<p>Identification of genetic variants associated with skeletal muscle function deficit in childhood acute lymphoblastic leukemia survivors</p>
Bibliographic record
Abstract
Identification of genetic variants associated with skeletal muscle function deficit in childhood acute lymphoblastic leukemia survivors Geneviève Nadeau,1 Erika Ouimet-Grennan,1 Michelle Aaron,1 Simon Drouin,2 Laurence Bertout,2 Albert Shalmiev,2 Patrick Beaulieu,2 Pascal St-Onge,2 Louis-Nicolas Veilleux,3 Frank Rauch,3 Kateryna Petrykey,1,2 Caroline Laverdière,1–2,4 Daniel Sinnett,1–2,4 Nathalie Alos,1–2,5 Maja Krajinovic1–2,41Department of Medicine, University of Montreal, Montreal, QC, Canada; 2Sainte-Justine University Hospital Research Centre, Montreal, QC, Canada; 3Division of paediatrics, Montreal Shriners Hospital for Children, Montreal, QC, Canada; 4Division of Hemato-Oncology, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; 5Division of Endocrinology, Sainte-Justine University Hospital Centre, Montreal, QC, CanadaBackground: Although 80% of childhood acute lymphoblastic leukemia (ALL) cases are cured with current treatment protocols, exposure to chemotherapeutics or radiation therapy during a vulnerable period of child development has been associated with a high frequency of late adverse effects (LAE). Previous observations suggest important skeletal muscle size, density and function deficits in ALL survivors.Purpose: Given that only a fraction of all patients will suffer from this particular complication, we investigated whether it could be predicted by genetic markers. Patients and methods: We analysed associations between skeletal muscle force (Fmax) and power (Pmax) and germline genetic variants from 1039 genes derived through whole-exome sequencing. Top-ranking association signals retained after correction for multiple testing were confirmed through genotyping, and further analysed through stratified analyses and multivariate models. Results: Our results show that skeletal muscle function deficit is associated with two common single nucleotide polymorphisms (SNPs) (rs2001616DUOX2, P=0.0002 (Pmax) and rs41270041ADAMTS4, P=0.02 (Fmax)) and two rare ones located in the ALOX15 gene (P=0.001 (Pmax)). These associations were further modulated by sex, body mass index and risk groups, which reflected glucocorticoid dose and radiation therapy (P≤0.02). Conclusion: Occurrence of muscle function deficit in childhood ALL is thus strongly modulated by variations in the DUOX2, ADAMTS4 and ALOX15 genes, which could lead to personalized prevention strategies in childhood ALL survivors.Keywords: acute lymphoblastic leukemia, late adverse effects, skeletal muscle deficit, genetic association study, whole exome sequencing
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".