Katalin Suszták

The paper identifies DNA methylation changes linked to cumulative hyperglycaemia in type 1 diabetes and links some to diabetic kidney disease through Mendelian randomization.

This study identifies 36 genetic loci associated with recurrent UTIs and highlights PSCA as a key gene involved in urinary epithelial defense against bacteria.

UTOPIA quantifies confidence in virtual spatial transcriptomics predictions across scales, improving reliability and preventing false conclusions.

Pixel2Gene improves spatial gene expression reconstruction and prediction by integrating histology images with spatial transcriptomics data.

The paper identifies platform-dependent effects of APOL1 variants on plasma levels measured by different proteomic technologies.

HistoSweep improves tissue quality control in gigapixel images by removing artifacts and preserving biologically relevant structures, enhancing analysis accuracy in digital pathology and spatial omics.

The paper identifies splicing variants in human kidney tissue associated with kidney function and cardiovascular-kidney-metabolic syndrome traits using long-read RNA sequencing and QTL analysis.

Nephrobase Cell+ is a kidney-specific foundation model that outperforms existing models in single-cell analysis, cross-species transfer, and batch effect correction.

S2Omics automatically selects regions of interest from histology images to maximize molecular information content in spatial omics experiments, improving reproducibility and downstream biological discovery.

The paper maps human kidney development using single-cell RNA sequencing and spatial transcriptomics, revealing fate decisions influenced by the local microenvironment.

This study shows that an ENL mutation disrupts kidney development by altering gene regulation, leading to developmental defects and early death in mice, and suggests potential therapeutic strategies.

This study identifies TET2 and INO80 as key genes in kidney disease pathogenesis through GWAS, single-cell analysis, and mouse models, showing their role in DNA damage response and disease progression.

The paper identifies lipidomic biomarkers and therapeutic targets in sepsis patients, including those with COVID-19, and develops an interactive network analysis tool for multiomic data exploration.

This paper introduces CellANOVA, a statistical model to recover biological signals lost during single-cell data integration by distinguishing batch effects from true biological variation.

Multi-omic and spatial profiling of 81 human kidney samples resolves four tissue microenvironments; the fibrotic one's gene signature is reported to beat histopathology at predicting outcome.

The paper maps genetic variants to cell types in the kidney to identify disease mechanisms and drug targets.

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 maps the regulatory landscape of the mouse kidney at single cell resolution, identifying key transcription factors and regulatory circuits, and linking variants to kidney disease.

This study identifies the cellular origins of perivascular adipose tissue using single-cell transcriptomics, fate mapping, and adipogenesis assays, revealing fibroblastic and smooth muscle progenitors.

ItClust improves clustering and cell type classification in scRNA-seq by using iterative transfer learning with neural networks, outperforming existing methods across diverse datasets.

This study shows that mesenchymal Gαq/11 signaling regulates TGFβ2 activation in response to stretch, which is critical for alveologenesis and lung homeostasis.

Multi-ethnic type 2 diabetes (T2D) meta-analysis of 228,499 cases and 1,178,783 controls finds 318 previously unreported loci, 804 expression-colocalized genes, and 13 SNP-by-T2D vascular-outcome interactions.

This paper introduces DESC, a deep learning method for single-cell clustering that improves accuracy and removes batch effects.

This study shows that Dnmt1 is critical for kidney development by maintaining methylation of transposable elements in Six2 progenitor cells, preventing their regression and ERV activation.

MuSiC deconvolves bulk RNA-seq data using single-cell RNA-seq reference to estimate cell type composition, outperforming existing methods in tissues with closely related cell types.

The paper uses allele-specific RNA imaging to show that allelic imbalances in tissues can result from transcriptional bursting and low mRNA abundance.

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