Genome-wide association (GWA) studies have identified hundreds of associations between genetic variants and complex human diseases, and for some diseases, such as diabetes and Crohn's disease, pooling of multiple GWA studies by meta-analysis has led to the discovery of new gene associations. However, most GWA studies have had relatively few phenotypic and exposure measures in common. Harmonizing data across studies that have used disparate measures to collect similar information is difficult and time consuming. Development and adoption of standard phenotypic and exposure measures could facilitate the creation of larger, more comprehensive datasets with a variety of phenotype and exposure data for cross-study analysis, thus increasing statistical power and the ability to detect associations of modest effect sizes and gene-gene and gene-environment interactions.
Recognizing the need for standard phenotypic and exposure measures, particularly as related to GWA studies, NHGRI initiated the PhenX Toolkit in 2006 through RFA-HG-07-006, "High-Priority Phenotype and Exposure Measures for Cross-Study Analysis in Genome-Wide Association Studies." The goal of this program is to identify and catalogue 15 high-quality, well-established, and broadly applicable measures for each of 21 research domains for use in GWA studies and other large-scale genomic research. A PhenX domain is a topic area with a unifying theme such as Demographics, Anthropometrics, Neurology, Cancer, or Social Environments. PhenX measures are selected by Working Groups of domain experts using a consensus process and are made available to the scientific community via the PhenX Toolkit (www.phenxtoolkit.org).
|Domain||Release Date||Number of Measures
in PhenX Toolkit
|Alcohol, Tobacco, & Other Substances||Feb 2009||14|
|Nutrition & Dietary Supplements||Oct 2009||12|
|Environmental Exposures||Oct 2009||14|
|Oral Health||Dec 2009||15|
|Reproductive Health||Feb 2010||14|
|Physical Activity & Physical Fitness||May 2010||14|
|Infectious Diseases & Immunity||Oct 2010||15|
|Skin, Bone, Muscle & Joint||Oct 2010||10|
|Speech & Hearing||Nov 2010||15|
|Social Environments||Dec 2010||15|
Pan, H., Tryka, K., Vreeman, D., Huggins, W., Phillips, M., Mehta, J., Phillips, J., McDonald, C., Junkins, H., Ramos, E. & Hamilton, C. M. (2012) Using PhenX Measures to Identify Opportunities for Cross-Study Analysis. Human Mutation, 33(5):849-857. 2012. [PubMed]
Hendershot, T., Pan, H., Haines, J., Harlan, W., Junkins, H., Ramos, E., & Hamilton, C. M. Using the PhenX Toolkit to Add Standard Measures to Your Study. Current Protocols in Human Genetics, Chapter 1:Unit1.21. 2011. [PubMed]
Hamilton, C. M., Strader, L. C., Pratt, J., Maiese, D., Hendershot, T., Kwok, R., Hammond, J., Huggins, W., Jackman, D., Pan, H., Nettles, D., Beaty, T., Farrer, L., Kraft, P., Marazita, M., Ordovas, J., Pato, C., Spitz, M., Wagener, D., Williams, M., Junkins, H., Harlan, W., Ramos, E & Haines, J. Response to Invited Commentary: Consolidating Data Harmonization. American Journal of Epidemiology, 174 (3), 265-266. 2011. [Response in AJE]
Schad, P. A., L. R. Mobley, et al. Building a biomedical cyberinfrastructure for collaborative research. Am J Prev Med, 40(5 Suppl 2): S144-150. 2011. [PubMed]
Pathak J., Pan H., Wang, J., Kashyap, S., Schad, P., Hamilton, C. M., Masys, D. & Chute. Evaluating Phenotypic Data Elements for Genetics and Epidemiological Research: Experiences from the eMERGE and PhenX Network Projects. American Medical Informatics Association (AMIA) Clinical Research Informatics (CRI) Summit Proceedings, 2011:41-5. 2011. [PubMed]
Hamilton CM, Strader LC, Pratt JG, Maiese D, Hendershot T, Kwok R, Hammond JA, Huggins W, Jackman D, Pan H, Nettles DS, Beaty TH, Farrer LA, Kraft P, Marazita M, Ordovas JM, Pato CN, Spitz MR, Wagener D, Williams M, Junkins HA, Harlan WR, Ramos EM, Haines J. The PhenX Toolkit: Get the Most From Your Measures. American Journal of Epidemiology, 2010. [PubMed]
Stover PJ, Harlan W, Hammond J, Hendershot T, Hamilton CM. PhenX: a toolkit for interdisciplinary genetics research. Current Opinion in Lipidology, 21(2):136-40. 2010. [PubMed]
Erin M. Ramos, M.D., M.P.H.
Epidemiologist, Project Scientist
Heather A. Colley, M.S.
Health Science Analyst
Last Updated: April 24, 2017