Unlocking Preclinical Alzheimer’s: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics
dc.contributor.author | López, Eneko | |
dc.contributor.author | Etxebarria Elezgarai, Jaione ![]() | |
dc.contributor.author | García Sebastián, Maite | |
dc.contributor.author | Altuna, Miren | |
dc.contributor.author | Ecay Torres, Mirian | |
dc.contributor.author | Estanga Alustiza, Ainara | |
dc.contributor.author | Tainta, Mikel | |
dc.contributor.author | López, Carolina | |
dc.contributor.author | Martínez-Lage, Pablo | |
dc.contributor.author | Amigo Rubio, José Manuel ![]() | |
dc.contributor.author | Seifert, Andreas | |
dc.date.accessioned | 2024-05-14T17:58:42Z | |
dc.date.available | 2024-05-14T17:58:42Z | |
dc.date.issued | 2024-04-26 | |
dc.identifier.citation | International Journal of Molecular Sciences 25(9) : (2024) // Article ID 4737 | es_ES |
dc.identifier.issn | 1422-0067 | |
dc.identifier.uri | http://hdl.handle.net/10810/67951 | |
dc.description.abstract | Alzheimer’s disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer’s encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer’s still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer’s diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer’s, which is particularly surprising because of Raman spectroscopy’s high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer’s disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods. | es_ES |
dc.description.sponsorship | This work was funded by the Basque Government (Ref. KK-2022/00001) and supported by grant CEX2020-001038-M funded by MICIU/AEI/10.13039/501100011033. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/CEX2020-001038-M | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/es/ | |
dc.subject | preclinical Alzheimer’s | es_ES |
dc.subject | cerebrospinal fluid | es_ES |
dc.subject | vibrational spectroscopy | es_ES |
dc.subject | machine learning | es_ES |
dc.subject | PLS-DA | es_ES |
dc.subject | variable selection | es_ES |
dc.title | Unlocking Preclinical Alzheimer’s: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2024-05-10T13:18:35Z | |
dc.rights.holder | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1422-0067/25/9/4737 | es_ES |
dc.identifier.doi | 10.3390/ijms25094737 | |
dc.departamentoes | Química analítica | |
dc.departamentoeu | Kimika analitikoa |
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Except where otherwise noted, this item's license is described as © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/).