Identification of Imaging Genetics Association for Mild Cognitive Impairment Based on Adaptive Constrained Canonical Correlation Analysis

Mild cognitive impairment (MCI) is a progressive neurodegenerative disease, with primary clinical manifestations including memory deterioration, declining cognitive abilities, and behavioral issues. Considering the progression over time, the disease advances with regional variations in different brain areas, possibly influenced by genetic molecular functions. Therefore, to determine the correlation between imaging genetics data, this study explores the association between multiple time point brain regions and genetic data based on the adaptive sparse multi-view canonical correlation analysis algorithm, aiming to fully utilize data from multiple time points. The study fully utilizes voxel data of brain regions at two time points of MCI and corresponding gene expression data of samples, thereby exploring high-order correlated features of brain imaging genetic data. This includes conducting bioinformatics analysis on identified high-risk brain regions and top-ranking genes to validate the supplemental effects of time point data. This research offers a new perspective on MCI and contributes to the discovery of potential biomarkers and early intervention strategies.