Flietner Valentin, Heidergott Bernd, den Hollander Frank, Lindner Ines, Parvaneh Azadeh, Strulik Holger
PwC, Bernhard-Wicki-Strasse 8, 80636, Munich, Germany.
Department of Operations Analytics, VU University Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands.
Sci Rep. 2025 Aug 6;15(1):28766. doi: 10.1038/s41598-025-11454-4.
In this paper, we advance the network theory of aging and mortality by developing a causal mathematical model for the mortality rate. First, we show that in large networks, where health deficits accumulate at nodes representing health indicators, the modelling of network evolution with Poisson processes is universal and can be derived from fundamental principles. Second, with the help of two simplifying approximations, which we refer to as mean-field assumption and homogeneity assumption, we provide an analytical derivation of Gompertz law under generic and biologically relevant conditions. Third, we identify for which network parameters Gompertz law is accurate, express the parameters in Gompertz law as a function of the network parameters, and illustrate our computations with simulations and analytic approximations. Our paper is the first to offer a full mathematical explanation of Gompertz law and its limitations based on network theory.
在本文中,我们通过开发死亡率的因果数学模型推进了衰老和死亡率的网络理论。首先,我们表明,在大型网络中,健康缺陷在代表健康指标的节点处累积,用泊松过程对网络演化进行建模具有普遍性,并且可以从基本原理推导得出。其次,借助我们称为平均场假设和同质性假设的两个简化近似,我们在一般且与生物学相关的条件下对冈珀茨定律进行了解析推导。第三,我们确定了冈珀茨定律对哪些网络参数是准确的,将冈珀茨定律中的参数表示为网络参数的函数,并用模拟和解析近似来说明我们的计算。我们的论文首次基于网络理论对冈珀茨定律及其局限性给出了完整的数学解释。