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Record W2886224969 · doi:10.1158/1538-7445.am2018-222

Abstract 222: Genome-wide association study of acute lymphoblastic leukemia in children with Down syndrome

2018· article· en· W2886224969 on OpenAlexaff
Austin L. Brown, Adam J. de Smith, Michael E. Scheurer, Noah A. Kallsen, Stephen Peyton, Gareth E. Davies, Erik A. Ehli, Michael E. Zwick, Naomi Winick, Kelly W. Maloney, Anne Angiolillo, Reuven J. Schore, Michael M. Burke, Wanda L. Salzer, Nyla A. Heerema, Andrew J. Carroll, Michael J. Borowitz, Brent L. Wood, William L. Carroll, Elizabeth A. Raetz, Elanor Feingold, Stephanie L. Sherman, Wenjian Yang, Meenakshi Devidas, Kyle M. Walsh, Andrew T. DeWan, Maria S. Pombo‐de‐Oliveira, Jeffrey W. Taub, Daniel Sinnett, Jasmine Healy, Jillian M. Birch, Lisa F. Barcellos, Helen M. Hansen, Ivan Smirnov, Charles G. Mullighan, Stephen P. Hunger, Ching‐Hon Pui, Mignon L. Loh, Joe Wiemels, Xiaomei Ma, Catherine Metayer, Beth A. Mueller, Mary V. Relling, Jun J. Yang, Philip J. Lupo, Karen R. Rabin

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsGenome-wide association studyMinor allele frequencySingle-nucleotide polymorphismMedicineOdds ratioSNP1000 Genomes ProjectExomeCohortOncologyGenetic associationImputation (statistics)GeneticsInternal medicineBiologyGenotypeExome sequencingMutationGene

Abstract

fetched live from OpenAlex

Abstract Purpose: Children with Down syndrome (DS) have a 20-fold increased risk of acute lymphoblastic leukemia (ALL) compared to children without DS. While genome-wide association studies (GWAS) have identified several susceptibility loci in childhood ALL, studies of ALL in children with DS are lacking. Therefore, we conducted the first GWAS of DS-ALL. Methods: We analyzed independent cohorts of: 1) 226 newly diagnosed DS-ALL cases from Children's Oncology Group (COG) ALL trials (2000-2013) and 436 DS controls from the National Down Syndrome Project (NDSP), 2) 124 additional COG ALL cases (2011-2015) and 336 additional NDSP DS controls, 3) 20 DS-ALL cases and 275 DS controls from Michigan neonatal bloodspots, and 4) 157 DS-ALL cases and 145 DS controls largely from neonatal bloodspots from California and Washington. Genotyping was performed with Affymetrix or Illumina single nucleotide polymorphism (SNP) arrays. STRUCTURE software was used to define European (372 cases, 1,056 controls), Hispanic (140 cases, 136 controls), and African (15 cases, 62 controls) genetic ancestry. After genome-wide imputation and quality control, ancestry- and cohort-specific associations were evaluated at >6,000,000 autosomal SNPs with minor allele frequency ≥1%. Associations were meta-analyzed across cohort and ancestry groups, assuming additive allelic effects. Results: Genome-wide significant (p<5x10-8) association signals were identified for known ALL susceptibility loci, including rs58923657 near IKZF1 (Odds Ratio [OR]=2.02, p=5.32x10-15), CDKN2A missense mutation rs3731249 (OR=3.63, p=3.91x10-10), rs3781093 near GATA3 (OR=1.73, p=2.89x10-8), and rs7090445 near ARID5B (OR=1.57, p=2.93x10-8). A novel potential risk locus was identified at chromosome 20q11.21 (rs78019519, OR=3.17, p=5.11x10-7) with consistent effects observed across each cohort and ancestry group. This SNP is in the promoter region of the oncogene TPX2 and is also associated with expression of HM13 in whole blood in the Genotype-Tissue Expression (GTEx) Portal. Conclusion: We confirmed that known ALL susceptibility loci in children without DS, including IKZF1, CDKN2A, GATA3, PIP4K2A and ARID5B, also confer risk of ALL in children with DS, with CDKN2A showing the largest effect size. We also identified a potentially novel locus associated with ALL susceptibility in DS at chromosome 20q11.21. Additional investigation of these loci is ongoing and may advance our understanding of DS-ALL etiology and biology. Citation Format: Austin L. Brown, Adam J. de Smith, Michael E. Scheurer, Noah A. Kallsen, Shanna A. Peyton, Gareth E. Davies, Erik A. Ehli, Michael E. Zwick, Naomi Winick, Kelly Maloney, Anne L. Angiolillo, Reuven Schore, MIchael M. Burke, Wanda L. Salzer, Nyla A. Heerema, Andrew J. Carroll, Michael J. Borowitz, Brent L. Wood, William L. Carroll, Elizabeth A. Raetz, Elanor Feingold, Stephanie L. Sherman, Wenjian Yang, Meenakshi Devidas, Kyle Walsh, Andrew T. DeWan, Maria S. Pombo-de-Oliveira, Jeffrey W. Taub, Daniel Sinnett, Jasmine Healy, Jillian M. Birch, Lisa F. Barcellos, Helen Hansen, Ivan Smirnov, Charles G. Mullighan, Stephen P. Hunger, Ching-Hon Pui, Mignon Loh, Joe L. Wiemels, Xiaomei Ma, Catherine Metayer, Beth A. Mueller, Mary V. Relling, Jun J. Yang, Philip J. Lupo, Karen R. Rabin. Genome-wide association study of acute lymphoblastic leukemia in children with Down syndrome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 222.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.343
Teacher spread0.318 · 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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Citations1
Published2018
Admission routes1
Has abstractyes

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