# Modeling Brainstem Inflammation's Role in Systemic Dysfunction during Sepsis

> **NIH NIH U01** · CASE WESTERN RESERVE UNIVERSITY · 2020 · $613,214

## Abstract

Sepsis is systemic infection accompanied by an uncontrolled inflammatory response; a condition that can
deteriorate rapidly. Early diagnosis is critical for survival. Heart rate variability (HRV), a proposed
biomarker for sepsis, predicts its prognosis but is too nonspecific to make a diagnosis. Often HRV is
quantified by its power spectra, its variability in the frequency domain; the `high-frequency' component
reflects respiratory modulation of vagal nerve activity. Computational deterministic models of the brainstem
cardiorespiratory control networks have proposed plausible neural mechanisms for the vago-respiratory
coupling. In contrast to HRV, Dynamic Network Analysis (DyNA) and Dynamic Bayesian Network (DyBN)
models are highly specific and successful in identifying a `tipping point' in sepsis, i.e. when a controlled
inflammatory response becomes uncontrolled but its many variables are hard to measure. Recently, we
identified that the brainstem becomes inflamed in endotoxemia. We hypothesize that progressive
inflammation is a critical factor in losing HRV, ventilatory pattern variability (VPV), and cardiorespiratory
coupling (CRC) associated with sepsis. We propose to build on the strengths of agent-based and
computational modeling approaches and perform model-driven experiments to determine how alterations
of brainstem neurophysiology in sepsis limit physiologic pattern variability. Our preliminary data show that
endotoxemic rats lose CRC progressively in association with proinflammatory cytokines expression first in
the nucleus tractus solitarius (nTS) then in the nucleus Ambiguus. Further, consistent with a progressive
loss of CRC focal IL-1β microinjections in the nTS uncouples the arterial pulse pressure's influence on
respiration leaving RSA intact. The Specific Aims are: 1) to develop DyNa and DyBN models of cytokine
expression in brainstem cardiorespiratory control nuclei during septicemia to determine if central and
peripheral inflammation patterns, 2) to adapt these models to critically-ill humans at risk for sepsis and
probe the robustness of the model by applying therapeutic interventions in rats, and 3) to apply our control
model to propose plausible and testable mechanisms for the effects of cytokines on the function of
cardiorespiratory control circuitry. Our computational model of the neural control of cardiorespiratory
coupling as well as the models defining the interactions among cytokines in tissue inflammation have been
applied successfully to other conditions (sympatho-respiratory coupling) or to peripheral tissues (cytokine
expression and interaction). Integrating these models will provide cross-scale mechanistic explanations for
the loss of RSA and CVC observed during sepsis, identify critical cytokines for therapeutic intervention,
and will establish a scientific rationale for using CRC and variability measures as complementary and
sensitive biomarkers of sepsis.

## Key facts

- **NIH application ID:** 10002328
- **Project number:** 5U01EB021960-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** THOMAS E DICK
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $613,214
- **Award type:** 5
- **Project period:** 2017-09-18 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10002328

## Citation

> US National Institutes of Health, RePORTER application 10002328, Modeling Brainstem Inflammation's Role in Systemic Dysfunction during Sepsis (5U01EB021960-04). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10002328. Licensed CC0.

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