Get insights into the relation between CMV and atherosclerosis

1. Get insights into the relation between CMV and atherosclerosis Case study 1

2. Background Atherosclerosis • The main cause of death in the Western world. • Multi-factorial disease : environmental (diet, smoking, exercise, infection) and genetic risk factors. • Inflammation is a main contributor. • Is a disease in which a fatty-like substance (plaque) is deposited on the inside of the arteria walls. • The exact cause of atherosclerosis remains unknown.

3. Atherosclerosis and cytomegalovirus • CMV is a double-stranded DNA beta herpes virus affecting 50 % of the population. • Increasing evidence linking CMV and atherosclerosis (epidemiologic, antibodies, gene expression etc…) • Nevertheless cellular mechanisms are not well understood and it is unknown whether the virus can causally contribute to atherosclerosis. • Recently, lipid modulation experiments (statins, polyunsaturated fatty acid etc…), showed a potential mechanism in viral and inflammatory process.

4. Aim The relation between CMV and atherosclerosis is controversial and not well understood. Therefore we aim to get insights into this relation Step 1 : To determine the proven relations between CMV and atherosclerosis

5. Review of literatureResults • All studies focused on the relation between CMV and consequences of atherosclerosis (e.g. death and restenosis) • Most studies conclude a positive relation between the two • No studies focused on the process of plaque formation • A negative relation has been demonstrated between CMV and plaque rapture Hypothesis: CMV influences plaque formation

6. Design of molecular study Design of medical strategy Model MicroArray Computarized modeling New epidemiological study design Imaging Strategy Aim : to get insights into the relation between CMV and atherosclerosis Review of literature Hypothesis: CMV influences plaque formation knowledge Pharmacology

7. Michiel Computer Scientist THE TEAM !!! Lula Biostatistician Cristina Medical Chemistry Mathieu Biologist Adrián Computational Biologist

8. Molecular Approach • Hypothesis: CMV trigger the formation of the plaques • Molecular mechanisms are not well understood: implication of inflammatory/ immune response and lipids pathway • Aim: Study the interactions between the CMV and the development of atherosclerosis CMV Cell Network interaction Understand Atherosclerosis

9. Molecular Approach Strategy Genes Network + Metabolite Interactions model Micro-Array Database Phase I Phase II Validation and upgrading of the network Model Identifications of key genes and metabolites playing a role in atherosclerosis regulated by lipids regulation and or CMV infections. Phase III Computer science Molecular biology/ Bioinformatic Pharmacology Simulation Parameter Estimation Sensitivity analysis New Hypothesis on possible molecular interaction and bench validation Drugs targeting

10. Phase I : Building a Network of interactions genes Lipids Genes Lipid Metabolites Pro-Atherosclerotic genes Knowledge Literature Genes list of the key genes/metabolite involved in each process Define interactions between this emtities to build a network Text Mining

11. Text-Mining 26 lipid genes related 11 pro-atherosclerotic genes 5 lipid Metabolites Text Mining tool : Pathway Studio (Use of options : add small molecules to integrate lipids). 99 proteins in total 98 small molecules (20 lipids) 771 interactions

12. Pathway Assist network interaction of lipid metabolite / lipid genes / Atherosclerosis genes

13. Limitations • Text Mining • Relation not always biologically relevant or true • Not useful too many putative interactions • Biological • Interactions Metabolites / Genes are very limited • Not useful too many putative interactions • Computational • Format compatibility • Lack of quantitative relationship Difficult to work with this network Using this network of interactions we decided to build a more specialised and reduced network around lipid genes/metabolites and pro-atherosclerotic genes which could be use by biologists and computer scientists

14. Creation of a curated and specialised interaction genes network • Limitations to the direct (genes/proteins) interactions. • Each interactions has been checked by one of us in the litterature and with our personal knowledge. • Add manually Interactions with lipids (cholesterol, oxysterols, fatty acid). 19 proteins 3 lipids 65 interactions

15. Pubmed GEO Array express GPX 11 studies and dataset available statin 11 studies and dataset available CMV infection 9 studies and dataset on lipid modulation CMV/Lipids Database 31 Array experiments Time point experiments Different cell line (fibroblast, macrophages Species: murine, human

17. Molecular Approach Strategy Genes Network + Metabolite Interactions model Micro-Array Database Phase I Phase II Validation and upgrading of the network Model Identifications of key genes and metabolites playing a role in atherosclerosis regulated by lipids regulation and or CMV infections. Phase III Tools Computer science Molecular biology/ Bioinformatic Pharmacology Simulation Parameter Estimation Sensitivity analysis New Hypothesis on possible molecular interaction and bench validation Drugs targeting

18. Tools for Computational biology • Quantitative relationships between network nodes allow to work with different prediction and simulation software programs.

19. Today, SBML is supported by over 90 software systems

20. No export support, we did it manually !!! Development of a computational tool !!! Today, SBML is supported by over 90 software systems

21. Logical translation of the pathway - positive interaction - negative interaction

22. Mathematical method Power Laws: Applied in large datasets of metabolism. Not much biological details needed First insights into biochemical mechanism Rate Laws: Not enough knowledge Boolean Networks: Far from biochemical mechanism PDEs: Complicate method, few tools

23. Simulation Results

24. GDS476: 12 temporal points of 12626 genes PARAMETER DETERMINATION OF THE NETWORK Experimentally tunned model

25. Parameter optimized model +

26. c c Parameter optimized model + Sensitive node Pharmacological target

27. Tool for biology • Analysis of micro-Array data using our model to identify new target • Clustering • Pathway mapping • Design of new micro-array experiments • CMV • Lipid modulation • Host/CMV chip array • Hypothesis key relations study them in a more “traditional” way • Molecular biology • Bench work • Develop high throughput methods to record different lipids level into the cells • Use of Mass spectrometry, • development of lipids Array.

28. Tool for pharmacology • Identification of drugs targeting key genes and metabolites involved in the intersection between lipid and inflammatory pathways in a CMV / atherosclerosis context.

29. CMV infection is involved in two of the major mechanism that lead development of atherosclerosis: Immune injury + CMV + - - CMV Lipid Alteration

30. CMV-Atherosclerosis from a medicinal chemistry point of view: rational multi-target poly-pharmacy • STATINS • LXRα and PPARα agonist Use of these drugs to limit CMV effects in atherosclerosis disease : lipid alteration and inflammatory effect

31. CMV-Atherosclerosis from a medicinal chemistry point of view: rational multi-target poly-pharmacy • Antagonist of Nf-kB to reduce immunity response through: • inhibition of iNOs genes. It produces nitric oxide (NO) that increase oxLDL • Inhibition of leukocyte adhesion cascade • NFKB expression is increase by CMV.

32. CMV-Atherosclerosis from a medicinal chemistry point of view: dual PPARα and PPARγagonist PPAR-alpha agonist induce expression of LXRα. PPAR-gamma agonists induced expression of ABCG1. ABCG1 has been shown to transfer cholesterol from cells to form HDL, the carrier of “good cholesterol” in the bloodand is regulated by CMV.

33. Design of molecular study Design of medical strategy Model MicroArray Computational modeling New epidemiological study design Imaging Strategy Aim : to get insights into the relation between CMV and atherosclerosis Review of literature Hypothesis: CMV influences plaque formation knowledge Pharmacology

34. Research plan • Define CMV measurement method • Determine plaque formation quantification method • Formalize epidemiological study • Perform study in population

35. CMV measurement Plaque measurement Total plaque progress CMV level Global Local Local Global Research planLocal vs. global measurements • Local measurements pinpoint the exact location of plaque and CMV (= histological) • Global measurements (=systemic) indicate the total amount of plaque and CMV. It is less specific than local measurements.

36. CMV measurement • Methods used in literature • CMV specific IgG antibodies • Measure virus activity • Global measurement • Virus detection with PCR • Measures the virus presence locally • Do not measure the activity • Done in vitro

37. Local CMV measurement • No existing technique available • Plan to develop measurement method: • Find or develop a label that indicates CMV • Attach radioactive or physical marker to the label • Quantify and localise agent with nuclear (radioactive) or possibly magnetic resonance (physical) imaging technique • A disadvantage of nuclear imaging is the exposure to radioactivity

38. Plaque formation measurement (1) • Not described or used in CMV-atherosclerosis studies • It is assumed that there is no way to measure directly plaque growth • Plaque growth can be determined by 2 separate plaque measurements • Several possibilities are available to measure the amount of plaque locally(i.e. make an image of a subject that indicates plaque presence at each anatomical location)

39. Plaque formation measurement (2) Plaque quantification techniques

40. Total plaque progress CMV level Local Global Global Local Epidemiological study • Objective : Determine if a relation exists between CMV and plaque growth • Two different possibilities • Global level of CMV versus global amount of plaque growth • Local level of CMV versus local amount of plaque formation CMV measurement Plaque measurement

41. Regular CMV activity measurements MR1 MR2 MR3 Epidemiological study (2)Global CMV vs. global plaque • Method: • Three plaque measurements with MR imaging in carotid arteries combined with automatic plaque quantification • Frequent CMV activity measurements in blood samples • Population: a big random selection • Determine number of necessary subjects from estimation of the probability to find CMV in plaque Determine: - Difference in plaque growth between the two periods (2plaque) - Amount of times the virus was activated (NCMV) Regression : 2plaque ~NCMV AbCMV

42. MR1 MR2 CMV Plaque Local CMV Local Epidemiological study (3)Local CMV vs. local plaque • Method • Two plaque measurements with MR imaging in carotid arteries combined with automatic plaque quantification and localisation • Image local CMV presence • Computerised alignment of plaque and CMV images • Population: a random selection • Determine number of necessary subjects from estimation of the probability to find CMV in plaque and to findplaque • Number of patients will be lower • Determine: • Plaque growth (plaque) at a large number of locations • The presence of the virus at the same locations • Regression : plaque ~ CMV

43. Summary and execution plan Hypothesis : CMV influences plaque formation Molecular study design Molecular study More founded hypothesis Epidemiological study design Epidemiological study ? Improved diagnosis New therapy Results

44. Team Pathway Interactions Literature Biological understanding Microarray data Imaging techniques Epidemiology Algorithms Task distribution Medical importance

45. What we learnt ! Building the monastery of Les Avellanes, every family marked the stones because they were afraid that someone could steal them. We come also from different scientific families but respected the different point of views. We synergically built our cathedral project!

46. Thank You Merci Gràcies Gracias Grazie Dank u Eskerrik asko

47. CMV-Atherosclerosis from a medicinal chemistry point of view: rational multitarget polypharmacy STATINS HMG-CoA Reductase inihibition Anti-inflammatoty effects: Lipid alteration: Cholesterol-lowering properties No prenylated proteins to activate NF-kB. NF-kB is implicated in viral replication, inflammation, apoptosis and autoimmune disease.

48. CMV-Atherosclerosis from a medicinal chemistry point of view: rational multitarget polypharmacy LXRα and PPARα agonist Lipid alteration: • LXRα agonists: • decrease circulating LDL • issue cholesterol • increase HDL • but • hypertriglyceridemia • PPARα agonists: • activates β-oxidation in the liver • increase HDL cholesterol Anti-inflammatory effect: PPARα agonists inhibit iNOS expression. NO is an inflammatory target.