Brain Microstructural Pattern Age Acceleration (BMPAA) in Long-Lived Bats: Disentangling Age-Related, Sex-Related, and Origin-Specific Signatures

Abstract: Investigating how brain microstructure changes with age and contributes to cognitive resilience, especially in long-lived species, necessitates a system-level approach beyond isolated regional analyses. To address this, we developed Brain Mean Diffusivity (MD) Pattern Age Acceleration (BMPAA), a novel metric capturing individual deviations from expected age-related changes in brain-wide MD covariance patterns, with the aim of relating these to cognitive performance in long-lived bats. Utilizing Diffusion Tensor Imaging (DTI) mean diffusivity maps, DNAmAge, and behavioral data from 30 Egyptian fruit bats (Rousettus aegyptiacus), we extracted regional MD values from 24 brain regions. Principal Component Analysis (PCA) was then applied to the standardized MD matrix to identify dominant modes of microstructural organization. BMPAA scores were subsequently derived as residuals from linear regression models predicting these principal component scores from DNAmAge, sex, and origin colony. PCA successfully identified six principal components, collectively explaining 87.33% of the variance in brain MD. Crucially, one component exhibited a significant association with DNAmAge, indicating a canonical age-related pattern of brain microstructural change. Other components were significantly linked to sex and colony of origin, thereby disentangling distinct biological influences on brain microstructure. The corresponding BMPAA scores were successfully calculated, offering novel measures of individual brain aging trajectories independent of these confounding covariates. However, a systematic parsing error during behavioral data extraction unfortunately prevented the planned analysis linking BMPAA scores to cognitive performance metrics. Nevertheless, this work successfully established a robust methodology for deriving brain-wide microstructural age acceleration scores that effectively disentangle the effects of aging from sex and environmental factors in a long-lived species. While the ultimate brain-behavior association could not be tested due to this technical limitation, the derived BMPAA metric represents a promising novel biomarker for future investigations into the neural underpinnings of cognitive resilience and healthy aging.

Subjects:	q-bio.NC; q-bio.QM
Cite as:	PX:2508.00046