Recent findings indicate that aspects of high-density lipoprotein (HDL) not captured by traditionally measured HDL–cholesterol levels (HDL‑C) are likely to be cardioprotective. This review will highlight some of these studies and suggest new directions to identify the specific molecules that are responsible for the cardioprotective nature of HDL.
by Daniel S. Kim, Dr Patrick M. Hutchins and Prof. Gail P. Jarvik
Raising HDL-C does not confer cardioprotection
There is a well-established inverse association between high-density lipoprotein–cholesterol (HDL-C) levels and cardiovascular disease (CVD) in epidemiological and clinical studies [1, 2]. This robust relationship suggested that HDL-C was in the causal pathway of atheroprotection. Indeed a large number of studies have demonstrated that HDL possesses various anti-atherogenic properties, primarily the ability to accept cholesterol from macrophages in a process termed reverse cholesterol transport [3, 4].
In contrast, several high-profile studies have demonstrated that increasing levels of HDL-C does not have a significant cardioprotective effect. In a large and well-conducted clinical trial of the cholesterol ester transport protein (CETP) inhibitor, torcetrapib, there was no reduction in the incidence of CVD-related events despite significantly higher HDL-C levels [5]. A follow-up study using a different CETP inhibitor, dalcetrapib, also showed increased HDL-C levels yet there was no significant difference in CVD event rate between the treatment and placebo groups [6]. In a third randomized clinical trial that used niacin to increase HDL-C levels, there was again no reduction in cardiovascular events [7]. Finally, a large-scale Mendelian randomization study of approximately 20 000 myocardial infarction (MI) cases and 100 000 controls, showed that a genetic polymorphism which associated with approximately 10% higher HDL-C levels was not associated with decreased incidence of MI [8], again suggesting that the relationship between HDL-C and the prevention of cardiac events is not causal.
HDL particle concentration is a superior predictor of CVD
As the elevation of HDL-C was not beneficial in these studies, some have speculated that HDL itself is not cardioprotective. An alternative explanation for these negative data is that the cholesterol content of HDL – a surrogate measure of HDL – does not best reflect the anti-atherogenic properties of HDL. To resolve these issues it is critical to identify new HDL metrics that reliably reflect its cardioprotective functions.
One promising approach for assessing the role of HDL in CVD is to evaluate the individual HDL particles. HDL is a heterogeneous mixture of lipoprotein particles composed of discrete subspecies that have unique structural compositions and biological functions. As different HDL particles carry vastly different amounts of cholesterol – ranging over an order-of-magnitude [9, 10] – measuring the total HDL-C does not provide information regarding the distribution of HDL subpopulations or the number of total HDL particles.
HDL can be fractionated based on a number of physicochemical properties, most commonly size or density. Several techniques, both qualitative and quantitative, have been developed for HDL subspecies analysis. The various HDL subspecies reported by these techniques and their associated nomenclature are briefly summarized in Table 1 [see also ref. 11]. Furthermore, HDL subspecies determined by ultracentrifugation and calibrated ion mobility analysis (both are discussed in detail later) are shown in Figure 1. Many studies have demonstrated the potential clinical utility of HDL subspecies analysis, which can be achieved by techniques such as 2D gradient gel electrophoresis [12] and nuclear magnetic resonance (NMR) [13]. For example, one study (using 2D gradient gel electrophoresis) showed that very-large, cholesterol-rich α-1 HDLs were better predictors than HDL-C levels of reduced coronary heart disease (CHD) in a subset of males from the Framingham Offspring Study [14]. Another high-profile study, using NMR to assess HDL subspecies in over 2200 participants in the EPIC-Norfolk cohort, showed that higher HDL particle (HDL-P) concentrations were a predictor of reduced CHD, independent of classic CHD risk factors [15]. In more recent work from the Multi-Ethnic Study of Atherosclerosis, total HDL-P (measured by NMR) and HDL-C were evaluated at baseline for 5598 participants, who were then followed prospectively for incident CHD (n=227 events) [16]. Although both HDL-P and HDL-C were highly correlated with each other, in multivariate regression models total HDL-P concentration was the superior predictor of reduced incident CHD when compared to HDL-C. This finding indicates that although HDL-C captures a large portion of HDL-P variation, HDL-P is the better predictor of CHD.
These studies support the notion that measuring individual HDL particle subspecies provides clinically useful information beyond traditionally measured HDL-C. However, both α-1 HDLs (which are cholesterol-rich) and HDL-P measured by NMR (which relies on lipid to generate signal) are highly correlated with HDL-C. Therefore, it is possible that these observations reflect a similar inverse association observed between HDL-C and cardiovascular disease. Importantly, two recent studies (discussed below) indicate that low levels of relatively cholesterol-poor, smaller HDLs also associate with cerebrovascular disease, again suggesting that subspecies of HDL not adequately captured by measuring HDL-C may also play important roles in the pathogenesis of atherosclerotic disease.
Shifting focus: HDL-3 and medium-HDL particles
We investigated the association of the subspecies HDL-2 and HDL-3 (Table 1; Fig. 1) with carotid artery disease (CAAD) [17]. Here, HDL was sub-fractionated by ultracentrifugation and the subspecies were quantified by their cholesterol content. In a case-control cohort of 1,725 participants [part of the Carotid Lesion Epidemiology And Risk (CLEAR) cohort], stepwise linear regression was used to determine whether total HDL-C, HDL-2 cholesterol (HDL-2C), HDL-3 cholesterol (HDL-3C), or apolipoprotein A-I (apoA-I) levels were the best predictor of CAAD. In this study, the smaller HDL-3C fraction was found to be the best predictor of reduced CAAD risk. Moreover, adding HDL-3C to the model improved prediction even when HDL-C levels were also considered, demonstrating added utility of the HDL-3C measure versus HDL-C.
In a separate study using calibrated ion mobility analysis, the particle concentrations of three HDL subspecies (Table 1; Fig. 1) were measured in a subset of the same CLEAR cohort [18]. Participants with severe carotid stenosis (n=40; >80% stenosis by ultrasound in either or both internal carotid artery) had significantly lower plasma concentrations of medium-HDL particles compared with control participants (n=40; <15% stenosis by ultrasound in both carotid arteries). In this population HDL-P was a superior predictor of CAAD compared to HDL-C and this relationship was significant after controlling for HDL-C. The case-control difference in total HDL-P was driven by dramatic changes in medium-HDL particles, the next best predictor of CAAD. This medium-HDL particle inverse association also remained significant after controlling for HDL-C. Considering HDL-3 is composed of small- and medium-HDL particles (Fig. 1) and medium-HDL contributes the majority of HDL-3 cholesterol content, these results are in excellent agreement with the previous study of the CLEAR cohort. Both results support the hypothesis that relatively cholesterol-poor, smaller HDL subspecies, which are under-represented by total HDL-C, are potentially important protective factors for CVD.
Summary and future directions
Considering that increased levels of cholesterol-poor HDL subspecies – reflected by measures of HDL-3, medium size particles, and increased HDL-P – can represent superior predictors of CVD phenotypes, it is possible that pharmacologic attempts to raise HDL-C fail to affect CVD event rates because specifically elevating the cholesterol content of HDL is insufficient. The mechanism of HDL-C elevation should be considered. The agents tested thus far may have increased HDL-C by forming large, cholesterol-rich HDL particles at the expense of medium- and small-HDL particles; having an overall null effect on total particle concentration. Indeed, there is evidence from 2D-gel electrophoresis that very high HDL-C levels observed in CETP deficiency result from a shift from small- and medium-HDLs to large-HDL particles [19]. Thus, HDL directed therapies – especially CETP inhibitors – might increase HDL-C without increasing the number of total HDL-P and possibly reducing the number of potentially beneficial medium-HDL particles. Considering that medium- and total HDL particle concentrations may represent superior predictors of cardioprotection, this hypothesis could explain the failures of the CETP inhibitors and niacin to prevent CVD. We speculate that HDL directed therapies might be more effective in reducing CVD-related events if the number of circulating HDL particles was increased by therapy, especially medium-HDLs.
In light of recent research showing that certain subspecies of HDL (such as medium-HDL and HDL-3) may specifically contribute to cardioprotection, it is our opinion that the focus of research and potential therapies should shift to these promising targets. Of particular interest is the protein cargo of these HDL subspecies, which may reveal important mechanisms related to their cardioprotective properties. For instance, HDL-3 is closely associated with PON1 enzyme activity [20], which is associated with cardioprotection [21, 22]. Notably, the cardioprotective association of HDL-3 was in part independent of both PON1 activity and HDL-C, indicating that there were unmeasured predictive elements of the HDL-3 proteome; these may be apolipoproteins, or ancillary proteins that are specifically associated with HDL-3 [17].
In summary, it is our opinion that the recent failure of increased HDL-C to be cardioprotective likely reflects the fact that increasing HDL-C alone does not adequately increase the concentration or activity of cardioprotective HDL subspecies. It would be an error to say that studies of HDL-C demonstrate that HDL is not cardioprotective. Increased total HDL particle concentration, or perhaps a specific increase in medium-HDL particles, may confer greater protection against CAAD and CHD than pharmaceutically generating a preponderance of large, cholesterol-rich HDL particles. Future research should focus on narrowing down focus through computational, structural and functional studies to identify the specific molecule or molecules that are responsible for the expected cardioprotective effect of HDL.
References
1. Castelli WP. Cardiovascular disease and multifactorial risk: challenge of the 1980s. Am Heart J. 1983; 106: 1191–1200.
2. Gordon DJ, Rifkind BM. High-density lipoprotein–the clinical implications of recent studies. N Engl J Med. 1989; 321: 1311–1316.
3. Rye KA, Bursill CA, Lambert G, Tabet F, Barter PJ. The metabolism and anti-atherogenic properties of HDL. J Lipid Res. 2008; 50: S195–S200.
4. Oram JF, Heinecke JW. ATP-binding cassette transporter A1: a cell cholesterol exporter that protects against cardiovascular disease. Physiol Rev. 2005; 85: 1343–1372.
5. Barter PJ, Barter PJ, Caulfield M, Caulfield M, et al. Effects of torcetrapib in patients at high risk for coronary events. N Engl J Med. 2007; 357: 2109–2122.
6. Schwartz GG, Olsson AG, Abt M, Ballantyne CM, et al. Effects of dalcetrapib in patients with a recent acute coronary syndrome. N Engl J Med. 2012; 367: 2089–2099.
7. AIM-HIGH Investigators, Boden WE, Probstfield JL, Anderson T, et al. Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. N Engl J Med. 2011; 365: 2255–2267.
8. Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet. 2012; 380: 572–580.
9. Shen BW, Scanu AM, Kézdy FJ. Structure of human serum lipoproteins inferred from compositional analysis. Proc Natl Acad Sci U S A. 1977; 74: 837–841.
10. Huang R, Silva RAGD, Jerome WG, Kontush A, et al. Apolipoprotein A-I structural organization in high-density lipoproteins isolated from human plasma. Nat Struct Mol Biol. 2011; 18: 416–422.
11. Rosenson RS, Brewer HB, Chapman MJ, Fazio S, et al. HDL measures, particle heterogeneity, proposed nomenclature, and relation to atherosclerotic cardiovascular events. Clin Chem. 2011; 57: 392–410.
12. Asztalos BF, Sloop CH, Wong L, Roheim PS. Two-dimensional electrophoresis of plasma lipoproteins: recognition of new apo A-I-containing subpopulations. Biochim Biophys Acta 1993; 1169: 291–300.
13. Otvos JD. Measurement of lipoprotein subclass profiles by nuclear magnetic resonance spectroscopy. Clin lab. 2002; 48: 171–180.
14. Asztalos BF, Cupples LA, Demissie S, Horvath KV, et al. High-density lipoprotein subpopulation profile and coronary heart disease prevalence in male participants of the Framingham Offspring Study. Arterioscler Thromb Vasc Biol. 2004; 24: 2181–2187.
15. Harchaoui El K, Arsenault BJ, Franssen R, Després J-P, et al. High-density lipoprotein particle size and concentration and coronary risk. Ann Intern Med. 2009; 150: 84–93.
16. Mackey RH, Greenland P, Goff DC, Lloyd-Jones D, et al. High-density lipoprotein cholesterol and particle concentrations, carotid atherosclerosis, and coronary events: MESA (multi-ethnic study of atherosclerosis). J Am Coll Cardiol. 2012; 60: 508–516.
17. Kim DS, Burt AA, Rosenthal EA, Ranchalis JE, et al. HDL-3 is a superior predictor of carotid artery disease in a case-control cohort of 1725 participants. J Am Heart Assoc. 2014; 3: e000902.
18. Hutchins PM, Ronsein GE, Monette JS, Pamir N, et al. Quantification of HDL particle concentration by calibrated ion mobility analysis. Clin Chem. 2014; 60: 1393–1401.
19. Asztalos BF. Apolipoprotein composition of HDL in cholesteryl ester transfer protein deficiency. J Lipid Res. 2003; 45: 448–455.
20. Kontush A, Chantepie S, Chapman MJ. Small, dense HDL particles exert potent protection of atherogenic LDL against oxidative stress. Arterioscler Thromb Vasc Biol. 2003; 23: 1881–1888.
21. Jarvik GP, Rozek LS, Brophy VH, Hatsukami TS, et al. Paraoxonase (PON1) Phenotype Is a Better Predictor of Vascular Disease Than Is PON1192 or PON155 Genotype. Arterioscler Thromb Vasc Biol. 2000; 20: 2441–2447.
22. Kim DS, Marsillach J, Furlong CE, Jarvik GP. Pharmacogenetics of paraoxonase activity: elucidating the role of high-density lipoprotein in disease. Pharmacogenomics 2013; 14: 1495–1515.
The authors
Daniel Seung Kim1–3† BS; Patrick M. Hutchins4† PhD; Gail P. Jarvik1,2 MD, PhD
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
2Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA
3Department of Biostatistics, University of Washington, Seattle, WA, USA
4Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington, Seattle, WA, USA
†Authors contributed equally to this work
*Corresponding author
E-mail: pair@u.washington.edu
Acknowledgement
DSK is supported in part by 1F31MH101905-01 and a Markey Foundation Award. PMH is supported by a Cardiovascular Fellowship Training Grant (NIH T32HL007828). Work on the CLEAR study referenced within was supported by National Institutes of Health RO1 HL67406 and a State of Washington Life Sciences Discovery Award (265508) to the Northwest Institute of Genetic Medicine.
A Comparative Study of Two Methods for the Determination of the Albumin/Creatinine Ratio
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, /in Featured Articles /by 3wmediaPossible polio resurgence and the anti-vax movement
, /in Featured Articles /by 3wmediaLast month was the 100th anniversary of the birth of Jonas Salk who developed the first effective polio vaccine. Prior to its widespread use in the West from the mid 1950s on, seasonal polio outbreaks in North America and Europe killed some children and caused life long paralysis in others. In the 1952 polio epidemic in the United States, 57,628 cases were reported with 3,145 fatalities and 21,269 cases of paralysis. Indeed those of us attending school before the advent of routine polio vaccination saw some of our fellow pupils returning after the summer break in leg braces; sadly occasionally a desk would remain empty. Now the global polio eradication effort has essentially eliminated the disease from all but three countries where it remains endemic, namely Nigeria, Afghanistan and Pakistan. In 2013 there were just 416 cases worldwide; so far this year there have been 306 cases. The aim is to totally eradicate the disease by 2018, but this goal may be thwarted because of the increased international spread of wild polio virus from endemic countries. The situation in Pakistan is causing most concern as the number of cases has more than quadrupled from 53 last year to 260 so far this year, and a major factor has been the ruthless militant violence against Pakistani teams vaccinating children against polio. More than 65 healthcare workers and supporting staff have been killed in the last two years, the latest shot dead in late November.
The anti-vax movement in the West is less immediately perilous, but is unfortunately growing, greatly facilitated by misinformed pressure groups disseminating dangerously misleading information using social media. One reason is that medical success has bred complacency: thanks to effective vaccination programmes polio is no longer endemic, and the former childhood scourges of measles, pertussis, tetanus and diphtheria are currently rare. Parents thus focus on the possible health risks of the vaccines – and most of these perceived risks have no scientific basis – rather than on the morbidity and mortality rate of the diseases themselves and the increasing danger of epidemics in non-immune populations. A common fallacy is that parental decisions have no repercussions for other families. But we know that 95% of children must be vaccinated against a disease to achieve ‘herd immunity’; this allows even hypersensitive children who cannot be vaccinated to be safe. If Western parents can’t be persuaded by means of pertinent information to protect their nation’s children from disease, it is high time for some coercion.
Metabolic syndrome: definition, grading and treatment
, /in Featured Articles /by 3wmediaMetabolic syndrome is characterized by a collection of disorders, making it difficult to diagnose and stage. This article describes the criteria used for diagnosis as well as discussing treatment strategies.
by Prof. Giuseppe Derosa and Dr Pamela Maffioli
Definition and grading
Metabolic syndrome is a combination of medical disorders that increases the risk of developing cardiovascular disease; it affects one in five people in the United States, and prevalence increases with age. There are different definitions of metabolic syndrome; according to the Adult Treatment Panel (ATP) III [1], metabolic syndrome requires the presence of at least three of the listed criteria (Table 1).
Recently insulin resistance has been cited to be associated with other metabolic risk factors and correlates with cardiovascular risk. The pro-inflammatory state has also been developed and used as a marker to predict coronary vascular diseases in metabolic syndrome: it is identified by higher C-reactive protein (CRP) levels, commonly present in people with metabolic syndrome. One cause of elevated CRP is obesity, because adipose tissue releases inflammatory cytokines that may elicit higher CRP levels. Also, the pro-thrombotic state has been recently considered for the definition of metabolic syndrome, characterized by increased plasma plasminogen activator inhibitor-1 (PAI-1) and fibrinogen. However, the ATP III panel did not find adequate evidence to recommend routine measurement of insulin-resistance, pro-inflammatory state (e.g. high-sensitivity C-reactive protein), or pro-thrombotic state (e.g. fibrinogen or PAI-1) in the diagnosis of the metabolic syndrome.
The World Health Organization (WHO) criteria, instead, emphasized insulin resistance as the major underlying risk factor and required evidence of insulin resistance for diagnosis (Table 2) [2, 3].
The International Diabetes Federation (IDF), instead, dropped the WHO requirement for insulin resistance, but made abdominal obesity necessary for the diagnosis, with particular emphasis on waist measurement as a simple screening tool [4]; the other criteria (Table 3) were essentially identical to those provided by ATP III [1].
The American Association of Clinical Endocrinologists (AACE) proposed a third set of clinical criteria for the insulin resistance syndrome [5]. These criteria appear to be a hybrid of those of the ATP III and WHO metabolic syndrome. However, no defined number of risk factors is specified and diagnosis is left to clinical judgment (Table 4).
Given that multiple definitions of the same disease can generate confusion among physicians, the major organizations made an attempt to unify the various criteria for the definition of metabolic syndrome [6]. It was agreed that there should not be an obligatory component, but that waist measurement would continue to be a useful preliminary screening tool. Three abnormal findings out of five would qualify a person for the metabolic syndrome according to the unified definition shown in Table 5.
As readers can easily understand, individuals with metabolic syndrome are at increased risk for coronary heart disease (CHD) [7]. In particular, in the absence of diabetes, the metabolic syndrome generally did not raise the 10-year risk for CHD by more than 20% [8], in particular 10-year risk generally ranged from 10% to 20% for men and did not exceed 10% for women. However, in the presence of diabetes, the risk increases. Obviously, patients fulfilling all or almost all of the metabolic syndrome potential criteria, have earlier and more serious organ damage, at both cardiac and vascular levels, than patients with only three out of five components of the metabolic syndrome definition.
Treatment
Despite the grade of metabolic syndrome, however, there are two general approaches to its treatment. The first strategy modifies root causes, overweight/obesity and physical inactivity, and their closely associated condition, insulin resistance. The second approach directly treats the metabolic risk factors such as atherogenic dyslipidemia, hypertension, the pro-thrombotic state, and underlying insulin resistance. ATP III recommended that obesity be the primary target of intervention for metabolic syndrome [9]. First-line therapy should be weight reduction; the current recommendations for the treatment of overweight and obese people include increased physical activity and reduced calorie intake [10, 11]. Pharmacological treatment with orlistat can be another option, and when it is not tolerated, bariatric surgery should be considered. However, surgery irreversibly changes the overall architecture of the digestive tract; in this regard, the endoscopic duodenal–jejunal bypass liner can be another option. It consists of a sheath that is inserted endoscopically through the mouth into the digestive tract of the obese patient creating a physical barrier between the intestinal wall and the food ingested. The device can be considered as an alternative to bariatric surgery because of the minimal adverse events and the possibility to easily remove the device when the desired weight has been achieved [12]. Weight loss is important because it lowers serum cholesterol and triglycerides, raises HDL-cholesterol, lowers blood pressure and glucose, and reduces insulin resistance. Published data further show that weight reduction can decrease serum levels of CRP and PAI-1 [13–16]. In addition, other lipid and non-lipid risk factors associated with the metabolic syndrome should be appropriately treated. Atherogenic dyslipidemia includes elevated serum triglycerides and apolipoprotein B, increased small LDL particles, and reduced level of HDL-cholesterol. The treatment strategy for atherogenic dyslipidemia in metabolic syndrome focuses on triglycerides. If triglycerides are ≥150 mg/dL and HDL-cholesterol is <40 mg/dL, a diagnosis of atherogenic dyslipidemia is made. If triglycerides are <200 mg/dL, and specific drug therapy to reduce triglyceride-rich lipoproteins is not indicated. However, if the patient has CHD or CHD risk equivalents, LDL-cholesterol goal has to be considered together with the use of a drug to raise HDL-cholesterol (fibrate). On the other hand, if triglycerides are 200–499 mg/dL, non-HDL cholesterol becomes a secondary target of therapy. Goals for non-HDL cholesterol are 30 mg/dL higher than those for LDL-cholesterol. First the LDL-cholesterol goal is attained, and if non-HDL remains elevated, additional therapy may be required to achieve the non-HDL goal. Alternative approaches for treatment of elevated non-HDL cholesterol that persists after the LDL goal has been achieved are (a) higher doses of statins, or (b) moderate doses of statins + triglyceride-lowering drug (fibrate). If triglycerides are very high (≥500 mg/dL), attention turns first to prevention of acute pancreatitis, which is more likely to occur when triglycerides are >1000 mg/dL. Triglyceride-lowering drugs (fibrate) become the first line therapy; although statins can be used to lower LDL-cholesterol to reach the LDL-cholesterol goal, in these patients it is often difficult (and unnecessary) to achieve a non-HDL cholesterol goal of only 30 mg/dL higher than for LDL-cholesterol [9].
Conclusion
In conclusion, metabolic syndrome increases cardiovascular risk; a multifactorial approach is necessary in order to prevent the development of the various components of this disease.
References
1. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation 2002; 106: 3143–3421.
2. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus: provisional report of a WHO consultation. Diabet Med. 1998; 15: 539–553.
3. World Health Organization. Definition, diagnosis and classification of diabetes mellitus and its complications: report of a WHO Consultation. Part 1: diagnosis and classification of diabetes mellitus. Geneva, Switzerland: World Health Organization; 1999. Available at: http:// whqlibdoc.who.int/hq/1999/WHO_NCD_NCS_99.2.pdf.
4. Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome: a new worldwide definition. Lancet 2005; 366: 1059–1062.
5. Einhorn D, Reaven GM, Cobin RH, Ford E, Ganda OP, Handelsman Y, Hellman R, Jellinger PS, Kendall D, Krauss RM, Neufeld ND, Petak SM, Rodbard HW, Seibel JA, Smith DA, Wilson PW. American College of Endocrinology position statement on the insulin resistance syndrome. Endocr Pract. 2003; 9: 237–252.
6. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr; International Diabetes Federation Task Force on Epidemiology and Prevention; Hational Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120 (16): 1640–1645.
7. Lakka HM, Laaksonen DE, Lakka TA, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 2002; 288: 2709–2716.
8. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbrshatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998; 97: 1837–1847.
9. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002; 106 (25): 3143–3421.
10. American Diabetes Association. Nutrition principles and recommendations in diabetes. Diabetes Care 2004; 27(S1): 36–46.
11. American Diabetes Association. Physical activity/exercise and diabetes. Diabetes Care 2004; 27(S1): 58–62.
12. Derosa G, Maffioli P. Possible therapies for obesity: focus on the available options for its treatment. Nutrition 2014; doi: 10.1016/j.nut.2014.09.005.
13. Dengel DR, Galecki AT, Hagberg JM, Pratley RE. The independent and combined effects of weight loss and aerobic exercise on blood pressure and oral glucose tolerance in older men. Am J Hypertens. 1998; 11: 1405–1412.
14. Ahmad F, Considine RV, Bauer TL, Ohannesian JP, Marco CC, Goldstein BJ. Improved sensitivity to insulin in obese subjects following weight loss is accompanied by reduced protein-tyrosine phosphatases in adipose tissue. Metabolism 1997; 46: 1140–1145.
15. Su HY, Sheu WH, Chin HM, Jeng CY, Chen YD, Reaven GM. Effect of weight loss on blood pressure and insulin resistance in normotensive and hypertensive obese individuals. Am J Hypertens. 1995; 8: 1067–1071.
16. Derosa G, Limas CP, Macías PC, Estrella A, Maffioli P. Dietary and nutraceutical approach to type 2 diabetes. Arch Med Sci. 2014; 10(2): 336–344.
The authors
Giuseppe Derosa1,2 MD, PhD, Pamela Maffioli1,3 MD
1Department of Internal Medicine and Therapeutics, University of Pavia, Fondazione IRCCS Policlinico S. Matteo, PAVIA, Italy.
2Center for the Study of Endocrine-Metabolic Pathophysiology and Clinical Research, University of Pavia, PAVIA, Italy.
3PhD School in Experimental Medicine, University of Pavia, PAVIA, Italy
E-mail: giuseppe.derosa@unipv.it
Cardiac biomarkers – new weapons against cardiovascular disease
, /in Featured Articles /by 3wmediaAlthough formally defined as recently as the early 2000s, biomarkers have quickly begun to gain acceptance in clinical practice. Many experts believe they will become an indispensable tool for the diagnosis and management of a wide variety of medical conditions in the near future.
Cardiovascular disease now a global priority
One of the priority applications for biomarkers is likely to be for cardiovascular diseases (CVD) – the leading cause of mortality and disability in the Western world. In Europe, CVD causes 1.9 million deaths a year, while the toll in the US is about 1 million.
The prevalence of CVD is also increasing rapidly in newly industrializing countries, especially among the more affluent urban populations adopting Western lifestyles. Indeed, “CVD is now more numerous in India and China than in all economically developed countries in the world added together.”
Mapping the disease progression pathway
It has, for some time, been accepted that CVD follows a relatively clear-cut pathway from subclinical to overt status. The Multi-Ethnic Study of Atherosclerosis (MESA), sponsored in the year 2000 by the US National Institutes of Health, has been seeking to assess the characteristics of subclinical CVD and means to predict its progression to clinically overt cardiovascular disease. More recently, in 2010, Spain’s Banco Santander and the Istituto de Salud Carlos III launched a similar effort in Europe called PESA (Progression of Early Subclinical Atherosclerosis).
Such efforts are targeted at providing clinicians with tools to help assess CVD and identify vulnerable, at-risk patients. In many respects, they complement the world’s most ambitious effort in the area, the Framingham Heart Study, which began in 1948 in a town in Massachusetts in the US with 5,209 adult subjects. The Study, which has now enrolled its third generation of participants, has resulted in the publication of over 1,000 medical papers. It has also provided many commonplace tools for the contemporary understanding of CVD, including the impact of smoking, diet and exercise, medications such as aspirin etc. – as well as the term ‘risk factor’.
The Framingham project: clarifying the role of biomarkers
Biomarkers began to be part of the Framingham project in the 2000s, although initial results were unclear. For instance, enthusiasm about elevated levels of the inflammation marker C-reactive protein (CRP) as an independent risk factor for future CVD events were dispelled in a 2005 study supported by the Framingham sponsors.
In September 2012, a study in the American Heart Association’s journal ‘Circulation’ pointed to one reason for such conflicting assessments, namely the “lack of cardiovascular specificity” in many of the new biomarkers. The authors sought to address such limitations by studying three key CVD biomarkers (soluble ST2, growth differentiation factor-15 and high-sensitivity troponin I) in almost 3,500 patients. The findings were conclusive: “Multiple biomarkers of cardiovascular stress,” they said “add prognostic value to standard risk factors for predicting death, overall cardiovascular events, and heart failure.”
In 2014, another study of 2,680 Framingham participants sought to associate circulating biomarkers with The American Heart Association Cardiovascular Health score (CVH score). The authors concluded there was an “inverse association” between ideal CVH and CVD incidence, and that this was partly attributable to its “favourable impact on CVD biomarker levels and subclinical disease.” The list of CVD biomarkers in the 2014 study includes natriuretic peptides (N-terminal pro-atrial and B-type natriuretic peptide), plasminogen activator inhibitor-1, aldosterone, C-reactive protein, D-dimer, fibrinogen, homocysteine and growth differentiation factor-15.
Identification of at-risk patients
One of the most promising biomarkers seems to be cardiac troponin, first identified in the early 1990s. Changes in cardiac troponin T (cTnT) levels over time appear to correlate with heart failure risk, especially in a major study of elderly subjects.
The potential of circulating cTnT may also extend beyond the heart failure setting. Some argue that circulating cTnT is representative of subclinical myocardial dysfunction. In the general population, studies show that elevated cTnT is associated with subclinical cardiac injury, and marks an increased risk for structural heart disease and all-cause mortality.
Other studies have found that myeloperoxidase (MPO) and high-sensitivity C-reactive protein (hsCRP) in apparently healthy populations can predict risk of coronary disease, allowing for early preventative treatment. Together, MPO and C-reactive protein have also shown promise in prognostic risk assessment for patients with systolic heart failure.
Enabling targeted and timely treatment
While screening the general population is bound to draw considerable attention, the more immediate application of CVD biomarkers is to enable treatment in a risk-stratified and timely fashion.
One of the biggest challenges faced by physicians is to differentiate between patients with unstable angina and acute myocardial infarction (AMI) in an emergency setting. Here too cTnT – as well as cardiac troponin I (cTnI) – have catalysed some of the greatest excitement, due to their high sensitivity and specificity for cardiac damage.
In 2007, the US National Academy of Clinical Biochemistry Laboratory Medicine Practice recommended the use of cardiac troponin as a ‘preferred’ biomarker for MI diagnosis, in conjunction with clinical evidence of myocardial ischemia. Creatine kinase-MB was positioned as an ‘acceptable alternative’. These recommendations were endorsed by the joint European Society of Cardiology/American College of Cardiology/American Heart Association/World Heart Federation task force for the definition of myocardial infarction.
Cardiac troponin ‘the best single marker’
Levels of cardiac troponin are dependent on infarct size, and directly indicate the prognosis following MI. Indeed, in recent years, some experts suggest that CTnI and CTnT have “displaced myoglobin and creatine kinase-MB as the preferred markers of myocardial injury.”
In 2013, a Health Technology Asssessment (HTA) by Britain’s National Institute for Health Research (NIHR) concurred with this view, observing that “high-sensitivity cardiac troponin is the best single marker in patients presenting with chest pain.” Additional measurements of myoglobin or creatine kinase-MB, it noted were “not clinically effective or cost-effective.”
Debate on troponin not over
Nevertheless, considerable debate remains about the utility of troponin in real world CVD management. Although patients with undetectable troponins are considered to have excellent short-term prognosis, levels may be undetectable “for six hours after the onset of myocardial cell injury,” making myoglobin “a preferred early marker” for MI. This limitation, which seems to go against the 2013 NIHR Health Technology Assessment, is also acknowledged by some proponents of troponin, who admit that although it “may be useful for risk assessment and management” in asymptomatic populations, there is no evidence that it confers “an advantage in the context of MI diagnosis.” In addition, they also note that “cTnI assays are not standardized; thus, there can be a substantial difference in values depending on the assay used.”
Defining assay sensitivity, differentiating troponin I and T
One challenge lies in the definition of a ‘high sensitivity’ assay, which can measure cTn in the single digit range of nanograms per litre. The term is used by vendors “for marketing purposes,” and there “is still no consensus” regarding its application. Making matters tougher is the fact that most manufacturers’ claims for assay precision “cannot be achieved in clinical laboratories.”
In effect, the jury on troponin is likely to be out for some time to come, accompanied by continuing uncertainties.
For instance, Britain’s respected health advisory site patient.co.uk suggests that troponin I and T “are of equal clinical value” while a 2010 guideline from NICE (National Institute for Healthcare and Clinical Excellence) advises taking a blood sample for troponin I or T as “preferred biochemical markers to diagnose acute MI.”
However, a very recent study published by the Journal of the American College of Cardiology finds that patients with neuromuscular disease can show elevated levels of troponin T but not I, thus questioning the guidelines which regard both as being “equally sensitive and specific for the diagnosis of myocardial injury.”
These may be some of the reasons why the US Food and Drug Administration (FDA) decided in June 2014 to discuss clarification of claims and protocols with vendors of troponin assays, in order to “modernize the performance evaluation and regulatory review.” In Britain, NICE is currently updating its 2010 guideline.
The role of B-type natriuretic peptide
Once acute MI is confirmed, a variety of other biomarkers are used to help make assessments.
One of the most promising of these is B-type natriuretic peptide or BNP, designated by the FDA in the year 2000 as a Class II diagnostic device.
Nevertheless, it is important to underline that only troponin has been used to direct therapeutic intervention. Though it is evident that the adoption of proven new biomarkers will increase prognostic accuracy, they have yet to be tested to alter outcomes of therapeutic intervention.
Thus, in spite of statements from reputable sources claiming that BNP is “already used to diagnose heart failure,” the truth is somewhat different, with the difference in the details. At the end of 2013, the US Agency for Healthcare Research and Quality (AHRQ), investigated BNP and the related N-terminal proBNP (NT-proBNP) for detecting heart failure (HF). The findings were guarded: “BNP and NT-proBNP had good diagnostic performance for ruling out HF but were less accurate for ruling in HF.” In addition, it found that the “therapeutic value was inconclusive.”
Other biomarkers remain valuable
In the meanwhile, clinicians in emergency settings have recourse to a variety of other established CVD risk markers, such as cholesterol. “Research is also under way on markers with strong predictive value that are not used in the clinic for cardiovascular disease risk prediction, such as fibrinogen, vitamin D, and cystatin C.” Some of these “are of special interest as these may prove to be valuable biomarkers in the future.”
To have clinical utility, however, such biomarkers will need to provide risk assessments independently of other established markers. They also require the presence of standardized assays which are specific and sensitive for the markers, with easy-to-interpret results.
In effect, biomarker-mediated approaches to CVD need to yield superior patient outcomes compared to current standard-of-care management schemes.
The HDL particle: frontiers for new discovery in cardioprotection
, /in Featured Articles /by 3wmediaRecent findings indicate that aspects of high-density lipoprotein (HDL) not captured by traditionally measured HDL–cholesterol levels (HDL‑C) are likely to be cardioprotective. This review will highlight some of these studies and suggest new directions to identify the specific molecules that are responsible for the cardioprotective nature of HDL.
by Daniel S. Kim, Dr Patrick M. Hutchins and Prof. Gail P. Jarvik
Raising HDL-C does not confer cardioprotection
There is a well-established inverse association between high-density lipoprotein–cholesterol (HDL-C) levels and cardiovascular disease (CVD) in epidemiological and clinical studies [1, 2]. This robust relationship suggested that HDL-C was in the causal pathway of atheroprotection. Indeed a large number of studies have demonstrated that HDL possesses various anti-atherogenic properties, primarily the ability to accept cholesterol from macrophages in a process termed reverse cholesterol transport [3, 4].
In contrast, several high-profile studies have demonstrated that increasing levels of HDL-C does not have a significant cardioprotective effect. In a large and well-conducted clinical trial of the cholesterol ester transport protein (CETP) inhibitor, torcetrapib, there was no reduction in the incidence of CVD-related events despite significantly higher HDL-C levels [5]. A follow-up study using a different CETP inhibitor, dalcetrapib, also showed increased HDL-C levels yet there was no significant difference in CVD event rate between the treatment and placebo groups [6]. In a third randomized clinical trial that used niacin to increase HDL-C levels, there was again no reduction in cardiovascular events [7]. Finally, a large-scale Mendelian randomization study of approximately 20 000 myocardial infarction (MI) cases and 100 000 controls, showed that a genetic polymorphism which associated with approximately 10% higher HDL-C levels was not associated with decreased incidence of MI [8], again suggesting that the relationship between HDL-C and the prevention of cardiac events is not causal.
HDL particle concentration is a superior predictor of CVD
As the elevation of HDL-C was not beneficial in these studies, some have speculated that HDL itself is not cardioprotective. An alternative explanation for these negative data is that the cholesterol content of HDL – a surrogate measure of HDL – does not best reflect the anti-atherogenic properties of HDL. To resolve these issues it is critical to identify new HDL metrics that reliably reflect its cardioprotective functions.
One promising approach for assessing the role of HDL in CVD is to evaluate the individual HDL particles. HDL is a heterogeneous mixture of lipoprotein particles composed of discrete subspecies that have unique structural compositions and biological functions. As different HDL particles carry vastly different amounts of cholesterol – ranging over an order-of-magnitude [9, 10] – measuring the total HDL-C does not provide information regarding the distribution of HDL subpopulations or the number of total HDL particles.
HDL can be fractionated based on a number of physicochemical properties, most commonly size or density. Several techniques, both qualitative and quantitative, have been developed for HDL subspecies analysis. The various HDL subspecies reported by these techniques and their associated nomenclature are briefly summarized in Table 1 [see also ref. 11]. Furthermore, HDL subspecies determined by ultracentrifugation and calibrated ion mobility analysis (both are discussed in detail later) are shown in Figure 1. Many studies have demonstrated the potential clinical utility of HDL subspecies analysis, which can be achieved by techniques such as 2D gradient gel electrophoresis [12] and nuclear magnetic resonance (NMR) [13]. For example, one study (using 2D gradient gel electrophoresis) showed that very-large, cholesterol-rich α-1 HDLs were better predictors than HDL-C levels of reduced coronary heart disease (CHD) in a subset of males from the Framingham Offspring Study [14]. Another high-profile study, using NMR to assess HDL subspecies in over 2200 participants in the EPIC-Norfolk cohort, showed that higher HDL particle (HDL-P) concentrations were a predictor of reduced CHD, independent of classic CHD risk factors [15]. In more recent work from the Multi-Ethnic Study of Atherosclerosis, total HDL-P (measured by NMR) and HDL-C were evaluated at baseline for 5598 participants, who were then followed prospectively for incident CHD (n=227 events) [16]. Although both HDL-P and HDL-C were highly correlated with each other, in multivariate regression models total HDL-P concentration was the superior predictor of reduced incident CHD when compared to HDL-C. This finding indicates that although HDL-C captures a large portion of HDL-P variation, HDL-P is the better predictor of CHD.
These studies support the notion that measuring individual HDL particle subspecies provides clinically useful information beyond traditionally measured HDL-C. However, both α-1 HDLs (which are cholesterol-rich) and HDL-P measured by NMR (which relies on lipid to generate signal) are highly correlated with HDL-C. Therefore, it is possible that these observations reflect a similar inverse association observed between HDL-C and cardiovascular disease. Importantly, two recent studies (discussed below) indicate that low levels of relatively cholesterol-poor, smaller HDLs also associate with cerebrovascular disease, again suggesting that subspecies of HDL not adequately captured by measuring HDL-C may also play important roles in the pathogenesis of atherosclerotic disease.
Shifting focus: HDL-3 and medium-HDL particles
We investigated the association of the subspecies HDL-2 and HDL-3 (Table 1; Fig. 1) with carotid artery disease (CAAD) [17]. Here, HDL was sub-fractionated by ultracentrifugation and the subspecies were quantified by their cholesterol content. In a case-control cohort of 1,725 participants [part of the Carotid Lesion Epidemiology And Risk (CLEAR) cohort], stepwise linear regression was used to determine whether total HDL-C, HDL-2 cholesterol (HDL-2C), HDL-3 cholesterol (HDL-3C), or apolipoprotein A-I (apoA-I) levels were the best predictor of CAAD. In this study, the smaller HDL-3C fraction was found to be the best predictor of reduced CAAD risk. Moreover, adding HDL-3C to the model improved prediction even when HDL-C levels were also considered, demonstrating added utility of the HDL-3C measure versus HDL-C.
In a separate study using calibrated ion mobility analysis, the particle concentrations of three HDL subspecies (Table 1; Fig. 1) were measured in a subset of the same CLEAR cohort [18]. Participants with severe carotid stenosis (n=40; >80% stenosis by ultrasound in either or both internal carotid artery) had significantly lower plasma concentrations of medium-HDL particles compared with control participants (n=40; <15% stenosis by ultrasound in both carotid arteries). In this population HDL-P was a superior predictor of CAAD compared to HDL-C and this relationship was significant after controlling for HDL-C. The case-control difference in total HDL-P was driven by dramatic changes in medium-HDL particles, the next best predictor of CAAD. This medium-HDL particle inverse association also remained significant after controlling for HDL-C. Considering HDL-3 is composed of small- and medium-HDL particles (Fig. 1) and medium-HDL contributes the majority of HDL-3 cholesterol content, these results are in excellent agreement with the previous study of the CLEAR cohort. Both results support the hypothesis that relatively cholesterol-poor, smaller HDL subspecies, which are under-represented by total HDL-C, are potentially important protective factors for CVD.
Summary and future directions
Considering that increased levels of cholesterol-poor HDL subspecies – reflected by measures of HDL-3, medium size particles, and increased HDL-P – can represent superior predictors of CVD phenotypes, it is possible that pharmacologic attempts to raise HDL-C fail to affect CVD event rates because specifically elevating the cholesterol content of HDL is insufficient. The mechanism of HDL-C elevation should be considered. The agents tested thus far may have increased HDL-C by forming large, cholesterol-rich HDL particles at the expense of medium- and small-HDL particles; having an overall null effect on total particle concentration. Indeed, there is evidence from 2D-gel electrophoresis that very high HDL-C levels observed in CETP deficiency result from a shift from small- and medium-HDLs to large-HDL particles [19]. Thus, HDL directed therapies – especially CETP inhibitors – might increase HDL-C without increasing the number of total HDL-P and possibly reducing the number of potentially beneficial medium-HDL particles. Considering that medium- and total HDL particle concentrations may represent superior predictors of cardioprotection, this hypothesis could explain the failures of the CETP inhibitors and niacin to prevent CVD. We speculate that HDL directed therapies might be more effective in reducing CVD-related events if the number of circulating HDL particles was increased by therapy, especially medium-HDLs.
In light of recent research showing that certain subspecies of HDL (such as medium-HDL and HDL-3) may specifically contribute to cardioprotection, it is our opinion that the focus of research and potential therapies should shift to these promising targets. Of particular interest is the protein cargo of these HDL subspecies, which may reveal important mechanisms related to their cardioprotective properties. For instance, HDL-3 is closely associated with PON1 enzyme activity [20], which is associated with cardioprotection [21, 22]. Notably, the cardioprotective association of HDL-3 was in part independent of both PON1 activity and HDL-C, indicating that there were unmeasured predictive elements of the HDL-3 proteome; these may be apolipoproteins, or ancillary proteins that are specifically associated with HDL-3 [17].
In summary, it is our opinion that the recent failure of increased HDL-C to be cardioprotective likely reflects the fact that increasing HDL-C alone does not adequately increase the concentration or activity of cardioprotective HDL subspecies. It would be an error to say that studies of HDL-C demonstrate that HDL is not cardioprotective. Increased total HDL particle concentration, or perhaps a specific increase in medium-HDL particles, may confer greater protection against CAAD and CHD than pharmaceutically generating a preponderance of large, cholesterol-rich HDL particles. Future research should focus on narrowing down focus through computational, structural and functional studies to identify the specific molecule or molecules that are responsible for the expected cardioprotective effect of HDL.
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The authors
Daniel Seung Kim1–3† BS; Patrick M. Hutchins4† PhD; Gail P. Jarvik1,2 MD, PhD
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
2Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA
3Department of Biostatistics, University of Washington, Seattle, WA, USA
4Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington, Seattle, WA, USA
†Authors contributed equally to this work
*Corresponding author
E-mail: pair@u.washington.edu
Acknowledgement
DSK is supported in part by 1F31MH101905-01 and a Markey Foundation Award. PMH is supported by a Cardiovascular Fellowship Training Grant (NIH T32HL007828). Work on the CLEAR study referenced within was supported by National Institutes of Health RO1 HL67406 and a State of Washington Life Sciences Discovery Award (265508) to the Northwest Institute of Genetic Medicine.