P F McArdle1, B W Whitcomb. 1. Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Md. 21201, USA. pmcardle@epi.umaryland.edu
Abstract
OBJECTIVE: In studies of associations between genetic factors and outcomes where change in phenotype is of interest, proper modeling of the data, particularly the treatment of baseline trait values, is required to draw valid conclusions. METHODS: The authors compared models of blood pressure response to a cold pressor test with and without inclusion of baseline blood pressure as a regressor and evaluate the resultant biases. RESULTS: Adjustment for baseline presents a potential source of bias for assessment of genotype-phenotype associations. This bias was observed to occur both under the absence of a true effect, as well when a relation between genotype and change in phenotype was simulated. In simulations that incorporated measurement error, estimates were as great as two fold the true parameter values when unmeasured confounding was a factor. CONCLUSIONS: Adjusting for baseline introduces bias in genetic association studies when change in phenotype is the outcome of interest. Model misspecification bias may impact inference and provide one possible source of non-replication of findings in the literature.
OBJECTIVE: In studies of associations between genetic factors and outcomes where change in phenotype is of interest, proper modeling of the data, particularly the treatment of baseline trait values, is required to draw valid conclusions. METHODS: The authors compared models of blood pressure response to a cold pressor test with and without inclusion of baseline blood pressure as a regressor and evaluate the resultant biases. RESULTS: Adjustment for baseline presents a potential source of bias for assessment of genotype-phenotype associations. This bias was observed to occur both under the absence of a true effect, as well when a relation between genotype and change in phenotype was simulated. In simulations that incorporated measurement error, estimates were as great as two fold the true parameter values when unmeasured confounding was a factor. CONCLUSIONS: Adjusting for baseline introduces bias in genetic association studies when change in phenotype is the outcome of interest. Model misspecification bias may impact inference and provide one possible source of non-replication of findings in the literature.
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