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

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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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'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
Number of pages	7
Journal	BMC Research Notes
Volume	16
Issue number	1
DOIs	https://doi.org/10.1186/s13104-023-06438-4
Publication status	Published - 30 Jul 2023

Bibliographical note

Funding Information:
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.

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

Publisher Copyright:
© 2023, The Author(s).

Research Groups and Themes

TARG

Keywords

Genome-Wide Association Study
Phenotype
Biological Specimen Banks
Smoking/genetics
United Kingdom
Polymorphism, Single Nucleotide

UN SDGs

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

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title = "Deriving GWAS summary estimates for paternal smoking in UK biobank: a GWAS by subtraction",

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.",

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note = "Funding Information: 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. Funding Information: This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol—http://www.bris.ac.uk/acrc/. Publisher Copyright: {\textcopyright} 2023, The Author(s).",

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doi = "10.1186/s13104-023-06438-4",

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AU - Woolf, Benjamin

AU - Sallis, Hannah M

AU - Munafò, Marcus R

AU - Gill, Dipender

N1 - Funding Information: 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. Funding Information: This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol—http://www.bris.ac.uk/acrc/. Publisher Copyright: © 2023, The Author(s).

PY - 2023/7/30

Y1 - 2023/7/30

N2 - 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.

AB - 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.

KW - Genome-Wide Association Study

KW - Phenotype

KW - Biological Specimen Banks

KW - Smoking/genetics

KW - United Kingdom

KW - Polymorphism, Single Nucleotide

U2 - 10.1186/s13104-023-06438-4

DO - 10.1186/s13104-023-06438-4

M3 - Article (Academic Journal)

C2 - 37518004

SN - 1756-0500

VL - 16

JO - BMC Research Notes

JF - BMC Research Notes

IS - 1

M1 - 159

ER -

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

Abstract

Bibliographical note

Research Groups and Themes

Keywords

UN SDGs

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