Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.

<h4>Background</h4>Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS.<h4>Met...

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Main Authors: Steven E Schutzer, Thomas E Angel, Tao Liu, Athena A Schepmoes, Therese R Clauss, Joshua N Adkins, David G Camp, Bart K Holland, Jonas Bergquist, Patricia K Coyle, Richard D Smith, Brian A Fallon, Benjamin H Natelson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-02-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21383843/pdf/?tool=EBI
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author Steven E Schutzer
Thomas E Angel
Tao Liu
Athena A Schepmoes
Therese R Clauss
Joshua N Adkins
David G Camp
Bart K Holland
Jonas Bergquist
Patricia K Coyle
Richard D Smith
Brian A Fallon
Benjamin H Natelson
author_facet Steven E Schutzer
Thomas E Angel
Tao Liu
Athena A Schepmoes
Therese R Clauss
Joshua N Adkins
David G Camp
Bart K Holland
Jonas Bergquist
Patricia K Coyle
Richard D Smith
Brian A Fallon
Benjamin H Natelson
author_sort Steven E Schutzer
collection DOAJ
description <h4>Background</h4>Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS.<h4>Methods and principal findings</h4>Pooled cerebrospinal fluid (CSF) samples from nPTLS patients, CFS patients, and healthy volunteers were comprehensively analyzed using high-resolution mass spectrometry (MS), coupled with immunoaffinity depletion methods to reduce protein-masking by abundant proteins. Individual patient and healthy control CSF samples were analyzed directly employing a MS-based label-free quantitative proteomics approach. We found that both groups, and individuals within the groups, could be distinguished from each other and normals based on their specific CSF proteins (p<0.01). CFS (n = 43) had 2,783 non-redundant proteins, nPTLS (n = 25) contained 2,768 proteins, and healthy normals had 2,630 proteins. Preliminary pathway analysis demonstrated that the data could be useful for hypothesis generation on the pathogenetic mechanisms underlying these two related syndromes.<h4>Conclusions</h4>nPTLS and CFS have distinguishing CSF protein complements. Each condition has a number of CSF proteins that can be useful in providing candidates for future validation studies and insights on the respective mechanisms of pathogenesis. Distinguishing nPTLS and CFS permits more focused study of each condition, and can lead to novel diagnostics and therapeutic interventions.
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spelling doaj.art-289b8e3f2af942ad86653c771d9bda422022-12-21T22:53:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-02-0162e1728710.1371/journal.pone.0017287Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.Steven E SchutzerThomas E AngelTao LiuAthena A SchepmoesTherese R ClaussJoshua N AdkinsDavid G CampBart K HollandJonas BergquistPatricia K CoyleRichard D SmithBrian A FallonBenjamin H Natelson<h4>Background</h4>Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS.<h4>Methods and principal findings</h4>Pooled cerebrospinal fluid (CSF) samples from nPTLS patients, CFS patients, and healthy volunteers were comprehensively analyzed using high-resolution mass spectrometry (MS), coupled with immunoaffinity depletion methods to reduce protein-masking by abundant proteins. Individual patient and healthy control CSF samples were analyzed directly employing a MS-based label-free quantitative proteomics approach. We found that both groups, and individuals within the groups, could be distinguished from each other and normals based on their specific CSF proteins (p<0.01). CFS (n = 43) had 2,783 non-redundant proteins, nPTLS (n = 25) contained 2,768 proteins, and healthy normals had 2,630 proteins. Preliminary pathway analysis demonstrated that the data could be useful for hypothesis generation on the pathogenetic mechanisms underlying these two related syndromes.<h4>Conclusions</h4>nPTLS and CFS have distinguishing CSF protein complements. Each condition has a number of CSF proteins that can be useful in providing candidates for future validation studies and insights on the respective mechanisms of pathogenesis. Distinguishing nPTLS and CFS permits more focused study of each condition, and can lead to novel diagnostics and therapeutic interventions.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21383843/pdf/?tool=EBI
spellingShingle Steven E Schutzer
Thomas E Angel
Tao Liu
Athena A Schepmoes
Therese R Clauss
Joshua N Adkins
David G Camp
Bart K Holland
Jonas Bergquist
Patricia K Coyle
Richard D Smith
Brian A Fallon
Benjamin H Natelson
Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.
PLoS ONE
title Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.
title_full Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.
title_fullStr Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.
title_full_unstemmed Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.
title_short Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome.
title_sort distinct cerebrospinal fluid proteomes differentiate post treatment lyme disease from chronic fatigue syndrome
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21383843/pdf/?tool=EBI
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