Brain rhythms of pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain

How Does the Body Affect the Mind? Role of Cardiorespiratory Coherence in the Spectrum of Emotions

The brain is considered to be the primary generator and regulator of emotions; however, afferent signals originating throughout the body are detected by the autonomic nervous system (ANS) and brainstem, and, in turn, can modulate emotional processes. During stress and negative emotional states, levels of cardiorespiratory coherence (CRC) decrease, and a shift occurs toward sympathetic dominance. In contrast, CRC levels increase during more positive emotional states, and a shift occurs toward parasympathetic dominance. Te dynamic changes in CRC that accompany different emotions can provide insights into how the activity of the limbic system and afferent feedback manifest as emotions. The authors propose that the brainstem and CRC are involved in important feedback mechanisms that modulate emotions and higher cortical areas. That mechanism may be one of many mechanisms that underlie the physiological and neurological changes that are experienced during pranayama and meditation and may support the use of those techniques to treat various mood disorders and reduce stress

A genetic network model of cellular responses to lithium treatment and cocaine abuse in bipolar disorder

<p>Abstract</p> <p>Background</p> <p>Lithium is an effective treatment for Bipolar Disorder (BD) and significantly reduces suicide risk, though the molecular basis of lithium's effectiveness is not well understood. We seek to improve our understanding of this effectiveness by posing hypotheses based on new experimental data as well as published data, testing these hypotheses in silico, and posing new hypotheses for validation in future studies. We initially hypothesized a gene-by-environment interaction where lithium, acting as an environmental influence, impacts signal transduction pathways leading to differential expression of genes important in the etiology of BD mania.</p> <p>Results</p> <p>Using microarray and rt-QPCR assays, we identified candidate genes that are differentially expressed with lithium treatment. We used a systems biology approach to identify interactions among these candidate genes and develop a network of genes that interact with the differentially expressed candidates. Notably, we also identified cocaine as having a potential influence on the network, consistent with the observed high rate of comorbidity for BD and cocaine abuse. The resulting network represents a novel hypothesis on how multiple genetic influences on bipolar disorder are impacted by both lithium treatment and cocaine use. Testing this network for association with BD and related phenotypes, we find that it is significantly over-represented for genes that participate in signal transduction, consistent with our hypothesized-gene-by environment interaction. In addition, it models related pharmacogenomic, psychiatric, and chemical dependence phenotypes.</p> <p>Conclusions</p> <p>We offer a network model of gene-by-environment interaction associated with lithium's effectiveness in treating BD mania, as well as the observed high rate of comorbidity of BD and cocaine abuse. We identified drug targets within this network that represent immediate candidates for therapeutic drug testing. Posing novel hypotheses for validation in future work, we prioritized SNPs near genes in the network based on functional annotation. We also developed a "concept signature" for the genes in the network and identified additional candidate genes that may influence the system because they are significantly associated with the signature.</p

Pathogenetic insights from the treatment of rheumatoid arthritis

Rheumatoid arthritis is a chronic autoimmune disease that causes progressive articular damage, functional loss, and comorbidity. The development of effective biologics and small-molecule kinase inhibitors in the past two decades has substantially improved clinical outcomes. Just as understanding of pathogenesis has led in large part to the development of drugs, so have mode-of-action studies of these specific immune-targeted agents revealed which immune pathways drive articular inflammation and related comorbidities. Cytokine inhibitors have definitively proven a critical role for tumour necrosis factor α and interleukin 6 in disease pathogenesis and possibly also for granulocyte-macrophage colony-stimulating factor. More recently, clinical trials with Janus kinase (JAK) inhibitors have shown that cytokine receptors that signal through the JAK/STAT signalling pathway are important for disease, informing the pathogenetic function of additional cytokines (such as the interferons). Finally, successful use of costimulatory blockade and B-cell depletion in the clinic has revealed that the adaptive immune response and the downstream events initiated by these cells participate directly in synovial inflammation. Taken together, it becomes apparent that understanding the effects of specific immune interventions can elucidate definitive molecular or cellular nodes that are essential to maintain complex inflammatory networks that subserve diseases like rheumatoid arthritis

Neurodevelopmental disorders: From genetics to functional pathways

Neurodevelopmental disorders (NDDs) are a class of disorders affecting brain development and function and are characterized by wide genetic and clinical variability. In this review, we discuss the multiple factors that influence the clinical presentation of NDDs, with particular attention to gene vulnerability, mutational load, and the two-hit model. Despite the complex architecture of mutational events associated with NDDs, the various proteins involved appear to converge on common pathways, such as synaptic plasticity/function, chromatin remodelers and the mammalian target of rapamycin (mTOR) pathway. A thorough understanding of the mechanisms behind these pathways will hopefully lead to the identification of candidates that could be targeted for treatment approaches

Thalamocortical bistable switch as a theoretical model of fibromyalgia pathogenesis inferred from a literature survey

Fibromyalgia (FM) is an unsolved central pain processing disturbance. We aim to provide a unifying model for FM pathogenesis based on a loop network involving thalamocortical regions, i.e., the ventroposterior lateral thalamus (VPL), the somatosensory cortex (SC), and the thalamic reticular nucleus (TRN). The dynamics of the loop have been described by three differential equations having neuron mean firing rates as variables and containing Hill functions to model mutual interactions among the loop elements. A computational analysis conducted with MATLAB has shown a transition from monostability to bistability of the loop behavior for a weakening of GABAergic transmission between TRN and VPL. This involves the appearance of a high-firing-rate steady state, which becomes dominant and is assumed to represent pathogenic pain processing giving rise to chronic pain. Our model is consistent with a bulk of literature evidence, such as neuroimaging and pharmacological data collected on FM patients, and with correlations between FM and immunoendocrine conditions, such as stress, perimenopause, chronic inflammation, obesity, and chronic dizziness. The model suggests that critical targets for FM treatment are to be found among immunoendocrine pathways leading to GABA/glutamate imbalance having an impact on the thalamocortical system

Thalamocortical bistable switch as a theoretical model of fibromyalgia pathogenesis inferred from a literature survey

Fibromyalgia (FM) is an unsolved central pain processing disturbance. We aim to provide a unifying model for FM pathogenesis based on a loop network involving thalamocortical regions, i.e., the ventroposterior lateral thalamus (VPL), the somatosensory cortex (SC), and the thalamic reticular nucleus (TRN). The dynamics of the loop have been described by three differential equations having neuron mean firing rates as variables and containing Hill functions to model mutual interactions among the loop elements. A computational analysis conducted with MATLAB has shown a transition from monostability to bistability of the loop behavior for a weakening of GABAergic transmission between TRN and VPL. This involves the appearance of a high-firing-rate steady state, which becomes dominant and is assumed to represent pathogenic pain processing giving rise to chronic pain. Our model is consistent with a bulk of literature evidence, such as neuroimaging and pharmacological data collected on FM patients, and with correlations between FM and immunoendocrine conditions, such as stress, perimenopause, chronic inflammation, obesity, and chronic dizziness. The model suggests that critical targets for FM treatment are to be found among immunoendocrine pathways leading to GABA/glutamate imbalance having an impact on the thalamocortical system

A narrative review on the similarities and dissimilarities between myalgic encephalomyelitis/chronic fatigue syndrome (me/cfs) and sickness behavior

It is of importance whether myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a variant of sickness behavior. The latter is induced by acute infections/injury being principally mediated through proinflammatory cytokines. Sickness is a beneficial behavioral response that serves to enhance recovery, conserves energy and plays a role in the resolution of inflammation. There are behavioral/symptomatic similarities (for example, fatigue, malaise, hyperalgesia) and dissimilarities (gastrointestinal symptoms, anorexia and weight loss) between sickness and ME/CFS. While sickness is an adaptive response induced by proinflammatory cytokines, ME/CFS is a chronic, disabling disorder, where the pathophysiology is related to activation of immunoinflammatory and oxidative pathways and autoimmune responses. While sickness behavior is a state of energy conservation, which plays a role in combating pathogens, ME/CFS is a chronic disease underpinned by a state of energy depletion. While sickness is an acute response to infection/injury, the trigger factors in ME/CFS are less well defined and encompass acute and chronic infections, as well as inflammatory or autoimmune diseases. It is concluded that sickness behavior and ME/CFS are two different conditions

From Mouse Models to Patients: A Comparative Bioinformatic Analysis of HFpEF and HFrEF

Heart failure (HF) represents an immense health burden with currently no curative therapeutic strategies. Study of HF patient heterogeneity has led to the recognition of HF with preserved (HFpEF) and reduced ejection fraction (HFrEF) as distinct syndromes regarding molecular characteristics and clinical presentation. Until the recent past, HFrEF represented the focus of research, reflected in the development of a number of therapeutic strategies. However, the pathophysiological concepts applicable to HFrEF may not be necessarily applicable to HFpEF. HF induces a series of ventricular modeling processes that involve, among others, hallmarks of hypertrophy, fibrosis, inflammation, all of which can be observed to some extent in HFpEF and HFrEF. Thus, by direct comparative analysis between HFpEF and HFrEF, distinctive features can be uncovered, possibly leading to improved pathophysiological understanding and opportunities for therapeutic intervention. Moreover, recent advances in biotechnologies, animal models, and digital infrastructure have enabled large-scale collection of molecular and clinical data, making it possible to conduct a bioinformatic comparative analysis of HFpEF and HFrEF. Here, I first evaluated the field of HF transcriptome research by revisiting published studies and data sets to provide a consensus gene expression reference. I discussed the patient clientele that was captured, revealing that HFpEF patients were not represented. Thus, I applied alternative approaches to study HFpEF. I utilized a mouse surrogate model of HFpEF and analyzed single cell transcriptomics to gain insights into the interstitial tissue remodeling. I contrasted this analysis by comparison of fibroblast activation patterns found in mouse models resembling HFrEF. The human reference was used to further demonstrate similarities between models and patients and a novel possible biomarker for HFpEF was introduced. Mouse models only capture selected aspects of HFpEF but largely fail to imitate the complex multi-factor and multi-organ syndrome present in humans. To account for this complexity, I performed a top-down analysis in HF patients by analyzing phenome-wide comorbidity patterns. I derived clinical insights by contrasting HFpEF and HFrEF patients and their comorbidity profiles. These profiles were then used to predict associated genetic profiles, which could be also recovered in the HFpEF mouse model, providing hypotheses about the molecular links of comorbidity profiles. My work provided novel insights into HFpEF and HFrEF syndromes and exemplified an interdisciplinary bioinformatic approach for a comparative analysis of both syndromes using different data modalities