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1000 Titel
  • Genotype imputation in case-only studies of gene-environment interaction: validity and power
1000 Autor/in
  1. Aleknonytė-Resch, Milda |
  2. Szymczak, Silke |
  3. Freitag-Wolf, Sandra |
  4. Dempfle, Astrid |
  5. Krawczak, Michael |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-05-26
1000 Erschienen in
1000 Quellenangabe
  • 140(8):1217-1228
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s00439-021-02294-z |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8263402/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Sacherschließung
lokal Algorithms [MeSH]
lokal Linkage Disequilibrium [MeSH]
lokal Models, Genetic [MeSH]
lokal Polymorphism, Single Nucleotide [MeSH]
lokal Humans [MeSH]
lokal Molecular Medicine
lokal Computer Simulation [MeSH]
lokal Crohn Disease/pathology [MeSH]
lokal Genome, Human [MeSH]
lokal Original Investigation
lokal Metabolic Diseases
lokal Germany [MeSH]
lokal Gene Function
lokal Crohn Disease/genetics [MeSH]
lokal Genotype [MeSH]
lokal Alleles [MeSH]
lokal Gene Frequency [MeSH]
lokal Crohn Disease/metabolism [MeSH]
lokal Gene-Environment Interaction [MeSH]
lokal Human Genetics
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/QWxla25vbnl0xJctUmVzY2gsIE1pbGRh|https://frl.publisso.de/adhoc/uri/U3p5bWN6YWssIFNpbGtl|https://frl.publisso.de/adhoc/uri/RnJlaXRhZy1Xb2xmLCBTYW5kcmE=|https://frl.publisso.de/adhoc/uri/RGVtcGZsZSwgQXN0cmlk|https://orcid.org/0000-0003-2603-1502
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1000 Erstellt am 2023-04-28T14:20:48.120+0200
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1000 Zuletzt bearbeitet 2023-10-20T19:06:32.767+0200
1000 Objekt bearb. Fri Oct 20 19:06:32 CEST 2023
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