*NEW STUDY*: Exploring Non-Invasive Imaging Markers for α-Synuclein Pathology

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We are happy to share our recently published article in npj Parkinson’s Disease titled “Radiological markers of CSF α-synuclein aggregation in Parkinson’s disease patients” (link to article). This study investigates the potential of radiological markers to detect cerebrospinal fluid (CSF) α-synuclein (αS) aggregation in Parkinson’s disease (PD) patients.

Recent research has proposed biological staging systems for PD based on αS pathology in the central nervous system (CNS) (1. https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(23)00405-2/fulltext ; 2. https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(23)00404-0/fulltext). While CSF analysis provides valuable insights, its invasive nature limits scalability. Identifying imaging markers associated with αS aggregation could serve as a more accessible and non-invasive screening alternative.

In this study, we employed multi-parametric imaging techniques to identify neuroimaging markers associated with CSF α-synuclein levels in PD patients. Our findings revealed that PD patients with positive CSF αS seeding assays exhibited distinct neuroimaging features, including:

  • Reduced whole-brain grey matter volume.
  • Decreased volumes in the putamen, brainstem, and substantia nigra.
  • Diminished functional connectivity in the left caudate.
  • Lower fractional anisotropy in the left fronto-occipital fasciculus.

These results suggest that these neuroimaging markers may serve as non-invasive indicators of α-synuclein pathology in early-stage PD patients.

This research demonstrates the promise of combining biochemical and imaging modalities to advance our understanding of the multifaceted PD pathology. Such approaches could pave the way for early detection, improved disease monitoring, and more targeted therapeutic interventions.

However, the study does have limitations. Our sample size was relatively small, and as a single-site study, the findings require multi-center validation to ensure generalizability. Despite these limitations, we view them as opportunities for further investigation and collaboration within the scientific community.

Looking forward, our findings hold significant implications for both PD research and clinical practice. The integration of imaging and biochemical markers could enhance early diagnosis and treatment monitoring, potentially providing a non-invasive alternative to CSF sampling for assessing α-synuclein pathology. Future studies should explore whether these radiological markers can track disease progression or evaluate treatment efficacy.

We are eager to engage with colleagues and researchers interested in this field. Your insights, questions, and potential collaborations could drive further advancements in our understanding of PD and improve outcomes for patients. Together, we can work towards developing more effective diagnostic tools and targeted therapies for Parkinson’s disease.

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Thanks for sharing, @AmgadDroby , and congrats on the publication! It’s exciting and important work to approach early-stage disease characterization by combining multi-modal data, particularly when certain methods (i.e., CSF sampling and the required lumbar punctures) can be quite invasive.

I’m curious if other community members with interest in imaging data have any insights or questions regarding this study? @flokri , @mejoh , @LauraJonkman , @marekpiatek , @awiederhold , @rickhelmich , @bmarebwa

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Interesting study @AmgadDroby , thanks for sharing! I agree this is a promising start using multi-modal imaging for disease characterization. It maybe interesting to see if network analysis (eg. PDCP/RP), more sensitive diffusion measures eg. FW, or measures of kurtosis, or looking at sub-regions such as the pars compacta or posterior putamen which have been shown to be particularly sensitive can raise your AUC.

Did you also try to see if your most predictive features could be helpful in the NSD-ISS staging system? It would be great if imaging measures such as these could help augment the staging system.

Finally, are there any imaging differences you noticed between the genetic groups i.e. LRRK2 vs GBA compared to iPD?

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@bmarebwa :Thank you for your insightful feedback and questions.
We have indeed investigated the relationship between the calculated functional Parkinson’s Disease-Related Pattern (fPDRP) and functional Parkinson’s Disease Cognitive Pattern (fPDCP) with CSF alpha-synuclein in our investigated PD grpup who underwent lumbar puncture and CSF collection. While we observed a trend, the limited sample size prevents us from drawing definitive conclusions at this stage.

To strengthen our findings, we are currently working on further validating these results using larger, multi-centric datasets. This expanded analysis will incorporate fPDRP and fPDCP as imaging features. Additionally, this approach will allow us to evaluate the sensitivity and predictive value of these identified features across various NSD-ISS stages .

When we stratified the PD group based on genetic status, we observed certain genotype-specific imaging features: For example, the diffusion-based measure FA in L SFOF is predominantly influenced by GBA-associated PD cases. On the other hand, the regional increase in striatal functional connectivity is primarily driven by LRRK2-associated PD cases. These observations align with previous reports in the literature, underscoring supporting the notion of a multi-modality approach that allows to encompass signatures for different [genetic] PD subtypes.

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Thanks @AmgadDroby ! Looking forward to the outcome of the larger study. It would be interesting to validate the genetic specific imaging changes and begin to understand what that could mean for the pathopysiology of the disease subtypes. For LRRK2, are you also consiering the cholinergic system and looking at the basal forebrain, and its functional and structural connections?

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