Funded Studies
Study Rationale:
In Parkinson's, the alpha-synuclein protein misfolds and aggregates into clumps, called Lewy bodies. When Lewy bodies are found in people without Parkinson’s, it can be diagnosed as incidental Lewy body disease (ILBD). ILBD may precede Parkinson’s or dementia with Lewy bodies (another disease of alpha-synuclein clumps).
A test called RTQuIC alpha-synuclein seeding assay appears to be extremely sensitive and specific for detecting pathological levels of alpha-synuclein in Parkinson’s disease and distinguishing Parkinson’s volunteers from control volunteers. No studies have been published on using RT QuIC to detect alpha-synuclein in ILBD.
Hypothesis:
We hypothesize that the RT-QuIC assay will detect relative amounts of misfolded alpha-synuclein in cerebrospinal fluid, submandibular gland tissue and skin samples of people with ILBD. The RTQuIC results will serve as a diagnostic biomarker of ILBD, which could be used to identify those at high-risk of Parkinson’s or dementia with Lewy bodies.
Study Design:
We will compare pathological alpha-synuclein levels using RT QuIC in cerebrospinal fluid, frozen skin, and frozen submandibular gland samples from 35 cases of ILBD. We would compare positivity across tissues in the same individual. In addition, 10 Parkinson’s cases and 10 controls would be included to allow for replication of previous findings. We will also test skin samples from an additional ~70 ILBD cases to add power to the study of skin biopsies as a potential early-sign biomarker.
Impact on Diagnosis/Treatment of Parkinson’s Disease:
The detection of ultra-low levels of pathological alpha-synuclein in peripheral tissues and cerebrospinal fluid would represent a promising approach in improving the early diagnosis of Parkinson’s/dementia with Lewy Bodies as well as for monitoring disease progression and effectiveness of treatment.
Next Steps for Development:
If alpha-synuclein is detected in cerebrospinal fluid, skin, and/or submandibular gland samples, then the next logical step will be to determine which one is the best peripheral biomarker for early disease.