A Prospective Treatment Option for Lysosomal Storage Diseases: CRISPR/Cas9 Gene Editing Technology for Mutation Correction in Induced Pluripotent Stem Cells
Bibliographic record
Abstract
Ease of design, relatively low cost and a multitude of gene-altering capabilities have all led to the adoption of the sophisticated and yet simple gene editing system: clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9). The CRISPR/Cas9 system holds promise for the correction of deleterious mutations by taking advantage of the homology directed repair pathway and by supplying a correction template to the affected patient's cells. Currently, this technique is being applied in vitro in human-induced pluripotent stem cells (iPSCs) to correct a variety of severe genetic diseases, but has not as of yet been used in iPSCs derived from patients affected with a lysosomal storage disease (LSD). If adopted into clinical practice, corrected iPSCs derived from cells that originate from the patient themselves could be used for therapeutic amelioration of LSD symptoms without the risks associated with allogeneic stem cell transplantation. CRISPR/Cas9 editing in a patient's cells would overcome the costly, lifelong process associated with currently available treatment methods, including enzyme replacement and substrate reduction therapies. In this review, the overall utility of the CRISPR/Cas9 gene editing technique for treatment of genetic diseases, the potential for the treatment of LSDs and methods currently employed to increase the efficiency of this re-engineered biological system will be discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".