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A test for gene-environment interaction in the presence of measurement error in the environmental variable
- Source :
- Genetic Epidemiology, Genetic Epidemiology, Wiley, 2018, 42 (3), pp.250-264. ⟨10.1002/gepi.22113⟩, Genetic Epidemiology, 2018, 42 (3), pp.250-264. ⟨10.1002/gepi.22113⟩
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- International audience; The identification of gene-environment interactions in relation to risk of human diseases has been challenging. One difficulty has been that measurement error in the exposure can lead to massive reductions in the power of the test, as well as in bias toward the null in the interaction effect estimates. Leveraging previous work on linear discriminant analysis, we develop a new test of interaction between genetic variants and a continuous exposure that mitigates these detrimental impacts of exposure measurement error in ExG testing by reversing the role of exposure and the diseases status in the fitted model, thus transforming the analysis to standard linear regression. Through simulation studies, we show that the proposed approach is valid in the presence of classical exposure measurement error as well as when there is correlation between the exposure and the genetic variant. Simulations also demonstrated that the reverse test has greater power compared to logistic regression. Finally, we confirmed that our approach eliminates bias from exposure measurement error in estimation. Computing times are reduced by as much as fivefold in this new approach. For illustrative purposes, we applied the new approach to an ExGWAS study of interactions with alcohol and body mass index among 1,145 cases with invasive breast cancer and 1,142 controls from the Cancer Genetic Markers of Susceptibility study.
- Subjects :
- 0301 basic medicine
Epidemiology
Genome-wide association study
Breast Neoplasms
MESH: Logistic Models
Interaction
Logistic regression
01 natural sciences
Article
Correlation
010104 statistics & probability
03 medical and health sciences
Bias
Statistics
Linear regression
MESH: Bias
Humans
normal discriminant analysis
MESH: Genetic Variation
MESH: Models, Genetic
0101 mathematics
Gene–environment interaction
gene-environment interaction test
Genetics (clinical)
Mathematics
[STAT.AP]Statistics [stat]/Applications [stat.AP]
Observational error
MESH: Humans
Models, Genetic
Genetic Variation
Reproducibility of Results
MESH: Gene-Environment Interaction
Linear discriminant analysis
3. Good health
MESH: Reproducibility of Results
030104 developmental biology
Logistic Models
[SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics
genome-wide association studies
MESH: Genome-Wide Association Study
Gene-Environment Interaction
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
[STAT.ME]Statistics [stat]/Methodology [stat.ME]
measurement error
MESH: Breast Neoplasms
Genome-Wide Association Study
Subjects
Details
- Language :
- English
- ISSN :
- 07410395 and 10982272
- Database :
- OpenAIRE
- Journal :
- Genetic Epidemiology, Genetic Epidemiology, Wiley, 2018, 42 (3), pp.250-264. ⟨10.1002/gepi.22113⟩, Genetic Epidemiology, 2018, 42 (3), pp.250-264. ⟨10.1002/gepi.22113⟩
- Accession number :
- edsair.doi.dedup.....b8d3c99b537e6bda5d03f1728f5d16ee