Cassandra A DeMarshall1, Min Han1, Eric P Nagele2, Abhirup Sarkar1, Nimish K Acharya3, George Godsey4, Eric L Goldwaser1, Mary Kosciuk3, Umashanger Thayasivam5, Benjamin Belinka6, Robert G Nagele7. 1. Biomarker Discovery Center, New Jersey Institute for Successful Aging, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA; Graduate School of Biomedical Sciences, Rowan University, Stratford, NJ, USA; Department of Geriatrics and Gerontology, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA. 2. Biomarker Discovery Center, New Jersey Institute for Successful Aging, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA; Durin Technologies, Inc., New Brunswick, NJ, USA. 3. Biomarker Discovery Center, New Jersey Institute for Successful Aging, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA; Department of Geriatrics and Gerontology, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA. 4. Graduate School of Biomedical Sciences, Rowan University, Stratford, NJ, USA; Department of Geriatrics and Gerontology, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA. 5. Department of Mathematics, Rowan University, Glassboro, NJ, USA. 6. Durin Technologies, Inc., New Brunswick, NJ, USA. 7. Biomarker Discovery Center, New Jersey Institute for Successful Aging, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA; Department of Geriatrics and Gerontology, Rowan University School of Osteopathic Medicine, Stratford, NJ, USA; Durin Technologies, Inc., New Brunswick, NJ, USA. Electronic address: nagelero@rowan.edu.
Abstract
INTRODUCTION: There is a great need to identify readily accessible, blood-based biomarkers for Parkinson's disease (PD) that are useful for accurate early detection and diagnosis. This advancement would allow early patient treatment and enrollment into clinical trials, both of which would greatly facilitate the development of new therapies for PD. METHODS: Sera from a total of 398 subjects, including 103 early-stage PD subjects derived from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, were screened with human protein microarrays containing 9,486 potential antigen targets to identify autoantibodies potentially useful as biomarkers for PD. A panel of selected autoantibodies with a higher prevalence in early-stage PD was identified and tested using Random Forest for its ability to distinguish early-stage PD subjects from controls and from individuals with other neurodegenerative and non-neurodegenerative diseases. RESULTS: Results demonstrate that a panel of selected, blood-borne autoantibody biomarkers can distinguish early-stage PD subjects (90% confidence in diagnosis) from age- and sex-matched controls with an overall accuracy of 87.9%, a sensitivity of 94.1% and specificity of 85.5%. These biomarkers were also capable of differentiating patients with early-stage PD from those with more advanced (mild-moderate) PD with an overall accuracy of 97.5%, and could distinguish subjects with early-stage PD from those with other neurological (e.g., Alzheimer's disease and multiple sclerosis) and non-neurological (e.g., breast cancer) diseases. CONCLUSION: These results demonstrate, for the first time, that a panel of selected autoantibodies may prove to be useful as effective blood-based biomarkers for the diagnosis of early-stage PD.
INTRODUCTION: There is a great need to identify readily accessible, blood-based biomarkers for Parkinson's disease (PD) that are useful for accurate early detection and diagnosis. This advancement would allow early patient treatment and enrollment into clinical trials, both of which would greatly facilitate the development of new therapies for PD. METHODS: Sera from a total of 398 subjects, including 103 early-stage PD subjects derived from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, were screened with human protein microarrays containing 9,486 potential antigen targets to identify autoantibodies potentially useful as biomarkers for PD. A panel of selected autoantibodies with a higher prevalence in early-stage PD was identified and tested using Random Forest for its ability to distinguish early-stage PD subjects from controls and from individuals with other neurodegenerative and non-neurodegenerative diseases. RESULTS: Results demonstrate that a panel of selected, blood-borne autoantibody biomarkers can distinguish early-stage PD subjects (90% confidence in diagnosis) from age- and sex-matched controls with an overall accuracy of 87.9%, a sensitivity of 94.1% and specificity of 85.5%. These biomarkers were also capable of differentiating patients with early-stage PD from those with more advanced (mild-moderate) PD with an overall accuracy of 97.5%, and could distinguish subjects with early-stage PD from those with other neurological (e.g., Alzheimer's disease and multiple sclerosis) and non-neurological (e.g., breast cancer) diseases. CONCLUSION: These results demonstrate, for the first time, that a panel of selected autoantibodies may prove to be useful as effective blood-based biomarkers for the diagnosis of early-stage PD.
Authors: Sid E O'Bryant; Michelle M Mielke; Robert A Rissman; Simone Lista; Hugo Vanderstichele; Henrik Zetterberg; Piotr Lewczuk; Holly Posner; James Hall; Leigh Johnson; Yiu-Lian Fong; Johan Luthman; Andreas Jeromin; Richard Batrla-Utermann; Alcibiades Villarreal; Gabrielle Britton; Peter J Snyder; Kim Henriksen; Paula Grammas; Veer Gupta; Ralph Martins; Harald Hampel Journal: Alzheimers Dement Date: 2016-11-18 Impact factor: 21.566
Authors: Piotr Lewczuk; Peter Riederer; Sid E O'Bryant; Marcel M Verbeek; Bruno Dubois; Pieter Jelle Visser; Kurt A Jellinger; Sebastiaan Engelborghs; Alfredo Ramirez; Lucilla Parnetti; Clifford R Jack; Charlotte E Teunissen; Harald Hampel; Alberto Lleó; Frank Jessen; Lidia Glodzik; Mony J de Leon; Anne M Fagan; José Luis Molinuevo; Willemijn J Jansen; Bengt Winblad; Leslie M Shaw; Ulf Andreasson; Markus Otto; Brit Mollenhauer; Jens Wiltfang; Martin R Turner; Inga Zerr; Ron Handels; Alexander G Thompson; Gunilla Johansson; Natalia Ermann; John Q Trojanowski; Ilker Karaca; Holger Wagner; Patrick Oeckl; Linda van Waalwijk van Doorn; Maria Bjerke; Dimitrios Kapogiannis; H Bea Kuiperij; Lucia Farotti; Yi Li; Brian A Gordon; Stéphane Epelbaum; Stephanie J B Vos; Catharina J M Klijn; William E Van Nostrand; Carolina Minguillon; Matthias Schmitz; Carla Gallo; Andrea Lopez Mato; Florence Thibaut; Simone Lista; Daniel Alcolea; Henrik Zetterberg; Kaj Blennow; Johannes Kornhuber Journal: World J Biol Psychiatry Date: 2017-10-27 Impact factor: 4.132
Authors: Cassandra A DeMarshall; Eric P Nagele; Abhirup Sarkar; Nimish K Acharya; George Godsey; Eric L Goldwaser; Mary Kosciuk; Umashanger Thayasivam; Min Han; Benjamin Belinka; Robert G Nagele Journal: Alzheimers Dement (Amst) Date: 2016-04-12
Authors: Umar Yazdani; Sayed Zaman; Linda S Hynan; L Steven Brown; Richard B Dewey; David Karp; Dwight C German Journal: NPJ Parkinsons Dis Date: 2016-06-23
Authors: Thomas A Pollak; Jonathan P Rogers; Robert G Nagele; Mark Peakman; James M Stone; Anthony S David; Philip McGuire Journal: Schizophr Bull Date: 2019-01-01 Impact factor: 9.306