Linking disease symptoms and subtypes with personalized systems-based phenotypes: a proof of concept study.

A dynamic systems model was used to generate parameters describing a phenotype of Hypothalamic-Pituitary-Adrenal (HPA) behavior in a sample of 36 patients with chronic fatigue syndrome (CFS) and/or fibromyalgia (FM) and 36 case-matched healthy controls. Altered neuroendocrine function, particularly in relation to somatic symptoms and poor sleep quality, may contribute to the pathophysiology of these disorders. Blood plasma was assayed for cortisol and ACTH every 10 min for 24h. The dynamic model was specified with an ordinary differential equation using three parameters: (1) ACTH-adrenal signaling, (2) inhibitory feedback, and (3) non-ACTH influences. The model was "personalized" by estimating an individualized set of parameters from each participant's data. Day and nighttime parameters were assessed separately. Two nocturnal parameters (ACTH-adrenal signaling and inhibitory feedback) significantly differentiated the two patient subgroups ("fatigue-predominant" patients with CFS only versus "pain-predominant" patients with FM and comorbid chronic fatigue) from controls (all p's<.05), whereas daytime parameters and diurnal/nocturnal slopes did not. The same nocturnal parameters were significantly associated with somatic symptoms among patients (p's<.05). There was a significantly different pattern of association between nocturnal non-ACTH influences and sleep quality among patients versus controls (p<.05). Although speculative, the finding that patient somatic symptoms decreased when more cortisol was produced per unit ACTH, is consistent with cortisol's anti-inflammatory and sleep-modulatory effects. Patients' HPA systems may compensate by promoting more rapid or sustained cortisol production. Mapping "behavioral phenotypes" of stress-arousal systems onto symptom clusters may help disentangle the pathophysiology of complex disorders with frequent comorbidity.

Metabolomic profiling of asthma: diagnostic utility of urine nuclear magnetic resonance spectroscopy.

BACKGROUND: The ability to diagnose and monitor asthma on the basis of noninvasive measurements of airway cellular dysfunction is difficult in the typical clinical setting. OBJECTIVE: Metabolomics is the study of molecules created by cellular metabolic pathways. We hypothesized that the metabolic activity of children with asthma would differ from healthy children without asthma. Furthermore, children having an asthma exacerbation would be different compared with children with stable asthma in outpatient clinics. Finally, we hypothesized that (1)H-nuclear magnetic resonance (NMR) would measure such differences using urine samples, one of the least invasive forms of biofluid sampling. METHODS: Children (135 total, ages 4-16 years) were enrolled, having met the criteria of healthy controls (C), stable asthma in the outpatient clinic (AO), or unstable asthma in the emergency department (AED). Partial least squares discriminant analysis was performed on the NMR data to create models of separation (70 metabolites were measured/urine sample). Some NMR data were withheld from modeling to be run blindly to determine possible diagnostic accuracy. RESULTS: On the basis of the model of AO versus C, 31 of 33 AO samples were correctly diagnosed with asthma (94% accuracy). Only 1 of 20 C samples was incorrectly labeled as asthma (5% misclassification). On the basis of the AO versus AED model, 31 of the 33 AO samples were correctly diagnosed as outpatient asthma (94% accurate). CONCLUSION: This is the first report suggesting that (1)H-NMR analysis of human urine samples has the potential to be a useful clinical tool for physicians treating asthma.

Model-based therapeutic correction of hypothalamic-pituitary-adrenal axis dysfunction.

The hypothalamic-pituitary-adrenal (HPA) axis is a major system maintaining body homeostasis by regulating the neuroendocrine and sympathetic nervous systems as well modulating immune function. Recent work has shown that the complex dynamics of this system accommodate several stable steady states, one of which corresponds to the hypocortisol state observed in patients with chronic fatigue syndrome (CFS). At present these dynamics are not formally considered in the development of treatment strategies. Here we use model-based predictive control (MPC) methodology to estimate robust treatment courses for displacing the HPA axis from an abnormal hypocortisol steady state back to a healthy cortisol level. This approach was applied to a recent model of HPA axis dynamics incorporating glucocorticoid receptor kinetics. A candidate treatment that displays robust properties in the face of significant biological variability and measurement uncertainty requires that cortisol be further suppressed for a short period until adrenocorticotropic hormone levels exceed 30% of baseline. Treatment may then be discontinued, and the HPA axis will naturally progress to a stable attractor defined by normal hormone levels. Suppression of biologically available cortisol may be achieved through the use of binding proteins such as CBG and certain metabolizing enzymes, thus offering possible avenues for deployment in a clinical setting. Treatment strategies can therefore be designed that maximally exploit system dynamics to provide a robust response to treatment and ensure a positive outcome over a wide range of conditions. Perhaps most importantly, a treatment course involving further reduction in cortisol, even transient, is quite counterintuitive and challenges the conventional strategy of supplementing cortisol levels, an approach based on steady-state reasoning.

Nonlinear dynamical analysis and optimization for biological/biomedical systems.

As mathematical models are increasingly available for biological/biomedical systems, dynamic optimization can be a useful tool for manipulating systems. Dynamic optimization is a computational tool for finding a sequence of optimal actions to attain desired outcomes from the system. This chapter discusses two dynamic optimization algorithms, model predictive control and dynamic programming, in the context of finding optimal treatment strategy for correcting hypothalamic-pituitary-adrenal (HPA) axis dysfunction. It is shown that dynamic programming approach has the advantage over the model predictive control (MPC) methodology in terms of robustness to error in parameter estimates and flexibility of accommodating clinically relevant objective function.

Evaluation of adverse reactions to local anesthetics: experience with 236 patients.

BACKGROUND: Adverse reactions to local anesthetics (LAs) are frequently reported. Although most of these reactions are not immune mediated, many patients are referred to allergy clinics and undergo extensive evaluation. OBJECTIVE: To determine the prevalence of true LA allergy among the patients referred for suspected hypersensitivity and to evaluate the usefulness of the currently used evaluation protocol. METHODS: A total of 236 patients referred to our allergy clinic for investigation of LA hypersensitivity were included in this study. The evaluation protocol was composed of skin prick and intradermal tests, followed by subcutaneous challenge with unrelated LA preparations that contained preservatives. RESULTS: Skin prick and intradermal test results were negative for all subjects. No objective adverse reactions were observed during the challenge in all but 1 patient, who developed local erythema at the site of injection and later underwent an uneventful challenge with a different LA. CONCLUSIONS: Allergic reactions were not reproduced during testing and challenge with LA preparations that contained preservatives or preservatives with adrenaline in our large group of patients with suspected LA allergy. Since both prick and intradermal skin test results were negative in all the patients and did not provide us with useful information, we propose to modify the standard protocol by omitting intradermal tests and shortening the challenge. We also suggest that the whole procedure be performed with LAs that contain preservatives, which are usually the preferred preparations widely used in daily practice.