ReviewPharmaceutics2023
Gene and Cellular Therapies for Leukodystrophies.
Review in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 9 citations in OpenAlex.
- Recent Developments in Lipid Nanoparticle-Mediated Delivery of Biotherapeutics and Gene Therapy Across the Blood-Brain Barrier.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026Review
- Preventing Parkinson's disease in the context of movement disorders: a narrative review of current evidence and future directions.Neurological research and practice · 2026Review
- Assessment of Potential Side Effects Related To RAB27A Gene Therapy in Stem Cells.Stem cell reviews and reports · 2026Article
- Pathologic and Therapeutic Schwann Cells.Cells · 2025Review
- Gene therapy for the leukodystrophies: From preclinical animal studies to clinical trials.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2024Review
- Correction of Griscelli Syndrome Type 2 causing mutations in theTurkish journal of biology = Turk biyoloji dergisi · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Leukodystrophies are a heterogenous group of inherited, degenerative encephalopathies, that if left untreated, are often lethal at an early age. Although some of the leukodystrophies can be treated with allogeneic hematopoietic stem cell transplantation, not all patients have suitable donors, and new treatment strategies, such as gene therapy, are rapidly being developed. Recent developments in the field of gene therapy for severe combined immune deficiencies, Leber's amaurosis, epidermolysis bullosa, Duchenne's muscular dystrophy and spinal muscular atrophy, have paved the way for the treatment of leukodystrophies, revealing some of the pitfalls, but overall showing promising results. Gene therapy offers the possibility for overexpression of secretable enzymes that can be released and through uptake, allow cross-correction of affected cells. Here, we discuss some of the leukodystrophies that have demonstrated strong potential for gene therapy interventions, such as X-linked adrenoleukodystrophy (X-ALD), and metachromatic leukodystrophy (MLD), which have reached clinical application. We further discuss the advantages and disadvantages of ex vivo lentiviral hematopoietic stem cell gene therapy, an approach for targeting microglia-like cells or rendering cross-correction. In addition, we summarize ongoing developments in the field of in vivo administration of recombinant adeno-associated viral (rAAV) vectors, which can be used for direct targeting of affected cells, and other recently developed molecular technologies that may be applicable to treating leukodystrophies in the future.
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.