Cornwell Adam, Llop Jesse R, Salzman Peter, Rasmussen Niels, Thakar Juilee, Samuelson Andrew V
Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, United States.
Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States.
Front Aging. 2022 Apr 28;3:861701. doi: 10.3389/fragi.2022.861701. eCollection 2022.
The advent of feeding based RNAi in led to an era of gene discovery in aging research. Hundreds of gerogenes were discovered, and many are evolutionarily conserved, raising the exciting possibility that the underlying genetic basis for healthy aging in higher vertebrates could be quickly deciphered. Yet, the majority of putative gerogenes have still only been cursorily characterized, highlighting the need for high-throughput, quantitative assessments of changes in aging. A widely used surrogate measure of aging is lifespan. The traditional way to measure mortality in tracks the deaths of individual animals over time within a relatively small population. This traditional method provides straightforward, direct measurements of median and maximum lifespan for the sampled population. However, this method is time consuming, often underpowered, and involves repeated handling of a set of animals over time, which in turn can introduce contamination or possibly damage increasingly fragile, aged animals. We have previously developed an alternative "Replica Set" methodology, which minimizes handling and increases throughput by at least an order of magnitude. The Replica Set method allows changes in lifespan to be measured for over one hundred feeding-based RNAi clones by one investigator in a single experiment- facilitating the generation of large quantitative phenotypic datasets, a prerequisite for development of biological models at a systems level. Here, we demonstrate through analysis of lifespan experiments simulated that the Replica Set method is at least as precise and accurate as the traditional method in evaluating and estimating lifespan, and requires many fewer total animal observations across the course of an experiment. Furthermore, we show that the traditional approach to lifespan experiments is more vulnerable than the Replica Set method to experimental and measurement error. We find no compromise in statistical power for Replica Set experiments, even for moderate effect sizes, or when simulated experimental errors are introduced. We compare and contrast the statistical analysis of data generated by the two approaches, and highlight pitfalls common with the traditional methodology. Collectively, our analysis provides a standard of measure for each method across comparable parameters, which will be invaluable in both experimental design and evaluation of published data for lifespan studies.
基于喂食的RNA干扰技术的出现开启了衰老研究中的基因发现时代。数百个衰老相关基因被发现，其中许多在进化上是保守的，这引发了一个令人兴奋的可能性，即高等脊椎动物健康衰老的潜在遗传基础可能很快被破解。然而，大多数假定的衰老相关基因仍只是被粗略地描述，这凸显了对衰老变化进行高通量、定量评估的必要性。一个广泛使用的衰老替代指标是寿命。传统的测量死亡率的方法是在相对较小的群体中跟踪个体动物随时间的死亡情况。这种传统方法能直接提供所采样群体的中位寿命和最大寿命的直接测量值。然而，这种方法耗时，往往效力不足，并且需要随着时间对一组动物进行反复处理，这反过来可能会引入污染或可能损害日益脆弱的老龄动物。我们之前开发了一种替代的“复制集”方法，该方法将处理量减到最小，并将通量提高了至少一个数量级。复制集方法允许一位研究人员在单个实验中对一百多个基于喂食的RNA干扰克隆的寿命变化进行测量，这有助于生成大量的定量表型数据集，而这是在系统水平上开发生物学模型的一个先决条件。在这里，我们通过对模拟的寿命实验进行分析表明，复制集方法在评估和估计寿命方面至少与传统方法一样精确和准确，并且在整个实验过程中所需的动物总观察数要少得多。此外，我们表明，寿命实验的传统方法比复制集方法更容易受到实验和测量误差的影响。我们发现复制集实验在统计效力上没有折损，即使对于中等效应大小，或者引入模拟实验误差时也是如此。我们比较并对比了两种方法产生的数据的统计分析，并突出了传统方法常见的陷阱。总体而言，我们的分析为每种方法在可比参数上提供了一个测量标准，这在寿命研究的实验设计和已发表数据的评估中都将是非常宝贵的。
