ArticleExpert opinion on orphan drugs2019
Progress in understanding Friedreich's ataxia using human induced pluripotent stem cells.
Article in Expert opinion on orphan drugs, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Frataxin deficiency drives cardiac dysfunction and transcriptional dysregulation in Friedreich ataxia iPSC model.Cell death & disease · 2026Article
- Human pluripotent stem cell models of Friedreich's ataxia: innovations, considerations, and future perspectives.Stem cell research & therapy · 2026Review
- Design and validation of cell-based potency assays for frataxin supplementation treatments.Molecular therapy. Methods & clinical development · 2024Article
- Perspectives on current models of Friedreich's ataxia.Frontiers in cell and developmental biology · 2022Article
- Modelling Mitochondrial Disease in Human Pluripotent Stem Cells: What Have We Learned?International journal of molecular sciences · 2021Review
- Patient-derived iPSC modeling of rare neurodevelopmental disorders: Molecular pathophysiology and prospective therapies.Neuroscience and biobehavioral reviews · 2021Review
- Genome Editing in iPSC-Based Neural Systems: From Disease Models to Future Therapeutic Strategies.Frontiers in genome editing · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
introductionFriedreich's ataxia (FRDA) is an autosomal recessive multisystem disease mainly affecting the peripheral and central nervous systems, and heart. FRDA is caused by a GAA repeat expansion in the first intron of the frataxin (FXN) gene, that leads to reduced expression of FXN mRNA and frataxin protein. Neuronal and cardiac cells are primary targets of frataxin deficiency and generating models via differentiation of induced pluripotent stem cells (iPSCs) into these cell types is essential for progress towards developing therapies for FRDA. AREAS COVERED: This review is focused on modeling FRDA using human iPSCs and various iPSC-differentiated cell types. We emphasized the importance of patient and corrected isogenic cell line pairs to minimize effects caused by biological variability between individuals. EXPERT OPINION: The versatility of iPSC-derived cellular models of FRDA is advantageous for developing new therapeutic strategies, and rigorous testing in such models will be critical for approval of the first treatment for FRDA. Creating a well-characterized and diverse set of iPSC lines, including appropriate isogenic controls, will facilitate achieving this goal. Also, improvement of differentiation protocols, especially towards proprioceptive sensory neurons and organoid generation, is necessary to utilize the full potential of iPSC technology in the drug discovery process.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.