Association of HDL composition and functionality with markers of subclinical vascular disease in individuals with extremely high HDL
Notice bibliographique
Résumé
Abstract Background Extremely elevated High-Density Lipoprotein cholesterol (HDL-c) concentrations, defined as hyperalphalipoproteinemia (HALP), have paradoxically been associated with increased cardiovascular (CV) risk. Emerging evidence suggests a U-shaped relationship between HDL-c and CV risk, suggesting that in HALP, HDL particles may exhibit altered composition or impaired functionality. Purpose To evaluate the association between HDL composition and functionality and altered markers of subclinical vascular disease (SVD) in individuals with HALP. Methods A total of 45,000 individuals from a large population cohort and a specialized cardiology center database were screened, identifying 62 participants (0.14%) aged 45–75 years, with HDL-c levels ≥90 mg/dL and no established clinical CV disease. Coronary artery calcium (CAC) quantification and carotid intima-media thickness (cIMT) were assessed, while pulse wave velocity (PWV) was measured using applanation tonometry, with all considered markers of SVD. Plasma lipid profile and apolipoprotein (apo) A-IV levels were measured using commercial assays. The simultaneous transfer of cholesteryl ester (CE) and unesterified cholesterol (UC) to the HDL fraction, along with its anti-inflammatory properties, assessed by the inhibition of IL-6 and TNF-α, were evaluated. Following the in vitro tests, HDL3 and HDL2 subfractions were characterized in terms of lipid composition, antioxidant capacity, and cholesterol efflux capacity. Results Among the 62 participants, 79.0% were female, with a median HDL-c level of 96 mg/dL (IQR 90–105) and a body mass index (BMI) of 23.5 kg/m² (IQR 21.4–26.3). Thirty-one participants exhibited at least one altered marker of SVD and were older than those without (64.2 ± 8.0 vs. 57.7 ± 9.1 years; p = 0.0043). Hypertension was more prevalent in the SVD group (p = 0.0209). While diabetes prevalence was similar across groups, glucose was higher in the SVD group (p = 0.0404). No differences were observed in the plasma lipid profile, apo A-IV levels, or HDL functionality-related parameters, in addition to the transfer of CE and UC to the HDL fraction. However, the SVD group showed increased concentrations of phospholipids and triglycerides in the HDL3 subfraction compared to the non-SVD group (p = 0.0113 and p = 0.0227, respectively). After multivariate adjustment for sex, BMI, hypertension, diabetes, glucose, and smoking, only age (OR 1.11, 95% CI 1.03–1.20; p = 0.0075) and phospholipid concentration in the HDL3 subfraction (OR 1.00, 95% CI 1.00–1.23; p = 0.0422) remained independently and positively linked to SVD. Conclusion Besides age, specific features of HDL composition, such as increased phospholipid concentrations in the HDL3 subfraction, are independently associated with SVD. This suggests that the protective role of HDL may be compromised in these individuals, regardless of their highly elevated HDL-c concentrations.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».