Lau, Winston;
Ali, Aminah;
Maude, Hannah;
Andrew, Toby;
Swallow, Dallas M;
Maniatis, Nikolas;
(2024)
The hazards of genotype imputation when mapping disease susceptibility variants.
Genome Biology
, 25
(1)
, Article 7. 10.1186/s13059-023-03140-3.
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Abstract
BACKGROUND: The cost-free increase in statistical power of using imputation to infer missing genotypes is undoubtedly appealing, but is it hazard-free? This case study of three type-2 diabetes (T2D) loci demonstrates that it is not; it sheds light on why this is so and raises concerns as to the shortcomings of imputation at disease loci, where haplotypes differ between cases and reference panel. RESULTS: T2D-associated variants were previously identified using targeted sequencing. We removed these significantly associated SNPs and used neighbouring SNPs to infer them by imputation. We compared imputed with observed genotypes, examined the altered pattern of T2D-SNP association, and investigated the cause of imputation errors by studying haplotype structure. Most T2D variants were incorrectly imputed with a low density of scaffold SNPs, but the majority failed to impute even at high density, despite obtaining high certainty scores. Missing and discordant imputation errors, which were observed disproportionately for the risk alleles, produced monomorphic genotype calls or false-negative associations. We show that haplotypes carrying risk alleles are considerably more common in the T2D cases than the reference panel, for all loci. CONCLUSIONS: Imputation is not a panacea for fine mapping, nor for meta-analysing multiple GWAS based on different arrays and different populations. A total of 80% of the SNPs we have tested are not included in array platforms, explaining why these and other such associated variants may previously have been missed. Regardless of the choice of software and reference haplotypes, imputation drives genotype inference towards the reference panel, introducing errors at disease loci.
Type: | Article |
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Title: | The hazards of genotype imputation when mapping disease susceptibility variants |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1186/s13059-023-03140-3 |
Publisher version: | http://dx.doi.org/10.1186/s13059-023-03140-3 |
Language: | English |
Additional information: | © 2024 BioMed Central Ltd. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Humans, Disease Susceptibility, Genome-Wide Association Study, Genotype, Haplotypes, Polymorphism, Single Nucleotide, Diabetes Mellitus, Type 2 |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
URI: | https://discovery.ucl.ac.uk/id/eprint/10185343 |
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