1.1.1. Complexity Science

A system is a group of independent but interrelated elements comprising a unified whole. A collection of elements comprises a complex system if open and dynamic connections and interactions exist between its components and contribute to the behavior of the collective. An open system is one that exists far from energetic equilibrium; that is, it takes in energy and expels waste. Formally, a complex system is any open system that involves a number of elements arranged in a structure and that requires many scales for adequate measurement. Such systems go through processes of change that defy description by a single rule or by reduction to a single level of explanation.

Complexity is a scientific approach for studying how the interacting parts of a system produce collective behaviors more complex than the sum of the contributing parts, and how the system responds to, and interacts with, its environment. Complexity theory provides a framework and language for describing and modeling such processes.

Complexity as a science studies the behavior of complex systems as a class using mathematical tools such as differential equations, graph theory, neural networks, time series analyses, and genetic algorithms as well as descriptive, predictive, and simulation modeling. Complexity theorists differ from conventional scientists in that they address unpredictable, nondeterministic processes within systems that do not decompose into simpler elements. This allows them to engage natural phenomena in natural settings more readily than their conventional science counterparts. Broadly, the complexity approach employs multi-scale descriptors to characterize dynamic systems and their phenomena. Applications include the study of economies, ecologies, weather, traffic flow, social organizations, and cultures, in addition to such physiological processes as gene and immune networks.

When living organisms engaged in adaptation and survival are the systems of interest, then complexity analysis falls under the heading of complex adaptive systems (CAS) (Gell-Mann 1994; Kelso 1998; Kaneko 2006). Such systems are purposeful, pro-creative and pro-active in relationship to their environments rather than simply reactive. An insect hive exemplifies a CAS, as does the immune system. When elements of a system are of interest, for example worker ants within an ant colony or antigen-presenting cells within the immune system, then modelers may designate the CAS as individual based or agent based. CASs manifest ever-changing, self-organizing behavior in response to a variable environment, and they move toward, but never sustain, equilibrium. In a classic paper, Prigogne and Stengers (1984) termed this behavior “order through fluctuations.”

1.1.2. Features of Complex Systems

Any complex system, including a CAS, has several fundamental distinguishing features. A CAS has additional properties because it continuously adapts to an environment. We first introduce these features here and subsequently explore their utility for describing and investigating the physiological and psychological impact of nociception.

1.1.3. Lack of Central Control

Complex systems differ from simple systems in that they lack central control. A control hierarchy with a leader at the top simply does not exist. Rather, the power spreads over a decentralized structure and multiple agents combine to generate the actual system behavior. A building heating system is a noncomplex, closed system in which a single component, a thermostat, controls system behavior. In this case, the whole can never be more complex than the sum of its parts. When control emerges from the collective in a way that exceeds the sum of the contribution of the individual agents, as it does in an insect swarm, then true complexity exists and the collective behaves in a manner more complex than the individual agent within it could ever achieve. In a complex system, control is an emergent property. That is, control appears spontaneously and is unpredictable solely on the basis of information about the individual components.

1.1.4. Emergence

Complexity researchers regard emergent phenomena as normal properties of dynamic, self-organizing systems. In principle, emergence is the process of deriving some new and coherent structures, patterns, and properties in a complex system. For example, an insect colony exhibits purposeful and intelligent adaptive behavior that makes possible foraging for food, defense, and reproduction. This property, which we may loosely term intelligence, is unpredictable from what we know about the individual insect and appears spontaneously. Emergence is readily apparent in the behaviors of an insect swarm, a flock of migrating birds, a human crowd, and indeed in human culture. As a general principle, complexity theorists hold that emergent phenomena occur due to patterning of interactions (nonlinear and distributed) between the elements of the system over time. One might describe acute-phase tissue inflammation as an emergent property of the immune system. Complex behaviors emerge as a result of often nonlinear, spatiotemporal interactions among a large number of component systems at different levels of system organization.

1.1.5. States and State Transitions

Complex systems of all types are dynamic and function in states; that is, relatively stable modes of operation. Complexity theorists refer to a collection of system properties as a state and the set of all possible states of a system is its state space. Basically, the total number of properties transmitted by a system, and detected by an observer, defines the complexity of that system. For the sake of illustration, consider familiar objects rather than complex systems. For a coin toss, there are only two states, namely heads and tails, but for a computer screen with a resolution of 800 × 600 pixels and 256 colors, the number of states is 256 to the power of 480,000. Of course, in a CAS, some states are much more likely to occur than others, and experience shapes the probability of transitions to certain states.

Complex systems sometimes undergo abrupt and unpredictable shifts in states. State transitions, often called phase transitions, are everywhere in nature. These are abrupt, nonlinear changes in a system. Water can change from solid to liquid and then to vapor with increasing temperature. The human brain can shift from waking consciousness to slow-wave sleep, and from that to paradoxical sleep, as a function of circadian rhythm. During combat, a soldier may become totally insensitive to injury, a state transition that fosters survival.

1.1.6. Attractors

Although complex systems are dynamic and self-organizing, when perturbed they go into disorder and then settle back into relatively stable states with relatively simple behavioral patterns. The transition from disorder to order reduces complexity and defines the new state space. A common metaphor describes a ball falling onto a three-dimensional landscape surface with peaks and depressions. The ball will roll away from the peaks and eventually settle into a depression. The depression, or basin, represents a subset of a system’s state space that the system can enter but not leave, unless boundary conditions or perturbations bring about reorganization. This is an attractor.

Systems are inherently dynamic, and so the interaction of the ball with the landscape may change over time, as the system’s environment varies. In this respect, a state space has a trajectory over time and may change as its environment changes. For example, one might characterize an ion channel as a two-state, or on-off, system and the probability of the on state will vary across time as a function of change in the system’s environment. Naturally, a CAS has a history, and the experience of prior states may influence the probability of occurrence of future states.

1.1.7. Nesting

A complex system always has the feature of nesting; that is, subsystems nest within it, and it nests within a higher-level complex system. Each system level can have its own state transitions, and these transitions occur within a higher-level system. Therefore, the first challenge we face in engaging the idea of multi-symptom disorder is deciding upon a level of inquiry. That is, we must single out one level of a hierarchically organized complex system as the System of Interest and define the levels above it as its environment. We could choose the sensory end organ, the dorsal horn of the spinal cord, the brain, the family, or the American culture. Because multi-symptom disorders happen to individual people, we normally select the individual as our System of Interest. Social systems such as the family comprise our system’s environment, and various psychological and physiological subsystems nest within the individual.

Figure 1.1 broadly illustrates the principle of hierarchal system nesting, within which the investigator defines the System of Interest, depicted as the Wider System of Interest in Figure 1.1. For our purposes, the Wider System of Interest is the individual, or person. The Environment immediately surrounding the person is his or her social network: family, friends, work environment, and perhaps involved health care professionals. Figure 1.1 designates this as the Wider Environment; that is, the surrounding social community, its economy, its culture, and all of the influences, opportunities, support, and hassles that this can exert upon the individual and his/her social network. Many stressors reside in the Wider Environment. The Narrow System of Interest, nested within the Wider System of Interest, refers to the physical and psychological health of the person. It is this to which health care providers normally attend. Of course, the Narrow System of Interest contains multiple physiological subsystems that are the concern of medicine and the targets of medical diagnosis and evaluation.

FIGURE 1.1

Hierarchal system nesting.

Causal influences are bidirectional and extend across system levels. For example, the interactions of the person, or Wider System of Interest, with the family, or Environment, if negative, can create stress at the psychological and physical level with negative effects on health. Conversely, improvements in health, or Narrow System of Interest, can positively influence the interactions of the person with his or her environment. The concept of dysregulation, which we discuss below, applies at all levels of the system. Dysregulation within the Wider Environment, or society, can evoke consequent dysregulation within the Environment, or family, and this subsequently can dysregulate the person and compromise health itself.

1.2.1. Adaptation and Agency

Adaptation is the continual adjustment of an agent to its changing environment. An agent is a living entity, a self-organizing system, and an individual entity operating purposefully within its environment in the service of adaptation. The concept of agent equates with the individual when the focus of study is on the interaction of the individual with the environment, especially the social environment. Grimm and colleagues advocate the concept of agent-based complex system, sometimes termed individual-based complex system, which directly identifies the individual in the world as an agent (Grimm et al. 2005).

The complexity investigator imputes agency to aspects of nested subsystems whenever an element exhibits some degree of autonomy. For example, the migratory cells of the immune system serve as agents for the detection of toxins, invading microorganisms and tumor development, all of which are invisible to the nervous and endocrine systems. Moreover, dendritic cells serve as professional antigen-presenting agents. They appear in peripheral organs such as skin where they encounter and capture antigens. They then migrate to the T cell areas of lymphoid tissues and present the processed antigens in order to elicit antigen-specific T cell responses.

Whatever the level of inquiry, agents are semi-autonomous units that evolve over time and help to maximize adaptation. They scan their environment and develop schemata, which are perceptual and/or motor patterns comprising rules for interpretation and action. Therefore, multiple agent-based subsystems exist in principle, nested within and working in service of the CAS of interest.

1.2.2. Equilibrium and Homeostasis

Complex systems are open, dissipative and operate far from equilibrium, but they tend to move toward equilibrium after disturbance and disorder. Physiologically, the bottom line for equilibrium is homeostasis. Although many writers equate homeostasis with adaptive adjustment, McEwen points out that homeostasis strictly applies to a limited set of systems concerned with maintaining the essentials of the internal milieu (McEwen 2000). The maintenance of homeostasis is the control of internal processes truly necessary for life such as thermoregulation, blood gases, acid base, fluid levels, metabolite levels, and blood pressure. McEwen’s distinction is critical because homeostasis has no adaptive features.

Three interdependent systems control the process of homeostasis: neural, immune, and endocrine (Goetzl and Sreedharan 1992). From the CAS perspective, specific processes must exist to protect and preserve homeostasis. Generic threats to homeostasis include environmental extremes, excessive physical exertion, depletion of essential resources, abnormal feedback processes, aging, and disease. Perturbations from the environment can threaten homeostatic regulation at any time.

1.2.3. Allostasis and Stress

Allostasis is an adaptive process in the service of homeostasis; it dynamically adapts multiple internal systems to changes in the environment and coordinates their responses (McEwen 2000; Korte et al. 2005). Changes in the external or internal environment trigger physiological coping mechanisms. These mechanisms insure that the processes sustaining homeostasis stay within normal range. The allostatic process, which involves substantial autonomic activity, depends upon the coordinating effects of agent messenger substances that also serve as mediators and determinants of neural regulatory processes, particularly hormones, neurotransmitters, peptides, endocannabinoids, and cytokines. I describe this more fully below.

Stress is the resource-intensive process of mounting adaptive coping responses to challenges that occur in the external or internal environment. A stressor is any event that elicits a stress response. It may be a physical or social event, an invading microorganism, or a signal of tissue trauma. Selye (1936) first described this response as a syndrome produced by “diverse nocuous agents.” He eventually characterized the stress response as having three stages: alarm reaction, resistance, and if the stressor does not relent, exhaustion. The normal stress responses of everyday life consist of the alarm reaction, resistance, and recovery. Stressors have as their primary features intensity, duration, and frequency. The impact of a stressor is the magnitude of the response it elicits. This impact involves cognitive mediation because it is a function of both the predictability and the controllability of the stressor.

Allostasis is the essence of the stress response because it mobilizes internal resources to meet the challenge that a stressor represents. Stressors may be multimodal and complex or unimodal and simple. When a stressor persists for a long period of time, or when repeated stressors occur in rapid succession, allostasis may burn resources faster than the body can replenish them. The cost to the body of allostatic adjustment, whether in response to extreme acute challenges or to lesser challenges over an extended period of time, is called allostatic load.

1.2.4. Feedback

In open systems, self-regulation and self-organization depend upon feedback, which determines stability. That is, information about the output of a system passes back to the input and thereby dynamically controls the level of the output. Figure 1.2 illustrates two fundamental feedback principles: negative and positive feedback. These are essential constructs in all areas of the biological, behavioral, and social sciences as well as in engineering and complexity science (Jones 1973; Thomas and D’Ari 1990; Northrop 2000; Flood and Carson 1993).

FIGURE 1.2

Negative and positive feedback.

Negative feedback generally involves a circuit and a controller with a set point, and it works toward establishing equilibrium. Figure 1.3 illustrates an adaptive negative feedback system that depends upon systemic circulation. Negative feedback regulation occurs throughout physiology and is a fundamental principle of endocrinology. Negative feedback acts to insure system stability and to maintain homeostasis. The difference between normal set point and current condition gauges allostatic load. Negative feedback continually moves a system away from imbalance and disorder toward balance and order. In principle, biological systems are always nested, and the set point for a negative feedback loop is generally under the control of a larger system within which it is embedded. Disturbance of a set point compromises negative feedback and is a potential cause of dysregulation.

FIGURE 1.3

Negative feedback with a controller and set point.

Positive feedback loops also occur such that, when a variable changes, the system responds by changing that variable even more in the same direction, generating escalation and rapid acceleration (Ferrell 2002). This is a process that abandons stability for instability. From an adaptation point of view, positive feedback loop capability is essential for meeting acute threat with defensive arousal or reproductive opportunity with sexual arousal. Positive feedback loops make state change possible.

A simple example of positive feedback is autocrine signaling. A cell may produce a substance, such as an activated microglial secreting a pro-inflammatory cytokine. The presence of the secreted cytokine in the cell’s environment stimulates the cell to produce still more of the cytokine. Such autocrine signaling, through a combination of strong nonlinearity and positive feedback, promotes cellular instability and allows transient inputs to shift the cellular system between two steady states, that is, bistability (Shvartsman et al. 2002). Brandman and colleagues pointed out that positive feedback allows systems to convert graded inputs to decisive all-or-none outputs (Brandman et al. 2005).

In this way positive feedback can move a CAS toward an adaptive state transition that by definition has an all-or-none quality (Brandman et al. 2005). Setting up stable transition is essential for rapid adaptation. In the case of the dorsal horn, this could be a biphasic state transition, as described below. Inhibitory systems may also have positive feedback components that can wind up inhibitory processes and eventually shut down an excitatory state. Such processes may play a role in sleep, fatigue, and other conditions of hypo-arousal or impaired cognition. In the CAS framework, positive feedback loops and bistable states are the products of evolution and are essential for adaptation and survival.

Positive feedback loops do not normally operate independently within a CAS. Because every system is embedded within a larger system, a positive feedback loop is typically under the control of an overarching negative feedback system that limits overshoot and can eventually terminate the positive feedback loop. Positive feedback can persist or terminate through state shift transition or in response to an overarching system that acts on the basic mechanism from which the positive feedback system arises or by initiating an opponent process. For example, to prevent overshoot in a positive feedback excitatory process, the superordinate system may initiate a competing inhibitory process. Overarching systems typically control the on-off state of a positive feedback loop.

Feedback loops appear to exist reciprocally across nervous, endocrine, and immune subsystems and thereby contribute to overall system regulation. For example, such processes clearly play key roles in the interdependence of endocrine and immune systems (Besedovsky and del Rey 2000; Rivest 2001). Glucocorticoid products of the hypothalamo-pituitary-adrenocortical (HPA) axis modulate the basal operations of cytokine-producing immune cells. Cytokines, in turn, influence the activity of the HPA axis. Thus, the products of one system provide messenger substances that serve a feedback function for another system.

Feedback loops are essential agents in system regulation. Negative feedback tends to sustain stability in an adaptive system despite changes in the external or internal environment, thereby minimizing allostatic load and protecting homeostasis. Positive feedback increases possibilities for change in system behavior and provides pathways to establish new set points for its negative feedback processes. More importantly, positive feedback is a mechanism for inducing rapid, adaptive state transitions that are necessary for emergency reactions in a threatening environment.

Negative and positive feedback can go awry within the nervous, endocrine, and immune systems. The result is a disease process. Negative feedback may fail when an endogenous messenger substance providing the feedback disappears, occurs in excess, or becomes confounded by exogenous products such as medications or substances of abuse that resemble the messenger substance in chemical structure. In some cases, negative feedback fails when an extraneous influence alters the set point. For example, chronic opioid pharmacotherapy in a male pain patient confuses the hypothalamo-pituitary-gonadal axis and results in hypogonadism (Daniell 2002; Bliesener et al. 2005; Daniell, Lentz, and Mazer 2006).

Positive feedback processes can also malfunction. When a positive feedback loop does not fulfill its natural purpose, it can generate an extreme shift in adaptive state. In some cases, this violates homeostasis and results in death. Although positive sensory input does not directly cause death, it can contribute to life-threatening conditions such as cardiovascular shock. Persistent, stressor-related positive feedback probably contributes to migraine headache, allodynia, severe idiopathic abdominal pain, noncardiac chest pain, and a variety of multi-symptom disorders.

1.2.5. Agent Connectivity

By definition, connections and interactions exist among the components, or agents, of a CAS, and these linkages define self-organization and behavior. The connectivity of a system is the nature and extent of such connections and interactions. It is from these connections that patterns form and feedback occurs. The relationships between the components, or agents, within a system are generally more important than the agents themselves.

Following a stressful event, connectivity insures an extensive, systemic response. It encompasses all forms of physiological information exchange: neural, blood-borne, extracellular, and immune. Neurotransmitters, peptides, hormones, endocannabinoids, and cytokines are among the tools of connectivity. Neural, endocrine, and immune systems are able to mount a concerted, fully coordinated response because these messenger substances constantly exchange information and provide feedback. Connectivity makes possible many negative and positive feedback functions.

1.3.1. Stress and Hormesis

Stress is a normal aspect of human life, and some degree of daily stress is necessary for health. Mild stress, like that induced with exercise, caloric restriction, or alcohol, is clearly beneficial. However, a severe stressor, repetitive or relentless stressors, or multiple simultaneous stressors can overwhelm allostatic resources and cause deleterious consequences.

The concept of hormesis captures the nonlinear relationship of stress severity to benefit versus harm. In toxicology it refers to a dose response pattern whereby a substance that in a high dose inhibits or is toxic to a biological process stimulates or protects that same process in a smaller dose. The analogy of drug dose to the magnitude of a stressor is straightforward. Hormesis refers to the nonlinear benefit versus harm effect resulting from varying degrees of exposure to a stressor.

Figure 1.5 illustrates this concept. A stressor disrupts supersystem homeodynamics. This results in modest over-compensation and restoration of homeodynamics, or recovery. This represents successful adaptation.

FIGURE 1.5

Hormesis.

At the apex of the curve, where the magnitude of the stressor is substantial, exposure to the stressor begins to harm rather than benefit the individual. It is clear from athletics that repeated exposure to a beneficial stressor increases resistance to subsequent stressors and increases overall fitness. This is as true for adaptive immunity as it is for the runner’s endurance. The peak of the curve in Figure 1.5 shifts to the right with repeated exposure at modest levels. It shifts to the left for individuals who manage to avoid most stressors including exercise, and the result is that their supersystems become hypersensitive.

What happens when the magnitude of the stressor exceeds the peak of the hormetic curve? The answer lies in the nature of the stress response. The stress literature tends to group all reactions to a stressor under the single heading of stress response, as the response consisted solely of arousal. However, deKloet and Derijk (2004) characterize the stress response as having two modes of operation, or states. The first state is immediate arousal in response to the stressor in order to enable adaptive behaviors, and the second state is a slower process that promotes recovery, behavioral adaptation, and return to normalcy. They describe these phases as the fast and slow responding modes. Repeated stressors, multiple stressors, or a severe stressor may interfere with the transition from fast to slow mode or the completion of the slow mode. This can generate dysregulation in an organ system or chronobiological processes, as I describe below.

1.3.2. Supersystem Arousal Mechanisms

1.3.2.1. Nervous System

The major brain mechanisms of the stress response are the locus coeruleus (LC) noradrenergic system, the HPA axis based in the hypothalamic periventricular nucleus (PVN) (Tsigos and Chrousos 2002), and the sympatho-adreno-medullary (SAM) axis (Padgett and Glaser 2003). The peripheral effectors of these mechanisms are the autonomic nervous system, the SAM circulating hormones, principally the catecholamines epinephrine (E) and norepinephrine (NE) together with the sympathetic co-transmitter neuropeptide Y (NPY) (Zukowska et al. 2003), all of which originate in the chromaffin cells of the adrenal medulla. The stress response also involves hypothalamically induced release of peptides derived from pro-opiomel-anocortin (POMC) at the anterior pituitary. The POMC-related family of anterior pituitary hormones includes adrenocorticotropin hormone (ACTH), β-lipotropin, β-melanocyte stimulating hormone, and β-endorphin.

Corticotropin-releasing hormone (CRH), produced at the hypothalamic PVN, initiates the stress response. CRH initiates and coordinates the stress response at many levels (Elenkov 2004), including the LC (Rassnick, Sved, and Rabin 1994). It is the key excitatory central neurotransmitter and regulator in the endocrine response to injury. Two receptors respond to CRH and CRH-related peptides, CRH-1 and CRH-2. These distribute widely in limbic brain (Leonard 2005). CRH-1 (deKloet and Derijk 2004) is the key mechanism of the defensive arousal response. Figure 1.6 illustrates the HPA axis response to a stressor such as tissue injury.

FIGURE 1.6

HPA axis response to a stressor. (Reprinted with permission from Chapman, C. R., R. P. Tuckett, and C. W. Song. 2008. Pain and stress in a systems perspective: reciprocal neural, endocrine, and immune interactions. J Pain 9 (2):122–145. Copyright (more...)

1.3.3. Supersystem Recovery Mechanisms

The recovery phase of the supersystem stress response commences before the arousal, or alarm, phase ends to protect against arousal and inflammatory overshoot. The arousal state is catabolic, and if the allostatic response is too strong or goes on too long, it can deplete neurotransmitters and/or dysregulate system functions. The purposes of the recovery response are first to regulate the intensity of the alarm reaction, and second, when it is safe to stop arousal, to terminate allostasis, minimize the costs of allostatic load, and bring the body back to normalcy.

CRH synthesis and release occur in response to a stressor and also in response to levels of circulating cortisol (CORT) and normal diurnal rhythm. The neurons of the median eminence secrete CRH into the hypophyseal portal circulation, and this carries it to the anterior pituitary where it binds to CRH receptors on corticotropes. This generates POMC synthesis and release of ACTH (Miller and O’Callaghan 2002) into systemic circulation. Circulating ACTH stimulates production of CORT at the adrenal cortex with release into the systemic circulation. Circulating CORT, in turn, provides a negative feedback signal to the PVN and the anterior pituitary. (See Figure 1.6.)

The endocrine mechanism for recovery induces CRH-2 receptor expression. This receptor responds to the CRH family of peptides (deKloet 2004) including the urocortins. The anterior pituitary initiates production of adrenocortical glucocorticoids (GCs), including CORT, that bind to glucocorticoid receptors (GRs). The primary agent and classical marker for stress recovery in humans is CORT. It normally functions in concert with the catecholamines and CRH. GR activation promotes energy storage and termination of inflammation to prepare for future emergency. Although the recovery process is inherently protective, prolonged CORT can cause substantial damage (deKloet and Derijk 2004; deKloet 2004; Elenkov 2004).

Immune mechanisms demonstrate a similar process in response to a stressor. There is first an inflammatory reaction and then an extended anti-inflammatory reaction that prevents overshoot and damage (Elenkov et al. 2005; Menger and Vollmar 2004). Pro- and anti-inflammatory influences are essentially opponent processes, and ultimately with healing the system should return to a balance.

Cytokines classify into two categories. Soon after formation, helper T cells differentiate into two types in response to existing cytokines and then secrete their own cytokines with one of two profiles: Thl, pro-inflammatory; and Th2, anti-inflammatory. Most cytokines classify readily as either Thl or Th2 according to the influence they exert. For example, IL-4 stimulates Th2 activity and suppresses Thl activity, so it is anti-inflammatory. IL-12, on the other hand, promotes pro-inflammatory activity and is therefore Thl. Pro-inflammatory cytokines include ILl-β, IL-2, IL-6, IL-8, IL-12, IFN-α, and TNF-α. Anti-inflammatory cytokines include IL-4, IL-10, insulin-like growth factor 1 (IGF-10), and IL-13. Some investigators characterize an individual’s immune response profile using a Th1/Th2 ratio.

The immune recovery process requires that the Thl predominant state wind down and return to a Th1/Th2 ratio equal to 1.0. A persisting imbalance in the Thl direction fosters harmful inflammation. Imbalance in the Th2 direction incurs risk of adventitious infection and tumor development.

1.4.1. Dysregulation

Dysregulation is prolonged dysfunction in the ability of a system to recover its normal relationship to other systems and its usual level of operation following perturbation. This concept applies to any level of system focus, whether it is the hypo-thalamo-pituitary-gonadal axis or the response of an individual to a demanding social environment. An extensive literature addresses the relationships of trauma and prolonged stress with dysregulation of the HPA axis, the central noradrenergic system, and the SAM axis (Neumeister, Daher, and Charney 2005; deKloet 2004). The supersystem model proposes that multi-symptom disorders emerge and become chronic and disabling conditions as a result of regulatory problems developing over time within the supersystem. An important concept is that dysfunction arising in one subsystem is likely to lead to dysfunction in the others because they operate interdependently within the supersystem. Prolonged dysregulation can cause irreversible organ pathology that in turn can generate somatic distress. Dysregulation may manifest in at least four ways in multi-symptom disorders. These manifestations are not mutually exclusive.

1.4.2. Biorhythm Disturbance

First, in a temporal frame of reference, dysregulation refers to deviation from or loss of normal biological rhythms: ultracadian, circadian, and infracadian. Humans secrete hormones, alter body temperature, eat, sleep, and work according to circadian rhythms; and social activity patterns reflect these rhythms. Rhythm is a fundamental feature of homeostasis, as temperature regulation demonstrates. Subsystems also operate according to rhythms. Hormones pulse at certain times, and the sinoatrial node gives the heart a rhythm. Dysregulation of temporal processes may play a role in peripheral neuropathy (Siau and Bennett 2006). The concept of cross-system rhythm is still poorly defined, but some substances participating in connectivity appear to coordinate biological rhythms at multiple system levels. The hormone melatonin is one example (Bella and Gualano 2006). Among its many effects is control of POMC gene expression (Rasmussen et al. 2003). The relationship of temporal rhythm dysregulation in multi-symptom syndrome is largely unexplored, apart from the documentation of sleep disturbances. Inquiry into multi-rhythm dysregulation at multiple system levels in multi-symptom syndrome patients could prove informative.

1.4.3. Feedback Dysfunction

Messenger substances play multiple roles, including feedback messaging. Subsystems like the HPA axis depend upon negative feedback to terminate recovery from stress processes. Subsystems also limit lower-level positive feedback loops that make possible emergency responses, thus protecting against overshoot. Positive feedback processes are not self-limiting by definition, and without such control they continue until either a state shift occurs or the system self-destructs. Allodynia is a familiar example of positive feedback in chronic pain, as is panic attack in emotional regulation. Within the immune system, positive and negative feedback play a central role in T cell discrimination of self from non-self ligands (Stefanova et al. 2003; Mueller 2003). This process, too, is subject to dysregulation with negative health consequences manifesting as auto-immune disorders.

The literature identifies many examples of disturbed feedback-dependent regulatory processes in stressed patients. For example, patients may develop HPA axis dysregulation (Herman et al. 2003; Dinan et al. 2006), autonomic dysregulation (Kodounis et al. 2005), peptide dysregulation (Staines 2006), Thl/Th2 cytokine dysregulation (Elenkov et al. 2005; Viveros-Paredes et al. 2006), endogenous opioid dysregulation (Ribeiro et al. 2005), and dysregulation of the relationship between pain and blood pressure (Bruehl, Burns, and McCubbin 1998). Basically, dysregulation occurs when a subsystem regulated by negative feedback breaks down in one way or another, for example, through depletion of a key neurotransmitter or peptide.

Feedback mechanisms may also falter under the opposite condition of resource excess. The medical introduction of substances that resemble biological messengers may interfere with normal allostasis and produce iatrogenic disorder. Opioid medications provide a strong example, as they resemble beta endorphin and other endogenous opioids. The hypothalamo-pituitary-gonadal axis responds to such products as though they were endogenous signals and the result is often hypogonadism (Daniell, Lentz, and Mazer 2006).

1.5.1. Incomplete Stress Response Recovery

Dysregulation could occur if a system alters its set point in response to a stressor and then fails to readjust to the normal level after the stress has passed. This corresponds with McEwen’s metaphor of failure to hear the all-clear signal (McEwen 2002). This explanatory model nicely describes the hypervigilance and hyperreactivity of posttraumatic stress disorder (Bedi and Arora 2007). Some multi-symptom syndrome patients have trauma histories.

Set points are often straightforward to define. For example, Vogeser and colleagues (Vogeser et al. 2003) studied major surgery as a stressor and chose the cortisol:cortisone ratio as a marker of HPA axis activity and as a stress-sensitive indicator of the overall set-point shift in the breakdown of cortisone to produce CORT, namely 11b-hydroxysteroid dehydrogenase activity. Surgery caused a shift in this set point that later returned to pre-surgical levels. Cardiac variability, MR/GR ratio, and Th1/Th2 ratio represent other potential system set-point indicators that may exhibit pathological shifts in chronic pain. The auditory startle response, which indicates excessive autonomic response activation to startling stimuli, may be a marker of past trauma (Siegelaar et al. 2006). Traumatic life events can permanently alter the set point of an individual’s feedback-dependent HPA axis (deKloet et al. 2005; Bremner et al. 2003).

1.6.1. Autonomic Dysregulation

Cardiac variability, sometimes called vagal tone, gauges sympathetic/parasympathetic balance in the autonomic nervous system. It indexes behavioral, cognitive, and emotional function (Beauchaine 2001). Basically, cardiac variability reflects the balance of sympathetic and parasympathetic influence in autonomic function as evident in cardiac activity. The vagus nerve is bidirectional. Vagal afferent fibers from the heart project to the solitary nucleus. Efferent fibers from the brain stem terminate on the sinoatrial node, the cardiac pacemaker. Sympathetic activation accelerates heart rate, and parasympathetic activation decelerates heart rate.

Estimation of cardiac variability derives from respiratory sinus arrhythmia; that is, changes in heart rate during the respiratory cycle. During exhalation, vagal efferent activity modulates this rate and causes deceleration. Inhalation increases heart rate. Statistical indexes of instantaneous heart rate variability based on the R-to-R wave interval estimate of cardiac variability. Such estimates are stress sensitive, and some investigators postulate that early trauma may permanently diminish cardiac variability, leaving the individual less resilient to future stressors (Bracha 2004; Porges 1992). High cardiac variability, or vagal tone, may be an indirect marker of an individual’s ability to respond effectively to a stressor and recover efficiently from it.

1.6.2. Sensory Dysregulation

Tracey and Mantyh (2007) postulate that chronic pain patients may have dysfunction in either the facilitatory system or the inhibitory system for noxious signal modulation. One can assess these processes by looking at wind-up and diffuse noxious inhibitory control (DNIC). Wind-up, or temporal summation, occurs when a subject undergoes a series of identical noxious stimuli. Tracking the pain rating across trials reveals increased pain or sensitization. This process may be abnormal in some chronic pain populations (Staud et al. 2001). When the activation of one noxious stimulus causes a diminished response to a second noxious stimulus, DNIC exists. In the laboratory, one measures the response to a phasic stimulus at baseline, applies a tonic stimulus such as the cold pressor test, and then measures the response to the phasic stimulus again. The response to the phasic stimulus should diminish following the tonic stimulus. This is independent of segment (hence, diffuse); and not being naloxone reversible in most reports, it is probably independent of the HPA axis. DNIC is a laboratory predictor of clinical pain and quality of life (Edwards et al. 2003). Whether wind-up and DNIC are true opposing processes is uncertain but worth exploration.

1.6.3. Endocrine Dysregulation

Potential trait measures exist for the HPA axis. DeKloet and Derijk postulated that mineralocorticoid receptor (MR)- and glucocorticoid receptor (GR)-mediated stress responses counterbalance. MR responses contribute to immediate arousal and coping, whereas GR responses attenuate emergency reactions and assist recovery from stress (deKloet and Derijk 2004). Normally, an individual possesses a characteristic MR/GR balance that is largely genetically determined.

Some approaches to diagnosing dysregulation involve challenging the HPA axis and looking for abnormal state responses to the challenges. The dexamethasone suppression test gauges HPA axis response in this way (Raison and Miller 2003). Dexamethasone is an exogenous steroid that provides negative feedback to the pituitary to suppress the secretion of ACTH. It does not cross the blood-brain barrier. Excessive CORT response to dexamethasone occurs in up to half of all severely depressed patients, indicating axis dysregulation. Alternatively, the CRH challenge involves the infusion of CRH and measurement of subsequent ACTH and cortisol responses (Dinan et al. 2006). It, too, can gauge HPA axis dysregulation.

Detection of biorhythm dysregulation necessitates examination of diurnal or other chronological variation in hormones. This typically requires multiple samples within a single day and examination of the resulting profile against a normal profile. CORT, for example, normally peaks shortly after arising, and then blood levels decline and are very low late in the day and evening. Any other pattern indicates dysregulation. In contrast, opponent process dysregulation indicators derive from a ratio of opposing processes like the Th1/Th2 ratio. For this, there are many possibilities.

In looking at the negative impact of sleep deprivation, Copinschi (2005) examined both types of dysregulation. Sleep-deprived subjects had increased cortisol levels in the late afternoon and evening. Examination of two brain-gut axis hormones related to appetite, ghrelin, and leptin also revealed dysregulation. Ghrelin increases appetite, but leptin decreases it. With sleep deprivation, the ghrelin-to-leptin ratio shifted in the direction of higher ghrelin and lower leptin; this correlated strongly with increased hunger.

1.6.4. Immune Dysregulation

For the immune subsystem, Thl/Th2 balance has become a focus of attention in cytokine research (Kidd 2003; Elenkov 2004). The general view holds that stress is immunosuppressive, but as we have seen, stress may be beneficial at lower levels but detrimental at higher levels. Moreover, the initial arousal/inflammatory response to stress is different from the subsequent recovery response. Much uncertainty still exists, but it is becoming clear that glucocorticoids and catecholamines support inflammation locally in certain conditions; that is, they promote Thl cytokine production. And yet, systemically these substances potentiate Th2 production while inhibiting Thl production, thereby exerting an anti-inflammatory effect (Calcagni and Elenkov 2006). Because cytokine activity depends heavily upon stress hormones, such localized targeting of pro-inflammatory processes could be advantageous in promoting increased blood flow and cell trafficking to injured tissue. Thl/Th2 balance varies with the stress response. Regardless of whether that response is hyperactive or hypoactive, it may alter the course of immune-related disease. The Th1/Th2 ratio is skewed in several common diseases (Elenkov 2004) and is a useful parameter from a psychosomatic perspective. For example, Glaser and colleagues (2001) examined Thl/Th2 balance in chronically stressed caregivers of demented patients and found a shift in the Th2 direction, suggesting vulnerability to infection.

1.7.1. Failed Arousal-to-Recovery Transition

Clinicians managing chronic multi-symptom disorders sometimes see pain patients who report surviving a horrific accident or event that left them traumatized. A single trauma of sufficient magnitude can produce a stress response that does not resolve properly. McEwen (2002) described other allostatic load scenarios that might lead to system malfunction: (1) unremitting or chronic stressors, (2) inability to adjust to a stressor of modest duration and demand, and (3) not hearing the “all clear” in which the stress response persists after the stressor has disappeared. These concepts, collectively, describe an arousal or fast-response phase that fails to give way to a recovery or slow-response phase. When the arousal-to-recovery process does not progress to completion, the patient is likely to suffer some form of system dysregulation with corresponding organ dysfunction and unremitting, disordered chronobiology.

1.7.2. Dysfunctional Recovery

In some cases recovery may occur but fail to return the supersystem to an approximate balance. For example, the recovery process in the HPA axis can go wrong in two ways. CORT insufficiency and CORT excess are both damaging (deKloet 2004). Too little CORT means prolonged anabolism. Moreover, positive feedback arousal processes can go unchecked, and conversion to a proper recovery state may not occur. Conversely, too much CORT over time has negative catabolic consequences. Hypercortisolism is a well-known marker of severe depression. In both cases, loss of normal diurnal variation in CORT pulsing indicates dysregulation. Thus, a dysfunctional endocrine recovery process is a mechanism for chronic endocrine dysregulation with a related constellation of chronic symptoms.

The boundaries of endocrine dysregulation extend to the immune subsystem. GCs profoundly affect cytokine responses. Evidence indicates that GCs inhibit Thl cytokine production while at the same time promoting Th2 cytokine production (Elenkov 2004). This is another form of protection against overshoot of positivefeedback-driven arousal responses (Elenkov and Chrousos 2002).

As noted above, many writers (Kidd 2003) characterize the immune system as operating in either Thl dominant (pro-inflammatory) or Th2 dominant (anti-inflammatory). These modes roughly parallel the stress-response arousal and recovery phases. This is more than a parallel concept. Evidence indicates that pro-inflammatory cytokines activate the HPA axis (Besedovsky and del Rey 2000) and thereby elicit MR and GC responses, whereas inhibitory peptides support Th2 processes (Ganea, Rodriguez, and Delgado 2003; Delgado et al. 2003). In this way, chronic endocrine dysregulation may contribute to immune dysregulation and incur the related symptom burden.

1.7.3. Dysfunctional Subsystem Interface

The interface between subsystems can become chronically dysfunctional, impairing intersystem coordination. For example, Calcagni and Elenkov, in reviewing both endocrine and immune system response patterns during stress, raised the possibility of dysregulation in the neuroendocrine-immune interface (Calcagni and Elenkov 2006). Weber identified the same potential source of disease (Weber 2003). By extension, potential chronic dysfunction could occur in the nervous–immune interface or the nervous–endocrine interface as causal mechanisms for chronic multi-symptom syndromes.