Parkinson's disease (PD) is the second most prevalent neurodegenerative disease worldwide. PD is characterized by the progressive deterioration of the dopaminergic system in the substantia nigra pars compacta (SNpc). Approximately 95% of PD cases are idiopathic suggesting environmental factors and genetic susceptibility play a role in disease onset. Diagnosis of PD is currently based on clinical assessment of motor symptoms. Unfortunately, motor symptoms in PD patients are usually manifested later in the course of the disease, and by the time a patient is diagnosed, a substantial number of dopaminergic neurons are dead. Further, there is a 30% misdiagnosis between PD and atypical parkinsonian disorders (APD), in particular, with progressive supranuclear palsy (PSP). The high misdiagnosis rate observed between PD and PSP is due to the overlap in clinical symptoms and initial response to levodopa therapy in early stages of these diseases. To address these issues, we previously identified and replicated RNA biomarkers that can be used to distinguish early stage PD patients from healthy controls (HC) in whole blood samples obtained from two independent clinical studies. Specifically, 13 splice variants were useful to distinguish PD from HC and APD with 90% sensitivity and 94 % specificity. Subsequently, we identified APP, SOD2, HNF4A and PTBP1 as additional putative biomarkers in both clinical trials. The ideal diagnostic PD bio signature of the biomarkers has not yet been determined however. Eight of the original splice variants were useful to distinguish PD from APD, including PSP and multiple system atrophy (MSA) with similar diagnostic accuracy. In a separate study, we identified PTPN1 as a diagnostic biomarker for PSP. Nonetheless, the APD signature and PTPN1 have not been replicated in an independent set of samples. In the proposed studies, we will determine the diagnostic utility of these biomarkers in an additional independent cohort of participants using samples obtained from the Parkinson's disease Biomarker Program (PDBP). This replication study is expected to identify a diagnostic PD and PSP bio signatures, which should advance the translation of these biomarkers into the clinic.

Public Health Relevance

Diagnosis of Parkinson's disease (PD) and progressive supranuclear palsy (PSP), both devastating neurodegenerative diseases, remains challenging and is currently based on the assessment of motor symptoms. Diagnosis of PD remains challenging and there is a high rate of misdiagnosis, reaching 30% between PD and PSP. Therefore, discovery and validation of sensitive and specific blood RNA biomarkers useful for distinguishing PD and PSP patients is expected to substantially improve the clinical management of both disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01NS097037-01
Application #
9136393
Study Section
Special Emphasis Panel (ZNS1-SRB-T (10))
Program Officer
Sutherland, Margaret L
Project Start
2016-06-01
Project End
2018-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
1
Fiscal Year
2016
Total Cost
$321,256
Indirect Cost
$108,067
Name
Rosalind Franklin University
Department
Pharmacology
Type
Schools of Medicine
DUNS #
069501252
City
North Chicago
State
IL
Country
United States
Zip Code
60064
Santiago, Jose A; Bottero, Virginie; Potashkin, Judith A (2018) Evaluation of RNA Blood Biomarkers in the Parkinson's Disease Biomarkers Program. Front Aging Neurosci 10:157
Santiago, Jose A; Potashkin, Judith A (2017) Blood Transcriptomic Meta-analysis Identifies Dysregulation of Hemoglobin and Iron Metabolism in Parkinson' Disease. Front Aging Neurosci 9:73
Santiago, Jose A; Bottero, Virginie; Potashkin, Judith A (2017) Biological and Clinical Implications of Comorbidities in Parkinson's Disease. Front Aging Neurosci 9:394
Gwinn, Katrina; David, Karen K; Swanson-Fischer, Christine et al. (2017) Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program. Biomark Med 11:451-473