We excited to share our work "Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome" has been published in Nature Communications. The study aimed to learn more about the genetic causes of pediatric steroid-sensitive nephrotic syndrome (pSSNS). Researchers analyzed the genes of over 38,000 people, including 2,440 with the disease, and identified 12 genetic factors that contribute to the disease. These discoveries help expand our knowledge of the disease and contribute to understanding the underlying mechanisms of pSSNS.

We're thrilled to announce our newest publication on "Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs" has been released in Nature Communications. Our study aimed to uncover how specific genes are regulated in the kidney by identifying genomic variants that influence their expression, referred to as expression quantitative trait loci (eQTLs). Using samples from human kidney biopsies, we discovered 5371 GLOM and 9787 TUBE genes with at least one variant significantly associated with expression.

Overall, this study highlights the value of tissue-specific eQTL maps and open chromatin data for analyses, which enhances our understanding of kidney function.

Michelle McNulty and Matt Sampson were psyched to contribute to this paper on APOL1 regulation via RNA-editing led by Cristian Riella, David Friedman, and Martin Pollak. We analyzed APOL1 RNA-editing in the glomeruli of NEPTUNE patients to support their meticulous, in vitro insights.

Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional signals. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. We conducted a multi-population GWAS meta-analysis in 38,463 participants (2,440 cases) and population specific GWAS, discovering twelve significant associations (eight novel).

Apolipoprotein L1 (APOL1)-associated focal segmental glomerulosclerosis (FSGS) is the dominant form of FSGS in Black individuals. There are no targeted therapies for this condition, in part because the molecular mechanisms underlying APOL1's pathogenic contribution to FSGS are incompletely understood. Studying the transcriptomic landscape of APOL1 FSGS in patient kidneys is an important way to discover genes and molecular behaviors that are unique or most relevant to the human disease.

Expression quantitative trait locus (eQTL) studies illuminate genomic variants that regulate specific genes and contribute to fine-mapped loci discovered via genome-wide association studies (GWAS). Efforts to maximize their accuracy are ongoing. Using 240 glomerular (GLOM) and 311 tubulointerstitial (TUBE) micro-dissected samples from human kidney biopsies, we discovered 5,371 GLOM and 9,787 TUBE eQTLs by incorporating kidney single-nucleus open chromatin data and transcription start site distance as an “integrative prior” for Bayesian statistical fine mapping.

Chromatin accessibility assays are central to the genome-wide identification of gene regulatory elements associated with transcriptional regulation. However, the data have highly variable quality arising from several biological and technical factors. To surmount this problem, we use the predictability of open-chromatin peaks from DNA sequence-based machine-learning models to evaluate and refine chromatin accessibility data. Our framework, gapped k-mer SVM quality check (gkmQC), provides the quality metrics for a sample based on the prediction accuracy of the trained models.