The aging process does not occur uniformly across biological systems and organs, giving rise to the concept of “biological age” as distinct from chronological age. Among these, “brain age”-a metric derived from neuroimaging data-has emerged as a valuable indicator of brain health and aging. Deviations between brain age and chronological age have been linked to a range of neurological and psychiatric conditions, suggesting that brain age may serve as a useful biomarker for early detection and monitoring of such disorders.
This project aims to advance our understanding of brain age by investigating its relationship with other biological age markers derived from diverse modalities (e.g., ECG, heart MRI, DEXA, full-body MRI). We will explore how discrepancies in brain age correlate with health outcomes, lifestyle choices, metabolic health, cognitive performance, and psychological well-being. In addition, we intend to replicate findings from previous work by our group-conducted in smaller cohorts-regarding the association between brain age and conditions such as migraine, pain-related disorders, and psychotic disorders. A further goal is to explore novel approaches to brain age estimation, including multimodal imaging integration and the evaluation of how image acquisition parameters influence brain age predictions.
Objectives:
* To develop predictive models to calculate brain age and other biological ages obtained from different medical imaging and biomedical signal information.
* To use statistical methods to explore associations between brain age discrepancies and various health conditions, including migraine, pain-related disorders, and psychotic disorders.
* To examine the influence of lifestyle factors, health parameters, and image acquisition parameters on brain age.