Characterization of Cortisol Dysregulation in Fibromyalgia and Chronic Fatigue Syndromes: A State-Space Approach

Divesh Deepak Pednekar, Md Rafiul Amin, Hamid Fekri Azgomi, Kirstin Aschbacher, Leslie J. Crofford, Rose T. Faghih

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Objective: Fibromyalgia syndrome (FMS) and chronic fatigue syndrome (CFS) are complicated medical disorders, with little known etiologies. The purpose of this research is to characterize FMS and CFS by studying the variations in cortisol secretion patterns, timings, amplitudes, the number of underlying pulses, as well as infusion and clearance rates of cortisol. Methods: Using a physiological state-space model with plausible constraints, we estimate the hormonal secretory events and the physiological system parameters (i.e., infusion and clearance rates). Results: Our results show that the clearance rate of cortisol is lower in FMS patients as compared to their matched healthy individuals based on a simplified cortisol secretion model. Moreover, the number, magnitude, and energy of hormonal secretory events are lower in FMS patients. During early morning hours, the magnitude and energy of the hormonal secretory events are higher in CFS patients. Conclusion: Due to lower cortisol clearance rate, there is a higher accumulation of cortisol in FMS patients as compared to their matched healthy subjects. As the FMS patient accumulates higher cortisol residues, internal inhibitory feedback regulates the hormonal secretory events. Therefore, the FMS patients show a lower number, magnitude, and energy of hormonal secretory events. Though CFS patients have the same number of secretory events, they secrete lower quantities during early morning hours. When we compare the results for CFS patients against FMS patients, we observe different cortisol alteration patterns. Significance: Characterizing CFS and FMS based on the cortisol alteration will help us to develop novel methods for treating these disorders.

    Original languageEnglish (US)
    Article number9025248
    Pages (from-to)3163-3172
    Number of pages10
    JournalIEEE Transactions on Biomedical Engineering
    Volume67
    Issue number11
    DOIs
    StatePublished - Nov 2020

    Keywords

    • Biomedical signal processing
    • deconvolution
    • state-space methods
    • statistical analysis
    • system identification

    ASJC Scopus subject areas

    • Biomedical Engineering

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