In the mid 1700s, Carl Linnaeus devised the binomial nomenclature to classify living things into a hierarchy, or taxonomy. Our modern day use of DNA sequencing has enabled the reorganization of the position of species within established taxonomical trees by providing a quantitative distance measure between species. Linnaeus was also the co-founder of systematic nosology, or the classification of disease. We hypothesize that genomic data, medical knowledge, and structured vocabularies have advanced to the point that we can begin to modernize the classification of disease, similar to how DNA sequencing has modernized taxonomy. The implications of a genomics-based nosology are many. Such a classification would serve as the beginnings of a continuous scale for pathology, where we could quantitate how similar one disease is to another. Diseases have long been organized based on common symptoms, and more recently, commonalities in known pathophysiology. With a genomics-based nosology, we can extend the age-old approach of taxonomy to relate diseases by the quantitative measurements of gene expression now available for many common disorders. In addition, a genomic nosology could be used to identify new therapeutic opportunities. The central hypotheses for this proposal are (1) sufficient data in the realm of genomic experiments exists to enable the formation of a genomic-data driven nosology, (2) that the largest current disease nosology, SNOMED-CT, resembles a genomic nosology, and (3) a genomic nosology can enable the discovery of novel testable pharmacogenomic relations. To build the tools and databases that address these aims, we are proposing a novel collaboration between the National Center for Biomedical Ontology (NCBO, PI: Mark Musen) and the Pharmacogenetic and pharmacogenomic Knowledge Base (PharmGKB, PI: Russ Altman). This project brings together researchers in bioinformatics, medical informatics, ontology's, and pharmacogenomics with a long track record of methodological contributions to bioinformatics, together with an advisory board with Principal Investigators from 3 of the 7 NIH-roadmap funded National Centers for Biomedical Computing, to develop a novel methodological approach to create the first genomic classification of medicine and apply this nosology to discover new relations between drugs and genes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM079719-04
Application #
7684065
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Long, Rochelle M
Project Start
2006-09-30
Project End
2011-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
4
Fiscal Year
2009
Total Cost
$383,545
Indirect Cost
Name
Stanford University
Department
Pediatrics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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