Association of Integrated Proteomic and Metabolomic Modules with Risk of Kidney Disease Progression

Background Proteins and metabolites play crucial roles in various biological functions and are frequently interconnected through enzymatic or transport processes. Methods We present an integrated analysis of 4091 proteins and 630 metabolites in the Chronic Renal Insufficiency Cohort study (N51708; average follow-up for kidney failure, 9.5 years, with 537 events). Proteins and metabolites were integrated using an unsupervised clustering method, and we assessed associations between clusters and CKD progression and kidney failure using Cox proportional hazards models. Analyses were adjusted for demographics and risk factors, including the eGFR and urine protein–creatinine ratio. Associations were identified in a discovery sample (random two thirds, n51139) and then evaluated in a replication sample (one third, n5569). Results We identified 139 modules of correlated proteins and metabolites, which were represented by their principal components. Modules and principal component loadings were projected onto the replication sample, which demonstrated a consistent network structure. Two modules, representing a total of 236 proteins and 82 metabolites, were robustly associated with both CKD progression and kidney failure in both discovery and validation samples. Using gene set enrichment, several transmembrane-related terms were identified as overrepresented in these modules. Transmembrane–ephrin receptor activity displayed the largest odds (odds ratio513.2, P value 5 5.5310²⁵). A module containing CRIM1 and NPNT expressed in podocytes demonstrated particularly strong associations with kidney failure (P value 5 2.6310²⁵). Conclusions This study demonstrates that integration of the proteome and metabolome can identify functions of pathophysiologic importance in kidney disease.