LAUSR

BACKGROUND age-related neurovascular structural and functional impairment is a major aetiology of dementia and stroke in older people. There is no single marker representative of neurovascular biological age yet. OBJECTIVE this study aims to develop and validate a white matter hyperintensities (WMH)-based model for characterising individuals' neurovascular biological age. METHODS in this prospective single-site study, the WMH-based age-prediction model was constructed based on WMH volumes of 491 healthy participants (21-89 years). In the training dataset, the constructed linear-regression model with log-transformed WMH volumes showed well-balanced complexity and accuracy (root mean squared error, RMSE = 10.20 and mean absolute error, MAE = 7.76 years). This model of neurovascular age estimation was then applied to a middle-to-old aged testing dataset (n = 726, 50-92 years) as the testing dataset for external validation. RESULTS the established age estimator also had comparable generalizability with the testing dataset (RMSE = 7.76 and MAE = 6.38 years). In the testing dataset, the WMH-predicted age difference was negatively associated with visual executive function. Individuals with older predicted-age for their chronological age had greater cardiovascular burden and cardiovascular disease risks than individuals with normal or delayed predicted age. These associations were independent of chronological age. CONCLUSIONS our model is easy to use in clinical practice that helps to evaluate WMH severity objective to chronological age. Current findings support our WMH-based age measurement to reflect neurovascular health and have potential diagnostic and prognostic value for clinical or research purposes in age-related neurovascular disorders.