Pain Signature Research Articles

Altered Dynamic Functional Network Connectivity in Healthy Adults with Acute Pain: Findings from the Human Connectome Project.

Characterizing the neural signature of pain and its modulation is critical for assessing treatment efficacy and conducting translational clinical research. However, the dynamics of pain processing in the brain have remained largely unknown. In this study, we employed independent component analysis (ICA) as a data-driven clustering method on resting-state functional magnetic resonance imaging (fMRI) to obtain intrinsic connectivity networks (ICNs) in a cohort of healthy adults from the Human Connectome Project (HCP) who were identified as having acute pain. We examined the temporal dynamic functional network connectivity (dFNC) with sliding time window correlation and k-means clustering, and compared dFNC state properties and meta-state metrics between groups. Results showed that acute pain had a significant impact on dFNC in a common connectivity state (dynamic state 5) among several ICN pairs, including the salience network, default mode network, central executive, dorsal attention networks, and basal ganglia (false discovery rate [FDR]-corrected p of 0.05). Furthermore, healthy adults with and without acute pain exhibited differences in mean dwell time (dynamic state 3), which indicated that individuals with acute pain spent more time in particular states than those without pain. Meta-state dynamic analysis further indicated significant group differences in the number of states (i.e., unique time windows for each subject), changes between states (i.e., number of times each subject changes from one meta-state to other), and total travelled distances. These preliminary results provide new information about time-varying properties of pain states related to acute pain and advocate for further state-based analyses of pain for future pain biomarker discovery and development.

Mapping the neuroethological signatures of pain, analgesia, and recovery in mice

Ongoing pain is driven by the activation and modulation of pain-sensing neurons, affecting physiology, motor function, and motivation to engage in certain behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in non-verbal animals. Here, in mice, we used site-specific electrophysiology to define key time points corresponding to peripheral sensitivity in acute paw inflammation and chronic knee pain models. Using supervised and unsupervised machine learning tools, we uncovered sensory-evoked coping postures unique to each model. Through 3D pose analytics, we identified movement sequences that robustly represent different pain states and found that commonly used analgesics do not return an animal's behavior to a pre-injury state. Instead, these analgesics induce a novel set of spontaneous behaviors that are maintained even after resolution of evoked pain behaviors. Together, these findings reveal previously unidentified neuroethological signatures of pain and analgesia at heightened pain states and during recovery.

Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain.

To unravel the complexity of the neuropathic pain experience, researchers have tried to identify reliable pain signatures (biomarkers) using electroencephalography (EEG) and skin conductance (SC). Nevertheless, their use as a clinical aid to design personalized therapies remains scarce and patients are prescribed with common and inefficient painkillers. To address this need, novel non-pharmacological interventions, such as transcutaneous electrical nerve stimulation (TENS) to activate peripheral pain relief via neuromodulation and virtual reality (VR) to modulate patients' attention, have emerged. However, all present treatments suffer from the inherent bias of the patient's self-reported pain intensity, depending on their predisposition and tolerance, together with unspecific, pre-defined scheduling of sessions which does not consider the timing of pain episodes onset. Here, we show a Brain-Computer Interface (BCI) detecting in real-time neurophysiological signatures of neuropathic pain from EEG combined with SC and accordingly triggering a multisensory intervention combining TENS and VR. After validating that the multisensory intervention effectively decreased experimentally induced pain, the BCI was tested with thirteen healthy subjects by electrically inducing pain and showed 82% recall in decoding pain in real time. Such constructed BCI was then validated with eight neuropathic patients reaching 75% online pain precision, and consequently releasing the intervention inducing a significant decrease (50% NPSI score) in neuropathic patients' pain perception. Our results demonstrate the feasibility of real-time pain detection from objective neurophysiological signals, and the effectiveness of a triggered combination of VR and TENS to decrease neuropathic pain. This paves the way towards personalized, data-driven pain therapies using fully portable technologies.

Brain imaging signatures of neuropathic facial pain derived by artificial intelligence

Advances in neuroimaging have permitted the non-invasive examination of the human brain in pain. However, a persisting challenge is in the objective differentiation of neuropathic facial pain subtypes, as diagnosis is based on patients’ symptom descriptions. We use artificial intelligence (AI) models with neuroimaging data to distinguish subtypes of neuropathic facial pain and differentiate them from healthy controls. We conducted a retrospective analysis of diffusion tensor and T1-weighted imaging data using random forest and logistic regression AI models on 371 adults with trigeminal pain (265 classical trigeminal neuralgia (CTN), 106 trigeminal neuropathic pain (TNP)) and 108 healthy controls (HC). These models distinguished CTN from HC with up to 95% accuracy, and TNP from HC with up to 91% accuracy. Both classifiers identified gray and white matter-based predictive metrics (gray matter thickness, surface area, and volume; white matter diffusivity metrics) that significantly differed across groups. Classification of TNP and CTN did not show significant accuracy (51%) but highlighted two structures that differed between pain groups—the insula and orbitofrontal cortex. Our work demonstrates that AI models with brain imaging data alone can differentiate neuropathic facial pain subtypes from healthy data and identify regional structural indicates of pain.

Sensory Profiling in Classical Ehlers-Danlos Syndrome: A Case-Control Study Revealing Pain Characteristics, Somatosensory Changes, and Impaired Pain Modulation

Pain is one of the most important yet poorly understood complaints in heritable connective tissue disorders (HCTDs) caused by monogenic defects in extracellular matrix molecules. This is particularly the case for the Ehlers-Danlos syndrome (EDS), paradigm collagen-related disorders. This study aimed to identify the pain signature and somatosensory characteristics in the rare classical type of EDS (cEDS) caused by defects in type V or rarely type I collagen. We used static and dynamic quantitative sensory testing and validated questionnaires in 19 individuals with cEDS and 19 matched controls. Individuals with cEDS reported clinically relevant pain/discomfort (Visual Analogue Scale ≥5/10 in 32% for average pain intensity the past month) and worse health-related quality of life. An altered somatosensory profile was found in the cEDS group with higher (P = .04) detection thresholds for vibration stimuli at the lower limb, indicating hypoesthesia, reduced thermal sensitivity with more (P < .001) paradoxical thermal sensations (PTSs), and hyperalgesia with lower pain thresholds to mechanical (P < .001) stimuli at both the upper and lower limbs and cold (P = .005) stimulation at the lower limb. Using a parallel conditioned pain modulation paradigm, the cEDS group showed significantly smaller antinociceptive responses (P-value .005–.046) suggestive of impaired endogenous pain modulation. In conclusion, individuals with cEDS report chronic pain and worse health-related quality of life and present altered somatosensory perception. This study is the first to systematically investigate pain and somatosensory characteristics in a genetically defined HCTD and provides interesting insights into the possible role of the ECM in the development and persistence of pain. PerspectiveChronic pain compromises the quality of life in individuals with cEDS. Moreover, an altered somatosensory perception was found in the cEDS group with hypoesthesia for vibration stimuli, more PTSs, hyperalgesia for pressure stimuli, and impaired pain modulation.

ID: 212541 Identification of Resting-State EEG Markers in Patients With Chronic Pain Before Spinal Cord Stimulation Surgery

Pain is a complex phenomenon resulting from dynamic interactions between sensory, cognitive, and emotional processes1. Studying electroencephalography (EEG) signatures of chronic pain can give insights into brain mechanisms of chronic pain and help to characterize the interactions between these dimensions and consequently to develop chronic pain biomarkers. Previous research has showed slower brain oscillations during resting2 and shifts in alpha frequency correlated with pain duration in patients with chronic pain3. We aimed to investigate the resting-state EEG patterns as potential neural markers in chronic pain patients before undergoing Spinal Cord Stimulation (SCS) surgery.

Functional Connectivity of the Anterior Cingulate Cortex and the Right Anterior Insula Differentiates between Major Depressive Disorder, Bipolar Disorder and Healthy Controls.

Background: This study aimed to explore possible differences of the whole-brain functional connectivity of the anterior cingulate cortex (ACC) and anterior insula (AI), in a sample of depressed patients with major depressive disorder (MDD), bipolar disorder (BD) and healthy controls (HC). Methods: A hundred and three subjects (nMDD = 35, nBD = 25, and nHC = 43) between the ages of eighteen and sixty-five years old underwent functional magnetic resonance imaging. The CONN Toolbox was used to process and analyze the functional connectivity of the ACC and AI. Results: The comparison between the patients (MDD/BD) and HC yielded increased resting-state functional connectivity (rsFC) between the ACC and the motor and somatosensory cortices (SSC), superior parietal lobule (SPL), precuneus, and lateral occipital cortex, which was driven by the BD group. In addition, hyperconnectivity between the right AI and the motor and SSC was found in BD, as compared to HC. In MDD, as compared to HC, hyperconnectivity between ACC and SPL and the lateral occipital cortex was found, with no statistical rsFC differences for the AI seed. Compared to BD, the MDD group showed ACC-cerebellum hyperconnectivity and a trend for increased rsFC between the right AI and the bilateral superior frontal cortex. Conclusions: Considering the observed hyperconnectivity between the ACC/somatosensory cortex in the patient group, we suggest depression may be related to an impairment of the sensory-discriminative function of the SSC, which results in the phenomenological signature of mental pain in both MDD and BD. These findings suggest that future research should investigate this particular network with respect to motor functions and executive control, as a potential differential diagnostic biomarker for MDD and BD.

Age-related neuroimmune signatures in dorsal root ganglia of a Fabry disease mouse model

Pain in Fabry disease (FD) is generally accepted to result from neuronal damage in the peripheral nervous system as a consequence of excess lipid storage caused by alpha-galactosidase A (α-Gal A) deficiency. Signatures of pain arising from nerve injuries are generally associated with changes of number, location and phenotypes of immune cells within dorsal root ganglia (DRG). However, the neuroimmune processes in the DRG linked to accumulating glycosphingolipids in Fabry disease are insufficiently understood.Therefore, using indirect immune fluorescence microscopy, transmigration assays and FACS together with transcriptomic signatures associated with immune processes, we assessed age-dependent neuroimmune alterations in DRG obtained from mice with a global depletion of α-Gal A as a valid mouse model for FD. Macrophage numbers in the DRG of FD mice were unaltered, and BV-2 cells as a model for monocytic cells did not show augmented migratory reactions to glycosphingolipids exposure suggesting that these do not act as chemoattractants in FD. However, we found pronounced alterations of lysosomal signatures in sensory neurons and of macrophage morphology and phenotypes in FD DRG. Macrophages exhibited reduced morphological complexity indicated by a smaller number of ramifications and more rounded shape, which were age dependent and indicative of premature monocytic aging together with upregulated expression of markers CD68 and CD163.In our FD mouse model, the observed phenotypic changes in myeloid cell populations of the DRG suggest enhanced phagocytic and unaltered proliferative capacity of macrophages as compared to wildtype control mice. We suggest that macrophages may participate in FD pathogenesis and targeting macrophages at an early stage of FD may offer new treatment options other than enzyme replacement therapy.

Gene expression signature of human neuropathic pain identified through transcriptome analysis.

Introduction: Neuropathic pain is a type of chronic pain that is characterized by ongoing discomfort and can be challenging to manage effectively. This study aimed to identify genes associated with neuropathic pain through transcriptome analysis in order to gain a better understanding of the mechanisms underlying this chronic, difficult-to-treat pain. Methods: We conducted transcriptome analysis using a training datasetof 202 individuals, including patients with neuropathic pain and healthy controls. Results: Our analysis identified five genes (GTF2H2, KLHL5, LRRC37A4P, PRR24, and MRPL23) that were significantly differentially expressed in the tissue of patients with neuropathic pain compared to controls. We constructed a neuropathic pain signature using these five genes and validated it using an independent dataset of 25 individuals. Receiver operating characteristic (ROC) curve analysis demonstrated that this signature had a high level of accuracy in differentiating between neuropathic pain patients and healthy controls, with an area under the curve (AUC) of 0.83 (95% CI 0.65-1). Discussion: These findings suggest that these five genes may be potential therapeutic targets for neuropathic pain.

Lipid signatures of chronic pain in female adolescents with and without obesity

BackgroundChronic pain in adolescence is associated with diminished outcomes, lower socioeconomic status in later life, and decreased family well-being. Approximately one third of adolescents with chronic pain have obesity compared to the general population. In obesity, lipid signals regulate insulin sensitivity, satiety, and pain sensation. We determined whether there is a distinct lipid signature associated with chronic pain and its co-occurrence with obesity in adolescents.MethodsWe performed global lipidomics in serum samples from female adolescents (N = 67, 13–17 years old) with no pain/healthy weight (Controls), chronic pain/healthy weight (Pain Non-obese), no pain/obesity (Obese), or chronic pain/obesity (Pain Obese).ResultsThe Pain Non-obese group had lipid profiles similar to the Obese and Pain Obese groups. The major difference in these lipids included decreased lysophosphatidylinositol (LPI), lysophosphatidylcholine (LPC), and lysophosphatidylethanolamine (LPE) in the three clinical groups compared to the Control group. Furthermore, ceramides and sphingomyelin were higher in the groups with obesity when compared to the groups with healthy weight, while plasmalogens were elevated in the Pain Obese group only.ConclusionsSerum lipid markers are associated with chronic pain and suggest that specific lipid metabolites may be a signaling mechanism for inflammation associated with co-occurring chronic pain and obesity.

Neural Signatures of Pain Modulation in Short-Term and Long-Term Mindfulness Training: A Randomized Active-Control Trial.

Mindfulness-based interventions are widely used to target pain, yet their neural mechanisms of action are insufficiently understood. The authors studied neural and subjective pain response in a randomized active-control trial of mindfulness-based stress reduction (MBSR) alongside long-term meditation practitioners. Healthy participants (N=115) underwent functional neuroimaging during a thermal acute pain task before and after random assignment to MBSR (N=28), an active control condition (health enhancement program [HEP]) (N=32), or a waiting list control condition (N=31). Long-term meditators (N=30) completed the same neuroimaging paradigm. Pain response was measured via self-reported intensity and unpleasantness, and neurally via two multivoxel machine-learning-derived signatures: the neurologic pain signature (NPS), emphasizing nociceptive pain processing, and the stimulus intensity independent pain signature-1 (SIIPS1), emphasizing stimulus-independent neuromodulatory processes. The MBSR group showed a significant decrease in NPS response relative to the HEP group (Cohen's d=-0.43) and from pre- to postintervention assessment (d=-0.47). The MBSR group showed small, marginal decreases in NPS relative to the waiting list group (d=-0.36), and in SIIPS1 relative to both groups (HEP group, d=-0.37; waiting list group, d=-0.37). In subjective unpleasantness, the MBSR and HEP groups also showed modest significant reductions compared with the waiting list group (d=-0.45 and d=-0.55). Long-term meditators reported significantly lower pain than nonmeditators but did not differ in neural response. Within the long-term meditator group, cumulative practice during intensive retreat was significantly associated with reduced SIIPS1 (r=-0.65), whereas daily practice was not. Mindfulness training showed associations with pain reduction that implicate differing neural pathways depending on extent and context of practice. Use of neural pain signatures in randomized trials offers promise for guiding the application of mindfulness interventions to pain treatment.

Systematic analysis of critical genes and pathways identified a signature of neuropathic pain after spinal cord injury.

Spinal cord injury (SCI) damages sensory systems, producing chronic neuropathic pain that is resistant to medical treatment. The specific mechanisms underlying SCI-induced neuropathic pain (SCI-NP) remain unclear, and protein biomarkers have not yet been integrated into diagnostic screening. To better understand the host molecular pathways involved in SCI-NP, we used the bioinformatics method, the PubMed database and bioinformatics methods to identify target genes and their associated pathways. We reviewed 2504 articles on the regulation of SCI-NP and used the text mining of PubMed database abstracts to determine associations among 12 pathways and networks. Based on this method, we identified two central genes in SCI-NP: interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α). Adult male Sprague-Dawley rats were used to build the SCI-NP models. The threshold for paw withdrawal was significantly reduced in the SCI group, and TLR4 was activated in microglia after SCI. Enzyme-linked immunosorbent assay（ELISA) analysis of TNF-α and IL-6 levels was significantly higher in the SCI group than in the sham group. Western blot showed that expressions of the TLR4/MyD88/NF-κB inflammatory pathway protein increased dramatically in the SCI group. Using the TLR4 inhibitor TAK-242, the pain threshold and expressions of inflammatory factors and proteins of the proteins of the inflammatory signal pathway were reversed, TLR4 in microglia was suppressed, suggesting that SCI-NP was related to neuroinflammation mediated by the TLR4 signalling pathway. In conclusion, we found that TNF-α and IL-6 were the neuroinflammation-related genes involved in SCI-NP that can be alleviated by inhibiting the inflammatory pathway upstream of the TLR4/MyD88/NF-κB inflammatory pathway.

Acute to Chronic Pain Signatures Program (a2CPS): Implementation of Remote Training for a Multisite Observation Study During COVID-19

Chronic pain produces the largest non-fatal burden of disease, yet our understanding of factors that contribute to the transition from acute chronic pain are poorly understood. The Acute to Chronic Pain Signatures Program (A2CPS) is a longitudinal, multi-site observational study to identify biomarkers (individual or biosignature combinations) that predict susceptibility or resilience to the development of chronic pain after surgery (knee replacement or thoracotomy). Due to the COVID-19 pandemic, however, travel between sites was restricted just as the study was preparing to begin enrollment. Here, we present multiple training protocol adaptations that were successfully implemented to facilitate remote research-related training. The A2CPS consortium includes 2 Multisite Clinical Centers (MCCs, 10 recruitment sites), a Clinical Coordinating Center (CCC), a Data Integration and Resource Center (DIRC), 3 Omics Data Generation Centers, and representation from the NIH Pain Consortium, Common Fund, and National Institute of Drug Abuse. The A2CPS is collecting candidate and exploratory biomarkers including pain, fatigue, function, sleep, psychosocial factors, quantitative sensory testing (QST), genomics, proteomics, metabolomics, lipidomics, and brain imaging. The CCC adapted the A2CPS training and evaluation techniques for certifying the MCCs to ensure competency with recruitment, assessments (surveys, QST, function), and data entry across clinical sites using a combination of virtual training sessions, standardized quantitative measurements, video demonstrations, and reliability assessments. Staff at data collection sites have been successfully certified in all psychophysical assessments (QST, function). This included use of stop watches and metronomes to ensure standard application rates, completion of application-rate and inter-rater-reliability worksheets at each clinical site, designation of site-specific master examiners, training rubrics and video demonstration to verify competency was harmonized across sites. Adaptation of training protocols to a remote format enabled initiation of subject enrollment while maintaining documented standards with high data completion rates for surveys and assessments. The A2CPS Consortium is supported by the National Institutes of Health Common Fund, which is managed by the OD/Office of Strategic Coordination (OSC). Consortium components include: Clinical Coordinating Center (UO1NS077179), Data Integration and Resource Center (UO1NS077352), Omics Data Generation Centers (U54DA049116, U54DA049115, U54DA09113), and Multisite Clinical Centers: MCC 1 (UM1NS112874) and MCC 2 (UM1NS118922). Postdoctoral support for GB provided by the National Institutes of Neurological Disease and Stroke (NINDS) of the NIH under Award Number U24NS112873-03S2.

Mindfulness Meditation Modulates Nociceptive-specific but Not Placebo-related Pain-predictive Patterns

Mindfulness meditation-induced pain relief is more effective and mechanistically distinct from placebo. Machine-learned multivariate patterns are highly specific and predictive of subjective pain responses. The Neurological Pain Signature (NPS) is a multivoxel pattern that is specific to direct nociceptive input. The Stimulus Intensity Independent Pain Signature-1 (SIIPS1) predicts pain beyond stimulus intensity and NPS response and explains placebo-related pain mechanisms, e.g., beliefs, conditioning. Because mindfulness meditation engages non-placebo mechanisms to reduce pain, we hypothesized that mindfulness-based analgesia would modulate the NPS but not SIIPS1. Forty healthy, pain-free individuals were randomly assigned to a four session (20 minutes/session) mindfulness (n=20) or book-listening control (n=20) regimen after baseline pain assessment. Following the respective interventions, BOLD scans were acquired during two heat series (ten, 12s stimuli of noxious 49°C) administered to the right calf at rest (pre-manipulation) followed by two heat series (post-manipulation) during mindfulness (meditation group) or rest (control group). Visual analog scale (VAS) pain ratings (0= "no pain"; 10="worst pain imaginable") were collected after each series. Stimulus-related activation beta maps were resampled to match the voxel dimensions of the NPS and SIIPS1 (canlab.github.io). Beta values were compared to respective signature weights by the dot product to create scalar response values to test study hypotheses. There was a significant pre vs. post X group interaction on NPS responses (p=.04, np2=.11). Post-hoc tests revealed that mindfulness meditation reduced NPS responses when compared to rest (p=.03, np2=.12) and the control group (p=.42, np2=.02). The ANOVA conducted on the SIIPS1 revealed no significant interactions (p=.33, np2=.02) or main effects of manipulation (p=.94, np2=.00) and group (p=.87, np2=.00). The present findings provide novel evidence that mindfulness directly modulates nociceptive-specific but not placebo-related neural mechanisms. Grant support from NCT03414138.

Multi-Site Observational Study to Assess Biomarkers for Susceptibility or Resilience to Chronic Pain: The Acute to Chronic Pain Signatures (A2CPS) Study Protocol.

Chronic pain has become a global health problem contributing to years lived with disability and reduced quality of life. Advances in the clinical management of chronic pain have been limited due to incomplete understanding of the multiple risk factors and molecular mechanisms that contribute to the development of chronic pain. The Acute to Chronic Pain Signatures (A2CPS) Program aims to characterize the predictive nature of biomarkers (brain imaging, high-throughput molecular screening techniques, or “omics,” quantitative sensory testing, patient-reported outcome assessments and functional assessments) to identify individuals who will develop chronic pain following surgical intervention. The A2CPS is a multisite observational study investigating biomarkers and collective biosignatures (a combination of several individual biomarkers) that predict susceptibility or resilience to the development of chronic pain following knee arthroplasty and thoracic surgery. This manuscript provides an overview of data collection methods and procedures designed to standardize data collection across multiple clinical sites and institutions. Pain-related biomarkers are evaluated before surgery and up to 3 months after surgery for use as predictors of patient reported outcomes 6 months after surgery. The dataset from this prospective observational study will be available for researchers internal and external to the A2CPS Consortium to advance understanding of the transition from acute to chronic postsurgical pain.

297 The Acute to Chronic Pain Signatures Program (A2CPS): Conceptual Design and Protocol Implementation of a Multi-site Observational Study Assessing Risk and Resilience Biomarkers

OBJECTIVES/GOALS: The A2CPS was funded by the National Institutes of Health (NIH) Common Fund to identify biomarkers and their collective biosignatures (combination of several biomarkers) that predict susceptibility or resilience to the development of chronic pain. METHODS/STUDY POPULATION: The A2CPS includes 2-Multisite Clinical Centers (10 recruitment sites and 6 data collection sites), 1-Clinical Coordinating Center, 1-Data Integration and Resource Center, 3-Omics Data Generation Centers, and representation from the NIH. The A2CPS will recruit a large cohort from 2 different surgical interventions, total knee arthroplasty (n?1800) and thoracotomy (n?1800). This observational study will collect candidate and exploratory biomarkers across the following domains: clinical pain, fatigue, function, sleep, psychosocial, genomics, proteomics, metabolomics, lipidomics, pain sensitivity, and brain imaging. Data will be collected before and up to 3 months after surgery to determine factors that predict chronic pain at 6 months. RESULTS/ANTICIPATED RESULTS: Recruitment started in 2021 following standard operating procedures and is ongoing at both Multisite Clinical Centers. The A2CPS will provide an example of collaborative, multidisciplinary efforts in establishing a data repository consisting of biopsychosocial markers that will be available to the research community to test novel hypotheses. This presentation will describe the conceptual design, study aims, biomarker selection, protocol standardization and study implementation for the A2CPS. An update on study progress and data completeness will be presented. Final results will be reported after study completion which is anticipated by 2024. DISCUSSION/SIGNIFICANCE: Identifying biomarkers and biosignatures that predict high- versus low-risk for the transition to chronic pain will inform future clinical trials, identify novel therapeutic targets, and advance personalized pain treatment strategies; ultimately transforming the prevention and treatment of chronic postsurgical pain.

Processing of pain by the developing brain: evidence of differences between adolescent and adult females.

Adolescence is a sensitive period for both brain development and the emergence of chronic pain particularly in females. However, the brain mechanisms supporting pain perception during adolescence remain unclear. This study compares perceptual and brain responses to pain in female adolescents and adults to characterize pain processing in the developing brain. Thirty adolescent (ages 13-17 years) and 30 adult (ages 35-55 years) females underwent a functional magnetic resonance imaging scan involving acute pain. Participants received 12 ten-second noxious pressure stimuli that were applied to the left thumbnail at 2.5 and 4 kg/cm 2 , and rated pain intensity and unpleasantness on a visual analogue scale. We found a significant group-by-stimulus intensity interaction on pain ratings. Compared with adults, adolescents reported greater pain intensity and unpleasantness in response to 2.5 kg/cm 2 but not 4 kg/cm 2 . Adolescents showed greater medial-lateral prefrontal cortex and supramarginal gyrus activation in response to 2.5 kg/cm 2 and greater medial prefrontal cortex and rostral anterior cingulate responses to 4 kg/cm 2 . Adolescents showed greater pain-evoked responses in the neurologic pain signature and greater activation in the default mode and ventral attention networks. Also, the amygdala and associated regions played a stronger role in predicting pain intensity in adolescents, and activity in default mode and ventral attention regions more strongly mediated the relationship between stimulus intensity and pain ratings. This study provides first evidence of greater low-pain sensitivity and pain-evoked brain responses in female adolescents (vs adult women) in regions important for nociceptive, affective, and cognitive processing, which may be associated with differences in peripheral nociception.

Neuroscientific evidence for pain being a classically conditioned response to trauma- and pain-related cues in humans.

Psychological trauma is typically accompanied by physical pain, and posttraumatic stress disorder (PTSD) often cooccurs with chronic pain. Clinical reports suggest that pain after trauma may be part of re-experiencing symptomatology. Classical conditioning can underlie visual re-experiencing because intrusions can occur as conditioned responses (CRs) to trauma-related cues. If individuals also experience pain to cues previously paired with, but not inflicting nociceptive stimulation anymore (ie, conditioned stimuli, CS), conditioning could also explain re-experiencing of pain. Sixty-five participants underwent classical conditioning, where painful electrocutaneous stimulation and aversive film clips served as unconditioned stimuli (US) in a 2 (pain/no pain) × 2 (aversive/neutral film) design. Conditioned stimuli were neutral pictures depicting contextual details from the films. One day later, participants were re-exposed to CS during a memory-triggering task (MTT). We assessed pain-CRs by self-report and an fMRI-based marker of nociceptive pain, the neurological pain signature (NPS), and recorded spontaneous daily-life pain intrusions with an e-diary. During conditioning, pain-signaling CS elicited more self-reported pain and NPS responses than no-pain-signaling CS. Possibly because the aversive film masked differences in participants' responses to pain-signaling CS vs no pain-signaling CS, pain-CRs during acquisition were most evident within the neutral film condition. When participants were re-exposed to CS during MTT, self-reported pain-CRs during the neutral film condition and, although more uncertain, NPS-CRs during the aversive film condition persisted. Of importance, participants with stronger pain-CRs showed a greater probability and severity of experiencing spontaneous pain intrusions during daily life. Our data support that spatiotemporally associating innocuous cues with pain (CS) endows these cues to elicit conditioned pain responses in the absence of noxious stimulation. In this way pain can emerge as a CR with emotional and sensory components. Classical conditioning presents a possible mechanism explaining pain intrusions and, more broadly, pain experienced without a nociceptive input.

The neurologic pain signature responds to nonsteroidal anti-inflammatory treatment vs placebo in knee osteoarthritis.

Many drug trials for chronic pain fail because of high placebo response rates in primary endpoints. Neurophysiological measures can help identify pain-linked pathophysiology and treatment mechanisms. They can also help guide early stop/go decisions, particularly if they respond to verum treatment but not placebo. The neurologic pain signature (NPS), an fMRI-based measure that tracks evoked pain in 40 published samples and is insensitive to placebo in healthy adults, provides a potentially useful neurophysiological measure linked to nociceptive pain. This study aims to validate the NPS in knee osteoarthritis (OA) patients and test the effects of naproxen on this signature. In 2 studies (50 patients, 64.6 years, 75% females), we (1) test the NPS and other control signatures related to negative emotion in knee OA pain patients; (2) test the effect of placebo treatments; and (3) test the effect of naproxen, a routinely prescribed nonsteroidal anti-inflammatory drug in OA. The NPS was activated during knee pain in OA (d = 1.51, P < 0.001) and did not respond to placebo (d = 0.12, P = 0.23). A single dose of naproxen reduced NPS responses (vs placebo, NPS d = 0.34, P = 0.03 and pronociceptive NPS component d = 0.38, P = 0.02). Naproxen effects were specific for the NPS and did not appear in other control signatures. This study provides preliminary evidence that fMRI-based measures, validated for nociceptive pain, respond to acute OA pain, do not appear sensitive to placebo, and are mild-to-moderately sensitive to naproxen.

Individually unique dynamics of cortical connectivity reflect the ongoing intensity of chronic pain.

Chronic pain diseases are characterised by an ongoing and fluctuating endogenous pain, yet it remains to be elucidated how this is reflected by the dynamics of ongoing functional cortical connections. In this study, we investigated the cortical encoding of 20 patients with chronic back pain and 20 chronic migraineurs in 4 repeated fMRI sessions. A brain parcellation approach subdivided the whole brain into 408 regions. Linear mixed-effects models were fitted for each pair of brain regions to explore the relationship between the dynamic cortical connectivity and the observed trajectory of the patients' ratings of fluctuating endogenous pain. Overall, we found that periods of high and increasing pain were predominantly related to low cortical connectivity. The change of pain intensity in chronic back pain was subserved by connections in left parietal opercular regions, right insular regions, as well as large parts of the parietal, cingular, and motor cortices. The change of pain intensity direction in chronic migraine was reflected by decreasing connectivity between the anterior insular cortex and orbitofrontal areas, as well as between the PCC and frontal and anterior cingulate cortex regions. Of interest, the group results were not mirrored by the individual patterns of pain-related connectivity, which rejects the idea of a common neuronal core problem for chronic pain diseases. The diversity of the individual cortical signatures of chronic pain encoding results adds to the understanding of chronic pain as a complex and multifaceted disease. The present findings support recent developments for more personalised medicine.