Change in resting state functional connectivity following working memory training in individuals with repetitive negative thinking.

BACKGROUND: Repetitive negative thinking (RNT) symptoms, which are characterized by pervasive, uncontrollable negative thoughts, are common in individuals with mood, anxiety, and traumatic stress disorders. Inability to regulate the contents of working memory is a hypothesized etiological factor in RNT, suggesting that training to improve working memory may be beneficial. This study examined the effects of working memory training on resting state functional connectivity (rsFC) in individuals with elevated RNT and whether such changes would be associated with clinical improvement. METHODS: We conducted a secondary analysis of pre-post resting state data collected as part of a randomized controlled trial [NCT04912089] of working memory training interventions (n=42) compared to a waitlist control group (n=23). We hypothesized that individuals completing training would show increased rsFC between the two key intrinsic connectivity networks - default mode network (posterior cingulate cortex; PCC) and frontoparietal network (dorsolateral prefrontal cortex; dlPFC). We explored whether magnitude of rsFC change was associated with change in RNT symptom severity. RESULTS: rsFC increased between the PCC and regions including frontal and parietal cortex in the training group relative to waitlist. Increased connectivity between the PCC and superior frontal cortex was associated with RNT symptom reduction. CONCLUSIONS: These data provide evidence that working memory training can modulate neural circuitry at rest in individuals with RNT. Results align with accounts of working memory training effects on large-scale neurocircuitry changes and suggest that these changes may contribute to clinical promise of this type of intervention on transdiagnostic RNT symptoms.

Motivational context and neurocomputation of stop expectation moderate early attention responses supporting proactive inhibitory control.

Alterations in attention to cues signaling the need for inhibitory control play a significant role in a wide range of psychopathology. However, the degree to which motivational and attentional factors shape the neurocomputations of proactive inhibitory control remains poorly understood. The present study investigated how variation in monetary incentive valence and stake modulate the neurocomputational signatures of proactive inhibitory control. Adults (N = 46) completed a Stop-Signal Task (SST) with concurrent EEG recording under four conditions associated with stop performance feedback: low and high punishment (following unsuccessful stops) and low and high reward (following successful stops). A Bayesian learning model was used to infer individual's probabilistic expectations of the need to stop on each trial: P(stop). Linear mixed effects models were used to examine whether interactions between motivational valence, stake, and P(stop) parameters predicted P1 and N1 attention-related event-related potentials (ERPs) time-locked to the go-onset stimulus. We found that P1 amplitudes increased at higher levels of P(stop) in punished but not rewarded conditions, although P1 amplitude differences between punished and rewarded blocks were maximal on trials when the need to inhibit was least expected. N1 amplitudes were positively related to P(stop) in the high punishment condition (low N1 amplitude), but negatively related to P(stop) in the high reward condition (high N1 amplitude). Critically, high P(stop)-related N1 amplitude to the go-stimulus predicted behavioral stop success during the high reward block, providing evidence for the role of motivationally relevant context and inhibitory control expectations in modulating the proactive allocation of attentional resources that affect inhibitory control. These findings provide novel insights into the neurocomputational mechanisms underlying proactive inhibitory control under valence-dependent motivational contexts, setting the stage for developing motivation-based interventions that boost inhibitory control.

Exploring the effects of fitbit incentive on treatment outcomes in veterans undergoing intensive pain rehabilitation program.

OBJECTIVE: This study compares clinical pain outcomes between patients in a pain treatment program that received a Fitbit, to patients that did not. We also explored: (1) cognitive, emotional, and psychological factors that may have impacted the decision to opt in to receiving a Fitbit; and (2) whether the choice to receive a Fitbit impacted changes in cognitive, emotional, and psychological factors following treatment. METHODS: Among 58 patients in a multidisciplinary pain treatment program at a Veterans Affairs Healthcare System hospital, 31 patients opted to receive a Fitbit as adjunct treatment, while 27 did not. This study utilized patient-reported and practitioner-collected data from the pain treatment program. RESULTS: Compared to the non-Fitbit group, the Fitbit group displayed a significant decrease in average pain intensity, however showed no correlation between Fitbit activity and average pain intensity. Additionally, treatment satisfaction was the only predictor of treatment group, when modeling pre- and post-treatment outcomes changes. CONCLUSION: The implementation of a Fitbit may lead to improved pain intensity. Initial evidence suggests that opting to receive a Fitbit during a pain treatment program indicates treatment engagement leading to greater treatment satisfaction. Future work is needed to verify and expand upon this potential mechanism.

Identification of group differences in predictive anticipatory biasing of pain during uncertainty: preparing for the worst but hoping for the best.

ABSTRACT: Pain anticipation during conditions of uncertainty can unveil intrinsic biases, and understanding these biases can guide pain treatment interventions. This study used machine learning and functional magnetic resonance imaging to predict anticipatory responses in a pain anticipation experiment. One hundred forty-seven participants that included healthy controls (n = 57) and individuals with current and/or past mental health diagnosis (n = 90) received cues indicating upcoming pain stimuli: 2 cues predicted high and low temperatures, while a third cue introduced uncertainty. Accurate differentiation of neural patterns associated with specific anticipatory conditions was observed, involving activation in the anterior short gyrus of the insula and the nucleus accumbens. Three distinct response profiles emerged: subjects with a negative bias towards high pain anticipation, those with a positive bias towards low pain anticipation, and individuals whose predictions during uncertainty were unbiased. These profiles remained stable over one year, were consistent across diagnosed psychopathologies, and correlated with cognitive coping styles and underlying insula anatomy. The findings suggest that individualized and stable pain anticipation occurs in uncertain conditions.

Amplification of Positivity Treatment for Anxiety and Depression: A Randomized Experimental Therapeutics Trial Targeting Social Reward Sensitivity to Enhance Social Connectedness.

BACKGROUND: Social disconnection is common and causes significant impairment in anxiety and depressive disorders, and it does not respond sufficiently to available treatments. The positive valence system supports social bond formation and maintenance but is often hyporesponsive in people with anxiety or depression. We conducted an experimental therapeutics trial to test the hypothesis that targeting positive valence processes through cognitive and behavioral strategies would enhance responsivity to social rewards, a core mechanism underlying social connectedness. METHODS: Sixty-eight adults who endorsed clinically elevated anxiety and/or depression with social impairment were randomized 1:1:1 to 5 (n = 23) or 10 (n = 22) sessions of amplification of positivity (AMP) treatment or waitlist (n = 23). Pre- to posttreatment change in striatal activity (primary outcome) during social reward anticipation was measured using functional magnetic resonance imaging, and reactivity to a social affiliation task (secondary) and self-reported social connectedness (exploratory) were examined. Primary analyses compared AMP (doses combined) versus waitlist. A second aim was to compare the effects of different doses. RESULTS: AMP engaged the hypothesized treatment target, leading to greater striatal activation during anticipation of social rewards versus waitlist (d = 1.01 [95% CI = 0.42-1.61]; largest striatal volume). AMP yielded larger improvements in positive affect and approach behavior during the affiliation task (but not other outcomes) and social connectedness. Larger striatal and social connectedness increases were observed for 5-session versus 10-session AMP (d range = 0.08-1.03). CONCLUSIONS: Teaching people with anxiety or depression strategies to increase positive thoughts, behaviors, and emotions enhances activity in brain regions that govern social reward processing and promotes social connectedness. Social reward sensitivity may be a transdiagnostic target for remediating social disconnection.

Unsupervised learning for prognostic validity in patients with chronic pain in transdisciplinary pain care.

Chronic pain is not a singular disorder and presents in various forms and phenotypes. Here we show data from a cohort of patients seeking treatment in a transdisciplinary pain clinic. Patients completed a multidimensional patient-reported battery as part of routine initial evaluation at baseline and at each of the four subsequent visits over 1-year follow-up (0, 1, 3, 6, 12 months). The goal of this work was to use unsupervised modeling approach to identify whether patients with chronic pain undergoing transdisciplinary intensive rehabilitation treatment: (1) can be derived based upon self-reported outcome measures at baseline (or before treatment initiation), (2) are clinically validated based on their clinical diagnosis and medication use, and (3) differ in treatment trajectories over 1 year of transdisciplinary treatment. We applied unsupervised clustering on baseline outcomes using nine patient-reported symptoms and examined treatment trajectories. The three-cluster solution was internally validated. Psychiatric diagnosis, chronic back pain-related disability and symptoms severity determined cluster assignment and treatment prognosis. Conversely, clinical pain severity had lesser effect. Furthermore, clusters showed stability over time despite symptoms improvement. The accurate and meaningful subgrouping of the underlying chronic pain phenotypes would greatly enhance treatment and provide personalized and effective pain management.

State-specific alterations in the neural computations underlying inhibitory control in women remitted from bulimia nervosa.

The neurocomputational processes underlying bulimia nervosa and its primary symptoms, out-of-control overeating and purging, are poorly understood. Research suggests that the brains of healthy individuals form a dynamic internal model to predict whether control is needed in each moment. This study tested the hypothesis that this computational process of inhibitory control is abnormally affected by metabolic state (being fasted or fed) in bulimia nervosa. A Bayesian ideal observer model was fit to behavioral data acquired from 22 women remitted from bulimia nervosa and 20 group-matched controls who completed a stop-signal task during two counterbalanced functional MRI sessions, one after a 16 h fast and one after a meal. This model estimates participants' trial-by-trial updating of the probability of a stop signal based on their experienced trial history. Neural analyses focused on control-related Bayesian prediction errors, which quantify the direction and degree of "surprise" an individual experiences on any given trial. Regardless of group, metabolic state did not affect behavioral performance on the task. However, metabolic state modulated group differences in neural activation. In the fed state, women remitted from bulimia nervosa had attenuated prediction-error-dependent activation in the left dorsal caudate. This fed-state activation was lower among women with more frequent past binge eating and self-induced vomiting. When they are in a fed state, individuals with bulimia nervosa may not effectively process unexpected information needed to engage inhibitory control. This may explain the difficulties these individuals have stopping eating after it begins.

Resting-state connectivity subtype of comorbid PTSD and alcohol use disorder moderates improvement from integrated prolonged exposure therapy in Veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid and are associated with significant functional impairment and inconsistent treatment outcomes. Data-driven subtyping of this clinically heterogeneous patient population and the associated underlying neural mechanisms are highly needed to identify who will benefit from psychotherapy. METHODS: In 53 comorbid PTSD/AUD patients, resting-state functional magnetic resonance imaging was collected prior to undergoing individual psychotherapy. We used a data-driven approach to subgroup patients based on directed connectivity profiles. Connectivity subgroups were compared on clinical measures of PTSD severity and heavy alcohol use collected at pre- and post-treatment. RESULTS: We identified a subgroup of patients associated with improvement in PTSD symptoms from integrated-prolonged exposure therapy. This subgroup was characterized by lower insula to inferior parietal cortex (IPC) connectivity, higher pregenual anterior cingulate cortex (pgACC) to posterior midcingulate cortex connectivity and a unique pgACC to IPC path. We did not observe any connectivity subgroup that uniquely benefited from integrated-coping skills or subgroups associated with change in alcohol consumption. CONCLUSIONS: Data-driven approaches to characterize PTSD/AUD subtypes have the potential to identify brain network profiles that are implicated in the benefit from psychological interventions - setting the stage for future research that targets these brain circuit communication patterns to boost treatment efficacy.

HIV peripheral neuropathy-related degeneration of white matter tracts to sensorimotor cortex.

Human immunodeficiency virus-associated distal sensory polyneuropathy (HIV-DSP) affects up to 50% of people with HIV and is associated with depression, unemployment, and generally worsened quality of life. Previous work on the cortical mechanism of HIV neuropathy found decreased gray matter volume in the bilateral midbrain, thalamus, and posterior cingulate cortex, but structural connectivity in this context remains under-studied. Here we examine alterations in white matter microstructure using diffusion imaging, hypothesizing that cortical white matter degeneration would be observed in continuation of the peripheral white matter atrophy previously observed in HIV-DSP. Male HIV seropositive patients (n = 57) experiencing varying degrees of HIV neuropathy underwent single-shell diffusion tensor imaging with 51 sampling directions. The scans were pooled using tractography and connectometry to create a quantitative map of white matter tract integrity, measured in generalized fractional anisotropy (GFA). The relationship between GFA and neuropathy severity was evaluated with linear regression. Correction for multiple comparisons was done using false discovery rate (FDR), a statistical method commonly used in genomics and imaging to minimize false positives when thousands of individual comparisons are made. Neuropathy severity was associated with decreased GFA along thalamocortical radiations leading along the lateral thalamus to sensorimotor cortex, with r = -0.405 (p < 0.001; FDR), as well as with the superior bilateral cingulum (r = -0.346 (p < 0.05; FDR)). Among a population of HIV neuropathy patients, greater neuropathy severity was correlated with lower white matter integrity running from midbrain to somatosensory cortex. This suggests ascending deafferentation extending from damaged peripheral nerves further downstream than seen previously, into the axons of third-order neurons. There is also evidence of cingulum degeneration, implying some more complex mechanism beyond the ascending atrophy observed here.

Distal neuropathic pain in HIV is associated with functional connectivity patterns in default mode and salience networks.

HIV-associated distal neuropathic pain (DNP) is one of the most prevalent, disabling, and treatment-resistant complications of HIV, but its biological underpinnings are incompletely understood. While data specific to mechanisms underlying HIV DNP are scarce, functional neuroimaging of chronic pain more broadly implicates the role of altered resting-state functional connectivity within and between salience network (SN) and default mode network (DMN) regions. However, it remains unclear the extent to which HIV DNP is associated with similar alterations in connectivity. The current study aimed to bridge this gap in the literature through examination of resting-state functional connectivity patterns within SN and DMN regions among people with HIV (PWH) with and without DNP. Resting state functional magnetic resonance imaging (rs-fMRI) scans were completed among 62 PWH with HIV-associated peripheral neuropathy, of whom 27 reported current DNP and 35 did not. Using subgrouping group iterative multiple estimation, we compared connectivity patterns in those with current DNP to those without. We observed weaker connectivity between the medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC) and stronger connectivity between the anterior cingulate cortex (ACC) and thalamus among those reporting DNP. Overall, these findings implicate altered within DMN (i.e., MPFC-PCC) and within SN (i.e., ACC-thalamus) connectivity as potential manifestations of adaptation to pain from neuropathy and/or mechanisms underlying the development/maintenance of DNP. Findings are discussed in the context of differential brain response to pain (i.e., mind wandering, pain aversion, pain facilitation/inhibition) and therapeutic implications.

A prospective investigation of youth alcohol experimentation and reward responsivity in the ABCD study.

Rationale: Greater risk-taking behaviors, such as alcohol experimentation, are associated with different patterns of brain functioning in regions implicated in reward (nucleus accumbens, NA) and cognitive control (inferior frontal gyrus, IFG). These neural features have been observed in youth with greater risk-taking tendencies prior to substance use initiation, suggesting NA-IFG disruption may serve as an early marker for subsequent substance use disorders. Prospective studies are needed to determine if NA-IFG neural disruption predicts future substance use in school-age children, including those with minimal use of alcohol (e.g., sipping). The present large-sample prospective study sought to use machine learning to: (1) examine alcohol sipping at ages 9, 10 as a potential behavioral indicator of concurrent underlying altered neural responsivity to reward, and (2) determine if alcohol sipping and NA-IFG activation at ages 9, 10 can be used to predict which youth reported increased alcohol use at ages 11, 12. Additionally, low-level alcohol use and brain functioning at ages 9, 10 were examined as predictors of substance use and brain functioning at ages 11, 12. Design and methods: This project used data from the baseline (Time 1) and two-year follow-up (Time 2) assessments of the Adolescent Brain Cognitive Development (ABCD) Study (Release 3.0). Support Vector Machine (SVM) learning determined if: (1) NA-IFG neural activity could correctly identify youth who reported alcohol sipping at Time 1 (n = 7409, mean age = 119.34 months, SD = 7.53; 50.27% female), and (2) NA-IFG and alcohol sipping frequency at Time 1 could correctly identify youth who reported drinking alcohol at Time 2 (n = 4000, mean age = 143.25 months, SD = 7.63; 47.53% female). Linear regression was also used to examine the relationship between alcohol sipping and NA-IFG activity at Time 1 and substance use and NA-IFG activity at Time 2. Data were also examined to characterize the environmental context in which youth first tried sips of alcohol (e.g., with or without parental permission, as part of a religious experience). Results: Approximately 24% of the sample reported having tried sips of alcohol by ages 9, 10. On average, youth reported trying sips of alcohol 4.87 times (SD = 23.19) with age of first sip occurring at 7.36 years old (SD = 1.91). The first SVM model classified youth according to alcohol sipping status at Time 1 no better than chance with an accuracy of 0.35 (balanced accuracy = 0.52, sensitivity = 0.24, specificity = 0.80). The second SVM model classified youth according to alcohol drinking status at Time 2 with an accuracy of 0.76 (balanced accuracy = 0.56, sensitivity = 0.21, specificity = 0.91). Linear regression demonstrated that frequency of alcohol sipping at Time 1 predicted frequency of alcohol use at Time 2 (p < 0.001, adjusted R 2 = 0.075). Alcohol sipping at Time 1 was not linearly associated with NA or IFG activity at Time 2 (all ps > 0.05), and NA activity at Time 1 and Time 2 were not related (all ps > 0.05). Activity in the three subsections of the IFG at Time 1 predicted activity in those same regions at Time 2 (all ps < 0.02). Conclusions and implications: Early sips of alcohol appear to predict alcohol use in early adolescence. Findings do not provide strong evidence for minimal early alcohol use (sipping) as a behavioral marker of underlying alterations in NA-IFG neural responsivity to reward. Improving our understanding of the neural and behavioral factors that indicate a greater propensity for future substance use is crucial for identifying at-risk youth and potential targets for preventative efforts.

Non-invasive cervical vagus nerve stimulation effects on reaction time and valence image anticipation response.

BACKGROUND: Norepinephrine (NE) driven noninvasive vagus nerve stimulation (nVNS), which improves attention and reduces reaction time, augments learning. Equally important, endogenous NE mediated arousal is highly dependent on the valence (positive or negative) of the exogenous stimulus. But to date, no study has measured valence specific effects of nVNS on both functional magnetic resonance imaging (fMRI) anticipation task response and reaction time in healthy individuals. Therefore, the aim of this pilot study was to assess whether nVNS vs sham modulates valence cortical anticipation task response and reaction time in a normative sample. METHODS: Participants received right sided transcutaneous cervical nVNS (N = 12) or sham (N = 12) stimulation during a 3T fMRI scan. Subjects first performed a continuous performance task (CPT) and then a cued anticipation task to images of positively and negatively valenced events during fMRI. Reaction times to cues and Blood oxygen level dependent (BOLD) response were examined over phase to identify effects of nVNS/sham over time. RESULTS: nVNS reduced reaction time for all valenced image anticipation trials. With the fMRI anticipation task, we observed a valence-specific effect; nVNS increased responsivity to images with negative valence and decreased responsivity to images with positive valence, whereas sham showed an inverse valence response. CONCLUSIONS: nVNS was linked to reduced reaction time during the anticipation task. In tandem, nVNS consistently enhanced responsivity to negatively valenced images and diminished responsivity to positively valenced images, suggesting specific nVNS driven endogenous neurotransmitter signaling may contribute.

Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling.

Trauma and posttraumatic stress are highly comorbid with chronic pain and are often antecedents to developing chronic pain conditions. Pain and trauma are associated with greater utilization of medical services, greater use of psychiatric medication, and increased total cost of treatment. Despite the high overlap in the clinic, the neural mechanisms of pain and trauma are often studied separately. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) scans were completed among a diagnostically heterogeneous sample of veterans with a range of back pain and trauma symptoms. Using Group Iterative Multiple Model Estimation (GIMME), an effective functional connectivity analysis, we explored an unsupervised model deriving subgroups based on path similarity in a priori defined regions of interest (ROIs) from brain regions implicated in the experience of pain and trauma. Three subgroups were identified by patterns in functional connection and differed significantly on several psychological measures despite similar demographic and diagnostic characteristics. The first subgroup was highly connected overall, was characterized by functional connectivity from the nucleus accumbens (NAc), the anterior cingulate cortex (ACC), and the posterior cingulate cortex (PCC) to the insula and scored low on pain and trauma symptoms. The second subgroup did not significantly differ from the first subgroup on pain and trauma measures but was characterized by functional connectivity from the ACC and NAc to the thalamus and from ACC to PCC. The third subgroup was characterized by functional connectivity from the thalamus and PCC to NAc and scored high on pain and trauma symptoms. Our results suggest that, despite demographic and diagnostic similarities, there may be neurobiologically dissociable biotypes with different mechanisms for managing pain and trauma. These findings may have implications for the determination of appropriate biotype-specific interventions that target these neurological systems.

Toward Composite Pain Biomarkers of Neuropathic Pain-Focus on Peripheral Neuropathic Pain.

Chronic pain affects ~10-20% of the U.S. population with an estimated annual cost of $600 billion, the most significant economic cost of any disease to-date. Neuropathic pain is a type of chronic pain that is particularly difficult to manage and leads to significant disability and poor quality of life. Pain biomarkers offer the possibility to develop objective pain-related indicators that may help diagnose, treat, and improve the understanding of neuropathic pain pathophysiology. We review neuropathic pain mechanisms related to opiates, inflammation, and endocannabinoids with the objective of identifying composite biomarkers of neuropathic pain. In the literature, pain biomarkers typically are divided into physiological non-imaging pain biomarkers and brain imaging pain biomarkers. We review both types of biomarker types with the goal of identifying composite pain biomarkers that may improve recognition and treatment of neuropathic pain.

Effects of Noninvasive Cervical Vagal Nerve Stimulation on Cognitive Performance But Not Brain Activation in Healthy Adults.

OBJECTIVES: While preliminary evidence suggests that noninvasive vagal nerve stimulation (nVNS) may enhance cognition, to our knowledge, no study has directly assessed the effects of nVNS on brain function and cognitive performance in healthy individuals. The aim of this study was therefore to assess whether nVNS enhances complex visuospatial problem solving in a normative sample. Functional magnetic resonance imaging (fMRI) was used to examine underlying neural substrates. MATERIAL AND METHODS: Participants received transcutaneous cervical nVNS (N = 15) or sham (N = 15) stimulation during a 3 T fMRI scan. Stimulation lasted for 2 min at 24 V for nVNS and at 4.5 V for sham. Subjects completed a matrix reasoning (MR) task in the scanner and a forced-choice recognition task outside the scanner. An analysis of variance (ANOVA) was used to assess group differences in cognitive performance. And linear mixed effects (LMEs) regression analysis was used to assess main and interaction effects of experimental groups, level of MR task difficulty, and recall accuracy on changes in blood oxygen level-dependent (BOLD) signal. RESULTS: Subjects who received nVNS showed higher accuracy for both easy (p = 0.017) and hard (p = 0.013) items of the MR task, slower reaction times for hard items (p = 0.014), and fewer false negative errors during the forced-choice recognition task (p = 0.047). MR task difficulty related to increased activation in frontoparietal regions (p < 0.001). No difference between nVNS and sham stimulation was found on BOLD response during performance of the MR task. CONCLUSIONS: We hypothesize that nVNS increased attention compared to sham, and that this effect led to enhanced executive functions, and consequently to better performance on visuospatial reasoning and recognition tasks. Results provide initial support that nVNS may be a low-risk, low-cost treatment for cognitive disorders.

Deriving psychiatric symptom-based biomarkers from multivariate relationships between psychophysiological and biochemical measures.

Identification of biomarkers for psychiatric disorders remains very challenging due to substantial symptom heterogeneity and diagnostic comorbidity, limiting the ability to map symptoms to underlying neurobiology. Dimensional symptom clusters, such as anhedonia, hyperarousal, etc., are complex and arise due to interactions of a multitude of complex biological relationships. The primary aim of the current investigation was to use multi-set canonical correlation analysis (mCCA) to derive biomarkers (biochemical, physiological) linked to dimensional symptoms across the anxiety and depressive spectrum. Active-duty service members (N = 2,592) completed standardized depression, anxiety and posttraumatic stress questionnaires and several psychophysiological and biochemical assays. Using this approach, we identified two phenotype associations between distinct physiological and biological phenotypes. One was characterized by symptoms of dysphoric arousal (anhedonia, anxiety, hypervigilance) which was associated with low blood pressure and startle reactivity. This finding is in line with previous studies suggesting blunted physiological reactivity is associated with subpopulations endorsing anxiety with comorbid depressive features. A second phenotype of anxious fatigue (high anxiety and reexperiencing/avoidance symptoms coupled with fatigue) was associated with elevated blood levels of norepinephrine and the inflammatory marker C-reactive protein in conjunction with high blood pressure. This second phenotype may describe populations in which inflammation and high sympathetic outflow might contribute to anxious fatigue. Overall, these findings support the growing consensus that distinct neuropsychiatric symptom patterns are associated with differential physiological and blood-based biological profiles and highlight the potential of mCCA to reveal important psychiatric symptom biomarkers from several psychophysiological and biochemical measures.

Craving of prescription opioids among veterans with chronic pain.

ABSTRACT: The United States faces a crisis because of the high prevalence of chronic pain, concurrent opioid use disorder, and overdose deaths. Prescription opioids remain a primary driver of opioid-related deaths. Craving is a core symptom of addiction, yet the degree to which craving plays a role in prescription opioid use among patients with chronic pain is unknown. Understanding the degree to which craving should be considered in patients with chronic pain is critical for developing effective interventions for supporting patients through opioid tapering. The current work combines data collected from (1) 2152 veterans screened for eligibility at a pain specialty care clinic at the San Francisco VA Health Care System and (2) medical records obtained from the VA Corporate Data Warehouse. We found that prescription opioid craving among veterans with chronic pain was low, with 66.4% of the sample reporting no craving and 33.6% reporting craving. We also found that craving had a small association with morphine equivalent daily dose and pain severity but was more strongly associated with depression. Craving of prescription opioids among veterans with chronic pain is complex. Findings are discussed in relation to chronic pain symptoms, psychiatric comorbidities, and demographics.