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Developing genomic knowledge bases and databases to support clinical management: current perspectives

Authors Huser V, Sincan M, Cimino J

Received 17 May 2014

Accepted for publication 10 July 2014

Published 9 September 2014 Volume 2014:7 Pages 275—283

DOI https://doi.org/10.2147/PGPM.S49904

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 4


Video abstract presented by Vojtech Huser

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Vojtech Huser,1 Murat Sincan,2,3 James J Cimino1,4


1Laboratory for Informatics Development, National Institutes of Health Clinical Center, Bethesda, MD, USA; 2Undiagnosed Diseases Program, 3Office of the Clinical Director, National Human Genome Research Institute, National Institutes of Health, MD, USA; 4National Library of Medicine, National Institutes of Health, MD, USA


Abstract: Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.


Keywords: personalized medicine, knowledge bases, databases, clinical decision support, clinical informatics

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