Latent class analysis of psychotic-affective disorders with data-driven plasma proteomics.

ABSTRACT: Data-driven approaches to subtype transdiagnostic samples are important for understanding heterogeneity within disorders and overlap between disorders. Thus, this study was conducted to determine whether plasma proteomics-based clustering could subtype patients with transdiagnostic psychotic-affective disorder diagnoses. The study population included 504 patients with schizophrenia, bipolar disorder, and major depressive disorder and 160 healthy controls, aged 19 to 65 years. Multiple reaction monitoring was performed using plasma samples from each individual. Pathologic peptides were determined by linear regression between patients and healthy controls. Latent class analysis was conducted in patients after peptide values were stratified by sex and divided into tertile values. Significant

SUBMITTER: Rhee SJ 

PROVIDER: S-EPMC9902608 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature