Identification of traits and functional connectivity-based neurotraits of chronic pain.

Psychological and personality factors, socioeconomic status, and brain properties all contribute to chronic pain but have essentially been studied independently. Here, we administered a broad battery of questionnaires to patients with chronic back pain (CBP) and collected repeated sessions of resting-state functional magnetic resonance imaging (fMRI) brain scans. Clustering and network analyses applied on the questionnaire data revealed four orthogonal dimensions accounting for 56% of the variance and defining chronic pain traits. Two of these traits-Pain-trait and Emote-trait-were associated with back pain characteristics and could be related to distinct distributed functional networks in a cross-validation procedure, identifying neurotraits. These neurotraits showed good reliability across four fMRI sessions acquired over five weeks. Further, traits and neurotraits all related to the income, emphasizing the importance of socioeconomic status within the personality space of chronic pain. Our approach is a first step in providing metrics aimed at unifying the psychology and the neurophysiology of chronic pain applicable across diverse clinical conditions.

Hippocampal morphology mediates biased memories of chronic pain.

Experiences and memories are often mismatched. While multiple studies have investigated psychological underpinnings of recall error with respect to emotional events, the neurobiological mechanisms underlying the divergence between experiences and memories remain relatively unexplored in the domain of chronic pain. Here we examined the discrepancy between experienced chronic low back pain (CBP) intensity (twice daily ratings) and remembered pain intensity (n = 48 subjects) relative to psychometric properties, hippocampus morphology, memory capabilities, and personality traits related to reward. 77% of CBP patients exaggerated remembered pain, which depended on their strongest experienced pain and their most recent mood rating. This bias persisted over nearly 1 year and was related to reward memory bias and loss aversion. Shape displacement of a specific region in the left posterior hippocampus mediated personality effects on pain memory bias, predicted pain memory bias in a validation CBP group (n = 21), and accounted for 55% of the variance of pain memory bias. In two independent groups (n = 20/group), morphology of this region was stable over time and unperturbed by the development of chronic pain. These results imply that a localized hippocampal circuit, and personality traits associated with reward processing, largely determine exaggeration of daily pain experiences in chronic pain patients.

Translation and validation of Simplified Chinese version of the Pain Catastrophizing Scale in chronic pain patients: Education may matter.

Objective Pain catastrophizing is linked to many aspects of pain perception and defines a unique dimension in predicting pain intensity and physical disability. Pain Catastrophizing Scale (PCS) is an effective, validated,self-report measure, commonly used in clinical trials. Here, we present a Simplified Chinese PCS (SC-PCS) version developed in Chinese patients suffering from chronic pain. Methods The SC-PCS was generated in five steps and tested on an initial patient cohort (N = 30). A convenience sample (N = 200) of in-hospital patients with non-malignant pain lasting for more than 12 weeks were recruited for the study, of which 81 completed 5 additional pain questionnaires. A subset (N = 24) of the patients completed an additional SC-PCS, 10 days after the initial query to assess test-retest validation. Results Intra-class correlations coefficient indicated high reproducibility and temporal consistency, (0.97), for the total score. Cronbach's alpha determined high internal consistency across the SC-PCS total score and its three subscales (0.87, 0.85, 0.62, and 0.65). The SC-PCS total score moderately or weakly (R = -0.2 to 0.49), but significantly, correlated with other measurements, such as pain Visual Analog Scale, Beck Depression Inventory, Pain Anxiety Symptoms Scales, Positive and Negative Affect Schedule, and education. We used exploratory factor analysis to examine the dimensionality of the SC-PCS, which indicated instability of the current three-factor model. However, a confirmatory factor analysis indicated that the three-factor model had the best goodness-fitting. Conclusions We demonstrate the successful translational adaptation from English to Simplified Chinese as well as the reliability and validity of SC-PCS. An important discovery was education level significantly correlated with SC-PCS, identifying a future consideration for other cross-cultural development of self-reported measures.

Validating a biosignature-predicting placebo pill response in chronic pain in the settings of a randomized controlled trial.

ABSTRACT: The objective of this study is to validate a placebo pill response predictive model-a biosignature-that classifies chronic pain patients into placebo responders (predicted-PTxResp) and nonresponders (predicted-PTxNonR) and test whether it can dissociate placebo and active treatment responses. The model, based on psychological and brain functional connectivity, was derived in our previous study and blindly applied to current trial participants. Ninety-four chronic low back pain (CLBP) patients were classified into predicted-PTxResp or predicted-PTxNonR and randomized into no treatment, placebo treatment, or naproxen treatment. To monitor analgesia, back pain intensity was collected twice a day: 3 weeks baseline, 6 weeks of treatment, and 3 weeks of washout. Eighty-nine CLBP patients were included in the intent-to-treat analyses and 77 CLBP patients in the per-protocol analyses. Both analyses showed similar results. At the group level, the predictive model performed remarkably well, dissociating the separate effect sizes of pure placebo response and pure active treatment response and demonstrating that these effects interacted additively. Pain relief was about 15% stronger in the predicted-PTxResp compared with the predicted-PTxNonR receiving either placebo or naproxen, and the predicted-PTxNonR successfully isolated the active drug effect. At a single subject level, the biosignature better predicted placebo nonresponders, with poor accuracy. One component of the biosignature (dorsolateral prefrontal cortex-precentral gyrus functional connectivity) could be generalized across 3 placebo studies and in 2 different cohorts-CLBP and osteoarthritis pain patients. This study shows that a biosignature can predict placebo response at a group level in the setting of a randomized controlled trial.

Quantitative language features identify placebo responders in chronic back pain.

ABSTRACT: Although placebo effect sizes in clinical trials of chronic pain treatments have been increasing, it remains unknown if characteristics of individuals' thoughts or previous experiences can reliably infer placebo pill responses. Research using language to investigate emotional and cognitive processes has recently gained momentum. Here, we quantified placebo responses in chronic back pain using more than 300 semantic and psycholinguistic features derived from patients' language. This speech content was collected in an exit interview as part of a clinical trial investigating placebo analgesia (62 patients, 42 treated; 20 not treated). Using a nested leave-one-out cross-validated approach, we distinguished placebo responders from nonresponders with 79% accuracy using language features alone; a subset of these features-semantic distances to identity and stigma and the number of achievement-related words-also explained 46% of the variance in placebo analgesia. Importantly, these language features were not due to generic treatment effects and were associated with patients' specific baseline psychological traits previously shown to be predictive of placebo including awareness and personality characteristics, explaining an additional 31% of the variance in placebo analgesia beyond that of personality. Initial interpretation of the features suggests that placebo responders differed in how they talked about negative emotions and the extent that they expressed awareness to various aspects of their experiences; differences were also seen in time spent talking about leisure activities. These results indicate that patients' language is sufficient to identify a placebo response and implie that specific speech features may be predictive of responders' previous treatment.

Brain and psychological determinants of placebo pill response in chronic pain patients.

The placebo response is universally observed in clinical trials of pain treatments, yet the individual characteristics rendering a patient a 'placebo responder' remain unclear. Here, in chronic back pain patients, we demonstrate using MRI and fMRI that the response to placebo 'analgesic' pills depends on brain structure and function. Subcortical limbic volume asymmetry, sensorimotor cortical thickness, and functional coupling of prefrontal regions, anterior cingulate, and periaqueductal gray were predictive of response. These neural traits were present before exposure to the pill and most remained stable across treatment and washout periods. Further, psychological traits, including interoceptive awareness and openness, were also predictive of the magnitude of response. These results shed light on psychological, neuroanatomical, and neurophysiological principles determining placebo response in RCTs in chronic pain patients, and they suggest that the long-term beneficial effects of placebo, as observed in clinical settings, are partially predictable.