Learning from addiction: Craving of prescription opioids in chronic pain sufferers

Repetitive transcranial magnetic stimulation ameliorates chronic pain behavior and modulates the brain transcriptome in a mouse model of chronic constriction injury

BACKGROUND AND AIM

Neuropathic pain (NP), caused by nerve injury or dysfunction, poses a significant clinical challenge due to its limited response to conventional pharmacological treatments. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising non-invasive neuromodulatory approach for NP management. This study aimed to evaluate the therapeutic efficacy of rTMS in alleviating NP induced by chronic constriction injury (CCI) in a mouse model and to investigate the underlying molecular mechanisms through transcriptomic profiling.

PROCEDURES

Adult male mice underwent CCI surgery to induce NP and were randomly assigned to receive either rTMS (5 Hz or 10 Hz) or sham stimulation. rTMS was applied once daily for 14 consecutive days, beginning on postoperative day 7. Behavioral assessments-including paw withdrawal latency (PWL) and paw withdrawal threshold (PWT)-were conducted to evaluate thermal hyperalgesia and mechanical allodynia, respectively. Anxiety-like behaviors were assessed using the open field test (OFT) and elevated plus maze (EPM). At the end of the treatment period, brain tissues were harvested for RNA sequencing and differentially expressed genes (DEGs) were identified and analyzed.

RESULTS AND CONCLUSION

rTMS at both 5 Hz and 10 Hz significantly improved PWL and PWT in CCI mice and reduced anxiety-like behaviors. Transcriptomic analysis revealed that CCI induced dysregulation of 66 genes, while rTMS partially normalized gene expression patterns. Functional enrichment analysis indicated significant involvement of pathways related to inflammatory responses, transporter activity, and ion channel regulation. These findings support the potential of rTMS as a multifaceted, non-invasive therapeutic strategy for neuropathic pain, with molecular mechanisms likely involving modulation of neuroinflammatory and neuroexcitatory pathways.

Comparing Pain Outcomes and Treatment Adherence Between In-Person and Virtual Interdisciplinary Pain Rehabilitation Programs at the San Francisco VA Health Care System

OBJECTIVE

This study compared clinical pain outcomes between patients in a pain treatment program that was conducted in-person, compared with a virtual program.

METHODS

In-person (N=127) and virtual (N=101) pain treatment programs were compared based on patient-reported, practitioner-collected, and medical record data. The patients were measured at baseline and post-treatment (week 12 for In-Person and week 8 for Virtual patients). We employed the last observation carried forward (LOCF) to handle missing data.

RESULTS

Both the In-Person and Virtual groups were similar in regard to all baseline outcomes, except the In-person group having significantly more co-morbidities at baseline, with particularly more cases of mental, behavioral, or neurodevelopmental diseases. Both groups demonstrated significant improvements in the pain-related measurements of pain interference and pain catastrophizing thoughts, but neither group displayed a change in average pain across treatment. Further, both groups improved significantly on emotional well-being scores, but not on physical functioning scores. No significant differences existed between groups on outcomes, except for pain catastrophizing, which was higher in the Virtual group at both time points. The Virtual group had lower rates of dropouts compared with In-Person, while the In-Person group had a larger proportion reach a clinically meaningful change in pain-related outcomes, defined as a >30% improvement.

DISCUSSION

While some changes were unique to the In-Person program, overall, patients in the Virtual program achieved similar treatment outcomes, suggesting that it can successfully treat Veterans seeking pain management, with less need for in-person facilities for both patients and clinicians.

Alcohol consumption and opioid craving among chronic pain patients prescribed long-term opioid therapy

BACKGROUND

Concurrent use of alcohol with opioids is common among chronic pain patients, heightening the risk for disordered opioid use and overdose, yet the relationship between alcohol consumption and opioid craving among chronic pain patients remains largely unexplored. Here we examined the relationship between alcohol consumption and opioid craving among chronic pain patients on long-term opioid therapy.

METHODS

A cross-sectional study was conducted with 335 chronic pain patients on long-term opioid therapy. Participants completed the Timeline Followback to assess alcohol consumption, as well as measures of opioid craving, pain severity, and pain interference. Linear regression analyses examined the relationship between alcohol consumption and opioid craving, controlling for pain severity, pain interference, and opioid misuse severity.

RESULTS

Alcohol consumption (total number of drinks and amount consumed in one sitting) was positively associated with opioid craving (p < 0.001 and p = 0.005, respectively). Pain severity did not predict opioid craving. The relationship between alcohol consumption and opioid craving remained significant after controlling for pain severity, pain interference, and opioid misuse severity.

CONCLUSION

Alcohol consumption is linked with more severe opioid craving among chronic pain patients prescribed long-term opioid therapy. Patients receiving opioid analgesics should be carefully screened for co-use of alcohol.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders

Background

Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders (SUD).

Aims

This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling (CPM).

Methods

One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging (fMRI) scans at baseline. The Heroin Craving Questionnaire (HCQ) was used to assess craving levels at baseline and at the 8-month follow-up of abstinence. CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ (HCQfollow-up-HCQbaseline). Then, the predictive ability of identified networks was tested in a separate, heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.

Results

CPM could predict craving changes induced by long-term abstinence, as shown by a significant correlation between predicted and actual HCQfollow-up (r=0.417, p<0.001) and changes in HCQ (negative: r=0.334, p=0.002；positive: r=0.233, p=0.038). Identified craving-related prediction networks included the somato-motor network (SMN), salience network (SALN), default mode network (DMN), medial frontal network, visual network and auditory network. In addition, decreased connectivity of frontal-parietal network (FPN)-SMN, FPN-DMN and FPN-SALN and increased connectivity of subcortical network (SCN)-DMN, SCN-SALN and SCN-SMN were positively correlated with craving levels.

Conclusions

These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence, as well as the generalisation ability; the identified brain networks might be the focus of innovative therapies in the future.