GSE212256: Multidimensional analysis and therapeutic development using patient iPSC-derived disease models of Wolfram syndrome

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Info Studies were incorporated in a barcode, matrix, feature format. This format can be found on the 10x Genomics website for processing of single cell studies to obtain the gene expression matrices. For each study, the metadata incorporated in GEO were manually curated into profiles and the samples were separated based on applicable groups and conditions. The expression data from the cells for the samples within the same profile and condition were aggregated into an expression matrix with the cell barcodes having the sample name appended to it to ensure unique cell names.

Description (from GEO)

Submission Date: Aug 29, 2022

Summary: Wolfram syndrome is a rare genetic disorder largely caused by pathogenic variants in the WFS1 gene and manifested by diabetes mellitus, optic nerve atrophy, and progressive neurodegeneration. Recent genetic and clinical findings have revealed Wolfram syndrome as a spectrum disorder. Therefore, a genotype-phenotype correlation analysis is needed for diagnosis and therapeutic development. Here, we focus on the WFS1 c.1672C>T, p.R558C variant which is highly prevalent in the Ashkenazi-Jewish population. Clinical investigation indicates that subjects carrying the homozygous WFS1 c.1672C>T, p.R558C variant show mild forms of Wolfram syndrome phenotypes. Expression of WFS1 p.R558C is more stable compared to the other known recessive pathogenic variants associated with Wolfram syndrome. Human induced pluripotent stem cell (iPSC)-derived islets (SC-islets) homozygous for WFS1 c.1672C>T variant recapitulate genotype-related Wolfram syndrome phenotypes. Enhancing residual WFS1 function by a combination treatment of chemical chaperones mitigates detrimental effects caused by the WFS1 c.1672C>T, p.R558C variant and increases insulin secretion in SC-islets. Thus, the WFS1 c.1672C>T, p.R558C variant causes a mild form of Wolfram syndrome phenotypes, which can be remitted with a combination treatment of chemical chaperones. We demonstrate that our patient iPSC-derived disease model provides a valuable platform for further genotype-phenotype analysis and therapeutic development for Wolfram syndrome.

GEO Accession ID: GSE212256

PMID: 36134655

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Info Preprocessing and downstream analysis were computed using the scanpy Python library and the steps of processing followed the Seurat vignette. Cells and genes with no expression or very low expression were removed from the dataset based on a predefined threshold. The data was then normalized across the expression within the cells and log normalized. The top 2000 highly variable genes were extracted to be used for downstream analysis. For each of these aggregated data matrices, the clusters were computed using the leiden algorithm. Scanpy was then used to compute the PCA, t-SNE, and UMAPs. The points in the plots are labelled by their corresponding cell type labels. The cell type labels were computed using the wilcoxon method as the differential gene expression method. The top 250 genes were then used for enrichment analysis against the CellMarker library in order to determine the most appropriate cell type label with the lowest p-value.
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Info Differential gene expression can be computed for a single cell type labeled group of cells vs the rest. These include wilcoxon, DESeq2, or characteristic direction.
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