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Record W3008110097 · doi:10.1038/s41467-020-14829-5

The complex genetic landscape of familial MDS and AML reveals pathogenic germline variants

2020· article· en· W3008110097 on OpenAlexaff
Ana Rio‐Machín, Tom Vulliamy, Nele Hug, Amanda J. Walne, Kiran Tawana, Shirleny Cardoso, Alicia Ellison, Nikolas Pontikos, Jun Wang, Hemanth Tummala, Ahad Al Seraihi, Jenna Alnajar, Findlay Bewicke‐Copley, Hannah Armes, Michael J. Barnett, Adrian Bloor, Csaba Bödör, David Bowen, Pierre Fenaux, Andrew Green, Andrew R. Hallahan, Henrik Hjorth‐Hansen, Upal Hossain, Sally Killick, Sarah Lawson, Mark Layton, Alison Male, Judith Marsh, Priyanka Mehta, Rogier Mous, Josep Nomdedéu, Carolyn Owen, Jiří Pavlů, Elspeth Payne, Rachel Protheroe, Claude Preudhomme, Núria Pujol‐Moix, Aline Renneville, Nigel H. Russell, Anand Saggar, Gabriela Sciuccati, David Taussig, Cynthia L. Toze, Anne Uyttebroeck, Peter Vandenberghe, Brigitte Schlegelberger, Tim Ripperger, Doris Steinemann, John K. Wu, Joanne Mason, Paula Page, Susanna Akiki, Kim Reay, Jamie Cavenagh, Vincent Plagnol, Javier F. Cáceres, Jude Fitzgibbon, Inderjeet Dokal

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsBC Children's HospitalFoothills Medical CentreUniversity of British Columbia
FundersMedical Research CouncilBlood Cancer UKCancer Research UKEuropean Hematology Association
KeywordsMyeloid leukemiaGermlineMyeloidGeneticsExome sequencingMyelodysplastic syndromesBiologyDiseaseEtiologyGeneComputational biologyBioinformaticsCancer researchMedicineBone marrowImmunologyMutationInternal medicine

Abstract

fetched live from OpenAlex

The inclusion of familial myeloid malignancies as a separate disease entity in the revised WHO classification has renewed efforts to improve the recognition and management of this group of at risk individuals. Here we report a cohort of 86 acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) families with 49 harboring germline variants in 16 previously defined loci (57%). Whole exome sequencing in a further 37 uncharacterized families (43%) allowed us to rationalize 65 new candidate loci, including genes mutated in rare hematological syndromes (ADA, GP6, IL17RA, PRF1 and SEC23B), reported in prior MDS/AML or inherited bone marrow failure series (DNAH9, NAPRT1 and SH2B3) or variants at novel loci (DHX34) that appear specific to inherited forms of myeloid malignancies. Altogether, our series of MDS/AML families offer novel insights into the etiology of myeloid malignancies and provide a framework to prioritize variants for inclusion into routine diagnostics and patient management.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.336
Teacher spread0.293 · 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 teacher head, 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".

Quick stats

Citations116
Published2020
Admission routes1
Has abstractyes

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