The shared genetic architecture between epidemiological and behavioral traits with lung cancer

Abstract The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between...

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Main Authors: Rowland W. Pettit, Jinyoung Byun, Younghun Han, Quinn T. Ostrom, Jacob Edelson, Kyle M. Walsh, Melissa L. Bondy, Rayjean J. Hung, James D. McKay, Christopher I. Amos
Format: Article
Language:English
Published: Nature Publishing Group 2021-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-96685-x
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spelling doaj-48f5fa5abd854b65a09e8928448fd58b2021-09-05T11:31:45ZengNature Publishing GroupScientific Reports2045-23222021-09-0111111210.1038/s41598-021-96685-xThe shared genetic architecture between epidemiological and behavioral traits with lung cancerRowland W. Pettit0Jinyoung Byun1Younghun Han2Quinn T. Ostrom3Jacob Edelson4Kyle M. Walsh5Melissa L. Bondy6Rayjean J. Hung7James D. McKay8Christopher I. Amos9Institute for Clinical and Translational Research, Baylor College of MedicineInstitute for Clinical and Translational Research, Baylor College of MedicineInstitute for Clinical and Translational Research, Baylor College of MedicineDuke Cancer Institute, Duke University Medical CenterDepartment of Biomedical Data Science, School of Medicine, Stanford UniversityDuke Cancer Institute, Duke University Medical CenterDepartment of Epidemiology and Population Health, School of Medicine, Stanford UniversityLunenfeld-Tanenbaum Research Institute, Sinai Health SystemSection of Genetics, International Agency for Research on Cancer, World Health OrganizationInstitute for Clinical and Translational Research, Baylor College of MedicineAbstract The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (rg = − 0.41, h2 = 0.10, p = 1.33 × 10–16), increased fluid intelligence scores (rg = − 0.25, h2 = 0.22, p = 4.54 × 10–8), and the age at which full time education was completed (rg = − 0.45, h2 = 0.11, p = 1.24 × 10–20) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (rg = 0.20, h2 = 0.25, p = 2.61 × 10–9). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.https://doi.org/10.1038/s41598-021-96685-x
collection DOAJ
language English
format Article
sources DOAJ
author Rowland W. Pettit
Jinyoung Byun
Younghun Han
Quinn T. Ostrom
Jacob Edelson
Kyle M. Walsh
Melissa L. Bondy
Rayjean J. Hung
James D. McKay
Christopher I. Amos
spellingShingle Rowland W. Pettit
Jinyoung Byun
Younghun Han
Quinn T. Ostrom
Jacob Edelson
Kyle M. Walsh
Melissa L. Bondy
Rayjean J. Hung
James D. McKay
Christopher I. Amos
The shared genetic architecture between epidemiological and behavioral traits with lung cancer
Scientific Reports
author_facet Rowland W. Pettit
Jinyoung Byun
Younghun Han
Quinn T. Ostrom
Jacob Edelson
Kyle M. Walsh
Melissa L. Bondy
Rayjean J. Hung
James D. McKay
Christopher I. Amos
author_sort Rowland W. Pettit
title The shared genetic architecture between epidemiological and behavioral traits with lung cancer
title_short The shared genetic architecture between epidemiological and behavioral traits with lung cancer
title_full The shared genetic architecture between epidemiological and behavioral traits with lung cancer
title_fullStr The shared genetic architecture between epidemiological and behavioral traits with lung cancer
title_full_unstemmed The shared genetic architecture between epidemiological and behavioral traits with lung cancer
title_sort shared genetic architecture between epidemiological and behavioral traits with lung cancer
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-09-01
description Abstract The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (rg = − 0.41, h2 = 0.10, p = 1.33 × 10–16), increased fluid intelligence scores (rg = − 0.25, h2 = 0.22, p = 4.54 × 10–8), and the age at which full time education was completed (rg = − 0.45, h2 = 0.11, p = 1.24 × 10–20) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (rg = 0.20, h2 = 0.25, p = 2.61 × 10–9). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.
url https://doi.org/10.1038/s41598-021-96685-x
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