The Foundation of P4 Medicine

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The Foundation of P4 Medicine Keynote Presentation as presented by Leroy Hood, M.D., PhD, at the Ohio State University Personalized Health Care National Conference 2010.

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The Foundation of P4 Medicine

  1. 1. The Foundations of P4 MedicinePredictive, Personalized, Preventive and Participatory<br />Lee Hood<br />Institute for Systems Biology, Seattle<br />
  2. 2. Outline<br />Principles of P4 medicine<br />P4 medicine— and the future<br />Societal implications of P4 medicine<br />ISB strategic partnerships for P4 medicine<br />
  3. 3. The Foundation of P4 Medicine – Four Concepts<br />View medicine as an informational science<br />Systems approaches allow one to understand wellness and disease—holist rather than atomistic<br />Emerging technologies will allow us to explore new dimensions of patient data space<br />Transforming analytic tools will allow us to decipher the billions of data points for the individual--sculpting in exquisite detail wellness and disease<br />
  4. 4. The Foundation of P4 Medicine – Four Concepts<br />View medicine as an informational science<br />Systems approaches allow one to understand wellness and disease—holist rather than atomistic<br />Emerging technologies will allow us to explore new dimensions of patient data space<br />Transforming analytic tools will allow us to decipher the billions of data points for the individual--sculpting in exquisite detail wellness and disease<br />
  5. 5. Humans Phenotypes are Specified by Two Types of Biological Information<br />The digital information of the genome<br /><ul><li>Theenvironmental information that impinges upon and modifies the digital information </li></li></ul><li>Two General Biological Structures Connect the Genotype and Phenotype<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 />
  6. 6. All Hierarchical or MultiscaleLevels of Biological Information—Are Modified by Environmental Signals <br />DNA<br />RNA<br />Protein<br />Protein interactions and biomodules<br />Protein and gene networks<br />Cells<br />Organs<br />Individuals<br />Populations<br />Ecologies<br />
  7. 7. The Foundation of P4 Medicine – Four Concepts<br />View medicine as an informational science<br />Systems approaches allow one to understand wellness and disease—holist rather than atomistic (systems biology and systems medicine<br />Emerging technologies will allow us to explore new dimensions of patient data space<br />Transforming analytic tools will allow us to decipher the billions of data points for the individual--sculpting in exquisite detail wellness and disease<br />
  8. 8. ISB’s View of Systems Biology<br />
  9. 9. Essentials of Systems Biology<br />Hypothesis-driven and hypothesis-generating<br />Data<br />Global data acquisition<br />Integrate multi scale data types<br />Delineate biological network dynamics—temporal and spatial<br />Dealing with biological and technical noise in large data sets<br />Formulate models that are predictive and actionable.<br />Discovery science is key<br />
  10. 10. 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
  11. 11. Chemistry
  12. 12. Computer Science
  13. 13. Engineering
  14. 14. Mathematics
  15. 15. Physics</li></ul>TECHNOLOGY<br />COMPUTATION<br />
  16. 16. Institute for Systems Biology<br />Founded 2000—10th Anniversary<br />ISB has 13 faculty and 300 staff <br />
  17. 17. ISB’s description of systems biology<br /> in 2000 is virtually identical to that of<br /> this National Academy of Sciences <br /> 2010 report entitled the “New Biology”.<br />ISB was the first Systems Biology <br /> organization in 2000—today there are <br /> more than 70 world wide<br />Predicted that systems approaches would<br /> drive medicine of the future<br />
  18. 18. SCImago Institutions Rankings: http://www.scimagoir.com/<br />Inst. Nat. de<br />Physique Nucleaire<br />Sanger<br />SSM Cardinal Glennon<br />Children’s Hospital<br />ISB<br />CSHL<br />International Agency for<br />Research on Cancer<br />Kaiser Permanente<br />Brigham and<br />Women’s Hospital<br />Rockefeller<br />Institut Catala<br />d’Investigacio<br />Quimica <br />MIT<br />Salk<br />WHO<br />Harvard<br />HHMI<br />MSFT<br />FHCRC<br />IBM<br />Parc<br />Mediterrani<br />de la<br />Tecnología<br />Centro de<br />Investigación<br />Príncipe<br />Felipe<br />CNRS<br />Chinese Academy of Science<br />Russian Academy of Sciences<br />National Academy of<br />Sciences of Ukraine<br />Tianjin<br />University<br />Harbin Engineering<br />University<br />Research Institute of<br />Petroleum Processing<br />ISB 1st in US and 3rd in World for Impact of Papers<br />
  19. 19. A Systems View of Disease<br />
  20. 20. dynamics of<br />pathophysiology<br />diagnosis<br />therapy<br />prevention<br />A Systems View of Medicine Postulates that Disease Arises from Disease-Perturbed Networks<br />Non-Diseased<br />Diseased<br />
  21. 21. Neuropathology Identifies 4 Aspects of PrionNeurodegeneration<br />Microglia / Astrocyte<br />activation<br />PrP accumulation<br />Synaptic Degeneration<br />Nerve cell death<br />Infected<br />Normal<br />
  22. 22. Dynamics of a Brain Network in Prion Neurodegenerative Disease in Mice<br />Prion accumulation network<br />
  23. 23. 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 />
  24. 24. DEGs Encoding Known and Novel Prion Disease Phenotypes<br />333 DEGs encode core prion disease<br />231/333 DEGs encode known 4 disease-perturbed networks from histopathology<br />102/333 DEGs encode 6 novel disease-perturbed 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 />Striking implications for blood diagnostics<br />
  25. 25. Dynamics of a Brain Network in PrionNeuroddegenerative Disease in Mice<br />Prion accumulation network<br />
  26. 26. Making Blood A Window Distinguishing Health and DiseaseOrgan-specific Blood Proteins<br />110 brain-specific blood proteins/80 liver-specific blood proteins<br />Blood Vessel<br />
  27. 27. Why Systems-Driven Blood Diagnostics Will Be the Key to P4 Medicine<br />Early detection<br />Disease stratification<br />Disease progression<br />Assess prognosis<br />Follow therapy<br />Assess reoccurances<br />
  28. 28. The Foundation of P4 Medicine – Four Concepts<br />View medicine as an informational science<br />Systems approaches allow one to understand wellness and disease—holist rather than atomistic<br />Emerging technologies will allow us to explore new dimensions of patient data space<br />Transforming analytic tools will allow us to decipher the billions of data points for the individual--sculpting in exquisite detail wellness and disease<br />
  29. 29. ISB’s Technology-Driven Big Biology Projects<br />
  30. 30. Four ISB Technology-Driven New Big Projects<br />The Human Proteome Project—SRM mass spectrometry assays for all human proteins<br />Clinical assays for patients that allow new dimensions of data space to be explored<br />Complete genome sequencing of families—sequences and new stratifications to identify disease genes—1000s individuals<br />The 2nd Human Genome Project—mining all complete human genomes and their phenotypic/clinical data<br />
  31. 31. Whole Genome Sequencing of Families: New Genomic Strategy<br />Sequencing by Complete Genomics, Inc.<br />
  32. 32. Whole Genome Sequencing of Family of Four <br />Unaffected parents<br />Children each with 2 diseases--craniofacial<br /> malformation (Miller Syndrome) <br />and lung disease (ciliarydyskinesia)<br />Identify 70% of sequence errors using principles of Mendelian genetics<br /> —less than 1/100,000 error rate<br />Discovery of about 230,000 rare variants in family—confirmed by identification<br /> in two or more family members<br />
  33. 33. Recominational Genome Map from Miller’s Syndrome Children:<br />65% of recombinational events fall in hot spots<br />Both children inherited the same allele from both parents<br />Each child inherited a different allele from each parent<br />Children inherited the same allele from dad, different alleles from mom<br />Children inherited the same allele from mom, different alleles from dad<br />x<br />x<br />x<br />65 crossovers in (2) male meioses (left)<br />104 crossovers in (2) female meioses (right)<br />250<br />200<br />More than 65% crossovers<br />In hot spots of recombination<br />150<br />100<br />50<br />0<br />X<br />1<br />2<br />3<br />4<br />5<br />6<br />7<br />8<br />9<br />10<br />11<br />12<br />13<br />14<br />15<br />16<br />17<br />18<br />19<br />20<br />21<br />22<br />
  34. 34. Inter-generational base-change mutations<br /><ul><li>“Genetic errors”: Genetically impossible SNPs in kids will most likely be sequencing errors, but some (perhaps ~1/1000) will be new mutations. We can find these!
  35. 35. New mutations, germline nucleotide substitutions, have never been directly measured before.
  36. 36. Low error rate & family makes this approach work
  37. 37. We trapped by Agilent hybridization selection and resequenced ~60,000 sites
  38. 38. Indirect, phylogenetic estimate is between 8 x 10-9 &2.1 x 10-8 per base per generation,
  39. 39. The intergenerational mutation rate of the autosome is
  40. 40. ~1.1 x 10-8 /bases/generation—70 mutations/ individual/generation</li></li></ul><li>106<br />Simple recessive<br />(SNPs)<br />all SNPs<br />105<br />exonic<br />104<br />rare<br />103<br />rare, exonic<br />102<br />10<br />rare, deleterious<br />1<br />104<br />Compound<br />heterozygous<br />(genes)<br />exonic<br />rare<br />103<br />Number of Genes<br />rare, exonic<br />102<br />rare, deleterious<br />10<br />1<br />Disease Gene Candidates Reduced to 4 Analyzing Complete Family <br />
  41. 41. 1<br />2<br />3<br />4<br />5<br />6<br />7<br />8<br />9<br />10<br />11<br />12<br />13<br />14<br />15<br />16<br />17<br />18<br />19<br />20<br />21<br />22<br />X<br />ZNF721<br />DNAH5<br />KIAA0556<br />DHODH<br />Miller’s gene<br />Ciliarydyskenesis gene<br />centromere<br />paternal recombination<br />heterochromatin<br />identical<br />error region<br />maternal recombination<br />CNV<br />haploidentical paternal<br />candidate gene<br />
  42. 42. Family Genome Sequencing May Facilitate Finding<br />Mendeliandisease genes<br />Modifiers of disease genes--sequencing genomes of 65 Huntington’s patients from families<br />Genes encoding complex genetic diseases after proper patient stratification—Alzheimer’s/Parkinson’s diseases<br />
  43. 43. The Human Proteome Project<br />Strategic partners: ISB (R. Moritz)/ETH (R. Aebersold)/Agilent/AB-Sciex/Origene<br />
  44. 44. ISB has made 4 fundamental contributions to the human proteome project<br />
  45. 45. 1. Trans Proteomic Pipeline (TPP) components<br />* Commercial software not part of TPP<br />
  46. 46. Drives tool development and optimization<br />Advanced, uniform processing of all data<br />2. TPP: Foundation for PeptideAtlas<br />
  47. 47. 3. Targeted Proteomics: Human SRMAtlas<br />SRM <br />assays for most of the known 20,333 <br />human proteins<br />39<br />
  48. 48. ISB Contributions to the Human Proteome Project<br />Trans Proteomic Pipeline—quality assessment/validation<br />Protein Atlas—large-scale MS database<br />Pioneered SRM/MRM mass spectrometry applications—a targeted approach to protein assays<br />4. First preliminary SRM assays (map) of all 20,333 human proteins<br />
  49. 49. Proposal for a Human Proteome Project<br />Create validated targeted assays (SRM) for each human protein<br />Do the same for carefully selected model organisms (mouse, rat, fly, nematode, etc.)<br />Develop diverse technologies to increase the power of proteome analyses—MS, protein chips, novel protein capture agents, imaging, single protein molecule analyses, etc.<br />Develop the computational and mathematical tools necessary for proteome analyses<br />Develop the software to make all proteins in their biologically relevant clusters--biological networks/molecular machines--accessible to all biologists<br />With appropriate time lines build in specific aims to include the many other dimensions of proteomics (7-10 yr project)<br />
  50. 50. Microfluidic Protein Chip:Assay 2500 Organ-Specific Blood Proteinsfrom Millions of Patients Using just a Drop of Blood—Follow Health Longitudinally and Detect Transitions to Disease<br />Jim Heath--Caltech<br />
  51. 51. DEAL for In vitro molecular diagnostics:<br />Integrated nanotech/microfluidics platform<br />300 nanoliters of plasma<br />cells out<br />Assay region<br />5 minute measurement<br />Jim Heath, et al<br />
  52. 52. Peptide Protein-Capture AgentsJim Heath--Caltech<br />Jim Heath--Caltech<br />
  53. 53. Antibody Displacement Technology—Heath--Caltech<br />An example of a triligand PCC agent for bovine carbonic anhydrase II <br />Protein Catalyzed Capture Agents:<br />triligands determined by repeated screening of target protein across synthetic bead-bound peptide libraries<br />anchor peptide is selected on the first screen<br />protein catalyzes the formation of second ligand to anchor ligand on second screen<br />protein catalyzes the formation of the third ligand to the anchor and second ligand on third screen<br />high affinity, stable and easily manufactured triligand capture agents<br />confidential<br />45<br />Jim Health et. al., <br />
  54. 54. Single-Cell Analysis<br />
  55. 55. Quantitative transcriptome clustering of single cells from the human glioblastoma cell line U87<br />CD markers let us sort into 3 quantized cell populations<br />
  56. 56. Technologies for Exploring New Dimensions of Patient Data Space<br />
  57. 57. 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 SNPs—pharmacogenetics-related and disease-related genes<br />Sequence 1000 transcriptomes—tissues and single cells—stratification disease<br />Analyze aging transcriptome profiles—tissues and single cells—wellness<br />Analyze miRNA profiles—tissues, single cells and blood—disease diagnosis<br />Proteomics<br />Organ-specific blood MRM protein assays—110 brain, 80 liver and 20 lung<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 />New protein capture agents.<br />Array of 13,000 human proteins—against autoimmune or allergic sera--stratify.<br />Single molecule protein analyses—blood organ-specific proteins and single cell analyses<br />
  58. 58. Individual Patient Information-Based Assays of the Present/ Future (II)<br />Single cells<br />Analyze10,000 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 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 />
  59. 59. Induced Pluripotent Stem Cells (iPS Cells)<br />
  60. 60. Stratification of Complex Genetic Diseases—e.g.Alzheimer’s Disease<br />Collect families of patients with the relevant disease (families will stratify disease to certain extent)<br />Create iPScells from each individual in families<br />Differentiate iPS cells to neuronsin test tubes<br />Probeindividual neurons with single cell transcriptomeanalyses to identify the degree of heterogeneity and neuron types—quantification of cell types--cell sorting if necessary<br />Probethese neurons (individually or as cell-sorted classes) with ligands, drugs and relevant RNAi’s and analyzetheir transcriptome, miRNAome and selected proteomes—this will stratify different combinations of disease-perturbed (or potentially disease-perturbed) networks<br />Sequence family genomes in keeping with their initial stratification types for error corrections<br />Global comparisons of data across and within families of the molecular data—for final disease stratification<br />
  61. 61. The Foundation of P4 Medicine – Four Concepts<br />View medicine as an informational science<br />Systems approaches allow one to understand wellness and disease—holist rather than atomistic<br />Emerging technologies will allow us to explore new dimensions of patient data space<br />Transforming analytic tools will allow us to decipher the billions of data points for the individual sculpting in exquisite detail wellness and disease<br />
  62. 62. Phenome<br />Transcriptome<br />Transactional<br />Epigenome<br />Single Cell<br />iPS Cells<br />Social Media<br />TeleHealth<br />UUAGUG<br />AUGCGUCUAGGCAUGCAUGCC<br />Na143 K 3.7 BP 110/70 HCT32 BUN 12.9 Pulse 110 PLT150 WBC 92<br />110101000101010101101010101001000101101010001<br />110101000101010101101010101001000101101010001<br />110101000101010101101010101001000101101010001<br />110101000101010101101010101001000101101010001<br />110101000101010101101010101001000101101010001<br />110101000101010101101010101001000101101010001<br />Genome<br />GCGTAG<br />ATGCGTAGGCATGCATGCCATTATAGCTTCCA<br />Proteome<br />arg-his-pro-gly-leu-ser-thr-ala-trp-tyr-val-met-phe-asp-cys<br />Billions of Data Points Are Emerging Around Each Individual<br />
  63. 63. The Foundation of P4 Medicine – Four Concepts<br />View medicine as an informational science<br />Systems approaches allow one to understand wellness and disease—holist rather than atomistic<br />Emerging technologies will allow us to explore new dimensions of patient data space<br />Transforming analytic tools will allow us to decipher the billions of data points for the individual--sculpting in exquisite detail wellness and disease<br />
  64. 64. 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 />56<br />
  65. 65. P4 medicine—the future<br />
  66. 66. P4 Medicine<br /><ul><li>Predictive:
  67. 67. Probabilistic health history--DNA sequence
  68. 68. Biannual multi-parameter blood protein measurements
  69. 69. In vivo molecular imaging</li></li></ul><li>P4 Medicine<br /><ul><li>Personalized:
  70. 70. Unique individual human genetic variation mandates individual treatment
  71. 71. Patient is his or her own control—longitudinal data
  72. 72. Billions of data points on each individual
  73. 73. Hundreds of millions of patients with billions of data points</li></li></ul><li>P4 Medicine<br /><ul><li>Preventive:
  74. 74. Design of therapeutic and preventive drugs </li></ul> via systems approaches<br /><ul><li>Systems approaches to vaccines will transform prevention of infectious diseases
  75. 75. Transition to wellness assessment</li></li></ul><li>P4 Medicine<br /><ul><li>Participatory:
  76. 76. Patient understands and participates in medical choices
  77. 77. Physicians trained before P4 will have to understand it
  78. 78. Medical community—interconnected and educated
  79. 79. Create IT for healthcare to handle billions of patients</li></li></ul><li>Two ISB Strategic partnerships for P4 medicine<br />
  80. 80. ISB’s Strategic Partners for P4 Medicine<br />Develop the P4 tools and strategies for patient assays—State of Luxembourg--$100 million over 5 years<br />Bring P4 medicine to patients with the creation of the non-profit P4 Medical Institute (P4MI) in partnership with Ohio State Medical School<br />
  81. 81. The P4 Medicine Institute (http://www.P4MI.org)<br />Non-profit 501c3--ISB and Ohio State founding members<br />Vision--identify, recruit and integrate strategic partners to bring P4 medicine to patients<br />Convince a skeptical medical community through promotion two Ohio pilot projects (and others)—wellness and lung cancer—exhibit success and power of P4 medicine<br />Seek academic and industrial partners who share the P4 vision and have complementary skills/resources<br />Bringing on consultants to analyze the societal challenges of P4 medicine—ethics, security, confidentiality, policy, regulation, economics, etc.<br />
  82. 82. 9 Dimensions of P4 Medicine (I)<br />P4 medicine is medicine of the present/near future.<br />P4 medicine is revolutionaryrather than evolutionary or incremental<br />P4 medicine is drivenbysystems approaches to disease and emerging technologies<br />P4 medicine will use measurements to quantify wellness and its transition into disease<br />P4 medicine sees the patient (consumer) as the central focus of healthcare<br />
  83. 83. 9 Dimensions of P4 Medicine (II)<br />Pilot projects with informational assays in patient groups will be necessary to convince skeptics.<br />P4 medicine will restructure the business plans of every sector of the healthcare industry—enormous economic opportunities<br />P4 medicine will be effective and inexpensive—readily available to poor and rich.<br />The national healthcare debate in the future should be reframed around P4 medicine rather than the old reactive medicine.<br />
  84. 84. Conceptual Themes of P4 Medicine<br />Disease Demystified<br />Wellness Quantified<br />P4 Medicine<br />Predictive<br />Preventive<br />Personalized<br />Participatory<br />
  85. 85. The Grand Challenge of the 21st Century in Science and Technology Is Complexity<br />New concepts, strategies and technologies permit biologists to successfully begin to attack biological and medical complexity<br />View biology as an informational science<br />Systems approaches permit one to attack complexity effectively<br />Evolving current and emerging technologies permit the exploration of new areas of data space (and improve the old) <br />Computation and mathematical tools permit one to acquire, store, transmit, integrate, mine and create predictive models.<br />These approaches will allow us to effectively attack some of society’s most vexing challenges—healthcare (P4 medicine), global health, environment, energy, nutrition, agriculture, etc.<br />
  86. 86. Acknowledgements<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, Mauricio Flories, Clay Marsh (OSU)<br />Single protein analysis—Chris Laustead<br />Brain imaging—Nathan Price (UI)UI)<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 />SRM protein assays and Human Proteome—R Moritz, R Aebersold, <br />OriGene and Agilent<br />Single-cell analyses—Leslie Chen and QiangTian<br />Luxemburg Strategic Partnership—David Galas, Diane Isonaka, Rudi Balling (Lux)<br />

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