrate for the seeding reaction, was purified and fibrils, to be used as recombinant seeds were generated according to our standard protocol. We tested different combinations of conditions regarding buffer composition, pH of the reaction, and incubation temperature. We checked for potential differences using sonicated or non-sonicated as well as centrifuged or non-centrifuged seeds. Furthermore we checked, whether different badges of purified substrate lead to different characteristics of the aggregation process. Based on the results of our analyses, we assume the assay conditions regarding especially its sensitivity to be adequately sufficient for now to move on to analyzing CSF samples. In a first step, the influence of the CSF matrix per se (e. g. blood contamination, cells, other proteins, electrolytes) as well as conditions of sample processing and storage have to be characterized by adding in vitro formed seeds to CSF samples of control patients without neurodegenerative disease (`spiked´ CSF). Subsequently, we will proceed to CSF samples from patients with synucleinopathies and further optimize the assay. The final adaptation of the qRT-QuIC assay for alpha-synuclein seeds will be the result of mutual optimization steps of the assay using purely in vitro components, spiked CSF matrix as well as CSF samples from patients with synucleinopathies. Once we could determine the optimal conditions for the seeding reaction of CSF-derived alpha-synuclein seeds, the assay is to be validated by testing adequate numbers of CSF samples of patients and healthy controls. The final aim will be to further standardize and automatize qRT-QuIC for the application in clinical routine diagnostics.

“A serum miRNAs signature as potential biomarker for MSA”: Annamaria Vallelunga, PhD (University of Salerno, Italy) and Maria Teresa Pellecchia, MD, PhD (University of Salerno, Italy)

MSA Coalition Grant #2016-09-007 – $50,000

At the moment, there is no specific diagnostic test for the early diagnosis of multiple system atrophy (MSA). Moreover, a major challenge in developing effective treatments for MSA is the difficulty to predict how the disease will evolve over time. To overcome these limitations, current research focuses on the development of reliable biomarkers, biological molecules present in bio-fluids and easily measurable in order to reflect disease processes. A new class of molecules called miRNAs has been recently studied in several neurodegenerative diseases. miRNAs are a class of small RNA molecules which modulate gene expression and protein production, and whose levels often change during the disease. Many miRNAs are present in different brain regions, cross the blood-brain barrier and can be detected in several bio-fluids such as blood and urine. miRNAs can be analyzed using simple technology present in the molecular clinical laboratory.

Recently, we ran a pilot study evidencing that a set of miRNAs could distinguish patients with MSA from healthy individuals simply based on blood sample analysis. We also identified a set of three miRNAs that allowed the discrimination between patients with MSA and Parkinson’s disease (PD). We hypothesize that they could facilitate the diagnosis of these conditions.

The overall objective of this proposal is to assess the usefulness of those miRNA panels for the early diagnosis of MSA. The validation of our miRNA panels could be a first step to develop a new test for early diagnosis of MSA based on blood miRNAs. Moreover, the identification of biomarkers that reflect the underlying disease process or progression would also be very useful for designing future clinical trials that assess compounds with putative disease-modifying properties.

RESULTS

1. Presentation (May 2019): A serum miRNAs signature as Potential Biomarker for MSA

2. Published Article (March 2019): Serum miR-30c-5p is a potential biomarker for multiple system atrophy

“Plasma exosomal IRS-1pS312 as biomarker for MSA”: Wassilios Meissner, MD, PhD (University of Bordeaux, France)

MSA Coalition Grant #2017-10-005 – $50,000

No specific diagnostic test is currently available for multiple system atrophy (MSA). It is also difficult to predict how the disease will evolve in each individual patient over time. To overcome these limitations, current research focuses on the development of body fluid biomarkers, i.e. the identification of substances that are easily measurable in the blood or other body fluids and that reflect fundamental disease mechanisms. The hope is that these biomarkers will help to make the right diagnosis more easily and to better predict how the disease will evolve in each individual patient. Doctors expect that these biomarkers will also allow to better measure the efficacy of new treatments in clinical studies.

In a recent experimental study, we have found changes reminiscent of diabetes in brains of deceased MSA patients and mice that mimic some features of MSA. We have further observed in these MSA mice that a drug used for the treatment of diabetes protects neurons and the amount of this protection correlates with a
blood biomarker called IRS-1pS312, which was measured in small blood vesicles called exosomes. Exosomes are released from brain cells and can cross the blood brain barrier. Therefore, the measurement of these vesicles in the blood provides a perfect window to monitor changes in brain activity.

The overall objective of the proposed study is to assess the usefulness of this easily accessible blood biomarker for the diagnosis and prognosis of MSA. This biomarker may also prove helpful for the assessment of the efficacy of antidiabetic drugs in future treatment trials in MSA patients.

RESULTS

1. Research update by Wassilios Meisner (July 2018)

According to the specific aims of the awarded grant, experiments were performed to establish a methodology for isolating oligodendrocyte-derived exosomes from plasma, similar to its methodology for isolating neuron-derived exosomes from plasma. These experiments are ongoing, but have not yet resulted in a definitively valid methodology. In parallel, approvals for shipping samples from Bordeaux and Salerno to the partner in Baltimore were obtained.

“A novel diagnostic test for distinguishing synucleinopathies”: Gal Bitan, PhD (University of California Los Angeles, CA)

MSA Coalition Grant #2017-10-007 – $50,000

Accurate diagnosis of multiple system atrophy (MSA) is difficult because the symptoms overlap with other diseases, such as Parkinson’s disease and ataxia, especially at early stages of the disease. However, the underlying mechanism in the brain of patients with MSA is distinct from those other diseases and if we could get a glimpse into the brain biochemistry, it could be used to accurately diagnose MSA.

We propose to develop a novel method that will allow getting such an insight into specific biochemical brain process that can reveal which disease is affecting a patient. The method is based on isolating miniature vesicles, which are secreted by all the cells in our body, and separating from the entire pool of vesicles only those whose origin is in specific brain cells that are involved in MSA. Then, specific biological molecules (biomarkers) can be measured in these vesicles and distinguish among the different diseases.

We have developed the technical tools necessary to achieve these goals and our initial data show that this strategy allows separating patients with Parkinson’s disease from healthy individuals with high accuracy. Here, we will extend the strategy to patients with MSA and examine its capability to distinguish between MSA and Parkinson’s disease.

Our project holds promise to lead to development of accurate diagnosis of MSA using a simple blood test.

RESULTS

1. Presentation (May 2019): A new blood test distinguishes MSA from Parkinson’s disease

2. Research update by Gal Bitan (May 2018)

Accurate diagnosis of multiple system atrophy (MSA) is difficult because the symptoms overlap with other diseases, such as Parkinson’s disease and ataxia, especially at early stages of the disease. To address this challenge, we proposed to develop a novel method that would allow analyzing specific biochemical brain processes that can reveal which disease is affecting a patient, using a blood test. We have now established the necessary methodology and used it to analyze one specific protein – alpha-synuclein – in two different brain cells, neurons and oligodendrocytes.

We chose to analyze alpha-synuclein in these two cell types because the accumulation of alphasynuclein in them distinguishes Parkinson’s disease from MSA. In Parkinson’s, alpha-synuclein forms abnormal clumps called Lewy bodies inside neurons, whereas similar clumps called GCIs are characteristic of MSA. Detecting these clumps in the brain of living patients currently is impossible. However, our new methodology allows isolating from the blood tiny “nanovesicles” that are secreted by all the cells in our body, then sorting out only those that came from the neurons and oligodendrocytes in the brain, and finally using highly sensitive analytical methods to measure how much alpha-synuclein is in these nanovesicles.

We used this new methodology to compare patients with MSA, patients with Parkinson’s, and age-matched healthy people. Our results show that we can not only separate the MSA patients from the healthy controls with very high accuracy, but also that in 9 out of 10 cases, the test can distinguish between MSA and Parkinson’s. We are now developing additional tests, including a protein called tau, which also forms toxic clumps in Parkinson’s disease and MSA, in order to improve to further improve the diagnostic power.

Our initial data suggest that measuring both alpha-synuclein and tau will increase the accuracy of the method so that in the future, a simple blood test will allow physicians to determine the diagnosis of MSA with high confidence.

Building Hope Through Research


Since 2013, the Multiple System Atrophy Coalition has funded 42 MSA focused research projects for a total of $2 Million.

Explore the links below to learn more about our research goals and the outcomes of our funded projects.

The 42 projects cover four major themes:

We are making an impact!