Richard A. Lafayette

This study characterizes transcriptomic and metabolomic profiles in human urine, identifying distinct cell type repertoires and metabolic signals compared to plasma.

The paper identifies high-risk nephrotic syndrome patients through transcriptome analysis and develops non-invasive biomarkers to predict disease progression.

The paper identifies shared molecular pathways between ANCA-associated vasculitis and nephrotic syndrome, highlighting JAK-STAT signaling as a potential therapeutic target.

The paper identifies eQTLs in glomerular and tubulointerstitial kidney tissues from nephrotic syndrome patients, finds tissue-specific eQTLs, and integrates them with a GWAS to identify associated genes.