Compositional brain scores capture Alzheimer's disease-specific structural brain patterns along the disease continuum

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Genius, Patricia
• dc.contributor.author Calle, M. Luz
• dc.contributor.author Rodríguez-Fernández, Blanca
• dc.contributor.author Minguillón, Carolina
• dc.contributor.author Cacciaglia, Raffaele
• dc.contributor.author Garrido Martín, Diego, 1992-
• dc.contributor.author Esteller, Manel
• dc.contributor.author Navarro i Cuartiellas, Arcadi, 1969-
• dc.contributor.author Gispert López, Juan Domingo
• dc.contributor.author Vilor Tejedor, Natàlia, 1988-
• dc.contributor.author Alzheimer's Disease Neuroimaging Initiative
• dc.contributor.author ALFA Study
• dc.date.accessioned 2025-03-18T07:45:08Z
• dc.date.available 2025-03-18T07:45:08Z
• dc.date.issued 2025
• dc.description.abstract Introduction: Traditional multivariate methods for neuroimaging studies overlook the interdependent relationship between brain features. This study addresses this gap by analyzing relative brain volumetric patterns to capture how Alzheimer's disease (AD) and genetics influence brain structure along the disease continuum. Methods: This study analyzed data from participants across the AD continuum from the Alzheimer's and Families (ALFA) and Alzheimer's Disease Neuroimaging Initiative (ADNI) studies. Compositional data analysis (CoDA) was exploited to examine relative brain volumetric variations that (1) were linked to different AD stages compared to cognitively unimpaired amyloid-β-negative (CU A-) individuals and (2) varied by AD genetic risk. Results: Disease stage-specific compositional brain scores were identified, differentiating CU A- individuals from those in more advanced stages. Genetic risk-stratified models revealed a broader genetic landscape affecting brain morphology in AD, beyond the well-known apolipoprotein E ε4 allele. Discussion: CoDA emerges as an alternative multivariate framework to deepen understanding of AD-related structural changes and support targeted interventions for those at higher genetic risk. Highlights: Compositional data analysis (CoDA) revealed the relative variation of brain region volumes, captured in compositional brain scores, capable of discerning between cognitively unimpaired amyloid-β-negative individuals and subjects within other disease-stage groups along the Alzheimer's disease (AD) continuum. CoDA also uncovered the genetic vulnerability of specific brain regions at each stage of the disease along the continuum. CoDA is capable of integrating magnetic resonance imaging data from two different cohorts without stringent requirements for harmonization. This translates as an advantage, compared to traditional methods, and strengthens the reliability of cross-study comparisons by standardizing the data despite different labeling agreements, facilitating collaborative and large-scale research. The algorithm is sensitive to AD-specific effects, as the main compositional brain scores display little overlap with the age-specific compositional brain score. CoDA provides a more accurate analysis of brain imaging data addressing its compositional nature, which can influence the development of targeted approaches, opening new avenues for enhancing brain health.
• dc.description.sponsorship The research leading to these results has received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004, the Health Department of the Catalan Government (Health Research and Innovation Strategic Plan (PERIS) 2016-2020 grant# SLT002/16/00201), and the Alzheimer's Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007). Additional support has been received from the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under the grant no. 2021 SGR 00913. All CRG authors acknowledge the support of the Spanish Ministry of Science, Innovation, and Universities to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya. N.V.-T. was supported by the Spanish Ministry of Science and Innovation—State Research Agency (IJC2020-043216-I/MCIN/AEI/10.13039/501100011033) and the European Union «NextGenerationEU»/PRTR and currently receives funding from the Spanish Research Agency MICIU/AEI/10.13039/501100011033 (grant RYC2022-038136-I cofunded by the European Union FSE+ and grant PID2022-143106OA-I00 cofunded by the European Union FEDER). In addition, N.V.-T. is supported by the William H. Gates Sr. Fellowship from the Alzheimer's Disease Data Initiative. Data partially used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.
• dc.format.mimetype application/pdf
• dc.identifier.citation Genius P, Calle ML, Rodríguez-Fernández B, Minguillon C, Cacciaglia R, Garrido-Martin D, et al. Compositional brain scores capture Alzheimer's disease-specific structural brain patterns along the disease continuum. Alzheimers Dement. 2025 Feb;21(2):e14490. DOI: 10.1002/alz.14490
• dc.identifier.doi http://dx.doi.org/10.1002/alz.14490
• dc.identifier.issn 1552-5260
• dc.identifier.uri http://hdl.handle.net/10230/69957
• dc.language.iso eng
• dc.publisher Wiley
• dc.relation.ispartof Alzheimers Dement. 2025 Feb;21(2):e14490
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PID2022-143106OA-I00
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/RYC2022-038136-I
• dc.rights © 2025 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.subject.keyword Alzheimer's disease genetic predisposition
• dc.subject.keyword Brain imaging genetics
• dc.subject.keyword Compositional brain score
• dc.subject.keyword Compositional data analysis
• dc.subject.keyword Multi phenotype analysis
• dc.subject.keyword Neurodegeneration
• dc.subject.keyword Polygenic risk scoring
• dc.title Compositional brain scores capture Alzheimer's disease-specific structural brain patterns along the disease continuum
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion