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Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases

Diagnosis of neurodegenerative disorders (NDDs) including Parkinson’s disease and Alzheimer’s disease is challenging owing to the lack of tools to detect preclinical biomarkers. The misfolding of proteins into oligomeric and fibrillar aggregates plays an important role in the development and progres...

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Autores principales: Kavungal, Deepthy, Magalhães, Pedro, Kumar, Senthil T., Kolla, Rajasekhar, Lashuel, Hilal A., Altug, Hatice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337894/
https://www.ncbi.nlm.nih.gov/pubmed/37436975
http://dx.doi.org/10.1126/sciadv.adg9644
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author Kavungal, Deepthy
Magalhães, Pedro
Kumar, Senthil T.
Kolla, Rajasekhar
Lashuel, Hilal A.
Altug, Hatice
author_facet Kavungal, Deepthy
Magalhães, Pedro
Kumar, Senthil T.
Kolla, Rajasekhar
Lashuel, Hilal A.
Altug, Hatice
author_sort Kavungal, Deepthy
collection PubMed
description Diagnosis of neurodegenerative disorders (NDDs) including Parkinson’s disease and Alzheimer’s disease is challenging owing to the lack of tools to detect preclinical biomarkers. The misfolding of proteins into oligomeric and fibrillar aggregates plays an important role in the development and progression of NDDs, thus underscoring the need for structural biomarker–based diagnostics. We developed an immunoassay-coupled nanoplasmonic infrared metasurface sensor that detects proteins linked to NDDs, such as alpha-synuclein, with specificity and differentiates the distinct structural species using their unique absorption signatures. We augmented the sensor with an artificial neural network enabling unprecedented quantitative prediction of oligomeric and fibrillar protein aggregates in their mixture. The microfluidic integrated sensor can retrieve time-resolved absorbance fingerprints in the presence of a complex biomatrix and is capable of multiplexing for the simultaneous monitoring of multiple pathology-associated biomarkers. Thus, our sensor is a promising candidate for the clinical diagnosis of NDDs, disease monitoring, and evaluation of novel therapies.
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spelling pubmed-103378942023-07-13 Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases Kavungal, Deepthy Magalhães, Pedro Kumar, Senthil T. Kolla, Rajasekhar Lashuel, Hilal A. Altug, Hatice Sci Adv Physical and Materials Sciences Diagnosis of neurodegenerative disorders (NDDs) including Parkinson’s disease and Alzheimer’s disease is challenging owing to the lack of tools to detect preclinical biomarkers. The misfolding of proteins into oligomeric and fibrillar aggregates plays an important role in the development and progression of NDDs, thus underscoring the need for structural biomarker–based diagnostics. We developed an immunoassay-coupled nanoplasmonic infrared metasurface sensor that detects proteins linked to NDDs, such as alpha-synuclein, with specificity and differentiates the distinct structural species using their unique absorption signatures. We augmented the sensor with an artificial neural network enabling unprecedented quantitative prediction of oligomeric and fibrillar protein aggregates in their mixture. The microfluidic integrated sensor can retrieve time-resolved absorbance fingerprints in the presence of a complex biomatrix and is capable of multiplexing for the simultaneous monitoring of multiple pathology-associated biomarkers. Thus, our sensor is a promising candidate for the clinical diagnosis of NDDs, disease monitoring, and evaluation of novel therapies. American Association for the Advancement of Science 2023-07-12 /pmc/articles/PMC10337894/ /pubmed/37436975 http://dx.doi.org/10.1126/sciadv.adg9644 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Physical and Materials Sciences
Kavungal, Deepthy
Magalhães, Pedro
Kumar, Senthil T.
Kolla, Rajasekhar
Lashuel, Hilal A.
Altug, Hatice
Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
title Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
title_full Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
title_fullStr Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
title_full_unstemmed Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
title_short Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
title_sort artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
topic Physical and Materials Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337894/
https://www.ncbi.nlm.nih.gov/pubmed/37436975
http://dx.doi.org/10.1126/sciadv.adg9644
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