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Modern molecular genetics has revolutionized gene discovery, genetic diagnoses, and precision medicine yet many patients remain unable to benefit from these advances as disease-causing variants remain elusive for up to half of Mendelian genetic disorders. Patient-derived induced pluripotent stem (iPS) cells and transcriptomics were used to identify the fate of unsolved ABCA4 alleles in patients with Stargardt disease. Multiple independent iPS lines were generated from skin biopsies of three patients with Stargardt disease harboring a single identified pathogenic ABCA4 variant. Derived retinal pigment epithelial cells (dRPE) from a normal control and patient cells were subjected to RNA-Seq on the Novaseq6000 platform, analyzed using DESeq2 with calculation of allele specific imbalance from the pathogenic or a known linked variant. Protein analysis was performed using the automated Simple Western system. Nine dRPE samples were generated, with transcriptome analysis on eight. Allele-specific expression indicated normal transcripts expressed from splice variants albeit at low levels, and missense transcripts expressed at near-normal levels. Corresponding protein was not easily detected. Patient phenotype correlation indicated missense variants expressed at high levels have more deleterious outcomes. Transcriptome analysis suggests mitochondrial membrane biodynamics and the unfolded protein response pathway may be relevant in Stargardt disease. Patient-specific iPS-derived RPE cells set the stage to assess non-expressing variants in difficult-to-detect genomic regions using easily biopsied tissue. This "Disease in a Dish" approach is likely to enhance the ability of patients to participate in and benefit from clinical trials while providing insights into perturbations in RPE biology.

Citation

Anna Matynia, Jun Wang, Sangbae Kim, Yumei Li, Anupama Dimashkie, Zhichun Jiang, Jane Hu, Samuel P Strom, Roxana A Radu, Rui Chen, Michael B Gorin. Assessing Variant Causality and Severity Using Retinal Pigment Epithelial Cells Derived from Stargardt Disease Patients. Translational vision science & technology. 2022 Mar 02;11(3):33

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PMID: 35348597

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