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Record W2646106353 · doi:10.1161/str.47.suppl_1.50

Abstract 50: Evaluation of Candidate Polymorphisms for Association With Brain Arteriovenous Malformations and Intracranial Hemorrhage in Hereditary Hemorrhagic Telangiectasia

2016· article· en· W2646106353 on OpenAlexaff
Ludmila Pawlikowska, Jeffrey Nelson, Diana E. Guo, Charles E. McCulloch, Michael T. Lawton, Helen Kim, Marie E. Faughnan

Bibliographic record

VenueStroke · 2016
Typearticle
Languageen
FieldMedicine
TopicVascular Anomalies and Treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineTelangiectasiaIntracerebral hemorrhageOdds ratioApolipoprotein EHaplotypeGenotypeArteriovenous malformationInternal medicineSingle-nucleotide polymorphismAlleleGastroenterologyPathologySurgerySubarachnoid hemorrhageGeneticsGene

Abstract

fetched live from OpenAlex

Introduction: Brain arteriovenous malformations (AVM) are an important cause of intracranial hemorrhage (ICH) in young adults. Most are sporadic, but also occur in inherited diseases such as hereditary hemorrhagic telangiectasia (HHT). ICH presentation of brain AVM in both sporadic and HHT cases is a marker of high ICH risk. In order to investigate whether the same genetic modifiers influence sporadic and HHT brain AVM, we evaluated candidate genetic polymorphisms reported as associated with sporadic brain AVM, with ICH presentation or ICH during clinical course, in HHT patients. Methods: We genotyped 8 polymorphisms ( APOE E2/3/4 [rs7412, rs429358], ANGPTL rs116724, EPHB4 rs314308, IL6 -174G>C [rs1800795], IL1B -31T>C [rs1143627], ITGB8 rs10486391, TNF -238G>A[rs361525]) in 753 Caucasian HHT patients enrolled by the Brian Vascular Malformation Consortium (BVMC). Genotypes were collapsed into risk allele carriers vs. other for analysis, as published for sporadic AVM. APOE E2/3/4 haplotypes were assigned based on genotypes of the 2 APOE polymorphisms. Association of genotype with phenotype was evaluated by multivariable logistic regression adjusted for age, gender and accounting for family clustering. We used a nominal significance threshold of p=0.05, requiring the same direction of effect as in sporadic brain AVM (odds ratio for risk genotype [OR]>1). Results: Among 753 HHT patients, 155 (21%) had brain AVM, of whom 26 (17%) presented with ICH. Two additional brain AVM patients had ICH during follow-up. None of the 7 variants (6 single nucleotide polymorphisms and APOE haplotype) were significantly associated with brain AVM (OR=0.6-1.3), with ICH presentation of brain AVM (OR=0.4-1.9), or with any brain AVM ICH in HHT patients (OR=0.5-2.1). Conclusions: Common genetic variants previously reported to be associated with sporadic brain AVM were not associated with brain AVM nor with ICH in the BVMC HHT cohort, suggesting different genetic modifiers may influence sporadic and HHT brain AVM. However, the number of ICH cases in the cohort is small, so the confidence intervals are wide and we cannot rule out clinically important associations. The BVMC is enrolling additional HHT patients to expand the cohort and increase power for association analyses.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.250
Teacher spread0.239 · 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
Published2016
Admission routes1
Has abstractyes

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