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Novel human cellular model of CDA IV enables comprehensive analysis revealing molecular basis of disease phenotype.

GSE226782 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2024/04/29 Platform GPL24676
Summary
Red blood cell disorders can result in severe anemia. One such disease, congenital dyserythropoietic anemia IV (CDA IV) is caused by heterozygous mutation E325K in the transcription factor KLF1. However, studying the molecular basis of CDA IV is severely impeded by paucity of suitable and adequate quantities of material from anaemic patients and rarity of the disease. We therefore took a novel approach, creating a human cellular disease model system for CDA IV, which accurately recapitulates the disease phenotype. Next, using comparative proteomics we reveal extensive distortion of the proteome and a wide range of disordered biological processes in CDA IV erythroid cells. These include down-regulated pathways governing cell cycle, chromatin separation, DNA repair, cytokinesis, membrane trafficking and global transcription, and upregulated networks governing mitochondria biogenesis. The diversity of such pathways elucidates the spectrum of phenotypic abnormalities that occur with CDA IV and impairment to erythroid cell development and survival, collectively explaining the CDA IV disease phenotype. The data also reveal far more extensive involvement of KLF1 in previously assigned biological processes, along with novel roles in the regulation of intracellular processes not previously attributed to this transcription factor. Overall, the data demonstrate the power of such a model cellular system to unravel the molecular basis of disease and how studying effects of a rare mutation can reveal fundamental biology.
Published in
A novel human cellular model of CDA IV enables comprehensive analysis revealing the molecular basis of the disease phenotype
Ferrer-Vicens I, Ferguson DCJ, Wilson MC et al. · Blood 2023 · PMID 37084386 · doi:10.1182/blood.2022018735
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Also filed as BioProject PRJNA941791 and SRA study SRP426043. Searching any of these in the dataset finder brings you back here.

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