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      High-density lipoprotein revisited: biological functions and clinical relevance

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          Graphical Abstract

          Graphical Abstract

          The great complexity of HDL. High-density lipoprotein (HDL) particles carry a large number of proteins and lipids, which contribute to define their compositional and functional complexity. HDLs exert multiple protective activities, essentially by three major mechanisms. HDLs, however, can lose their protective functions and even gain adverse functions in chronic diseases or during infections. U-shaped relationships between HDL-cholesterol (HDL-C) levels and several conditions have been reported, being both low and extremely high HDL-C levels associated with an increased risk of several pathologies and mortality. LCAT, lecithin:cholesterol acyltransferase; CETP, cholesteryl ester transfer protein; PONI, paraoxonase 1; S1P, sphingosine-1-phosphate; ASCVD, atherosclerotic cardiovascular disease; LDL, low-density lipoprotein; SAA, serum amyloid A; OxPL, oxidized phospholipids

          Abstract

          Previous interest in high-density lipoproteins (HDLs) focused on their possible protective role in atherosclerotic cardiovascular disease (ASCVD). Evidence from genetic studies and randomized trials, however, questioned that the inverse association of HDL-cholesterol (HDL-C) is causal. This review aims to provide an update on the role of HDL in health and disease, also beyond ASCVD. Through evolution from invertebrates, HDLs are the principal lipoproteins, while apolipoprotein B-containing lipoproteins first developed in vertebrates. HDLs transport cholesterol and other lipids between different cells like a reusable ferry, but serve many other functions including communication with cells and the inactivation of biohazards like bacterial lipopolysaccharides. These functions are exerted by entire HDL particles or distinct proteins or lipids carried by HDL rather than by its cholesterol cargo measured as HDL-C. Neither does HDL-C measurement reflect the efficiency of reverse cholesterol transport. Recent studies indicate that functional measures of HDL, notably cholesterol efflux capacity, numbers of HDL particles, or distinct HDL proteins are better predictors of ASCVD events than HDL-C. Low HDL-C levels are related observationally, but also genetically, to increased risks of infectious diseases, death during sepsis, diabetes mellitus, and chronic kidney disease. Additional, but only observational, data indicate associations of low HDL-C with various autoimmune diseases, and cancers, as well as all-cause mortality. Conversely, extremely high HDL-C levels are associated with an increased risk of age-related macular degeneration (also genetically), infectious disease, and all-cause mortality. HDL encompasses dynamic multimolecular and multifunctional lipoproteins that likely emerged during evolution to serve several physiological roles and prevent or heal pathologies beyond ASCVD. For any clinical exploitation of HDL, the indirect marker HDL-C must be replaced by direct biomarkers reflecting the causal role of HDL in the respective disease.

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          Major lipids, apolipoproteins, and risk of vascular disease.

          Associations of major lipids and apolipoproteins with the risk of vascular disease have not been reliably quantified. To assess major lipids and apolipoproteins in vascular risk. Individual records were supplied on 302,430 people without initial vascular disease from 68 long-term prospective studies, mostly in Europe and North America. During 2.79 million person-years of follow-up, there were 8857 nonfatal myocardial infarctions, 3928 coronary heart disease [CHD] deaths, 2534 ischemic strokes, 513 hemorrhagic strokes, and 2536 unclassified strokes. Hazard ratios (HRs), adjusted for several conventional factors, were calculated for 1-SD higher values: 0.52 log(e) triglyceride, 15 mg/dL high-density lipoprotein cholesterol (HDL-C), 43 mg/dL non-HDL-C, 29 mg/dL apolipoprotein AI, 29 mg/dL apolipoprotein B, and 33 mg/dL directly measured low-density lipoprotein cholesterol (LDL-C). Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. The rates of CHD per 1000 person-years in the bottom and top thirds of baseline lipid distributions, respectively, were 2.6 and 6.2 with triglyceride, 6.4 and 2.4 with HDL-C, and 2.3 and 6.7 with non-HDL-C. Adjusted HRs for CHD were 0.99 (95% CI, 0.94-1.05) with triglyceride, 0.78 (95% CI, 0.74-0.82) with HDL-C, and 1.50 (95% CI, 1.39-1.61) with non-HDL-C. Hazard ratios were at least as strong in participants who did not fast as in those who did. The HR for CHD was 0.35 (95% CI, 0.30-0.42) with a combination of 80 mg/dL lower non-HDL-C and 15 mg/dL higher HDL-C. For the subset with apolipoproteins or directly measured LDL-C, HRs were 1.50 (95% CI, 1.38-1.62) with the ratio non-HDL-C/HDL-C, 1.49 (95% CI, 1.39-1.60) with the ratio apo B/apo AI, 1.42 (95% CI, 1.06-1.91) with non-HDL-C, and 1.38 (95% CI, 1.09-1.73) with directly measured LDL-C. Hazard ratios for ischemic stroke were 1.02 (95% CI, 0.94-1.11) with triglyceride, 0.93 (95% CI, 0.84-1.02) with HDL-C, and 1.12 (95% CI, 1.04-1.20) with non-HDL-C. Lipid assessment in vascular disease can be simplified by measurement of either total and HDL cholesterol levels or apolipoproteins without the need to fast and without regard to triglyceride.
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            Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study

            Summary Background High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal. Methods We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. Findings Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10−13) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84–0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88–1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58–0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68–1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45–1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69–2·69, p=2×10−10). Interpretation Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction. Funding US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.
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              Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis

              Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD. Methods and findings We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39–73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10−8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%–93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10−8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation–higher trait; 95% CI: 1.49–1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25–1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56–1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31–2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57–1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02–1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation–higher HDL cholesterol (OR 0.80; 95% CI: 0.75–0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77–0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components. Conclusions These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD.
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                Author and article information

                Contributors
                Journal
                Eur Heart J
                Eur Heart J
                eurheartj
                European Heart Journal
                Oxford University Press (US )
                0195-668X
                1522-9645
                21 April 2023
                07 November 2022
                07 November 2022
                : 44
                : 16 , Focus Issue on Dyslipidaemias
                : 1394-1407
                Affiliations
                Institute of Clinical Chemistry, University Hospital Zurich and University of Zurich , Zurich, Switzerland
                Department of Clinical Biochemistry, Copenhagen University Hospital, Herlev and Gentofte Hospital , Herlev, Denmark
                The Copenhagen General Population Study, Copenhagen University Hospital, Herlev and Gentofte Hospital , Herlev, Denmark
                Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen, Denmark
                Lipoprotein Metabolism Section, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, MD, USA
                Department of Pharmacological and Biomolecular Sciences, University of Milan , Milan, Italy
                IRCCS MultiMedica, Sesto S. Giovanni , Milan, Italy
                Author notes
                Corresponding author. Tel: +39 (0)250318302, E-mail: alberico.catapano@ 123456unimi.it

                Conflict of interest: B.G.N. reports consultancies and talks sponsored by AstraZeneca, Sanofi, Regeneron, Akcea, Amgen, Kowa, Denka, Amarin, Novartis, Novo Nordisk, Esperion, and Silence Therapeutics. A.v.E. and A.T.R. have nothing to disclose. A.L.C. reports grant(s)/support from Akcea, Amarin, Amgen, Menarini, Mylan, Sanofi, and Sanofi/Regeneron; consultant for Akcea, Amgen, Amarin, Daiichi-Sankyo, Eli Lilly, Esperion, Kowa, Ionis Pharmaceuticals, Menarini, MSD, Mylan, Novartis, Recordati, Regeneron, and Sanofi.

                Author information
                https://orcid.org/0000-0002-1666-2266
                https://orcid.org/0000-0002-1954-7220
                https://orcid.org/0000-0001-5839-7280
                https://orcid.org/0000-0002-7593-2094
                Article
                ehac605
                10.1093/eurheartj/ehac605
                10119031
                36337032
                a41addf8-268f-4896-8f06-88543635c99d
                © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 09 June 2022
                : 16 September 2022
                : 10 October 2022
                Page count
                Pages: 14
                Funding
                Funded by: Swiss National Science Foundation, doi 10.13039/501100001711;
                Funded by: Herlev and Gentofte Hospital;
                Funded by: Copenhagen University Hospital, doi 10.13039/501100002918;
                Funded by: Italian Ministry of Health, doi 10.13039/501100003196;
                Categories
                State of the Art Review
                AcademicSubjects/MED00200
                Eurheartj/45
                Eurheartj/47
                Eurheartj/8
                Eurheartj/15
                Eurheartj/17
                Eurheartj/14

                Cardiovascular Medicine
                cholesterol efflux,evolution,remnants,triglycerides,infectious disease,cancer,age-related macular degeneration,autoimmune disease

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