Systemic inflammation and circadian rhythm of cardiac autonomic modulation

Xian Li, Michele L. Shaffer, Sol M. Rodríguez-Colón, Fan He, Edward O. Bixler, Alexandros N. Vgontzas, Deborah L. Wolbrette, Chuntao Wu, Richard W. Ball, Duanping Liao

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11 Scopus citations


Systemic inflammation (SI) is associated with impairment of cardiac autonomic modulation (CAM), which is associated with cardiac disease. However, there is limited data about SI on CAM circadian pattern, which this study aimed to investigate in a middle-aged sample. C-reactive protein (CRP) was used as a SI marker. We performed HRV analysis on each 5-min segment RRs from a 24-h 12-lead ECG to obtain time and frequency domain HRV indices as measures of CAM. The circadian pattern of CAM was analyzed by a two-stage modeling. Stage one, for each individual we fit a cosine periodic model based on the 288 segments of 5-min HRV data to produce three individual-level cosine parameters that quantity the circadian pattern: mean (M), amplitude (Â), and acrophase time (Θ), measure the overall average, the amplitude of the oscillation, and the timing of the highest oscillation, respectively. Stage two, we used random-effects-meta-analysis to summarize the effects of CRP on the three circadian parameters obtained in stage one. CRP was adversely associated with lower M of log-HF, log-LF, SDNN, and RMSSD [β (SE): -0.22 (0.07) ms2, -0.20 (0.06) ms2, -3.62 (0.99) ms, and -2.32 (0.73) ms, respectively, with all p-values <0.01]. More importantly, CRP was also adversely associated with lower  of SDNN and RMSSD [β (SE): -0.84 (0.44) ms and -0.86 (0.38) ms, respectively, both p-values <0.05]. SI is adversely associated with circadian pattern of CAM, suggesting that the cardiac risk associated with SI may be partially mediated via inflammation-related changes in CAM.

Original languageEnglish (US)
Pages (from-to)72-76
Number of pages5
JournalAutonomic Neuroscience: Basic and Clinical
Issue number1-2
StatePublished - Jul 5 2011

All Science Journal Classification (ASJC) codes

  • Endocrine and Autonomic Systems
  • Clinical Neurology
  • Cellular and Molecular Neuroscience


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