Declaration of conflict of interest. Dominique de Kleijn is founder of a UMC Utrecht spin-off biomarker company Cavadis BV
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1 Declaration of conflict of interest Dominique de Kleijn is founder of a UMC Utrecht spin-off biomarker company Cavadis BV
2 BIOMARKERS OF DISEASE Microvesicle proteins as diagnostic and predictive biomarkers of cardiovascular disease Dominique de Kleijn NUHS & CVRI, Singapore UMCU & ICIN Utrecht, the Netherlands
3 Thrombus on rupture: Underlying cause of a cardiovascular event Davies MJ, Heart 2000;83:
4 Blood as a biomarker source A few proteins are present in a very large amount fe albumin Biomarkers are often present in a very low concentration Concentration of proteins can fluctuate due to unrelated causes (common cold vs atherosclerosis)
5 5 Exosomes & microvesicles Exosomes are small micro-vesicles shed by cells into the blood and other body fluids as a way of cell-cell communication. Vesicles of nm in diameter with a bi-lipid membrane Exosomes & microvesicles contain significant amounts of RNA, microrna and proteins Isolated by ultracentrifugation, filtration, precipitation techniques
6 Micro-vesicles as biological messengers
7 Microparticles after MI & endothelial function Boulanger C M et al. Circulation 2001;104:
8 Levels CD31+/Annexin V+ microparticles and MACE Sinning J et al. Eur Heart J 2011;32: Published on behalf of the European Society of Cardiology. All rights reserved. The Author For permissions please journals.permissions@oup.com
9 Microvesicle proteins Prediction of having a second cardiovascular event Diagnosis of having a myocardial infarction or not
10 Aim: Prediction of secondary events Determine if Plasma microvesicle proteins levels are Associated with future secondary events
11 Athero-Express Study Collecting end-arterectomy plaque specimen (carotid and femoral) and blood (start 2002) Patient characteristics* by questionnaire, clinical parameters Now >2500 patients included of which >1500 with CEA. Follow up: duplex and adverse cardiovascular events (hospital and phone) Study objective: to discover local plaque characteristics predictive for systemic adverse events
12 12 Proteomics on Athero- Express Cohort Quantitative itraq proteomics Samples: 50 pooled samples Ultracentrifuged isolated microvesicles (A-E cohort) with Coronary Artery Disease as secondary endpoint versus 50 sex and age-matched controls Identified 112 differentially expressed markers Biological pathways (Ingenuity) over-represented in CAD group 1. Acute Phase Response Signaling 2. Coagulation System Selection biomarker validation panel for Luminex Based on over-representation of above-mentioned biological pathways Availability of two non-competitive antibodies and recombinant antigen 4 microvesicle proteins: CystatinC, CD14, SerpinF2, SerpinG1
13 Validation study SMART: Second Manifestations of ARTerial disease study (n=1060) Baseline: Patients already suffered first event (MI, Stroke, TIA or AAA) Study endpoints: Coronary endpoint: Myocardial infarction Composite endpoint: Stroke, Cerebral hemorrhage, Myocardial Infarction, Retinal infarction, Vascular mortality - Exoquick was used for the isolation of microvesicles of individual samples 13
14 Baseline characteristics SMART cohort (N=1060) Characteristic n (%) Male gender 839 (79%) Type 2 diabetes 164 (16%) Smoking Never Ever Current History of vascular disease CVA CAD PAD AAA 177 (17%) 492 (46%) 391 (37%) 285 (27%) 617 (58%) 261 (25%) 108 (10%) Metabolic syndrome (ATPIII) 406 (38%) Characteristic mean (SD) Age 59 (10) BMI (kg/m2) 26.9 (3.9) egfr (ml/min/1.73m2) 77.5 (18%) 14
15 Hazard ratios MV-markers: adjusted Study Endpoints SMART (n=1060) Hazard ratio (95% CI) per 1 SD increase in marker level CystatinC CD14 SerpinF2 SerpinG1 Myocardial Infarction 1.49* ( ) 1.55* ( ) 1.22* ( ) 0.95 ( ) Composite vascular endpoint # 1.27* ( ) 1.32* ( ) 1.14 ( ) 1.08 ( ) All-cause mortality 1.41* ( ) 1.36* ( ) 1.22* ( ) 0.99 ( ) # Composite endpoint: Stroke, Cerebral hemorrhage, Myocardial infarction, Retinal infarction or Vascular mortality * significant Adjusted for: Age, Gender, Smoking, syst. BP, egfr, medication, type II Diabetes, metabolic syndrome, history of CVD, CAD, PAD, AAA, albuminaria, LDL, CRP 15
16 16 CD14 Endpoint: ischaemic cardiac events Biomarker Adjusted Hazard Ratio At 3-years [95% CI] Adjusted P-value Adjusted Hazard Ratio At 8-years [95% CI] Adjusted P-value CD [ ] [ ] CD14 CD14 % ischemic cardiac endpoint 8 P< Time (years) Q4 Q3 Q2 Q1 % ischemic cardiac endpoint 20 P< Time (years) Q4 Q3 Q2 Q1
17 17 Proteins are associated with microvesicles Density of the collected UC fractio CD9 microvesicle marker CD14 SerpinG1 SerpinF2 Cyst C: 50 kd Cyst C: kd bands
18 Prediction of secondary events Plasma microvesicle proteins levels are associated with future secondary events
19 Diagnosis of Acute Coronary Syndrome ER Acute Coronary Syndrome Electrocardiogram ST-elevation No ST-elevation Cardiac Markers Positive (~20%) Negative (~80%) PCI Other causes
20 Aim diagnosis Determine if microvesicle proteins levels are associated with the diagnosis of myocardial infarction in a Non-ST elevated ER population
21 FAME-ER cohort FAME-ER: Fatty acid-binding protein in Acute Myocardial infarction Exclusion in the Emergency Room Meander Medical Center Amersfoort, the Netherlands 471 frozen serum samples of Non-ST ER patients
22 FAME-ER cohort & proteomics Quantitative Proteomics were performed on Ultracentrifugation isolated microvesicles from 30 pooled ACS patients and compared to 30 gender and age matched non-acs patients. Differential expressed proteins were uploaded in Ingenuity: 2 Top networks selected with 36 proteins 3 proteins selected on availability of 2 antibodies and recombinant antigen for Luminex: Cystatin C, C5a, pigr Individual sample measurement after Exoquick isolation
23 Baseline characteristics FAME-ER cohort (N=471) Characteristic Non-ACS (n=331) ACS (n=140) p-value Male gender, n (%) 171 (52) 92 (66) Age mean yr+/-sd 60.1+/ /-12.6 <0.001 Duration of symptoms mean hr +/-SD History of cardiac disease MI, n (%) CABG, n (%) PCI, n (%) 12.5+/ / (18) 27 (8) 67 (20) 40 (29) 19 (14) 30 (22) Hypertension, n (%) 121 (37) 79 (58) <0.001 Type 2 DM, n (%) 47 (14) 25 (18) Hyperchol., n (%) 93 (28) 56 (41) Statin use, n (%) 140 (42) 121 (87) <0.001 Smoking, n (%) 171 (52) 70 (51)
24 Multivariate corrected for risk factors FAME-ER cohort (N=471) 24 Marker HR 95% CI p-value pigr Cystatin C C5A Protein Conc Corrected for: Age, Gender, Previous MI, Hypertension, Hypercholesterolemia, DM, smoking
25 Forrest plot Are Males different from Females? Corrected for: Age, Gender, Previous MI, Hypertension, Hypercholesterolemia, DM, smoking
26 Summary and conclusions Predictive: plasma microvesicle protein levels are associated with future secondary events on top of risk factors Microvesicle proteins have a strong potential to predict secondary cardiovascular events Diagnostic: plasma microvesicle protein levels are associated with the diagnosis of ACS on top of risk factors Differences between gender are striking and might apply to other cardiovascular cohorts
27 Therapeutics 27 Future We are just scratching the surface Well characterized mirror international biobanks PCI, CABG, CEA, ER, HF patients Netherlands (ICIN, Meander & UMC Utrecht) and Singapore NUH&CVRI & other hospitals Detection & Isolation FACS (Van der Vlist EJ, Nat Protocol, 2012, 14;7: ) Exoquick Beads Subfractions of plasma microvesicles Biological activity & Function
28 Acknowledgements University Medical Center Utrecht Guus van Lammeren Arjan Schoneveld Hanna Inganas Sander van de Weg Leo Timmers Vince de Hoog Karlijn van Keulen Gerard Pasterkamp Singapore Sai Kiang Lim (IMB) Sze (Newman) Sui Kwan (NTU) Cavadis BV Heico Breek Jaques de Jong Louise Catanzeriti Sander van der Laan Dept of Cardiology Danny Kanhai Frank Visseren Frans Moll Jean Paul de Vries Aryan Vink Michiel Bots Meander Medical Center Amersfoort Arend Mosterd FAME study group Monday 27 august: 14:00-18:00 P3574
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