CIG - Interdepartmental Centre L Galvani, University of Bologna, Bologna, Italy.
Curr Pharm Des. 2010;16(7):802-13. doi: 10.2174/138161210790883660.
Human aging and longevity are complex and multi-factorial traits that result from a combination of environmental, genetic, epigenetic and stochastic factors, each contributing to the overall phenotype. The multi-factorial process of aging acts at different levels of complexity, from molecule to cell, from organ to organ systems and finally to organism, giving rise to the dynamic "aging mosaic". At present, an increasing amount of experimental data on genetics, genomics, proteomics and other -omics are available thanks to new high-throughput technologies but a comprehensive model for the study of human aging and longevity is still lacking. Systems biology represents a strategy to integrate and quantify the existing knowledge from different sources into predictive models, to be later tested and then implemented with new experimental data for validation and refinement in a recursive process. The ultimate goal is to compact the new acquired knowledge into a single picture, ideally able to characterize the phenotype at systemic/organism level. In this review we will briefly discuss the aging phenotype in a systems biology perspective, showing four specific examples at different levels of complexity, from a systemic process (inflammation) to a cascade-process pathways (coagulation) and from cellular organelle (proteasome) to single gene-network (PON-1), which could also represent targets for anti-aging strategies.
人类衰老和长寿是复杂的多因素特征，是环境、遗传、表观遗传和随机因素综合作用的结果，每个因素都对整体表型有贡献。衰老的多因素过程在不同的复杂层次上起作用，从分子到细胞，从器官到器官系统，最后到生物体，产生动态的“衰老马赛克”。目前，由于高通量新技术的出现，越来越多的关于遗传学、基因组学、蛋白质组学和其他组学的实验数据可用，但仍缺乏全面的人类衰老和长寿研究模型。系统生物学代表了一种策略，即将来自不同来源的现有知识整合和量化为预测模型，然后用新的实验数据进行测试和实施，以验证和细化，在一个递归过程中。最终目标是将新获得的知识压缩到一个单一的画面中，理想情况下能够在系统/生物体水平上描述表型。在这篇综述中，我们将从系统生物学的角度简要讨论衰老表型，展示四个不同复杂层次的具体例子，从系统过程（炎症）到级联过程途径（凝血），从细胞细胞器（蛋白酶体）到单个基因网络（PON-1），这些也可以作为抗衰老策略的靶点。
