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Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function
BACKGROUND: Recent studies have leveraged quantitative traits from imaging to amplify the power of genome-wide association studies (GWAS) to gain further insights into the biology of diseases and traits. However, measurement imprecision is intrinsic to phenotyping and can impact downstream genetic a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949184/ https://www.ncbi.nlm.nih.gov/pubmed/36824841 http://dx.doi.org/10.1101/2023.02.16.23286058 |
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author | Vukadinovic, Milos Renjith, Gauri Yuan, Victoria Kwan, Alan Cheng, Susan C. Li, Debiao Clarke, Shoa L. Ouyang, David |
author_facet | Vukadinovic, Milos Renjith, Gauri Yuan, Victoria Kwan, Alan Cheng, Susan C. Li, Debiao Clarke, Shoa L. Ouyang, David |
author_sort | Vukadinovic, Milos |
collection | PubMed |
description | BACKGROUND: Recent studies have leveraged quantitative traits from imaging to amplify the power of genome-wide association studies (GWAS) to gain further insights into the biology of diseases and traits. However, measurement imprecision is intrinsic to phenotyping and can impact downstream genetic analyses. METHODS: Left ventricular ejection fraction (LVEF), an important but imprecise quantitative imaging measurement, was examined to assess the impact of precision of phenotype measurement on genetic studies. Multiple approaches to obtain LVEF, as well as simulated measurement noise, were evaluated with their impact on downstream genetic analyses. RESULTS: Even within the same population, small changes in the measurement of LVEF drastically impacted downstream genetic analyses. Introducing measurement noise as little as 7.9% can eliminate all significant genetic associations in an GWAS with almost forty thousand individuals. An increase of 1% in mean absolute error (MAE) in LVEF had an equivalent impact on GWAS power as a decrease of 10% in the cohort sample size, suggesting optimizing phenotyping precision is a cost-effective way to improve power of genetic studies. CONCLUSIONS: Improving the precision of phenotyping is important for maximizing the yield of genome-wide association studies. |
format | Online Article Text |
id | pubmed-9949184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-99491842023-02-24 Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function Vukadinovic, Milos Renjith, Gauri Yuan, Victoria Kwan, Alan Cheng, Susan C. Li, Debiao Clarke, Shoa L. Ouyang, David medRxiv Article BACKGROUND: Recent studies have leveraged quantitative traits from imaging to amplify the power of genome-wide association studies (GWAS) to gain further insights into the biology of diseases and traits. However, measurement imprecision is intrinsic to phenotyping and can impact downstream genetic analyses. METHODS: Left ventricular ejection fraction (LVEF), an important but imprecise quantitative imaging measurement, was examined to assess the impact of precision of phenotype measurement on genetic studies. Multiple approaches to obtain LVEF, as well as simulated measurement noise, were evaluated with their impact on downstream genetic analyses. RESULTS: Even within the same population, small changes in the measurement of LVEF drastically impacted downstream genetic analyses. Introducing measurement noise as little as 7.9% can eliminate all significant genetic associations in an GWAS with almost forty thousand individuals. An increase of 1% in mean absolute error (MAE) in LVEF had an equivalent impact on GWAS power as a decrease of 10% in the cohort sample size, suggesting optimizing phenotyping precision is a cost-effective way to improve power of genetic studies. CONCLUSIONS: Improving the precision of phenotyping is important for maximizing the yield of genome-wide association studies. Cold Spring Harbor Laboratory 2023-02-18 /pmc/articles/PMC9949184/ /pubmed/36824841 http://dx.doi.org/10.1101/2023.02.16.23286058 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Vukadinovic, Milos Renjith, Gauri Yuan, Victoria Kwan, Alan Cheng, Susan C. Li, Debiao Clarke, Shoa L. Ouyang, David Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function |
title | Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function |
title_full | Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function |
title_fullStr | Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function |
title_full_unstemmed | Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function |
title_short | Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function |
title_sort | impact of measurement imprecision on genetic association studies of cardiac function |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949184/ https://www.ncbi.nlm.nih.gov/pubmed/36824841 http://dx.doi.org/10.1101/2023.02.16.23286058 |
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