ReviewBiomedicines2022
HDL Is Not Dead Yet.
Review in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Current Understanding of Circulating Apolipoprotein E-Containing High-Density Lipoproteins and Their Clinical Utility in Cardiovascular Disease Risk Assessment.Yonago acta medica · 2026Review
- Article
- A Current Update on the Role of HDL-Based Nanomedicine in Targeting Macrophages in Cardiovascular Disease.Pharmaceutics · 2023Review
- Porphyromonas gingivalis Virulence Factors and Clinical Significance in Periodontal Disease and Coronary Artery DiseasesPathogens (Basel, Switzerland) · 2022Review
- Different Pathways of Cellular Cholesterol Efflux.Cell biochemistry and biophysics · 2022Review
- High-Density Lipoproteins and Cardiovascular Disease: The Good, the Bad, and the Future II.Biomedicines · 2022Article
- Glycosylation of HDL-Associated Proteins and Its Implications in Cardiovascular Disease Diagnosis, Metabolism and Function.Frontiers in cardiovascular medicine · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
High-density lipoprotein cholesterol (HDL-C) levels are inversely correlated with coronary heart disease (CHD) in multiple epidemiological studies, but whether HDL is causal or merely associated with CHD is unclear. Recent trials for HDL-raising drugs were either not effective in reducing CHD events or, if beneficial in reducing CHD events, were not conclusive as the findings could be attributed to the drugs' LDL-reducing activity. Furthermore, the first large Mendelian randomization study did not causally relate HDL-C levels to decreased CHD. Thus, the hypothesis that HDL is protective against CHD has been rightfully challenged. However, subsequent Mendelian randomization studies found HDL characteristics that are causally related to decreased CHD. Many aspects of HDL structure and function, especially in reverse cholesterol transport, may be better indicators of HDL's protective activity than simply measuring HDL-C. Cholesterol efflux capacity is associated with lower levels of prevalent and incident CHD, even after adjustment for HDL-C and apolipoprotein A-1 levels. Also, subjects with very high levels of HDL-C, including those with rare mutations that disrupt hepatic HDL uptake and reverse cholesterol transport, may be at higher risk for CHD than those with moderate levels. We describe here several cell-based and cell-free in vitro assays of HDL structure and function that may be used in clinical studies to determine which of HDL's functions are best associated with protection against CHD. We conclude that the HDL hypothesis may need revision based on studies of HDL structure and function, but that the HDL hypothesis is not dead yet.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.