An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms

Abstract Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers...

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Autores principales:	Lila Lovergne, Dhruba Ghosh, Renaud Schuck, Aris A. Polyzos, Andrew D. Chen, Michael C. Martin, Edward S. Barnard, James B. Brown, Cynthia T. McMurray
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/846890e2041e4915b5b464f2f470d9da
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spelling	oai:doaj.org-article:846890e2041e4915b5b464f2f470d9da2021-12-02T14:53:49ZAn infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms10.1038/s41598-021-93686-82045-2322https://doaj.org/article/846890e2041e4915b5b464f2f470d9da2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93686-8https://doaj.org/toc/2045-2322Abstract Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.Lila LovergneDhruba GhoshRenaud SchuckAris A. PolyzosAndrew D. ChenMichael C. MartinEdward S. BarnardJames B. BrownCynthia T. McMurrayNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-19 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lila Lovergne Dhruba Ghosh Renaud Schuck Aris A. Polyzos Andrew D. Chen Michael C. Martin Edward S. Barnard James B. Brown Cynthia T. McMurray An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
description	Abstract Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.
format	article
author	Lila Lovergne Dhruba Ghosh Renaud Schuck Aris A. Polyzos Andrew D. Chen Michael C. Martin Edward S. Barnard James B. Brown Cynthia T. McMurray
author_facet	Lila Lovergne Dhruba Ghosh Renaud Schuck Aris A. Polyzos Andrew D. Chen Michael C. Martin Edward S. Barnard James B. Brown Cynthia T. McMurray
author_sort	Lila Lovergne
title	An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
title_short	An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
title_full	An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
title_fullStr	An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
title_full_unstemmed	An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
title_sort	infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/846890e2041e4915b5b464f2f470d9da
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An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms

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