Detailed Analysis of <scp><i>ITPR1</i></scp> Missense Variants Guides Diagnostics and Therapeutic Design
Bibliographic record
Abstract
BACKGROUND: R1), a critical player in cerebellar intracellular calcium signaling. Pathogenic missense variants in ITPR1 cause congenital spinocerebellar ataxia type 29 (SCA29), Gillespie syndrome (GLSP), and severe pontine/cerebellar hypoplasia. The pathophysiological basis of the different phenotypes is poorly understood. OBJECTIVES: We aimed to identify novel SCA29 and GLSP cases to define core phenotypes, describe the spectrum of missense variation across ITPR1, standardize the ITPR1 variant nomenclature, and investigate disease progression in relation to cerebellar atrophy. METHODS: Cases were identified using next-generation sequencing through the Deciphering Developmental Disorders study, the 100,000 Genomes project, and clinical collaborations. ITPR1 alternative splicing in the human cerebellum was investigated by quantitative polymerase chain reaction. RESULTS: -binding domain, the carbonic anhydrase 8 (CA8)-binding region, and the C-terminal transmembrane channel domain. Variants outside these domains were of questionable clinical significance. Standardized transcript annotation, based on our ITPR1 transcript expression data, greatly facilitated analysis. Genotype-phenotype associations were highly variable. Importantly, while cerebellar atrophy was common, cerebellar volume loss did not correlate with symptom progression. CONCLUSIONS: This dataset represents the largest cohort of patients with ITPR1 missense variants, expanding the clinical spectrum of SCA29 and GLSP. Standardized transcript annotation is essential for future reporting. Our findings will aid in diagnostic interpretation in the clinic and guide selection of variants for preclinical studies. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".