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Record W2922106038 · doi:10.1093/brain/awz024

Association of variants in<i>HTRA1</i>and<i>NOTCH3</i>with MRI-defined extremes of cerebral small vessel disease in older subjects

2019· article· en· W2922106038 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBrain · 2019
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and genetic disorders
Canadian institutionsMcGill Genome Centre
FundersH2020 European Research CouncilFondation LeducqAgence Nationale de la RechercheNational Center for Research ResourcesNational Heart, Lung, and Blood InstituteNational Center for Advancing Translational SciencesMedical Research CouncilCanadian Institutes of Health ResearchNational Institute on AgingDiabetes Research CenterNational Institutes of HealthNational Health and Medical Research CouncilNational Institute of Diabetes and Digestive and Kidney DiseasesFondation Claude PompidouUniversité de BordeauxBundesministerium für Wissenschaft, Forschung und WirtschaftNational Institute of Neurological Disorders and StrokeCenter for Hellenic Studies, Harvard UniversityBundesministerium für Bildung und ForschungZonMwNational Human Genome Research InstituteEuropean CommissionEU Joint Programme – Neurodegenerative Disease ResearchIndiana Clinical and Translational Sciences Institute
KeywordsExomeExome sequencingGeneticsPopulationGenetic associationLinkage disequilibriumGenome-wide association studyCandidate geneDiseaseHyperintensityPhenotypeBiologyMedicineGenotypePathologyGeneMagnetic resonance imagingSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

We report a composite extreme phenotype design using distribution of white matter hyperintensities and brain infarcts in a population-based cohort of older persons for gene-mapping of cerebral small vessel disease. We demonstrate its application in the 3C-Dijon whole exome sequencing (WES) study (n = 1924, nWESextremes = 512), with both single variant and gene-based association tests. We used other population-based cohort studies participating in the CHARGE consortium for replication, using whole exome sequencing (nWES = 2,868, nWESextremes = 956) and genome-wide genotypes (nGW = 9924, nGWextremes = 3308). We restricted our study to candidate genes known to harbour mutations for Mendelian small vessel disease: NOTCH3, HTRA1, COL4A1, COL4A2 and TREX1. We identified significant associations of a common intronic variant in HTRA1, rs2293871 using single variant association testing (Pdiscovery = 8.21 × 10-5, Preplication = 5.25 × 10-3, Pcombined = 4.72 × 10-5) and of NOTCH3 using gene-based tests (Pdiscovery = 1.61 × 10-2, Preplication = 3.99 × 10-2, Pcombined = 5.31 × 10-3). Follow-up analysis identified significant association of rs2293871 with small vessel ischaemic stroke, and two blood expression quantitative trait loci of HTRA1 in linkage disequilibrium. Additionally, we identified two participants in the 3C-Dijon cohort (0.4%) carrying heterozygote genotypes at known pathogenic variants for familial small vessel disease within NOTCH3 and HTRA1. In conclusion, our proof-of-concept study provides strong evidence that using a novel composite MRI-derived phenotype for extremes of small vessel disease can facilitate the identification of genetic variants underlying small vessel disease, both common variants and those with rare and low frequency. The findings demonstrate shared mechanisms and a continuum between genes underlying Mendelian small vessel disease and those contributing to the common, multifactorial form of the disease.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.411

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)0.0000.000

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 head0.006
GPT teacher head0.207
Teacher spread0.202 · 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