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通过非线性心率动力学分析识别心血管风险:从小鼠到人类的转化生物标志物。

Identifying Cardiovascular Risk by Nonlinear Heart Rate Dynamics Analysis: Translational Biomarker from Mice to Humans.

作者信息

Hager Torben, Agorastos Agorastos, Ögren Sven Ove, Stiedl Oliver

机构信息

Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands.

Division of Neurosciences, II. Department of Psychiatry, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece.

出版信息

Brain Sci. 2025 Mar 14;15(3):306. doi: 10.3390/brainsci15030306.

Abstract

BACKGROUND

The beat-by-beat fluctuation of heart rate (HR) in its temporal sequence (HR dynamics) provides information on HR regulation by the autonomic nervous system (ANS) and its dysregulation in pathological states. Commonly, linear analyses of HR and its variability (HRV) are used to draw conclusions about pathological states despite clear statistical and translational limitations.

OBJECTIVE

The main aim of this study was to compare linear and nonlinear HR measures, including detrended fluctuation analysis (DFA), based on ECG recordings by radiotelemetry in C57BL/6N mice to identify pathological HR dynamics.

METHODS

We investigated different behavioral and a wide range of pharmacological interventions which alter ANS regulation through various peripheral and/or central mechanisms including receptors implicated in psychiatric disorders. This spectrum of interventions served as a reference system for comparison of linear and nonlinear HR measures to identify pathological states.

RESULTS

Physiological HR dynamics constitute a self-similar, scale-invariant, fractal process with persistent intrinsic long-range correlations resulting in physiological DFA scaling coefficients of α~1. Strongly altered DFA scaling coefficients (α ≠ 1) indicate pathological states of HR dynamics as elicited by (1) parasympathetic blockade, (2) parasympathetic overactivation and (3) sympathetic overactivation but not inhibition. The DFA scaling coefficients are identical in mice and humans under physiological conditions with identical pathological states by defined pharmacological interventions.

CONCLUSIONS

Here, we show the importance of tonic vagal function for physiological HR dynamics in mice, as reported in humans. Unlike linear measures, DFA provides an important translational measure that reliably identifies pathological HR dynamics based on altered ANS control by pharmacological interventions. Central ANS dysregulation represents a likely mechanism of increased cardiac mortality in psychiatric disorders.

摘要

背景

心率(HR)在其时间序列中的逐搏波动(HR动态)提供了有关自主神经系统(ANS)对HR调节及其在病理状态下失调的信息。尽管存在明显的统计和转化局限性,但通常仍使用HR及其变异性(HRV)的线性分析来得出关于病理状态的结论。

目的

本研究的主要目的是比较基于C57BL/6N小鼠无线电遥测心电图记录的线性和非线性HR测量方法,包括去趋势波动分析(DFA),以识别病理性HR动态。

方法

我们研究了不同的行为和广泛的药理干预措施,这些措施通过各种外周和/或中枢机制改变ANS调节,包括与精神疾病相关的受体。这一系列干预措施作为比较线性和非线性HR测量方法以识别病理状态的参考系统。

结果

生理HR动态构成一个自相似、尺度不变的分形过程,具有持续的内在长程相关性,导致生理DFA标度系数α~1。DFA标度系数的强烈改变(α≠1)表明HR动态的病理状态是由(1)副交感神经阻滞、(2)副交感神经过度激活和(3)交感神经过度激活而非抑制引起的。通过定义的药理干预,在生理条件下处于相同病理状态的小鼠和人类中,DFA标度系数是相同的。

结论

在此,我们证明了在小鼠中,如在人类中所报道的,紧张性迷走神经功能对生理HR动态的重要性。与线性测量方法不同,DFA提供了一种重要的转化测量方法,可根据药理干预引起的ANS控制改变可靠地识别病理性HR动态。中枢ANS失调可能是精神疾病中心脏死亡率增加的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14f2/11940095/022e1c350c1e/brainsci-15-00306-g001.jpg

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