van den Berg Stéphanie M, Service Susan K
Department of Research Methodology, Measurement and Data Analysis, University of Twente, The Netherlands.
Genet Epidemiol. 2012 Dec;36(8):882-9. doi: 10.1002/gepi.21680. Epub 2012 Sep 10.
As data from sequencing studies in humans accumulate, rare genetic variants influencing liability to disease and disorders are expected to be identified. Three simulation studies show that characteristics and properties of diagnostic instruments interact with risk allele frequency to affect the power to detect a quantitative trait locus (QTL) based on a test score derived from symptom counts or questionnaire items. Clinical tests, that is, tests that show a positively skewed phenotypic sum score distribution in the general population, are optimal to find rare risk alleles of large effect. Tests that show a negatively skewed sum score distribution are optimal to find rare protective alleles of large effect. For alleles of small effect, tests with normally distributed item parameters give best power for a wide range of allele frequencies. The item-response theory framework can help understand why an existing measurement instrument has more power to detect risk alleles with either low or high frequency, or both kinds.
随着人类测序研究数据的积累，预计会识别出影响疾病易感性的罕见基因变异。三项模拟研究表明，诊断工具的特征和属性与风险等位基因频率相互作用，会影响基于症状计数或问卷项目得出的测试分数来检测数量性状位点（QTL）的效能。临床测试，即在一般人群中表现出正偏态表型总分分布的测试，最适合发现具有大效应的罕见风险等位基因。表现出负偏态总分分布的测试最适合发现具有大效应的罕见保护性等位基因。对于效应较小的等位基因，具有正态分布项目参数的测试在广泛的等位基因频率范围内具有最佳效能。项目反应理论框架有助于理解为什么现有的测量工具在检测低频或高频或两种频率的风险等位基因时具有更高的效能。
