Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment

Pain Phenotypes in Rare Musculoskeletal and Neuromuscular Diseases

For patients diagnosed with a rare musculoskeletal or neuromuscular disease, pain may transition from acute to chronic; the latter yielding additional challenges for both patients and care providers. We assessed the present understanding of pain across a set of ten rare, noninfectious, noncancerous disorders; Osteogenesis Imperfecta, Ehlers-Danlos Syndrome, Achondroplasia, Fibrodysplasia Ossificans Progressiva, Fibrous Dysplasia/McCune-Albright Syndrome, Complex Regional Pain Syndrome, Duchenne Muscular Dystrophy, Infantile- and Late-Onset Pompe disease, Charcot-Marie-Tooth Disease, and Amyotrophic Lateral Sclerosis. Through the integration of natural history, cross-sectional, retrospective, clinical trials, & case studies we described pathologic and genetic factors, pain sources, phenotypes, and lastly, existing therapeutic approaches. We highlight that while rare diseases possess distinct core pathologic features, there are a number of shared pain phenotypes and mechanisms that may be prospectively examined and therapeutically targeted in a parallel manner. Finally, we describe clinical and research approaches that may facilitate more accurate diagnosis, monitoring, and treatment of pain as well as elucidation of the evolving nature of pain phenotypes in rare musculoskeletal or neuromuscular illnesses.

Breathlessness in COPD: linking symptom clusters with brain activity

Background

Current models of breathlessness often fail to explain disparities between patients' experiences of breathlessness and objective measures of lung function. While a mechanistic understanding of this discordance has thus far remained elusive, factors such as mood, attention and expectation have all been implicated as important modulators of breathlessness. Therefore, we have developed a model to better understand the relationships between these factors using unsupervised machine learning techniques. Subsequently we examined how expectation-related brain activity differed between these symptom-defined clusters of participants.

Methods

A cohort of 91 participants with mild-to-moderate chronic obstructive pulmonary disease (COPD) underwent functional brain imaging, self-report questionnaires and clinical measures of respiratory function. Unsupervised machine learning techniques of exploratory factor analysis and hierarchical cluster modelling were used to model brain–behaviour–breathlessness links.

Results

We successfully stratified participants across four key factors corresponding to mood, symptom burden and two capability measures. Two key groups resulted from this stratification, corresponding to high and low symptom burden. Compared with the high symptom burden group, the low symptom burden group demonstrated significantly greater brain activity within the anterior insula, a key region thought to be involved in monitoring internal bodily sensations (interoception).

Conclusions

This is the largest functional neuroimaging study of COPD to date, and is the first to provide a clear model linking brain, behaviour and breathlessness expectation. Furthermore, it was possible to stratify participants into groups, which then revealed differences in brain activity patterns. Together, these findings highlight the value of multimodal models of breathlessness in identifying behavioural phenotypes and for advancing understanding of differences in breathlessness burden.

Towards individualised treatments for chronic breathlessness with functional neuroimaging: revealing the factors underlying the breathlessness experience in COPDhttps://bit.ly/3a8fXPt

Methods to discriminate between mechanism-based categories of pain experienced in the musculoskeletal system: a systematic review

ABSTRACT

Mechanism-based classification of pain has been advocated widely to aid tailoring of interventions for individuals experiencing persistent musculoskeletal pain. Three pain mechanism categories (PMCs) are defined by the International Association for the Study of Pain: nociceptive, neuropathic, and nociplastic pain. Discrimination between them remains challenging. This study aimed to build on a framework developed to converge the diverse literature of PMCs to systematically review methods purported to discriminate between them; synthesise and thematically analyse these methods to identify the convergence and divergence of opinion; and report validation, psychometric properties, and strengths/weaknesses of these methods. The search strategy identified articles discussing methods to discriminate between mechanism-based categories of pain experienced in the musculoskeletal system. Studies that assessed the validity of methods to discriminate between categories were assessed for quality. Extraction and thematic analysis were undertaken on 184 articles. Data synthesis identified 200 methods in 5 themes: clinical examination, quantitative sensory testing, imaging, diagnostic and laboratory testing, and pain-type questionnaires. Few methods have been validated for discrimination between PMCs. There was general convergence but some disagreement regarding findings that discriminate between PMCs. A combination of features and methods, rather than a single method, was generally recommended to discriminate between PMCs. Two major limitations were identified: an overlap of findings of methods between categories due to mixed presentations and many methods considered discrimination between 2 PMCs but not others. The results of this review provide a foundation to refine methods to differentiate mechanisms for musculoskeletal pain.

Systems Biology Guided Gene Enrichment Approaches Improve Prediction of Chronic Post-surgical Pain After Spine Fusion

Objectives

Incorporation of genetic factors in psychosocial/perioperative models for predicting chronic postsurgical pain (CPSP) is key for personalization of analgesia. However, single variant associations with CPSP have small effect sizes, making polygenic risk assessment important. Unfortunately, pediatric CPSP studies are not sufficiently powered for unbiased genome wide association (GWAS). We previously leveraged systems biology to identify candidate genes associated with CPSP. The goal of this study was to use systems biology prioritized gene enrichment to generate polygenic risk scores (PRS) for improved prediction of CPSP in a prospectively enrolled clinical cohort.

Methods

In a prospectively recruited cohort of 171 adolescents (14.5 ± 1.8 years, 75.4% female) undergoing spine fusion, we collected data about anesthesia/surgical factors, childhood anxiety sensitivity (CASI), acute pain/opioid use, pain outcomes 6-12 months post-surgery and blood (for DNA extraction/genotyping). We previously prioritized candidate genes using computational approaches based on similarity for functional annotations with a literature-derived "training set." In this study, we tested ranked deciles of 1336 prioritized genes for increased representation of variants associated with CPSP, compared to 10,000 randomly selected control sets. Penalized regression (LASSO) was used to select final variants from enriched variant sets for calculation of PRS. PRS incorporated regression models were compared with previously published non-genetic models for predictive accuracy.

Results

Incidence of CPSP in the prospective cohort was 40.4%. 33,104 case and 252,590 control variants were included for association analyses. The smallest gene set enriched for CPSP had 80/1010 variants associated with CPSP (p < 0.05), significantly higher than in 10,000 randomly selected control sets (p = 0.0004). LASSO selected 20 variants for calculating weighted PRS. Model adjusted for covariates including PRS had AUROC of 0.96 (95% CI: 0.92-0.99) for CPSP prediction, compared to 0.70 (95% CI: 0.59-0.82) for non-genetic model (p < 0.001). Odds ratios and positive regression coefficients for the final model were internally validated using bootstrapping: PRS [OR 1.98 (95% CI: 1.21-3.22); β 0.68 (95% CI: 0.19-0.74)] and CASI [OR 1.33 (95% CI: 1.03-1.72); β 0.29 (0.03-0.38)].

Discussion

Systems biology guided PRS improved predictive accuracy of CPSP risk in a pediatric cohort. They have potential to serve as biomarkers to guide risk stratification and tailored prevention. Findings highlight systems biology approaches for deriving PRS for phenotypes in cohorts less amenable to large scale GWAS.

Exploring Dynamic Connectivity Biomarkers of Neuropsychiatric Disorders

A recent study by Lee et al. showed that a dynamic functional connectivity pattern induced by tonic experimental pain might serve as a biomarker of chronic pain. The study illustrates key topics in translational neuroscience: the differentiation of biomarker functions, the multimodal integration of biomarkers, and the functional relevance of dynamic connectivity.

Distinct thalamocortical circuits underlie allodynia induced by tissue injury and by depression-like states

In humans, tissue injury and depression can both cause pain hypersensitivity, but whether this involves distinct circuits remains unknown. Here, we identify two discrete glutamatergic neuronal circuits in male mice: a projection from the posterior thalamic nucleus (PO^Glu) to primary somatosensory cortex glutamatergic neurons (S1^Glu) mediates allodynia from tissue injury, whereas a pathway from the parafascicular thalamic nucleus (PF^Glu) to anterior cingulate cortex GABA-containing neurons to glutamatergic neurons (ACC^GABA→Glu) mediates allodynia associated with a depression-like state. In vivo calcium imaging and multi-tetrode electrophysiological recordings reveal that PO^Glu and PF^Glu populations undergo different adaptations in the two conditions. Artificial manipulation of each circuit affects allodynia resulting from either tissue injury or depression-like states, but not both. Our study demonstrates that the distinct thalamocortical circuits PO^Glu→S1^Glu and PF^Glu→ACC^GABA→Glu subserve allodynia associated with tissue injury and depression-like states, respectively, thus providing insights into the circuit basis of pathological pain resulting from different etiologies.

Peripheral arterial stiffness during electrocutaneous stimulation is positively correlated with pain-related brain activity and subjective pain intensity: an fMRI study

Brain activity associated with pain perception has been revealed by numerous PET and fMRI studies over the past few decades. These findings helped to establish the concept of the pain matrix, which is the distributed brain networks that demonstrate pain-specific cortical activities. We previously found that peripheral arterial stiffness [Formula: see text] responds to pain intensity, which is estimated from electrocardiography, continuous sphygmomanometer, and photo-plethysmography. However, it remains unclear whether and to what extent [Formula: see text] aligns with pain matrix brain activity. In this fMRI study, 22 participants received different intensities of pain stimuli. We identified brain regions in which the blood oxygen level-dependent signal covaried with [Formula: see text] using parametric modulation analysis. Among the identified brain regions, the lateral and medial prefrontal cortex and ventral and dorsal anterior cingulate cortex were consistent with the pain matrix. We found moderate correlations between the average activities in these regions and [Formula: see text] (r = 0.47, p < 0.001). [Formula: see text] was also significantly correlated with self-reported pain intensity (r = 0.44, p < 0.001) and applied pain intensity (r = 0.43, p < 0.001). Our results indicate that [Formula: see text] is positively correlated with pain-related brain activity and subjective pain intensity. This study may thus represent a basis for adopting peripheral arterial stiffness as an objective pain evaluation metric.

Variability and effect sizes of intracranial current source density estimations during pain: Systematic review, experimental findings, and future perspectives

Pain arises from the integration of sensory and cognitive processes in the brain, resulting in specific patterns of neural oscillations that can be characterized by measuring electrical brain activity. Current source density (CSD) estimation from low-resolution brain electromagnetic tomography (LORETA) and its standardized (sLORETA) and exact (eLORETA) variants, is a common approach to identify the spatiotemporal dynamics of the brain sources in physiological and pathological pain-related conditions. However, there is no consensus on the magnitude and variability of clinically or experimentally relevant effects for CSD estimations. Here, we systematically examined reports of sample size calculations and effect size estimations in all studies that included the keywords pain, and LORETA, sLORETA, or eLORETA in Scopus and PubMed. We also assessed the reliability of LORETA CSD estimations during non-painful and painful conditions to estimate hypothetical sample sizes for future experiments using CSD estimations. We found that none of the studies included in the systematic review reported sample size calculations, and less than 20% reported measures of central tendency and dispersion, which are necessary to estimate effect sizes. Based on these data and our experimental results, we determined that sample sizes commonly used in pain studies using CSD estimations are suitable to detect medium and large effect sizes in crossover designs and only large effects in parallel designs. These results provide a comprehensive summary of the effect sizes observed using LORETA in pain research, and this information can be used by clinicians and researchers to improve settings and designs of future pain studies.

Preclinical Neuropathic Pain Assessment; the Importance of Translatability and Bidirectional Research

For patients suffering with chronic neuropathic pain the need for suitable novel therapies is imperative. Over recent years a contributing factor for the lack of development of new analgesics for neuropathic pain has been the mismatch of primary neuropathic pain assessment endpoints in preclinical vs. clinical trials. Despite continuous forward translation failures across diverse mechanisms, reflexive quantitative sensory testing remains the primary assessment endpoint for neuropathic pain and analgesia in animals. Restricting preclinical evaluation of pain and analgesia to exclusively reflexive outcomes is over simplified and can be argued not clinically relevant due to the continued lack of forward translation and failures in the clinic. The key to developing new analgesic treatments for neuropathic pain therefore lies in the development of clinically relevant endpoints that can translate preclinical animal results to human clinical trials. In this review we discuss this mismatch of primary neuropathic pain assessment endpoints, together with clinical and preclinical evidence that supports how bidirectional research is helping to validate new clinically relevant neuropathic pain assessment endpoints. Ethological behavioral endpoints such as burrowing and facial grimacing and objective measures such as electroencephalography provide improved translatability potential together with currently used quantitative sensory testing endpoints. By tailoring objective and subjective measures of neuropathic pain the translatability of new medicines for patients suffering with neuropathic pain will hopefully be improved.

Altered network architecture of functional brain communities in chronic nociplastic pain

Neuroimaging has enhanced our understanding of the neural correlates of pain. Yet, how neural circuits interact and contribute to persistent pain remain largely unknown. Here, we investigate the mesoscale organization of the brain through intrinsic functional communities generated from resting state functional MRI data from two independent datasets, a discovery cohort of 43 Fibromyalgia (FM) patients and 20 healthy controls (HC) as well as a replication sample of 34 FM patients and 21 HC. Using normalized mutual information, we found that the global network architecture in chronic pain patients is less stable (more variable). Subsequent analyses of node community assignment revealed the composition of the communities differed between FM and HC. Furthermore, differences in network organization were associated with the changes in the composition of communities between patients with varying levels of clinical pain. Together, this work demonstrates that intrinsic network communities differ substantially between patients with FM and controls. These differences may represent a novel aspect of the pathophysiology of chronic nociplastic pain.

Cortico-spinal imaging to study pain

Functional magnetic resonance imaging of the brain has helped to reveal mechanisms of pain perception in health and disease. Recently, imaging approaches have been developed that allow recording neural activity simultaneously in the brain and in the spinal cord. These approaches offer the possibility to examine pain perception in the entire central pain system and in addition, to investigate cortico-spinal interactions during pain processing. Although cortico-spinal imaging is a promising technique, it bears challenges concerning data acquisition and data analysis strategies. In this review, we discuss studies that applied simultaneous imaging of the brain and spinal cord to explore central pain processing. Furthermore, we describe different MR-related acquisition techniques, summarize advantages and disadvantages of approaches that have been implemented so far and present software that has been specifically developed for the analysis of spinal fMRI data to address challenges of spinal data analysis.

A Deep Brain Stimulation Trial Period for Treating Chronic Pain

Early studies of deep brain stimulation (DBS) for various neurological disorders involved a temporary trial period where implanted electrodes were externalized, in which the electrical contacts exiting the patient's brain are connected to external stimulation equipment, so that stimulation efficacy could be determined before permanent implant. As the optimal brain target sites for various diseases (i.e., Parkinson's disease, essential tremor) became better established, such trial periods have fallen out of favor. However, deep brain stimulation trial periods are experiencing a modern resurgence for at least two reasons: (1) studies of newer indications such as depression or chronic pain aim to identify new targets and (2) a growing interest in adaptive DBS tools necessitates neurophysiological recordings, which are often done in the peri-surgical period. In this review, we consider the possible approaches, benefits, and risks of such inpatient trial periods with a specific focus on developing new DBS therapies for chronic pain.

Literature review and methodological considerations for understanding circulating risk biomarkers following trauma exposure

Exposure to traumatic events is common. While many individuals recover following trauma exposure, a substantial subset develop adverse posttraumatic neuropsychiatric sequelae (APNS) such as posttraumatic stress, major depression, and regional or widespread chronic musculoskeletal pain. APNS cause substantial burden to the individual and to society, causing functional impairment and physical disability, risk for suicide, lost workdays, and increased health care costs. Contemporary treatment is limited by an inability to identify individuals at high risk of APNS in the immediate aftermath of trauma, and an inability to identify optimal treatments for individual patients. Our purpose is to provide a comprehensive review describing candidate blood-based biomarkers that may help to identify those at high risk of APNS and/or guide individual intervention decision-making. Such blood-based biomarkers include circulating biological factors such as hormones, proteins, immune molecules, neuropeptides, neurotransmitters, mRNA, and noncoding RNA expression signatures, while we do not review genetic and epigenetic biomarkers due to other recent reviews of this topic. The current state of the literature on circulating risk biomarkers of APNS is summarized, and key considerations and challenges for their discovery and translation are discussed. We also describe the AURORA study, a specific example of current scientific efforts to identify such circulating risk biomarkers and the largest study to date focused on identifying risk and prognostic factors in the aftermath of trauma exposure.

Pain-autonomic interaction: A surrogate marker of central sensitization

BACKGROUND

Central sensitization represents a key pathophysiological mechanism underlying the development of neuropathic pain, often manifested clinically as mechanical allodynia and hyperalgesia. Adopting a mechanism-based treatment approach relies highly on the ability to assess the presence of central sensitization. The aim of the study was to investigate potential pain-autonomic readouts to operationalize experimentally induced central sensitization in the area of secondary hyperalgesia.

METHODS

Pinprick evoked potentials (PEPs) and sympathetic skin responses (SSRs) were recorded in 20 healthy individuals. Three blocks of PEP and SSR recordings were performed before and after heat-induced secondary hyperalgesia. All measurements were also performed before and after a control condition. Multivariate analyses were performed using linear mixed-effect regression models to examine the effect of experimentally induced central sensitization on PEP and SSR parameters (i.e. amplitudes, latencies and habituation) and on pinprick pain ratings.

RESULTS

The noxious heat stimulation induced robust mechanical hyperalgesia with a significant increase in PEP and SSR amplitudes (p < 0.001) in the area of secondary hyperalgesia. Furthermore, PEP and SSR habituation were reduced (p < 0.001) after experimentally induced central sensitization.

CONCLUSIONS

The findings demonstrate that combined recordings of PEPs and SSRs are sensitive to objectify experimentally induced central sensitization and may have a great potential to reveal its presence in clinical pain conditions. Corroborating current pain phenotyping with pain-autonomic markers has the potential to unravel central sensitization along the nociceptive neuraxis and might provide a framework for mechanistically founded therapies.

SIGNIFICANCE

Our findings provide evidence that combined recordings of sympathetic skin responses (SSRs) and pinprick evoked potentials (PEPs) might be able to unmask central sensitization induced through a well-established experimental pain model in healthy individuals. As such, these novel readouts of central sensitization might attain new insights towards complementing clinical pain phenotyping.

Placebos in chronic pain: evidence, theory, ethics, and use in clinical practice

Despite their ubiquitous presence, placebos and placebo effects retain an ambiguous and unsettling presence in biomedicine. Specifically focused on chronic pain, this review examines the effect of placebo treatment under three distinct frameworks: double blind, deception, and open label honestly prescribed. These specific conditions do not necessarily differentially modify placebo outcomes. Psychological, clinical, and neurological theories of placebo effects are scrutinized. In chronic pain, conscious expectation does not reliably predict placebo effects. A supportive patient-physician relationship may enhance placebo effects. This review highlights "predictive coding" and "bayesian brain" as emerging models derived from computational neurobiology that offer a unified framework to explain the heterogeneous evidence on placebos. These models invert the dogma of the brain as a stimulus driven organ to one in which perception relies heavily on learnt, top down, cortical predictions to infer the source of incoming sensory data. In predictive coding/bayesian brain, both chronic pain (significantly modulated by central sensitization) and its alleviation with placebo treatment are explicated as centrally encoded, mostly non-conscious, bayesian biases. The review then evaluates seven ways in which placebos are used in clinical practice and research and their bioethical implications. In this way, it shows that placebo effects are evidence based, clinically relevant, and potentially ethical tools for relieving chronic pain.

Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.

A review on the ongoing quest for a pain signature in the human brain

Developing an objective biomarker for pain assessment is crucial for understanding neural coding mechanisms of pain in the human brain as well as for effective treatment of pain disorders. Neuroimaging techniques have been proven to be powerful tools in the ongoing quest for a pain signature in the human brain. Although there is still a long way to go before achieving a truly successful pain signature based on neuroimaging techniques, important progresses have been made through great efforts in the last two decades by the Pain Society. Here, we focus on neural responses to transient painful stimuli in healthy people, and review the relevant studies on the identification of a neuroimaging signature for pain.

Pediatric Clinical Endpoint and Pharmacodynamic Biomarkers: Limitations and Opportunities

Medical research in children typically lags behind that of adult research in both quantity and quality. The conduct of rigorous clinical trials in children can raise ethical concerns because of children's status as a 'vulnerable' population. Moreover, carrying out studies in pediatrics also requires logistical considerations that rarely occur with adult clinical trials. Due to the relatively smaller number of pediatric studies to support evidence-based medicine, the practice of medicine in children is far more reliant upon expert opinion than in adult medicine. Children are at risk of not receiving the same level of benefits from precision medicine research, which has flourished with new technologies capable of generating large amounts of data quickly at an individual level. Although progress has been made in pediatric pharmacokinetics, which has led to safer and more effective dosing, gaps in knowledge still exists when it comes to characterization of pediatric disease and differences in pharmacodynamic response between children and adults. This review highlights three specific therapeutic areas where biomarker development can enhance precision medicine in children: asthma, type 2 diabetes mellitus, and pain. These 'case studies' are meant to update the reader on biomarkers used currently in the diagnosis and treatment of these conditions, and their shortcomings within a pediatric context. Current research on surrogate endpoints and pharmacodynamic biomarkers in the above therapeutic areas will also be described. These cases highlight the current lack in pediatric specific surrogate endpoints and pharmacodynamic biomarkers, as well as the research presently being conducted to address these deficiencies. We finally briefly highlight other therapeutic areas where further research in pediatric surrogate endpoints and pharmacodynamic biomarkers can be impactful to the care of children.

The feasibility and acceptability of research magnetic resonance imaging in adolescents with moderate-severe neuropathic pain

Supplemental Digital Content is Available in the Text.

Introduction:

Multimodal characterisation with questionnaires, Quantitative Sensory Testing (QST), and neuroimaging will improve understanding of neuropathic pain (NeuP) in adolescents. Magnetic resonance imaging (MRI) data in adolescents with NeuP are limited, and the perceived practical or ethical burden of scanning may represent a barrier to research.

Objective:

To determine the feasibility of MRI scanning in adolescents with moderate–severe NeuP, with respect to consent rate, postscan acceptability, and data quality.

Methods:

This prospective cohort study evaluating questionnaires and QST recruited adolescents aged 10 to 18 years with clinically diagnosed NeuP from a tertiary clinic. Eligible adolescents aged 11 years and older could additionally agree/decline an MRI scan. After the scan, families rated discomfort, perceived risk, and acceptability of current and future MRI scans (0–10 numerical rating scales). Head motion during scanning was compared with healthy controls to assess data quality.

Results:

Thirty-four families agreed to MRI (72% recruitment), and 21 adolescents with moderate–severe pain (average last week 6.7 ± 1.7; mean ± SD) and with neuropathic QST profiles were scanned. Three adolescents reported positional or noise-related discomfort during scanning. Perceived risk was low, and acceptability of the current scan was high for parents (range [median]: 7 to 10/10 [10]) and adolescents (8–10/10 [10]). Willingness to undergo a future research scan was high for parents (7–10/10 [10]) and adolescents (5–10/10 [10]) and did not differ from future scans for clinical purposes. Mean head motion during resting state functional MRI did not differ from control adolescents.

Conclusion:

Research MRI is feasible and acceptable for many adolescents with moderate–severe NeuP.

Pain-free resting-state functional brain connectivity predicts individual pain sensitivity

Individual differences in pain perception are of interest in basic and clinical research as altered pain sensitivity is both a characteristic and a risk factor for many pain conditions. It is, however, unclear how individual sensitivity to pain is reflected in the pain-free resting-state brain activity and functional connectivity. Here, we identify and validate a network pattern in the pain-free resting-state functional brain connectome that is predictive of interindividual differences in pain sensitivity. Our predictive network signature allows assessing the individual sensitivity to pain without applying any painful stimulation, as might be valuable in patients where reliable behavioural pain reports cannot be obtained. Additionally, as a direct, non-invasive readout of the supraspinal neural contribution to pain sensitivity, it may have implications for translational research and the development and assessment of analgesic treatment strategies.

Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review

Non-oncologic chronic pain is a common high-morbidity impairment worldwide and acknowledged as a condition with significant incidence on quality of life. Pain intensity is largely perceived as a subjective experience, what makes challenging its objective measurement. However, the physiological traces of pain make possible its correlation with vital signs, such as heart rate variability, skin conductance, electromyogram, etc., or health performance metrics derived from daily activity monitoring or facial expressions, which can be acquired with diverse sensor technologies and multisensory approaches. As the assessment and management of pain are essential issues for a wide range of clinical disorders and treatments, this paper reviews different sensor-based approaches applied to the objective evaluation of non-oncological chronic pain. The space of available technologies and resources aimed at pain assessment represent a diversified set of alternatives that can be exploited to address the multidimensional nature of pain.

MHCII-restricted T helper cells: an emerging trigger for chronic tactile allodynia after nerve injuries

Nerve injury-induced chronic pain has been an urgent problem for both public health and clinical practice. While transition to chronic pain is not an inevitable consequence of nerve injuries, the susceptibility/resilience factors and mechanisms for chronic neuropathic pain after nerve injuries still remain unknown. Current preclinical and clinical studies, with certain notable limitations, have shown that major histocompatibility complex class II–restricted T helper (Th) cells is an important trigger for nerve injury-induced chronic tactile allodynia, one of the most prevalent and intractable clinical symptoms of neuropathic pain. Moreover, the precise pathogenic neuroimmune interfaces for Th cells remain controversial, not to mention the detailed pathogenic mechanisms. In this review, depending on the biology of Th cells in a neuroimmunological perspective, we summarize what is currently known about Th cells as a trigger for chronic tactile allodynia after nerve injuries, with a focus on identifying what inconsistencies are evident. Then, we discuss how an interdisciplinary perspective would improve the understanding of Th cells as a trigger for chronic tactile allodynia after nerve injuries. Finally, we hope that the expected new findings in the near future would translate into new therapeutic strategies via targeting Th cells in the context of precision medicine to either prevent or reverse chronic neuropathic tactile allodynia.

Threat Prediction from Schemas as a Source of Bias in Pain Perception

Our sensory impressions of pain are generally thought to represent the noxious properties of an agent but can be influenced by the predicted level of threat. Predictions can be sourced from higher-order cognitive processes, such as schemas, but the extent to which schemas can influence pain perception relative to bottom-up sensory inputs and the underlying neural underpinnings of such a phenomenon are unclear. Here, we investigate how threat predictions generated from learning a cognitive schema lead to inaccurate sensory impressions of the pain stimulus. Healthy male and female participants first detected a linear association between cue values and stimulus intensity and rated pain to reflect the linear schema when compared with uncued heat stimuli. The effect of bias on pain ratings was reduced when prediction errors (PEs) increased, but pain perception was only partially updated when measured against stepped increases in PEs. Cognitive, striatal, and sensory regions graded their responses to changes in predicted threat despite the PEs (p < 0.05, corrected). Individuals with more catastrophic thinking about pain and with low mindfulness were significantly more reliant on the schema than on the sensory evidence from the pain stimulus. These behavioral differences mapped to variability in responses of the striatum and ventromedial prefrontal cortex. Thus, this study demonstrates a significant role of higher-order schemas in pain perception and indicates that pain perception is biased more toward predictions and less toward nociceptive inputs in individuals who report less mindfulness and more fear of pain.SIGNIFICANCE STATEMENT This study demonstrates that threat predictions generated from cognitive schemas continue to influence pain perception despite increasing prediction errors arising in pain pathways. Individuals first formed a cognitive schema of linearity in the relationship between the cued threat value and the stimulus intensity. Subsequently, the linearity was reduced gradually, and participants partially updated their evaluations of pain in relation to the stepped increases in prediction errors. Individuals who continued to rate pain based more on the predicted threat than on changes in nociceptive inputs reported high pain catastrophizing and less mindful-awareness scores. These two affects mapped to activity in the ventral and dorsal striatum, respectively. These findings direct us to a significant role of top-down processes in pain perception.

Capturing Novel Non-opioid Pain Targets

The relatively high efficacy of opioids, which have associated risks of addiction, tolerance, and dependence, for the management of acute and terminal pain has been a major driver of the opioid crisis, together with the availability, overprescription, and diversion of these drugs. Eliminating opioids without an effective replacement is, however, no solution, as it substitutes one major problem with another. To deal successfully with the opioid crisis, we need to discover novel analgesics whose mechanisms do not involve the mu opioid receptor but that have high analgesic potency and low risk of adverse effects, particularly no abuse liability. The question is how to achieve this. There are several necessary elements; first, we need to understand the nature of pain and the mechanisms responsible for it, and second, we need to adopt novel and unbiased approaches to the identification and validation of pain targets.

Biological and behavioral markers of pain following nerve injury in humans

The evolution of peripheral and central changes following a peripheral nerve injury imply the onset of afferent signals that affect the brain. Changes to inflammatory processes may contribute to peripheral and central alterations such as altered psychological state and are not well characterized in humans. We focused on four elements that change peripheral and central nervous systems following ankle injury in 24 adolescent patients and 12 age-sex matched controls. Findings include (a) Changes in tibial, fibular, and sciatic nerve divisions consistent with neurodegeneration; (b) Changes within the primary motor and somatosensory areas as well as higher order brain regions implicated in pain processing; (c) Increased expression of fear of pain and pain reporting; and (d) Significant changes in cytokine profiles relating to neuroinflammatory signaling pathways. Findings address how changes resulting from peripheral nerve injury may develop into chronic neuropathic pain through changes in the peripheral and central nervous system.

Regional Differences in Tight Junction Protein Expression in the Blood-DRG Barrier and Their Alterations after Nerve Traumatic Injury in Rats

The nervous system is shielded by special barriers. Nerve injury results in blood–nerve barrier breakdown with downregulation of certain tight junction proteins accompanying the painful neuropathic phenotype. The dorsal root ganglion (DRG) consists of a neuron-rich region (NRR, somata of somatosensory and nociceptive neurons) and a fibre-rich region (FRR), and their putative epi-/perineurium (EPN). Here, we analysed blood–DRG barrier (BDB) properties in these physiologically distinct regions in Wistar rats after chronic constriction injury (CCI). Cldn5, Cldn12, and Tjp1 (rats) mRNA were downregulated 1 week after traumatic nerve injury. Claudin-1 immunoreactivity (IR) found in the EPN, claudin-19-IR in the FRR, and ZO-1-IR in FRR-EPN were unaltered after CCI. However, laser-assisted, vessel specific qPCR, and IR studies confirmed a significant loss of claudin-5 in the NRR. The NRR was three-times more permeable compared to the FRR for high and low molecular weight markers. NRR permeability was not further increased 1-week after CCI, but significantly more CD68⁺ macrophages had migrated into the NRR. In summary, NRR and FRR are different in naïve rats. Short-term traumatic nerve injury leaves the already highly permeable BDB in the NRR unaltered for small and large molecules. Claudin-5 is downregulated in the NRR. This could facilitate macrophage invasion, and thereby neuronal sensitisation and hyperalgesia. Targeting the stabilisation of claudin-5 in microvessels and the BDB barrier could be a future approach for neuropathic pain therapy.

The Genetics of Neuropathic Pain from Model Organisms to Clinical Application

Neuropathic pain (NeuP) arises due to injury of the somatosensory nervous system and is both common and disabling, rendering an urgent need for non-addictive, effective new therapies. Given the high evolutionary conservation of pain, investigative approaches from Drosophila mutagenesis to human Mendelian genetics have aided our understanding of the maladaptive plasticity underlying NeuP. Successes include the identification of ion channel variants causing hyper-excitability and the importance of neuro-immune signaling. Recent developments encompass improved sensory phenotyping in animal models and patients, brain imaging, and electrophysiology-based pain biomarkers, the collection of large well-phenotyped population cohorts, neurons derived from patient stem cells, and high-precision CRISPR generated genetic editing. We will discuss how to harness these resources to understand the pathophysiological drivers of NeuP, define its relationship with comorbidities such as anxiety, depression, and sleep disorders, and explore how to apply these findings to the prediction, diagnosis, and treatment of NeuP in the clinic.

Neuroimaging-based pain biomarkers: definitions, clinical and research applications, and evaluation frameworks to achieve personalized pain medicine

One of the key ambitions of neuroimaging-based pain biomarker research is to augment patient and clinician reporting of clinically relevant phenomena with neural measures for prediction, prognosis, and detection of pain. Despite years of productive research on the neuroimaging of pain, such applications have seen little advancement. However, recent developments in identifying brain-based biomarkers of pain through advances in technology and multivariate pattern analysis provide some optimism. Here, we (1) define and review the different types of potential neuroimaging-based biomarkers, their clinical and research applications, and their limitations and (2) describe frameworks for evaluation of pain biomarkers used in other fields (eg, genetics, cancer, cardiovascular disease, immune system disorders, and rare diseases) to achieve broad clinical and research utility and minimize the risks of misapplication of this emerging technology. To conclude, we discuss future directions for neuroimaging-based biomarker research to achieve the goal of personalized pain medicine.

Introduction to a Special Issue on Innovations and Controversies in Brain Imaging of Pain: Methods and Interpretations

This special issue comprised 14 articles from leaders in the field, that provide opinions and reviews of concepts that are central to the next generation of pain imaging studies. Topics include cutting-edge technologies and approaches that are at the forefront of such studies, as well as developments toward biomarkers of pain and clinical applications that bring us closer to harnessing understanding of pains and its modulation to offer better options to those suffering from pain.