Residual Partial Least Squares Learning: Brain Cortical Thickness Simultaneously Predicts Eight Non-pairwise-correlated Behavioural and Disease Outcomes in Alzheimer's Disease

2024/03/13 by Duy-Thanh Vu, Duy-Cat Can, Christelle Schneuwly Diaz +21 · 1 voice
Neuroscience · Computer Science · Medicine · #Functional Brain Connectivity Studies #Computational Drug Discovery Methods #Dementia and Cognitive Impairment Research

paper · pdf · doi:10.1101/2024.03.11.584383

openalex publication_date 2024/03/13 · openalex created_date 2024/03/15 · openalex updated_date 2026/08/01

Abstract

Alzheimer's Disease (AD) is the leading cause of dementia, affecting brain structure, function, cognition, and behaviour. While previous studies have linked brain regions to univariate outcomes (e.g., disease status), the relationship between brain-wide changes and multiple disease and behavioural outcomes of AD is still not well understood. Here, we propose Residual Partial Least Squares (re-PLS) Learning, an explainable and generalisable framework that models high-dimensional brain features and multivariate outcomes, accounting for confounders. Using re-PLS, we map the many-to-many pathways between cortical thickness and multivariate AD outcomes; identify neural biomarkers that simultaneously predict multiple outcomes; control for confounding variables; conduct longitudinal AD prediction; and perform cross-cohort AD prediction. To evaluate its efficacy, we first carry out within-cohort cross-subject validation using ADNI data, and further examine its reproducibility via between-cohort cross-validation using ADNI and OASIS data. Together, our results unveil brain regions jointly but differentially predictive of distinctive cognitive-behavioural scores in AD.

Citations

• Memory, perception, and the ventral visual‐perirhinal‐hippocampal stream: Thinking outside of the boxes
• Molecular, Structural, and Functional Characterization of Alzheimer's Disease: Evidence for a Relationship between Default Activity, Amyloid, and Memory
• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Discussions

• [BioRxiv] Residual Partial Least Squares Learning: Brain Cortical Thickness Simultaneously Predicts Eight Non-pairwise-correlated Behavioural and Disease Outcomes in Alzheimer's Disease https://doi.o [bsky, 0 points, 0 comments]

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