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Record W4390461395 · doi:10.1101/2023.12.30.23300391

Germline and Somatic Mutations in DNA Methyltransferase 3A <i>(DNMT3A)</i> Predispose to Pulmonary Arterial Hypertension (PAH) in Humans and Mice: <i>Implications for Associated PAH</i>

2023· preprint· en· W4390461395 on OpenAlexafffund
Ruaa Al‐Qazazi, Isaac Emon, François Potus, Ashley Martin, Patricia D.A. Lima, Caitlyn Vlasschaert, Kuang‐Hueih Chen, Danchen Wu, Asish Das Gupta, Curtis Noordhof, Lindsay Jefferson, Amy J. M. McNaughton, Alexander G. Bick, Michael W. Pauciulo, William C. Nichols, Wendy K. Chung, Paul M. Hassoun, Rachel L. Damico, Michael J. Rauh, Stephen L. Archer

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de QuébecQueen's University
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of HealthCanadian Vascular Network
KeywordsGermline mutationSomatic cellGermlineMethyltransferaseGeneticsInternal medicineMutationMedicineDNABiologyMethylationGene

Abstract

fetched live from OpenAlex

Abstract Background Mutations are found in 10-20% of idiopathic PAH (IPAH) patients, but none are consistently identified in connective tissue disease-associated PAH (APAH), which accounts for ∼45% of PAH cases. TET2 mutations, a cause of clonal hematopoiesis of indeterminant potential (CHIP), predispose to an inflammatory type of PAH. We now examine mutations in another CHIP gene, DNMT3A , in PAH. Methods We assessed DNMT3A mutation prevalence in PAH Biobank subjects as compared with controls, first using whole exome sequencing (WES)-derived CHIP calls in 1832 PAH Biobank patients versus 7509 age-and sex-matched gnomAD controls. We then performed deep, targeted panel sequencing of CHIP genes on a subset of 710 PAH Biobank patients and compared the prevalence of DNMT3A mutations therein to an independent pooled control cohort (N = 3645). In another cohort of 80 PAH patients and 41 controls, DNMT3A mRNA expression was studied in peripheral blood mononuclear cells (PBMCs). Finally, we evaluated the development of PAH in a conditional, hematopoietic, Dnmt3a knockout mouse model. Results DNMT3A mutations were more frequent in PAH cases versus control subjects in the WES dataset (OR 2.60, 95% CI: 1.71-4.27). Among PAH patients, 33 had DNMT3A variants, most of whom had APAH (21/33). While 21/33 had somatic mutations (female:male 17:4), germline variants occurred in 12/33 (female:male 11:1). Hemodynamics were comparable with and without DNMT3A mutations (mPAP=58±21 vs. 52±18 mmHg); however, patients with DNMT3A mutations were unresponsive to acute vasodilator testing. Targeted panel sequencing identified that 14.6% of PAH patients had CHIP mutations (104/710), with DNMT3A accounting for 49/104. There was a significant association between all CHIP mutations and PAH in analyses adjusted for age and sex (OR 1.40, 95% CI: 1.09-1.80), though DNMT3A CHIP alone was not significantly enriched (OR:1.15, 0.82-1.61). DNMT3A expression was reduced in patient-derived versus control PAH-PBMCs. Spontaneous PAH developed in Dnmt3a -/- mice, and it was exacerbated by 3 weeks of hypoxia. Dnmt3a -/- mice had increased lung macrophages and elevated plasma IL-13. The IL-1β antibody canakinumab attenuated PAH in Dnmt3a -/- mice. Conclusions Germline and acquired DNMT3A variants predispose to PAH in humans. DNMT3A mRNA expression is reduced in human PAH PBMCs. Hematopoietic depletion of Dnmt3a causes inflammatory PAH in mice. DNMT3A is a novel APAH gene and may be a biomarker and therapeutic target.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

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 integrity0.0000.000
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 head0.063
GPT teacher head0.332
Teacher spread0.270 · 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 designBench or experimental
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

Citations3
Published2023
Admission routes2
Has abstractyes

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