Adults with systemic lupus exhibit distinct molecular phenotypes in a cross-sectional study.

ABSTRACT:

Background

The clinical and pathologic diversity of systemic lupus erythematosus (SLE) hinders diagnosis, management, and treatment development. This study addresses heterogeneity in SLE through comprehensive molecular phenotyping and machine learning clustering.

Methods

Adult SLE patients (n = 198) provided plasma, serum, and RNA. Disease activity was scored by modified SELENA-SLEDAI. Twenty-nine co-expression module scores were calculated from microarray gene-expression data. Plasma soluble mediators (n = 23) and autoantibodies (n = 13) were assessed by multiplex bead-based assays and ELISAs. Patient clusters were identified by machine learning combining K-means clustering and random forest analysis of co-expression module scores and soluble mediators.

SUBMITTER: Guthridge JM 

PROVIDER: S-EPMC7058913 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature