Proteomics based markers of clinical pain severity in juvenile idiopathic arthritis

Introduction Juvenile idiopathic arthritis (JIA) is a cluster of autoimmune rheumatic diseases occurring in children 16 years of age or less. While it is well-known that pain may be experienced during inflammatory and non-inflammatory states, much remains ambiguous regarding the molecular mechanisms that may drive JIA pain. Thus, in this pilot study, we explored the variability of the serum proteomes in relation to pain severity in a cohort of JIA patients. Methods Serum samples from 15 JIA patients (male and female, 12.7 ± 2.8 years of age) were assessed using liquid chromatography/mass spectrometry (LC/MS). Correlation analyses were performed to determine the relationships among protein levels and self-reported clinical pain severity. Additionally, how the expression of pain-associated proteins related to markers of inflammation (Erythrocyte Sedimentation Rate (ESR)) or morphological properties of the central nervous system (subcortical volume and cortical thickness) implicated in JIA were also evaluated. Results 306 proteins were identified in the JIA cohort of which 14 were significantly (p < 0.05) associated with clinical pain severity. Functional properties of the identified pain-associated proteins included but were not limited to humoral immunity (IGLV3.9), inflammatory response (PRG4) and angiogenesis (ANG). Associations among pain-associated proteins and ESR (IGHV3.9, PRG4, CST3, VWF, ALB), as well as caudate nucleus volume (BTD, AGT, IGHV3.74) and insular cortex thickness (BTD, LGALS3BP) were also observed. Conclusions The current proteomic findings suggest both inflammatory- and non-inflammatory mediated mechanisms as potential factors associated with JIA pain. Validation of these preliminary observations using larger patient cohorts and a longitudinal study design may further point to novel serologic markers of pain in JIA.

Advances With Non-coding RNAs in Neuropathic Pain

Neuropathic pain (NP) is one of the most common types of clinical pain. The common causes of this syndrome include injury to the central or peripheral nervous systems and pathological changes. NP is characterized by spontaneous pain, hyperalgesia, abnormal pain, and paresthesia. Because of its diverse etiology, the pathogenesis of NP has not been fully elucidated and has become one of the most challenging problems in clinical medicine. This kind of pain is extremely resistant to conventional treatment and is accompanied by serious complications. Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), contribute to diverse biological processes by regulating the expression of various mRNAs involved in pain-related pathways, at the posttranscriptional level. Abnormal regulation of ncRNAs is closely related to the occurrence and development of NP. In this review, we summarize the current state of understanding of the roles of different ncRNAs in the development of NP. Understanding these mechanisms can help develop novel therapeutic strategies to prevent or treat chronic pain.

Remotely Supervised Cranial Electrical Stimulation and Clinical Pain for Older Adults With Knee Osteoarthritis

Knee osteoarthritis (KOA) is one of the most prominent causes of chronic pain, functional impairment, and disability in older adults. The current standards of care for KOA are aimed toward reducing pain and are largely comprised of analgesic medications, but existing pharmacologic approaches often produce significant adverse effects. Moreover, recent evidence suggests that KOA pain is characterized by alterations in pain-related brain mechanisms. Cranial electrical stimulation (CES), which delivers a low-amplitude alternating electric current to the brain, can facilitate the reversal of maladaptive brain function. Portable CES devices can be used at home with real-time monitoring through a secure videoconferencing platform to facilitate high adherence. Thus, the purpose of this pilot clinical study was to examine the preliminary efficacy of remotely supervised CES on clinical pain severity in older adults with KOA. Thirty participants with KOA were randomly assigned to receive 10 daily sessions of remotely supervised CES with 0.1 mA at a frequency of 0.5 Hz for 60 minutes (n=15) or sham CES (n=15). We measured clinical pain severity using the numeric rating scale (NRS; range, 0 – 100). Participants (67% female) had a mean age of 59 years. Active CES significantly reduced scores on the NRS (Cohen’s d = 1.43, P &lt; 0.01). Participants tolerated CES well without any adverse events. Our findings demonstrate the promising clinical efficacy of remotely supervised CES for older adults with KOA. Future studies with larger-scale randomized controlled trials with follow-up assessments are needed to validate and extend our findings.

Associations of pain severity and mobility with age in chronic low back pain: does the type of assessment matter?

Chronic low back pain (cLBP) can lead to severe pain symptoms as well as disability in adults. As individuals age, pain symptoms and mobility outcomes can become increasingly debilitating. However, current findings regarding the influence of age on symptoms and outcomes are mixed and may be attributed to the assessment methodologies for pain and mobility. Therefore, we sought to examine the association of age with broad and specific assessments of pain severity and mobility commonly implemented in adults with cLBP. cLBP participants (n = 158) completed questionnaires regarding pain intensity and disability including demographics, Clinical Pain Assessment (CPA) and the Oswestry Low Back Pain questionnaire (OLBP). Participants also completed assessments of movement-evoked pain and difficulty by performing the Short Physical Performance Battery (SPPB). Pearson’s chi-square tests and regression-based analyses were conducted using SPSS version 26.0. Among cLBP participants, age was associated with pain-related disability indexed by section one of the OLBPS regarding pain intensity (F= 5.0, p&lt;.05), and mobility via total SPPB score (F= 11.7, p&lt;.05). Interestingly, age predicted greater self-reported difficulty climbing stairs (F= 21.7, p&lt;.05), performing chores (F= 17.0, p&lt;.05), walking (F= 14.0, p&lt;.05), and running errands (F= 13.4, p&lt;.05) from the CPA. Further, age predicted total balance (F= 3.2, p&lt;.05), gait speed (F= 7.8, p&lt;.05), and chair stand (F= 6.5, p&lt;.05) scores of SPPB. Age is associated with questionnaires assessing cLBP pain severity and is also associated with mobility outcomes. Future research should seek to understand the influence of age on movement-evoked pain in cLBP.

Pain Persistence Is Associated With Increased Odds of MCI in Late Midlife and Early Older Adulthood

Twenty percent of older adults will experience persistent pain, the sensation of bodily harm lasting three or more months. Persistent pain doubles the risk of dementia, but we know less about the impact on earlier stages, such as mild cognitive impairment (MCI). As a step for clarification, this study leveraged data from the Vietnam Era Twin Study of Aging (VETSA) to understand how pain persistence relates to MCI in late midlife to early older adulthood. Participants (n=1,465, 100% male) were recruited across three waves at average ages 56, 62, and 68. At each wave, participants completed the SF-36 and were asked to rate their pain intensity from none (1) to very severe (6). Clinical pain was coded as pain intensity rated more than mild (&gt;3/6). As a time-varying predictor, pain persistence was then calculated as a running frequency of the total waves reporting clinical pain. MCI diagnosis was based on Jak-Bondi criteria. Age, depressive symptoms, comorbidities, and opioid use were included as time-varying covariates. Age and education were included as time-invariant covariates. General estimating equations showed that pain persistence over two waves, reported in 35% of the sample, increased MCI odds by 57% (OR=1.57, 95%CI: 1.28 to 1.94). Pain persistence over three waves, reported in 17% of the sample, increased MCI odds by 98% (OR=1.98, 95%CI: 1.44 to 2.70). The findings emphasize the role of pain in earlier stages of dementia and the potential importance of pain management in offsetting cognitive decline.

What Is the Numerical Nature of Pain Relief?

Pain relief, or a decrease in self-reported pain intensity, is frequently the primary outcome of pain clinical trials. Investigators commonly report pain relief in one of two ways: using raw units (additive) or using percentage units (multiplicative). However, additive and multiplicative scales have different assumptions and are incompatible with one another. In this work, we describe the assumptions and corollaries of additive and multiplicative models of pain relief to illuminate the issue from statistical and clinical perspectives. First, we explain the math underlying each model and illustrate these points using simulations, for which readers are assumed to have an understanding of linear regression. Next, we connect this math to clinical interpretations, stressing the importance of statistical models that accurately represent the underlying data; for example, how using percent pain relief can mislead clinicians if the data are actually additive. These theoretical discussions are supported by empirical data from four longitudinal studies of patients with subacute and chronic pain. Finally, we discuss self-reported pain intensity as a measurement construct, including its philosophical limitations and how clinical pain differs from acute pain measured during psychophysics experiments. This work has broad implications for clinical pain research, ranging from statistical modeling of trial data to the use of minimal clinically important differences and patient-clinician communication.

Segmental Chiropractic Spinal Manipulation Does not Reduce Pain Amplification and the Associated Pain-Related Brain Activity in a Capsaicin-Heat Pain Model

Musculoskeletal injuries lead to sensitization of nociceptors and primary hyperalgesia (hypersensitivity to painful stimuli). This occurs with back injuries, which are associated with acute pain and increased pain sensitivity at the site of injury. In some cases, back pain persists and leads to central sensitization and chronic pain. Thus, reducing primary hyperalgesia to prevent central sensitization may limit the transition from acute to chronic back pain. It has been shown that spinal manipulation (SM) reduces experimental and clinical pain, but the effect of SM on primary hyperalgesia and hypersensitivity to painful stimuli remains unclear. The goal of the present study was to investigate the effect of SM on pain hypersensitivity using a capsaicin-heat pain model. Laser stimulation was used to evoke heat pain and the associated brain activity, which were measured to assess their modulation by SM. Eighty healthy participants were recruited and randomly assigned to one of the four experimental groups: inert cream and no intervention; capsaicin cream and no intervention; capsaicin cream and SM at T7; capsaicin cream and placebo. Inert or capsaicin cream (1%) was applied to the T9 area. SM or placebo were performed 25 min after cream application. A series of laser stimuli were delivered on the area of cream application (1) before cream application, (2) after cream application but before SM or placebo, and (3) after SM or placebo. Capsaicin cream induced a significant increase in laser pain (p &lt; 0.001) and laser-evoked potential amplitude (p &lt; 0.001). However, SM did not decrease the amplification of laser pain or laser-evoked potentials by capsaicin. These results indicate that segmental SM does not reduce pain hypersensitivity and the associated pain-related brain activity in a capsaicin-heat pain model.

Built to Scale: A Corpus-Based Analysis of Adjective Scales in the Mcgill Pain Questionnaire

Modern medical diagnosis relies on precise pain assessment tools in translating clinical information from patient to physician. The McGill Pain Questionnaire (MPQ) is a clinical pain assessment technique that utilizes 78 adjectives of different intensities in 20 categories to quantify a patient’s pain. The questionnaire’s efficacy depends on a predictable pattern of adjective use by patients experiencing pain. In this study, I recreate the MPQ’s adjective intensity orderings using data gathered from patient forums and modern NLP techniques. I extract adjective intensity relationships by searching for key linguistic contexts, and then combine the relationship information to form robust adjective scales. Of 17 adjective relationships predicted by this research, only 4 diverge from the MPQ’s orderings, which is statistically significant at the 0.1 alpha level. The results suggest predictable patterns of adjective use by people experiencing pain, but call into question the MPQ’s categories for grouping adjectives.