Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function

Abstract

BackgroundRecent 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.MethodsLeft 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.ResultsEven 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.ConclusionsImproving the precision of phenotyping is important for maximizing the yield of genome-wide association studies.

A genome-wide association study reveals that epistasis underlies the pathogenicity of Pectobacterium

“…The discovery potential of GWAS could be weakened by phenotyping errors introduced by imprecise measurement methods ( 21 ). For example, small changes in the measurement of left ventricular ejection fractions (LVEFs) drastically impacted downstream genetic analyses, even within the same population ( 31 ). Introducing measurement noise as little as 7.9% can eliminate all significant genetic associations in GWAS with almost 40,000 individuals, and an increase of 1% in mean absolute error in LVEF had an equivalent impact on GWAS power as a decrease of 10% in the cohort sample size, suggesting that optimizing phenotyping precision is a cost-effective means to improve the power of genetic studies ( 31 ).…”

“…For example, small changes in the measurement of left ventricular ejection fractions (LVEFs) drastically impacted downstream genetic analyses, even within the same population ( 31 ). Introducing measurement noise as little as 7.9% can eliminate all significant genetic associations in GWAS with almost 40,000 individuals, and an increase of 1% in mean absolute error in LVEF had an equivalent impact on GWAS power as a decrease of 10% in the cohort sample size, suggesting that optimizing phenotyping precision is a cost-effective means to improve the power of genetic studies ( 31 ). Thus, the use of precise virulence data from Pectobacterium is important for GWAS analysis, although current lesion size measurement approaches are inadequate for these studies, including the lesion length detection method, the grid method, and the use of digital tools like ImageJ and Assess.…”