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Record W2277986603 · doi:10.1161/str.46.suppl_1.wp417

Abstract W P417: A Common Variant in a TGFβ Modifier Locus Is Associated with Intracranial Hemorrhage Presentation of Brain Arteriovenous Malformation in Hereditary Hemorrhagic Telangiectasia

2015· article· en· W2277986603 on OpenAlexaff
Ludmila Pawlikowska, Jeffrey Nelson, Diana E. Guo, Charles E. McCulloch, Michael T. Lawton, Helen Kim, Marie E. Faughnan

Bibliographic record

VenueStroke · 2015
Typearticle
Languageen
FieldMedicine
TopicVascular Anomalies and Treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineTelangiectasiaArteriovenous malformationACVRL1Intracerebral hemorrhageVascular malformationIntracranial Arteriovenous MalformationsInternal medicinePathologyEndoglinSubarachnoid hemorrhageSurgeryCerebral angiographyAngiographyGenetics

Abstract

fetched live from OpenAlex

Introduction: Hereditary hemorrhagic telangiectasia (HHT) is caused by mutations in TGFβ/BMP9 pathway genes, most commonly ENG or ALK1. HHT patients have arteriovenous malformations (AVM) in brain, lung and liver, leading to severe complications including intracranial hemorrhage (ICH) from brain AVM. ICH presentation of brain AVM in HHT is a marker of high ICH risk. The clinical heterogeneity of HHT suggests a potential role for genetic modifier effects. Common genetic variants in loci that modify phenotype severity in Tgfb knockout mice have been reported to be associated with pulmonary AVM in HHT. We sought to replicate these associations and investigate whether these variants are also associated with brain AVM and ICH presentation of brain AVM in HHT patients. Methods: We genotyped 3 variants (PTPN14 rs2936018, USH2A rs700024 and ADAM17 rs10495565) in 665 Caucasian HHT patients enrolled by the Brian Vascular Malformation Consortium (BVMC). Association of genotype with pulmonary AVM, brain AVM and ICH presentation was evaluated by multivariate logistic regression adjusted for age, gender and family clustering, and also stratified by HHT mutation (ALK1 or ENG). Results: Of 665 Caucasian HHT patients analyzed, 51% had pulmonary AVM and 20% had brain AVM, of whom 17% presented with ICH. None of the 3 SNPs was significantly associated with pulmonary or brain AVM. Among 130 brain AVM patients, USH2A rs700024 was associated with ICH presentation (OR=3.34, 95% CI=1.22-9.15, p=0.019). The effect size was similar in HHT patients with ALK1 and ENG mutations, but only reached statistical significance among the latter (OR=6.77, p=0.014). Conclusions: A common variant in USH2A, rs700024, previously reported to be associated with pulmonary AVM in HHT, was associated with ICH presentation of brain AVM, but not with brain or pulmonary AVM, in the BVMC HHT cohort. Association of the same USH2A variant with different HHT severity phenotypes in different cohorts suggests that it may act as a genetic modifier of HHT phenotype severity in concert with other genetic and environmental factors. Once validated, such genetic modifiers may improve our understanding of the phenotypic heterogeneity of HHT and aid in ICH risk prediction in HHT brain AVM.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.252
Teacher spread0.237 · 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
Published2015
Admission routes1
Has abstractyes

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