Multi‐region brain transcriptomes uncover two subtypes of aging individuals with differences in the impact of APOEe4.

Background: Multi‐region brain transcriptomes uncover two subtypes of aging individuals with differences in the impact of APOEe4 Method: We preprocessed transcriptomic RNA sequencing profiles from three brain regions and deployed the canonical correlation analysis in the discovery set of individuals that have transcription profiles in all three regions. The subgroups of participants were identified through unsupervised k‐means clustering for each region and then integrated into "meta‐clusters" through a non‐negative matrix factorization. The clustering analysis was replicated in the remaining set of individuals that have data in only one or two of the three regions. To assess the clinicopathologic relevance of the meta‐clusters, we assessed whether clinical and pathologic features are different between the meta‐clusters by conducting a meta‐analysis of discovery and replication cohorts. We further investigated the mechanisms underlying the differences in clinical phenotypes between the two groups. Result: The clustering analysis revealed two stable subgroups of aging participants in each cohort. The empirically defined subgroups differ in their extent of the rate of cognitive decline and exhibit evidence of biological differences in the impact of APOEe4. Conclusion: These findings suggest that our population structure captures an aspect of the molecular state of the brain that affects cognition in a manner that may be independent of the underlying pathologies that accumulate with older age. [ABSTRACT FROM AUTHOR]