Lipids, Lipoproteins and Cardiovascular Risk: Getting the Most out of New and Old Biomarkers. New and Old Biomarkers. Disclosures

Size: px

Start display at page:

Download "Lipids, Lipoproteins and Cardiovascular Risk: Getting the Most out of New and Old Biomarkers. New and Old Biomarkers. Disclosures"

Wendy Hubbard
6 years ago
Views:

1 Lipids, Lipoproteins and Cardiovascular Risk: Getting the Most out of New and Old Biomarkers William Cromwell, MD, FAHA, FNLA Diplomate, American Board of Clinical Lipidology Chief Lipoprotein and Metabolic Disorders Institute Adjunct Associate Professor Wake Forest University School of Medicine Disclosures William Cromwell, MD, FAHA, FNLA Chief Lipoprotein and Metabolic Disorders Institute Adjunct Associate Professor Wake Forest University School of Medicine Speaker: Consultant: Abbott, Kowa, LipoScience, Merck Genzyme, Health Diagnostic Laboratory, Isis LabCorp Three Part Lecture Series 1. Lipids, Lipoproteins and Cardiovascular Risk: Getting the Most out of New and Old Biomarkers Analytic Issues Involving Alternate Lipid and Lipoprotein Quantity Measures Clinical Expectations of Cardiovascular Biomarkers 2. -C, Non-HDL-C, Measures of Particle Number (apob and -P): And the Winner is Influence of concordance versus discordance between lipid and lipoprotein measures on cardiovascular outcomes Impact of confounding factors and methods of data analysis on outcome associations of lipid and lipoprotein biomarkers 3. Can We Optimize Individual Care Without Knowledge of Particle Number? Expert opinion and guideline recommendations on use of lipid and lipoprotein measures to optimize of individual management 1

no single test that infallibly separates all those who have dyslipoproteinemia from those who do not.

2 Analytic Issues Involving Alternate Lipid and Lipoprotein Quantity Measures Lipids, Lipoproteins and Atherosclerosis: Historic Perspective Distinction Between Lipids (Cholesterol) and Lipoproteins Noted in 1960s - But Then Forgotten there is no single test that infallibly separates all those who have dyslipoproteinemia from those who do not. the majority of laboratories still employ a combination of chemical measurements of plasma lipids for this purpose. Fredrickson et al., NEJM 1967; 276: 148 2

-C and HDL-C Were the Only Clinically Accessible Biomarkers of and HDL

20 HDL 3 HDL 2 IDL HDL Cholesterol Cholesterol Chylomicron Remnants

Equation Introduced in 1972 Sealed the Deal -C = TC - HDL-C - (TG/5) As did

3 -C and HDL-C Were the Only Clinically Accessible Biomarkers of and HDL Levels For Decades 0.95 V Chylomicrons Density (g/ml) HDL 3 HDL 2 IDL HDL Cholesterol Cholesterol Chylomicron Remnants Triglycerides (mainly) Diameter (nm) Friedewald Equation Introduced in 1972 Sealed the Deal -C = TC - HDL-C - (TG/5) As did the National Cholesterol Education Program Does Cholesterol Accurately Quantify Lipoprotein Particles? Apolipoprotein Apolipoprotein POLAR SURFACE COAT Phospholipid Free cholesterol NON-POLAR LIPID CORE Cholesterol Ester Triglyceride Apolipoprotein 3

4 Cholesterol Carried Inside Lipoprotein Particles Is Highly Variable Cholesterol ester Triglyceride TG Hepatic Lipase Small CETP CE TG CETP Hepatic Small HDL CE Lipase Otvos JD, Jayarajah E, Cromwell, WC. AJC 2002;90(8A):22i-29i Cholesterol Content Variability of is Driven Partly by Size Differences Framingham Offspring Study (n=3,066) 21.2* Cholesterol Molecules Per Particle < > > < 100 -C (mg/dl) Triglycerides (mg/dl) Cromwell WC et al. J Clin Lipidology 2007;1(6): * Numbers are mean sizes (nm) Cholesterol Content Variability of is Driven Also by Concentration! Framingham Offspring Study (n=3,066) 21.2* Cholesterol Molecules Per Particle < > > < 100 -C (mg/dl) Triglycerides (mg/dl) Cromwell WC et al. J Clin Lipidology 2007;1(6): * Numbers are mean sizes (nm) 4

5 Distinction Between Lipids (Cholesterol) and Lipoproteins Noted in 1960s - But Then Forgotten all abnormalities in plasma lipid concentrations, or dyslipidemia, can be translated into dyslipoproteinemia. the shift of emphasis to lipoproteins offers distinct advantages in the recognition and management of such disorders. Fredrickson et al., NEJM 1967; 276: 148 What s Actually Bad and Good are Different Lipoprotein Particles 0.95 V Density (g/ml) IDL Chylomicron Remnants HDL 3 HDL 2 Good Particles Bad Particles Diameter (nm) Other Lipoprotein Biomarkers Are Now Available: Apolipoproteins 0.95 V Chylomicrons Chylomicrons Density (g/ml) HDL 3 HDL 2 Apo A-1 IDL Apo B Chylomicron Remnants Except for type III hyperlipidemia, more than 90% of total plasma ApoB particles are particles (even among high TG patients) [1,2] Diameter (nm) 1 Sniderman,A,et al. Atherosclerosis 1991; 89: Durrington PN,et al. Clin Chim Acta 1978; 82:

Other Lipoprotein Biomarkers Are Now Available: Particle Number by NMR 0.95 V Chylomicrons Density (g/ml) 1.006 1.02 1.06 1.10 1.

Concordance Concordance 49% Discordance 51% Percent Percent Concordance 63% Discordance 37% Adapted from Sniderman AD, et al.

6 Other Lipoprotein Biomarkers Are Now Available: Particle Number by NMR 0.95 V Chylomicrons Density (g/ml) HDL 3 HDL 2 HDL-P IDL -P Chylomicron Remnants V-P Diameter (nm) Analytic Relations of Lipid and Particle Number Measures Quebec Cardiovascular Study (n=2,103) Correlation Concordance Concordance 49% Discordance 51% Percent Percent Concordance 63% Discordance 37% Adapted from Sniderman AD, et al. Am J Cardiol 2003;91: Analytic Relations of Lipid and Particle Number Measures Multi Ethnic Study of Atherosclerosis [MESA] (n=6,697) -C (mg/dl) P > -C cholesterol-poor P percentile P (nmol/l) Discordant Concordant -P < -C cholesterol-rich C percentile Otvos, JD, et al. J Clin Lipidol 2011;5:

7 Concordance / Discordance Associations with Alternate Measures of Quantity 1. Discordance between -C and particle number (Apo B, NMR -P) Noted in up to 50% of all subjects [1-8] 75% among T2DM and Met Syn subjects with -C <100 mg/dl [2,3] 2. Less discordance between non-hdl-c and particle number (Apo B, NMR -P) [2,4,6,9] Noted in more than 1/3 of all subjects and up to 40% of subjects with T2DM 3. Discordance is highly prevalent among 22,000 subjects at ATP goal values [6] In 14,425 subjects with TG <200 mg/dl, 66% and 58% met -C and non-hdl-c goals (100 mg/dl and < 130 mg/dl), respectively; however, only 30% of these same individuals met the Apo B goal Among 7,611 subjects with TG levels greater than 200 mg/dl, only 17% met the Apo B goal, whereas 60% and 51% of subjects met the -C and non-hdl-c goals, respectively 1 Otvos JD, et al. Am J Cardiol. 2002;90(8A):22i-9i. 2 Cromwell WC, Otvos JD. Am J Cardiol. 2006; 98(12): Kathiresan S, et al. Circulation. 2006;113(1): Sniderman AD, etal. Am J Cardiol. 2003;91(10): Kim BJ, et al. Clin Chem. 2005;51(12): Stein EA, et al. Am J Cardiol. 2005;96(9A):36K-43K; 7 Otvos JD, et al. J Clin Lipidol ;5(2): Sniderman AD, et al. Am J Cardiol. 2001;87(6): 792-3, A8. 9 Malave H, et al. Am J Cardiol;110(5): Sniderman AD. J Clin Lipidol ;2(1): Concordance / Discordance Associations with Alternate Measures of Quantity 4.Discordance is highly prevalent among T2DM subjects at ATP goal values [2]. Among 1,484 subjects with -C mg/dl (5 th -20 th percentile), 75% manifested discordantly high particle number (>20 th percentile). Among 871 subjects with -C < 70 mg/dl (<5 th percentile), 40% showing similar magnitude of particle discordance (> 20 th percentile). 5.Statin therapy results in greater -C & non-hdl-c reductions versus particle number (Apo B or NMR -P) [10]. 6.Thus, many patients show discordant elevations in particle number despite being having low or very low -C or non- HDL-C values. 1 Otvos JD, et al. Am J Cardiol. 2002;90(8A):22i-9i. 2 Cromwell WC, Otvos JD. Am J Cardiol. 2006; 98(12): Kathiresan S, et al. Circulation. 2006;113(1): Sniderman AD, etal. Am J Cardiol. 2003;91(10): Kim BJ, et al. Clin Chem. 2005;51(12): Stein EA, et al. Am J Cardiol. 2005;96(9A):36K-43K; 7 Otvos JD, et al. J Clin Lipidol ;5(2): Sniderman AD, et al. Am J Cardiol. 2001;87(6): 792-3, A8. 9 Malave H, et al. Am J Cardiol;110(5): Sniderman AD. J Clin Lipidol ;2(1): Clinical Expectations of Cardiovascular Biomarkers 7

8 Evaluating Cardiovascular Biomarkers Intended Application Type of Biomarker Clinical Use Impact on Clinical Decision Making Evidence Needed to Support Use Risk Assessment Risk Management New Biomarker (Inflammatory measures, Particle size) New Measure of Established Biomarker ( Quantity) New Biomarker (inflammatory measures, particle size) New Measure of Established Biomarker ( Quantity) Biomarker is added to other information to enhance risk assessment Biomarker serves as a treatment target and guides need for additional therapy Allocate patient to different risk category which may result in more aggressive or less aggressive therapy Modify therapy (different agents, dosage, or combinations) as indicated to achieve new therapeutic target Significant improvement in risk stratification with the addition of new biomarker, or substitution of new measure of existing biomarker, in risk models (net reclassification, c-statistic, ROC) Outcome improvement established independent of other risk factors New measure consistently outperforms the existing measure in the setting of discordance Ann Intern Med 2008;149: Criteria and principles for accepting a new test as a better reference standard: 1) Value of the new reference test is best examined in cases of disagreement (discordance) between the current and new tests. Ann Intern Med 2008;149: Criteria and principles for accepting a new test as a better reference standard: 2) Resolving disagreements between old and new test requires a fair umpire test. 3) Fair umpire tests include clinical events or disease progression. 8

9 Evaluating Lipid and Lipoprotein Measures 1. What are the associations of various biomarkers with cardiovascular outcomes? A. Simple univariate biomarker associations are often incomplete and potentially misleading. B. Is there a consistent, strong and independent association between the biomarker and clinical outcomes after adjustment for confounding factors? 2. Does the biomarker add substantial new information and / or uniquely change risk assessment? 3. Does the biomarker meet expectations for use in risk management? 4. Can the clinician feasibly measure the biomarker? A. Are there accurate and reproducible analytical methods readily available to the clinician? B. Is the cost reasonable for the information obtained? Summary 1. History, not biomarker performance, made bad and good HDL cholesterol the clinical standard of care. 2. The cholesterol content of lipoprotein particles can differ more than two fold between patients, as well as in the same patient over time. 3. Differences in cholesterol content of lipoprotein particles results in discordance between cholesterol and particle number measures of and HDL quantity. 4. Outstanding questions to be discussed in upcoming lectures: What is the clinical significance of discordance between lipid and lipoprotein measures? How do confounding factors and methods of data analysis affect our understanding of lipid and lipoprotein biomarkers? How can we use lipid and lipoprotein biomarkers to optimize individual management? 9

Pdf. TC = 152 TG = 170 HDL-C = 37 VLDL-C = 34 LDL-C = 81 Non-HDL-C = 115 TC/HDL-C = 4.1 TG/HDL-C = 4.6. I was asked for my thoughts.

Pdf. TC = 152 TG = 170 HDL-C = 37 VLDL-C = 34 LDL-C = 81 Non-HDL-C = 115 TC/HDL-C = 4.1 TG/HDL-C = 4.6. I was asked for my thoughts. Pdf LIPID CASE 252 Particle Core Composition Hi Lipidaholics: The following case demonstrates a topic I have wanted to discuss in depth. It illustrates the concept of particle composition meaning what