Parkinson's disease progression: Increasing expression of an invariant common core subnetwork.

ABSTRACT: Notable success has been achieved in the study of neurodegenerative conditions using reduction techniques such as principal component analysis (PCA) and sparse inverse covariance estimation (SICE) in positron emission tomography (PET) data despite their widely differing approach. In a recent study of SICE applied to metabolic scans from Parkinson's disease (PD) patients, we showed that by using PCA to prespecify disease-related partition layers, we were able to optimize maps of functional metabolic connectivity within the relevant networks. Here, we show the potential of SICE, enhanced by disease-specific subnetwork partitions, to identify key regional hubs and their connections, and track their associations in PD patients with increasing disease duration. This approach enabled the identif

SUBMITTER: Spetsieris PG 

PROVIDER: S-EPMC10491857 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature