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Association of HDL composition and functionality with markers of subclinical vascular disease in individuals with extremely high HDL

2025· article· en· W7127998457 on OpenAlexaff
F C Juliani, M H Miname, A G Laurinavicius, V Z Rocha, M Nakandakare, Marisa Passarelli, L Bortolotto, R C Maranhao, R D Santos

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsSubclinical infectionCholesterolBody mass indexApolipoprotein A1PopulationApolipoprotein BCoronary artery diseaseLipid profile

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.290
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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