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Record W2565686091 · doi:10.1016/s1525-0016(16)33991-0

382. Osteopetrosis: An Unusual Presentation of a Rare Disease as a Candidate for Gene Therapy

2015· article· en· W2565686091 on OpenAlexaff
Alan O’Brien, Joerg Krueger, Lucie Dupuis, Irina Voronov, Pekka Kannus, Ronald D. Cohn, Roberto Mendoza‐Londono

Bibliographic record

VenueMolecular Therapy · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsOsteopetrosisTCIRG1MedicineBone resorptionOsteoclastLoss functionPathologyInternal medicinePediatricsImmunologyPhenotypeGeneticsBiologyGene

Abstract

fetched live from OpenAlex

Osteopetrosis refers to a group of genetic disorders characterized by increased bone density due to failure of osteoclastic bone resorption. Infantile malignant osteopetrosis (IMO; MIM 259700) is the most severe form of the disease. It presents in early infancy and can lead to significant morbidity and death if untreated. Osteosclerotic changes lead to progressive blindness and hearing loss, bone marrow failure, hypocalcemic seizures and pathological fractures. The majority of cases of IMO are due to complete loss-of-function mutations in TCIRG1, which codes for a subunit of the osteoclast vacuolar proton pump (V-ATPase). Currently, hematopoietic stem cell transplantation (HSCT) is the only curative treatment, but can be associated with significant morbidity and toxicity and has a varying success rate depending on the donor source. We present a 9 year old boy from Pakistan in whom increased bone mass and x-ray changes typical of osteopetrosis were found incidentally at age 7. His prior medical history was mostly unremarkable, except for strabismus and dentition problems. Sequence analysis of the TCIRG1 gene revealed a homozygous c.630G>A mutation that changes the last nucleotide of exon 6 and is predicted to result in aberrant splicing, possibly creating a hypomorphic allele and explaining his milder phenotype. Detailed phenotypic evaluation of the patient after diagnosis showed normal bone marrow function, but identified visual impairment with impingement of the optic nerves, and hearing loss. Given the patient's milder phenotype, the morbidity and mortality of HSCT and uncertainty about his speed of disease progression we decided to not pursue HSCT at this point. Thus, novel therapeutic options should be contemplated. Given that the mutation likely results in a splicing defect, this patient could potentially benefit from splicemodifying drugs that are under development. Moreover, we suggest that this patient's clinical presentation makes him an ideal candidate for a trial of gene therapy. Indeed, considering the mortality and morbidity of IMO as well as the established role of HSCT as curative treatment, a randomized clinical trial for the severe form of the disease is not ethically acceptable. There have been encouraging steps towards establishing lentiviral-mediated gene transfer of TCIRG1 as a potential treatment of osteopetrosis in humans. Furthermore, considering the point mutation found in our patient, gene editing technologies, such as CRISPR/Cas9 could allow us to correct this defect by ex-vivo editing of affected CD34+ cells and subsequent re-engraftment. Finally, we suggest that patients with a similarly mild phenotype and mutations in TCIRG1 would be ideal candidates for a clinical trial for gene therapy of osteopetrosis and could be gathered through an international consortium.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.005

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 head0.024
GPT teacher head0.291
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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