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There is a high misdiagnosis rate between Parkinson's disease (PD) and atypical parkinsonian disorders (APD), such as progressive supranuclear palsy (PSP), the second most common parkinsonian syndrome. In our earlier studies, we identified and replicated RNA blood biomarkers in several independent cohorts, however, replication in a cohort that includes PSP patients has not yet been performed. To this end, we evaluated the diagnostic potential of nine previously identified RNA biomarkers using quantitative PCR assays in 138 blood samples at baseline from PD, PSP and healthy controls (HCs) nested in the PD Biomarkers Program. Linear discriminant analysis showed that COPZ1 and PTPN1 distinguished PD from PSP patients with 62.5% accuracy. Five biomarkers, PTPN1, COPZ1, FAXDC2, SLC14A1s and NAMPT were useful for distinguishing PSP from controls with 69% accuracy. Several biomarkers correlated with clinical features in PD patients. SLC14A1-s correlated with Unified Parkinson's Disease Rating Scale total and part III scores. In addition, COPZ1, PTPN1 and MLST8, correlated with Montreal Cognitive Assessment (MoCA). Interestingly, COPZ1, EFTUD2 and PTPN1 were downregulated in cognitively impaired (CI) compared to normal subjects. Linear discriminant analysis showed that age, PTPN1, COPZ1, FAXDC2, EFTUD2 and MLST8 distinguished CI from normal subjects with 65.9% accuracy. These results suggest that COPZ1 and PTPN1 are useful for distinguishing PD from PSP patients. In addition, the combination of PTPN1, COPZ1, FAXDC2, EFTUD2 and MLST8 is a useful signature for cognitive impairment. Evaluation of these biomarkers in a larger study will be a key to advancing these biomarkers into the clinic.
Pubmed ID: 29896099
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Database of the results of the ADNI study. ADNI is an initiative to develop biomarker-based methods to detect and track the progression of Alzheimer's disease (AD) that provides access to qualified scientists to their database of imaging, clinical, genomic, and biomarker data.
View all literature mentionsCommercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsThe Museum of Comparative Anthropogeny (MOCA) is a collection of comparative information regarding humans and our closest evolutionary cousins (chimpanzees, bonobos, gorillas and orangutans i.e, great apes), with an emphasis on uniquely human features. MOCA is organized by Domains, each grouping Topics by areas of interest and scientific discipline. Each topic entry will eventually cover existing information about a particular difference (alleged or documented) between humans and non-human hominids. Comparisons of these non-human hominids with humans are difficult, as so little is known about their phenotypic features (phenomes), in contrast to humans. Ethical, fiscal and practical issues also limit collection of further information about great apes. MOCA attempts to collect existing information about human-specific differences from great apes, currently scattered in the literature. Having such information in one location could lead to new insights and multi-disciplinary interactions, and to ethically-sound studies to explain differences, and uniquely human specializations. MOCA is not targeted at experts in specific disciplines, but rather aims to communicate basic information to a broad audience of scientists from many backgrounds, and to the interested lay public. MOCA includes not only aspects wherein there are known or apparent differences between humans and great apes, but additionally, topics for which popular wisdom about claimed or assumed differences is not entirely correct. It is for all these reasons that MOCA is called a Museum, and not an Encyclopedia or Database.
View all literature mentionsCommon data management resource and web portal to promote discovery of Parkinson's Disease diagnostic and progression biomarker candidates for early detection and measurement of disease progression. PDBP will serve as multi-faceted platform for integrating existing biomarker efforts, standardizing data collection and management across these efforts, accelerating discovery of new biomarkers, and fostering and expanding collaborative opportunities for all stakeholders.
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