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Record W4210374789 · doi:10.1016/j.nbd.2022.105652

Cerebrospinal fluid mutant huntingtin is a biomarker for huntingtin lowering in the striatum of Huntington disease mice

2022· article· en· W4210374789 on OpenAlexafffund
Nicholas S. Caron, Raúl Baños, Amirah E.-E. Aly, Yuanyun Xie, Seung‐Hyun Ko, Nalini Potluri, Hailey Findlay Black, Lisa M. Anderson, Benjamin Gordon, Amber L. Southwell, Michael R. Hayden

Bibliographic record

VenueNeurobiology of Disease · 2022
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsPacific Centre for Reproductive MedicineBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchNational Institute of Neurological Disorders and StrokeHuntington's Disease Society of America
KeywordsHuntingtinStriatumHuntington's diseaseHuntingtin ProteinBiologyNeurodegenerationPolyglutamine tractNeuroscienceMedicineDiseasePathologyDopamine

Abstract

fetched live from OpenAlex

Huntington disease (HD) is a neurodegenerative disease caused by a trinucleotide repeat expansion in the HTT gene encoding an elongated polyglutamine tract in the huntingtin (HTT) protein. Expanded mutant HTT (mHTT) is toxic and leads to regional atrophy and neuronal cell loss in the brain, which occurs earliest in the striatum. Therapeutic lowering of mHTT in the central nervous system (CNS) has shown promise in preclinical studies, with multiple approaches currently in clinical development for HD. Quantitation of mHTT in the cerebrospinal fluid (CSF) is being used as a clinical pharmacodynamic biomarker of target engagement in the CNS. We have previously shown that the CNS is a major source of mHTT in the CSF. However, little is known about the specific brain regions and cell types that contribute to CSF mHTT. Therefore, a better understanding of the origins of CSF mHTT and whether therapies targeting mHTT in the striatum would be expected to be associated with significant lowering of mHTT in the CSF is needed. Here, we use complementary pharmacological and genetic-based approaches to either restrict expression of mHTT to the striatum or selectively deplete mHTT in the striatum to evaluate the contribution of this brain region to mHTT in the CSF. We show that viral expression of a mHTT fragment restricted to the striatum leads to detectable mHTT in the CSF. We demonstrate that targeted lowering of mHTT selectively in the striatum using an antisense oligonucleotide leads to a significant reduction of mHTT in the CSF of HD mice. Furthermore, using a transgenic mouse model of HD that expresses full length human mHTT and wild type HTT, we show that genetic inactivation of mHTT selectively in the striatum results in a significant reduction of mHTT in the CSF. Taken together, our data supports the conclusion that the striatum contributes sufficiently to the pool of mHTT in the CSF that therapeutic levels of mHTT lowering in the striatum can be detected by this measure in HD mice. This suggests that CSF mHTT may represent a pharmacodynamic biomarker for therapies that lower mHTT in the striatum.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.031
GPT teacher head0.277
Teacher spread0.246 · 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 designBench or experimental
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

Citations30
Published2022
Admission routes2
Has abstractyes

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