Polygenic evidence and overlapped brain functional connectivities for the association between chronic pain and sleep disturbance

Pathology of pain and its implications for therapeutic interventions

Pain is estimated to affect more than 20% of the global population, imposing incalculable health and economic burdens. Effective pain management is crucial for individuals suffering from pain. However, the current methods for pain assessment and treatment fall short of clinical needs. Benefiting from advances in neuroscience and biotechnology, the neuronal circuits and molecular mechanisms critically involved in pain modulation have been elucidated. These research achievements have incited progress in identifying new diagnostic and therapeutic targets. In this review, we first introduce fundamental knowledge about pain, setting the stage for the subsequent contents. The review next delves into the molecular mechanisms underlying pain disorders, including gene mutation, epigenetic modification, posttranslational modification, inflammasome, signaling pathways and microbiota. To better present a comprehensive view of pain research, two prominent issues, sexual dimorphism and pain comorbidities, are discussed in detail based on current findings. The status quo of pain evaluation and manipulation is summarized. A series of improved and innovative pain management strategies, such as gene therapy, monoclonal antibody, brain-computer interface and microbial intervention, are making strides towards clinical application. We highlight existing limitations and future directions for enhancing the quality of preclinical and clinical research. Efforts to decipher the complexities of pain pathology will be instrumental in translating scientific discoveries into clinical practice, thereby improving pain management from bench to bedside.

Sleep and Pain: A Role for the Anterior Cingulate Cortex, Nucleus Accumbens, and Dopamine in the Increased Pain Sensitivity Following Sleep Restriction

Persistent pain conditions and sleep disorders are public health problems worldwide. It is widely accepted that sleep disruption increases pain sensitivity; however, the underlying mechanisms are poorly understood. In this study, we used a protocol of 6 hours a day of total sleep deprivation for 3 days in rats to advance the understanding of these mechanisms. We focused on gender differences and the dopaminergic mesocorticolimbic system. The findings demonstrated that sleep restriction (SR) increased pain sensitivity in a similar way in males and females, without inducing a significant stress response. This pronociceptive effect depends on a nucleus accumbens (NAc) neuronal ensemble recruited during SR and on the integrity of the anterior cingulate cortex (ACC). Data on indirect dopaminergic parameters, dopamine transporter glycosylation, and dopamine and cyclic adenosine monophosphate (AMP)-regulated phosphoprotein-32 phosphorylation, as well as dopamine, serotonin, and norepinephrine levels, suggest that dopaminergic function decreases in the NAc and ACC after SR. Complementarily, pharmacological activation of dopamine D2, but not D1 receptors either in the ACC or in the NAc prevents SR from increasing pain sensitivity. The ACC and NAc are the main targets of dopaminergic mesocorticolimbic projections with a key role in pain modulation. This study showed their integrative role in the pronociceptive effect of SR, pointing to dopamine D2 receptors as a potential target for pain management in patients with sleep disorders. These findings narrow the focus of future studies on the mechanisms by which sleep impairment increases pain sensitivity. PERSPECTIVE: This study demonstrates that the pronociceptive effect of SR affects similarly males and females and depends on a NAc neuronal ensemble recruited during SR and on the integrity of the ACC. Findings on dopaminergic function support dopamine D2 receptors as targets for pain management in sleep disorders patients.

Artificial intelligence in psychiatry research, diagnosis, and therapy

Psychiatric disorders are now responsible for the largest proportion of the global burden of disease, and even more challenges have been seen during the COVID-19 pandemic. Artificial intelligence (AI) is commonly used to facilitate the early detection of disease, understand disease progression, and discover new treatments in the fields of both physical and mental health. The present review provides a broad overview of AI methodology and its applications in data acquisition and processing, feature extraction and characterization, psychiatric disorder classification, potential biomarker detection, real-time monitoring, and interventions in psychiatric disorders. We also comprehensively summarize AI applications with regard to the early warning, diagnosis, prognosis, and treatment of specific psychiatric disorders, including depression, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, addiction, sleep disorders, and Alzheimer's disease. The advantages and disadvantages of AI in psychiatry are clarified. We foresee a new wave of research opportunities to facilitate and improve AI technology and its long-term implications in psychiatry during and after the COVID-19 era.

A common neuronal ensemble in nucleus accumbens regulates pain-like behaviour and sleep

A comorbidity of chronic pain is sleep disturbance. Here, we identify a dual-functional ensemble that regulates both pain-like behaviour induced by chronic constrictive injury or complete Freund's adjuvant, and sleep wakefulness, in the nucleus accumbens (NAc) in mice. Specifically, a select population of NAc neurons exhibits increased activity either upon nociceptive stimulation or during wakefulness. Experimental activation of the ensemble neurons exacerbates pain-like (nociceptive) responses and reduces NREM sleep, while inactivation of these neurons produces the opposite effects. Furthermore, NAc ensemble primarily consists of D1 neurons and projects divergently to the ventral tegmental area (VTA) and preoptic area (POA). Silencing an ensemble innervating VTA neurons selectively increases nociceptive responses without affecting sleep, whereas inhibiting ensemble-innervating POA neurons decreases NREM sleep without affecting nociception. These results suggest a common NAc ensemble that encodes chronic pain and controls sleep, and achieves the modality specificity through its divergent downstream circuit targets.

A pathway model of chronic pain and frailty in older Chinese cancer patients: The mediating effect of sleep

This study aimed to explore the association between chronic pain, sleep quality, and frailty, and whether sleep quality will mediate the relationship between chronic pain and frailty. A cross-sectional study was conducted between June 2020 and July 2021 among 308 patients in Nantong city. The relationship between chronic pain and frailty was tested using linear regression. The bootstrap method was used to examine mediating effect of sleep quality. Chronic pain was significantly correlated with frailty (r=0.271, P<.001). Sleep quality played a partially mediating role between chronic pain and frailty (β=0.160, R²=32%, P<.001). Interventions to scientifically manage chronic pain and improve sleep quality may be effective in reducing the incidence of frailty in elderly cancer patients.

Back Pain without Disease or Substantial Injury in Children and Adolescents: A Twin Family Study Investigating Genetic Influence and Associations

This twin family study first aimed to investigate the evidence for genetic factors predicting the risk of lifetime prevalence of non-specific low back pain of at least three months duration (LBP (life)) and one-month current prevalence of thoracolumbar back pain (TLBP (current)) using a study of children, adolescents, and their first-degree relatives. Secondly, the study aimed to identify associations between pain in the back with pain in other regions and also with other conditions of interest. Randomly selected families (n = 2479) with child or adolescent twin pairs and their biological parents and first siblings were approached by Twins Research Australia. There were 651 complete twin pairs aged 6-20 years (response 26%). Casewise concordance, correlation, and odds ratios were compared for monozygous (MZ) and dizygous (DZ) pairs to enable inference about the potential existence of genetic vulnerability. Multivariable random effects logistic regression was used to estimate associations between LBP (life) or TLBP (current) as an outcome with the potentially relevant condition as predictors. The MZ pairs were more similar than the DZ pairs for each of the back pain conditions (all p values < 0.02). Both back pain conditions were associated with pain in multiple sites and with primary pain and other conditions using the combined twin and sibling sample (n = 1382). Data were consistent with the existence of genetic influences on the pain measures under the equal environments assumption of the classic twin model and associations with both categories of back pain were consistent with primary pain conditions and syndromes of childhood and adolescence which has research and clinical implications.

Causal association of sleep disturbances and low back pain: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have shown that low back pain (LBP) often coexists with sleep disturbances, however, the causal relationship remains unclear. In the present study, the causal relationship between sleep disturbances and LBP was investigated and the importance of sleep improvement in the comprehensive management of LBP was emphasized.

METHODS

Genetic variants were extracted as instrumental variables (IVs) from the genome-wide association study (GWAS) of insomnia, sleep duration, short sleep duration, long sleep duration, and daytime sleepiness. Information regarding genetic variants in LBP was selected from a GWAS dataset and included 13,178 cases and 164,682 controls. MR-Egger, weighted median, inverse-variance weighted (IVW), penalized weighted median, and maximum likelihood (ML) were applied to assess the causal effects. Cochran's Q test and MR-Egger intercept were performed to estimate the heterogeneity and horizontal pleiotropy, respectively. Outliers were identified and eliminated based on MR-PRESSO analysis to reduce the effect of horizontal pleiotropy on the results. Removing each genetic variant using the leave-one-out analysis can help evaluate the stability of results. Finally, the reverse causal inference involving five sleep traits was implemented.

RESULTS

A causal relationship was observed between insomnia-LBP (OR = 1.954, 95% CI: 1.119-3.411), LBP-daytime sleepiness (OR = 1.011, 95% CI: 1.004-1.017), and LBP-insomnia (OR = 1.015, 95% CI: 1.004-1.026), however, the results of bidirectional MR analysis between other sleep traits and LBP were negative. The results of most heterogeneity tests were stable and specific evidence was not found to support the disturbance of horizontal multiplicity. Only one outlier was identified based on MR-PRESSO analysis.

CONCLUSION

The main results of our research showed a potential bidirectional causal association of genetically predicted insomnia with LBP. Sleep improvement may be important in comprehensive management of LBP.

Identify novel, shared and disorder-specific genetic architecture of major depressive disorder, insomnia and chronic pain

Major depressive disorder (MDD), insomnia (INS) and chronic pain (CP) often have high comorbidity and show high genetic correlation. Here we aimed to better characterize their novel, shared and disorder-specific genetic architecture. Based on genome-wide association study (GWAS) summary data, we applied the conditional false discovery rate (condFDR) and conjunctional FDR (conjFDR) approach to investigate the novel and overlapped genetic loci for MDD, INS and CP. In addition, putative disorder-specific SNP associations were analyzed by conditioning the other two traits. The functions of the identified genomic loci were explored by performing gene set enrichment analysis (GSEA) for the loci mapped genes. We identified 22, 43 and 91 novel risk loci for MDD, INS and CP. GSEA for the loci mapped genes highlighted olfactory signaling pathway for MDD novel loci, breast cancer related gene set for both INS and CP novel loci, and nervous system related development, structure and activity for CP. Furthermore, we identified three loci jointly associated with the three disorders, including 13q14.3 locus with nearby gene OLFM4, 14q21.1 locus with nearby gene LRFN5 and 5q21.2 locus located in intergenic region. In addition, we identified one specific loci for MDD, 7 for INS and 11 for CP respectively by conditioning the other two traits, which were mapped to 68 genes for MDD, 85 for INS and 100 for CP. The MDD specific genes are enriched in immune system related pathways. This study increases understanding of the genetic architectures underlying MDD, INS and CP. The shared underlying genetic risk may help to explain the high comorbidity rates of the disorders.

Brain-specific genes contribute to chronic but not to acute back pain

Introduction

Back pain is the leading cause of disability worldwide. Although most back pain cases are acute, 20% of acute pain patients experience chronic back pain symptoms. It is unclear whether acute pain and chronic pain have similar or distinct underlying genetic mechanisms.

Objectives

To characterize the molecular and cellular pathways contributing to acute and chronic pain states.

Methods

Cross-sectional observational genome-wide association study.

Results

A total of 375,158 individuals from the UK Biobank cohort were included in the discovery of genome-wide association study. Of those, 70,633 (19%) and 32,209 (9%) individuals met the definition of chronic and acute back pain, respectively. A total of 355 single nucleotide polymorphism grouped into 13 loci reached the genome-wide significance threshold (5x10^-8) for chronic back pain, but none for acute. Of these, 7 loci were replicated in the Nord-Trøndelag Health Study (HUNT) cohort (19,760 chronic low back pain cases and 28,674 pain-free controls). Single nucleotide polymorphism heritability was 4.6% (P=1.4x10^-78) for chronic back pain and 0.81% (P=1.4x10-8) for acute back pain. Similar differences in heritability estimates between acute and chronic back pain were found in the HUNT cohort: 3.4% (P=0.0011) and 0.6% (P=0.851), respectively. Pathway analyses, tissue-specific heritability enrichment analyses, and epigenetic characterization suggest a substantial genetic contribution to chronic but not acute back pain from the loci predominantly expressed in the central nervous system.

Conclusion

Chronic back pain is substantially more heritable than acute back pain. This heritability is mostly attributed to genes expressed in the brain.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

Home-Based EEG Neurofeedback Intervention for the Management of Chronic Pain

Background

Chronic pain and associated symptoms often cause significant disability and reduced quality of life (QoL). Neurofeedback (NFB) as part of a Brain Computer Interface can help some patients manage chronic pain by normalising maladaptive brain activity measured with electroencephalography (EEG).

Objectives

This study was designed to assess the efficacy and safety of a novel home-based NFB device for managing chronic pain by modifying specific EEG activity.

Methods

A prospective, single-arm, proof-of-concept study was conducted between June 2020 and March 2021 among adults with chronic pain (registered with ClinicalTrials.gov NCT04418362). Axon EEG NFB systems for home use were provided to each, and 32–48 NFB training sessions were completed by the participants over 8-weeks. The primary outcome was self-reported pain. Assessment of central sensitisation, sleep quality, affective symptoms, change in QoL, adverse events during use and EEG correlations with symptoms were secondary outcomes.

Results

Sixteen participants were enrolled. Eleven reported pain relief following NFB training, eight reporting clinically significant improvements. Central sensitisation symptoms improved by a third (p &lt; 0.0001), sleep quality by almost 50% (p &lt; 0.001), anxiety reduced by 40% (p = 0.015), and QoL improved at final follow-up for 13 participants. The majority (69%) of participants who upregulated relative alpha reported improved pain, and those who downregulated relative hi-beta reported improved pain, reduced anxiety and depression scores. There were no adverse events during the trial.

Conclusions

Home-based NFB training is well-tolerated and may provide relief for sufferers of chronic pain and its associated symptoms.

Summary

Axon, a home-based NFB training device, can positively influence pain and associated symptoms in a proportion of people with chronic pain.

Abnormal Visual Evoked Responses to Emotional Cues Correspond to Diagnosis and Disease Severity in Fibromyalgia

Background

Chronic pain disorders are often associated with cognitive-emotional dysregulation. However, the relations between such dysregulation, underlying brain processes, and clinical symptom constellations, remain unclear. Here, we aimed to characterize the abnormalities in cognitive-emotional processing involved in fibromyalgia syndrome (FMS) and their relation to disease severity.

Methods

Fifty-eight participants, 39 FMS patients (35F), and 19 healthy control subjects (16F) performed an EEG-based paradigm assessing attention allocation by extracting steady-state visually evoked potentials (ssVEP) in response to affective distractors presented during a cognitive task. Patients were also evaluated for pain severity, sleep quality, depression, and anxiety.

Results

EEG ssVEP measurement indicated that, compared to healthy controls, FMS patients displayed impaired affective discrimination, and sustained attention to negative distractors. Moreover, patients displayed decreased task-related fronto-occipital EEG connectivity. Lack of adaptive attentional discrimination, measured via EEG, was predictive of pain severity, while impairments in fronto-occipital connectivity were predictive of impaired sleep.

Conclusions

FMS patients display maladaptive affective attention modulation, which predicts disease symptoms. These findings support the centrality of cognitive-emotional dysregulation in the pathophysiology of chronic pain.

The Impact of Quarantine on Pain Sensation among the General Population in China during the COVID-19 Pandemic

During the pandemic era, quarantines might potentially have negative effects and disproportionately exacerbate health condition problems. We conducted this cross-sectional, national study to ascertain the prevalence of constant pain symptoms and how quarantines impacted the pain symptoms and identify the factors associated with constant pain to further guide reducing the prevalence of chronic pain for vulnerable people under the pandemic. The sociodemographic data, quarantine conditions, mental health situations and pain symptoms of the general population were collected. After adjusting for potential confounders, long-term quarantine (≥15 days) exposures were associated with an increased risk of constant pain complaints compared to those not under a quarantine (Odds Ratio (OR): 1.26; 95% Confidence Interval (CI): 1.03, 1.54; p = 0.026). Risk factors including unemployment (OR: 1.55), chronic disease history (OR: 2.38) and infection with COVID-19 (OR: 2.15), and any of mental health symptoms including depression, anxiety, insomnia and PTSD (OR: 5.44) were identified by a multivariable logistic regression. Additionally, mediation analysis revealed that the effects of the quarantine duration on pain symptoms were mediated by mental health symptoms (indirect effects: 0.075, p < 0.001). These results advocated that long-term quarantine measures were associated with an increased risk of experiencing pain, especially for vulnerable groups with COVID-19 infection and with mental health symptoms. The findings also suggest that reducing mental distress during the pandemic might contribute to reducing the burden of pain symptoms and prioritizing interventions for those experiencing a long-term quarantine.

Genetic basis to structural grey matter associations with chronic pain

Structural neuroimaging studies of individuals with chronic pain conditions have often observed decreased regional grey matter at a phenotypic level. However, it is not known if this association can be attributed to genetic factors. Here we employed a novel integrative data-driven and hypothesis-testing approach to determine whether there is a genetic basis to grey matter morphology differences in chronic pain. Using publicly available genome-wide association study summary statistics for regional chronic pain conditions (n = 196 963) and structural neuroimaging measures (n = 19 629-34 000), we applied bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine the genetic correlations (rG) and genetic causal proportion (GCP) between these complex traits, respectively. Five a priori brain regions (i.e. prefrontal cortex, cingulate cortex, insula, thalamus and superior temporal gyrus) were selected based on systematic reviews of grey matter morphology studies in chronic pain. Across this evidence-based selection of five brain regions, 10 significant negative genetic correlations (out of 369) were found (false discovery rate < 5%), suggesting a shared genetic basis to both reduced regional grey matter morphology and the presence of chronic pain. Specifically, negative genetic correlations were observed between reduced insula grey matter morphology and chronic pain in the abdomen (mean insula cortical thickness), hips (left insula volume) and neck/shoulders (left and right insula volume). Similarly, a shared genetic basis was found for reduced posterior cingulate cortex volume in chronic pain of the hip (left and right posterior cingulate), neck/shoulder (left posterior cingulate) and chronic pain at any site (left posterior cingulate); and for reduced pars triangularis volume in chronic neck/shoulder (left pars triangularis) and widespread pain (right pars triangularis). Across these negative genetic correlations, a significant genetic causal proportion was only found between mean insula thickness and chronic abdominal pain [rG (standard error, SE) = -0.25 (0.08), P = 1.06 × 10-3; GCP (SE) = -0.69 (0.20), P = 4.96 × 10-4]. This finding suggests that the genes underlying reduced cortical thickness of the insula causally contribute to an increased risk of chronic abdominal pain. Altogether, these results provide independent corroborating evidence for observational reports of decreased grey matter of particular brain regions in chronic pain. Further, we show for the first time that this association is mediated (in part) by genetic factors. These novel findings warrant further investigation into the neurogenetic pathways that underlie the development and prolongation of chronic pain conditions.

The Human Connectome Project: A retrospective

The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.

Comorbid Chronic Pain and Depression: Shared Risk Factors and Differential Antidepressant Effectiveness

The bidirectional relationship between depression and chronic pain is well-recognized, but their clinical management remains challenging. Here we characterize the shared risk factors and outcomes for their comorbidity in the Australian Genetics of Depression cohort study (N = 13,839). Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health. Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for 10 different antidepressants. Chronic pain was associated with an increased risk of depression (OR = 1.86 [1.37-2.54]), recent suicide attempt (OR = 1.88 [1.14-3.09]), higher use of tobacco (OR = 1.05 [1.02-1.09]) and misuse of painkillers (e.g., opioids; OR = 1.31 [1.06-1.62]). Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR = 0.75 [0.68-0.83]), escitalopram (OR = 0.75 [0.67-0.85]) and venlafaxine (OR = 0.78 [0.68-0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR = 0.45 [0.30-0.67]), escitalopram (OR = 0.45 [0.27-0.74]) and citalopram (OR = 0.32 [0.15-0.67]) specifically for chronic pain (among other indications) reported lower benefits compared to other participants taking these same medications but not for chronic pain. These findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further examination is warranted in targeted interventional clinical trials, which also include neuroimaging genetics and pharmacogenomics protocols. This work will advance the delineation of disease risk indicators and novel aetiological pathways for therapeutic intervention in comorbid pain and depression as well as other psychiatric comorbidities.