ClinCirc identifies alterations of the circadian peripheral oscillator in critical care patients
Peter S. Cunningham, Gareth B. Kitchen, Callum Jackson, Stavros Papachristos, Thomas Springthorpe, David van Dellen, Julie Gibbs, Timothy W. Felton, Anthony J. Wilson, Jonathan Bannard-Smith, Martin K. Rutter, Thomas House, Paul Dark, Titus Augustine, Ozgur E. Akman, Andrew L. Hazel, John F. Blaikley
Peter S. Cunningham, Gareth B. Kitchen, Callum Jackson, Stavros Papachristos, Thomas Springthorpe, David van Dellen, Julie Gibbs, Timothy W. Felton, Anthony J. Wilson, Jonathan Bannard-Smith, Martin K. Rutter, Thomas House, Paul Dark, Titus Augustine, Ozgur E. Akman, Andrew L. Hazel, John F. Blaikley
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Clinical Research and Public Health Inflammation

ClinCirc identifies alterations of the circadian peripheral oscillator in critical care patients

Abstract

Background Assessing circadian rhythmicity from infrequently sampled data is challenging; however, these types of data are often encountered when measuring circadian transcripts in hospitalized patients.Methods We present ClinCirc. This method combines 2 existing mathematical methods (Lomb-Scargle periodogram and cosinor) sequentially and is designed to measure circadian oscillations from infrequently sampled clinical data. The accuracy of this method was compared against 9 other methods using simulated and frequently sampled biological data. ClinCirc was then evaluated in 13 intensive care unit (ICU) patients as well as in a separate cohort of 29 kidney-transplant recipients. Finally, the consequences of circadian alterations were investigated in a retrospective cohort of 726 kidney-transplant recipients.Results ClinCirc had comparable performance to existing methods for analyzing simulated data or clock transcript expression of healthy volunteers. It had improved accuracy compared with the cosinor method in evaluating circadian parameters in PER2:luc cell lines. In ICU patients, it was the only method investigated to suggest that loss of circadian oscillations in the peripheral oscillator was associated with inflammation, a feature widely reported in animal models. Additionally, ClinCirc was able to detect other circadian alterations, including a phase shift following kidney transplantation that was associated with the administration of glucocorticoids. This phase shift could explain why a significant complication of kidney transplantation (delayed graft dysfunction) oscillates according to the time of day kidney transplantation is performed.Conclusion ClinCirc analysis of the peripheral oscillator reveals important clinical associations in hospitalized patients.Funding UK Research and Innovation (UKRI), National Institute of Health Research (NIHR), Engineering and Physical Sciences Research Council (EPSRC), National Institute on Academic Anaesthesia (NIAA), Asthma+Lung UK, Kidneys for Life.

Authors

Peter S. Cunningham, Gareth B. Kitchen, Callum Jackson, Stavros Papachristos, Thomas Springthorpe, David van Dellen, Julie Gibbs, Timothy W. Felton, Anthony J. Wilson, Jonathan Bannard-Smith, Martin K. Rutter, Thomas House, Paul Dark, Titus Augustine, Ozgur E. Akman, Andrew L. Hazel, John F. Blaikley

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Figure 1

Performance of ClinCirc in detecting circadian rhythmicity.

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Performance of ClinCirc in detecting circadian rhythmicity. (A) Flow dia...
(A) Flow diagram depicting how cosinor analysis was combined with L-SP to create ClinCirc. (B) Sampling periods of 24 hours and (C) 48 hours were used to characterize the sensitivity and specificity of 10 mathematical methods on infrequently (every 4 hours) sampled data. Sensitivity was calculated using a waveform created following the addition of 40% noise (Supplemental Methods) to a sinusoidal wave. Specificity was calculated from a straight line (5,000 simulations). Data are represented as mean ± SD. (D) Two data sets measuring clock-gene expression in healthy human volunteers were reanalyzed using the same 10 mathematical methods. The average number of clock genes per volunteer that each method detected as having a circadian rhythm is shown. Data are represented as mean ± SEM. (E) ClinCirc was used to evaluate circadian rhythmicity of clock genes in ICU patients (n = 13) as well as in healthy volunteers (n = 23). Bar chart shows the proportion of subjects in which ClinCirc detected a circadian oscillation per clock gene. Heatmap shows which subjects had a detected circadian oscillation. Each subject is represented by a row, and a filled square represents a detected circadian oscillation. (F) ClinCirc was used to evaluate circadian rhythmicity of clock genes in kidney-transplant recipients at 0 to 24 hours after transplantation (n = 22; 24 hours after transplant) or 48 to 72 hours after transplantation (n = 7; 72 hours after transplant) as well as in healthy volunteers (n = 23). Bar chart shows the proportion of subjects that had a circadian oscillation for the clock gene. Heatmap shows which subjects had the circadian oscillation. Each subject is represented by a row in which the filled squares represent a detected circadian oscillation. *P < 0.05, χ2 test.