| A new paradigm for drug discovery: integrating clinical, genetic, genomic and molecular phenotype data to identify drug targets
Biochemical Society Transactions (2003) Volume 31, part 2
E.E. Schadt*¹, S.A. Monks*† and S.H. Friend*‡¹
Abstract
Application of statistical genetics approaches to variations in mRNA transcript abundances in segregating
populations can be used to identify genes and pathways associated with common human diseases. The
combination of this genetic information with gene expression and clinical trait data can also be used to
identify subtypes of a disease and the genetic loci speci.c to each subtype. Here we highlight results from
some of our recent work in this area and further explore the many possibilities that exist in employing a
more comprehensive genetics and functional genomics approach to the functional annotation of genomes,
and in applying such methods to the validation of targets for complex traits in the drug discovery process.
* Rosetta Inpharmatics LLC, 12040 115th Avenue N.E., Kirkland, WA 98034, U.S.A.
† Department of Biostatistics, University of Washington, Seattle, WA 98195, U.S.A.
‡ Merck Research Laboratories, W42-213 Sumneytown Pike, POB 4, Westpoint, PA 19846, U.S.A.
¹To whom correspondence should be addressed (e-mail eric_schadt@merck.com or stephen_friend@merck.com).
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