Potential two-step proteomic signature for Parkinson's disease

Pilot analysis in the Harvard Biomarkers Study

Sidney O'Bryant, Melissa Edwards, Fan Zhang, Leigh A. Johnson, James Hall, Yuliya Kuras, Clemens R. Scherzer

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Introduction: We sought to determine if our previously validated proteomic profile for detecting Alzheimer's disease would detect Parkinson's disease (PD) and distinguish PD from other neurodegenerative diseases. Methods: Plasma samples were assayed from 150 patients of the Harvard Biomarkers Study (PD, n = 50; other neurodegenerative diseases, n = 50; healthy controls, n = 50) using electrochemiluminescence and Simoa platforms. Results: The first step proteomic profile distinguished neurodegenerative diseases from controls with a diagnostic accuracy of 0.94. The second step profile distinguished PD cases from other neurodegenerative diseases with a diagnostic accuracy of 0.98. The proteomic profile differed in step 1 versus step 2, suggesting that a multistep proteomic profile algorithm to detecting and distinguishing between neurodegenerative diseases may be optimal. Discussion: These data provide evidence of the potential use of a multitiered blood-based proteomic screening method for detecting individuals with neurodegenerative disease and then distinguishing PD from other neurodegenerative diseases.

Original languageEnglish
Pages (from-to)374-382
Number of pages9
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume11
DOIs
StatePublished - 1 Dec 2019

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Neurodegenerative Diseases
Proteomics
Parkinson Disease
Biomarkers
Alzheimer Disease

Keywords

  • Blood biomarkers
  • Diagnostic accuracy
  • Parkinson's disease
  • Precision medicine
  • Proteomics

Cite this

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title = "Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study",
abstract = "Introduction: We sought to determine if our previously validated proteomic profile for detecting Alzheimer's disease would detect Parkinson's disease (PD) and distinguish PD from other neurodegenerative diseases. Methods: Plasma samples were assayed from 150 patients of the Harvard Biomarkers Study (PD, n = 50; other neurodegenerative diseases, n = 50; healthy controls, n = 50) using electrochemiluminescence and Simoa platforms. Results: The first step proteomic profile distinguished neurodegenerative diseases from controls with a diagnostic accuracy of 0.94. The second step profile distinguished PD cases from other neurodegenerative diseases with a diagnostic accuracy of 0.98. The proteomic profile differed in step 1 versus step 2, suggesting that a multistep proteomic profile algorithm to detecting and distinguishing between neurodegenerative diseases may be optimal. Discussion: These data provide evidence of the potential use of a multitiered blood-based proteomic screening method for detecting individuals with neurodegenerative disease and then distinguishing PD from other neurodegenerative diseases.",
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Potential two-step proteomic signature for Parkinson's disease : Pilot analysis in the Harvard Biomarkers Study. / O'Bryant, Sidney; Edwards, Melissa; Zhang, Fan; Johnson, Leigh A.; Hall, James; Kuras, Yuliya; Scherzer, Clemens R.

In: Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, Vol. 11, 01.12.2019, p. 374-382.

Research output: Contribution to journalArticleResearchpeer-review

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T2 - Pilot analysis in the Harvard Biomarkers Study

AU - O'Bryant, Sidney

AU - Edwards, Melissa

AU - Zhang, Fan

AU - Johnson, Leigh A.

AU - Hall, James

AU - Kuras, Yuliya

AU - Scherzer, Clemens R.

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AB - Introduction: We sought to determine if our previously validated proteomic profile for detecting Alzheimer's disease would detect Parkinson's disease (PD) and distinguish PD from other neurodegenerative diseases. Methods: Plasma samples were assayed from 150 patients of the Harvard Biomarkers Study (PD, n = 50; other neurodegenerative diseases, n = 50; healthy controls, n = 50) using electrochemiluminescence and Simoa platforms. Results: The first step proteomic profile distinguished neurodegenerative diseases from controls with a diagnostic accuracy of 0.94. The second step profile distinguished PD cases from other neurodegenerative diseases with a diagnostic accuracy of 0.98. The proteomic profile differed in step 1 versus step 2, suggesting that a multistep proteomic profile algorithm to detecting and distinguishing between neurodegenerative diseases may be optimal. Discussion: These data provide evidence of the potential use of a multitiered blood-based proteomic screening method for detecting individuals with neurodegenerative disease and then distinguishing PD from other neurodegenerative diseases.

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