Evidence mapPaperPMID 41949264Full record

ReviewCurrent opinion in lipidology2026

HDL and ASCVD: is high HDL-C protective, harmful, or simply misleading?

Paolo Parini, Matteo Pedrelli

Abstract readReview
In one paragraph

Review in Current opinion in lipidology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Paolo PariniCardio Metabolic Unit, Department of Medicine Huddinge and Department of Laboratory Medicine, Karolinska Institutet.
Matteo PedrelliCardio Metabolic Unit, Department of Medicine Huddinge and Department of Laboratory Medicine, Karolinska Institutet.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis review examines whether high high-density lipoprotein cholesterol (HDL-C) is protective, harmful, or simply misleading in relation to atherosclerotic cardiovascular disease (ASCVD), with emphasis on recent mechanistic, epidemiologic, genetic, and trial evidence. RECENT

findingsHDL is biologically important and multifunctional, but HDL-C is an imperfect surrogate for HDL function. Recent cohort studies show nonlinear associations, with very high HDL-C not consistently protective and in some settings associated with increased mortality. Mendelian randomization studies do not support HDL-C as a causal protective factor, and randomized trials of HDL-C-raising strategies have generally failed to reduce ASCVD events. These findings have shifted attention from HDL quantity to HDL quality, including cholesterol efflux capacity, particle characteristics, and pathway-specific biology. At the same time, modern cholesteryl ester transfer protein (CETP) inhibition has renewed interest in whether benefit, if any, relates to Apolipoprotein B-lowering rather than HDL-C elevation itself. SUMMARY: HDL biology remains highly relevant, but HDL-C alone should not be interpreted as a reliable marker of atheroprotection or as a therapeutic target. Very high HDL-C should not be used to downplay established causal risk factors. Future research should prioritize functional HDL metrics, deeper phenotyping, and mechanism-aligned trials to determine whether improving HDL quality, rather than simply raising HDL-C, can reduce ASCVD risk.

Indexed as

AtherosclerosisCholesterol, HDLAnimalsCholesterol Ester Transfer ProteinsHumansCholesterol Ester Transfer ProteinsCholesterol, HDLApoB-containing lipoproteinsatherosclerotic cardiovascular diseaseCETP inhibitorscholesterol efflux capacityhigh-density lipoprotein cholesterolhigh-density lipoprotein functionMendelian randomization

Identifiers

PMID41949264
PMCPMC13152047

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.