Dr. Leroy Hood lectured to a group of Ohio State University College of Medicine students and faculty on May 13, 2010 in advance of an announcement of a partnership between the Ohio State University Medical Center and the Institute for Systems Biology. The partnership will be known as

1. Systems Biology and Systems Medicine: Catalyzing a Revolution from Reactive to Proactive (P4) MedicinePredictive, Personalized, Preventive and Participatory Lee Hood Institute for Systems Biology, Seattle

2. I Participated in Four Paradigm Changes in Biology Leading to P4 Medicine Bringing engineering to biology (high throughput biology) The human genome project Cross-disciplinary biology Systems biology Predictive, Preventive, Personalized, and Participatory medicine (P4 Medicine) Each fundamentally changed how we think about biology and medicine. Each was met initially with enormous skepticism. Each new idea needed new organizational structure.

3. Contemporary Systems Biology is Predicated on Viewing Biology is an Informational Science

5. ISB’s View of Systems Biology

7. Chemistry

8. Computer Science

9. Engineering

10. Mathematics

11. PhysicsTECHNOLOGY COMPUTATION

12. Essentials of Systems Biology Hypothesis-driven Global data acquisition Integrate different types of data Delineate biological network dynamics Formulate models that are predictive and actionable.

13. A Systems View of Disease

14. dynamics of pathophysiology diagnosis therapy prevention A Systems View of Medicine Postulates that Disease Arises from Disease- Perturbed Networks Non-Diseased Diseased

15. A Systems Approach to Prion Disease in Mice

16. Prion disease example:Prion Protein Exists in Two Forms PrP Genetic Mutations PrPSc Infections Spontaneous conversion Cellular PrPC Infectious PrPSc

18. FVB/NCr-RML: 11 time points

19. BL6.I-301V: 9 time points

22. FVB/NCr

23. BL6.I

24. FVB/B4053 Prion infected brain RNA from brain homogenate Almost 50 million Data points Mouse Genome array: 45,000 probe sets ~22,000 mouse genes. Uninfected brain Carlson lab Inyoul Lee (Brianne Ogata, David Baxter) Bruz Marzolf (Microarray Facility)

25. Prion Disease in Eight Mouse Strains: dealing with the signal to noise challenge employing subtractive biology Differentially Expressed Genes--DEGs--7400 to 333

26. Neuropathology Identifies 4 Networks Microglia / Astrocyte activation PrP accumulation Synaptic Degeneration Nerve cell death Infected Normal

27. Integration of Six Data Types for Prion Disease Studies in Mice Deep brain transcriptome analyses at 10 time points across disease onset in 8 mouse strains Correlate with protein interaction data from known (histopathology) disease-perturbed networks Correlation with dynamical histopathologicalstudies Correlation with clinical signs Distribution of infectious prion protein in the brains across disease progression Brain-specific blood protein concentration changes

28. Dynamics of Prion Accumulation Network in the Brain: 6 weeks, 10 weeks and 20 weeks of 22 week course

29. PrP accumulation and replication network—6 weeks

30. PrP accumulation and replication network—10 weeks

31. PrP accumulation and replication network—20 weeks

32. Sequential Disease-Perturbation of the Four Networks of Prion Disease 18~20 wk 22 wk 0 wk Clinical Signs Prion accumulation Glial Activation SynapticDegeneration Neuronal Cell Death Na+ channels Reactive Astrocytes Cholesterol transport Caspases Sphingolipid synthesis Cargo transport Leukocyte extravasation Lysosome proteolysis *Arachidonate metab./Ca+ sig.

33. 333 DEGs encode core prion disease 231/333 DEGs encode known disease pathogenic networks 102/333 DEGs encode novel pathogenic networks--the dark genes of prion disease Disease-perturbed networks sequentially activated Re-engineer disease-perturbed networks with drugs—new approach to drug target discovery Implications for systems diagnostics DEGs Encoding Known and Novel Prion Disease Phenotypes

34. A Systems Approach to Blood Diagnostics

35. Organ-Specific Blood FingerprintsMaking Blood A Window Distinguishing Health and Disease Blood Vessel

36. Organ-specific Protein Blood Fingerprints—Disease Diagnostics Early detection Disease stratification Disease progression Follow therapy Assess reoccurances Integrated Diagnostics—platform company for P4 medicine

37. Strategies and Technologies: Exploring New Dimensions of Data Space

38. Whole Genome Sequencing of Families: New Genomic Strategy

40. Identify 70% sequencing errors using principles of Mendelian genetics — ~1/100,000 error rate

41. Discovery of ~230,000 novel (rare) SNPs—4.2 million SNPs in family

43. DEAL for In vitro molecular diagnostics: Integrated nanotech/microfluidics platform 300 nanoliters of plasma cells out Assay region Organ 1 Organ 2 Tox response inflammation Dynamic range—106 Sensitivity--high atmole 5 minute measurement Jim Heath, et al

44. Patient Assays that Explore New Dimensions of Data Space

45. Individual Patient Information-Based Assays of the Present/ Future (I) Genomics Complete individual genome sequences—predictive health history—will be done sequencing families Complete individual cell genome sequences—cancer. Complete MHC chromosomal sequence in families—autoimmune disease and allegies 200 Actionable single-nucleotide polymorphisms (SNPs)—pharmacogenetics-related and disease-related genes Sequence 1000 transcriptomessimultaneously in one DNA sequencing run from single cancer cells to identify quantized cells states and dissect cancer Analyze aging transcriptome profiles Proteomics 2500 blood organ-specific blood proteins from 300 nanoliters of blood in 5 minutes—twice per year (50 proteins from 50 organs)—wellness assessment. Array of 13,000 human proteins—against autoimmune or allergic sera--stratify. Single molecule protein analyses—blood organ-specific proteins

46. Individual Patient Information-Based Assays of the Present/ Future (II) Single cells Analyze 10,000 B cells and 10,000 T cells for the functional regions of their immune receptors—past and present immune responsiveness—follow vaccinations—identify autoimmune antibodies. Analyze individual blood macrophages—inflammation, etc. Use molecular-pore technology to separate epithelial cells from blood cells--cancer iPS (stem) cells Analyze individual stem (iPS) cells from each individual differentiated to relevant tissues to get important phenotypic information—molecular, imaging and higher level phenotypic measurements.

47. 35 Predictive, Personalized, Preventive and Participatory (P4) Medicine Driven by systems approaches to disease, new measurement (nanotechnology) and visualization technologies and powerful new computational tools, P4 medicine will emerge over the next 10-20 years

49. Probabilistic health history--DNA sequence

50. Biannual multi-parameter blood protein measurements

52. Unique individual human genetic variation mandates individual treatment

53. Patient is his or her own control—longitudinal data

54. Billions of data points on each individual

55. 100s millions patients with billions data points

59. Patient understands and participates in medical choices

60. Physicians trained before P4 will have to understand it

61. Medical community—interconnected and educated

63. ISB Strategic Partnerships for P4 Medicine

64. ISB’s Two-Fold Strategy for P4 Medicine and Strategic Partnerships Inventing strategies, technologies and computational tools—ISB/Luxembourg Creating the P4 Medicine Institute to be an innovative advocate in bringing P4 medicine to patients--ISB/OSU

66. Executing tangible & pragmatic demonstration projects—lung cancer and wellness

67. Developing public-private industry collaboration

68. Addressing technical, strategic, operational, policy, economic, & sociologic issuesScience & Technology + Policy & Industry

69. Six Assertions About P4 Medicine P4 medicine is medicine of the present/near future Proactive P4 medicine is revolutionary rather than incremental or evolutionary—medicine is becoming an information science. Generate billions of data points on each individual. P4 medicine will transform the healthcare industry. P4 medicine will be effective and inexpensive. Pilot projects with informational assays in patient groups will be necessary to convince skeptics. The national healthcare debate in the future should be reframed around P4 medicine rather than the old reactive medicine.

70. Acknowledgements Prion--Institute for Systems Biology Daehee Hwang Inyoul Lee HyuntaeYoo Eugene Yi (proteomics core facility) BruzMarzolf (Affymetrix core facility) Nanotechnology—protein chips, protein-capture agents--Jim Heath, Caltech MRM protein assays—R Moritz, R Aebersold Single-cell analyses—Leslie Chen and QiangTian Luxemburg Strategic Partnership—David Galas, Diane Isonaka, Rudi Balling (Lux) Prion--McLaughlin Research Institute Great Falls, Montana RanjitGiri Douglas Spicer Rajeev Kumar Rose Pitstick Rebecca Young George A. Carlson Family genome project—ISB/UW/Utah/Complete Genomics—David Galas P4MI Institute—Fred Lee, Clay Marsh (OSU) Single protein analysis—Chris Laustead