Biology subjects

Sampson, M. G.

Publications and source records attributed to Sampson, M. G..

7 recordsLinked to original sources

bioRxiv2025

The landscape of allele-specific expression in human kidneys

Allele-specific expression (ASE), the preferential expression of one gene copy, is a key mechanism of genomic regulation. However, its role in human kidney disease remains poorly understood. In this study, we generated a high-quality, genome-wide ASE map using paired whole-genome sequencing and RNA-seq from microdissected glomerular (GLOM) and tubulointerstitial (TUBE) compartments of patients with proteinuric kidney disease. We showed that the majority of common ASE events were deterministic and sequence-mediated. We also found that diseased kidneys exhibited significantly more ASE in GLOM than TUBE, compared to controls. Unexpectedly, higher ASE in GLOM than TUBE was significantly associated with improved kidney disease outcomes in the disease cohort. Differential gene expression analysis suggested this was the result of an active, protective transcriptional response, including ribosome and ATP synthesis upregulation, rather than pathogenic dysregulation. Our work reveals glomerular ASE as a marker of adaptive transcriptional activity in proteinuric kidney disease.

genomics↗

bioRxiv2022

Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs

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. The use of an integrative prior resulted in higher resolution eQTLs illustrated by (1) smaller numbers of variants in credible sets with greater confidence, (2) increased enrichment of partitioned heritability for GWAS of two kidney traits, (3) an increased number of variants colocalized with the GWAS loci, and (4) enrichment of computationally predicted functional regulatory variants. A subset of variants and genes were validated experimentally in vitro and using a Drosophila nephrocyte model. More broadly, this study demonstrates that tissue-specific eQTL maps informed by single-nucleus open chromatin data have enhanced utility for diverse downstream analyses.

genomics↗

bioRxiv2022

Quality assessment and refinement of chromatin accessibility data using a sequence-based predictive model

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. We tested 886 samples with DNase-seq from the ENCODE/Roadmap projects to demonstrate that gkmQC can effectively identify high-quality samples underperforming owing to marginal read depths. Peaks identified in high-quality samples by gkmQC are more accurately aligned at functional regulatory elements, show greater enrichment of regulatory elements harboring functional variants from genome-wide association studies (GWAS), and explain greater heritability of phenotypes from their relevant tissues. Moreover, gkmQC can optimize the peak-calling threshold to identify additional peaks, especially for single-cell chromatin accessibility data as well as bulk data. Here we provide a standalone open-source toolkit (https://github.com/Dongwon-Lee/gkmQC) for such analyses and share improved regulatory maps using gkmQC. These resources will contribute to the functional interpretation of disease-associated regulatory genetic variation.

genomics↗

bioRxiv2021

Analyzing and Reconciling Colocalization and Transcriptome-wide Association Studies from the Perspective of Inferential Reproducibility

Transcriptome-wide association studies and colocalization analysis are popular computational approaches for integrating genetic association data from molecular and complex traits. They show the unique ability to go beyond variant-level genetic association evidence and implicate critical functional units, e.g., genes, in disease etiology. However, in practice, when the two approaches are applied to the same molecular and complex trait data, the inference results can be markedly different. This paper systematically investigates the inferential reproducibility between the two approaches through theoretical derivation, numerical experiments, and analyses of 4 complex trait GWAS and GTEx eQTL data. We identify two classes of inconsistent inference results. We find that the first class of inconsistent results may suggest an interesting biological phenomenon, i.e., horizontal pleiotropy; thus, the two approaches are truly complementary. The inconsistency in the second class can be understood and effectively reconciled. To this end, we propose a novel approach for locus-level colocalization analysis. We demonstrate that the joint TWAS and locus-level colocalization analysis improves specificity and sensitivity for implicating biological-relevant genes.

genetics↗

bioRxiv2020

DNA damage activates mTORC1 signaling in podocytes leading to glomerulosclerosis

DNA repair is essential for preserving genome integrity and ensuring cellular functionality and survival. Podocytes, post-mitotic glomerular epithelial cells, bear limited regenerative capacity, and their survival is indispensable to maintain the function of the kidneys filtration units. While podocyte depletion is a hallmark of the aging process and of many proteinuric kidney diseases, the underlying factors remain unclear. We investigated DNA repair in podocyte diseases by using a constitutive and an inducible podocyte-specific knockout mouse model for Ercc1, a multifunctional endonuclease cofactor involved in nucleotide excision repair (NER), interstrand crosslink (ICL) repair, and DNA double-strand break (DSB) repair. We assessed the consequences of Ercc1 loss in vivo, complemented by mechanistical in vitro studies of induced DNA damage in cultured podocytes. Furthermore, we characterized DNA damage-related alterations in mouse and human renal tissue of different ages as well as in patient biopsies with minimal change disease and focal segmental glomerulosclerosis. Podocyte-specific Ercc1 knockout resulted in accumulation of DNA damage with ensuing proteinuria, podocyte loss, glomerulosclerosis, renal insufficiency, and reduced lifespan. The response to genomic stress was different to the pattern reported in other cell types, as podocytes activated mTORC1 signaling upon DNA damage in vitro and in vivo. The induced mTORC1 activation was abrogated by inhibiting DNA damage response through DNA-PK and ATM kinases in vitro. Moreover, pharmacological inhibition of mTORC1 modulated the development of glomerulosclerosis in Ercc1-deficient mice. Perturbed DNA repair gene expression and genomic stress was also detected in podocytes of human focal segmental glomerulosclerosis, characterized by podocyte loss. Beyond that, DNA damage accumulation occurred in podocytes of healthy aging mice and humans. These findings reveal that genome maintenance is crucial for podocyte maintenance, linked to the mTORC1 pathway, and involved in the aging process as well as in the development of glomerulosclerosis, potentially serving as a therapeutic target in the future.

cell biology↗

bioRxiv2018

Inflammatory and JAK-STAT Pathways as Shared Molecular Targets for ANCA-Associated Vasculitis and Nephrotic Syndrome

BackgroundGlomerular diseases of the kidney are presently differentiated, diagnosed and treated according to conventional clinical or structural features. While etiologically diverse, these diseases share common clinical features including but not limited to reduced glomerular filtration rate, increased serum creatinine and proteinuria suggesting shared pathogenic mechanisms across diseases. Renal biopsies from patients with nephrotic syndrome (NS) or ANCA-associated vasculitis (AAV) were evaluated for molecular signals cutting across conventional disease categories as candidates for therapeutic targets.\n\nMethodsRenal biopsies were obtained from patients with NS (minimal change disease, focal segmental glomerulosclerosis, or membranous nephropathy) (n=187) or AAV (granulomatosis with polyangiitis or microscopic polyangiitis) (n=80) from the Nephrotic Syndrome Study Network (NEPTUNE) and the European Renal cDNA Bank. Transcriptional profiles were assessed for shared disease mechanisms.\n\nResultsIn the discovery cohort, 10-25% transcripts were differentially regulated versus healthy controls in both NS and AAV, >500 transcripts were shared across diseases. The majority of shared transcripts (60-77%) were validated in independent samples. Therapeutically targetable networks were identified, including inflammatory JAK-STAT signaling. STAT1 eQTLs were identified and STAT1 expression associated with GFR-based outcome. A transcriptional STAT1 activity score was generated from STAT1-regulated target genes which correlated with CXCL10 (p<0.001), a JAK-STAT biomarker, predictors of CKD progression, interstitial fibrosis (r=0.41, p<0.001), and urinary EGF (r=-0.51, p<0.001).\n\nConclusionAAV and NS caused from histopathologically distinct disease categories share common intra-renal molecular pathways cutting across conventional disease classifications. This approach provides a starting point for de novo drug development, and repurposing efforts in rare kidney diseases.

systems biology↗

bioRxiv2018

Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis

Chronic Kidney Disease (CKD) is a growing health burden currently affecting 10-15% of adults worldwide. Estimated glomerular filtration rate (eGFR) as a marker of kidney function is commonly used to diagnose CKD. Previous genome-wide association study (GWAS) meta-analyses of CKD and eGFR or related phenotypes have identified a number of variants associated with kidney function, but these only explain a fraction of the variability in kidney phenotypes attributed to genetic components. To extend these studies, we analyzed data from the Nord-Trondelag Health Study (HUNT), which is more densely imputed than previous studies, and performed a GWAS meta-analysis of eGFR with publicly available summary statistics, more than doubling the sample size of previous meta-analyses. We identified 147 loci (53 novel loci) associated with eGFR, including genes involved in transcriptional regulation, kidney development, cellular signaling, metabolism, and solute transport. Moreover, genes at these loci show enriched expression in urogenital tissues and highlight gene sets known to play a role in kidney function. In addition, sex-stratified analysis identified three regions (prioritized genes: PPM1J, MCL1, and SLC47A1) with more significant effects in women than men. Using genetic risk scores constructed from these eGFR meta-analysis results, we show that associated variants are generally predictive of CKD but improve detection only modestly compared with other known clinical risk factors. Collectively, these results yield additional insight into the genetic factors underlying kidney function and progression to CKD.

genomics↗