MétaCan
Menu
Back to cohort
Record W2154874332 · doi:10.1161/strokeaha.107.502930

Genome Screen to Detect Linkage to Intracranial Aneurysm Susceptibility Genes

2008· article· en· W2154874332 on OpenAlexafffund
Tatiana Foroud, Laura Sauerbeck, Robert D. Brown, Craig S. Anderson, Daniel Woo, Dawn Kleindorfer, Matthew L. Flaherty, Ranjan Deka, Richard Hornung, Irene Meissner, Joan E. Bailey‐Wilson, Guy A. Rouleau, E. Sander Connolly, Dongbing Lai, Daniel L. Koller, John Huston, Joseph P. Broderick

Bibliographic record

VenueStroke · 2008
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsHôpital Notre-Dame
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of HealthRoyal Adelaide HospitalUniversity of OttawaUniversity of CincinnatiUniversity of PittsburghJohns Hopkins UniversityCleveland ClinicCleveland Clinic FoundationUniversity of WashingtonNorthwestern UniversityNational Human Genome Research InstituteUniversity of Southern California
KeywordsGenetic linkageMedicineGeneticsLinkage (software)ChromosomeSNPGeneGenomeFamily historyGenotypeBiologyInternal medicineSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Evidence supports a substantial genetic contribution to the risk of intracranial aneurysm (IA). The purpose of this study was to identify chromosomal regions likely to harbor genes that contribute to the risk of IA. METHODS: Multiplex families having at least 2 individuals with "definite" or "probable" IA were ascertained through an international consortium. First-degree relatives of individuals with IA who were at increased risk of an IA because of a history of hypertension or present smoking were offered cerebral magnetic resonance angiography. A genome screen was completed using the Illumina 6K SNP system, and the resulting data from 192 families, containing 1155 genotyped individuals, were analyzed. Narrow and broad disease definitions were used when testing for linkage using multipoint model-independent methods. Ordered subset analysis was performed to test for a gene x smoking (pack-years) interaction. RESULTS: The greatest evidence of linkage was found on chromosomes 4 (LOD=2.5; 156 cM), 7 (LOD=1.7; 183 cM), 8 (LOD=1.9; 70 cM), and 12 (LOD=1.6; 102 cM) using the broad disease definition. Using the average pack-years for the affected individuals in each family, the genes on chromosomes 4 (LOD=3.5; P=0.03), 7 (LOD=4.1; P=0.01) and 12 (LOD=3.6; P=0.02) all appear to be modulated by the degree of smoking in the affected members of the family. On chromosome 8, inclusion of smoking as a covariate did not significantly strengthen the linkage evidence, suggesting no interaction between the loci in this region and smoking. CONCLUSIONS: We have detected possible evidence of linkage to 4 chromosomal regions. There is potential evidence for a gene x smoking interaction with 3 of the loci.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.266
Teacher spread0.243 · 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.

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

Citations53
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueStrokeSame topicIntracranial Aneurysms: Treatment and ComplicationsFrench-language works237,207