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Li LJ, Wei Y, Zhao YL, Gao Y, Hu XQ. Radical-Mediated Decarboxylative C-C and C-S Couplings of Carboxylic Acids via Iron Photocatalysis. Org Lett 2024; 26:1110-1115. [PMID: 38277128 DOI: 10.1021/acs.orglett.3c04395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
Despite the significant success of decarboxylative radical reactions, the catalytic systems vary considerably upon different radical acceptors, requiring renewed case-by-case reaction optimization. Herein, we developed an iron catalytic condition that enables the highly efficient decarboxylation of various carboxylic acids for a range of radical transformations. This operationally simple protocol was amenable to a wide array of radical acceptors, delivering structurally diverse oxime ethers, alkenylation, alkynylation, thiolation, and amidation products in useful to excellent yields (>40 examples, up to 95% yield).
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Affiliation(s)
- Li-Jing Li
- Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education & Hubei Key Laboratory of Catalysis and Materials Science, School of Chemistry and Materials Science, South-Central Minzu University, Wuhan 430074, China
| | - Yi Wei
- Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education & Hubei Key Laboratory of Catalysis and Materials Science, School of Chemistry and Materials Science, South-Central Minzu University, Wuhan 430074, China
| | - Yu-Lian Zhao
- Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education & Hubei Key Laboratory of Catalysis and Materials Science, School of Chemistry and Materials Science, South-Central Minzu University, Wuhan 430074, China
| | - Yang Gao
- School of Chemical Engineering and Light Industry, Guangdong University of Technology, Guangzhou 510006, China
| | - Xiao-Qiang Hu
- Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education & Hubei Key Laboratory of Catalysis and Materials Science, School of Chemistry and Materials Science, South-Central Minzu University, Wuhan 430074, China
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2
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Ahsan L, Zheng WQ, Kaur G, Kadakuntla A, Remaley AT, Sampson M, Feustel P, Nappi A, Mookherjee S, Lyubarova R. Association of Lipoprotein Subfractions With Presence and Severity of Coronary Artery Disease in Patients Referred for Coronary Angiography. Am J Cardiol 2023; 203:212-218. [PMID: 37499601 DOI: 10.1016/j.amjcard.2023.06.107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/13/2023] [Accepted: 06/29/2023] [Indexed: 07/29/2023]
Abstract
Lipoprotein subfractions (LS) can be used for better risk stratification in subjects deemed not at high risk for coronary artery disease (CAD). In this study, we evaluated the correlation between LS with CAD presence and severity. This is a prospective case-control study of 157 patients referred for coronary angiography who were not on lipid-lowering therapy and had LS measured by nuclear magnetic resonance spectroscopy. Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) scores were calculated to estimate CAD severity. Univariate and multivariable regression analysis was performed to determine correlation of LS with CAD presence and severity and acute coronary syndrome (ACS). There was significant association of certain LS (positive for total low-density lipoprotein particle [LDL-P], small LDL-P and apolipoprotein B, negative for large high-density lipoprotein particle [HDL-P] and apolipoprotein A1 [ApoA1]) with the presence of obstructive CAD and CAD severity. Small LDL-P and HDL-P were still predictive for obstructive CAD after adjusting for traditional risk factors, 10-year atherosclerotic cardiovascular disease risk score and in those with low-density lipoprotein cholesterol <100 mg/100 ml. Total LDL-P and ApoA1 were predictive of CAD severity on multivariable analysis. Higher small LDL-P and lower large HDL-P were associated with ACS presence, although only large HDL-P had a significant inverse correlation with ACS on adjusted analysis (odds ratio 0.74 95% confidence interval 0.58, 0.95) In conclusion, in our cohort of patients referred for coronary angiography, total LDL-P, small LDL-P, and apolipoprotein B had significant direct correlation, and large HDL-P and ApoA1 had significant inverse correlation with obstructive CAD and CAD severity.
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Affiliation(s)
- Lusana Ahsan
- Department of Medicine, Albany Medical College, Albany, New York
| | - Wen Qian Zheng
- Department of Medicine, Albany Medical College, Albany, New York
| | - Gurleen Kaur
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Alan T Remaley
- Lipoprotein Metabolism Laboratory, National Heart, Lung and Blood Institute, National Institute of Health, Bethesda, Maryland
| | - Maureen Sampson
- Department Laboratory Medicine, Clinical Center, National Institute of Health, Bethesda, Maryland
| | - Paul Feustel
- Department of Medicine, Albany Medical College, Albany, New York
| | - Anthony Nappi
- Department of Medicine, Albany Medical College, Albany, New York
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3
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Cole J, Zubirán R, Wolska A, Jialal I, Remaley AT. Use of Apolipoprotein B in the Era of Precision Medicine: Time for a Paradigm Change? J Clin Med 2023; 12:5737. [PMID: 37685804 PMCID: PMC10488498 DOI: 10.3390/jcm12175737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/10/2023] Open
Abstract
Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death worldwide and the risk of a major cardiovascular event is highest among those with established disease. Ongoing management of these patients relies on the accurate assessment of their response to any prescribed therapy, and their residual risk, in order to optimize treatment. Recent international guidelines and position statements concur that the plasma concentration of apolipoprotein B (apoB) is the most accurate measure of lipoprotein associated ASCVD risk. This is especially true for the growing number of individuals with diabetes, obesity, or the metabolic syndrome, and those on statin therapy. Most guidelines, however, continue to promote LDL-C as the primary risk marker due to uncertainty as to whether the greater accuracy of apoB is sufficient to warrant a paradigm shift. Recommendations regarding apoB measurement vary, and the information provided on how to interpret apoB results is sometimes insufficient, particularly for non-lipid specialists. Misinformation regarding the reliability of the assays is also frequently repeated despite its equivalent or better standardization than many other diagnostic assays. Thus, demand for apoB testing is relatively low, which means there is little incentive to increase its availability or reduce its cost. In this review, we examine the results of recent clinical outcomes studies and meta-analyses on the relative values of apoB, LDL-C, and non-HDL-C as markers of ASCVD risk. Although there is seemingly minimal difference among these markers when only population-based metrics are considered, it is evident from our analysis that, from a personalized or precision medicine standpoint, many individuals would benefit, at a negligible total cost, if apoB measurement were better integrated into the diagnosis and treatment of ASCVD.
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Affiliation(s)
- Justine Cole
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA; (R.Z.); (A.W.); (A.T.R.)
| | - Rafael Zubirán
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA; (R.Z.); (A.W.); (A.T.R.)
| | - Anna Wolska
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA; (R.Z.); (A.W.); (A.T.R.)
| | - Ishwarlal Jialal
- Department of Pathology and Internal Medicine, University of California-Davis, Sacramento, CA 95817, USA;
| | - Alan T. Remaley
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA; (R.Z.); (A.W.); (A.T.R.)
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4
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Shao B, Afshinnia F, Mathew AV, Ronsein GE, Thornock C, Irwin AD, Kansal M, Rao PS, Dobre M, Al-Kindi S, Weir MR, Go A, He J, Chen J, Feldman H, Bornfeldt KE, Pennathur S. Low concentrations of medium-sized HDL particles predict incident CVD in chronic kidney disease patients. J Lipid Res 2023; 64:100381. [PMID: 37100172 PMCID: PMC10323925 DOI: 10.1016/j.jlr.2023.100381] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 04/18/2023] [Accepted: 04/19/2023] [Indexed: 04/28/2023] Open
Abstract
Patients with chronic kidney disease (CKD) are at high risk for CVD. However, traditional CVD risk factors cannot completely explain the increased risk. Altered HDL proteome is linked with incident CVD in CKD patients, but it is unclear whether other HDL metrics are associated with incident CVD in this population. In the current study, we analyzed samples from two independent prospective case-control cohorts of CKD patients, the Clinical Phenotyping and Resource Biobank Core (CPROBE) and the Chronic Renal Insufficiency Cohort (CRIC). We measured HDL particle sizes and concentrations (HDL-P) by calibrated ion mobility analysis and HDL cholesterol efflux capacity (CEC) by cAMP-stimulated J774 macrophages in 92 subjects from the CPROBE cohort (46 CVD and 46 controls) and in 91 subjects from the CRIC cohort (34 CVD and 57 controls). We tested associations of HDL metrics with incident CVD using logistic regression analysis. No significant associations were found for HDL-C or HDL-CEC in either cohort. Total HDL-P was only negatively associated with incident CVD in the CRIC cohort in unadjusted analysis. Among the six sized HDL subspecies, only medium-sized HDL-P was significantly and negatively associated with incident CVD in both cohorts after adjusting for clinical confounders and lipid risk factors with odds ratios (per 1-SD) of 0.45 (0.22-0.93, P = 0.032) and 0.42 (0.20-0.87, P = 0.019) for CPROBE and CRIC cohorts, respectively. Our observations indicate that medium-sized HDL-P-but not other-sized HDL-P or total HDL-P, HDL-C, or HDL-CEC-may be a prognostic cardiovascular risk marker in CKD.
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Affiliation(s)
- Baohai Shao
- Department of Medicine, UW Medicine Diabetes Institute, University of Washington, Seattle, WA, USA.
| | - Farsad Afshinnia
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Anna V Mathew
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Graziella E Ronsein
- Department of Medicine, UW Medicine Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Carissa Thornock
- Department of Medicine, UW Medicine Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Angela D Irwin
- Department of Medicine, UW Medicine Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Mayank Kansal
- Department of Cardiology, University of Illinois at Chicago, Chicago, IL, USA
| | - Panduranga S Rao
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Mirela Dobre
- Division of Nephrology and Hypertension, Case Western Reserve University, Cleveland, OH, USA
| | - Sadeer Al-Kindi
- Division of Nephrology and Hypertension, Case Western Reserve University, Cleveland, OH, USA
| | - Matthew R Weir
- Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alan Go
- Department of Health System Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Jing Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Harold Feldman
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Karin E Bornfeldt
- Department of Medicine, UW Medicine Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Subramaniam Pennathur
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA; Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
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5
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Kostara CE. Expanding the Molecular Disturbances of Lipoproteins in Cardiometabolic Diseases: Lessons from Lipidomics. Diagnostics (Basel) 2023; 13. [PMID: 36832218 DOI: 10.3390/diagnostics13040721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 01/28/2023] [Accepted: 02/13/2023] [Indexed: 02/17/2023] Open
Abstract
The increasing global burden of cardiometabolic diseases highlights the urgent clinical need for better personalized prediction and intervention strategies. Early diagnosis and prevention could greatly reduce the enormous socio-economic burden posed by these states. Plasma lipids including total cholesterol, triglycerides, HDL-C, and LDL-C have been at the center stage of the prediction and prevention strategies for cardiovascular disease; however, the bulk of cardiovascular disease events cannot be explained sufficiently by these lipid parameters. The shift from traditional serum lipid measurements that are poorly descriptive of the total serum lipidomic profile to comprehensive lipid profiling is an urgent need, since a wealth of metabolic information is currently underutilized in the clinical setting. The tremendous advances in the field of lipidomics in the last two decades has facilitated the research efforts to unravel the lipid dysregulation in cardiometabolic diseases, enabling the understanding of the underlying pathophysiological mechanisms and identification of predictive biomarkers beyond traditional lipids. This review presents an overview of the application of lipidomics in the study of serum lipoproteins in cardiometabolic diseases. Integrating the emerging multiomics with lipidomics holds great potential in moving toward this goal.
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6
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Jin Q, Lau ESH, Luk AO, Tam CHT, Ozaki R, Lim CKP, Wu H, Chow EYK, Kong APS, Lee HM, Fan B, Ng ACW, Jiang G, Lee KF, Siu SC, Hui G, Tsang CC, Lau KP, Leung JY, Tsang MW, Cheung EYN, Kam G, Lau IT, Li JK, Yeung VT, Lau E, Lo S, Fung S, Cheng YL, Chow CC, Yu W, Tsui SKW, Huang Y, Lan HY, Szeto CC, So WY, Jenkins AJ, Chan JCN, Ma RCW. High-density lipoprotein subclasses and cardiovascular disease and mortality in type 2 diabetes: analysis from the Hong Kong Diabetes Biobank. Cardiovasc Diabetol 2022; 21:293. [PMID: 36587202 PMCID: PMC9805680 DOI: 10.1186/s12933-022-01726-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/13/2022] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVE High-density lipoproteins (HDL) comprise particles of different size, density and composition and their vasoprotective functions may differ. Diabetes modifies the composition and function of HDL. We assessed associations of HDL size-based subclasses with incident cardiovascular disease (CVD) and mortality and their prognostic utility. RESEARCH DESIGN AND METHODS HDL subclasses by nuclear magnetic resonance spectroscopy were determined in sera from 1991 fasted adults with type 2 diabetes (T2D) consecutively recruited from March 2014 to February 2015 in Hong Kong. HDL was divided into small, medium, large and very large subclasses. Associations (per SD increment) with outcomes were evaluated using multivariate Cox proportional hazards models. C-statistic, integrated discrimination index (IDI), and categorial and continuous net reclassification improvement (NRI) were used to assess predictive value. RESULTS Over median (IQR) 5.2 (5.0-5.4) years, 125 participants developed incident CVD and 90 participants died. Small HDL particles (HDL-P) were inversely associated with incident CVD [hazard ratio (HR) 0.65 (95% CI 0.52, 0.81)] and all-cause mortality [0.47 (0.38, 0.59)] (false discovery rate < 0.05). Very large HDL-P were positively associated with all-cause mortality [1.75 (1.19, 2.58)]. Small HDL-P improved prediction of mortality [C-statistic 0.034 (0.013, 0.055), IDI 0.052 (0.014, 0.103), categorical NRI 0.156 (0.006, 0.252), and continuous NRI 0.571 (0.246, 0.851)] and CVD [IDI 0.017 (0.003, 0.038) and continuous NRI 0.282 (0.088, 0.486)] over the RECODe model. CONCLUSION Small HDL-P were inversely associated with incident CVD and all-cause mortality and improved risk stratification for adverse outcomes in people with T2D. HDL-P may be used as markers for residual risk in people with T2D.
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Affiliation(s)
- Qiao Jin
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Eric S. H. Lau
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Andrea O. Luk
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Claudia H. T. Tam
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Risa Ozaki
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Cadmon K. P. Lim
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Hongjiang Wu
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Elaine Y. K. Chow
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Alice P. S. Kong
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Heung Man Lee
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Baoqi Fan
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Alex C. W. Ng
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Guozhi Jiang
- grid.12981.330000 0001 2360 039XSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong China
| | - Ka Fai Lee
- grid.415591.d0000 0004 1771 2899Department of Medicine and Geriatrics, Kwong Wah Hospital, Yau Ma Tei, Hong Kong Special Administrative Region China
| | - Shing Chung Siu
- grid.417347.20000 0004 1799 526XDiabetes Centre, Tung Wah Eastern Hospital, Sheung Wan, Hong Kong Special Administrative Region China
| | - Grace Hui
- grid.417347.20000 0004 1799 526XDiabetes Centre, Tung Wah Eastern Hospital, Sheung Wan, Hong Kong Special Administrative Region China
| | - Chiu Chi Tsang
- grid.413608.80000 0004 1772 5868Diabetes and Education Centre, Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong Special Administrative Region China
| | - Kam Piu Lau
- grid.490321.d0000000417722990North District Hospital, Sheung Shui, Hong Kong Special Administrative Region China
| | - Jenny Y. Leung
- grid.416291.90000 0004 1775 0609Department of Medicine and Geriatrics, Ruttonjee Hospital, Wan Chai, Hong Kong Special Administrative Region China
| | - Man-wo Tsang
- grid.417037.60000 0004 1771 3082Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong Special Administrative Region China
| | - Elaine Y. N. Cheung
- grid.417037.60000 0004 1771 3082Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong Special Administrative Region China
| | - Grace Kam
- grid.417037.60000 0004 1771 3082Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong Special Administrative Region China
| | - Ip Tim Lau
- grid.490601.a0000 0004 1804 0692Tseung Kwan O Hospital, Hang Hau, Hong Kong Special Administrative Region China
| | - June K. Li
- grid.417335.70000 0004 1804 2890Department of Medicine, Yan Chai Hospital, Tsuen Wan, Hong Kong Special Administrative Region China
| | - Vincent T. Yeung
- grid.499546.30000 0000 9690 2842Centre for Diabetes Education and Management, Our Lady of Maryknoll Hospital, Wong Tai Sin, Hong Kong Special Administrative Region China
| | - Emmy Lau
- grid.417134.40000 0004 1771 4093Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong Special Administrative Region China
| | - Stanley Lo
- grid.417134.40000 0004 1771 4093Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong Special Administrative Region China
| | - Samuel Fung
- grid.415229.90000 0004 1799 7070Department of Medicine and Geriatrics, Princess Margaret Hospital, Lai Chi Kok, Hong Kong Special Administrative Region China
| | - Yuk Lun Cheng
- grid.413608.80000 0004 1772 5868Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong Special Administrative Region China
| | - Chun Chung Chow
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Weichuan Yu
- grid.24515.370000 0004 1937 1450Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Kowloon, Hong Kong Special Administrative Region China
| | - Stephen K. W. Tsui
- grid.10784.3a0000 0004 1937 0482School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Yu Huang
- grid.10784.3a0000 0004 1937 0482School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.35030.350000 0004 1792 6846Department of Biomedical Sciences, City University of Hong Kong, Kowloon, Hong Kong Special Administrative Region China
| | - Hui-yao Lan
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Cheuk Chun Szeto
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Wing Yee So
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China
| | - Alicia J. Jenkins
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.1013.30000 0004 1936 834XNHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia
| | - Juliana C. N. Chan
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
| | - Ronald C. W. Ma
- grid.10784.3a0000 0004 1937 0482Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,grid.10784.3a0000 0004 1937 0482Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region China ,CUHK-SJTU Joint Research Centre on Diabetes Genomics and Precision Medicine, Shatin, Hong Kong Special Administrative Region China
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7
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Quesada JA, Bertomeu-gonzález V, Orozco-beltrán D, Cordero A, Gil-guillén VF, López-pineda A, Nouni-garcía R, Carratalá-munuera C. The benefits of measuring the size and number of lipoprotein particles for cardiovascular risk prediction: A systematic review and meta-analysis. Clínica e Investigación en Arteriosclerosis 2022. [PMID: 36522243 DOI: 10.1016/j.arteri.2022.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/10/2022] [Accepted: 11/14/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Cardiovascular risk (CVR) is conventionally calculated by measuring the total cholesterol content of high-density lipoproteins (HDL) and low-density lipoproteins (LDL). The purpose of this systematic review was to assess the CVR associated with LDL and HDL particle size and number as determined by nuclear magnetic resonance (NMR) spectroscopy. MATERIAL AND METHODS A literature search was performed using the electronic databases MEDLINE and Scopus. All cohort and case-control studies published before January 1, 2019 that met the following inclusion criteria were included: HDL-P, LDL-P, HDL-Z and/or LDL-Z measured by NMR spectroscopy; cardiovascular event as an outcome variable; risk of cardiovascular events expressed as odds ratios or hazard ratios; only adult patients. A meta-analysis was performed for each exposure variable (4 for LDL and 5 for HDL) and for each exposure measure (highest versus lowest quartile and 1-standard deviation increment). RESULTS This review included 24 studies. Number of LDL particles was directly associated with CVR: risk increased by 28% with each standard deviation increment. LDL particle size was inversely and significantly associated with CVR: each standard deviation increment corresponded to an 8% risk reduction. CVR increased by 12% with each standard deviation increase in number of small LDL particles. HD, particle number and size were inversely associated with CVR. CONCLUSION Larger particle size provided greater protection, although this relationship was inconsistent between studies. Larger number of LDL particles and smaller LDL particle size are associated with increased CVR. Risk decreases with increasing number and size of HDL particles.
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Chen Y, Fu Y, Wang S, Chen P, Pei Y, Zhang J, Zhang R, Niu G, Gu F, Li X. Clinical significance of neutrophil gelatinase-associated lipocalin and sdLDL-C for coronary artery disease in patients with type 2 diabetes mellitus aged ≥ 65 years. Cardiovasc Diabetol 2022; 21:252. [PMID: 36397150 DOI: 10.1186/s12933-022-01668-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/14/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND AND AIMS Although type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) share many common pathological and physiological characteristics, there are few studies assessing the predictive capacity of novel biomarkers in occurrence and development of CAD in T2DM patients aged ≥ 65 years. In addition, T2DM patients aged ≥ 65 years are prone to CAD. Therefore, it is of great significance to find novel biomarkers for the development CAD in T2DM. METHODS In this retrospective cohort study, 579 T2DM patients aged ≥ 65 years were consecutively enrolled in this work, and 177 of whom had major adverse cardiovascular and cerebrovascular events (MACCE: cardiovascular or cerebrovascular death, acute coronary syndrome, coronary stent implantation, and stroke) during the follow up. Univariate and multivariate factors were employed to analyze the correlation between each variable and the occurrence of MACCE, and the Spearman's rank correlation analysis was performed to assess the relationships between Neutrophil gelatinase-associated lipocalin (NGAL) and small dense low-density lipoprotein-cholesterol (LDL-C) (sdLDL-C). The receiver operating characteristic (ROC) curve was adopted to determine the predictive value of NGAL and sdLDL-C elevation for MACCE in T2DM patients aged ≥ 65 years. RESULTS After a median 48 months follow-up [19, (10 ~ 32) ], the levels of NGAL, sdLDL-C, hemoglobin A1c (HbA1c), LDL-C, and apolipoprotein B (ApoB) were significantly higher while those of high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A I (ApoA-I) were lower in MACCE positive group. NGAL correlated to body mass index (BMI) (r = 0.391, P = 0.001) and triglyceride (TG) (r = 0.228, P = 0.032), and high-sensitivity CRP (hsCRP) (r = 0.251, P = 0.007), and neutrophils (r = 0.454, P = 0.001), sdlDL-C level was found to be positively correlated with LDL-C (r = 0.413, P = 0.001), TG (r = 0.432, P = 0.001), and ApoB (r = 0.232, P = 0.002); and it was negatively correlated with HDL-C (r = -0.362, P = 0.031) and ApoA-I (r = -0.402, P = 0.001). Age-adjusted Cox regression analysis showed that NGAL (HR = 1.006, 95% confidence interval (CI): 1.005-1.008, P < 0.001) and sdLDL-C (HR = 1.052, 95% CI: 1.037-1.066, P < 0.001) were independently associated with occurrence of MACCE. ROC curve analysis showed that NGAL (area under ROC (AUC) = 0.79, 95% CI: 0.75-0.84, P < 0.001) and sdlDL-C (AUC = 0.76, 95% CI: 0.72-0.80, P < 0.001) could predict the occurrence of MACCE (area under ROC. NGAL combined with sdlDL-C could predict the occurrence of MACCE well (AUC = 0.87, 95% CI: 0.84-0.90, P < 0.001). CONCLUSION The higher NGAL and sdLDL-C in T2DM patients aged ≥ 65 years were significantly and independently associated with the risk of MACCE, and showed higher clinical values than other lipid biomarkers or other chronic inflammation, so they were expected to be the most effective predictors of MACCE assessment.
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Sykes AV, Patel N, Lee D, Taub PR. Integrating Advanced Lipid Testing and Biomarkers in Assessment and Treatment. Curr Cardiol Rep 2022; 24:1647-1655. [PMID: 36001215 DOI: 10.1007/s11886-022-01775-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/15/2022] [Indexed: 01/11/2023]
Abstract
PURPOSE OF REVIEW Our ability to assess and stratify atherosclerotic disease risk in patients is evolving. Recent advances in advanced lipid testing have created opportunities for clinical application of novel biomarkers. RECENT FINDINGS Until recently, LDL-C has served largely as the singular biomarker of ASCVD and guide for decisions in treatment for high-risk groups. There are important evolutions in the measurement of LDL-C but even still, the pathogenesis of atherosclerosis and ASCVD is not solely driven by LDL-C. As atherosclerosis is driven by multiple complex pathways including inflammation, it is important to expand our focus beyond LDL-C and utilize multiple biomarkers in the assessment of this disease process. Non-HDL, ApoB, LDL-P, Lp(a), and hsCRP are unique tools to aid in cardiac risk evaluation, especially in higher risk patients, though not limited to this population. A multifaceted approach to advanced lipid testing with novel biomarkers will enhance comprehensive ASCVD risk assessments.
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Affiliation(s)
- Alexandra Vaio Sykes
- Internal Medicine UC San Diego, La Jolla, 200 W. Arbor Drive, San Diego, CA, 92103-8425, USA.
| | - Neeja Patel
- UC San Diego School of Medicine, La Jolla, San Diego, CA, USA
| | - Danielle Lee
- Family Medicine UC San Diego, La Jolla, San Diego, CA, USA
| | - Pam R Taub
- Cardiovascular Medicine, UC San Diego, La Jolla, San Diego, CA, USA
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Dogay Us G, Mushtaq S. N-3 fatty acid supplementation mediates lipid profile, including small dense LDL, when combined with statins: a randomized double blind placebo controlled trial. Lipids Health Dis 2022; 21:84. [PMID: 36050695 PMCID: PMC9434850 DOI: 10.1186/s12944-022-01686-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 08/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epidemiological and clinical evidence suggests that high-dose intake of omega 3 fatty acids (n-3 FA) have a favorable role in altering serum triglycerides (TG) and non-high density lipoprotein cholesterol (non-HDL-C) when combined with statins in hyperlipidemic patients. Their efficacy in altering low-density lipoprotein cholesterol (LDL-C) particle size is yet to be established. AIM This study evaluated the effects of supplementing 4 g/day Eicosapentaenoic acid (EPA) and Docosahexaenoic acid (DHA) on serum blood lipids, including small, dense LDL-C particle concentration, in hyperlipidemic patients receiving stable statin therapy. METHODS In this randomized, placebo-controlled, double-blind parallel group study, 44 patients on statin therapy for > 8 weeks with non-HDL-C concentrations above 130 mg/dL were randomized into two groups. For 8 weeks, together with their prescribed statin, the intervention group received 4 g/day EPA + DHA (3000 mg EPA + 1000 mg DHA in ethyl ester form) and the placebo group received 4 g/day olive oil (OO). Measurements of serum non-HDL-C, TG, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), LDL-C (including large - LDL I; intermediate - LDL II; and small - LDL III subclasses), very-low-density lipoprotein cholesterol (VLDL-C) concentration, were taken at baseline and post-intervention. Dietary intake was assessed with a weighed intake, 3-day food diary at week 4. Primary outcome measures were percent change in LDL III, non-HDL-C and LDL particle number. RESULTS At the end of treatment, the median percent change in serum LDL III concentration was significantly greater in the n-3 FA group plus atorvastatin compared to placebo (- 67.5% vs - 0%, respectively; P < 0.001). Supplementation with n-3 FA plus atorvastatin led to significant reductions in serum non-HDL-C (- 9.5% vs 4.7%, P < 0.01), TG (- 21.5% vs 6.2%, P < 0.001) and VLDL-C (- 36.9% vs 4.0%, P < 0.001) and TC (- 6.6% vs 2.1%, P < 0.001). Between the groups, no significant difference in percent change in the serum concentration of LDL-C, HDL-C, as well as in the LDL I and LDL II subclasses was observed. CONCLUSION In this group of hyperlipidemic patients on a stable statin prescription, OM3 plus atorvastatin improved small dense LDL concentrations, non-HDL-C, VLDL-C and TG to a greater extent than atorvastatin alone. Further studies are warranted in this area. TRIAL REGISTRATION This trial was retrospectively registered on 23 May 2019 on ClinicalTrials.gov with ID: NCT03961763.
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Affiliation(s)
- Gediz Dogay Us
- University of Chester, Parkgate Road, Chester, CH1 4BJ, UK. .,NUTRIM School of Nutrition and Translational Research In Metabolism, Maastricht University, Maastricht, Netherlands.
| | - Sohail Mushtaq
- University of Chester, Parkgate Road, Chester, CH1 4BJ, UK.,University of Chester, Faculty of Medicine, Dentistry and Life Sciences, Parkgate Road, Chester, CH1 4BJ, UK
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Rief M, Raggam R, Rief P, Metnitz P, Stojakovic T, Reinthaler M, Brodmann M, März W, Scharnagl H, Silbernagel G. Comparison of Two Nuclear Magnetic Resonance Spectroscopy Methods for the Measurement of Lipoprotein Particle Concentrations. Biomedicines 2022; 10:biomedicines10071766. [PMID: 35885071 PMCID: PMC9312544 DOI: 10.3390/biomedicines10071766] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 07/05/2022] [Accepted: 07/16/2022] [Indexed: 11/25/2022] Open
Abstract
Background: Measuring lipoprotein particle concentrations may help to improve cardiovascular risk stratification. Both the lipofit (Numares) and lipoprofile (LabCorp) NMR methods are widely used for the quantification of lipoprotein particle concentrations. Objective: The aim of the present work was to perform a method comparison between the lipofit and lipoprofile NMR methods. In addition, there was the objective to compare lipofit and lipoprofile measurements of standard lipids with clinical chemistry-based results. Methods: Total, LDL, and HDL cholesterol and triglycerides were measured with ß-quantification in serum samples from 150 individuals. NMR measurements of standard lipids and lipoprotein particle concentrations were performed by Numares and LabCorp. Results: For both NMR methods, differences of mean concentrations compared to ß-quantification-derived measurements were ≤5.5% for all standard lipids. There was a strong correlation between ß-quantification- and NMR-derived measurements of total and LDL cholesterol and triglycerides (all r > 0.93). For both, the lipofit (r = 0.81) and lipoprofile (r = 0.84) methods, correlation coefficients were lower for HDL cholesterol. There was a reasonable correlation between LDL and HDL lipoprotein particle concentrations measured with both NMR methods (both r > 0.9). However, mean concentrations of major and subclass lipoprotein particle concentrations were not as strong. Conclusions: The present analysis suggests that reliable measurement of standard lipids is possible with these two NMR methods. Harmonization efforts would be needed for better comparability of particle concentration data.
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Affiliation(s)
- Martin Rief
- Division of General Anaesthesiology, Emergency- and Intensive Care Medicine, Department of Anaesthesiology and Intensive Care Medicine, Medical University of Graz, A-8036 Graz, Austria; (M.R.); (P.M.)
| | - Reinhard Raggam
- Division of Angiology, Department of Internal Medicine, Medical University of Graz, A-8036 Graz, Austria; (R.R.); (P.R.); (M.B.); (G.S.)
| | - Peter Rief
- Division of Angiology, Department of Internal Medicine, Medical University of Graz, A-8036 Graz, Austria; (R.R.); (P.R.); (M.B.); (G.S.)
| | - Philipp Metnitz
- Division of General Anaesthesiology, Emergency- and Intensive Care Medicine, Department of Anaesthesiology and Intensive Care Medicine, Medical University of Graz, A-8036 Graz, Austria; (M.R.); (P.M.)
| | - Tatjana Stojakovic
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, University Hospital Graz, A-8036 Graz, Austria;
| | - Markus Reinthaler
- Department of Cardiology (CBF), Charité-Universitätsmedizin Berlin, 12203 Berlin, Germany;
- Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht, 14513 Teltow, Germany
| | - Marianne Brodmann
- Division of Angiology, Department of Internal Medicine, Medical University of Graz, A-8036 Graz, Austria; (R.R.); (P.R.); (M.B.); (G.S.)
| | - Winfried März
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, A-8036 Graz, Austria;
| | - Hubert Scharnagl
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, A-8036 Graz, Austria;
- Correspondence: ; Tel.: +43-(0)316-385-86030
| | - Günther Silbernagel
- Division of Angiology, Department of Internal Medicine, Medical University of Graz, A-8036 Graz, Austria; (R.R.); (P.R.); (M.B.); (G.S.)
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Li T, Zhang Y, Xu J, Wang L, Zhang F, Cong H. Lipoprotein Subfractions as Markers for Predicting the Presence and Severity of Coronary Artery Disease in Patients Undergoing Coronary Angiography. Angiology 2022; 74:435-442. [PMID: 35786030 DOI: 10.1177/00033197221112134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Patients with coronary artery disease (CAD) often have normal blood cholesterol profiles that make it difficult to identify those at risk. The role of lipoprotein subfractions in the development of CAD has attracted increasing attention, and can further stratify risks. We enrolled 1578 patients undergoing coronary angiography and not taking any lipid-lowering drugs; 1033 of them were diagnosed with CAD. The severity of CAD was assessed using Gensini score (GS) and divided into 3 groups. Multivariate regression analysis showed that low-density lipoprotein particle 6 (LDL-P6) and lipoprotein (a) (Lp(a)) were independent risk factors for CAD, apart for the traditional risk factors. In receiver-operating characteristic (ROC) analysis for predicting the presence of CAD, the area under the ROC curve of traditional risk factors combined with Lp(a) and LDL-P6 for predicting CAD was .723, which was better than for traditional risk factors (P = .023). The plasma LDL-P6 and Lp(a) concentrations in the highest tertile GS group were significantly higher than that in the lowest GS group (P < .001). Stepwise linear regression analysis demonstrated positive correlations between Lp(a), LDL-P6 and GS (P = .007 and P < .001). LDL-P6 and Lp(a) are useful markers for predicting the presence and severity of CAD.
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Affiliation(s)
- Tingting Li
- Department of Cardiology, 499773Tianjin Chest Hospital, Tianjin, China
| | - Yingyi Zhang
- Department of Cardiology, 499773Tianjin Chest Hospital, Tianjin, China
| | - Jinghan Xu
- Department of Cardiology, 499773Tianjin Chest Hospital, Tianjin, China
| | - Le Wang
- Department of Cardiology, 499773Tianjin Chest Hospital, Tianjin, China
| | - Fomin Zhang
- 12610Thoracic Clinical College, Tianjin Medical University, Tianjin, China
| | - Hongliang Cong
- Department of Cardiology, 499773Tianjin Chest Hospital, Tianjin, China
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de la Cruz-Ares S, Leon-Acuña A, Yubero-Serrano EM, Torres-Peña JD, Arenas-de Larriva AP, Cardelo MP, Rangel-Zuñiga OA, Luque RM, Alcala-Diaz JF, Ordovas JM, Perez-Martinez P, Lopez-Miranda J, Delgado-Lista J. High density lipoprotein subfractions and extent of coronary atherosclerotic lesions: From the cordioprev study. Clin Chim Acta 2022; 533:89-95. [PMID: 35700819 DOI: 10.1016/j.cca.2022.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/02/2022] [Accepted: 06/03/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND AND AIMS The extent of atherosclerotic coronary heart disease (CHD) is associated with its prognosis, thus discovering potential biomarkers related to worse outcomes could prove valuable. The present work aims to investigate whether lipoprotein subfractions are associated with angiographic CHD severity. MATERIALS AND METHODS Patients from the CORDIOPREV study exhibiting coronary lesions in angiography were classified into two groups (single-vessel coronary disease (SVD) or multivessel coronary disease (MVD)). High-throughput nuclear magnetic resonance (NMR) spectroscopy determined lipoprotein subfractions concentration and composition. RESULTS SVD patients showed a higher concentration of medium and small HDL particles compared with MVD patients. For medium HDL, total lipids, phospholipids, total cholesterol, cholesteryl esters and free cholesterol reflected HDL particle concentration, whereas, for small HDL, total lipids, phospholipids, and free cholesterol mirrored lipoprotein particle concentration. Among traditional cardiovascular risk factors, age, hypertension and T2D were independently associated with angiography severity. In multivariate logistic regression models, medium and small HDL particles remained inversely associated with angiography severity (OR 0.77 (95% CI: 0.64-0.91); OR 0.78 (95% CI: 0.67-0.91), respectively) after adjusting with covariates. CONCLUSION In CHD patients mostly on statin treatment, angiography severity is inversely related to small and medium HDL subclasses concentration measured by NMR. These particles are also independent predictors of the presence of MVD, and its use increased the prediction of this entity over traditional risk factors.
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Affiliation(s)
- Silvia de la Cruz-Ares
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Ana Leon-Acuña
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Elena M Yubero-Serrano
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose D Torres-Peña
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Antonio P Arenas-de Larriva
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain
| | - Magdalena P Cardelo
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Oriol A Rangel-Zuñiga
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Raul M Luque
- Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain; Department of Cell Biology, Physiology, and Immunology, University of Cordoba, 14004 Cordoba, Spain
| | - Juan F Alcala-Diaz
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Human Nutrition Research Center of Aging, Tufts University, Boston, MA 02111, USA; IMDEA Food Institute, 28049 Madrid, Spain
| | - Pablo Perez-Martinez
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jose Lopez-Miranda
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Javier Delgado-Lista
- Lipids and Atherosclerosis Unit, Internal Medicine Unit, Reina Sofia University Hospital, 14004 Cordoba, Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Cordoba, Spain; Department of Medical and Surgical Sciences, University of Cordoba, 14004 Cordoba, Spain; CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
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Abstract
PURPOSE OF REVIEW Levels of small, dense low-density lipoprotein (LDL) (sdLDL) particles determined by several analytic procedures have been associated with risk of atherosclerotic cardiovascular disease (ASCVD). This review focuses on the clinical significance of sdLDL measurement. RECENT FINDINGS Results of multiple prospective studies have supported earlier evidence that higher levels of sdLDL are significantly associated with greater ASCVD risk, in many cases independent of other lipid and ASCVD risk factors as well as levels of larger LDL particles. A number of properties of sdLDL vs. larger LDL, including reduced LDL receptor affinity and prolonged plasma residence time as well as greater oxidative susceptibility and affinity for arterial proteoglycans, are consistent with their heightened atherogenic potential. Nevertheless, determination of the extent to which sdLDL can preferentially impact ASCVD risk compared with other apoprotein B-containing lipoproteins has been confounded by their metabolic interrelationships and statistical collinearity, as well as differences in analytic procedures and definitions of sdLDL. SUMMARY A growing body of data points to sdLDL concentration as a significant determinant of ASCVD risk. Although future studies should be aimed at determining the clinical benefit of reducing sdLDL levels, there is sufficient evidence to warrant consideration of sdLDL measurement in assessing and managing risk of cardiovascular disease. VIDEO ABSTRACT https://www.dropbox.com/s/lioohr2ead7yx2p/zoom_0.mp4?dl=0.
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Karwatowska-prokopczuk E, Tardif J, Gaudet D, Ballantyne CM, Shapiro MD, Moriarty PM, Baum SJ, Amour ES, Alexander VJ, Xia S, Otvos JD, Witztum JL, Tsimikas S. Effect of olezarsen targeting APOC-III on lipoprotein size and particle number measured by NMR in patients with hypertriglyceridemia. J Clin Lipidol 2022. [DOI: 10.1016/j.jacl.2022.06.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 06/01/2022] [Accepted: 06/15/2022] [Indexed: 11/21/2022]
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Affiliation(s)
- Don P Wilson
- Pediatric Cardiovascular Health and Risk Prevention Program, Pediatric Endocrinology and Diabetes, Cook Children's Medical Center, Fort Worth, TX.
| | - Lauren Williams
- Pediatric Cardiovascular Health and Risk Prevention Program, Pediatric Endocrinology and Diabetes, Cook Children's Medical Center, Fort Worth, TX
| | - Rae-Ellen W Kavey
- Department of Pediatrics, University of Rochester School of Medicine, Rochester, NY
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O’Kelly AC, Michos ED, Shufelt CL, Vermunt JV, Minissian MB, Quesada O, Smith GN, Rich-Edwards JW, Garovic VD, El Khoudary SR, Honigberg MC. Pregnancy and Reproductive Risk Factors for Cardiovascular Disease in Women. Circ Res 2022; 130:652-672. [PMID: 35175837 PMCID: PMC8870397 DOI: 10.1161/circresaha.121.319895] [Citation(s) in RCA: 96] [Impact Index Per Article: 48.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Beyond conventional risk factors for cardiovascular disease, women face an additional burden of sex-specific risk factors. Key stages of a woman's reproductive history may influence or reveal short- and long-term cardiometabolic and cardiovascular trajectories. Early and late menarche, polycystic ovary syndrome, infertility, adverse pregnancy outcomes (eg, hypertensive disorders of pregnancy, gestational diabetes, preterm delivery, and intrauterine growth restriction), and absence of breastfeeding are all associated with increased future cardiovascular disease risk. The menopause transition additionally represents a period of accelerated cardiovascular disease risk, with timing (eg, premature menopause), mechanism, and symptoms of menopause, as well as treatment of menopause symptoms, each contributing to this risk. Differences in conventional cardiovascular disease risk factors appear to explain some, but not all, of the observed associations between reproductive history and later-life cardiovascular disease; further research is needed to elucidate hormonal effects and unique sex-specific disease mechanisms. A history of reproductive risk factors represents an opportunity for comprehensive risk factor screening, refinement of cardiovascular disease risk assessment, and implementation of primordial and primary prevention to optimize long-term cardiometabolic health in women.
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Affiliation(s)
- Anna C. O’Kelly
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Erin D. Michos
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, MD,Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chrisandra L. Shufelt
- Barbra Streisand Women’s Heart Center, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jane V. Vermunt
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Margo B. Minissian
- Barbra Streisand Women’s Heart Center, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA,Geri and Richard Brawerman Nursing Institute, Cedars-Sinai Medical Center, Los Angeles CA
| | - Odayme Quesada
- Women’s Heart Center, The Christ Hospital Heart and Vascular Institute, Cincinnati, OH,The Carl and Edyth Lindner Center for Research and Education, The Christ Hospital, Cincinnati, OH
| | - Graeme N. Smith
- Department of Obstetrics and Gynecology, Queen’s University, Kingston, Ontario, Canada
| | - Janet W. Rich-Edwards
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Vesna D. Garovic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Samar R. El Khoudary
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Michael C. Honigberg
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA,Corrigan Women’s Heart Health Program, Massachusetts General Hospital, Boston, MA
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18
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Asztalos BF, Hauser TH, Goldfine AB, Welty FK, Horvath KV, Schaefer EJ. The role of HDL- and non-HDL-related parameters in cell-cholesterol efflux capacity. Atherosclerosis 2022. [DOI: 10.1016/j.atherosclerosis.2022.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 02/02/2022] [Accepted: 02/09/2022] [Indexed: 11/23/2022]
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19
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Grao-Cruces E, Lopez-Enriquez S, Martin ME, Montserrat-de la Paz S. High-density lipoproteins and immune response: A review. Int J Biol Macromol 2022; 195:117-123. [PMID: 34896462 DOI: 10.1016/j.ijbiomac.2021.12.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 01/04/2023]
Abstract
High-density lipoproteins (HDLs) are heterogeneous lipoproteins that modify their composition and functionality depending on physiological or pathological conditions. The main roles of HDL are cholesterol efflux, and anti-inflammatory and antioxidant functions. These functions can be compromised under pathological conditions. HDLs play a role in the immune system as anti-inflammatory molecules but when inflammation occurs, HDLs change their composition and carry pro-inflammatory cargo. Hence, many molecular intermediates that influence inflammatory microenvironments and cell signaling pathways can modulate HDLs structural modification and function. This review provides a comprehensive assessment of the importance of HDL composition and anti-inflammatory function in the onset and progression of atherosclerotic cardiovascular diseases. On the other hand, immune cell activation during progression of atheroma plaque formation can be influenced by HDLs through HDL-derived cholesterol depletion from lipid rafts and through HDL interaction with HDL receptors expressed on T and B lymphocytes. Cholesterol efflux is mediated by HDL receptors located in lipid rafts in peripheral cells, which undergo membrane structural modifications, and interferes with subsequent molecules interactions or intracellular signaling cascades. Regarding antigen-presentation cells such as macrophages or dendritic cells, HDL function may then modulate lymphocytes activation in immune response. Our review also contributes to the understanding of the effects exerted by HDLs in signal transduction associated to our immune cell population during chronic diseases progression.
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Affiliation(s)
- Elena Grao-Cruces
- Department of Medical Biochemistry, Molecular Biology, and Immunology, School of Medicine, University of Seville, Av. Sanchez Pizjuan s/n, 41009 Seville, Spain
| | - Soledad Lopez-Enriquez
- Department of Medical Biochemistry, Molecular Biology, and Immunology, School of Medicine, University of Seville, Av. Sanchez Pizjuan s/n, 41009 Seville, Spain
| | - Maria E Martin
- Department of Cell Biology, Faculty of Biology, University of Seville, Av. Reina Mercedes s/n, 41012 Seville, Spain
| | - Sergio Montserrat-de la Paz
- Department of Medical Biochemistry, Molecular Biology, and Immunology, School of Medicine, University of Seville, Av. Sanchez Pizjuan s/n, 41009 Seville, Spain.
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20
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Wei D, Marrachelli VG, Melgarejo JD, Liao CT, Janssens S, Verhamme P, Vanassche T, Van Aelst L, Monleon D, Redón J, Zhang ZY. Lipoprotein profiles of fat distribution and its association with insulin sensitivity. Front Endocrinol (Lausanne) 2022; 13:978745. [PMID: 36387872 PMCID: PMC9640977 DOI: 10.3389/fendo.2022.978745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 10/10/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Fat deposition is associated with adverse outcomes. Waist-to-hip (WHR) ratio is a simple feasible index to assess fat distribution. Lipoprotein particle composition in relation to WHR and to what extent their association is mediated by insulin sensitivity are less investigated. METHODS In 504 randomly recruited Flemish (mean age: 48.9 years; women: 51.6%), we analyzed the lipoprotein particle constitutions using nuclear magnetic resonance spectroscopy. WHR obesity described a WHR of ≥ 0.85 for women or 0.9 for men. Insulin sensitivity was evaluated by the homeostasis model assessment-estimated insulin resistance (HOMA-IR). SCORE-2 risk algorithm was applied to estimate 10-year cardiovascular risk. Statistical methods included multivariable-adjusted linear regression analysis, logistic regression analysis, and mediation analysis. RESULTS The prevalence of WHR obesity was 54.6%, approximately 3 times of BMI-determined obesity (19.1%). Individuals with WHR obesity had significantly higher metabolic complications, such as hypertension (57.1%), dyslipidemia (61.8%), and insulin resistance (14.2%). WHR and WHR obesity were positively associated with total very-low-density lipoprotein (VLDL) particle concentration, remnant cholesterol, and triglycerides, but were negatively associated with VLDL particle size (P ≤ 0.027), independent of body mass index and other covariates. WHR was inversely associated with total high-density lipoprotein (HDL) particle concentration, whereas WHR obesity was inversely associated with HDL cholesterol (P ≤ 0.039). Neither WHR nor WHR obesity was associated with the concentration of total low-density lipoprotein (LDL) particles, LDL particle size, and LDL cholesterol (P ≥ 0.089). In the mediation analysis, insulin sensitivity significantly mediated the effect of WHR on total VLDL particle concentration (mediation percentage: 37.0%), remnant cholesterol (47.7%), and HDL cholesterol (41.1%). Individuals with WHR obesity were at increased cardiovascular risk, regardless of LDL cholesterol (P ≤0.028). In WHR obesity, higher total VLDL particle concent36ration and remnant cholesterol, and lower HDL cholesterol were associated with an increased cardiovascular risk (P≤ 0.002). CONCLUSIONS Upper-body fat deposition was independently associated with an unfavorable lipoprotein profile, and insulin sensitivity significantly mediated this association. LDL cholesterol might underestimate lipid abnormality for people with upper-body obesity and lowering VLDL particles and remnant cholesterol might potentially reduce the residual cardiovascular risk.
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Affiliation(s)
- Dongmei Wei
- Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Vannina González Marrachelli
- Department of Physiology, Faculty of Medicine, University of Valencia, Valencia, Spain
- INCLIVA Research Institute, University of Valencia, Valencia, Spain
| | - Jesus D. Melgarejo
- Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Chia-Te Liao
- Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Stefan Janssens
- Division of Cardiology, University Hospitals Leuven, Leuven, Belgium
| | - Peter Verhamme
- Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Thomas Vanassche
- Division of Cardiology, University Hospitals Leuven, Leuven, Belgium
| | - Lucas Van Aelst
- Division of Cardiology, University Hospitals Leuven, Leuven, Belgium
| | - Daniel Monleon
- INCLIVA Research Institute, University of Valencia, Valencia, Spain
- Department of Pathology, University of Valencia, Valencia, Spain
| | - Josep Redón
- INCLIVA Research Institute, University of Valencia, Valencia, Spain
| | - Zhen-Yu Zhang
- Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
- *Correspondence: Zhen-Yu Zhang,
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21
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El Khoudary SR, Nasr A, Billheimer J, Brooks MM, McConnell D, Crawford S, Orchard TJ, Rader DJ, Matthews KA. Associations of Endogenous Hormones With HDL Novel Metrics Across the Menopause Transition: The SWAN HDL Study. J Clin Endocrinol Metab 2022; 107:e303-e314. [PMID: 34390340 PMCID: PMC8684446 DOI: 10.1210/clinem/dgab595] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Indexed: 01/28/2023]
Abstract
CONTEXT Novel metrics of high-density lipoprotein (HDL) (subclasses, lipid content, and function) may improve characterization of the anti-atherogenic features of HDL. In midlife women, changes in these metrics vary by time relative to the final menstrual period (FMP), supporting a contribution of estradiol (E2) and follicle-stimulating hormone (FSH). OBJECTIVE We tested associations of endogenous E2 and FSH with novel HDL metrics and assessed whether these associations varied by time relative to FMP. METHODS This study was a longitudinal analysis from the Study of Women's Health Across the Nation (SWAN) HDL study, using a community-based cohort of 463 women, baseline mean age 50.2 (2.7) years. The main outcome measures were HDL cholesterol efflux capacity (HDL-CEC), HDL phospholipids (HDL-PL), HDL triglycerides (HDL-Tg), HDL particles (HDL-P), HDL size, and HDL cholesterol (HDL-C). RESULTS In multivariable analyses, E2 was positively associated with HDL size, large HDL-P, HDL-CEC, and HDL-Tg, but negatively with medium HDL-P (P values < 0.05). The positive association between E2 and HDL-Tg was stronger 2 years post-FMP than before, (interaction P = 0.031). FSH was positively related to total and medium HDL-P, but negatively to HDL size, large HDL-P, and HDL-CEC per particle (P values < 0.05). Associations of higher FSH with greater total HDL-P and smaller HDL size were only evident at/after menopause (interaction P values < 0.05). CONCLUSION Some of the associations linking E2 and FSH with novel HDL metrics were vulnerable to time relative to menopause onset. Whether a late initiation of hormone therapy relative to menopause could have a detrimental effect on lipid content of HDL particles should be tested in the future.
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Affiliation(s)
- Samar R El Khoudary
- Department of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA 15261, USA
- Correspondence: Samar R. El Khoudary, PhD, MPH, FAHA, Associate Professor of Epidemiology, Clinical and Translational Science Institute, Epidemiology Data Center, 4420 Bayard Street, Suite 600, Pittsburgh, PA, 15260, USA.
| | - Alexis Nasr
- Department of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA 15261, USA
| | - Jeffrey Billheimer
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Maria M Brooks
- Department of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA 15261, USA
| | - Dan McConnell
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sybil Crawford
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Trevor J Orchard
- Department of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA 15261, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Karen A Matthews
- Department of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA 15261, USA
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
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22
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Afrin H, Salazar CJ, Kazi M, Ahamad SR, Alharbi M, Nurunnabi M. Methods of screening, monitoring and management of cardiac toxicity induced by chemotherapeutics. CHINESE CHEM LETT 2022. [DOI: 10.1016/j.cclet.2022.01.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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23
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Wilkens TL, Tranæs K, Eriksen JN, Dragsted LO. Moderate alcohol consumption and lipoprotein subfractions: a systematic review of intervention and observational studies. Nutr Rev 2021; 80:1311-1339. [PMID: 34957513 DOI: 10.1093/nutrit/nuab102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
CONTEXT Moderate alcohol consumption is associated with decreased risk of cardiovascular disease (CVD) and improvement in cardiovascular risk markers, including lipoproteins and lipoprotein subfractions. OBJECTIVE To systematically review the relationship between moderate alcohol intake, lipoprotein subfractions, and related mechanisms. DATA SOURCES Following PRISMA, all human and ex vivo studies with an alcohol intake up to 60 g/d were included from 8 databases. DATA EXTRACTION A total of 17 478 studies were screened, and data were extracted from 37 intervention and 77 observational studies. RESULTS Alcohol intake was positively associated with all HDL subfractions. A few studies found lower levels of small LDLs, increased average LDL particle size, and nonlinear relationships to apolipoprotein B-containing lipoproteins. Cholesterol efflux capacity and paraoxonase activity were consistently increased. Several studies had unclear or high risk of bias, and heterogeneous laboratory methods restricted comparability between studies. CONCLUSIONS Up to 60 g/d alcohol can cause changes in lipoprotein subfractions and related mechanisms that could influence cardiovascular health. SYSTEMATIC REVIEW REGISTRATION PROSPERO registration no. 98955.
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Affiliation(s)
- Trine L Wilkens
- Department of Nutrition, Exercise and Sports, Section for Preventive and Clinical Nutrition, University of Copenhagen, Denmark
| | - Kaare Tranæs
- Department of Nutrition, Exercise and Sports, Section for Preventive and Clinical Nutrition, University of Copenhagen, Denmark
| | - Jane N Eriksen
- Department of Nutrition, Exercise and Sports, Section for Preventive and Clinical Nutrition, University of Copenhagen, Denmark
| | - Lars O Dragsted
- Department of Nutrition, Exercise and Sports, Section for Preventive and Clinical Nutrition, University of Copenhagen, Denmark
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24
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Wieczorek E, Ćwiklińska A, Kuchta A, Kortas-Stempak B, Gliwińska A, Jankowski M. The Differential Effects of HDL Subpopulations on Lipoprotein Lipase (LPL)-Mediated VLDL Catabolism. Biomedicines 2021; 9:1839. [PMID: 34944655 DOI: 10.3390/biomedicines9121839] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 11/25/2021] [Accepted: 12/02/2021] [Indexed: 12/19/2022] Open
Abstract
High-density lipoprotein (HDL) subpopulations functional assessment is more relevant for HDL anti-atherogenic activity than cholesterol level. The aim of the study was to assess the impact of HDL-2 and HDL-3 on lipoprotein lipase (LPL)-mediated very-low-density lipoprotein (VLDL) catabolism related to hypertriglyceridemia development. VLDL and HDLs were isolated from serum by ultracentrifugation. VLDL was incubated with LPL in the absence and presence of total HDL or HDL subpopulations. Next, VLDL remnants were separated, and their composition and electrophoretic mobility was assessed. Both HDL subpopulations increased the efficiency of triglyceride lipolysis and apolipoprotein CII and CIII removal from VLDL up to ~90%. HDL-3 exerted significantly greater impact than HDL-2 on apolipoprotein E (43% vs. 18%, p < 0.001), free cholesterol (26% vs. 18%, p < 0.05) and phospholipids (53% vs. 43%, p < 0.05) removal from VLDL and VLDL remnant electrophoretic mobility (0.18 vs. 0.20, p < 0.01). A greater release of these components was also observed in the presence of total HDL with a low HDL-2/HDL-3 cholesterol ratio. Both HDL subpopulations affect VLDL composition during lipolysis, but HDL-3 exhibited a greater effect on this process. Altered composition of HDL related to significant changes in the distribution between HDL-2 and HDL-3 can influence the VLDL remnant features, affecting atherosclerosis progression.
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25
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Wilson PWF, Jacobson TA, Martin SS, Jackson EJ, Le NA, Davidson MH, Vesper HW, Frikke-Schmidt R, Ballantyne CM, Remaley AT. Lipid measurements in the management of cardiovascular diseases: Practical recommendations a scientific statement from the national lipid association writing group. J Clin Lipidol 2021; 15:629-648. [PMID: 34802986 DOI: 10.1016/j.jacl.2021.09.046] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 01/31/2023]
Abstract
Lipoprotein measurements are pivotal in the management of patients at risk for atherosclerotic coronary heart disease (CHD) with myocardial infarction and coronary death as the main outcomes, and for atherosclerotic cardiovascular disease (ASCVD), which includes CHD and stroke. Recent developments and changes in guidelines affect optimization of using lipid measures as cardiovascular biomarkers. This scientific statement reviews the pre-analytical, analytical, post-analytical, and clinical aspects of lipoprotein measurements. Highlights include the following: i) It is acceptable to screen with nonfasting lipids. ii) non-high-density lipoprotein HDL-cholesterol (non-HDL-C) is measured reliably in either the fasting or the nonfasting state and can effectively guide ASCVD prevention. iii) low density lipoprotein cholesterol (LDL-C) can be estimated from total cholesterol, high density lipoprotein cholesterol (HDL-C), and triglyceride (TG) measurements. For patients with LDL-C>100 mg/dL and TG ≤150 mg/dL it is reasonable to use the Friedewald formula. However, for those with TG 150-400 mg/dL the Friedewald formula for LDL-C estimation is less accurate. The Martin/Hopkins method is recommended for LDL-C estimation throughout the range of LDL-C levels and up to TG levels of 399 mg/dL. For TG levels ≥400 mg/dL LDL-C estimating equations are currently not recommended and newer methods are being evaluated. iv) When LDL-C or TG screening results are abnormal the clinician should consider obtaining fasting lipids. v) Advanced lipoprotein tests using apolipoprotein B (apoB), LDL Particle Number (LDL-P) or remnant cholesterol may help to guide therapeutic decisions in select patients, but data are limited for patients already on lipid lowering therapy with low LDL-C levels. Better harmonization of advanced lipid measurement methods is needed. Lipid measurements are recommended 4-12 weeks after a change in lipid treatment. Lipid laboratory reports should denote desirable values and specifically identify extremely elevated LDL-C levels (≥190 mg/dL at any age or ≥160 mg/dL in children) as severe hypercholesterolemia. Potentially actionable abnormal lipid test results, including fasting triglycerides (TG) ≥500 mg/dL, should be reported as hypertriglyceridemia. Appropriate use and reporting of lipid tests should improve their utility in the management of persons at high risk for ASCVD events.
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Affiliation(s)
- Peter W F Wilson
- Emory University School of Medicine, Atlanta, GA, United States; Atlanta Veterans Affairs Medical Center, Atlanta, GA, United States.
| | | | - Seth S Martin
- Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | | | - N-Anh Le
- Atlanta Veterans Affairs Medical Center, Atlanta, GA, United States
| | | | - Hubert W Vesper
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Ruth Frikke-Schmidt
- Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | | | - Alan T Remaley
- National Heart, Lung and Blood Institute, Bethesda, MD, United States
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26
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Jin Q, Ma RCW. Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies. Cells 2021; 10:cells10112832. [PMID: 34831057 PMCID: PMC8616415 DOI: 10.3390/cells10112832] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 10/11/2021] [Accepted: 10/13/2021] [Indexed: 12/18/2022] Open
Abstract
The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.
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Affiliation(s)
- Qiao Jin
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China;
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China;
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Correspondence: ; Fax: +852-26373852
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27
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Abstract
Low plasma levels of High Density Lipoprotein (HDL) cholesterol (HDL-C) are associated with increased risks of atherosclerotic cardiovascular disease (ASCVD). In cell culture and animal models, HDL particles exert multiple potentially anti-atherogenic effects. However, drugs increasing HDL-C have failed to prevent cardiovascular endpoints. Mendelian Randomization studies neither found any genetic causality for the associations of HDL-C levels with differences in cardiovascular risk. Therefore, the causal role and, hence, utility as a therapeutic target of HDL has been questioned. However, the biomarker "HDL-C" as well as the interpretation of previous data has several important limitations: First, the inverse relationship of HDL-C with risk of ASCVD is neither linear nor continuous. Hence, neither the-higher-the-better strategies of previous drug developments nor previous linear cause-effect relationships assuming Mendelian randomization approaches appear appropriate. Second, most of the drugs previously tested do not target HDL metabolism specifically so that the futile trials question the clinical utility of the investigated drugs rather than the causal role of HDL in ASCVD. Third, the cholesterol of HDL measured as HDL-C neither exerts nor reports any HDL function. Comprehensive knowledge of structure-function-disease relationships of HDL particles and associated molecules will be a pre-requisite, to test them for their physiological and pathogenic relevance and exploit them for the diagnostic and therapeutic management of individuals at HDL-associated risk of ASCVD but also other diseases, for example diabetes, chronic kidney disease, infections, autoimmune and neurodegenerative diseases.
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Affiliation(s)
- Arnold von Eckardstein
- Institute of Clinical Chemistry, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
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28
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Ma S, Xia M, Gao X. Biomarker Discovery in Atherosclerotic Diseases Using Quantitative Nuclear Magnetic Resonance Metabolomics. Front Cardiovasc Med 2021; 8:681444. [PMID: 34395555 PMCID: PMC8356911 DOI: 10.3389/fcvm.2021.681444] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 07/02/2021] [Indexed: 12/23/2022] Open
Abstract
Despite great progress in the management of atherosclerosis (AS), its subsequent cardiovascular disease (CVD) remains the leading cause of morbidity and mortality. This is probably due to insufficient risk detection using routine lipid testing; thus, there is a need for more effective approaches relying on new biomarkers. Quantitative nuclear magnetic resonance (qNMR) metabolomics is able to phenotype holistic metabolic changes, with a unique advantage in regard to quantifying lipid-protein complexes. The rapidly increasing literature has indicated that qNMR-based lipoprotein particle number, particle size, lipid components, and some molecular metabolites can provide deeper insight into atherogenic diseases and could serve as novel promising determinants. Therefore, this article aims to offer an updated review of the qNMR biomarkers of AS and CVD found in epidemiological studies, with a special emphasis on lipoprotein-related parameters. As more researches are performed, we can envision more qNMR metabolite biomarkers being successfully translated into daily clinical practice to enhance the prevention, detection and intervention of atherosclerotic diseases.
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Affiliation(s)
- Shuai Ma
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.,Fudan Institute for Metabolic Diseases, Shanghai, China
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29
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Abstract
Diabetes mellitus (DM) is an escalating pandemic and an established cardiovascular risk factor. An important aspect of the interaction between DM and atherosclerotic cardiovascular disease (ASCVD) is diabetic dyslipidaemia, an atherogenic dyslipidaemia encompassing quantitative [hypertriglyceridaemia (hyperTG) and decreased high density lipoprotein cholesterol (HDL)] and qualitative [increased small dense low density lipoprotein cholesterol (sdLDL) particles, large very low density lipoprotein cholesterol (VLDL) subfraction (VLDL1) and dysfunctional HDL] modifications in lipoproteins. Much of the pathophysiology linking DM and dyslipidaemia has been elucidated. This paper aims to review the pathophysiology and management of diabetic dyslipidaemia with respect to ASCVD. Briefly, the influence of diabetic kidney disease on lipid profile and lipid changes causing type 2 diabetes mellitus are highlighted. Biomarkers of diabetic dyslipidaemia, including novel markers and clinical trials that have demonstrated that non-lipid and lipid lowering therapies can lower cardiovascular risk in diabetics are discussed. The stands of various international guidelines on lipid management in DM are emphasised. It is important to understand the underlying mechanisms of diabetic dyslipidaemia in order to develop new therapeutic strategies against dyslipidaemia and diabetes. The various international guidelines on lipid management can be used to tailor a holistic approach specific to each patient with diabetic dyslipidaemia.
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Affiliation(s)
- Subashini C Thambiah
- Department of Pathology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
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30
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Rajalahti T, Aadland E, Resaland GK, Anderssen SA, Kvalheim OM. Cardiometabolic Associations between Physical Activity, Adiposity, and Lipoprotein Subclasses in Prepubertal Norwegian Children. Nutrients 2021; 13:2095. [PMID: 34205279 DOI: 10.3390/nu13062095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/11/2021] [Accepted: 06/16/2021] [Indexed: 11/17/2022] Open
Abstract
Lipoprotein subclasses possess crucial cardiometabolic information. Due to strong multicollinearity among variables, little is known about the strength of influence of physical activity (PA) and adiposity upon this cardiometabolic pattern. Using a novel approach to adjust for covariates, we aimed at determining the "net" patterns and strength for PA and adiposity to the lipoprotein profile. Principal component and multivariate pattern analysis were used for the analysis of 841 prepubertal children characterized by 26 lipoprotein features determined by proton nuclear magnetic resonance spectroscopy, a high-resolution PA descriptor derived from accelerometry, and three adiposity measures: body mass index, waist circumference to height, and skinfold thickness. Our approach focuses on revealing and validating the underlying predictive association patterns in the metabolic, anthropologic, and PA data to acknowledge the inherent multicollinear nature of such data. PA associates to a favorable cardiometabolic pattern of increased high-density lipoproteins (HDL), very large and large HDL particles, and large size of HDL particles, and decreasedtriglyceride, chylomicrons, very low-density lipoproteins (VLDL), and their subclasses, and to low size of VLDL particles. Although weakened in strength, this pattern resists adjustment for adiposity. Adiposity is inversely associated to this pattern and exhibits unfavorable associations to low-density lipoprotein (LDL) features, including atherogenic small and very small LDL particles. The observed associations are still strong after adjustment for PA. Thus, lipoproteins explain 26.0% in adiposity after adjustment for PA compared to 2.3% in PA after adjustment for adiposity.
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Sampson M, Wolska A, Warnick R, Lucero D, Remaley AT. A New Equation Based on the Standard Lipid Panel for Calculating Small Dense Low-Density Lipoprotein-Cholesterol and Its Use as a Risk-Enhancer Test. Clin Chem 2021; 67:987-997. [PMID: 33876239 DOI: 10.1093/clinchem/hvab048] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 03/04/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Increased small dense low-density lipoprotein-cholesterol (sdLDL-C) is a risk factor for atherosclerotic cardiovascular disease (ASCVD) but typically requires advanced lipid testing. We describe two new equations, first one for calculating large buoyant LDL-C (lbLDL-C), based only upon results from the standard lipid panel, and the second one for sdLDL-C. METHODS Equations for sdLDL-C and lbLDL-C were generated with least-squares regression analysis using the direct Denka sdLDL-C assay as reference (n = 20 171). sdLDL-C was assessed as a risk-enhancer test in the National Heart and Nutrition Examination Survey (NHANES), and for its association with ASCVD in the Multi-Ethnic Study of Atherosclerosis (MESA). RESULTS The newly derived equations depend on two terms, namely LDL-C as determined by the Sampson equation, and an interaction term between LDL-C and the natural log of triglycerides (TG). The lbLDL-C equation (lbLDLC=1.43 × LDLC-0.14 ×(ln(TG)× LDLC)- 8.99) was more accurate (R2 = 0.933, slope = 0.94) than the sdLDL-C equation (sdLDLC=LDLC- lbLDLC; R2 = 0.745, slope = 0.73). Using the 80th percentile (46 mg/dL) as a cut-point, sdLDL-C identified in NHANES additional high-risk patients not identified by other risk-enhancer tests based on TG, LDL-C, apolipoprotein B, and nonHDL-C. By univariate survival-curve analysis, estimated sdLDL-C was superior to other risk-enhancer tests in predicting ASCVD events in MESA. After multivariate adjustment for other known ASCVD risk factors, estimated sdLDL-C had the strongest association with ASCVD compared to other lipid parameters, including measured sdLDL-C. CONCLUSIONS Estimated sdLDL-C could potentially be calculated on all patients tested with a standard lipid panel to improve ASCVD risk stratification.
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Affiliation(s)
- Maureen Sampson
- Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Anna Wolska
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Diego Lucero
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alan T Remaley
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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Shaya GE, Leucker TM, Jones SR, Martin SS, Toth PP. Coronary heart disease risk: Low-density lipoprotein and beyond. Trends Cardiovasc Med 2021; 32:181-194. [PMID: 33872757 DOI: 10.1016/j.tcm.2021.04.002] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 03/30/2021] [Accepted: 04/05/2021] [Indexed: 01/06/2023]
Abstract
Coronary heart disease (CHD) is the leading cause of morbidity and mortality world-wide and has been characterized as a chronic immunoinflammatory, fibroproliferative disease fueled by lipids. Great advances have been made in elucidating the complex mechanistic interactions among risk factors associated with CHD, yielding abundant success towards preventive measures and the development of pharmaceuticals to prevent and treat CHD via attenuation of lipoprotein-mediated risk. However, significant residual risk remains. Several potentially modifiable CHD risk factors ostensibly contributing to this residual risk have since come to the fore, including systemic inflammation, diabetes mellitus, high-density lipoprotein, plasma triglycerides (TG) and remnant lipoproteins (RLP), lipoprotein(a) (Lp[a]), and vascular endothelial dysfunction (ED). Herein, we summarize the body of evidence implicating each of these risk factors in residual CHD risk.
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Affiliation(s)
- Gabriel E Shaya
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Thorsten M Leucker
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Steven R Jones
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Seth S Martin
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Peter P Toth
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA; Community Hospital General Medical Center, Sterling, IL, USA.
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Hoyt L, O'Day EM. Perspective: A potential role for NUS in metabolite-based in vitro diagnostics. Magn Reson Chem 2021; 59:257-263. [PMID: 32997360 DOI: 10.1002/mrc.5104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 09/17/2020] [Accepted: 09/25/2020] [Indexed: 06/11/2023]
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Ahmed MO, Byrne RE, Pazderska A, Segurado R, Guo W, Gunness A, Frizelle I, Sherlock M, Ahmed KS, McGowan A, Moore K, Boran G, McGillicuddy FC, Gibney J. HDL particle size is increased and HDL-cholesterol efflux is enhanced in type 1 diabetes: a cross-sectional study. Diabetologia 2021; 64:656-667. [PMID: 33169205 DOI: 10.1007/s00125-020-05320-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 09/09/2020] [Indexed: 01/02/2023]
Abstract
AIMS/HYPOTHESIS The prevalence of atherosclerosis is increased in type 1 diabetes despite normal-to-high HDL-cholesterol levels. The cholesterol efflux capacity (CEC) of HDL is a better predictor of cardiovascular events than static HDL-cholesterol. This cross-sectional study addressed the hypothesis that impaired HDL function contributes to enhanced CVD risk within type 1 diabetes. METHODS We compared HDL particle size and concentration (by NMR), total CEC, ATP-binding cassette subfamily A, member 1 (ABCA1)-dependent CEC and ABCA1-independent CEC (by determining [3H]cholesterol efflux from J774-macrophages to ApoB-depleted serum), and carotid intima-media thickness (CIMT) in 100 individuals with type 1 diabetes (37.6 ± 1.2 years; BMI 26.9 ± 0.5 kg/m2) and 100 non-diabetic participants (37.7 ± 1.1 years; 27.1 ± 0.5 kg/m2). RESULTS Compared with non-diabetic participants, total HDL particle concentration was lower (mean ± SD 31.01 ± 8.66 vs 34.33 ± 8.04 μmol/l [mean difference (MD) -3.32 μmol/l]) in participants with type 1 diabetes. However, large HDL particle concentration was greater (9.36 ± 3.98 vs 6.99 ± 4.05 μmol/l [MD +2.37 μmol/l]), resulting in increased mean HDL particle size (9.82 ± 0.57 vs 9.44 ± 0.56 nm [MD +0.38 nm]) (p < 0.05 for all). Total CEC (14.57 ± 2.47%CEC/4 h vs 12.26 ± 3.81%CEC/4 h [MD +2.31%CEC/4 h]) was greater in participants with type 1 diabetes relative to non-diabetic participants. Increased HDL particle size was independently associated with increased total CEC; however, following adjustment for this in multivariable analysis, CEC remained greater in participants with type 1 diabetes. Both components of CEC, ABCA1-dependent (6.10 ± 2.41%CEC/4 h vs 5.22 ± 2.57%CEC/4 h [MD +0.88%CEC/4 h]) and ABCA1-independent (8.47 ± 1.79% CEC/4 h vs 7.05 ± 1.76% CEC/4 h [MD +1.42% CEC/4 h]) CEC, were greater in type 1 diabetes but the increase in ABCA1-dependent CEC was less marked and not statistically significant in multivariable analysis. CIMT was increased in participants with type 1 diabetes but in multivariable analysis it was only associated negatively with age and BMI. CONCLUSIONS/INTERPRETATION HDL particle size but not HDL-cholesterol level is independently associated with enhanced total CEC. HDL particle size is greater in individuals with type 1 diabetes but even after adjusting for this, total and ABCA1-independent CEC are enhanced in type 1 diabetes. Further studies are needed to understand the mechanisms underlying these effects, and whether they help attenuate progression of atherosclerosis in this high-risk group. Graphical abstract.
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Affiliation(s)
- Mohamad O Ahmed
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Rachel E Byrne
- Diabetes Complications Research Centre, School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Agnieszka Pazderska
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Ricardo Segurado
- School of Public Health, Physiotherapy, and Sports Science, University College Dublin, Belfield, Dublin, Ireland
| | - Weili Guo
- Diabetes Complications Research Centre, School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Anjuli Gunness
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Isolda Frizelle
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Mark Sherlock
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Khalid S Ahmed
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Anne McGowan
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Kevin Moore
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland
| | - Gerard Boran
- Department of Chemical Pathology, Tallaght University Hospital, Dublin, Ireland
| | - Fiona C McGillicuddy
- Diabetes Complications Research Centre, School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - James Gibney
- Robert Graves Institute of Endocrinology, Tallaght University Hospital, Dublin, Ireland.
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Teis A, Cediel G, Amigó N, Julve J, Aranyó J, Andrés-Cordón J, Puig-Jové C, Castelblanco E, Gual-Capllonch F, Ferrer-Sistach E, Vallejo N, Juncà G, López-Ayerbe J, De Antonio M, Domingo M, Santiago-Vacas E, Codina P, Mauricio D, Lupón J, Alonso N, Bayes-Genis A. Particle size and cholesterol content of circulating HDL correlate with cardiovascular death in chronic heart failure. Sci Rep 2021; 11:3141. [PMID: 33542459 PMCID: PMC7862293 DOI: 10.1038/s41598-021-82861-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 01/25/2021] [Indexed: 12/15/2022] Open
Abstract
Evidence regarding any association of HDL-particle (HDL-P) derangements and HDL-cholesterol content with cardiovascular (CV) death in chronic heart failure (HF) is lacking. To investigate the prognostic value of HDL-P size (HDL-Sz) and the number of cholesterol molecules per HDL-P for CV death in HF patients. Outpatient chronic HF patients were enrolled. Baseline HDL-P number, subfractions and HDL-Sz were measured using 1H-NMR spectroscopy. The HDL-C/P ratio was calculated as HDL-cholesterol over HDL-P. Endpoint was CV death, with non-CV death as the competing event. 422 patients were included and followed-up during a median of 4.1 (0–8) years. CV death occurred in 120 (30.5%) patients. Mean HDL-Sz was higher in CV dead as compared with survivors (8.39 nm vs. 8.31 nm, p < 0.001). This change in size was due to a reduction in the percentage of small HDL-P (54.6% vs. 60% for CV-death vs. alive; p < 0.001). HDL-C/P ratio was higher in the CV-death group (51.0 vs. 48.3, p < 0.001). HDL-Sz and HDL-C/P ratio were significantly associated with CV death after multivariable regression analysis (HR 1.22 [95% CI 1.01–1.47], p = 0.041 and HR 1.04 [95% CI 1.01–1.07], p = 0.008 respectively). HDL-Sz and HDL-C/P ratio are independent predictors of CV death in chronic HF patients.
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Affiliation(s)
- Albert Teis
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain. .,Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain.
| | - G Cediel
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - N Amigó
- Biosfer Teslab, SL, Reus, Spain.,Metabolomics Platform, Rovira i Virgili University (URV), Instituto de Investigación Sanitaria Pere Virigili (IISPV), Tarragona, Spain.,Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Barcelona, Spain
| | - J Julve
- Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Barcelona, Spain.,Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau i Institut d'Investigació Biomèdica de l'Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain
| | - J Aranyó
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - J Andrés-Cordón
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - C Puig-Jové
- Endocrinology and Nutrition Department, Germans Trias University Hospital, Badalona, Barcelona, Spain
| | - E Castelblanco
- Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Barcelona, Spain.,Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau i Institut d'Investigació Biomèdica de l'Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - F Gual-Capllonch
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - E Ferrer-Sistach
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - N Vallejo
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - G Juncà
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - J López-Ayerbe
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain
| | - M De Antonio
- Heart Institute, Heart Failure Unit, Germans Trias University Hospital, Badalona, Barcelona, Spain
| | - M Domingo
- Heart Institute, Heart Failure Unit, Germans Trias University Hospital, Badalona, Barcelona, Spain
| | - E Santiago-Vacas
- Heart Institute, Heart Failure Unit, Germans Trias University Hospital, Badalona, Barcelona, Spain
| | - P Codina
- Heart Institute, Heart Failure Unit, Germans Trias University Hospital, Badalona, Barcelona, Spain
| | - D Mauricio
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain.,Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Barcelona, Spain.,Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau i Institut d'Investigació Biomèdica de l'Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain.,Endocrinology and Nutrition Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.,Lleida Biomedical Research Institute's Dr. Pifarré Foundation (IRBLleida), University of Lleida, Lleida, Spain
| | - J Lupón
- Heart Institute, Heart Failure Unit, Germans Trias University Hospital, Badalona, Barcelona, Spain
| | - Nuria Alonso
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain. .,Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Barcelona, Spain. .,Endocrinology and Nutrition Department, Heart Failure Unit, Hospital Universitari Germans Trias i Pujol, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain.
| | - A Bayes-Genis
- Heart Institute, Cardiology Department, Germans Trias University Hospital, Carretera de Canyet s/n, 08916, Badalona, Barcelona, Spain.,Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain.,Centre for Biomedical Research on cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Barcelona, Spain
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Gu C, Wang N, Ren P, Wu X, Pang B, Zhang S, Hou X, Xu D, Yuan Y, Liu G. Association between postprandial lipoprotein subclasses and Framingham cardiovascular disease risk stratification. Clin Biochem 2020; 89:51-57. [PMID: 33359967 DOI: 10.1016/j.clinbiochem.2020.12.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 12/18/2020] [Accepted: 12/20/2020] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To determine the ability of postprandial lipoprotein subclass concentrations to stratify patients with respect to their risk for cardiovascular disease (CVD). METHODS Using the Framingham cardiovascular disease risk score (FRS) algorithm, a total of 112 consecutive patients referred for community health screening were stratified into two groups: (a) low-risk (FRS < 10%) and (b) intermediate/high-risk (FRS ≥ 10%). Serum lipoprotein subclass concentrations were determined by Vertical Auto Profile (VAP-II). RESULTS Fasting and postprandial levels of LDL4, HDL2, VLDL1 + 2, VLDL3, and RLP, as well as fasting levels of ApoB and postprandial levels of LDL3 and IDL1, were significantly different in the intermediate/high risk FRS group vs. the low-risk group (P < 0.05). Correlations between Framingham CVD risk and LDL3, LDL4, IDL1, VLDL1 + 2, VLDL3, RLP, and ApoB were positive while negative for HDL2 in both the fasting and postprandial states. Intermediate/high risk for CVD was shown to be significantly associated with both fasting and postprandial levels of VLDL1 + 2 and RLP, as well as with postprandial LDL4 and VLDL3, as determined using forward conditional logistic regression analysis. Postprandial levels of VLDL1 + 2 were better at identifying patients in the intermediate/high-risk FRS group than fasting levels, although the differences were not significant due to overlapping reference intervals. In addition, the association between RLP and VLDL subclasses relative to Framingham CVD risk increased significantly in the postprandial state (ΔR2 = 0.023; ΔF = 7.178; ΔP = 0.025) but not in the fasting state. CONCLUSIONS The use of postprandial lipoprotein subclass concentrations is not inferior to the use of fasting levels in identifying intermediate/high-risk FRS individuals. In addition, changes in RLP and VLDL subclass concentrations in fasting vs. postprandial states may reveal lipid metabolic mechanisms associated with CVD.
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Affiliation(s)
- Chun Gu
- Department of Laboratory, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Na Wang
- Department of Laboratory, Southern District of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Peng Ren
- Department of Laboratory, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Xuemei Wu
- Department of Laboratory, Southern District of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Bo Pang
- Department of Laboratory, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Shuying Zhang
- Department of Laboratory, Southern District of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Xueyun Hou
- Department of Laboratory, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Dan Xu
- Department of Laboratory, Southern District of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China
| | - Yuliang Yuan
- Department of Laboratory, Southern District of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China.
| | - Guijian Liu
- Department of Laboratory, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, China.
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Ellison S, Abdulrahim JW, Kwee LC, Bihlmeyer NA, Pagidipati N, McGarrah R, Bain JR, Kraus WE, Shah SH. Novel plasma biomarkers improve discrimination of metabolic health independent of weight. Sci Rep 2020; 10:21365. [PMID: 33288813 PMCID: PMC7721699 DOI: 10.1038/s41598-020-78478-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 11/18/2020] [Indexed: 01/14/2023] Open
Abstract
We sought to determine if novel plasma biomarkers improve traditionally defined metabolic health (MH) in predicting risk of cardiovascular disease (CVD) events irrespective of weight. Poor MH was defined in CATHGEN biorepository participants (n > 9300), a follow-up cohort (> 5600 days) comprising participants undergoing evaluation for possible ischemic heart disease. Lipoprotein subparticles, lipoprotein-insulin resistance (LP-IR), and GlycA were measured using NMR spectroscopy (n = 8385), while acylcarnitines and amino acids were measured using flow-injection, tandem mass spectrometry (n = 3592). Multivariable Cox proportional hazards models determined association of poor MH and plasma biomarkers with time-to-all-cause mortality or incident myocardial infarction. Low-density lipoprotein particle size and high-density lipoprotein, small and medium particle size (HMSP), GlycA, LP-IR, short-chain dicarboxylacylcarnitines (SCDA), and branched-chain amino acid plasma biomarkers were independently associated with CVD events after adjustment for traditionally defined MH in the overall cohort (p = 3.3 × 10-4-3.6 × 10-123), as well as within most of the individual BMI categories (p = 8.1 × 10-3-1.4 × 10-49). LP-IR, GlycA, HMSP, and SCDA improved metrics of model fit analyses beyond that of traditionally defined MH. We found that LP-IR, GlycA, HMSP, and SCDA improve traditionally defined MH models in prediction of adverse CVD events irrespective of BMI.
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Affiliation(s)
- Stephen Ellison
- Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Jawan W Abdulrahim
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA
| | - Lydia Coulter Kwee
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA
| | - Nathan A Bihlmeyer
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA
| | - Neha Pagidipati
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Robert McGarrah
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - James R Bain
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA
| | - William E Kraus
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Svati H Shah
- Duke Molecular Physiology Institute, Duke University School of Medicine, 300 North Duke St, Durham, NC, 27701, USA.
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
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38
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Kostara CE, Ferrannini E, Bairaktari ET, Papathanasiou A, Elisaf M, Tsimihodimos V. Early Signs of Atherogenic Features in the HDL Lipidomes of Normolipidemic Patients Newly Diagnosed with Type 2 Diabetes. Int J Mol Sci 2020; 21:ijms21228835. [PMID: 33266469 PMCID: PMC7700318 DOI: 10.3390/ijms21228835] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 11/20/2020] [Accepted: 11/20/2020] [Indexed: 02/07/2023] Open
Abstract
Cardiovascular disease (CVD) is the major cause of death in patients with type-2 diabetes mellitus (T2DM), although the factors that accelerate atherosclerosis in these patients are poorly understood. The identification of the altered quantity and quality of lipoproteins, closely related to atherogenesis, is limited in routine to a pattern of high triglycerides and low HDL-cholesterol (HDL-C) and in research as dysfunctional HDLs. We used the emerging NMR-based lipidomic technology to investigate compositional features of the HDLs of healthy individuals with normal coronary arteries, drug-naïve; recently diagnosed T2DM patients with normal coronary arteries; and patients with recent acute coronary syndrome. Patients with T2DM and normal serum lipid profiles even at diagnosis presented significant lipid alterations in HDL, characterized by higher triglycerides, lysophosphatidylcholine and saturated fatty acids; and lower cholesterol, phosphatidylcholine, phosphatidylethanolamine, sphingomyelin, plasmalogens and polyunsaturated fatty acids, an atherogenic pattern that may be involved in the pathogenesis of atherosclerosis. These changes are qualitatively similar to those found, more profoundly, in normolipidemic patients with established Coronary Heart Disease (CHD). We also conclude that NMR-based lipidomics offer a novel holistic exploratory approach for identifying and quantifying lipid species in biological matrixes in physiological processes and disease states or in disease biomarker discovery.
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Affiliation(s)
- Christina E. Kostara
- Laboratory of Clinical Chemistry, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (C.E.K.); (E.T.B.)
| | | | - Eleni T. Bairaktari
- Laboratory of Clinical Chemistry, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (C.E.K.); (E.T.B.)
| | - Athanasios Papathanasiou
- Department of Internal Medicine, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (A.P.); (M.E.)
| | - Moses Elisaf
- Department of Internal Medicine, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (A.P.); (M.E.)
| | - Vasilis Tsimihodimos
- Department of Internal Medicine, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece; (A.P.); (M.E.)
- Correspondence: ; Tel.: +30-2651007362
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Liou L, Kaptoge S. Association of small, dense LDL-cholesterol concentration and lipoprotein particle characteristics with coronary heart disease: A systematic review and meta-analysis. PLoS One 2020; 15:e0241993. [PMID: 33166340 PMCID: PMC7652325 DOI: 10.1371/journal.pone.0241993] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 10/25/2020] [Indexed: 02/02/2023] Open
Abstract
OBJECTIVES The aim of this study was to systematically collate and appraise the available evidence regarding the associations between small, dense low-density lipoprotein (sdLDL) and incident coronary heart disease (CHD), focusing on cholesterol concentration (sdLDL-C) and sdLDL particle characteristics (presence, density, and size). BACKGROUND Coronary heart disease (CHD) is the leading cause of death worldwide. Small, dense low-density lipoprotein (sdLDL) has been hypothesized to induce atherosclerosis and subsequent coronary heart disease (CHD). However, the etiological relevance of lipoprotein particle size (sdLDL) versus cholesterol content (sdLDL-C) remains unclear. METHODS PubMed, MEDLINE, Web of Science, and EMBASE were systematically searched for studies published before February 2020. CHD associations were based on quartile comparisons in eight studies of sdLDL-C and were based on binary categorization in fourteen studies of sdLDL particle size. Reported hazards ratios (HR) and odds ratios (OR) with 95% confidence interval (CI) were standardized and pooled using a random-effects meta-analysis model. RESULTS Data were collated from 21 studies with a total of 30,628 subjects and 5,693 incident CHD events. The average age was 67 years, and 53% were men. Higher sdLDL and sdLDL-C levels were both significantly associated with higher risk of CHD. The pooled estimate for the high vs. low categorization of sdLDL was 1.36 (95% CI: 1.21, 1.52) and 1.07 (95% CI: 1.01, 1.12) for comparing the top quartiles versus the bottom of sdLDL-C. Several studies suggested a dose response relationship. CONCLUSIONS The findings show a positive association between sdLDL or sdLDL-C levels and CHD, which is supported by an increasing body of genetic evidence in favor of its causality as an etiological risk factor. Thus, the results support sdLDL and sdLDL-C as a risk marker, but further research is required to establish sdLDL or sdLDL-C as a potential therapeutic marker for incident CHD risk reduction.
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Affiliation(s)
- Lathan Liou
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Stephen Kaptoge
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Prats-Uribe A, Sayols-Baixeras S, Fernández-Sanlés A, Subirana I, Carreras-Torres R, Vilahur G, Civeira F, Marrugat J, Fitó M, Hernáez Á, Elosua R. High-density lipoprotein characteristics and coronary artery disease: a Mendelian randomization study. Metabolism 2020; 112:154351. [PMID: 32891675 DOI: 10.1016/j.metabol.2020.154351] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/25/2020] [Accepted: 08/31/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND To assess whether genetically determined quantitative and qualitative HDL characteristics were independently associated with coronary artery disease (CAD). METHODS We designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I levels, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al. study, n = 24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D, n = 184,305). We validated these results by defining our genetic variables in another database (METSIM, n = 8372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits and minimize potential pleiotropy, we used the Multi-trait-based Conditional & Joint analysis. RESULTS Genetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter (β = 0.27 [95%CI = 0.19; 0.35]), cholesterol levels in very large HDLs (β = 0.29 [95%CI = 0.17; 0.40]), and triglyceride content in very large HDLs (β = 0.14 [95%CI = 0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs (β = -0.076 [95%CI = -0.10; -0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. CONCLUSIONS Some qualitative HDL characteristics (related to size, particle distribution, and cholesterol and triglyceride content) are related to CAD risk while HDL cholesterol levels are not.
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Affiliation(s)
- Albert Prats-Uribe
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Preventive Medicine and Public Health Unit, Parc de Salut Mar-Universitat Pompeu Fabra-ISGLOBAL, Barcelona, Spain; Centre for Statistics in Medicine, Botnar Research Centre, NDORMS, University of Oxford, Oxford, United Kingdom.
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Alba Fernández-Sanlés
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
| | - Isaac Subirana
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
| | - Robert Carreras-Torres
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain.
| | - Gemma Vilahur
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Program-ICCC, Research Institute-Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain.
| | - Fernando Civeira
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Lipid Unit, Hospital Universitario Miguel Servet, IIS Aragon, Zaragoza, Spain.
| | - Jaume Marrugat
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Girona Heart Registre Research Group (REGICOR), IMIM, Barcelona, Spain.
| | - Montserrat Fitó
- Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Álvaro Hernáez
- Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Risk, Nutrition, and Aging Research Unit, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Blanquerna School of Life Sciences, Universitat Ramon Llull, Barcelona, Spain.
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Medicine Department, Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain.
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Ingueneau C, Hollstein T, Grenkowitz T, Ruidavets JB, Kassner U, Duparc T, Combes G, Perret B, Genoux A, Schumann F, Bobbert T, Steinhagen-Thiessen E, Martinez LO. Treatment with PCSK9 inhibitors induces a more anti-atherogenic HDL lipid profile in patients at high cardiovascular risk. Vascul Pharmacol 2020; 135:106804. [PMID: 32987194 DOI: 10.1016/j.vph.2020.106804] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 09/16/2020] [Accepted: 09/23/2020] [Indexed: 01/30/2023]
Abstract
BACKGROUND Proprotein Convertase Subtilisin/Kexin type 9 inhibitors (PCSK9-I) have been reported to cause a moderate increase in high-density lipoprotein (HDL) cholesterol in human studies. We thus evaluated the effect of two approved PCSK9-I on the concentration and lipid composition of HDL particle subclasses. SUBJECTS AND METHODS 95 patients (62.8 ± 10.3 years old, 58% men), with or without statin and/or ezetimibe treatment and eligible for PCSK9-I therapy, received either evolocumab (140 mg) or alirocumab (75 or 150 mg). Their HDL particle profiles were measured by NMR spectroscopy at baseline and after 4 weeks of PCSK9-I treatment. RESULTS PCSK9-I treatment increased the level of HDL-C by 7%. The level of medium-sized HDL particles (M-HDL-P) increased (+8%) while the level of XL-HDL-P decreased (-19%). The lipid core composition was altered in the smaller S- and M-HDL-P, with a reduction in triglycerides (TG) and an enrichment in cholesterol esters (CE), whereas the for the larger XL- and L-HDL-P the relative CE content decreased and the TG content increased. Ezetimibe therapy differentially impacted the HDL particle distribution, independently of statin use, with an increase in S-HDL-P in patients not receiving ezetimibe. CONCLUSIONS As S- and M-HDL-P levels are inversely related to cardiovascular risk, PCSK9-I treatment may result in a more atheroprotective HDL particle profile, particularly in patients not concomitantly treated with ezetimibe.
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Ajala ON, Demler OV, Liu Y, Farukhi Z, Adelman SJ, Collins HL, Ridker PM, Rader DJ, Glynn RJ, Mora S. Anti-Inflammatory HDL Function, Incident Cardiovascular Events, and Mortality: A Secondary Analysis of the JUPITER Randomized Clinical Trial. J Am Heart Assoc 2020; 9:e016507. [PMID: 32799709 PMCID: PMC7660788 DOI: 10.1161/jaha.119.016507] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background High‐density lipoprotein (HDL) cholesterol has inverse association with cardiovascular disease. HDL possesses anti‐inflammatory properties in vitro, but it is unknown whether this may be protective in individuals with inflammation. Methods and Results The functional capacity of HDL to inhibit oxidation of oxidized low‐density lipoprotein (ie, the HDL inflammatory index; HII) was measured at baseline and 12 months after random allocation to rosuvastatin or placebo in a nested case‐control study of the JUPITER (Justification for the Use of Statins in Prevention: An Intervention Evaluating Rosuvastatin) trial. There were 517 incident cases of cardiovascular disease and all‐cause mortality compared to 517 age‐ and sex‐matched controls. Multivariable conditional logistic regression was used to examine associations of HII with events. Median baseline HII was 0.54 (interquartile range, 0.50–0.59). Twelve months of rosuvastatin decreased HII by a mean of 5.3% (95% CI, −8.9% to −1.7%; P=0.005) versus 1.3% (95% CI, −6.5% to 4.0%; P=0.63) with placebo (P=0.22 for between‐group difference). HII had a nonlinear relationship with incident events. Compared with the reference group (HII 0.5–1.0) with the lowest event rates, participants with baseline HII ≤0.5 had significantly increased risk of cardiovascular disease/mortality (adjusted hazard ratio, 1.53; 95% CI, 1.06–2.21; P=0.02). Furthermore, there was significant (P=0.002) interaction for HDL particle number with HII, such that having more HDL particles was associated with decreased risk only when HDL was anti‐inflammatory. Conclusions In JUPITER participants recruited on the basis of chronic inflammation, HII was associated with incident cardiovascular disease/mortality, with an optimal anti‐inflammatory HII range between 0.5 and 1.0. This nonlinear relationship of anti‐inflammatory HDL function with risk may account in part for the HDL paradox. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT00239681.
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Affiliation(s)
- Oluremi N Ajala
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA.,Harvard Medical School Boston MA
| | - Olga V Demler
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA.,Harvard Medical School Boston MA
| | - Yanyan Liu
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA
| | - Zareen Farukhi
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA.,Harvard Medical School Boston MA
| | | | | | - Paul M Ridker
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA.,Harvard Medical School Boston MA.,Division of Cardiovascular Medicine Brigham and Women's Hospital Boston MA
| | - Daniel J Rader
- Department of Genetics University of Pennsylvania Philadelphia PA
| | - Robert J Glynn
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA.,Harvard Medical School Boston MA
| | - Samia Mora
- Center for Lipid Metabolomics and Division of Preventive Medicine Brigham and Women's Hospital Boston MA.,Harvard Medical School Boston MA.,Division of Cardiovascular Medicine Brigham and Women's Hospital Boston MA
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Pappa E, Elisaf MS, Kostara C, Bairaktari E, Tsimihodimos VK. Cardioprotective Properties of HDL: Structural and Functional Considerations. Curr Med Chem 2020; 27:2964-2978. [PMID: 30714519 DOI: 10.2174/0929867326666190201142321] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 12/03/2018] [Accepted: 12/11/2018] [Indexed: 11/22/2022]
Abstract
BACKGROUND As Mendelian Randomization (MR) studies showed no effect of variants altering HDL-cholesterol (HDL-C) levels concerning Cardiovascular Disease (CVD) and novel therapeutic interventions aiming to raise HDL-C resulted to futility, the usefulness of HDL-C is unclear. OBJECTIVE As the role of HDL-C is currently doubtful, it is suggested that the atheroprotective functions of HDLs can be attributed to the number of HDL particles, and their characteristics including their lipid and protein components. Scientific interest has focused on HDL function and on the causes of rendering HDL particles dysfunctional, whereas the relevance of HDL subclasses with CVD remains controversial. METHODS The present review discusses changes in quality as much as in quantity of HDL in pathological conditions and the connection between HDL particle concentration and cardiovascular disease and mortality. Emphasis is given to the recently available data concerning the cholesterol efflux capacity and the parameters that determine HDL functionality, as well as to recent investigations concerning the associations of HDL subclasses with cardiovascular mortality. RESULTS MR studies or pharmacological interventions targeting HDL-C are not in favor of the hypothesis of HDL-C levels and the relationship with CVD. The search of biomarkers that relate with HDL functionality is needed. Similarly, HDL particle size and number exhibit controversial data in the context of CVD and further studies are needed. CONCLUSION There is no room for the old concept of HDL as a silver bullet,as HDL-C cannot be considered a robust marker and does not reflect the importance of HDL particle size and number. Elucidation of the complex HDL system, as well as the finding of biomarkers, will allow the development of any HDL-targeted therapy.
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Affiliation(s)
- Eleni Pappa
- Department of Internal Medicine, Medical University of Ioannina, Ioannina, Greece
| | - Moses S Elisaf
- Department of Internal Medicine, Medical University of Ioannina, Ioannina, Greece
| | - Christina Kostara
- Laboratory of Clinical Chemistry, School of Medicine, University of Ioannina, Ioannina, Greece
| | - Eleni Bairaktari
- Laboratory of Clinical Chemistry, School of Medicine, University of Ioannina, Ioannina, Greece
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Connelly MA, Velez Rivera J, Guyton JR, Siddiqui MS, Sanyal AJ. Review article: the impact of liver-directed therapies on the atherogenic risk profile in non-alcoholic steatohepatitis. Aliment Pharmacol Ther 2020; 52:619-636. [PMID: 32638417 PMCID: PMC7497003 DOI: 10.1111/apt.15935] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/23/2020] [Accepted: 06/11/2020] [Indexed: 12/17/2022]
Abstract
BACKGROUND Patients with non-alcoholic fatty liver disease (NAFLD), the most common cause of chronic liver disease, are at higher risk of cardiovascular disease (CVD) and associated mortality. Therefore, it is important to understand how new therapies for non-alcoholic steatohepatitis (NASH) may impact CVD risk factors in these patients. AIMS To summarise the effects of drug therapies on lipid and lipoprotein levels in patients with NASH and provide insight into the potential mechanisms for the observed changes. METHODS PubMed searches of the literature were performed and results were compiled. RESULTS Recent clinical trials have highlighted the safety and efficacy of drug candidates for the treatment of NASH. Several agents have shown improvements in the histological features of NASH and liver function. Pioglitazone, a drug that is currently available for type 2 diabetes and may be useful for NASH, exhibits beneficial effects on lipids. However, agents such as farnesoid X receptor agonists, which are in development for NASH, may adversely affect circulating lipids and lipoproteins. CONCLUSIONS NASH is a multi-system disease with a disproportionate CVD burden. Current and future drugs for NASH have had variable impact on the atherogenic risk profile. Potential co-administration of a statin may help mitigate the negative impact of some of these therapies on lipid and lipoprotein levels.
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Affiliation(s)
| | - Jonathan Velez Rivera
- Division of Endocrinology, Metabolism, and NutritionDepartment of MedicineDuke University Medical CenterDurhamNCUSA
| | - John R. Guyton
- Division of Endocrinology, Metabolism, and NutritionDepartment of MedicineDuke University Medical CenterDurhamNCUSA
| | | | - Arun J. Sanyal
- Division of Gastroenterology and HepatologyVirginia Commonwealth UniversityRichmondVAUSA
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Davis DW, Tallent R, Navalta JW, Salazar A, Lyons TJ, Basu A. Effects of Acute Cocoa Supplementation on Postprandial Apolipoproteins, Lipoprotein Subclasses, and Inflammatory Biomarkers in Adults with Type 2 Diabetes after a High-Fat Meal. Nutrients 2020; 12:E1902. [PMID: 32605005 DOI: 10.3390/nu12071902] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 06/22/2020] [Accepted: 06/24/2020] [Indexed: 12/22/2022] Open
Abstract
Dyslipidemia and inflammation exacerbate postprandial metabolic stress in people with diabetes. Acute dietary supplementation with polyphenols shows promise in improving postprandial metabolic stress in type 2 diabetes (T2D). Cocoa is a rich source of dietary polyphenols with demonstrated cardioprotective effects in adults without diabetes. To date, the acute effects of cocoa on postprandial lipids and inflammation have received little attention in the presence of T2D. This report expands on our earlier observation that polyphenol-rich cocoa, given as a beverage with a fast-food-style, high-fat breakfast, increased postprandial high-density lipoprotein-cholesterol (HDL-C) in adults with T2D. We now test whether polyphenol-rich cocoa modulated postprandial apolipoproteins (Apo-A1, B), non-esterified fatty acids, nuclear magnetic resonance (NMR)-derived lipoprotein subclass profiles, and select biomarkers of inflammation following the same dietary challenge. We found that cocoa decreased NMR-derived concentrations of total very low-density lipoprotein and chylomicron particles and increased the concentration of total HDL particles over the 6-hour postprandial phase. Serum interleukin-18 was decreased by cocoa vs. placebo. Thus, polyphenol-rich cocoa may alleviate postprandial dyslipidemia and inflammation following a high-fat dietary challenge in adults with T2D. The study was registered at clinicaltrials.gov as NCT01886989.
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Robbins JM, Herzig M, Morningstar J, Sarzynski MA, Cruz DE, Wang TJ, Gao Y, Wilson JG, Bouchard C, Rankinen T, Gerszten RE. Association of Dimethylguanidino Valeric Acid With Partial Resistance to Metabolic Health Benefits of Regular Exercise. JAMA Cardiol 2020; 4:636-643. [PMID: 31166569 DOI: 10.1001/jamacardio.2019.1573] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Importance Metabolic responses to exercise training are variable. Metabolite profiling may aid in the clinical assessment of an individual's responsiveness to exercise interventions. Objective To investigate the association between a novel circulating biomarker of hepatic fat, dimethylguanidino valeric acid (DMGV), and metabolic health traits before and after 20 weeks of endurance exercise training. Design, Setting, and Participants This study involved cross-sectional and longitudinal analyses of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a 20-week, single-arm endurance exercise clinical trial performed in multiple centers between 1993 and 1997. White participants with sedentary lifestyles who were free of cardiometabolic disease were included. Metabolomic tests were performed using a liquid chromatography, tandem mass spectrometry method on plasma samples collected before and after exercise training in the HERITAGE study. Metabolomics and data analysis were performed from August 2017 to May 2018. Exposures Plasma DMGV levels. Main Outcome and Measures The association between DMGV levels and measures of body composition, plasma lipids, insulin, and glucose homeostasis before and after exercise training. Results Among the 439 participants included in analyses from HERITAGE, the mean (SD) age was 36 (15) years, 228 (51.9%) were female, and the median (interquartile range) body mass index was 25 (22-28). Baseline levels of DMGV were positively associated with body fat percentage, abdominal visceral fat, very low-density lipoprotein cholesterol, and triglycerides, and inversely associated with insulin sensitivity, low-density lipoprotein cholesterol, high-density lipoprotein size, and high-density lipoprotein cholesterol (range of β coefficients, 0.17-0.46 [SEs, 0.026-0.050]; all P < .001, after adjusting for age and sex). After adjusting for age, sex, and baseline traits, baseline DMGV levels were positively associated with changes in small high-density lipoprotein particles (β, 0.14 [95% CI, 0.05-0.23]) and inversely associated with changes in medium and total high-density lipoprotein particles (β, -0.15 [95% CI, -0.24 to -0.05] and -0.19 [95% CI, -0.28 to -0.10], respectively), apolipoprotein A1 (β, -0.14 [95% CI, -0.23 to -0.05]), and insulin sensitivity (β, -0.13; P = 3.0 × 10-3) after exercise training. Conclusions and Relevance Dimethylguanidino valeric acid is an early marker of cardiometabolic dysfunction that is associated with attenuated improvements in lipid traits and insulin sensitivity after exercise training. Levels of DMGV may identify individuals who require additional therapies beyond guideline-directed exercise to improve their metabolic health.
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Affiliation(s)
- Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Matthew Herzig
- Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Jordan Morningstar
- Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Mark A Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia
| | - Daniel E Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Thomas J Wang
- Division of Cardiovascular Medicine, Vanderbilt University, Nashville, Tennessee
| | - Yan Gao
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Cardiovascular Research Center, Beth Israel Deaconess Medical Center, Boston, Massachusetts
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Duparc T, Ruidavets JB, Genoux A, Ingueneau C, Najib S, Ferrières J, Perret B, Martinez LO. Serum level of HDL particles are independently associated with long-term prognosis in patients with coronary artery disease: The GENES study. Sci Rep 2020; 10:8138. [PMID: 32424189 DOI: 10.1038/s41598-020-65100-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 04/27/2020] [Indexed: 01/07/2023] Open
Abstract
HDL-Cholesterol (HDL-C) is not an accurate surrogate marker to measure the cardioprotective functions of HDL in coronary artery diseases (CAD) patients. Hence, measurement of other HDL-related parameters may have prognostic superiority over HDL-C. In this work, we examined the predictive value of HDL particles profile for long-term mortality in CAD patients and to compare its informative value to that of HDL-C and apoA-I. HDL particles profiles were measured by nuclear magnetic resonance (NMR) spectroscopy in 214 male participants with stable CAD (45-74 years). Median follow up was 12.5 years with a 36.4% mortality rate. Cardiovascular mortality accounted for 64.5%. Mean concentrations of total HDL particles (HDL-P), small-sized HDL (SHDL-P) and apoA-I were lower in deceased than in surviving patients whereas no difference was observed according to HDL-C and large HDL particles. All NMR-HDL measures were correlated between themselves and with other HDL markers (HDL-C, apoA-I and LpA-I). In a multivariate model adjusted for cardiovascular risk factors and bioclinical variables, HDL-P and SHDL-P displayed the strongest inverse association with all-cause and cardiovascular mortality. Weaker associations were recorded for apoA-I. Based on our results, we conclude that HDL particle profile measured by NMR spectroscopy should be considered to better stratify risk in population at high risk or in the setting of pharmacotherapy.
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Insenser M, Moncayo S, Martínez‐García MÁ, Fernández‐Durán E, Samino S, Álvarez‐Blasco F, Luque‐Ramírez M, Escobar‐Morreale HF. 2D Diffusion‐Ordered
1
H‐NMR Spectroscopy Lipidomic Profiling after Oral Single Macronutrient Loads: Influence of Obesity, Sex, and Female Androgen Excess. Mol Nutr Food Res 2020; 64:e1900928. [DOI: 10.1002/mnfr.201900928] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 01/02/2020] [Indexed: 01/29/2023]
Affiliation(s)
- María Insenser
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
| | - Samuel Moncayo
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
| | - M. Ángeles Martínez‐García
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
| | - Elena Fernández‐Durán
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
| | - Sara Samino
- Departament d'Enginyeria ElectrònicaElèctrica i AutomàticaUniversitat Rovira i Virgili Reus Tarragona E‐43007 Spain
| | - Francisco Álvarez‐Blasco
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
| | - Manuel Luque‐Ramírez
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
| | - Héctor F. Escobar‐Morreale
- Diabetes, Obesity and Human Reproduction Research GroupDepartment of Endocrinology & NutritionHospital Universitario Ramón y Cajal & Universidad de Alcalá & Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS) & Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid E‐28034 Spain
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Sokooti S, Szili-Torok T, Flores-Guerrero JL, Osté MCJ, Gomes-Neto AW, Kootstra-Ros JE, Heerspink HJ, Connelly MA, Bakker SJL, Dullaart RPF. High-Density Lipoprotein Particles and Their Relationship to Posttransplantation Diabetes Mellitus in Renal Transplant Recipients. Biomolecules 2020; 10:E481. [PMID: 32245262 PMCID: PMC7175217 DOI: 10.3390/biom10030481] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 03/11/2020] [Accepted: 03/19/2020] [Indexed: 12/12/2022] Open
Abstract
High concentrations of high-density lipoprotein (HDL) cholesterol are likely associated with a lower risk of posttransplantation diabetes mellitus (PTDM). However, HDL particles vary in size and density with yet unestablished associations with PTDM risk. The aim of our study was to determine the association between different HDL particles and development of PTDM in renal transplant recipients (RTRs). We included 351 stable outpatient adult RTRs without diabetes at baseline evaluation. HDL particle characteristics and size were measured by nuclear magnetic resonance (NMR) spectroscopy. During 5.2 (IQR, 4.1‒5.8) years of follow-up, 39 (11%) RTRs developed PTDM. In multivariable Cox regression analysis, levels of HDL cholesterol (hazard ratio [HR] 0.61, 95% confidence interval [CI] 0.40-0.94 per 1SD increase; p = 0.024) and of large HDL particles (HR 0.68, 95% CI 0.50-0.93 per log 1SD increase; p = 0.017), as well as larger HDL size (HR 0.58, 95% CI 0.36-0.93 per 1SD increase; p = 0.025) were inversely associated with PTDM development, independently of relevant covariates including, age, sex, body mass index, medication use, transplantation-specific parameters, blood pressure, triglycerides, and glucose. In conclusion, higher concentrations of HDL cholesterol and of large HDL particles and greater HDL size were associated with a lower risk of PTDM development in RTRs, independently of established risk factors for PTDM development.
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Affiliation(s)
- Sara Sokooti
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
| | - Tamas Szili-Torok
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
| | - Jose L. Flores-Guerrero
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
| | - Maryse C. J. Osté
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
| | - António W. Gomes-Neto
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
| | - Jenny E. Kootstra-Ros
- Department of Laboratory Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands;
| | - Hiddo J.L. Heerspink
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands;
| | - Margery A. Connelly
- Laboratory Corporation of America® Holdings (LabCorp), Morrisville, NC 27560, USA;
| | - Stephan J. L. Bakker
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
| | - Robin P. F. Dullaart
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (T.S.-T.); (J.L.F.-G.); (M.C.J.O.); (A.W.G.-N.); (S.J.L.B.); (R.P.F.D.)
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50
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Salahuddin T, Kittelson J, Tardif JC, Shah PK, Olsson AG, Nicholls SJ, Leitersdorf E, Leiter LA, Kallend D, Black DM, Barter PJ, Ballantyne CM, Schwartz GG. Association of high-density lipoprotein particle concentration with cardiovascular risk following acute coronary syndrome: A case-cohort analysis of the dal-Outcomes trial. Am Heart J 2020; 221:60-66. [PMID: 31927126 DOI: 10.1016/j.ahj.2019.12.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 12/09/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND High-density lipoprotein cholesterol (HDL-C) concentration is inversely related to risk of major adverse cardiovascular events (MACE) in epidemiologic studies but is a poorer predictor of MACE in patients with established coronary heart disease. HDL particle concentration (HDLP) has been proposed as a better predictor of risk. We investigated whether HDLP is associated with risk of MACE after acute coronary syndrome (ACS). METHODS The dal-Outcomes trial compared the CETP inhibitor dalcetrapib with placebo in patients with recent ACS. In a nested case-cohort analysis, total, large, medium, and small HDLPs were measured by nuclear magnetic resonance spectroscopy at baseline (4-12 weeks after ACS) in 476 cases with MACE and 902 controls. Hazard ratios (HRs; case-control) for 1-SD increment of HDLP or HDL-C at baseline were calculated with and without adjustment for demographic, clinical, laboratory, and treatment variables. Similarly, HRs for MACE were calculated for changes in HDLP or HDL-C from baseline to month 3 of assigned treatment. RESULTS Over median follow-up of 28 months, the risk of MACE was not associated with baseline HDLP (adjusted HR = 0.98, 95% CI = 0.84-1.15, P = .81), any HDLP subclass, or HDL-C. Dalcetrapib increased HDL-C and total, medium, and large HDLP and decreased small HDLP but had no effect on MACE compared with placebo. There were no association of risk of MACE with change in HDLP or HDL-C and no interaction with assigned study treatment. CONCLUSIONS Neither baseline HDLP nor the change in HDLP on treatment with dalcetrapib or placebo was associated with risk of MACE after ACS.
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