Sean F. Eddy

The paper generates disease-specific genetic effect maps on the blood transcriptome for five glomerular diseases using whole genome and transcriptome sequencing data from the CureGN cohort.

This study identifies early glomerular changes and gene expression patterns in Alport syndrome, showing ER stress and four genes as key drivers of disease before proteinuria, and highlights potential therapeutic targets.

The paper creates a high-resolution cellular atlas of healthy and injured kidney cell states and niches using single-cell and spatial technologies, identifying molecular signatures and pathways related to kidney injury.

MultiPLIER uses transfer learning from large public data to improve analysis of small rare disease datasets by capturing systemic biological features.

The paper identifies a transcriptional signature of glomerular disease using single-cell profiling of human kidney organoids and validates it in disease cohorts.

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.