Matthias Kretzler

The paper integrates multiple single-cell and single-nucleus RNA-sequencing datasets to create a comprehensive Human Kidney Cell Atlas, identifying cell types, states, and disease-associated populations.

This paper introduces STORM, a statistical framework for analyzing spatial patterns in multi-omics data, demonstrating reliable performance in detecting spatial structures and supporting study design decisions.

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 uses single-cell RNA-sequencing and spatial transcriptomics to analyze myeloid cell dynamics in lupus nephritis, showing shifts in immune responses linked to disease progression.

This paper performs a cross-organ meta-analysis of single-cell transcriptomic data to identify shared and organ-specific gene expression programs in fibrotic diseases.

Volaria integrates coding and regulatory variation into gene-centered representations for disease outcome prediction using whole-genome sequencing data.

This study shows dapagliflozin reduces hypoxia-induced metabolic stress, cell death, and fibrosis in kidney organoids derived from human pluripotent stem cells.

The paper presents a multi-modal atlas of human kidney disease, identifying cellular and spatial mechanisms of injury resolution or failure and linking them to clinical outcomes.

This paper benchmarks multimodal single-cell data integration methods to improve kidney reference atlas quality by identifying adaptive states and rare cell types.

The paper analyzes glomerular transcriptomes to show APOL1 risk variants affect parietal epithelial cells in nephrotic patients, linking gene expression patterns to disease outcomes.

The paper uses ontologies to integrate clinical, pathological, and molecular kidney data for precision medicine analysis.

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 defines the chromatin landscape of healthy and injured kidney cells using multi-omics data, identifying regulatory elements and transcription factor networks involved in injury response.

The paper shows the APOL1 p.N264K variant reduces the risk of FSGS and kidney disease in individuals with G2 APOL1 risk alleles.

This study uses single-cell RNA sequencing to identify a mechanosensitive MRTF-SRF pathway in early diabetic nephropathy, validated in human datasets and ex vivo experiments.

The paper constructs a reference tissue atlas of the human kidney using multi-omics data to identify cell types, pathways, and genes across nephron segments and interstitium.

The paper develops a pipeline combining micro-dissection and long/short-read sequencing to identify compartment-specific isoforms in kidney tissue, finding distinct isoform expression in glomerular and tubulo-interstitial compartments.

The paper identifies differentially methylated loci in individuals with end-stage kidney disease due to diabetic kidney disease, linking them to key pathways and genes.

The paper identifies 100 distinct kidney cell clusters using Mux-Seq and scRNA-seq, revealing novel proximal tubular subsets and cell state transitions in the collecting duct.

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.

This study identifies 16 genome-wide significant loci associated with diabetic kidney disease, including a protective variant in the COL4A3 gene.

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.

This study uses single-cell transcriptomics to analyze human fetal kidney development, identifying 17 cell clusters and their lineage trajectories.

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.

This paper estimates narrow-sense heritability using identity-by-descent information in unrelated individuals and finds that IBD-based methods can capture rare variant contributions but are affected by stratification.

This paper establishes a protocol for preserving and analyzing single-cell transcriptomes from cryopreserved renal tissue and urine samples in lupus nephritis studies.