2026-08-29T14:07:37Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/267612025-12-18T12:56:53Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605
Repisalud
author
Genius, Patricia
author
Calle, M Luz
author
Rodríguez-Fernández, Blanca
author
Minguillon, Carolina
author
Cacciaglia, Raffaele
author
Garrido-Martin, Diego
author
Esteller, Manel
author
Navarro, Arcadi
author
Gispert, Juan Domingo
author
Vilor-Tejedor, Natalia
funder
Fundación La Caixa
funder
Ministerio de Ciencia e Innovación. Centro de Excelencia Severo Ochoa (España)
funder
Ministerio de Ciencia e Innovación (España)
funder
Unión Europea. Comisión Europea. NextGenerationEU
funder
Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF)
2025-06-17T11:42:54Z
2025-06-17T11:42:54Z
2025-02
Alzheimers Dement. 2025 Feb;21(2):e14490.
Alzheimers & Dementia
39868465
https://hdl.handle.net/20.500.12105/26761
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. 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.
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. 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.
eng
Alzheimer's disease genetic predisposition
brain imaging genetics
compositional brain score
compositional data analysis
multi phenotype analysis
neurodegeneration
polygenic risk scoring
Compositional brain scores capture Alzheimer's disease-specific structural brain patterns along the disease continuum.
research article
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URL
https://repisalud.isciii.es/bitstreams/7a873a74-78d4-4cae-abb1-92dac2d3b2d8/download
File
MD5
5504ae7dcb6a69fa8093766678fc002e
1371106
application/pdf
Compositional brain scores capture_Alzheimers Dement_2025.pdf