Appraisal of multiple polygenic risk scores to estimate the risk of myocardial infarction and coronary artery lesions
Notice bibliographique
Résumé
Polygenic risk scores (PRS) could help to identify individuals with a high genetic risk profile for coronary artery disease (CAD). We aimed to evaluate the association between previously reported PRS and myocardial infarction (MI) as well as the extent and recurrence of coronary artery lesions. We validated previously reported CAD-PRS and 6 cardiovascular (CV) risk factors PRS (systolic blood pressure [SBP], type 2 diabetes [T2D], body-mass index [BMI], low-density lipoprotein cholesterol [LDL], triglycerides [TG], and lipoprotein-[a][Lp(a)]) in individuals of European ancestry from two Canadian population-based cohorts, the Canadian Longitudinal Study on Aging (CLSA, N = 24,599) and CARTaGENE (N = 26,806). Using a stepwise model, we determined an optimal combination of PRS to identify MI. We tested the selected PRS for association with the severity and recurrence of atherosclerotic CAD evaluated by coronary angiography in patients undergoing cardiac surgery (QUEBEC-ANGIO, N = 4108). We show that the CAD-PRS most strongly associated with MI has odds ratios per standard deviation increment of 1.75 [1.64–1.86] (P = 1.57E-70) in CLSA and 1.87 [1.73–2.03] (P = 3.06E-53) in CARTaGENE. In CLSA, the optimal model includes CAD-PRS, SBP-PRS, BMI-PRS, LDL-PRS, TG-PRS and Lp(a)-PRS. Adding these PRS increases modestly yet significantly the discriminative capacity when compared to traditional risk factors (difference of AUC = 0.025 [0.019–0.031] in CLSA, 0.018 [0.012–0.024] in CARTaGENE). In QUEBEC-ANGIO, the CAD-PRS is gradually and significantly associated with the extent and recurrence of CAD. Screening multiple validated PRS may significantly improve genetic risk estimation of MI as well as the extent and recurrence of coronary artery lesions. Scores using common genetic (DNA) variations that can be measured in a blood sample have been developed to predict the risk of many diseases, including coronary heart disease (leading to heart attacks). In this study, we combined many of these scores to identify individuals who had a heart attack. We show that adding scores to known risk factors significantly improves prediction. We also show that some of these scores are associated with the level of obstruction in heart vessels measured during a specialized procedure. The use of these scores may improve the prediction of the risk of heart attack and obstruction of heart vessels. Manikpurage et al. evaluate the association between existing polygenic risk scores (PRS) and myocardial infarction (MI) as well as the extent of coronary artery lesions at coronary angiography. The combination of several PRS could improve risk estimation of MI, extent and recurrence of atherosclerotic coronary lesions.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».