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Record W4210897276 · doi:10.1089/crispr.2021.0085

Insertion of the Icelandic Mutation (A673T) by Prime Editing: A Potential Preventive Treatment for Familial and Sporadic Alzheimer's Disease

2022· article· en· W4210897276 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe CRISPR Journal · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité Laval
FundersNational Institute on AgingCanadian Institutes of Health Research
KeywordsMutationAmyloid precursor proteinCRISPRGeneticsBiologyPopulationGeneAlzheimer's diseaseMolecular biologyDiseaseMedicinePathology

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is the result of abnormal processing of the amyloid precursor protein (APP) by β-secretase and γ-secretase, which leads to the formation of toxic β-amyloid peptides. The toxic β-amyloid peptides induce neuron death, memory problems, and AD development. Several APP mutations increase the risk of developing early-onset AD. However, the A673T mutation identified in the Icelandic population prevents AD development by reducing the cleavage of APP by β-secretase. In this study, we inserted the A673T mutation in human cells using the CRISPR prime editing (PE) technique. Repeated PE treatments resulted in the insertion of the A673T mutation in up to 49.2% of APP genes when a second nick was induced in the other DNA strand. When the protospacer adjacent motif used for PE was also mutated, up to 68.9% of the APP genes contained the protective A673T mutation. PE is a promising approach to introduce the A673T mutation precisely without mutating nearby nucleotides.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.007
GPT teacher head0.277
Teacher spread0.270 · 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