Abstract

The article describes the history of studies of survival data carried out at the Research Institute of Physico-Chemical Biology under the leadership of Academician V. P. Skulachev from 1970s until present, with special emphasis on the last decade. The use of accelerated failure time (AFT) model and analysis of coefficient of variation of lifespan (CV_LS) in addition to the Gompertz methods of analysis, allows to assess survival curves for the presence of temporal scaling (i.e., manifestation of accelerated aging), without changing the shape of survival curve with the same coefficient of variation. A modification of the AFT model that uses temporal scaling as the null hypothesis made it possible to distinguish between the quantitative and qualitative differences in the dynamics of aging. It was also shown that it is possible to compare the data on the survival of species characterized by the survival curves of the original shape (i.e., “flat” curves without a pronounced increase in the probability of death with age typical of slowly aging species), when considering the distribution of lifespan as a statistical random variable and comparing parameters of such distribution. Thus, it was demonstrated that the higher impact of mortality caused by external factors (background mortality) in addition to the age-dependent mortality, the higher the disorder of mortality values and the greater its difference from the calculated value characteristic of developed countries (15-20%). For comparison, CV_LS for the Paraguayan Ache Indians is 100% (57% if we exclude prepuberty individuals as suggested by Jones et al.). According to Skulachev, the next step is considering mortality fluctuations as a measure for the disorder of survival data. Visual evaluation of survival curves can already provide important data for subsequent analysis. Thus, Sokolov and Severin [1] found that mutations have different effects on the shape of survival curves. Type I survival curves generally retains their standard convex rectangular shape, while type II curves demonstrate a sharp increase in the mortality which makes them similar to a concave exponential curve with a stably high mortality rate. It is noteworthy that despite these differences, mutations in groups I and II are of a similar nature. They are associated (i) with “DNA metabolism” (DNA repair, transcription, and replication); (ii) protection against oxidative stress, associated with the activity of the transcription factor Nrf2, and (iii) regulation of proliferation, and (or these categories may overlap). However, these different mutations appear to produce the same result at the organismal level, namely, accelerated aging according to the Gompertz’s law. This might be explained by the fact that all these mutations, each in its own unique way, either reduce the lifespan of cells or accelerate their transition to the senescent state, which supports the concept of Skulachev on the existence of multiple pathways of aging (chronic phenoptosis).

中文翻译：

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计算衰老：正常和病理的生存曲线分析、死亡率动态波动、寿命分布特征和寿命变异指标

摘要

本文介绍了理化生物学研究所在 V. P. Skulachev 院士的领导下从 20 世纪 70 年代至今进行的生存数据研究的历史，特别重点介绍了过去十年。除了 Gompertz 分析方法之外，使用加速失效时间 (AFT) 模型和寿命变异系数 (CV _LS ) 分析，可以评估存在时间尺度的生存曲线（即加速老化的表现） ，不改变具有相同变异系数的生存曲线的形状。使用时间尺度作为原假设的 AFT 模型的修改使得区分衰老动态的定量和定性差异成为可能。研究还表明，可以比较以原始形状的生存曲线为特征的物种的生存数据（即，随着缓慢衰老物种的典型年龄，死亡概率没有明显增加的“平坦”曲线） ，将寿命分布视为统计随机变量并比较该分布的参数时。由此可见，除年龄依赖性死亡率外，外部因素（背景死亡率）对死亡率的影响越大，死亡率值的紊乱程度越高，与发达国家计算值特征的差异越大（15 -20%）。作为比较，巴拉圭 Ache 印第安人的 CV _LS为 100%（如果我们按照 Jones 等人的建议排除青春期前个体，则为 57%）。斯库拉切夫表示，下一步是考虑将死亡率波动作为生存数据紊乱的衡量标准。生存曲线的目视评估已经可以为后续分析提供重要数据。因此，索科洛夫和塞维林 [ 1]发现突变对生存曲线的形状有不同的影响。 I型生存曲线通常保持其标准的凸矩形形状，而II型曲线则显示死亡率急剧增加，这使得它们类似于具有稳定的高死亡率的凹指数曲线。值得注意的是，尽管存在这些差异，I 组和 II 组的突变具有相似的性质。它们与 (i) 与“DNA 代谢”（DNA 修复、转录和复制）有关； (ii) 防止与转录因子 Nrf2 的活性相关的氧化应激，以及 (iii) 增殖调节，以及（或者这些类别可能重叠）。然而，这些不同的突变似乎在有机体水平上产生相同的结果，即根据冈珀茨定律加速衰老。这可能是通过这样一个事实来解释的：所有这些突变，每种突变都以其独特的方式，要么缩短细胞的寿命，要么加速它们向衰老状态的转变，这支持了斯库拉切夫关于衰老的多种途径（慢性衰老）存在的概念。死亡）。