PhenX Toolkit

The PhenX Toolkit
Type of site
Content Site
Available inEnglish
OwnerNHGRI
Created byRTI International
URLwww.phenxtoolkit.org
Commercialno
RegistrationOptional
Users3700+ Registered, 1.6M+ visits
Launched6 February 2009 (2009-02-06)
Current statusActive
Content license
Public Domain

The PhenX Toolkit is a web-based catalog of high-priority measures related to complex diseases, phenotypic traits and environmental exposures. These measures were selected by working groups of experts using a consensus process.[1] Use of PhenX measures facilitates combining data from a variety of studies, and makes it easy for investigators to expand a study design beyond the primary research focus.[2][3][4] The Toolkit is funded by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) with co-funding by the Office of Behavioral and Social Sciences Research (OBSSR) and the National Institute on Drug Abuse (NIDA).[5][6] Supplemental funding is provided by the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute on Minority Health and Health Disparities (NIMHD).[7] The PhenX Toolkit is available to the scientific community at no cost.

For genome-wide association studies (GWAS) and other studies involving human subjects, the use of standard measures can facilitate cross-study analyses.[8][9][10] Such analyses compare independent findings to validate results or combine studies to increase sample size and statistical power.[11][12] This increased power makes it possible to identify more subtle and complex associations such as gene-gene and gene-environment interactions.[13][14][15][16] PhenX is an NIH Common Data Element (CDE) Repository project and supports the NIH Strategic Plan for Data Science, which promotes FAIR principles (i.e., Findable, Accessible, Interoperable, Reusable) to facilitate data sharing.[17]

In 2020, PhenX collaborated with the U.S. NIH's Public Health Emergency and Disaster Research Response Program (DR2) to collect and review research protocols for epidemiologists, clinicians and other scientists studying COVID-19.[18] The Toolkit released six specialty collections of protocols to promote the use of CDEs for research on COVID-19 in October 2020.[19]

See also

References

  1. ↑ Maiese DR, Hendershot TP, Strader LC, et al. (2013). PhenX—Establishing a consensus process to select common measures for collaborative research (Technical report). Research Triangle Park, NC: RTI Press. doi:10.3768/rtipress.2013.mr.0027.1310. MR-0027-1310.
  2. ↑ Hamilton CM, Strader LC, Pratt JG, et al. (1 August 2011). "The PhenX Toolkit: Get the Most From Your Measures". American Journal of Epidemiology. 174 (3): 253–260. doi:10.1093/aje/kwr193. PMC 3141081. PMID 21749974.
  3. ↑ Hendershot T, Pan H, Haines J, et al. (October 2011). "Using the PhenX Toolkit to Add Standard Measures to Your Study". Current Protocols in Human Genetics. 1 (21). Unit 1.21. doi:10.1002/0471142905.hg0121s71. PMID 21975939. S2CID 7273784.
  4. ↑ Fortier, Isabel; Doiron, Dany; Burton, Paul; Raina, Parminder (2011-08-01). "Invited Commentary: Consolidating Data Harmonization—How to Obtain Quality and Applicability?". American Journal of Epidemiology. 174 (3): 261–264. doi:10.1093/aje/kwr194. ISSN 0002-9262. PMID 21749975.
  5. ↑ "A research toolkit of standard measures to be expanded to further support the biomedical community". RTI International. September 28, 2017. Retrieved 9 May 2018.
  6. ↑ "Resource Summaries". wayback.archive-it.org. Retrieved 2021-05-21.
  7. ↑ Eckman, JR; et al. (December 26, 2017). "Standard measures for sickle cell disease research: the PhenX Toolkit sickle cell disease collections" (PDF). Blood Advances. 1 (27): 2703–2711. doi:10.1182/bloodadvances.2017010702. PMC 5745137. PMID 29296922. Retrieved 9 May 2018.
  8. ↑ Pan H, Tryka KA, Vreeman DJ, et al. (May 2012). "Using PhenX Measures to Identify Opportunities for Cross-Study Analysis". Human Mutation. 33 (5): 849–857. doi:10.1002/humu.22074. PMC 3780790. PMID 22415805.
  9. ↑ Manolio TA (February 2009). "Collaborative Genome-wide Association Studies of Diverse Diseases: Programs of the NHGRI's Office of Population Genomics". Pharmacogenomics. 10 (3): 235–241. doi:10.2217/14622416.10.2.235. PMC 2714942. PMID 19207024.
  10. ↑ Sheehan, Jerry; Hirschfeld, Steven; Foster, Erin; Ghitza, Udi; Goetz, Kerry; Karpinski, Joanna; Lang, Lisa; Moser, Richard P.; Odenkirchen, Joanne; Reeves, Dianne; Rubinstein, Yaffa (December 2016). "Improving the value of clinical research through the use of Common Data Elements (CDEs)". Clinical Trials (London, England). 13 (6): 671–676. doi:10.1177/1740774516653238. ISSN 1740-7745. PMC 5133155. PMID 27311638.
  11. ↑ Sheehan, Jerry; Hirschfeld, Steven; Foster, Erin; Ghitza, Udi; Goetz, Kerry; Karpinski, Joanna; Lang, Lisa; Moser, Richard P.; Odenkirchen, Joanne; Reeves, Dianne; Rubinstein, Yaffa (December 2016). "Improving the value of clinical research through the use of Common Data Elements (CDEs)". Clinical Trials (London, England). 13 (6): 671–676. doi:10.1177/1740774516653238. ISSN 1740-7745. PMC 5133155. PMID 27311638.
  12. ↑ Fortier, Isabel; Dragieva, Nataliya; Saliba, Matilda; Craig, Camille; Robson, Paula J. (2019-04-16). "Harmonization of the Health and Risk Factor Questionnaire data of the Canadian Partnership for Tomorrow Project: a descriptive analysis". CMAJ Open. 7 (2): E272–E282. doi:10.9778/cmajo.20180062. ISSN 2291-0026. PMC 6498449. PMID 31018973.
  13. ↑ Barrett JC, Hansoul S, Nicolae DL, et al. (August 2008). "Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease". Nature Genetics. 40 (8): 955–962. doi:10.1038/ng.175. PMC 2574810. PMID 18587394.
  14. ↑ Barrett JC, Clayton DG, Concannon P, et al. (June 2009). "Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes" (PDF). Nature Genetics. 41 (6): 703–707. doi:10.1038/ng.381. PMC 2889014. PMID 19430480.
  15. ↑ Cooper JD, Smyth DJ, Smiles AM, et al. (December 2008). "Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci". Nature Genetics. 40 (12): 1399–1401. doi:10.1038/ng.249. PMC 2635556. PMID 18978792.
  16. ↑ Hunter DJ (April 2005). "Gene-environment Interactions in Human Diseases". Nature Reviews Genetics. 6 (4): 287–298. doi:10.1038/nrg1578. PMID 15803198. S2CID 27052260.
  17. ↑ "NIH Common Data Elements (CDE) Repository". cde.nlm.nih.gov. Retrieved 2021-05-21.
  18. ↑ "Covid-19 researchers gain quick access to surveys, protocols (Environmental Factor, May 2020)". National Institute of Environmental Health Sciences. Retrieved 2021-05-20.
  19. ↑ Krzyzanowski, Michelle C.; Terry, Ian; Williams, David; West, Pat; Gridley, Lauren N.; Hamilton, Carol M. (2021). "The PhenX Toolkit: Establishing Standard Measures for COVID-19 Research". Current Protocols. 1 (4): e111. doi:10.1002/cpz1.111. ISSN 2691-1299. PMC 8206667. PMID 33905618.
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