White matter brain aging in relationship to schizophrenia and its cognitive deficit.

ABSTRACT: We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition. A feature selection procedure was first employed to choose fractional anisotropy values in 34 of 43 white fiber tracts. Using these features, a machine learning model was trained based on a trai

SUBMITTER: Wang J 

PROVIDER: S-EPMC8222174 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature