Evidence on Chromosome 11 for a Quantitative Trait Locus Influencing Levels of Activated Protein C-Protein C Inhibitor Complex.
Notice bibliographique
Résumé
Abstract Earlier we showed high heritability for the variation in levels of activated protein C-protein C inhibitor complex in a large kindred with type I protein C deficiency (Vossen et al. 2004). To identify genomic regions, which might harbour a gene with a mutation that accounts for a difference in the levels of activated protein C-protein C inhibitor complex, we performed a variance component linkage analysis. Family members were genotyped for 375 autosomal markers at the Marshfield Medical Research Foundation with an average marker spacing of 9.4 cM (range 0–18 cM) and an average marker heterozygosity of 75% (range 42–89%). Levels of activated protein C-protein C inhibitor complex were measured using commercial paired antibody sets from Affinity Biologicals Inc. (Ancaster, Ontario, Canada). We estimated the probability of Identity By Descent (IBD) using the multipoint IBD method in Simwalk2 (Sobel & Lange 1996), in which the proportion of alleles shared identical by descent at marker loci is used to estimate IBD sharing at arbitrary points along the chromosome for each relative pair. Then, variance component linkage analysis was performed using SOLAR (Almasy & Blangero 1998) to test whether a proportion of the genetic variance in the levels of activated protein C-protein C inhibitor complex could be attributed to specific genomic locations. The levels of activated protein C-protein C inhibitor were log-transformed to reduce skewness (from 3.0 to 0.2) and kurtosis (from 11.6 to 0.4) and were assumed to distribute as a multivariate normal density with correlation =h2K + c2H + q2B + e2I, where matrix K contains the kinship coefficients, H contains 1 for pairs from the same household and 0 otherwise, B contains the IBD probabilities, and I represents the identity matrix. The parameters for heritability (h2), household effect (c2), and heritability contributed to a specific genomic location (q2) as well as the effects of the covariates were estimated simultaneously using maximum likelihood analysis. Lod scores were computed as the log10 likelihood for q2 estimated to q2=0. A lod score of 3.3 was used as cut-off point for statistical evidence for significant linkage (as suggested by Lander and Kruglyak 1995), and a lod score above 1.9 but below 3.3 for suggestive linkage evidence. We found suggestive linkage evidence for levels of activated protein C in complex with protein C inhibitor in 121 tested family members (without a history of venous thrombosis) for a region on chromosome 11 (marker D11S969, 146 cM) with a LOD-score of 2.6, with age added to the model. As no obvious candidate genes were available under the peak, and because the linkage region is too wide to be certain of linkage, we are currently finemapping the peak by adding microsatellite markers to the genome scan to narrow the region on chromosome 11.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».