Inflammation, Biological Rhythms, and Basketball

Inflammation, Biological Rhythms, and Basketball Jeremy D. Scheff

Inflammation: A complex dynamic process The good, the bad and the ugly Immunologic dissonance Bone, 1996 Inflammation under normal circumstances is a protective response to biological stressors (tissue injury, foreign bodies and microbial invasions) promoting wound healing, immune system activation and elimination of microorganisms Oftentimes the process is not adequately controlled and persistent inflammation can be amplified leading to a detrimental physiological state characterized by severe, uncontrolled systemic inflammation possibly leading to MODS The highly complex (non-linear, redundant?) nature of the response has challenged the management and treatment of severe human inflammation Laroux, F.S., Front Biosci, 2004

Health, disease and immunologic attractors

Critical illness and physiologic variability: Linking processes to outcomes Homeostasis exhibits rhythmic variability enabling organisms to synchronize with the environment and maintain function • “Illness, organ-specific or systemic, may result in a detectable loss of organ or systemic signal variability associated with reduced adaptability” Lowry and Calvano, J. Leuk. Biol.,2008 Loss of variability in beat-to-beat intervals correlates with age/fitness, critical illness and (possibly) turning points Although significant progress has been made in analyzing systemic responses important questions remain unanswered • Fundamental causes of observed, and loss of, variability • Mechanistic explanations for the beneficial properties of oscillations and the negative properties associated with their loss • Linking variability (outcome) to cellular events (processes) will enable better control

1. Ultradian rhythms in cortisol production • Scheff JD, Calvano SE, Lowry SF, Androulakis IP: Transcriptional implications of ultradian glucocorticoid secretion, in homeostasis and in the acute stress response. Physiol Genomics 2012, 42(2):121–129. 2. Heart rate variability and autonomic dysfunction in inflammation 3. Basketball

Cortisol’s importance and rhythmicity Anti-inflammatory hormone Strong circadian pattern driven by an underlying ultradian (~1hr) rhythm Source of cortisol’s ultradian rhythm? HPA axis, ACTH-cortisol negative feedback loop What are the implications? Oscillations by chance, or not? Hand-waving arguments: great for circadian, not ultradian Negative feedback matters, but do oscillations? “Mathematically controlled comparison” (Savageau, Nature, 1974) 24 hours of rat data: (Walker et al., Proc BiolSci, 2010)

Ultradian rhythms in cortisol secretion By combining a model for the rhythmic production of cortisol with a model of cortisol pharmacodynamics, we can study the effects of ultradian rhythms. (Scheff et al., Physiol Genomics, 2012)

Stress responsiveness and ultradian amplitude Acute stress applied throughout the ultradian cycle produces a significant ultradian pattern in responsiveness. Relationship between amplitude and responsiveness? Generate random parametrizations of the model. Keep only parametrizations which produce homeostatic responses near those produced by the original parameter values Evaluate CRH stress responsiveness as a function of ultradian cortisol amplitude (Scheff et al., Physiol Genomics, 2012)

Who got scooped? Then a month later…

1. Ultradian rhythms in cortisol production 2. Heart rate variability and autonomic dysfunction in inflammation • Scheff JD, Griffel B, Corbett SA, Calvano SE, Androulakis IP: On heart rate variability and autonomic activity, in homeostasis and in systemic inflammation. Math Biosc 2014, 252C:36-44. 3. Basketball

Inflammation and the autonomic nervous system (ANS) There is cross-talk between inflammation and the ANS. • Important in understanding and treating inflammation-linked diseases. Good measurements of autonomic activity are difficult! • HR and HRV are easy to measure, but are they good metrics? Effect of inflammation on HR+HRV can be studied in a controlled environment through endotoxemia experiments. • Why confusion? Why conflicting results? Why limited clinical applications?

The relationship between HR/HRV and autonomic activity (Sayket al., AJP Regu, 2008) (Task Force, Circulation, 1996) ↑ Uncoupling between the heart and the ANS in endotoxemia. Direct SNS measurement shows decreased sympathetic activity in enotoxemia? ↑ ANS and spectral analysis HRV in endotoxemia → (Jan et al., Shock, 2010) How should these results be interpreted?

Modeling the ANS and HR/HRV Effect of mean levels Effect of saturation (Scheff et al., Math Biosc, 2014)

Modeling the ANS and HR/HRV Effect of mean levels Increase sym or decrease par: LESS VARIABILITY Decrease sym or increase par: MORE VARIABILITY Effect of saturation (Scheff et al., Math Biosc, 2014)

Modeling the ANS and HR/HRV Effect of mean levels Increase sym or decrease par: LESS VARIABILITY Decrease sym or increase par: MORE VARIABILITY Effect of saturation Increase sym or par: LESS VARIABILITY Decrease sym or par: MORE VARIABILITY (Scheff et al., Math Biosc, 2014)

The ANS and HR/HRV in human endotoxemia (1) Homeostasis (2) sym ↑, par ↑; sym predominates (3) sym ↑, par ↓; diminished cardiac autonomic sensitivity (4) ANS and heart are nearly entirely uncoupled; HR increases due to non-autonomic factors (Scheff et al., Math Biosc, 2014)

1. Ultradian rhythms in cortisol production • 2. Heart rate variability and autonomic dysfunction in inflammation 3. Basketball Basketball GM, http://basketball-gm.com/

Platform: Desktop? Web? Mobile? Desktop: Fast and flexible, but also complicated and unpopular. Web: Easy to use and cross-platform support is free, but then server costs are a significant concern. Mobile: Great for gaining users through app stores, but phones/tablets are slow and have small screens.

Client-side HTML5/JS Crazy idea: do it all in JavaScript! Run in any web browser! Nearly no server costs! JavaScript is so trendy these days Atwood's Law: any application that can be written in JavaScript, will eventually be written in JavaScript.

Client-side HTML5/JS Crazy idea: do it all in JavaScript! Run in any web browser! Nearly no server costs! JavaScript is so trendy these days But… I didn’t know JavaScript (1.5 years ago) What I did know about JavaScript scared me Where to store data? Atwood's Law: any application that can be written in JavaScript, will eventually be written in JavaScript.

IndexedDB What is it? Part of HTML5 NoSQL database Accessible only from client-side JavaScript

IndexedDB What is it really? Weird mix of high level (indexes, fancy/confusing automatic transaction handling) and low level (difficult API, no joins!!!). About 10x slower than using a typical relational database from a native app. Gotchasgalore (e.g. if you add some data and listen for the “success” event to fire, that doesn’t necessarily mean the data was successfully added to the database!).

IndexedDB What is it really? Weird mix of high level (indexes, fancy/confusing automatic transaction handling) and low level (difficult API, no joins!!!). About 10x slower than using a typical relational database from a native app. Gotchas galore (e.g. if you add some data and listen for the “success” event to fire, that doesn’t necessarily mean the data was successfully added to the database!). The only way to store large amounts of client-side data from JavaScript.

Am I making a game or building a model? The same challenges often arise in making a video game andmodeling a biological system. Game simulation Level of detail to balance realism and performance? What is the scope of my model? Biologist vs. mathematician

Am I making a game or building a model?q1 The same challenges often arise in making a video game andmodeling a biological system. Game simulation Level of detail to balance realism and performance? What is the scope of my model? Biologist vs. mathematician AI In fixing an “exploit”, do I introduce a new one? Am I fitting or overfitting?

Conclusions and Future Outlook Ultradian rhythms in cortisol production allow for a maximal peak stress response while maintaining low homeostatic activation of HPA-responsive genes. Importance in a larger system (mathematical or experimental)? HRV changes during human endotoxemia give insight into the relationship between autonomic dysfunction and systemic inflammation; however, further experimental work is required to more precisely elucidate these connections. More measurements of autonomic activity; more autonomic perturbations in endotoxemia experiments Making video games and building mathematical models of biological systems really aren’t that different.

Acknowledgments GM082974 GM34695 Rutgers University Prof. IoannisAndroulakis Rutgers RWJ Medical School Prof. Stephen Lowry, MD Prof. Steve Calvano Prof. Siobhan Corbett, MD Ben Griffel Funding

Back-up slides

Ultradian Model HPA Axis Glucocorticoid Pharmacodynamics (Yao et al., Pharm Res, 2006) (Walker et al., Proc BiolSci, 2010) CRH Stress Test

Dynamics of autonomic regulation of heart rate and heart rate variability HR depends on the sinus node’s intrinsic rate and the integration of sympathetic and parasympathetic nervous tone HR fluctuates on a beat-to-beat basis reflecting dynamic response to physiological perturbations. The [S(LF)/P(HF)]NS oscillations are involved in short-term cardiovascular control An IPFM model expresses the neural signal to the heart assuming it to be the input modulator whose output is the frequency of cardiac excitations. [S/P]NS influences on the SA node are lumped into a single HR modulating signal

Critical illness and physiologic variability:Linking processes to outcomes Homeostasis exhibits rhythmic variability enabling organisms to synchronize with the environment and maintain function • “Illness, organ-specific or systemic, may result in a detectable loss of organ or systemic signal variability associated with reduced adaptability” Lowry and Calvano, J. Leuk. Biol. ,2008 Loss of variability in beat-to-beat intervals correlates with age/fitness, critical illness and (possibly) turning points Hayano, Card. Res. , 2003

Research Papers Review Papers • Scheff JD, Mavroudis PD, Calvano SE, An G, Vodovotz Y, Androulakis IP: A chemical engineer's perspective on translational systems biology. AIChE J, in preparation. • Scheff JD, Calvano SE, Androulakis IP: Multi-scale equation-based models: Insights for Inflammation and Physiological Variability. In Complex Systems and Computational Biology Approaches to Acute Inflammation. Edited by: An G , Vodovotz Y: Springer; in press. • Scheff JD, Mavroudis PD, Calvano SE, Lowry SF, Androulakis IP: Autonomic dysfunction in SIRS and sepsis. In Brain Dysfunction in Critical Illness. Edited by: Stevens RD , Ely EW, Sharshar T: Cambridge University Press; in press. • Scheff JD, Mavroudis PD, Foteinou PT, Calvano SE, Androulakis IP: Translational applications of evaluating physiologic variability in human endotoxemia. J ClinMonitComput, in press. • Scheff JD, Mavroudis PD, Foteinou PT, Calvano SE, Androulakis IP: Modeling physiologic variability in human endotoxemia. Crit Rev Biomed Eng 2012, 40(4):313–322. • Scheff JD, Mavroudis PD, Foteinou PT, An G, Calvano SE, Doyle J, Dick TE, Lowry SF, Vodovotz Y, Androulakis IP: A multiscale modeling approach to inflammation: A case study in human endotoxemia. J Comput Phys, 244:279-289. • Mavroudis PD, Scheff JD, Calvano SE, Androulakis IP: Systems biology of circadian-immune interactions. J Innate Immue, 5(2):153-162. • Dick TE, Molkov YI, Nieman G, Hsieh YH, Jacono FJ, Doyle J, Scheff JD, Calvano SE, Androulakis IP, An G, Vodovotz Y: Linking inflammation, cardiorespiratory variability, and neural control in acute inflammation via computational modeling. Front Physiol 2012, 3:222. • Scheff JD, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP: Reverse Engineering Approaches in Systems Biology: Towards a Model of Systemic Inflammation in Humans. In Process Systems Engineering. Edited by: Pistikopoulos E, Georgiadis M, Dua V: Wiley-VCH; 2010. • Foteinou PT, Scheff JD, Calvano SE, Lowry SF, Androulakis IP: Approaches Towards a Multi-scale Model of Systemic Inflammation in Humans. In Methods in Bioengineering: Alternatives to Animal Testing. Edited by: Yarmush ML, Langer RS: Artech House; 2010. Scheff JD, Corbett SA, Calvano SE, Androulakis IP: On heart rate and heart rate variability in human endotoxemia. In preparation. Scheff JD, Mavroudis PD, Doyle J, Vodovotz Y, Androulakis IP: The impact of stochasticity on a model of the inflammatory response. Math Biosc, in preparation. Scheff JD, Calvano SE, Androulakis IP: Predicting critical transitions in a model of systemic inflammation. J TheorBiol, submitted. Mavroudis PD, Scheff JD, Calvano SE, Lowry SF, Androulakis IP: Entrainment of peripheral clock genes by cortisol. Physiol Genomics 2012, 44(11):607–621. Scheff JD, Calvano SE, Lowry SF, Androulakis IP: Transcriptional implications of ultradian glucocorticoid secretion, in homeostasis and in the acute stress response. Physiol Genomics 2012, 42(2):121–129. Scheff JD, Kosmides AK, Calvano SE, Lowry SF, Androulakis IP: Pulsatile glucocorticoid secretion: origins and downstream effects. IEEE Trans Biomed Eng 2011, 58(12):3504–3507. Scheff JD, Mavroudis PD, Calvano SE, Lowry SF, Androulakis IP: Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia. Physiol Genomics 2011, 43(16):951–964. Scheff JD, Almon RR, DuBois DC, Jusko WJ, Androulakis IP: Assessment of pharmacologic area under the curve when baselines are variable.Pharm Res 2011, 28(5):1081–1089. Scheff JD, Calvano SE, Lowry SF, Androulakis IP: Modeling the influence of circadian rhythms on the acute inflammatory response. J TheorBiol 2010, 264(3):1068-1076. Scheff JD, Almon RR, DuBois DC, Jusko WJ, Androulakis IP: A new symbolic representation for the identification of informative genes in replicated microarray experiments. OMICS 2010, 14(3):239-248.

Inflammation, Biological Rhythms, and Basketball