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

Benjamin Woolf; Hannah M. Sallis; Marcus R. Munafò; Dipender Gill

doi:10.1186/s13104-023-06438-4

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

Benjamin Woolf, Hannah M. Sallis, Marcus R. Munafò, Dipender Gill

Vice Chancellor's Office

Research output: Contribution to journal › Article › peer-review

4 Citations (SciVal)

Abstract

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.

Original language	English
Article number	159
Journal	BMC Research Notes
Volume	16
Issue number	1
Early online date	30 Jul 2023
DOIs	https://doi.org/10.1186/s13104-023-06438-4
Publication status	Published - 31 Dec 2023

Data Availability Statement

The code and GWAS summary statistics used in this study is available from https://doi.org/10.17605/OSF.IO/SPKMT.

Acknowledgements

This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol—http://www.bris.ac.uk/acrc/.

Funding

Benjamin Woolf is funded by an Economic and Social Research Council (ESRC) South West Doctoral Training Partnership (SWDTP) 1 + 3 PhD Studentship Award (ES/P000630/1). BW, HS and MM work in the MRC Integrative Epidemiology Unit that is supported by the University of Bristol and UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/7). DG is funded by the British Heart Foundation Centre of Research Excellence (RE/18/4/34215) at Imperial College London. This research was funded by United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7). For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.

Keywords

Family GWAS
Genome Wide association studies
GWAS-by-subtraction
Intergenerational Mendelian randomisation

ASJC Scopus subject areas

General Biochemistry,Genetics and Molecular Biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1186/s13104-023-06438-4Licence: CC BY

Cite this

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abstract = "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{\textquoteright}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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Deriving GWAS summary estimates for paternal smoking in UK biobank: a GWAS by subtraction

Abstract

Data Availability Statement

Acknowledgements

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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