Deriving GWAS summary estimates for paternal smoking in UK biobank: a GWAS by subtraction.

BMC Res Notes

Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.

Published: July 2023

Objective: To use genome-wide association study (GWAS) by subtraction, a method for deriving novel GWASs from existing summary statistics, to derive genome-wide summary statistics for paternal smoking.

Result: A GWAS by subtraction was implemented using a weighted linear model that defined the child-genotype paternal-phenotype association as the child-genotype child-phenotype association minus the child-genotype maternal-phenotype association. We first use the laws of inherence to derive the weighted linear model. We then implemented the linear model to create a GWAS of paternal smoking by subtracting the summary statistics from a GWAS of maternal smoking from the summary statistics of a GWAS of the index individual's smoking. We used a Monte-Carlo simulation to validate the model and showed that this approach performed similarly in terms of bias to performing a traditional GWAS of paternal smoking. Finally, we validated the summary statistics in a Mendelian randomisation analysis by demonstrating an association of genetically predicted paternal smoking with paternal lung cancer and emphysema.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10387204PMC
http://dx.doi.org/10.1186/s13104-023-06438-4DOI Listing

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