Department of Physiology, Medical College of Wisconsin , Milwaukee, Wisconsin.
Center of Systems Molecular Medicine, Medical College of Wisconsin , Milwaukee, Wisconsin.
Physiol Genomics. 2018 Jun 1;50(6):440-447. doi: 10.1152/physiolgenomics.00034.2018. Epub 2018 Mar 30.
Studies exploring the development of hypertension have traditionally been unable to distinguish which of the observed changes are underlying causes from those that are a consequence of elevated blood pressure. In this study, a custom-designed servo-control system was utilized to precisely control renal perfusion pressure to the left kidney continuously during the development of hypertension in Dahl salt-sensitive rats. In this way, we maintained the left kidney at control blood pressure while the right kidney was exposed to hypertensive pressures. As each kidney was exposed to the same circulating factors, differences between them represent changes induced by pressure alone. RNA sequencing analysis identified 1,613 differently expressed genes affected by renal perfusion pressure. Three pathway analysis methods were applied, one a novel approach incorporating arterial pressure as an input variable allowing a more direct connection between the expression of genes and pressure. The statistical analysis proposed several novel pathways by which pressure affects renal physiology. We confirmed the effects of pressure on p-Jnk regulation, in which the hypertensive medullas show increased p-Jnk/Jnk ratios relative to the left (0.79 ± 0.11 vs. 0.53 ± 0.10, P < 0.01, n = 8). We also confirmed pathway predictions of mitochondrial function, in which the respiratory control ratio of hypertensive vs. control mitochondria are significantly reduced (7.9 ± 1.2 vs. 10.4 ± 1.8, P < 0.01, n = 6) and metabolomic profile, in which 14 metabolites differed significantly between hypertensive and control medullas ( P < 0.05, n = 5). These findings demonstrate that subtle differences in the transcriptome can be used to predict functional changes of the kidney as a consequence of pressure elevation.
传统上,探索高血压发展的研究一直无法区分观察到的变化中哪些是潜在的原因,哪些是血压升高的结果。在这项研究中,我们使用定制的伺服控制系统,在 Dahl 盐敏感型大鼠高血压发展过程中,持续精确地控制左肾的肾灌注压。通过这种方式,我们在维持左肾控制血压的同时,使右肾暴露于高血压压力下。由于每个肾脏都暴露在相同的循环因素下,它们之间的差异代表仅由压力引起的变化。RNA 测序分析确定了 1613 个受肾灌注压影响的差异表达基因。我们应用了三种途径分析方法,其中一种是将动脉压作为输入变量的新方法,使基因表达与压力之间的连接更加直接。统计分析提出了几种压力影响肾脏生理学的新途径。我们证实了压力对 p-Jnk 调节的影响,其中高血压髓质相对于左肾(0.79±0.11 对 0.53±0.10,P<0.01,n=8)表现出增加的 p-Jnk/Jnk 比值。我们还证实了途径预测的线粒体功能,其中高血压与对照线粒体的呼吸控制比显著降低(7.9±1.2 对 10.4±1.8,P<0.01,n=6)和代谢组学谱,其中 14 种代谢物在高血压和对照髓质之间差异显著(P<0.05,n=5)。这些发现表明,转录组中的细微差异可用于预测肾脏因压力升高而导致的功能变化。