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Record W4406313043 · doi:10.1038/s41525-024-00453-5

Pre-T cell receptor-α immunodeficiency detected exclusively using whole genome sequencing

2025· article· en· W4406313043 on OpenAlexafffund
Daniele Merico, Nigel Sharfe, Harjit Dadi, Bhooma Thiruvahindrapuram, Jill de Rijke, Zakia Dahi, Mehdi Zarrei, Abdulrahman Al Ghamdi, Azhar Al Shaqaq, Linda Vong, Stephen W. Scherer, Chaim M. Roifman

Bibliographic record

Venuenpj Genomic Medicine · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersImmunodeficiency Canada
KeywordsT-cell receptorExome sequencingWhole genome sequencingBiologyT cellImmunodeficiencyGenomeGeneticsDNA sequencingComputational biologyGeneCellMutationImmune system

Abstract

fetched live from OpenAlex

Maturation of αβ lineage T cells in the thymus relies on the formation and cell surface expression of a pre-T cell receptor (TCR) complex, composed of TCRβ chain and pre-TCRα (pTCRα) chain heterodimers, giving rise to a diverse T cell repertoire. Genetic aberrations in key molecules involved in T cell development lead to profound T cell immunodeficiency. Definitive genetic diagnosis guides treatment choices and counseling. In this study, we describe the role of whole genome sequencing (WGS) in providing a definitive diagnosis for a child with T cell deficiency, where targeted panel sequencing of SCID genes and whole exome sequencing had failed. A novel homozygous 8kb deletion in PTCRA, encoding pTCRα, was identified. To date, use of WGS remains restricted and for many geographical regions, is clinically unavailable.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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 designCase report
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

Citations1
Published2025
Admission routes2
Has abstractyes

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Same venuenpj Genomic MedicineSame topicImmunodeficiency and Autoimmune DisordersFrench-language works237,207