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Phenomics
  1. Matthew B. Lanktree, BSc*†,
  2. Reina G. Hassell, MSc,
  3. Piya Lahiry, MSc*†,
  4. Robert A. Hegele, MD, FRCPC, FACP*†
  1. From the *Departments of Medicine and Biochemistry, Schulich School of Medicine & Dentistry; and †Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.
  1. Received December 10, 2009, and in revised form February 8, 2010.
  2. Accepted for publication February 8, 2010.
  3. Reprints: Robert A. Hegele, MD, FRCPC, FACP, Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada N6A 5K8. E-mail: hegele{at}robarts.ca.
  4. Supported by the Canadian Institutes for Health Research (MOP-13430; MOP-79533), the Heart and Stroke Foundation of Ontario (NA-6059; T-6018), Genome Canada through Ontario Genomics Institute, and the Pfizer Jean Davignon Distinguished Cardiovascular and Metabolic Research Award.
  5. M.B.L. is supported by the Canadian Institute of Health Research (CIHR) MD/PhD Studentship Award. P.L. is supported by the CIHR Scriver Family MD/PhD studentship award. Both M.B.L. and P.L. are supported by the University of Western Ontario MD/PhD Program and are CIHR Fellows in Vascular Research.
  6. The authors have no conflicts of interest to declare.

Expanding the Role of Clinical Evaluation in Genomic Studies

Abstract

With advances in high-throughput genotyping technologies, the rate-limiting step of large-scale genetic investigations has become the collection of sensitive and specific phenotype information in large samples of study participants. Clinicians play a pivotal role for successful genetic studies because sound clinical acumen can substantially increase study power by reducing measurement error and improving diagnostic precision for translational research. Phenomics is the systematic measurement and analysis of qualitative and quantitative traits, including clinical, biochemical, and imaging methods, for the refinement and characterization of a phenotype. Phenomics requires deep phenotyping, the collection of a wide breadth of phenotypes with fine resolution, and phenomic analysis, composed of constructing heat maps, cluster analysis, text mining, and pathway analysis. In this article, we review the components of phenomics and provide examples of their application to genomic studies, specifically for implicating novel disease processes, reducing sample heterogeneity, hypothesis generation, integration of multiple types of data, and as an extension of Mendelian randomization studies.

Key Words
  • phenomics
  • genetics
  • phenotype
  • cluster analysis
  • Mendelian randomization

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