Dr. Leroy Hood Lecuture on P4 Medicine


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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

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Dr. Leroy Hood Lecuture on P4 Medicine

  1. 1. Systems Biology and Systems Medicine: Catalyzing a Revolution from Reactive to Proactive (P4) MedicinePredictive, Personalized, Preventive and Participatory<br />Lee Hood<br />Institute for Systems Biology, Seattle<br />
  2. 2. I Participated in Four Paradigm Changes in Biology Leading to P4 Medicine<br />Bringing engineering to biology (high throughput biology)<br />The human genome project <br />Cross-disciplinary biology<br />Systems biology<br />Predictive, Preventive, Personalized, and Participatory medicine (P4 Medicine)<br />Each fundamentally changed how we think about biology and medicine.<br />Each was met initially with enormous skepticism.<br />Each new idea needed new organizational structure.<br />
  3. 3. Contemporary Systems Biology is Predicated on Viewing Biology is an Informational Science<br />
  4. 4. There are Two Types of Biological Information that <br />Can Lead to Disease<br />Thedigital informationof the genome<br /><ul><li>The environmental information that impinges upon and modifies the digital information </li></li></ul><li>Two General Biological Structures that Handle Information<br />Biological networks capture, transmit, process and pass on information<br /><ul><li>Simple and complex molecular machines execute biological functions</li></li></ul><li>Left Index Fingerprints from Identical Twins<br />
  5. 5. ISB’s View of Systems Biology<br />
  6. 6. Agenda: Use biology to drive technology and computation. Need to create a cross-disciplinary culture.<br />Biological Information<br />BIOLOGY<br />Cross-Disciplinary<br />Culture <br />Team Science<br /><ul><li>Biology
  7. 7. Chemistry
  8. 8. Computer Science
  9. 9. Engineering
  10. 10. Mathematics
  11. 11. Physics</li></ul>TECHNOLOGY<br />COMPUTATION<br />
  12. 12. Essentials of Systems Biology<br />Hypothesis-driven<br />Global data acquisition<br />Integrate different types of data<br />Delineate biological network dynamics<br />Formulate models that are predictive and actionable.<br />
  13. 13. A Systems View of Disease<br />
  14. 14. dynamics of<br />pathophysiology<br />diagnosis<br />therapy<br />prevention<br />A Systems View of Medicine Postulates that Disease Arises from Disease- <br />Perturbed Networks<br />Non-Diseased<br />Diseased<br />
  15. 15. A Systems Approach to Prion Disease in Mice<br />
  16. 16. Prion disease example:Prion Protein Exists in Two Forms<br />PrP Genetic Mutations<br />PrPSc Infections<br />Spontaneous conversion<br />Cellular PrPC<br />Infectious PrPSc<br />
  17. 17. Global TranscriptomeAnalysis—Differentially Expressed Genes (DEGs)<br />Time-course array analysis:<br />subtrative analyses to DEGs<br /><ul><li>C57BL/6J-RML: 12 time points
  18. 18. FVB/NCr-RML: 11 time points
  19. 19. BL6.I-301V: 9 time points
  20. 20. FVB/B4053-RML: 8 time points</li></ul>Inoculate w/ Prions<br />Prion strains:<br /><ul><li> RML
  21. 21. 301V </li></ul>Mouse strains:<br /><ul><li> C57BL/6J
  22. 22. FVB/NCr
  23. 23. BL6.I
  24. 24. FVB/B4053 </li></ul>Prion infected brain <br />RNA<br />from brain<br />homogenate<br />Almost 50 million<br />Data points<br />Mouse Genome array:<br />45,000 probe sets<br /> ~22,000 mouse genes.<br />Uninfected brain<br />Carlson lab<br />Inyoul Lee (Brianne Ogata, David Baxter)<br />Bruz Marzolf (Microarray Facility)<br />
  25. 25. Prion Disease in Eight Mouse Strains: dealing with the signal to noise challenge<br />employing subtractive biology<br />Differentially Expressed Genes--DEGs--7400 to 333<br />
  26. 26. Neuropathology Identifies 4 Networks<br />Microglia / Astrocyte<br />activation<br />PrP accumulation<br />Synaptic Degeneration<br />Nerve cell death<br />Infected<br />Normal<br />
  27. 27. Integration of Six Data Types for Prion Disease Studies in Mice<br />Deep brain transcriptome analyses at 10 time points across disease onset in 8 mouse strains<br />Correlate with protein interaction data from known (histopathology) disease-perturbed networks<br />Correlation with dynamical histopathologicalstudies<br />Correlation with clinical signs<br />Distribution of infectious prion protein in the brains across disease progression<br />Brain-specific blood protein concentration changes<br />
  28. 28. Dynamics of Prion Accumulation Network in the Brain: 6 weeks, 10 weeks and 20 weeks of 22 week course<br />
  29. 29. PrP accumulation and replication network—6 weeks<br />
  30. 30. PrP accumulation and replication network—10 weeks<br />
  31. 31. PrP accumulation and replication network—20 weeks<br />
  32. 32. Sequential Disease-Perturbation of the Four Networks of Prion Disease<br />18~20 wk<br />22 wk<br />0 wk<br />Clinical Signs<br />Prion<br />accumulation<br />Glial<br />Activation<br />SynapticDegeneration<br />Neuronal <br />Cell Death<br />Na+<br />channels<br />Reactive<br />Astrocytes<br />Cholesterol<br />transport<br />Caspases<br />Sphingolipid<br />synthesis<br />Cargo<br />transport<br />Leukocyte<br />extravasation<br />Lysosome<br />proteolysis<br />*Arachidonate<br />metab./Ca+ sig.<br />
  33. 33. 333 DEGs encode core prion disease<br />231/333 DEGs encode known disease pathogenic networks<br />102/333 DEGs encode novel pathogenic networks--the dark genes of prion disease<br />Disease-perturbed networks sequentially activated<br />Re-engineer disease-perturbed networks with drugs—new approach to drug target discovery<br />Implications for systems diagnostics<br />DEGs Encoding Known and Novel Prion Disease Phenotypes<br />
  34. 34. A Systems Approach to Blood Diagnostics<br />
  35. 35. Organ-Specific Blood FingerprintsMaking Blood A Window Distinguishing Health and Disease<br />Blood Vessel<br />
  36. 36. Organ-specific Protein Blood Fingerprints—Disease Diagnostics<br />Early detection<br />Disease stratification<br />Disease progression<br />Follow therapy<br />Assess reoccurances<br />Integrated Diagnostics—platform company for P4 medicine<br />
  37. 37. Strategies and Technologies: Exploring New Dimensions of Data Space<br />
  38. 38. Whole Genome Sequencing of Families: New Genomic Strategy<br />
  39. 39. Whole Genome Sequencing of Family of Four <br />Unaffected parents<br />Children with craniofacial<br />Malformation (Miller Syndrome) <br />and lung disease (ciliary dyskinesia)<br /><ul><li>Noise reduction power of a family sequence permits:
  40. 40. Identify 70% sequencing errors using principles of Mendelian genetics — ~1/100,000 error rate
  41. 41. Discovery of ~230,000 novel (rare) SNPs—4.2 million SNPs in family
  42. 42. Reduced disease gene candidates to 4 </li></li></ul><li>Microfluidic Protein Chip:Assay 2500 Organ-Specific Blood Proteinsfrom Millions of Patients Using a Drop of Blood<br />Jim Heath--Caltech<br />
  43. 43. DEAL for In vitro molecular diagnostics:<br />Integrated nanotech/microfluidics platform<br />300 nanoliters of plasma<br />cells out<br />Assay region<br />Organ 1<br />Organ 2<br />Tox response<br />inflammation<br />Dynamic range—106<br />Sensitivity--high atmole<br />5 minute measurement<br />Jim Heath, et al<br />
  44. 44. Patient Assays that Explore New Dimensions of Data Space<br />
  45. 45. Individual Patient Information-Based Assays of the Present/ Future (I)<br />Genomics<br />Complete individual genome sequences—predictive health history—will be done sequencing families<br />Complete individual cell genome sequences—cancer.<br />Complete MHC chromosomal sequence in families—autoimmune disease and allegies<br />200 Actionable single-nucleotide polymorphisms (SNPs)—pharmacogenetics-related and disease-related genes<br />Sequence 1000 transcriptomessimultaneously in one DNA sequencing run from single cancer cells to identify quantized cells states and dissect cancer<br />Analyze aging transcriptome profiles<br />Proteomics<br />2500 blood organ-specific blood proteins from 300 nanoliters of blood in 5 minutes—twice per year (50 proteins from 50 organs)—wellness assessment.<br />Array of 13,000 human proteins—against autoimmune or allergic sera--stratify.<br />Single molecule protein analyses—blood organ-specific proteins<br />
  46. 46. Individual Patient Information-Based Assays of the Present/ Future (II)<br />Single cells<br />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. <br />Analyze individual blood macrophages—inflammation, etc.<br />Use molecular-pore technology to separate epithelial cells from blood cells--cancer<br />iPS (stem) cells<br />Analyze individual stem (iPS) cells from each individual differentiated to relevant tissues to get important phenotypic information—molecular, imaging and higher level phenotypic measurements.<br />
  47. 47. 35<br />Predictive, Personalized, Preventive and Participatory (P4) Medicine<br />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<br />
  48. 48. P4 Medicine<br /><ul><li>Predictive:
  49. 49. Probabilistic health history--DNA sequence
  50. 50. Biannual multi-parameter blood protein measurements
  51. 51. In vivo molecular imaging</li></li></ul><li>P4 Medicine<br /><ul><li>Personalized:
  52. 52. Unique individual human genetic variation mandates individual treatment
  53. 53. Patient is his or her own control—longitudinal data
  54. 54. Billions of data points on each individual
  55. 55. 100s millions patients</li></ul> with billions data points<br />
  56. 56. P4 Medicine<br /><ul><li>Preventive:
  57. 57. Design of therapeutic and preventive drugs </li></ul> via systems approaches<br /><ul><li>Systems approaches to vaccines will transform prevention of infectious diseases
  58. 58. Transition to wellness assessment</li></li></ul><li>P4 Medicine<br /><ul><li>Participatory:
  59. 59. Patient understands and participates in medical choices
  60. 60. Physicians trained before P4 will have to understand it
  61. 61. Medical community—interconnected and educated
  62. 62. Create IT for healthcare to handle billions of patients, each with billions of data points</li></li></ul><li>Digitalization of Biology and Medicine Will Transform Medicine<br />Analysis of single molecules, single cells, single organs and single individuals<br />A revolution that will transform medicine even more than digitalization transformed information technologies and communications<br />Digitization of medicine will lead to dramatically lower healthcare costs<br />Single individual<br />Single cell<br />Single molecule<br />
  63. 63. ISB Strategic Partnerships for P4 Medicine<br />
  64. 64. ISB’s Two-Fold Strategy for P4 Medicine and Strategic Partnerships<br />Inventing strategies, technologies and computational tools—ISB/Luxembourg <br />Creating the P4 Medicine Institute to be an innovative advocate in bringing P4 medicine to patients--ISB/OSU<br />
  65. 65. The P4 Medicine Institute (ISB/OSU)<br />Goal is to catalyze the P4 medical transformation of healthcare by:<br /><ul><li>Accelerating translation of systems science to clinical practice
  66. 66. Executing tangible & pragmatic demonstration projects—lung cancer and wellness
  67. 67. Developing public-private industry collaboration
  68. 68. Addressing technical, strategic, operational, policy, economic, & sociologic issues</li></ul>Science & Technology<br />+<br />Policy & Industry<br />
  69. 69. Six Assertions About P4 Medicine<br />P4 medicine is medicine of the present/near future<br />Proactive P4 medicine is revolutionary rather than incremental or evolutionary—medicine is becoming an information science. Generate billions of data points on each individual.<br />P4 medicine will transform the healthcare industry.<br />P4 medicine will be effective and inexpensive.<br />Pilot projects with informational assays in patient groups will be necessary to convince skeptics.<br />The national healthcare debate in the future should be reframed around P4 medicine rather than the old reactive medicine.<br />
  70. 70. Acknowledgements<br />Prion--Institute for Systems Biology<br />Daehee Hwang <br />Inyoul Lee<br />HyuntaeYoo<br />Eugene Yi (proteomics core facility)<br />BruzMarzolf (Affymetrix core facility)<br />Nanotechnology—protein chips, protein-capture agents--Jim Heath, Caltech<br />MRM protein assays—R Moritz, R Aebersold<br />Single-cell analyses—Leslie Chen and QiangTian<br />Luxemburg Strategic Partnership—David Galas, Diane Isonaka, Rudi Balling (Lux)<br />Prion--McLaughlin Research Institute<br />Great Falls, Montana<br />RanjitGiri<br />Douglas Spicer <br />Rajeev Kumar <br />Rose Pitstick<br />Rebecca Young <br />George A. Carlson<br />Family genome project—ISB/UW/Utah/Complete Genomics—David Galas<br />P4MI Institute—Fred Lee, Clay Marsh (OSU)<br />Single protein analysis—Chris Laustead<br />
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