Multimodal quantitative MRI reveals age-related biophysical alterations in the human brain across the adult lifespan

Understanding how brain tissue properties change with age is crucial for identifying early markers of neurodegenerative disease. However, the biophysical alterations and their molecular bases remain poorly understood. Quantitative MRI (qMRI) offers non-invasive insight into brain tissue properties. In this study, we employed three qMRI metrics-quantitative susceptibility mapping (QSM), longitudinal relaxation rate (R1), and effective transverse relaxation rate (R2*)-to investigate age-related brain changes across the adult lifespan. Applying linear and nonlinear modeling, we observed distinct patterns of cross-sectional age-related biophysical alterations (early, late, and inverted-U patterns) in the human brain. Predictive modeling identified subcortical and thalamic regions as key contributors to age estimation. Integrating transcriptomic data revealed that these imaging-derived patterns spatially co-localize with gene expression signatures enriched in neurodevelopmental and neurodegenerative pathways. Our study advances current understanding by integrating multimodal qMRI age-related patterns and transcriptomics, uncovering distinct aging patterns, candidate age-sensitive imaging features that warrant further validation, and their potential molecular underpinnings.