Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study

Sid E. O'Bryant; Melissa Edwards; Fan Zhang; Leigh A. Johnson; James Hall; Yuliya Kuras; Clemens R. Scherzer

doi:10.1016/j.dadm.2019.03.001

Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study

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

Research output: Contribution to journal › Article

2 Scopus citations

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 language	English
Pages (from-to)	374-382
Number of pages	9
Journal	Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume	11
DOIs	https://doi.org/10.1016/j.dadm.2019.03.001
State	Published - Dec 2019

Keywords

Blood biomarkers
Diagnostic accuracy
Parkinson's disease
Precision medicine
Proteomics

Access to Document

10.1016/j.dadm.2019.03.001

Link to publication in Scopus

Fingerprint Dive into the research topics of 'Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study'. Together they form a unique fingerprint.

Cite this

O'Bryant, S. E., Edwards, M., Zhang, F., Johnson, L. A., Hall, J., Kuras, Y., & Scherzer, C. R. (2019). Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study. Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, 11, 374-382. https://doi.org/10.1016/j.dadm.2019.03.001

@article{974368350e574c619ca2ffd527c11fa3,

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.",

keywords = "Blood biomarkers, Diagnostic accuracy, Parkinson's disease, Precision medicine, Proteomics",

author = "O'Bryant, {Sid E.} and Melissa Edwards and Fan Zhang and Johnson, {Leigh A.} and James Hall and Yuliya Kuras and Scherzer, {Clemens R.}",

year = "2019",

month = dec,

doi = "10.1016/j.dadm.2019.03.001",

language = "English",

volume = "11",

pages = "374--382",

journal = "Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring",

issn = "2352-8729",

publisher = "Elsevier BV",

}

Potential two-step proteomic signature for Parkinson's disease : Pilot analysis in the Harvard Biomarkers Study. / O'Bryant, Sid E.; 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, 12.2019, p. 374-382.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Potential two-step proteomic signature for Parkinson's disease

T2 - Pilot analysis in the Harvard Biomarkers Study

AU - O'Bryant, Sid E.

AU - Edwards, Melissa

AU - Zhang, Fan

AU - Johnson, Leigh A.

AU - Hall, James

AU - Kuras, Yuliya

AU - Scherzer, Clemens R.

PY - 2019/12

Y1 - 2019/12

N2 - 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.

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.

KW - Blood biomarkers

KW - Diagnostic accuracy

KW - Parkinson's disease

KW - Precision medicine

KW - Proteomics

UR - http://www.scopus.com/inward/record.url?scp=85065074000&partnerID=8YFLogxK

U2 - 10.1016/j.dadm.2019.03.001

DO - 10.1016/j.dadm.2019.03.001

M3 - Article

AN - SCOPUS:85065074000

VL - 11

SP - 374

EP - 382

JO - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring

JF - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring

SN - 2352-8729

ER -