paperKB
coga / coga-kb
Help
Sign in

Chunk #21 — RESULTS

Source
Development and evaluation of a genetic risk score for obesity.
Embedded
yes

Text

increased by 3.54% (p=0.059) and 4.92% (p=0.017), respectively. Results were substantively unchanged when control variables were removed from the models. To determine whether population substructure influenced our estimates of GRS-BMI or GRS-obesity associations, we repeated our analyses of the white and black subsamples, including as covariates the first 5 principal components derived for each ethnic group using the method described by Patterson et al.40 (principal components derived for the white and black subsamples were included as part of the ARIC database obtained from dbGaP41) Adjustment for these principal components is a valid method of controlling for population stratification in genetic association analyses.42 Inclusion of principal components as covariates in regression analyses did not change results.