Adjustment for index event bias in genome-wide association studies of subsequent events

Frank Dudbridge (), Richard J. Allen, Nuala A. Sheehan, A. Floriaan Schmidt, James C. Lee, R. Gisli Jenkins, Louise V. Wain, Aroon D. Hingorani and Riyaz S. Patel
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Frank Dudbridge: University of Leicester
Richard J. Allen: University of Leicester
Nuala A. Sheehan: University of Leicester
A. Floriaan Schmidt: University of Groningen
James C. Lee: University of Cambridge School of Clinical Medicine
R. Gisli Jenkins: Nottingham Respiratory Biomedical Research Centre, City Campus
Louise V. Wain: University of Leicester
Aroon D. Hingorani: University College London
Riyaz S. Patel: University College London

Nature Communications, 2019, vol. 10, issue 1, 1-10

Abstract: Abstract Following numerous genome-wide association studies of disease susceptibility, there is increasing interest in genetic associations with prognosis, survival or other subsequent events. Such associations are vulnerable to index event bias, by which selection of subjects according to disease status creates biased associations if common causes of incidence and prognosis are not accounted for. We propose an adjustment for index event bias using the residuals from the regression of genetic effects on prognosis on genetic effects on incidence. Our approach eliminates this bias when direct genetic effects on incidence and prognosis are independent, and otherwise reduces bias in realistic situations. In a study of idiopathic pulmonary fibrosis, we reverse a paradoxical association of the strong susceptibility gene MUC5B with increased survival, suggesting instead a significant association with decreased survival. In re-analysis of a study of Crohn’s disease prognosis, four regions remain associated at genome-wide significance but with increased standard errors.

Date: 2019
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DOI: 10.1038/s41467-019-09381-w

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