Bioinformatics:  Definitions,   Challenges and Impact on Health Care Systems Daniel Masys, M.D. Professor and Chair Depart...
Topics <ul><li>What is Bioinformatics? </li></ul><ul><li>Health Informatics compared to Bioinformatics </li></ul><ul><li>S...
Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Transcription Translation Replication Post Translat...
What is Bioinformatics? Definitions…
NIH Working Definition <ul><li>Bioinformatics :  Research, development, or application of computational tools and approach...
Another… NCBI  (National Center for Biotechnology Information <ul><li>Bioinformatics  is the field of science in which bio...
Bioinformatics & Health Informatics <ul><li>Bioinformatics is the study of the flow of information in biological sciences....
Different Areas of Strength <ul><li>Bioinformatics </li></ul><ul><ul><li>Much more data available on the Internet than Hea...
Scope of Bioinformatics OMES and OMICS
Omes and Omics <ul><li>Genomics </li></ul><ul><ul><li>Primarily sequences (DNA and RNA) </li></ul></ul><ul><ul><li>Databan...
Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Structural Genomics Functional Genomics (Transcript...
Genome and Genomics <ul><li>Genome – entire complement of DNA in a species </li></ul><ul><ul><li>Both nuclear and mitochon...
Genome Databases (e.g., GenBank) <ul><li>Consists of  </li></ul><ul><ul><li>long strings of DNA bases – ATCG….. </li></ul>...
Human Genome Project <ul><li>Human Genome Project - International research effort </li></ul><ul><li>Determine sequence of ...
 
The Genome Sequence  is at hand…so? “ The good news is that we have the human genome.  The bad news is it’s just a parts l...
“ The Human Genome Project has catalyzed striking paradigm changes in biology - biology is an information science.” Leroy ...
Genomes In Public Databases <ul><li>Published complete genomes: </li></ul><ul><li>Ongoing prokaryotic genomes: </li></ul><...
Genomics activities  <ul><li>Sequence  the genes and chromosomes – done by breaking the DNA into parts </li></ul><ul><li>M...
Structural genomics vocabulary <ul><li>Homolog </li></ul><ul><ul><li>a gene from one species, for example the mouse, that ...
Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Genomics Transcriptomics Functional Genetics Proteo...
Proteome vs Transcriptome <ul><li>Functional genomics (transcriptomics) looks at the timing and regulation of gene product...
Functional Genomics – Microarrays <ul><li>Transcriptome and transcriptomics </li></ul><ul><li>High throughput technique de...
Functional Genomics Technologies: Slide, Chip and Filter Arrays
How Microarrays Work <ul><li>Conceptual description: </li></ul><ul><ul><li>Set of  targets  (oligonucleotides, cDNA’s, pro...
Schematic of probe preparation, hybridization, scanning and image analysis for slide arrays
Array slides Amino-silane/poly l-lysine coated
Arrayer
 
GeneChip synthesis
Genechip analysis system
Genechip array design
Raw data
Genechip analysis software
Duplicate Experiments Determination of the confidence level between duplicates. 3 fold differences are generally considere...
Experimental Design <ul><li>A fundamental challenge of microarray experiments: underdetermined systems </li></ul>Kohane IS...
Characteristics of Array Data <ul><li>Voluminous – tens of thousands of variables with relatively few observations of each...
 
Uses of Expression Profiling <ul><li>Pharmaceutical research: </li></ul><ul><ul><li>ID drug targets by comparing expressio...
Future Applications <ul><li>Diagnostic tool to screen for infective agents </li></ul><ul><ul><li>Chip imprinted with set o...
Public Microarray Data Repositories <ul><li>Major public repositories: </li></ul><ul><li>GEO (NCBI) </li></ul><ul><ul><li>...
Standards and Repositories <ul><li>Brazma, A, et al. Minimum information about a microarray experiment (MIAME)-toward stan...
Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Tissues Organs Organisms Genomics Transcriptomics F...
Proteome and Proteomics <ul><li>Proteome – the entire set of proteins (and other gene products) made by the genome. </li><...
Protein Functions <ul><li>Catalysis </li></ul><ul><li>Transport </li></ul><ul><li>Nutrition and storage </li></ul><ul><li>...
Protein Databases <ul><li>SwissProt  </li></ul><ul><li>PIR  http://www.pir.uniprot.org/   </li></ul><ul><li>GENE  http://w...
Gene/Protein Database entries <ul><li>HFE record in Entrez GENE (NCBI) </li></ul><ul><li>http://www.ncbi.nlm.nih.gov/entre...
Structure & Function Determination <ul><li>X-ray crystallography </li></ul><ul><li>Nuclear magnetic resonance spectroscopy...
Structure Databases <ul><li>Contain experimentally determined and predicted structures of biological molecules </li></ul><...
Protein Interaction Databases <ul><li>Record observations of protein-protein interactions in cells </li></ul><ul><li>Attem...
Controlled Vocabularies in  Bioinformatics <ul><li>The Gene Ontology  http://www. geneontology .org/ </li></ul><ul><ul><li...
Genomics Data and Patient Care From genotype to phenotype
Human Disease Gene Specifics <ul><li>Genes linked to human diseases  (9-2004) </li></ul><ul><li>+ 425 in 2 yrs </li></ul><...
Informatics Issues related to Genomics Data and Patient Care <ul><li>Linking known data for genes causing human diseases t...
Clinical Bioinformatics: Common Questions <ul><li>What genes cause the condition? </li></ul><ul><li>What are the normal fu...
Answers exist online <ul><li>…  but it is not easy; answers in many places </li></ul><ul><li>Can’t navigate by genes names...
Major Challenges of Navigation <ul><li>Complexity of data </li></ul><ul><li>Dynamic nature of the data </li></ul><ul><li>D...
Genetics Home Reference <ul><li>Consumer health resource to help the public navigate from phenotype to genotype. </li></ul...
Genetics is Impacting Medicine Today <ul><li>1700 genes  & health conditions </li></ul><ul><li>> 1100 gene tests for diagn...
Well-known Examples <ul><li>Pharmacogenetics: </li></ul><ul><ul><li>CYP450 alleles: exaggerated, diminished or ultra-rapid...
Iressa  (gefitinib) <ul><li>Non-small cell lung CA ~ 140,000 pt/yr </li></ul><ul><li>Iressa (Astra Zeneca) causes remissio...
Implications for Health Care System <ul><li>More gene tests will be ordered.  [reports of 300% increase in gene tests in 2...
Unsolved Informatics Issues: What Should Be Stored in the EMR? <ul><li>Complete DNA sequence for specific genes into the E...
Genetic data in electronic medical records <ul><li>Implications for component systems: </li></ul><ul><ul><li>Laboratory </...
Genome Data and Other  Information Systems <ul><li>Genomic information will be pervasive in all healthcare information sys...
Summary <ul><li>Informatics will be the key enabling technology for personalized, genomic medicine. </li></ul><ul><li>Curr...
Optional Exercise: Hands-on with GHR <ul><li>Scavenger hunt with hemochromatosis and the genes that influence it. </li></u...
GHR Scavenger Hunt <ul><li>How common is hemochromatosis? </li></ul><ul><li>How many genes have been proven to be involved...
GHR Scavenger Hunt <ul><li>What are the names of the patient support associations for hemochromatosis? </li></ul><ul><li>O...
GHR Scavenger Hunt <ul><li>For the genes involved in hemochromatosis, how many of them are available as a DNA test? </li><...
GHR Scavenger Hunt <ul><li>How do people inherit hemochromatosis? </li></ul><ul><li>Do the genes involved in hemochromatos...
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  • Principle of high density cDNA microarrays. Easy, Southern technique. 500-500 bp with average around 1000 bp. Requires about 1-3 ug of total RNA per sample. Caveats: Discrimination between closely related family members not too good. 85-85% homology is not discriminated and actually contribute to the signal in an additive fashion. Consequences in analyzing specific phenotypes For example, Bcl-XL and Bcl-Xs have opposing phenotypes in vivo and would not be distinguish by this technology.
  • Add scanned image from Integrative p. 75
  • Photolithochemistry to add 25 mer to a glass surface. Literally millions of oligonucleotide probes per chip
  • Process of genechip assay. cRNA is fragmented prior to be hybridized to the array.
  • The perfect match and mismatch approaches control for non-specific hybridization.
  • What it looks like
  • Oftware to manage the data provide an intensity of fluorescence and a call on the presence, absence or marginal status of a queried gene.
  • Average difference (intensity of fluorescence) was plotted for duplicate experiments. Nearly all genes called present were found to be expressed at the same level in a duplicate experiment. The diagonal across represent a perfect correlation between experiment. The next line up or down represents a 3 fold difference and the next lines a 10 fold difference. The variability was within 3 fold. This was used as our reference for calling a modulation significant.
  • Integrative, pp. 13-15
  • presentation

    1. 1. Bioinformatics: Definitions, Challenges and Impact on Health Care Systems Daniel Masys, M.D. Professor and Chair Department of Biomedical Informatics Vanderbilt University School of Medicine
    2. 2. Topics <ul><li>What is Bioinformatics? </li></ul><ul><li>Health Informatics compared to Bioinformatics </li></ul><ul><li>Scope of Bioinformatics </li></ul><ul><li>Genomics data and patient care </li></ul><ul><li>Impact of Bioinformatics on Health Information Systems </li></ul>
    3. 3. Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Transcription Translation Replication Post Translational Modification
    4. 4. What is Bioinformatics? Definitions…
    5. 5. NIH Working Definition <ul><li>Bioinformatics : Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. </li></ul><ul><li>http://www. bisti . nih . gov / CompuBioDef . pdf </li></ul>
    6. 6. Another… NCBI (National Center for Biotechnology Information <ul><li>Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights and to create a global perspective from which unifying principles in biology can be discerned. </li></ul><ul><li>http://www.ncbi.nlm.nih.gov/About/primer/bioinformatics.html </li></ul>
    7. 7. Bioinformatics & Health Informatics <ul><li>Bioinformatics is the study of the flow of information in biological sciences. </li></ul><ul><li>Health Informatics is the study of the flow of information in patient care. </li></ul><ul><li>These two field are on a collision course as genomics data becomes used in patient care. </li></ul><ul><ul><ul><ul><ul><li>Russ Altman,MD, PhD, Stanford Univ. </li></ul></ul></ul></ul></ul>
    8. 8. Different Areas of Strength <ul><li>Bioinformatics </li></ul><ul><ul><li>Much more data available on the Internet than Health Informatics </li></ul></ul><ul><ul><li>Much more progress on database integration across multiple data sources </li></ul></ul><ul><li>Health (Clinical) Informatics </li></ul><ul><ul><li>Focus on tailoring common functions to local (very complex) healthcare environments </li></ul></ul><ul><ul><li>More need for aggregation of local, regional, national outcomes, statistics, knowledge </li></ul></ul><ul><ul><li>Much more progress on terminologies for integration of data </li></ul></ul>
    9. 9. Scope of Bioinformatics OMES and OMICS
    10. 10. Omes and Omics <ul><li>Genomics </li></ul><ul><ul><li>Primarily sequences (DNA and RNA) </li></ul></ul><ul><ul><li>Databanks and search algorithms </li></ul></ul><ul><ul><li>Supports studies of molecular evolution (“Tree wars”) </li></ul></ul><ul><li>Proteomics </li></ul><ul><ul><li>Sequences (Protein) and structures </li></ul></ul><ul><ul><li>Mass spectrometry, X-ray crystallography </li></ul></ul><ul><ul><li>Databanks, knowledge bases, visualization </li></ul></ul><ul><li>Functional Genomics (transcriptomics) </li></ul><ul><ul><li>Microarray data </li></ul></ul><ul><ul><li>Databanks, analysis tools, controlled terminologies </li></ul></ul><ul><li>Systems Biology (metabolomics) </li></ul><ul><ul><li>Metabolites and interacting systems (interactomics) </li></ul></ul><ul><ul><li>Graphs, visualization, modeling, networks of entities </li></ul></ul>
    11. 11. Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Structural Genomics Functional Genomics (Transcriptomics) Proteomics Phenomics
    12. 12. Genome and Genomics <ul><li>Genome – entire complement of DNA in a species </li></ul><ul><ul><li>Both nuclear and mitochondrial/chloroplast </li></ul></ul><ul><ul><li>Variants among individuals </li></ul></ul><ul><li>Genomics – study of the sequence, structure and function of the genome. Study relationships among sets of genes rather than single genes. </li></ul><ul><li>Comparative genomics – study of the differences among species. Usually covers evolutionary studies of differences & conservation over time. </li></ul>
    13. 13. Genome Databases (e.g., GenBank) <ul><li>Consists of </li></ul><ul><ul><li>long strings of DNA bases – ATCG….. </li></ul></ul><ul><ul><li>Annotations of this database to attach meaning to the sequence data. </li></ul></ul><ul><li>Example entry from GenBank: </li></ul><ul><ul><li>http://www.ncbi.nlm.nih.gov/entrez/viewer.fcgi?val=NM_000410&dopt=gb Hemochromatosis gene HFE </li></ul></ul>
    14. 14. Human Genome Project <ul><li>Human Genome Project - International research effort </li></ul><ul><li>Determine sequence of human genome and other model organisms </li></ul><ul><li>Began 1987, completed 2003 </li></ul><ul><li>Next steps for ~20,000 genes </li></ul><ul><ul><li>Function and regulation of all genes </li></ul></ul><ul><ul><li>Significance of variations between people </li></ul></ul><ul><ul><li>Cures, therapies, “genomic healthcare” </li></ul></ul>
    15. 16. The Genome Sequence is at hand…so? “ The good news is that we have the human genome. The bad news is it’s just a parts list”
    16. 17. “ The Human Genome Project has catalyzed striking paradigm changes in biology - biology is an information science.” Leroy Hood, MD, PhD Institute for Systems Biology Seattle, Washington
    17. 18. Genomes In Public Databases <ul><li>Published complete genomes: </li></ul><ul><li>Ongoing prokaryotic genomes: </li></ul><ul><li>Ongoing eukaryotic genomes: </li></ul>http://www.genomesonline.org/ 2050 72 255 158 12/01 10/02 104 316 218 8/03 156 386 246 6/2006 375 945 730
    18. 19. Genomics activities <ul><li>Sequence the genes and chromosomes – done by breaking the DNA into parts </li></ul><ul><li>Map the location of various gene entities to establish their order </li></ul><ul><li>Compare the sequences with other known sequences to determine similarity </li></ul><ul><ul><li>Across species, conserved sequence “motifs” </li></ul></ul><ul><ul><li>Predict secondary structure of proteins </li></ul></ul><ul><li>Create large databases – GenBank, EMBL, DDBJ </li></ul><ul><li>Develop algorithms and similarity measures </li></ul><ul><ul><li>BLAST and its many forms </li></ul></ul>
    19. 20. Structural genomics vocabulary <ul><li>Homolog </li></ul><ul><ul><li>a gene from one species, for example the mouse, that has a common origin and functions the same as a gene from another species, for example, humans, Drosophila, or yeast </li></ul></ul><ul><li>Orthologs </li></ul><ul><ul><li>genes in different species that evolved from a common ancestral gene by speciation. Normally, orthologs retain the same function in the course of evolution. </li></ul></ul><ul><li>Paralogs </li></ul><ul><ul><li>Genes related by duplication within a genome . Orthologs retain the same function in the course of evolution, whereas paralogs evolve new functions </li></ul></ul>
    20. 21. Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Genomics Transcriptomics Functional Genetics Proteomics
    21. 22. Proteome vs Transcriptome <ul><li>Functional genomics (transcriptomics) looks at the timing and regulation of gene products (mRNA, primarily) </li></ul><ul><li>Proteome is final end-product (set of many or all proteins). </li></ul><ul><li>Relationship between transcriptome and proteome is complex, due to longevity of mRNA signal, subsequent control of translation to protein, and post translational modifications. </li></ul>
    22. 23. Functional Genomics – Microarrays <ul><li>Transcriptome and transcriptomics </li></ul><ul><li>High throughput technique designed to measure the relative abundance of mRNA in a cell or tissue in response to an experiment. </li></ul><ul><li>Also called gene expression analysis </li></ul>
    23. 24. Functional Genomics Technologies: Slide, Chip and Filter Arrays
    24. 25. How Microarrays Work <ul><li>Conceptual description: </li></ul><ul><ul><li>Set of targets (oligonucleotides, cDNA’s, proteins, tissues, etc) are immobilized in predetermined positions on a substrate </li></ul></ul><ul><ul><li>Solution containing tagged molecules capable of binding to the targets is placed over the targets </li></ul></ul><ul><ul><li>Binding occurs between targets and tagged molecules. </li></ul></ul><ul><ul><li>Fluorescent or radiolabel tags allows visualization of targets that have been bound. </li></ul></ul>
    25. 26. Schematic of probe preparation, hybridization, scanning and image analysis for slide arrays
    26. 27. Array slides Amino-silane/poly l-lysine coated
    27. 28. Arrayer
    28. 30. GeneChip synthesis
    29. 31. Genechip analysis system
    30. 32. Genechip array design
    31. 33. Raw data
    32. 34. Genechip analysis software
    33. 35. Duplicate Experiments Determination of the confidence level between duplicates. 3 fold differences are generally considered significant.
    34. 36. Experimental Design <ul><li>A fundamental challenge of microarray experiments: underdetermined systems </li></ul>Kohane IS, Kho AT, Butte AJ. Microarrays for an Integrative Genomics. (The MIT Press; Cambridge, MA; 2003), p. 11.
    35. 37. Characteristics of Array Data <ul><li>Voluminous – tens of thousands of variables with relatively few observations of each (upside down vs. classical biostatistics) </li></ul><ul><li>Noisy – error rates up to 8% </li></ul><ul><li>Methods designed to detect patterns and associations always find patterns and associations </li></ul>
    36. 39. Uses of Expression Profiling <ul><li>Pharmaceutical research: </li></ul><ul><ul><li>ID drug targets by comparing expression profile of drug-treated cells with those of cells containing mutations in genes encoding known drug targets </li></ul></ul><ul><li>Disease Dx and Tx: </li></ul><ul><ul><li>Distinguish morphologically similar cancers </li></ul></ul><ul><ul><ul><li>DLBCL (Poulsen et al (2005) Microarray-based classification of diffuse large B-cell lymphomas European Journal of Haematology 74(6):453-65.)) </li></ul></ul></ul><ul><ul><li>Therapy potential </li></ul></ul><ul><ul><ul><li>Rabson AB, Weissmann D. From microarray to bedside: targeting NF-kappaB for therapy of lymphomas. Clin Cancer Res. 2005 Jan 1;11(1)2-6. </li></ul></ul></ul>
    37. 40. Future Applications <ul><li>Diagnostic tool to screen for infective agents </li></ul><ul><ul><li>Chip imprinted with set of pathogenic genomes used to identify bacterial, viral, or parasite genomic material in patient’s body fluids </li></ul></ul><ul><li>Diagnostic chip to check for mutations involved in drug-gene interactions. </li></ul><ul><ul><li>Roche Amplichip </li></ul></ul>
    38. 41. Public Microarray Data Repositories <ul><li>Major public repositories: </li></ul><ul><li>GEO (NCBI) </li></ul><ul><ul><li>http://www.ncbi.nlm.nih.gov/geo/ </li></ul></ul><ul><li>ArrayExpress (EBI) </li></ul><ul><ul><li>http://www.ebi.ac.uk/arrayexpress/ </li></ul></ul>
    39. 42. Standards and Repositories <ul><li>Brazma, A, et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nature Genetics. 2001 Dec;29(4):373. </li></ul><ul><li>http://www.nature.com/ cgi - taf / DynaPage . taf ?file=/ng/journal/v29/n4/full/ng1201-365.html </li></ul><ul><li>Ball, CA, et al. Submission of Microarray Data to Public Repositories. PLoS Biology . 2004 September; 2 (9): e317 </li></ul><ul><li>http://www. pubmedcentral . nih . gov / articlerender . fcgi ?tool= pubmed & pubmedid =15340489 </li></ul>
    40. 43. Central Dogma of Molecular Biology DNA RNA Protein Phenotype Phenotype Tissues Organs Organisms Genomics Transcriptomics Functional Genetics Proteomics
    41. 44. Proteome and Proteomics <ul><li>Proteome – the entire set of proteins (and other gene products) made by the genome. </li></ul><ul><li>Proteomics – study of the interactions among proteins in the proteome, including networks of interacting proteins and metabolic considerations. Also includes differences in developmental stages, tissues and organs. </li></ul>
    42. 45. Protein Functions <ul><li>Catalysis </li></ul><ul><li>Transport </li></ul><ul><li>Nutrition and storage </li></ul><ul><li>Contraction and mobility </li></ul><ul><li>Structural elements </li></ul><ul><ul><li>Cytoskeleton </li></ul></ul><ul><ul><li>Basement membranes </li></ul></ul><ul><li>Defense mechanisms </li></ul><ul><li>Regulation </li></ul><ul><ul><li>Genetic </li></ul></ul><ul><ul><li>Hormonal </li></ul></ul><ul><li>Buffering capacity </li></ul>
    43. 46. Protein Databases <ul><li>SwissProt </li></ul><ul><li>PIR http://www.pir.uniprot.org/ </li></ul><ul><li>GENE http://www.ncbi.nlm.nih.gov/gene </li></ul><ul><li>InterPro http://www.ebi.ac.uk/interpro/ </li></ul><ul><li>Correspond to (and derived from) Genome data bases </li></ul><ul><li>All connected by Reference Sequences (NCBI) </li></ul>UniProt
    44. 47. Gene/Protein Database entries <ul><li>HFE record in Entrez GENE (NCBI) </li></ul><ul><li>http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?&db=gene&cmd=retrieve&dopt=Graphics&list_uids=3077 </li></ul>
    45. 48. Structure & Function Determination <ul><li>X-ray crystallography </li></ul><ul><li>Nuclear magnetic resonance spectroscopy and tandem MS/MS </li></ul><ul><li>Computational modeling </li></ul><ul><li>Sequence alignment from others </li></ul><ul><li>Homology modeling </li></ul>
    46. 49. Structure Databases <ul><li>Contain experimentally determined and predicted structures of biological molecules </li></ul><ul><li>Most structures determined by X-ray crystallography, NMR </li></ul><ul><li>Example – MMDB molecular modeling db http://www.ncbi.nlm.nih.gov/Structure/MMDB/mmdb.shtml </li></ul><ul><li>HFE Entry </li></ul><ul><ul><li>http://www.ncbi.nlm.nih.gov/Structure/mmdb/mmdbsrv.cgi?form=6&db=t&Dopt=s&uid=9816 </li></ul></ul>
    47. 50. Protein Interaction Databases <ul><li>Record observations of protein-protein interactions in cells </li></ul><ul><li>Attempts to detail interactions observed in thousands of small-scale experiments described in published articles </li></ul><ul><li>Examples: </li></ul><ul><ul><li>BIND: Biomolecular Interaction Network Database </li></ul></ul><ul><ul><li>DIP: Database of Interacting Proteins </li></ul></ul><ul><ul><li>MIPS: Munich Information Center for Protein Sequences </li></ul></ul><ul><ul><li>PRONET: Protein interaction on the Web </li></ul></ul><ul><ul><li>Many others, both academic and commercial </li></ul></ul>
    48. 51. Controlled Vocabularies in Bioinformatics <ul><li>The Gene Ontology http://www. geneontology .org/ </li></ul><ul><ul><li>Knowledge about gene function (the ontology itself) </li></ul></ul><ul><ul><li>Annotation of gene products (for comparisons) </li></ul></ul><ul><li>The MGED Ontology (arising from MIAME) </li></ul><ul><ul><li>http:// mged . sourceforge .net/ </li></ul></ul><ul><ul><li>Annotation of microarray experiments for public repositories </li></ul></ul><ul><li>Clinical Bioinformatics Ontology: </li></ul><ul><ul><li>Annotation of gene tests in electronic medical records </li></ul></ul><ul><ul><li>http://www.cerner.com/cbo </li></ul></ul><ul><li>MIAPE from Proteomics Standards Initiative (PSI) </li></ul><ul><ul><li>Annotation of proteomics experiments for public repositories </li></ul></ul><ul><ul><li>http://psidev.sourceforge.net/ </li></ul></ul>
    49. 52. Genomics Data and Patient Care From genotype to phenotype
    50. 53. Human Disease Gene Specifics <ul><li>Genes linked to human diseases (9-2004) </li></ul><ul><li>+ 425 in 2 yrs </li></ul><ul><li>1700/20,000 = 9% of loci </li></ul>
    51. 54. Informatics Issues related to Genomics Data and Patient Care <ul><li>Linking known data for genes causing human diseases to clinical decision support and EMR documentation </li></ul><ul><li>Representation of genetic data in electronic medical records </li></ul>
    52. 55. Clinical Bioinformatics: Common Questions <ul><li>What genes cause the condition? </li></ul><ul><li>What are the normal function of the gene? </li></ul><ul><li>What mutations have been linked to diseases? </li></ul><ul><li>How does the mutation alter gene function? </li></ul><ul><li>What laboratories are performing DNA tests? </li></ul><ul><li>Are there gene therapies or clinical trials? </li></ul><ul><li>What names are used to refer to the genes and the diseases? </li></ul><ul><li>What other conditions are linked to these same genes? </li></ul>
    53. 56. Answers exist online <ul><li>… but it is not easy; answers in many places </li></ul><ul><li>Can’t navigate by genes names - must use hot links and numeric identifiers </li></ul><ul><li>The number and function of alternate forms of the protein are inconsistently reported </li></ul><ul><li>Synonymy (many names, same meaning) and polysemy (same name, different meanings) cause confusion </li></ul><ul><li>Upper and lower case are used for species distinctions </li></ul>
    54. 57. Major Challenges of Navigation <ul><li>Complexity of data </li></ul><ul><li>Dynamic nature of the data </li></ul><ul><li>Diverse foci and number of data/knowledge base systems </li></ul><ul><li>Data and knowledge representation lack standards </li></ul><ul><li>Can navigate if you know what you are looking for. </li></ul>
    55. 58. Genetics Home Reference <ul><li>Consumer health resource to help the public navigate from phenotype to genotype. </li></ul><ul><li>Focus on health implications of the Human Genome Project. </li></ul><ul><li>http://ghr.nlm.nih.gov </li></ul><ul><li>Mitchell, Fun, McCray, JAMIA, 2004 Nov 11(6):439-437 </li></ul>
    56. 59. Genetics is Impacting Medicine Today <ul><li>1700 genes & health conditions </li></ul><ul><li>> 1100 gene tests for diagnosis </li></ul><ul><li>Relate to diagnosis, therapy, drug dosage, occupational hazards, reproductive plans, health risks, …. </li></ul>
    57. 60. Well-known Examples <ul><li>Pharmacogenetics: </li></ul><ul><ul><li>CYP450 alleles: exaggerated, diminished or ultra-rapid drug responses. E.G., Warfarin. 93% of patients are OK on standard doses. 7% of patients have severe hemorrhage. CYP2C9*2 and CYP2C9*3 most severe of 6 known mutations. </li></ul></ul><ul><li>Environmental susceptibility </li></ul><ul><ul><li>Sickle Cell trait carrier and malaria parasite </li></ul></ul><ul><li>Nutrition </li></ul><ul><ul><li>PKU and avoidance of phenylalanine </li></ul></ul>
    58. 61. Iressa (gefitinib) <ul><li>Non-small cell lung CA ~ 140,000 pt/yr </li></ul><ul><li>Iressa (Astra Zeneca) causes remission in 1 of 10 patients if taken daily for life. </li></ul><ul><li>Iressa efficacy correlates with EGFR mutation in the tumor. Now have gene testing for EGFR so can target appropriate people. http://www.sciencemag.org/cgi/content/full/305/5688/1222a </li></ul><ul><li>BUT – Astra Zeneca can’t make money on only 14,000 per year. </li></ul><ul><li>http://www.ncbi.nlm.nih.gov/entrez/dispomim.cgi?id=131550 </li></ul>
    59. 62. Implications for Health Care System <ul><li>More gene tests will be ordered. [reports of 300% increase in gene tests in 2003.] </li></ul><ul><ul><li>Arch Pathol Lab Med – 2004, 128(12):1330-1333 </li></ul></ul><ul><li>Simultaneous testing will cause the “Incidentalome” – unanticipated findings on screeening genetic tests. </li></ul><ul><ul><li>Kohane , Masys, Altman, RB. The incidentalome : a threat to genomic medicine. JAMA, 296(2), 212-5, 2006. </li></ul></ul><ul><li>Preventive healthcare will play a larger part. </li></ul><ul><li>Environmental risk factors dictate OSHA-type approach to worker empowerment and education about safe behavior </li></ul>
    60. 63. Unsolved Informatics Issues: What Should Be Stored in the EMR? <ul><li>Complete DNA sequence for specific genes into the EMR? Where? </li></ul><ul><li>Meta-data about the DNA sequence? </li></ul><ul><li>If not the sequence (ie., diff from reference sequence), what to do when the reference sequence changes? </li></ul><ul><li>How to trigger alerts and reminders? And for what? </li></ul>
    61. 64. Genetic data in electronic medical records <ul><li>Implications for component systems: </li></ul><ul><ul><li>Laboratory </li></ul></ul><ul><ul><li>Pharmacy </li></ul></ul><ul><ul><li>Computerized order entry </li></ul></ul><ul><ul><li>Documentation and notes </li></ul></ul><ul><li>Knowledge management </li></ul><ul><ul><li>Alerts and reminders </li></ul></ul><ul><ul><li>Finding patients matching profiles </li></ul></ul><ul><ul><li>Practice guidelines and clinical trials </li></ul></ul>
    62. 65. Genome Data and Other Information Systems <ul><li>Genomic information will be pervasive in all healthcare information systems. </li></ul><ul><li>Also in public health systems </li></ul><ul><ul><li>Newborn screening </li></ul></ul><ul><ul><li>Tissue and organ banks </li></ul></ul><ul><ul><li>DOD requires DNA samples </li></ul></ul><ul><ul><li>Bioterrorism and homeland security </li></ul></ul><ul><ul><li>Identification of World Trade Center victims </li></ul></ul><ul><li>Privacy and security issues are important but not inherently different than other EMR data. </li></ul>
    63. 66. Summary <ul><li>Informatics will be the key enabling technology for personalized, genomic medicine. </li></ul><ul><li>Current separation between bioinformatics and clinical informatics will diminish as the two subdisciplines merge </li></ul>
    64. 67. Optional Exercise: Hands-on with GHR <ul><li>Scavenger hunt with hemochromatosis and the genes that influence it. </li></ul><ul><li>Explore the Genetics Home Reference by answering the following questions. Start at http:// ghr . nlm . nih . gov . </li></ul>
    65. 68. GHR Scavenger Hunt <ul><li>How common is hemochromatosis? </li></ul><ul><li>How many genes have been proven to be involved in hemochromatosis when the genes are mutated? </li></ul><ul><li>What are the symbols for these genes? </li></ul><ul><li>Can you find the link to MedlinePlus with health information on hemochromatosis? </li></ul>
    66. 69. GHR Scavenger Hunt <ul><li>What are the names of the patient support associations for hemochromatosis? </li></ul><ul><li>One synonym for this condition is “bronze diabetes”. Can you find a reason for this? </li></ul><ul><li>What kind of damage is done to the liver of people with hemochromatosis? </li></ul>
    67. 70. GHR Scavenger Hunt <ul><li>For the genes involved in hemochromatosis, how many of them are available as a DNA test? </li></ul><ul><li>Give one place where you would choose to send a tissue sample for DNA testing. </li></ul><ul><li>What sites are listed under “Research Resources” for the TFR2 gene? </li></ul><ul><ul><li>How many alternately spliced proteins for TFR2? </li></ul></ul><ul><ul><li>In what tissues is this gene expressed? </li></ul></ul>
    68. 71. GHR Scavenger Hunt <ul><li>How do people inherit hemochromatosis? </li></ul><ul><li>Do the genes involved in hemochromatosis cause other health conditions when they are mutated? </li></ul><ul><li>Can you find a protein sequence for one of the genes? </li></ul><ul><li>What clinical trials are available for hemochromatosis patients close to where you live? </li></ul>
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