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首页> 外文期刊>The journals of gerontology.Series A. Biological sciences and medical sciences >Biomarkers for Aging Identified in Cross-sectional Studies Tend to Be Non-causative
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Biomarkers for Aging Identified in Cross-sectional Studies Tend to Be Non-causative

机译：用于横截面研究中鉴定的衰老的生物标志物往往是不造成的

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Biomarkers are important tools for diagnosis, prognosis, and identification of the causal factors of physiological conditions. Biomarkers are typically identified by correlating biological measurements with the status of a condition in a sample of subjects. Cross-sectional studies sample subjects at a single timepoint, whereas longitudinal studies follow a cohort through time. Identifying biomarkers of aging is subject to unique challenges. Individuals who age faster have intrinsically higher mortality rates and so are preferentially lost over time, in a phenomenon known as cohort selection. In this article, we use simulations to show that cohort selection biases cross-sectional analysis away from identifying causal loci of aging, to the point where cross-sectional studies are less likely to identify loci that cause aging than if loci had been chosen at random. We go on to show this bias can be corrected by incorporating correlates of mortality identified from longitudinal studies, allowing cross-sectional studies to effectively identify the causal factors of aging.
机译：生物标志物是诊断，预后和鉴定生理条件因因素的重要工具。通常通过将生物测量与受试者样本中的状态的状态相关性来鉴定生物标志物。横截面研究在单个时间点处的样本受试者，而纵向研究通过时间遵循队列。鉴定老龄化的生物标志物受到独特挑战的影响。年龄更快的人具有内在的死亡率，因此优先丢失随着时间的推移，在称为队列选择的现象中。在本文中，我们使用模拟表明，群组选择偏离识别老化的因果基因率的横截面分析，到横截面研究不太可能识别导致老化的基因座，而不是如果在随机中选择了锁定的终点。我们继续展示通过掺入从纵向研究中鉴定的死亡率的相关性来校正该偏差，从而允许横截面研究有效地识别老化的因果区。

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