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Abstract B025: Genome-wide study identifies novel genes associated with bone toxicities among children with acute lymphoblastic leukemia

2024· article· en· W4402267081 on OpenAlexaffabout
Qianqian Zhu, Ram Mambiar, Emily Schultz, Xinyu Gao, Shuyi Liang, Yael Flamand, Kristen E. Stevenson, Peter D. Cole, Lisa Gennarini, Marian H. Harris, Justine M. Kahn, Elena J. Ladas, Uma H. Athale, Thai H. Tran, Bruno Michon, Jennifer Welch, Stephen E. Sallan, Lewis B. Silverman, Kara M. Kelly, Song Yao

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsCentre hospitalier de l'Université LavalUniversité de MontréalMcMaster University
Fundersnot available
KeywordsLymphoblastic LeukemiaGeneMedicineGenomeLeukemiaOncologyGeneticsBiologyBioinformaticsCancer researchInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Bone toxicities, including non-traumatic fracture and osteonecrosis, occur at a high rate among pediatric patients treated for acute lymphoblastic leukemia (ALL). In the Dana Farber Cancer Institute (DFCI) 05-001 trial, 25% of patients experienced fracture and 10% experienced osteonecrosis during or after treatment. Fracture at a young age can have major negative impact on patients’ quality of life when considering the active behavior typical in this age group. Patients and Methods: To identify the underlying genetic contributors to bone toxicities in children treated for ALL, we conducted a genome-wide association study (GWAS) and a transcriptome-wide association study (TWAS) in 260 self-identified non-Hispanic White (NHW) patients from the DFCI 05-001 ALL trial, with validation in 101 NHW patients from the DFCI 11-001 ALL trial. In addition, we measured and tested plasma 25OHD levels, as well as two existing polygenic scores (PGS), one for circulating vitamin D. levels and the other for heel quantitative ultrasound speed of sound (SOS), with fracture risk in our cohorts. Results: We identified an imputed variant, rs844882 on chromosome 20 (minor allele frequency = 0.059, imputation Rsq = 0.9685), in significant association with bone toxicities in DFCI 05-001 (per alternative T allele, sub-distribution hazard ratio [sHR] = 0.35, P = 1.7×10−8). The variant was an expression quantitative trait locus (eQTL) for two nearby genes, CD93 and THBD. In DFCI 11-001, we observed a consistent trend of this variant with fracture and the meta-p-value for bone toxicities based on the two cohorts was 5.1×10−7. In TWAS, genetically predicted ACAD9 expression was associated with increased risk of bone toxicities, which was confirmed by meta-analysis of the two cohorts (meta-P = 2.4x10−6). While we found no association of plasma 25OHD levels or the PGS for vitamin D. levels with fracture risk, the PGS for heel quantitative ultrasound speed of sound was associated with fracture risk in both cohorts (meta-P = 2.3x10−3). Conclusions: Our findings highlight the genetic influence on treatment-related bone toxicities in this patient population. The genes we identified in our study provide new biological insights into development of bone adverse events related to ALL treatment. Citation Format: Qianqian Zhu, Ram Mambiar, Emily Schultz, Xinyu Gao, Shuyi Liang, Yael Flamand, Kristen Stevenson, Peter D. Cole, Lisa Gennarini, Marian H. Harris, Justine M. Kahn, Elena J. Ladas, Uma H. Athale, Thai H. Tran, Bruno Michon, Jennifer J.G. Welch, Stephen E. Sallan, Lewis B. Silverman, Kara M. Kelly, Song Yao. Genome-wide study identifies novel genes associated with bone toxicities among children with acute lymphoblastic leukemia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B025.

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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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.367
Teacher spread0.320 · 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 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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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