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Record W1939617308 · doi:10.1371/journal.pone.0127045

Alternating Hemiplegia of Childhood: Retrospective Genetic Study and Genotype-Phenotype Correlations in 187 Subjects from the US AHCF Registry

2015· article· en· W1939617308 on OpenAlex
Louis Viollet, Gustavo Glusman, Kelley J. Murphy, Tara Newcomb, Sandra P. Reyna, Matthew Sweney, B.E. Nelson, Frédérick Andermann, Eva Andermann, Gyula Acsádi, Richard L. Barbano, Candida Brown, Mary E. Brunkow, Harry T. Chugani, Sarah Cheyette, Abigail Collins, Suzanne D. DeBrosse, David J. Galas, Jennifer Friedman, Lee Hood, Chad D. Huff, Lynn B. Jorde, Mary D. King, Bernie LaSalle, Richard J. Leventer, Aga Lewelt, Mylynda Massart, Mario Merida, Louis J. Ptáček, Jared C. Roach, Robert S. Rust, Francis Renault, Terry D. Sanger, Márcio A Sotero de Menezes, Rachel B. Tennyson, Peter Uldall, Yue Zhang, Mary L. Zupanc, Winnie Xin, Kenneth Silver, Kathryn J. Swoboda

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.

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of General Medical SciencesUniversité du LuxembourgSyracuse University
KeywordsMissense mutationSanger sequencingMedicineMutationPhenotypeGenotypeGeneticsRetrospective cohort studyPediatricsBiologyInternal medicineGene

Abstract

fetched live from OpenAlex

Mutations in ATP1A3 cause Alternating Hemiplegia of Childhood (AHC) by disrupting function of the neuronal Na+/K+ ATPase. Published studies to date indicate 2 recurrent mutations, D801N and E815K, and a more severe phenotype in the E815K cohort. We performed mutation analysis and retrospective genotype-phenotype correlations in all eligible patients with AHC enrolled in the US AHC Foundation registry from 1997-2012. Clinical data were abstracted from standardized caregivers' questionnaires and medical records and confirmed by expert clinicians. We identified ATP1A3 mutations by Sanger and whole genome sequencing, and compared phenotypes within and between 4 groups of subjects, those with D801N, E815K, other ATP1A3 or no ATP1A3 mutations. We identified heterozygous ATP1A3 mutations in 154 of 187 (82%) AHC patients. Of 34 unique mutations, 31 (91%) are missense, and 16 (47%) had not been previously reported. Concordant with prior studies, more than 2/3 of all mutations are clusteredin exons 17 and 18. Of 143 simplex occurrences, 58 had D801N (40%), 38 had E815K(26%) and 11 had G947R (8%) mutations [corrected].Patients with an E815K mutation demonstrate an earlier age of onset, more severe motor impairment and a higher prevalence of status epilepticus. This study further expands the number and spectrum of ATP1A3 mutations associated with AHC and confirms a more deleterious effect of the E815K mutation on selected neurologic outcomes. However, the complexity of the disorder and the extensive phenotypic variability among subgroups merits caution and emphasizes the need for further studies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.354

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 head0.034
GPT teacher head0.265
Teacher spread0.231 · 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