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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Main Authors:	Lila Lovergne, Dhruba Ghosh, Renaud Schuck, Aris A. Polyzos, Andrew D. Chen, Michael C. Martin, Edward S. Barnard, James B. Brown, Cynthia T. McMurray
Format:	Article
Language:	English
Published:	Nature Publishing Group 2021-08-01
Series:	Scientific Reports
Online Access:	https://doi.org/10.1038/s41598-021-93686-8

id	doaj-846890e2041e4915b5b464f2f470d9da
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spelling	doaj-846890e2041e4915b5b464f2f470d9da2021-08-08T11:24:48ZengNature Publishing GroupScientific Reports2045-23222021-08-0111111910.1038/s41598-021-93686-8An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptomsLila Lovergne0Dhruba Ghosh1Renaud Schuck2Aris A. Polyzos3Andrew D. Chen4Michael C. Martin5Edward S. Barnard6James B. Brown7Cynthia T. McMurray8Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National LaboratoryDepartment of Statistics, University of CaliforniaDivision of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National LaboratoryDivision of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National LaboratoryDepartment of Statistics, University of CaliforniaAdvanced Light Source, Lawrence Berkeley National LaboratoryMolecular Foundry, Lawrence Berkeley National LaboratoryDepartment of Statistics, University of CaliforniaDivision of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National LaboratoryAbstract 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.https://doi.org/10.1038/s41598-021-93686-8
collection	DOAJ
language	English
format	Article
sources	DOAJ
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
spellingShingle	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 Scientific Reports
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 Publishing Group
series	Scientific Reports
issn	2045-2322
publishDate	2021-08-01
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.
url	https://doi.org/10.1038/s41598-021-93686-8
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An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms

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