1. Szilard Voros, MD, FACC, FSCCT, FAHA Chief Executive Officer | Founder
Precision Phenotyping, Panomics and Systems-Biology to Delineate Complex Networks of Atherosclerosis
Szilard Voros, MD, FACC, FSCCT, FAHA
Chief Executive Officer | Founder

2. Main Points
The recent biological thinking in atherosclerosis has been too narrow, pragmatic and linear
One solution is to create integrated, complex networks of atherosclerosis using precision phenotyping, panomics and systems- biology-drive bioinformatics (the GLOBAL study)
Preliminary insights from the GLOBAL study suggest functional and chromosomal positional convergence of the biology of atherosclerosis

3. Outline Development of Atherosclerosis
The Scientific Need: Linear Thinking to Networks
The Scientific Solution: the GLOBAL Study
Preliminary Insights

4. Outline Development of Atherosclerosis
The Scientific Need: Linear Thinking to Networks
The Scientific Solution: the GLOBAL Study
Preliminary Insights

5. Cardiovascular Disease Identifying the Root Cause: Atherosclerosis
Luminal Stenosis
Plaque Rupture
Coronary Pressure Drop
Thrombosis
Exertional Angina (Stable CAD)
Acute Coronary Syndromes
Demand
Myocardial Ischemia
Resting
Myocardial Ischemia/Infarct
Exertional Angina
Rest Angina, SCD

6. Cardiovascular Disease Identifying the Root Cause: Atherosclerosis
Lipoprotein
Deposition
Maladaptive
Inflammation
Apoptosis
VSMC
LRNC
Calcification
Fibrosis
Positive Remodeling
Negative Remodeling
Non-Calcified Plaque
Partially Calcified Plaque
Calcified Plaque

7. Outline Development of Atherosclerosis
The Scientific Need: Linear Thinking to Networks
The Scientific Solution: the GLOBAL Study
Preliminary Insights

8. Cardiovascular Disease Linear Thinking
Inhibit HMG-CoA Reductase
Inhibit cholesterol synthesis and apo B particles
Reduce lipid components of plaques (“NCP”)

9. Atherosclerosis Therapies Drugs Have a Very Large Number of Effects
Gene Expression Pattern of Different Statins in EC and SC

10. Outline Development of Atherosclerosis
The Scientific Need: Linear Thinking to Networks
The Scientific Solution: the GLOBAL Study
Preliminary Insights

11. G3: The Platform Clinical Study to Big Data to Biomarkers and Targets
G3’s “GLOBAL” CLINICAL STUDY
Most Comprehensive Clinical Study of Cardiovascular and Cardio-Metabolic Diseases
7,500 Subjects Enrolled
BIG DATA
22 Trillion Data-Points
COMPREHENSIVE NETWORKS
Most Detailed Network of Human Biology
BIOMARKERS
DRUG TARGETS

12. G3: The Platform G3’s Scientific Panomic Paradigm
DNA
25,000 genes
Epigenetics
micro-RNAs
RNA
100,000 transcripts
Environment
Proteins
1,000,000 proteins
Metabolites
7,000 small molecules
Lipids/ Lipoproteins
Phenotypes
Atherosclerosis
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

13. G3: The Platform Clinical Study to Big Data to Biomarkers and Targets
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

14. G3: The Platform Clinical Study to Big Data to Biomarkers and Targets
G3’s “GLOBAL” CLINICAL STUDY
7,500 Subjects
SPECTRUM OF CORONARY DISEASE
Controls: ~3500 Subjects
Cases: ~4000 Pts
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

15. The Solution GLOBAL Design: Analysis Cohorts
7500 Patients P D P V
Pilot
340 Pts
340 Pts
Interim
Discovery
Interim
Validation
Interim
2000 Pts
2000 Pts
DISCOVERY
5500 Patients
VALIDATION
2000 Patients
Entire
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

16. G3: The Platform Three Pillars
Precision Phenotyping
Advanced imaging with proprietary cardiac CT methods
Pan-Omic Evaluation
Whole Genome Sequencing (WGS) (DNA) (3 billion base pairs)
Whole Genome Methylation (WGM) (DNA) (500,000 bases)
Whole Transcriptome Sequencing (WTS) (RNA) (28,000 genes)
Proteomics (1800 proteins)
Metabolomics (over 800 metabolites)
Lipidomics (over 150 complex lipids)
Lipoprotein Proteomics (over 30 measurements)
Systems-Biology-Driven Bioinformatics
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

17. The Three Pillars of the GLOBAL Platform

18. A Novel Standard for Discovery The Three Key Components
Integrated, systems-biology-based bioinformatics
Next-generation phenotyping
Next-generation panomics

19. A Novel Standard for Discovery The Three Key Components
Integrated, systems-biology-based bioinformatics
Next-generation phenotyping
Next-generation panomics

20. G3: The Platform G3’s International and Proprietary Expertise in Cardiac CT
Maurovich-Horvat…Voros…Hoffmann.
Nature Reviews Cardiology 2014.

21. G3: The Platform G3’s International and Proprietary Expertise in Cardiac CT
U.S. Patent No. 12/643,962
Qian, Anderson. Marvasty, Akram, Vazquez, Rinehart, Voros. Journal of Cardiovascular Computed Tomography (2010) 4, 391–399.

22. The Solution Next-Generation Phenotyping
Validation of Cardiovascular CT
Maurovich-Horvat...Voros...Hoffmann. Nat Rev Cardiol Apr 22.

23. The Solution Next-Generation Phenotyping
Validation of Cardiovascular CT
Voros et al. JACC Cardiovasc Interv Feb;4(2):

24. The Solution Next-Generation Phenotyping: CT Analysis
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

25. A Novel Standard for Discovery The Three Key Components
Integrated, systems-biology-based bioinformatics
Next-generation phenotyping
Next-generation panomics

26. Need for Panomics
Definition of “panomics”: …combination of several “omics” approaches, including genomics, proteomics, metabolomics, lipidomics, etc….

27. Scientific Need Pan-Omics: The Modern Rosetta Stone
Egyptian Hieroglyphs
DNA
Demotic
RNA
Ancient Greek
Proteins

28. Scientific Need Characteristics of Disease Associated SNP’s
The majority of disease-associated DNA variants are in regulatory regions of the genome
93% of disease-associated DNA variants are in non- coding regions of the genome
77% of variants in non-coding regions are in regulatory regions; either in a DHS region (57.1%) or in perfect LD with SNP’s in DHS regions (19.5%)
Of all GWAS SNP’s in DHS, 93% overlap a transcription factor recognition sequence
A large proportion of regulatory regions are at significant distance from the target gene
41% are more than 250 kb away (threshold for LD)
There is significant enrichment of disease-associated DNA variants in relevant tissue types
Maurano et al. Science 337, 1190 (2012); DOI: /science

29. …accordingly, a panomic approach is very important…
Need for Panomics
…accordingly, a panomic approach is very important…

30. A Novel Standard for Discovery The Three Key Components
Integrated, systems-biology-based bioinformatics
Next-generation phenotyping
Next-generation panomics

31. The Solution Bioinformatics: The G3 Model
Atherosclerosis
Phenotype ↑ ↓
Lipids/Lipoproteins ↑ ↓
Metabolites ↑ ↓
Protein Levels ↑ ↓
Gene Expression
SNP/SNV; Epigenetic variants
DNA
Voros et al. J Cardiovasc Comput Tomogr 2014:8(6); 442–451.

32. Outline Development of Atherosclerosis
The Scientific Need: Linear Thinking to Networks
The Scientific Solution: the GLOBAL Study
Preliminary Insights

33. GLOBAL Pilot Discovery Cohort Demographic Data
Parameter
Controls
Native CAD
p-value
Age (Years)
54.8±0.8
55.1±0.9
0.78
Male (%)
71 (44.4)
51 (42.5)
0.85
Hypertension (%)
85 (53.1)
82 (68.3)
0.02
Dyslipidemia
80 (50.1)
85 (71.4)
<0.01
Diabetes
9 (5.6)
19 (15.8)
0.01
T2DM
18 (15.0)
Current Smoker
17 (10.6)
25 (20.8)
0.03
Chest Pain
109 (68.1)
78 (65.0)
0.67
Angina Equivalent
67 (41.9)
48 (40.0)
Dyspnea
42 (26.3)
28 (23.3)
0.68
Statin Use
49 (30.6)
59 (49.2)
Niacin Use
5 (3.1)
1 (0.8)
0.37
Fibrate Use
4 (2.5)
7 (5.8)
0.27
Ezetimibe Use
3 (2.5)
1.0
Fish Oil Use
18 (11.3)
23 (19.2)
0.09

34. GLOBAL Pilot Discovery Cohort Diamond-Forrester Distribution

35. GLOBAL Pilot Discovery Cohort Baseline CT Data: Case-Control Status

36. dysfunction, inflammation and insulin resistance…
GLOBAL Pilot Discovery Cohort Conventional Biomarkers
…early atherosclerosis is associated with atherogenic liporoteins, endothelial
dysfunction, inflammation and insulin resistance…

37. GLOBAL Pilot Discovery Cohort Relative Predictive Accuracy of Different “Omics”
…we have identified diagnostic biomarker signatures based on
lipidomics, metabolomics and gene expression; we are
evaluating these for potential clinical applications…

38. GLOBAL Pilot Discovery Cohort Relative Predictive Accuracy of Different “Omics”
…we had the opportunity to compare the relative predictive accuracy
of different “omics”…
…gene expression appears robust…

39. …we have observed the convergence of the top hits to single,
GLOBAL Pilot Discovery Cohort Relative Predictive Accuracy of Different “Omics”
…we have observed the convergence of the top hits to single,
isolated pathways…

40. …we have observed chromosomal positional enrichment of the top hits…
GLOBAL Pilot Discovery Cohort Relative Predictive Accuracy of Different “Omics”
…we have observed chromosomal positional enrichment of the top hits…

41. Main Points
The recent biological thinking in atherosclerosis has been too narrow, pragmatic and linear
One solution is to create integrated, complex networks of atherosclerosis using precision phenotyping, panomics and systems- biology-drive bioinformatics (the GLOBAL study)
Preliminary insights from the GLOBAL study suggest functional and chromosomal positional convergence of the biology of atherosclerosis

42. Szilard Voros, MD, FACC, FSCCT, FAHA Chief Executive Officer | Founder
Precision Phenotyping, Panomics and Systems-Biology to Delineate Complex Networks of Atherosclerosis
Szilard Voros, MD, FACC, FSCCT, FAHA
Chief Executive Officer | Founder