从生存曲线分析衰老的类型及不同抗衰老方法的影响

Research on the biology of aging has been conducted for more than a century, and the age of death, as an unambiguously defined, universally occurring event, is the most commonly used phenotype. Changes in lifespan between groups with identical genetic background and environmental conditions between groups with identical genetic background and environmental conditions except for one defined difference can be used to demonstrate the effect of this factor on survival. Survival analysis is a key component in research on aging. Traditionally in research on aging, survival data from lifespan experiments are only analyzed in the original study and there have been very few studies combining survival data from multiple studies. Use beyond the primary study is generally limited to comparing changes in mean lifespan or similar high-level summary statistics. This is not least due to the fact that survival data from lifespan experiments have not been publicly accessible. A secondfactor complicating meta-analysis is that survival is influenced by many environmental factors and these are not standardized across different laboratories. Thus, meta-analyses are limited to either large enough subsets of data with identical conditions or involve the application of methods accounting for varying additional factors. Here we use a large set of survival curves from various studies to address the mechanisms of different interventions in aging, which are beyond the scope of individual studies. With the help of key algorithms in bioinformatics, we have focused our analyses of different aging interventions such as caloric restriction, exercise, drugs and environment in various living organisms including yeast, nematodes, drosophila, mice, primates and humanbeings. We compare the difference in the impact of various anti-aging strategies on the same model organism, then we explore whether the effect of one specific anti-aging strategy on different organisms are universally. Our investigation use statistical data analysis methods to reveal the aging rules reflected by survival cures, combined with the possible biological mechanisms in original literatures, we aim to finally find effective and reasonable anti-aging strategy. The project effectively combine theoretical analysis with biology experiment, avoiding the limitation of simple calculation or simple experiment methods, so as to guarantee smooth implementation of both theoretical calculation and experiment research, which will lay a solid foundation to achieve expected results.

本课题旨在利用生物信息学关键算法和分析手段对国内外衰老研究中的模式动物生存曲线进行系统、全方位的聚类分析，探讨不同模式动物的衰老类型及不同抗衰老因素对衰老的影响及生物学机制。通过广泛查阅相关文献、搜集衰老研究中模式动物的生存曲线，利用Matlab和R软件还原生存数据并重新拟合，对拟合得到的生存曲线进行非监督学习，建立数据库，分析模式动物在正常实验条件下的生存曲线并比较不同物种衰老类型之间的差异和规律。为进一步揭示不同抗衰老因素干预衰老过程的机制，我们拟在横向比较不同抗衰老因素对同种模式动物生存曲线影响类型的区别基础上，同时纵向比较同种抗衰老因素对生存曲线的影响在不同模型动物中是否具有普适性，利用统计学数据分析手段揭示生存曲线反映的衰老规律，结合原始文献中的生物学机制提出合理假设，并设计衰老相关实验对其进行验证，以探究有效、合理的抗衰老策略，为政府相关部门制定养老政策和策略提供科学依据。

随着世界各国人口老龄化步伐的加快，衰老机制的研究及抗衰老干预措施的开发日益成为生物医学领域的重要课题之一。生存曲线因其可直观表达同级生物的完整存活过程，常用于观察饮食、基因、药物和锻炼等多种干预措施对寿命的影响。国内外已有大量研究报道不同衰老干预措施能够延长多种模式生物的寿命，然而这些衰老干预措施的差异仍缺乏系统研究。本课题的研究以衰老研究领域热点模式生物线虫和果蝇为对象，搜集1990年以来国内外正式发表的寿命试验研究文献及其涉及的生存曲线，利用荟萃分析比较不同衰老干预措施与生存曲线变化类型间的关系，并结合衰老干预措施的生物学作用探讨其延寿机制。研究表明，热量限制和基因干预比药物更能有效地延长线虫和果蝇的整体寿命，并且热量限制可以改善线虫的衰老类型。按照药理作用对药物进一步分类，类内分析结果表明，尽管控制血糖类药物和抗氧化剂对生存曲线的改善总体增益不是最大，但是它们可以通过改善年龄结构对整个群体产生显著增益。抗癫痫类药物虽然对寿命的总体增益较大，但是只能延长少数个体的最大寿命，对种群大多数个体的寿命延长程度并不显著。控制血糖类药物和抗氧化剂是潜在的热量限制拟效剂。基因干预分析结果表明，寿命增益程度较大且能改善种群年龄结构的基因或者信号通路与热量限制相关。综上所述，热量限制或热量限制拟效剂是最健康合理的衰老干预措施。为了进一步探究热量限制延寿机制，我们设计了6种不同的饮食干预方式来定量研究单独限制热量或食量对小鼠衰老表征与关键基因、蛋白表达水平的改变。结果表明，低热量正常食量组小鼠寿命最长，限制食量可以改善健康寿命但会减弱热量限制的延寿作用。我们的研究结果为最终发现有效的衰老干预措施及制定健康合理的抗衰老策略奠定了科学基础。