Clemmer John S, Hester Robert L, Pruett W Andrew
Department of Physiology and Biophysics, Center for Computational Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
Interface Focus. 2018 Feb 6;8(1):20160134. doi: 10.1098/rsfs.2016.0134. Epub 2017 Dec 15.
Salt sensitivity, with or without concomitant hypertension, is associated with increased mortality. Reduced functional renal mass plays an important role in causing salt-sensitive hypertension for many individuals. Factors that are important in the condition of decreased renal mass and how they affect blood pressure (BP) or salt sensitivity are unclear. We used HumMod, an integrative mathematical model of human physiology, to create a heterogeneous population of 1000 virtual patients by randomly varying physiological parameters. We examined potential physiological mechanisms responsible for the change in BP in response to high-salt diet (8× change in salt intake for three weeks) with full kidney mass and again after the removal of one kidney in the same group of virtual patients. We used topological data analysis (TDA), a clustering algorithm tool, to analyse the large dataset and separate patient subpopulations. TDA distinguished five unique clusters of salt-sensitive individuals (more than 15 mmHg change in BP with increased salt). While these clusters had similar BP responses to salt, different collections of variables were responsible for their salt sensitivity, e.g. greater reductions in glomerular filtration rate (GFR) or impairments in the renin-angiotensin system. After simulating uninephrectomy in these virtual patients, the three most salt-sensitive clusters were associated with a blunted increase in renal blood flow (RBF) and higher increase in loop and distal sodium reabsorption when compared with the salt-resistant population. These data suggest that the suppression of sodium reabsorption and renin-angiotensin system is key for salt resistance, and RBF in addition to GFR may be an important factor when considering criteria for kidney donors. Here, we show that in our model of human physiology, different derangements result in the same phenotype. While these concepts are known in the experimental community, they were derived here by considering only the data obtained from our virtual experiments. These methodologies could potentially be used to discover patterns in patient sensitivity to dietary change or interventions and could be a revolutionary tool in personalizing medicine.
盐敏感性，无论是否伴有高血压，都与死亡率增加相关。对于许多个体而言，功能性肾质量的降低在导致盐敏感性高血压方面起着重要作用。肾质量降低情况下的重要因素以及它们如何影响血压（BP）或盐敏感性尚不清楚。我们使用HumMod（一种人体生理学综合数学模型），通过随机改变生理参数创建了1000名虚拟患者的异质群体。我们研究了在全肾质量时以及在同一组虚拟患者切除一侧肾脏后，对高盐饮食（盐摄入量在三周内变化8倍）时血压变化负责的潜在生理机制。我们使用拓扑数据分析（TDA）（一种聚类算法工具）来分析大型数据集并分离患者亚群。TDA区分出了五个独特的盐敏感个体聚类（盐增加时血压变化超过15 mmHg）。虽然这些聚类对盐的血压反应相似，但不同的变量组合导致了它们的盐敏感性，例如肾小球滤过率（GFR）的更大降低或肾素 - 血管紧张素系统的损伤。在这些虚拟患者中模拟单侧肾切除术后，与盐抵抗人群相比，三个盐敏感性最高的聚类与肾血流量（RBF）的钝性增加以及髓袢和远曲小管钠重吸收的更高增加相关。这些数据表明，抑制钠重吸收和肾素 - 血管紧张素系统是盐抵抗的关键，并且在考虑肾脏供体标准时，除了GFR之外，RBF可能是一个重要因素。在这里，我们表明在我们的人体生理学模型中，不同的紊乱会导致相同的表型。虽然这些概念在实验领域是已知的，但它们是在这里仅通过考虑从我们的虚拟实验中获得的数据而得出的。这些方法有可能用于发现患者对饮食变化或干预的敏感性模式，并且可能成为个性化医疗中的一种革命性工具。
