CRP and Inflammatory Markers

Transcription

1 CRP and Inflammatory Markers Christie M. Ballantyne, M.D. Center for Cardiovascular Disease Prevention Methodist DeBakey Heart & Vascular Center Baylor College of Medicine Houston, Texas

2 Case 66 year old nondiabetic Hispanic woman with history of borderline hypertension, not on meds Height 5'6" Waist 36" Weight 188 lb BMI 30.3 BP 145/83 Smoker No TC 231 TG 240 HDL 57 LDL 126

3 Framingham Risk Score Age 66 TC Nonsmoker HDL-C SBP Total 5% 10-year risk Expert Panel on Detection, Evaluation, and Treatment of High Blood od Cholesterol in Adults. JAMA 2001;285:

4 How Can Biomarkers be Used to Improve Patient Care? Improve global risk assessment, particularly in intermediate-risk risk patients Guide selection or intensity of therapy Provide target of therapy if risk factor and not just marker

5 Overview of Efforts to Identify Biochemical and Molecular Markers for Atherosclerosis Risk Stratification Surveys for identification of risk factors: large epidemiological trials and clinical event trials Candidate molecules based upon biology Inflammation and thrombosis

6 C-Reactive Protein Pentameric polypeptide produced by hepatocytes in response to inflammatory cytokines such as IL-6 Acute-phase protein involved in a variety of disorders that are mediated by inflammatory processes Stimulates secretion of proinflammatory cytokines (e.g., IL-6, TNF-α,, adhesion molecules, endothelin-1, and MCP-1) by endothelial cells Can bind to apolipoprotein B containing B lipoproteins and opsonize LDL for uptake by human monocyte- derived macrophages Predictive of cardiovascular events in prospective studies

7 hscrp Adds Prognostic Information Beyond the Framingham Risk Score in ALL Major Cohorts Evaluated Framingham Adjusted Relative Risk PHS 2 WHS MONICA ARIC < > 3 < > 3 < > 3 < > NHS 2 1 HPFS 2 1 CHS 2 1 EPIC-Norfolk Reykjavik* PIMA 0 < > 3 0 < > 3 0 <1 1-3 >3 0 <1 1-3 >3 0 <1 1-3 >3

8 Multivariable-Adjusted Relative Risk for First CV Event by CRP and Framingham Risk Score and by CRP and LDL-C C Categories: WHS Multivariable Relative Risk < > < >160 Framingham Estimate of 10-yr Risk, % Ridker PM et al. N Engl J Med 2002;347: LDL-C, mg/dl Slide Source: Lipids Online Slide Library

9 Lipoprotein-Associated Phospholipase A 2 (Lp-PLA 2 ) Hydrolyzes oxidized phospholipids to lysophosphatidylcholine and oxidized free fatty acids Unique phospholipase distinct from spla 2 ; also known as platelet-activating activating factor acetylhydrolase Co-traffics in circulation with LDL In WOSCOPS, relative risk for a coronary event was approximately twice as high in the highest quintile of Lp-PLA 2 compared with the lowest quintile 1 1 Packard CJ et al. N Engl J Med 2000;343:

10 LUMEN The Role of Lp-PLA 2 in CHD LDL Lp-PLA2 INTIMA MEDIA

11 LUMEN The Role of Lp-PLA 2 in CHD LDL Adhesion Molecules Cytokines Lp-PLA2 INTIMA Oxidized LDL Lyso-PC + OxFA MEDIA

12 LUMEN The Role of Lp-PLA 2 in CHD LDL Adhesion Molecules Monocytes Cytokines Plaque Formation Lp-PLA2 Foam Cell INTIMA Oxidized LDL Lyso-PC + OxFA Macrophage MEDIA

13 Ischemic Stroke Hazard Ratios (95% CI) by CRP Categories Defined by AHA/CDC Model 1 1 Categories of hs-crp CRP* Average Risk ( mg/l) 1.65 ( ) High Risk (> 3.0 mg/l) 2.70 ( ) Model 2 2 Model ( ) 1.54 ( ) 1.87 ( ) 1.97 ( ) * Low risk (<1 mg/l) is reference; ARIC tertiles were <1.01, , and >2.82. Adjusted for age, sex, and race Also adjusted for smoking status, SBP, LDL-C, HDL-C, and diabetes Also adjusted for antihypertensive medication and BMI Ballantyne CM et al. Arch Intern Med 2005;165:

14 Ischemic Stroke Hazard Ratios (95% CI) by Lp-PLA 2 Tertiles Model 1 1 Model 2 2 Model 3 3 Model 4 4 Tertiles of Lp-PLA 2 * 2 ( µg/l) 0.87 ( ) 0.87 ( ) 0.86 ( ) 0.89 ( ) 3 ( 422 µg/l) 2.23 ( ) 1.91 ( ) 1.97 ( ) 1.93 ( ) * Lowest (1st) tertile (< 310 µg/l) ) is reference Adjusted for age, sex, and race Also adjusted for smoking status, SBP, LDL-C, HDL-C, and diabetes Also adjusted for CRP Also adjusted for antihypertensive medication and BMI Ballantyne CM et al. Arch Intern Med 2005;165:

15 Association of Lp-PLA 2 and CRP with Incident Ischemic Stroke Ischemic Stroke Hazard Ratio High Medium Low (>3) (1 3) (<1) CRP, mg/l 95% CI , p<0.001 Low (<310) High Medium ( 422) ( ) Lp-PLALp PLA 2, mg/lg/l Ballantyne CM et al. Arch Intern Med 2005;165:

16 How Can Biomarkers be Used to Improve Patient Care? Improve global risk assessment, particularly in intermediate-risk risk patients Guide selection or intensity of therapy Provide target of therapy if risk factor and not just marker

17 AUCs for Incident CHD in 5 Years: ARIC AUC at 5 years Case cohort subjects, n Novel risk factor Basic * Basic and factor Increment CRS CHD cases Log CRP Lp-PLA *Basic model included age (continuous), race (white, African American), sex, total cholesterol (continuous), HDL-C (continuous), SBP (continuous), antihypertensive medications (yes or no), smoking status (current smoker or nonsmoker), and diabetes (yes or no) Basic model plus the indicated novel risk factor Sample group 4: visit 2 baseline followed up through 31 December 1998; median follow-up 7.3 years P <.05 for increase in AUC Folsom A et al. Arch Intern Med 2006;166:

18 Comparison of Areas under Receiver-Operating Characteristic Curve for Models with Traditional CVD Risk Factors Alone or with CRP Added Study WHS Rotterdam MONICA Augsburg Reykjavik Framingham Offspring Framingham Heart CHS Design prospective nested case control prospective nested case control prospective prospective prospective Sex women men and women men men and women men and women men and women men and women Multivariate- adjusted RR for CRP, quartile 4 vs quartile NA AUC for traditional risk factors alone 0.81 * AUC with CRP added ** *Age, smoking, DM, BP, HRT, treatment. Framingham risk score. Age, sex, exam period, TC, smoking, SBP. Age, sex, metabolic syndrome. Age, sex, SBP, TC/HDL-C, C, DM, smoking. Age, sex, race, education, CVD, elevated SBP, DM, smoking low HDL-C, high LDL-C, TG, alcohol, obesity, physical activity, LVH, diuretic use. **CRP + 5 other novel risk factors. Lloyd-Jones DM et al. Ann Intern Med 2006;145:35-42.

19 AUCs for Incident Stroke: ARIC Model TRF* TRF* + CRP TRF* + CRP + Lp-PLA 2 TRF* + CRP + Lp-PLA 2 + interaction AUC P (bootstrap test) <.05 <.05 <.05 <.05 *Age, sex, race, smoking, SBP, LDL-C, HDL-C, diabetes, antihypertensive medication, BMI Nambi V et al. Stroke 2009;40:

20 Stroke Risk by TRF Low (<2%) Moderate (2 5%) High (>5%) Overall Reclassification of Stroke Risk by Addition of Lp-PLA 2 and CRP to Traditional Risk Factors: ARIC Stroke Risk by TRF + CRP + Lp-PLA 2 Low (<2%) Moderate (2 5%) High (>5%) Overall % of TRF yr risk % of TRF yr risk % of TRF yr risk % of population TRF = traditional risk factors: age, sex, race, smoking, SBP, LDL-C, HDL-C, diabetes, antihypertensive medication, BMI Nambi V et al. Stroke 2009;40: yr risk

21 Reclassification of Stroke Risk by Addition of Lp-PLA 2 and CRP to Traditional Risk Factors: ARIC In analyses of 5-year stroke risk in the ARIC study, the area under the receiver operating characteristic curve was significantly improved by the addition of CRP and Lp-PLA 2 to traditional risk factors Most reclassification occurred in individuals who were at moderate risk for stroke based on traditional risk factors: only 4% of low-risk individuals but 36% of moderate-risk individuals were reclassified with the addition of CRP and Lp- PLA 2 to traditional risk factors Nambi V et al. Stroke 2009;40:

22 Development and Validation of Two Improved Algorithms for the Assessment of Global Cardiovascular Risk N = 8, events Derivation Cohort N = 16, events Validation Cohort Ridker et al, JAMA 2007;297:611-9

23 Candidate variables considered in predictive model development. (Transformations and interactions of these were also considered) Demographic variables Blood Biomarkers Age (years) History of diabetes (yes/no) Systolic blood pressure (mmhg) Diastolic blood pressure (mmhg) Treatment for hypertension (yes/no) Current smoking (yes/no) Past smoking (yes/no) Menopause (yes/no) Post-menopausal hormone use (yes/no) Body mass index (kg/m 2 ) Weight (pounds) Height (inches) Race (White, Black, Hispanic, Asian, Pacific Islander, American Indian/Alaskan Native, Other) Alcohol use (>once/wk) Exercise frequency (>once/wk) Parental history of myocardial infarction before age 60 years (yes/no) Current multivitamin use (yes/no) Migraine (yes/no) Aspirin use (randomization variable) Vitamin E (randomization variable) Beta-carotene (randomization variable) Total cholesterol (yes/no) High-density lipoprotein cholesterol (mg/dl) Low-density lipoprotein cholesterol (mg/dl) Non-HDL cholesterol (mg/dl) Treatment for hyperlipidemia (yes/no) Apolipoprotein A-I mg/dl) Apolipoprotein B 100 (mg/dl) C-reactive protein (mg/l) Creatinine (mg/dl) Homocysteine (umol/l) Lipoprotein(a) (mg/dl) Hemoglobin A 1 C Fibrinogen (mg/dl) Soluble intercellular adhesion molecule type-1 (sicam-1) (ng/ml) Ridker et al, JAMA 2007;297:611-9

24 Best Fitting Model A Age HbA1c %) if diabetic Ln(SBP) Current Smoking Ln(hsCRP) Parental history of MI < age 60 Apo-B 100 Apo A-I [Lp(a)-10] if Apo-B Clinically Simplified Model B (Reynolds Risk Score) Age HbA1c %) if diabetic Ln(SBP) Current Smoking Ln(hsCRP) Parental history of MI < age 60 Non-HDL-C (TC-HDL-C) HDL-C -- Not in the final model: Obesity, exercise levels, alcohol use, creatinine, homocysteine, fibrinogen, sicam-1

25 Risk Reclassification: ATP-III vs Reynolds Risk Score 10-Year Risk Reynolds Risk Score (%) % 27% 21% 55% 4% 56% 20% 96% 16% 4% 75% 25% Year Risk ATP-III (%) percent of those at intermediate risk according to ATP-III were reclassified by the addition of hscrp and family history to clinically relevant higher or lower risk groups. When comparing predicted to observed event rates, reclassification was correct in more than 98 percent of cases Ridker et al, JAMA 2007;297:611-9

26 The Reynolds Risk Score Calculating Heart and Stroke Risk for Women all the above were optimal 4% JAMA 2007;297:

27 Case 66 year old nondiabetic Hispanic woman with history of borderline hypertension, not on meds Height 5'6" Waist 36" Weight 188 lb BMI 30.3 BP 145/83 hscrp 3.3 Smoker No TC 231 TG 240 HDL 57 LDL 126 Parental history Yes 10-year risk: Framingham Risk Score: 5% Reynolds Risk Score: 10% Myocardial infarction age 72 JAMA 2007;297:

28 How Can Biomarkers be Used to Improve Patient Care? Improve global risk assessment, particularly in intermediate-risk risk patients Guide selection or intensity of therapy Provide target of therapy if risk factor and not just marker

29 Lp-PLA 2 and CRP: Markers or Targets of Therapy? LDL-C C levels have no correlation to incident stroke in ARIC, HPS LDL-C C and HDL-C C levels are strongly correlated to incident CHD Statins, which reduce LDL-C, Lp-PLA 2, and CRP, reduce CHD and stroke If reductions in Lp-PLA 2 and CRP are related to stroke reduction, Lp-PLA 2 and/or CRP may be markers for risk and possible targets for therapy

30 Justification for the Use of statins in Primary prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) ~15,000 men (age 55) and women (age 65) without prior cardiovascular event or CHD risk equivalent CRP 2 2 mg/l LDL-C C <130 mg/dl Randomization to rosuvastatin 20 mg/d or placebo Planned follow-up: years Primary endpoint: first occurrence of a major cardiovascular event (cardiovascular death, stroke, myocardial infarction, arterial revascularization, or hospitalization for unstable angina) Ridker PM. Circulation 2003;108:

31 JUPITER: Effects of rosuvastatin 20 mg on LDL, HDL, TG, and hscrp LDL (mg/dl) hscrp (mg/l) LDL decrease 50 percent at 12 months hscrp decrease 37 percent at 12 months Months TG (mg/dl) HDL (mg/dl) Ridker PM et al. N Engl J Med. 2008;359: HDL increase 4 percent at 12 months TG decrease 17 percent at 12 months Months

32 Cumulative Incidence Number at Risk Rosuvastatin Placebo JUPITER: Primary Endpoint (MI, Stroke, UA/Revascularization, CV Death) HR 0.56, 95% CI P < Follow-up (years) Placebo 251 / % Rosuvastatin 142 / ,901 8,631 8,412 6,540 3,893 1,958 1, ,901 8,621 8,353 6,508 3,872 1,963 1, Ridker PM et al. N Engl J Med. 2008;359:

33 How Can Biomarkers be Used to Improve Patient Care? Improve global risk assessment, particularly in intermediate-risk risk patients Guide selection or intensity of therapy Provide target of therapy if risk factor and not just marker

34 Clinical Relevance of Achieving LDL-C < 70 mg/dl and hscrp < 2 mg/l Following Initiation of Statin Therapy LDL>70, hscrp>2 LDL<70, hscrp>2 LDL>70, hscrp<2 LDL<70, hscrp<2 Recurrent Myocardial Infarction or Death (percent) Follow-up (days) Follow-up (days) PROVE IT TIMI 22 NEJM 2005;352: A to Z Circulation 2006;114:281-8

35 JUPITER Dual Target Analysis: LDLC<70 mg/dl, hscrp<2 mg/l Cumulative Incidence Placebo HR 1.0 (referent) LDL > 70 mg/dl and / or hscrp > 2 mg/l HR 0.64 ( ) LDL < 70 mg/dl and hscrp < 2 mg/l HR 0.35 ( ) Number at Risk Rosuvastatin Placebo Follow-up (years) 7,716 7,699 7,678 6,040 3,608 1,812 1, ,832 7,806 7,777 6,114 3,656 1,863 1, P <

36 Jupiter: Limitations 1. No control group to test the hypothesis that low LDL-C C and low hscrp do not have benefit from statins,, no published studies have shown significant treatment interaction between statins and hscrp 2. Impossible to answer the question of whether CRP levels are a target of therapy (dual targets) based upon Jupiter as not designed to answer this question

37 Selective Lp-PLA2 Inhibitor Darapladib Plaque Composition by IVUS - VH change from baseline in necrotic core volume entire region of interest [mean 48 mm] key secondary endpoint the worst 10 mm subsegment mean change (mm 3 ) p=0.012 * p=0.009 p=0.71 mean change (mm 3 ) p=0.003 p=0.162 * p=0.008 placebo (plus standard of care) n=110 darapladib 160 mg (plus standard of care) n=129 Between groups comparison: ANCOVA adjusted for ACS, pooled country, baseline value and segment length; within groups comparison: paired t test SerruysPW et al. Circulation 2008;118:

38 STABILITY: Aim of Study To evaluate clinical efficacy of long- term treatment with darapladib (Lp- PLA 2 inhibitor) versus placebo when added to standard of care in chronic CHD patient population on the incidence of major cardiovascular events

39 Conclusions 1. Inflammatory biomarkers such as hs-crp and Lp-PLA 2, improve risk classification in intermediate-risk risk individuals 2. Data do not support use in the entire adult population 3. No current biomarkers have been validated to examine "antiatherosclerotic" antiatherosclerotic" " efficacy of therapy 4. Individuals with high hs-crp levels benefit from statin therapy even if LDL-C C is not elevated

40 Conclusions 1. Patients who are on statin therapy with high levels of hscrp have higher events than those with low levels of hscrp but no data on how such patients should be treated to improve outcomes 2. Ongoing trials will examine if targeting LpPLA2 reduces CV events in high risk patients

41 Limitations with Current Approaches "Candidate molecule" biology based related to inflammation and thrombosis, neither of which is specific to atherosclerosis Therefore, problems with specificity, sensitivity, very small increases in AUC of ROC, modest net reclassification index Approach may still more useful for identifying targets of therapy, i.e., "risk factors"

42 Future Directions to Develop More Specific and More Sensitive Biomarkers Genomics Gene expression and profiling in cells/lesions Genetic polymorphisms associated with CHD from GWAS Proteomics Profile of differential expression of proteins in cell/lesions Microsequencing by mass spectrometry