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Record W4401208268 · doi:10.3390/genes15080999

Recent Progress in Gene-Targeting Therapies for Spinal Muscular Atrophy: Promises and Challenges

2024· review· en· W4401208268 on OpenAlexafffund
Umme Sabrina Haque, Toshifumi Yokota

Bibliographic record

VenueGenes · 2024
Typereview
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsMuscular Dystrophy CanadaUniversity of Alberta
FundersFaculty of Medicine and Dentistry, University of AlbertaMuscular Dystrophy CanadaUniversity of AlbertaCanadian Institutes of Health ResearchWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsSpinal muscular atrophyMedicineNeuroscienceGenetic enhancementGeneBioinformaticsBiologyComputational biologyGenetics

Abstract

fetched live from OpenAlex

Spinal muscular atrophy (SMA) is a severe genetic disorder characterized by the loss of motor neurons, leading to progressive muscle weakness, loss of mobility, and respiratory complications. In its most severe forms, SMA can result in death within the first two years of life if untreated. The condition arises from mutations in the SMN1 (survival of motor neuron 1) gene, causing a deficiency in the survival motor neuron (SMN) protein. Humans possess a near-identical gene, SMN2, which modifies disease severity and is a primary target for therapies. Recent therapeutic advancements include antisense oligonucleotides (ASOs), small molecules targeting SMN2, and virus-mediated gene replacement therapy delivering a functional copy of SMN1. Additionally, recognizing SMA’s broader phenotype involving multiple organs has led to the development of SMN-independent therapies. Evidence now indicates that SMA affects multiple organ systems, suggesting the need for SMN-independent treatments along with SMN-targeting therapies. No single therapy can cure SMA; thus, combination therapies may be essential for comprehensive treatment. This review addresses the SMA etiology, the role of SMN, and provides an overview of the rapidly evolving therapeutic landscape, highlighting current achievements and future directions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.148
GPT teacher head0.411
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations20
Published2024
Admission routes2
Has abstractyes

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