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Record W4393289813 · doi:10.1016/j.ebiom.2024.105077

The genetic landscape and phenotypic spectrum of GAA-FGF14 ataxia in China: a large cohort study

2024· article· en· W4393289813 on OpenAlexafffundabout
Riwei Ouyang, Linlin Wan, David Pellerin, Zhe Long, Jian Hu, Qian Jiang, Chunrong Wang, Linliu Peng, Huirong Peng, Lang He, Rong Qiu, Junling Wang, Jifeng Guo, Lu Shen, Bernard Brais, Matt C. Danzi, Stephan Züchner, Beisha Tang, Zhao Chen, Hong Jiang

Bibliographic record

VenueEBioMedicine · 2024
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchNatural Science Foundation of Hunan ProvinceCentral South UniversityHunan Provincial Science and Technology DepartmentNational Natural Science Foundation of ChinaMinistry of Science and Technology of the People's Republic of ChinaKey Project of Research and Development Plan of Hunan ProvinceXiangya Hospital, Central South UniversityDevelopment and Reform Commission of Hunan Province
KeywordsAtaxiaPhenotypeGeneticsBiologyMedicineBioinformaticsEvolutionary biologyNeuroscienceGene

Abstract

fetched live from OpenAlex

BACKGROUND: An intronic GAA repeat expansion in FGF14 was recently identified as a cause of GAA-FGF14 ataxia. We aimed to characterise the frequency and phenotypic profile of GAA-FGF14 ataxia in a large Chinese ataxia cohort. METHODS: A total of 1216 patients that included 399 typical late-onset cerebellar ataxia (LOCA), 290 early-onset cerebellar ataxia (EOCA), and 527 multiple system atrophy with predominant cerebellar ataxia (MSA-c) were enrolled. Long-range and repeat-primed PCR were performed to screen for GAA expansions in FGF14. Targeted long-read and whole-genome sequencing were performed to determine repeat size and sequence configuration. A multi-modal study including clinical assessment, MRI, and neurofilament light chain was conducted for disease assessment. FINDINGS: alleles were identified. The clinical phenotypes of the 19 positive and possible positive cases covered LOCA phenotype, EOCA phenotype and MSA-c phenotype. Five of six patients with EOCA phenotype were found to have another genetic disorder. The NfL levels of patients with EOCA and MSA-c phenotypes were significantly higher than patients with LOCA phenotype and age-matched controls (p < 0.001). NfL levels of pre-ataxic GAA-FGF14 positive individuals were lower than pre-ataxic SCA3 (p < 0.001) and similar to controls. INTERPRETATION: alleles and co-occurrence with other acquired or hereditary diseases may contribute to phenotypic variation and different progression. FUNDING: This study was funded by the National Key R&D Program of China (2021YFA0805200 to H.J.), the National Natural Science Foundation of China (81974176 and 82171254 to H.J.; 82371272 to Z.C.; 82301628 to L.W.; 82301438 to Z.L.; 82201411 to L.H.), the Innovation Research Group Project of Natural Science Foundation of Hunan Province (2020JJ1008 to H.J.), the Key Research and Development Program of Hunan Province (2020SK2064 to H.J.), the Innovative Research and Development Program of Development and Reform Commission of Hunan Province to H.J., the Natural Science Foundation of Hunan Province (2024JJ3050 to H.J.; 2022JJ20094 and 2021JJ40974 to Z.C.; 2022JJ40783 to L.H.; 2022JJ40703 to Z.L.), the Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital, 2020LNJJ12 to H.J.), the Central South University Research Programme of Advanced Interdisciplinary Study (2023QYJC010 to H.J.) and the Science and Technology Innovation Program of Hunan Province (2022RC1027 to Z.C.). D.P. holds a Fellowship award from the Canadian Institutes of Health Research (CIHR).

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations37
Published2024
Admission routes3
Has abstractyes

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