Circulating microRNAs as Progression Biomarkers for Parkinson's Disease
Resource: Utilizing DATATOP Biospecimens, 2014
This grant builds upon the research from a prior grant:
Promising Outcomes of Original Grant:
Our earlier study tested whether Parkinsonís disease (PD)-specific microRNAs in blood can be used to: (a) monitor disease development and (b) separate patients with fast-progressing PD from those with slow-progressing PD. We used blood serum from early and untreated people with PD patients, and showed that microRNAs can be used to track the progression of PD, as well as separate fast from slow progressors.
Objectives for Supplemental Investigation: † † † † ††
This is a follow-up study using additional samples from the same patient group to repeat and confirm our early study. Replication is an important step in biomarker development; the ability to reproduce our previous findings will enable us to test on a new group of patients as a validation study in the near future.
Importance of This Research for the Development of a New PD Therapy: † † †
MicroRNAs related to PD progression can be studied to better understand the disease development, which will inform potential new treatments. Moreover, microRNA biomarkers that can separate fast and slow progressors have the potential to guide different treatments between these two groups to improve outcomes.
microRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression and are essential in the development and differentiation of cells.† Changes in miRNAs expression are known to reflect specific disease status.† Previously, we identified miRNAs that can discriminate between Parkinsonís disease (PD) patients that progress slowly and rapidly.† In addition, miRNA expression changes from baseline (year 0) to endpoint (year 0.5-2).† Here, we aimed to validate our study with a larger sample size to confirm our previous findings. †To date, we confirmed two miRNAs that can differentiate PD patients with slow vs. fast progression and one miRNA that can differentiate baseline from endpoint.
Distinguished Associate Professor of Molecular Genomics at Grand Valley State University
Location: Grand Rapids, Michigan, United States