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Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution

BACKGROUND: “Quantile-dependent expressivity” refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV(1)), and the FEV(1)/FVC ratio...

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Autor principal: Williams, Paul T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233273/
https://www.ncbi.nlm.nih.gov/pubmed/32461834
http://dx.doi.org/10.7717/peerj.9145
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author Williams, Paul T.
author_facet Williams, Paul T.
author_sort Williams, Paul T.
collection PubMed
description BACKGROUND: “Quantile-dependent expressivity” refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV(1)), and the FEV(1)/FVC ratio are moderately heritable spirometric traits. The aim of the analyses is to test whether their heritability (h(2)) is constant over all quantiles of their distribution. METHODS: Quantile regression was applied to the mean age, sex, height and smoking-adjusted spirometric data over multiple visits in 9,993 offspring-parent pairs and 1,930 sibships from the Framingham Heart Study to obtain robust estimates of offspring-parent (β(OP)), offspring-midparent (β(OM)), and full-sib regression slopes (β(FS)). Nonparametric significance levels were obtained from 1,000 bootstrap samples. β(OP)s were used as simple indicators of quantile-specific heritability (i.e., h(2) = 2β(OP)/(1+r(spouse)), where r(spouse) was the correlation between spouses). RESULTS: β(OP) ± standard error (SE) decreased by 0.0009 ± 0.0003 (P = 0.003) with every one-percent increment in the population distribution of FEV(1)/FVC, i.e., β(OP) ± SE were: 0.182 ± 0.031, 0.152 ± 0.015; 0.136 ± 0.011; 0.121 ± 0.013; and 0.099 ± 0.013 at the 10th, 25th, 50th, 75th, and 90th percentiles of the FEV(1)/FVC distribution, respectively. These correspond to h(2) ± SEs of 0.350 ± 0.060 at the 10th, 0.292 ± 0.029 at the 25th, 0.262 ± 0.020 at the 50th, 0.234 ± 0.025 at the 75th, and 0.191 ± 0.025 at the 90th percentiles of the FEV(1)/FVC ratio. Maximum mid-expiratory flow (MMEF) h(2) ± SEs increased 0.0025 ± 0.0007 (P = 0.0004) with every one-percent increment in its distribution, i.e.: 0.467 ± 0.046, 0.467 ± 0.033, 0.554 ± 0.038, 0.615 ± 0.042, and 0.675 ± 0.060 at the 10th, 25th, 50th, 75th, and 90th percentiles of its distribution. This was due to forced expiratory flow at 75% of FVC (FEF75%), whose quantile-specific h(2) increased an average of 0.0042 ± 0.0008 for every one-percent increment in its distribution. It is speculated that previously reported gene-environment interactions may be partially attributable to quantile-specific h(2), i.e., greater heritability in individuals with lower FEV(1)/FVC due to smoking or airborne particles exposure vs. nonsmoking, unexposed individuals. CONCLUSION: Heritabilities of FEV(1)/FVC, MMEF, and FEF75% from quantile-regression of offspring-parent and sibling spirometric data suggest their quantile-dependent expressivity.
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spelling pubmed-72332732020-05-26 Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution Williams, Paul T. PeerJ Genetics BACKGROUND: “Quantile-dependent expressivity” refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV(1)), and the FEV(1)/FVC ratio are moderately heritable spirometric traits. The aim of the analyses is to test whether their heritability (h(2)) is constant over all quantiles of their distribution. METHODS: Quantile regression was applied to the mean age, sex, height and smoking-adjusted spirometric data over multiple visits in 9,993 offspring-parent pairs and 1,930 sibships from the Framingham Heart Study to obtain robust estimates of offspring-parent (β(OP)), offspring-midparent (β(OM)), and full-sib regression slopes (β(FS)). Nonparametric significance levels were obtained from 1,000 bootstrap samples. β(OP)s were used as simple indicators of quantile-specific heritability (i.e., h(2) = 2β(OP)/(1+r(spouse)), where r(spouse) was the correlation between spouses). RESULTS: β(OP) ± standard error (SE) decreased by 0.0009 ± 0.0003 (P = 0.003) with every one-percent increment in the population distribution of FEV(1)/FVC, i.e., β(OP) ± SE were: 0.182 ± 0.031, 0.152 ± 0.015; 0.136 ± 0.011; 0.121 ± 0.013; and 0.099 ± 0.013 at the 10th, 25th, 50th, 75th, and 90th percentiles of the FEV(1)/FVC distribution, respectively. These correspond to h(2) ± SEs of 0.350 ± 0.060 at the 10th, 0.292 ± 0.029 at the 25th, 0.262 ± 0.020 at the 50th, 0.234 ± 0.025 at the 75th, and 0.191 ± 0.025 at the 90th percentiles of the FEV(1)/FVC ratio. Maximum mid-expiratory flow (MMEF) h(2) ± SEs increased 0.0025 ± 0.0007 (P = 0.0004) with every one-percent increment in its distribution, i.e.: 0.467 ± 0.046, 0.467 ± 0.033, 0.554 ± 0.038, 0.615 ± 0.042, and 0.675 ± 0.060 at the 10th, 25th, 50th, 75th, and 90th percentiles of its distribution. This was due to forced expiratory flow at 75% of FVC (FEF75%), whose quantile-specific h(2) increased an average of 0.0042 ± 0.0008 for every one-percent increment in its distribution. It is speculated that previously reported gene-environment interactions may be partially attributable to quantile-specific h(2), i.e., greater heritability in individuals with lower FEV(1)/FVC due to smoking or airborne particles exposure vs. nonsmoking, unexposed individuals. CONCLUSION: Heritabilities of FEV(1)/FVC, MMEF, and FEF75% from quantile-regression of offspring-parent and sibling spirometric data suggest their quantile-dependent expressivity. PeerJ Inc. 2020-05-15 /pmc/articles/PMC7233273/ /pubmed/32461834 http://dx.doi.org/10.7717/peerj.9145 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, made available under the Creative Commons Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/) . This work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Genetics
Williams, Paul T.
Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
title Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
title_full Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
title_fullStr Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
title_full_unstemmed Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
title_short Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
title_sort spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233273/
https://www.ncbi.nlm.nih.gov/pubmed/32461834
http://dx.doi.org/10.7717/peerj.9145
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