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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...

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Detalles Bibliográficos
Autores principales: Vukadinovic, Milos, Renjith, Gauri, Yuan, Victoria, Kwan, Alan, Cheng, Susan C., Li, Debiao, Clarke, Shoa L., Ouyang, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
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
Descripción
Sumario: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.