Abstract
Accurate and consistent phenotyping of cases and disease-free control participants is important to maximise study power and reduce the risk of misclassification bias in genetic association studies. In this analysis of UK Biobank data, the definition of self-report of gout or urate lowering therapy use detected the highest number of gout cases and had greatest precision for genetic association analysis. This study supports the use of the self-report of gout or urate lowering therapy use definition for use in epidemiological studies when more detailed gout-specific clinical data are not available. The main results are the output from a logistic regression using plink2 with the added column of GoutDef at the start which defined the gout definition used (see below) and the plink2 specification for the other columns can also be found here https://www.cog-genomics.org/plink2/formats under ".assoc.linear, .assoc.logistic (multi-covariate association analysis report)" BP is base position and NMISS is number of non-missing individuals included in analysis. A2, A1/A2, and INFO weren't generated. A1 is the minor allele. 15 genetic PCAs (f.22009) that were provided with the interim data release GoutDef is the definition of gout used and is described best in the paper (Cadzow_et_al_2017.pdf) but in summary is 6 different definitions (self reported, self reported or on self reported urate lowering therapy (ULT), on self reported ULT, the "Winnard" definition, Hospital diagnosis (HES I think), or any of the previous (all). ULT was based on a medical doctor going through the list of self reported drugs and indicating what drugs were relevant to gout (UKBio_drugs_ND_formatted.csv).
1 Application
Application ID | Title |
12611 | A genome-wide association study in gout: the NZ/Eurogout/US Consortium |
1 Return
Return ID | App ID | Description | Archive Date |
1825 | 12611 | Performance of gout definitions for genetic epidemiological studies: analysis of UK Biobank | 22 Nov 2019 |