Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
J Hum Genet. 2013 Jul;58(7):461-6. doi: 10.1038/jhg.2013.23. Epub 2013 Mar 28.
Studies of multiple measures of a quantitative trait can have greater precision and thus statistical power compared with single-measure studies, but this has rarely been studied in the relation to quantitative trait measurement error models in genetic association studies. Using estimated glomerular filtration rate (eGFR), a quantitative measure of kidney function, as an example we constructed measurement error models of a quantitative trait with systematic and random error components. We then examined the effects on precision of the parameter estimate between genetic loci and eGFR, resulting from varying the correlation and contribution of the error components. We also compared the empirical results from three genome-wide association studies (GWAS) of kidney function in 9049 European Americans: a single measure model, a three-measure model of the same biomarker of kidney function and a six-measure model of different biomarkers of kidney function. Simulations showed that given the same amount of overall errors, inclusion of measures with less correlated systematic errors led to greater gain in precision. The empirical GWAS results confirmed that both the three- and six-measure models detected more eGFR-associated genomic loci with stronger statistical association than the single-measure model despite some heterogeneity among the measures. Multiple measures of a quantitative trait can increase the statistical power of a study without additional participant recruitment. However, careful attention must be paid to the correlation of systematic errors and inconsistent associations when different biomarkers or methods are used to measure the quantitative trait.
对定量性状的多种测量方法的研究与单一测量研究相比，可以具有更高的精度和统计效力，但在遗传关联研究中，这在定量性状测量误差模型方面很少得到研究。我们以肾小球滤过率估计值（eGFR）为例，构建了具有系统误差和随机误差分量的定量性状测量误差模型。然后，我们考察了遗传位点与 eGFR 之间参数估计的精度变化，这种变化是由误差分量的相关性和贡献的变化引起的。我们还比较了三个全基因组关联研究（GWAS）在 9049 名欧洲裔美国人中肾功能的经验结果：单一测量模型、相同肾功能生物标志物的三测量模型和不同肾功能生物标志物的六测量模型。模拟结果表明，在相同的总体误差下，纳入系统误差相关性较低的测量方法可以获得更高的精度增益。实证 GWAS 结果证实，尽管测量值之间存在一定的异质性，但三测量模型和六测量模型都检测到了与 eGFR 相关的基因组区域，这些区域的统计学关联更强，比单一测量模型更具统计学意义。在不增加参与者招募的情况下，对定量性状进行多次测量可以提高研究的统计效力。然而，在使用不同的生物标志物或方法来测量定量性状时，必须仔细注意系统误差的相关性和不一致的关联。
