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Genotype imputation in case-only studies of gene-environment interaction: validity and power
Case-only (CO) studies are a powerful means to uncover gene-environment (G × E) interactions for complex human diseases. Moreover, such studies may in principle also draw upon genotype imputation to increase statistical power even further. However, genotype imputation usually employs healthy control...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8263402/ https://www.ncbi.nlm.nih.gov/pubmed/34041609 http://dx.doi.org/10.1007/s00439-021-02294-z |
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author | Aleknonytė-Resch, Milda Szymczak, Silke Freitag-Wolf, Sandra Dempfle, Astrid Krawczak, Michael |
author_facet | Aleknonytė-Resch, Milda Szymczak, Silke Freitag-Wolf, Sandra Dempfle, Astrid Krawczak, Michael |
author_sort | Aleknonytė-Resch, Milda |
collection | PubMed |
description | Case-only (CO) studies are a powerful means to uncover gene-environment (G × E) interactions for complex human diseases. Moreover, such studies may in principle also draw upon genotype imputation to increase statistical power even further. However, genotype imputation usually employs healthy controls such as the Haplotype Reference Consortium (HRC) data as an imputation base, which may systematically perturb CO studies in genomic regions with main effects upon disease risk. Using genotype data from 719 German Crohn Disease (CD) patients, we investigated the level of imputation accuracy achievable for single nucleotide polymorphisms (SNPs) with or without a genetic main effect, and with varying minor allele frequency (MAF). Genotypes were imputed from neighbouring SNPs at different levels of linkage disequilibrium (LD) to the target SNP using the HRC data as an imputation base. Comparison of the true and imputed genotypes revealed lower imputation accuracy for SNPs with strong main effects. We also simulated different levels of G × E interaction to evaluate the potential loss of statistical validity and power incurred by the use of imputed genotypes. Simulations under the null hypothesis revealed that genotype imputation does not inflate the type I error rate of CO studies of G × E. However, the statistical power was found to be reduced by imputation, particularly for SNPs with low MAF, and a gradual loss of statistical power resulted when the level of LD to the SNPs driving the imputation decreased. Our study thus highlights that genotype imputation should be employed with great care in CO studies of G × E interaction. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00439-021-02294-z. |
format | Online Article Text |
id | pubmed-8263402 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-82634022021-07-20 Genotype imputation in case-only studies of gene-environment interaction: validity and power Aleknonytė-Resch, Milda Szymczak, Silke Freitag-Wolf, Sandra Dempfle, Astrid Krawczak, Michael Hum Genet Original Investigation Case-only (CO) studies are a powerful means to uncover gene-environment (G × E) interactions for complex human diseases. Moreover, such studies may in principle also draw upon genotype imputation to increase statistical power even further. However, genotype imputation usually employs healthy controls such as the Haplotype Reference Consortium (HRC) data as an imputation base, which may systematically perturb CO studies in genomic regions with main effects upon disease risk. Using genotype data from 719 German Crohn Disease (CD) patients, we investigated the level of imputation accuracy achievable for single nucleotide polymorphisms (SNPs) with or without a genetic main effect, and with varying minor allele frequency (MAF). Genotypes were imputed from neighbouring SNPs at different levels of linkage disequilibrium (LD) to the target SNP using the HRC data as an imputation base. Comparison of the true and imputed genotypes revealed lower imputation accuracy for SNPs with strong main effects. We also simulated different levels of G × E interaction to evaluate the potential loss of statistical validity and power incurred by the use of imputed genotypes. Simulations under the null hypothesis revealed that genotype imputation does not inflate the type I error rate of CO studies of G × E. However, the statistical power was found to be reduced by imputation, particularly for SNPs with low MAF, and a gradual loss of statistical power resulted when the level of LD to the SNPs driving the imputation decreased. Our study thus highlights that genotype imputation should be employed with great care in CO studies of G × E interaction. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00439-021-02294-z. Springer Berlin Heidelberg 2021-05-26 2021 /pmc/articles/PMC8263402/ /pubmed/34041609 http://dx.doi.org/10.1007/s00439-021-02294-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Investigation Aleknonytė-Resch, Milda Szymczak, Silke Freitag-Wolf, Sandra Dempfle, Astrid Krawczak, Michael Genotype imputation in case-only studies of gene-environment interaction: validity and power |
title | Genotype imputation in case-only studies of gene-environment interaction: validity and power |
title_full | Genotype imputation in case-only studies of gene-environment interaction: validity and power |
title_fullStr | Genotype imputation in case-only studies of gene-environment interaction: validity and power |
title_full_unstemmed | Genotype imputation in case-only studies of gene-environment interaction: validity and power |
title_short | Genotype imputation in case-only studies of gene-environment interaction: validity and power |
title_sort | genotype imputation in case-only studies of gene-environment interaction: validity and power |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8263402/ https://www.ncbi.nlm.nih.gov/pubmed/34041609 http://dx.doi.org/10.1007/s00439-021-02294-z |
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