Towards precision medicine for pain: diagnostic biomarkers and repurposed drugs

The synergistic anti-nociceptive effects of nefopam and gabapentinoids in inflammatory, osteoarthritis, and neuropathic pain mouse models

Pain is a common public health problem and remains as an unmet medical need. Currently available analgesics usually have limited efficacy or are accompanied by many adverse side effects. To achieve satisfactory pain relief by multimodal analgesia, new combinations of nefopam and gabapentinoids (pregabalin/gabapentin) were designed and assessed in inflammatory, osteoarthritis and neuropathic pain. Isobolographic analysis was performed to analyze the interactions between nefopam and gabapentinoids in carrageenan-induced inflammatory pain, mono-iodoacetate-induced osteoarthritis pain and paclitaxel-induced peripheral neuropathic pain in mice. The anti-inflammatory effect and motor performance of monotherapy or their combinations were evaluated in the carrageenan-induced inflammatory responses and rotarod test, respectively. Nefopam (1, 3, 5, 10, 30 mg/kg, p.o.), pregabalin (3, 6, 12, 24 mg/kg, p.o.) or gabapentin (25, 50, 75, 100 mg/kg, p.o.) dose-dependently reversed mechanical allodynia in three pain models. Isobolographic analysis indicated that the combinations of nefopam and gabapentinoids exerted synergistic anti-nociceptive effects in inflammatory, osteoarthritis, and neuropathic pain mouse models, as evidenced by the experimental ED50 (median effective dose) falling below the predicted additive line. Moreover, the combination of nefopam-pregabalin/gabapentin alleviated carrageenan-induced inflammation and edema, and also prevented gabapentinoids-related sedation or ataxia by lowering their effective doses. Collectively, the co-administration of nefopam and gabapentinoids showed synergistic analgesic effects and may result in improved therapeutic benefits for treating pain.

Establishing a research agenda for the study and assessment of opioid withdrawal

The opioid crisis is an international public health concern. Treatments for opioid use disorder centre largely on the management of opioid withdrawal, an aversive collection of signs and symptoms that contribute to opioid use disorder. Whereas in the past 50 years more than 90 medications have been developed for depression, only five medications have been developed for opioid use disorder during this period. We posit that underinvestment has occurred in part due to an underdeveloped understanding of opioid withdrawal syndrome. This Personal View summarises substantial gaps in our understanding of opioid withdrawal that are likely to continue to limit major advancements in its treatment. There is no firm consensus in the field as to how withdrawal should be precisely defined; 10-550 symptoms of withdrawal can be measured on 18 scales. The imprecise understanding of withdrawal is likely to result in overestimating or underestimating the severity of an individual's withdrawal syndrome or potential therapeutic effects of different candidate medications. The severity of the opioid crisis is not remitting, and an international research agenda for the study and assessment of opioid withdrawal is necessary to support transformational changes in withdrawal management and treatment of opioid use disorder. Nine actionable targets are delineated here: develop a consensus definition of opioid withdrawal; understand withdrawal symptomatology after exposure to different opioids (particularly fentanyl); understand precipitated opioid withdrawal; understand how co-exposure of other drugs (eg, xylazine and stimulants) influences withdrawal expression; examine individual variation in withdrawal phenotypes; precisely characterise the protracted withdrawal syndrome; identify biomarkers of opioid withdrawal severity; identify predictors of opioid withdrawal severity; and understand which symptoms are most closely associated with treatment attrition or relapse. The US Food and Drug Administration recently established a formal indication for opioid withdrawal that has invigorated interest in drug development for opioid withdrawal management. Action is now needed to support these interests and help industry identify new classes of medications so that real change can be achieved for people with opioid use disorder.

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.

Precision medicine for psychotic disorders: objective assessment, risk prediction, and pharmacogenomics

Psychosis occurs inside the brain, but may have external manifestations (peripheral molecular biomarkers, behaviors) that can be objectively and quantitatively measured. Blood biomarkers that track core psychotic manifestations such as hallucinations and delusions could provide a window into the biology of psychosis, as well as help with diagnosis and treatment. We endeavored to identify objective blood gene expression biomarkers for hallucinations and delusions, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We were successful in identifying biomarkers that were predictive of high hallucinations and of high delusions states, and of future psychiatric hospitalizations related to them, more so when personalized by gender and diagnosis. Top biomarkers for hallucinations that survived discovery, prioritization, validation and testing include PPP3CB, DLG1, ENPP2, ZEB2, and RTN4. Top biomarkers for delusions include AUTS2, MACROD2, NR4A2, PDE4D, PDP1, and RORA. The top biological pathways uncovered by our work are glutamatergic synapse for hallucinations, as well as Rap1 signaling for delusions. Some of the biomarkers are targets of existing drugs, of potential utility in pharmacogenomics approaches (matching patients to medications, monitoring response to treatment). The top biomarkers gene expression signatures through bioinformatic analyses suggested a prioritization of existing medications such as clozapine and risperidone, as well as of lithium, fluoxetine, valproate, and the nutraceuticals omega-3 fatty acids and magnesium. Finally, we provide an example of how a personalized laboratory report for doctors would look. Overall, our work provides advances for the improved diagnosis and treatment for schizophrenia and other psychotic disorders.

Pancreatic quantitative sensory testing to predict treatment response of endoscopic therapy or surgery for painful chronic pancreatitis with pancreatic duct obstruction: study protocol for an observational clinical trial

INTRODUCTION

Treatment for abdominal pain in patients with chronic pancreatitis (CP) remains challenging in the setting of central nervous system sensitisation, a phenomenon of remodelling and neuronal hyperexcitability resulting from persistent pain stimuli. This is suspected to render affected individuals less likely to respond to conventional therapies. Endotherapy or surgical decompression is offered to patients with pancreatic duct obstruction. However, the response to treatment is unpredictable. Pancreatic quantitative sensory testing (P-QST), an investigative technique of standardised stimulations to test the pain system in CP, has been used for phenotyping patients into three mutually exclusive groups: no central sensitisation, segmental sensitisation (pancreatic viscerotome) and widespread hyperalgesia suggestive of supraspinal central sensitisation. We will test the predictive capability of the pretreatment P-QST phenotype to predict the likelihood of pain improvement following invasive treatment for painful CP.

METHODS AND ANALYSIS

This observational clinical trial will enrol 150 patients from the University of Pittsburgh, Johns Hopkins and Indiana University. Participants will undergo pretreatment phenotyping with P-QST. Treatment will be pancreatic endotherapy or surgery for clearance of painful pancreatic duct obstruction.

PRIMARY OUTCOME

average pain score over the preceding 7 days measured by Numeric Rating Scale at 6 months postintervention. Secondary outcomes will include changes in opioid use during follow-up, and patient-reported outcomes in pain and quality of life at 3, 6 and 12 months after the intervention. Exploratory outcomes will include creation of a model for individualised prediction of response to invasive treatment.

ETHICS AND DISSEMINATION

The trial will evaluate the ability of P-QST to predict response to invasive treatment for painful CP and develop a predictive model for individualised prediction of treatment response for widespread use. This trial was approved by the University of Pittsburgh Institutional Review Board. Data and results will be reported and disseminated in conjunction with National Institutes of Health policies.

TRIAL REGISTRATION NUMBER

NCT04996628.

COMT Val158Met Affects the Analgesic Response to Acupuncture Among Cancer Survivors With Chronic Pain

Catechol-O-methyltransferase (COMT) is the major enzyme involved in the catabolism of dopamine, a neurotransmitter in the brain's reward system. The common COMT polymorphism Val158Met (rs4680 G>A) modulates pain response to opioids through a reward-motivated mechanism; however, its role in nonpharmacological pain medicine has not been clinically characterized. We genotyped 325 participants from a randomized controlled trial of cancer survivors with chronic musculoskeletal pain. We found that carrying methionine at position 158 (158Met) of COMT, encoded by the A allele, significantly increased the analgesic response to electroacupuncture (74% vs 50%; odds ratio [OR]: 2.79; 95% confidence interval [CI]: 1.31, 6.05; P < .01), but not to auricular acupuncture (68% vs 60%; OR: 1.43; 95% CI: .65, 3.12; P = .37) or usual care (24% vs 18%; OR: 1.46; 95% CI: .38, 7.24; P = .61) compared to Val/Val. These findings raise the possibility that COMT Val158Met might be an important predictor of analgesic response to electroacupuncture, providing novel insights into precision nonpharmacologic pain management tailored to individual genetic backgrounds. PERSPECTIVE: This work suggests the modulating effects of the polymorphism in COMT Val158Met on the response to acupuncture. Further research needs to validate these findings, increase the mechanistic understanding of acupuncture, and guide further development of acupuncture as a precision pain management strategy.

Circuits and Biomarkers of the Central Nervous System Relating to Astronaut Performance: Summary Report for a NASA-Sponsored Technical Interchange Meeting

Biomarkers, ranging from molecules to behavior, can be used to identify thresholds beyond which performance of mission tasks may be compromised and could potentially trigger the activation of countermeasures. Identification of homologous brain regions and/or neural circuits related to operational performance may allow for translational studies between species. Three discussion groups were directed to use operationally relevant performance tasks as a driver when identifying biomarkers and brain regions or circuits for selected constructs. Here we summarize small-group discussions in tables of circuits and biomarkers categorized by (a) sensorimotor, (b) behavioral medicine and (c) integrated approaches (e.g., physiological responses). In total, hundreds of biomarkers have been identified and are summarized herein by the respective group leads. We hope the meeting proceedings become a rich resource for NASA's Human Research Program (HRP) and the community of researchers.

Towards precision medicine for anxiety disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Anxiety disorders are increasingly prevalent, affect people's ability to do things, and decrease quality of life. Due to lack of objective tests, they are underdiagnosed and sub-optimally treated, resulting in adverse life events and/or addictions. We endeavored to discover blood biomarkers for anxiety, using a four-step approach. First, we used a longitudinal within-subject design in individuals with psychiatric disorders to discover blood gene expression changes between self-reported low anxiety and high anxiety states. Second, we prioritized the list of candidate biomarkers with a Convergent Functional Genomics approach using other evidence in the field. Third, we validated our top biomarkers from discovery and prioritization in an independent cohort of psychiatric subjects with clinically severe anxiety. Fourth, we tested these candidate biomarkers for clinical utility, i.e. ability to predict anxiety severity state, and future clinical worsening (hospitalizations with anxiety as a contributory cause), in another independent cohort of psychiatric subjects. We showed increased accuracy of individual biomarkers with a personalized approach, by gender and diagnosis, particularly in women. The biomarkers with the best overall evidence were GAD1, NTRK3, ADRA2A, FZD10, GRK4, and SLC6A4. Finally, we identified which of our biomarkers are targets of existing drugs (such as a valproate, omega-3 fatty acids, fluoxetine, lithium, sertraline, benzodiazepines, and ketamine), and thus can be used to match patients to medications and measure response to treatment. We also used our biomarker gene expression signature to identify drugs that could be repurposed for treating anxiety, such as estradiol, pirenperone, loperamide, and disopyramide. Given the detrimental impact of untreated anxiety, the current lack of objective measures to guide treatment, and the addiction potential of existing benzodiazepines-based anxiety medications, there is a urgent need for more precise and personalized approaches like the one we developed.

A Scalable Radiomics- and Natural Language Processing-Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study

BACKGROUND

The identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better management. Hence, it has the potential to improve the quality of life of patients with cancer. Artificial intelligence can aid in the extraction of objective pain biomarkers for patients with cancer with bone metastases (BMs).

OBJECTIVE

This study aimed to develop and evaluate a scalable natural language processing (NLP)- and radiomics-based machine learning pipeline to differentiate between painless and painful BM lesions in simulation computed tomography (CT) images using imaging features (biomarkers) extracted from lesion center point-based regions of interest (ROIs).

METHODS

Patients treated at our comprehensive cancer center who received palliative radiotherapy for thoracic spine BM between January 2016 and September 2019 were included in this retrospective study. Physician-reported pain scores were extracted automatically from radiation oncology consultation notes using an NLP pipeline. BM center points were manually pinpointed on CT images by radiation oncologists. Nested ROIs with various diameters were automatically delineated around these expert-identified BM center points, and radiomics features were extracted from each ROI. Synthetic Minority Oversampling Technique resampling, the Least Absolute Shrinkage And Selection Operator feature selection method, and various machine learning classifiers were evaluated using precision, recall, F1-score, and area under the receiver operating characteristic curve.

RESULTS

Radiation therapy consultation notes and simulation CT images of 176 patients (mean age 66, SD 14 years; 95 males) with thoracic spine BM were included in this study. After BM center point identification, 107 radiomics features were extracted from each spherical ROI using pyradiomics. Data were divided into 70% and 30% training and hold-out test sets, respectively. In the test set, the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of our best performing model (neural network classifier on an ensemble ROI) were 0.82 (132/163), 0.59 (16/27), 0.85 (116/136), and 0.83, respectively.

CONCLUSIONS

Our NLP- and radiomics-based machine learning pipeline was successful in differentiating between painful and painless BM lesions. It is intrinsically scalable by using NLP to extract pain scores from clinical notes and by requiring only center points to identify BM lesions in CT images.

Precision Medicine in Oral Health and Diseases: A Systematic Review

Precision medicine (PM) is personalized medicine that can develop targeted medical therapies for the individual patient, in which "omics" sciences lead to an integration of data that leads to highly predictive models of the functioning of the individual biological system. They enable rapid diagnosis, assessment of disease dynamics, identification of targeted treatment protocols, and reduction of costs and psychological stress. "Precision dentistry" (DP) is one promising application that need further investigation; the purpose of this paper is therefore to give physicians an overview of the knowledge they need to enhance treatment planning and patient response to therapy. A systematic literature review was conducted on the PubMed, Scopus, and Web of Science databases by analyzing the articles examining the role of precision medicine in dentistry. PM aims to shed light on cancer prevention strategies, by identifying risk factors, and on malformations such as orofacial cleft. Another application is pain management by repurposing drugs created for other diseases to target biochemical mechanisms. The significant heritability of traits regulating bacterial colonization and local inflammatory responses is another result of genomic research, and is useful for DP in the field of caries and periodontitis. This approach may also be useful in the field of orthodontics and regenerative dentistry. The possibility of creating an international network of databases will lead to the diagnosis, prediction, and prevention of disease outbreaks, providing significant economic savings for the world's health care systems.

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

In a healthy state, pain plays an important role in natural biofeedback loops and helps to detect and prevent potentially harmful stimuli and situations. However, pain can become chronic and as such a pathological condition, losing its informative and adaptive function. Efficient pain treatment remains a largely unmet clinical need. One promising route to improve the characterization of pain, and with that the potential for more effective pain therapies, is the integration of different data modalities through cutting edge computational methods. Using these methods, multiscale, complex, and network models of pain signaling can be created and utilized for the benefit of patients. Such models require collaborative work of experts from different research domains such as medicine, biology, physiology, psychology as well as mathematics and data science. Efficient work of collaborative teams requires developing of a common language and common level of understanding as a prerequisite. One of ways to meet this need is to provide easy to comprehend overviews of certain topics within the pain research domain. Here, we propose such an overview on the topic of pain assessment in humans for computational researchers. Quantifications related to pain are necessary for building computational models. However, as defined by the International Association of the Study of Pain (IASP), pain is a sensory and emotional experience and thus, it cannot be measured and quantified objectively. This results in a need for clear distinctions between nociception, pain and correlates of pain. Therefore, here we review methods to assess pain as a percept and nociception as a biological basis for this percept in humans, with the goal of creating a roadmap of modelling options.

Platelet Membrane Proteins as Pain Biomarkers in Patients with Severe Dementia

Pain is one of the most frequent health problems, and its evaluation and therapeutic approach largely depend on patient self-report. When it is not possible to obtain a self-report, the therapeutic decision becomes more difficult and limited. This study aims to evaluate whether some membrane platelet proteins could be of value in pain characterization. To achieve this goal, we used 53 blood samples obtained from palliative patients, 44 with non-oncological pain and nine without pain. We observed in patients with pain a decrease in the percentage of platelets expressing CD36, CD49f, and CD61 and in the expression levels of CD49f and CD61 when compared with patients without pain. Besides that, an increase in the percentage of platelets expressing CD62p was observed in patients with pain. These results suggest that the levels of these platelet cluster differentiations (CDs) could have some value as pain biomarkers objectively since they are not dependent on the patient's participation. Likewise, CD40 seems to have some importance as a biomarker of moderate and/or severe pain. The identification of pain biomarkers such as CD40, CD49f, CD62p and CD61 can lead to an adjustment of the therapeutic strategy, contributing to a faster and more adequate control of pain and reduction in patient-associated suffering.

Derivation of nociceptive sensory neurons from hiPSCs with early patterning and temporally controlled NEUROG2 overexpression

Despite development of protocols to differentiate human pluripotent stem cells (hPSCs), those used to produce sensory neurons remain difficult to replicate and result in heterogenous populations. There is a growing clinical burden of chronic pain conditions, highlighting the need for relevant human cellular models. This study presents a hybrid differentiation method to produce nociceptive sensory neurons from hPSCs. Lines harboring an inducible NEUROG2 construct were patterned toward precursors with small molecules followed by NEUROG2 overexpression. Neurons expressed key markers, including BRN3A and ISL1, with single-cell RNA sequencing, revealing populations of nociceptors expressing SCN9A and TRP channels. Physiological profiling with multi-electrode arrays revealed that neurons responded to noxious stimuli, including capsaicin. Finally, we modeled pain-like states to identify genes and pathways involved in pain transduction. This study presents an optimized method to efficiently produce nociceptive sensory neurons and provides a tool to aid development of chronic pain research.

Biomarkers for Chronic Pain: Significance and Summary of Recent Advances

Chronic pain can be difficult to predict and a challenge to treat. Biomarkers for chronic pain signal an opportunity for advancements in both management and prevention, and through their research and development offer new insights into the complex processes at play. This review considers the latest research in chronic pain biomarker development and considers how close we are to bringing these from bench to bedside. While some headway has been made that offers efficiencies in patient selection, it is unlikely that a single test will encompass the variety of chronic pain phenotypes. We offer some insights for the near future in biomarker development and areas of continued unmet need.

Genetic risk for chronic pain is associated with lower antidepressant effectiveness: Converging evidence for a depression subtype

INTRODUCTION

Chronic pain and depression are highly comorbid and difficult-to-treat disorders. We previously showed this comorbidity is associated with higher depression severity, lower antidepressant treatment effectiveness and poorer prognosis in the Australian Genetics of Depression Study.

OBJECTIVE

The current study aimed to assess whether a genetic liability to chronic pain is associated with antidepressant effectiveness over and above the effect of genetic factors for depression in a sample of 12,863 Australian Genetics of Depression Study participants.

METHODS

Polygenic risk scores were calculated using summary statistics from genome-wide association studies of multisite chronic pain and major depression. Cumulative linked regressions were employed to assess the association between polygenic risk scores and antidepressant treatment effectiveness across 10 different medications.

RESULTS

Mixed-effects logistic regressions showed that individual genetic propensity for chronic pain, but not major depression, was significantly associated with patient-reported chronic pain (Pain^PRS OR = 1.17 [1.12, 1.22]; MD^PRS OR = 1.01 [0.98, 1.06]). Significant associations were also found between lower antidepressant effectiveness and genetic risk for chronic pain or for major depression. However, a fully adjusted model showed the effect of Pain^PRS (adjOR = 0.93 [0.90, 0.96]) was independent of MD^PRS (adjOR = 0.96 [0.93, 0.99]). Sensitivity analyses were performed to assess the robustness of these results. After adjusting for depression severity measures (i.e. age of onset; number of depressive episodes; interval between age at study participation and at depression onset), the associations between Pain^PRS and patient-reported chronic pain with lower antidepressant effectiveness remained significant (0.95 [0.92, 0.98] and 0.84 [0.78, 0.90], respectively).

CONCLUSION

These results suggest genetic risk for chronic pain accounted for poorer antidepressant effectiveness, independent of the genetic risk for major depression. Our results, along with independent converging evidence from other studies, point towards a difficult-to-treat depression subtype characterised by comorbid chronic pain. This finding warrants further investigation into the implications for biologically based nosology frameworks in pain medicine and psychiatry.

Recent advances in pain management based on nanoparticle technologies

BACKGROUND

Pain is a vital sense that indicates the risk of injury at a particular body part. Successful control of pain is the principal aspect in medical treatment. In recent years, the advances of nanotechnology in pain management have been remarkable. In this review, we focus on literature and published data that reveal various applications of nanotechnology in acute and chronic pain management.

METHODS

The presented content is based on information collected through pain management publications (227 articles up to April 2021) provided by Web of Science, PubMed, Scopus and Google Scholar services.

RESULTS

A comprehensive study of the articles revealed that nanotechnology-based drug delivery has provided acceptable results in pain control, limiting the side effects and increasing the efficacy of analgesic drugs. Besides the ability of nanotechnology to deliver drugs, sophisticated nanosystems have been designed to enhance imaging and diagnostics, which help in rapid diagnosis of diseases and have a significant impact on controlling pain. Furthermore, with the development of various tools, nanotechnology can accurately measure pain and use these measurements to display the efficiency of different interventions.

CONCLUSIONS

Nanotechnology has started a new era in the pain management and many promising results have been achieved in this regard. Nevertheless, there is still no substantial and adequate act of nanotechnology in this field. Therefore, efforts should be directed to broad investigations.

Uncontrolled pain in critically ill patients and acute kidney injury: a hypothesis-generating cohort study

Background

In critically ill patients, acute pain occurs frequently, causes sympathetic activation, release of inflammatory mediators, and potential organ dysfunction, with the kidneys potentially sensitive to inflammation-mediated injury. This study aimed to explore the association between acute pain in critically ill patients and the occurrence of acute kidney injury (AKI).

Methods

Data from a retrospective cohort of adult patients admitted between June 2013 and June 2016 to the Intensive Care Unit (ICU) of a tertiary hospital in São Paulo, Brazil, were analyzed. The main exclusion criteria were ICU length of stay < 48 h, coma, and prior kidney dysfunction. The outcome (AKI) was defined as an elevation in the baseline serum creatinine level of ≥ 0.3 mg/dl and/or > 50% at any time after the first 48 h in the ICU. Multivariable logistic regression and hierarchical cluster analysis were performed.

Results

The isolated incidence of pain was 23.6%, and the incidence of pain duration > 5 days was 10.6%. AKI occurred in 31.7% of the cohort. In multivariable logistic analysis, duration of pain > 5 days (OR 5.25 CI 2.19–12.57 p < 0.01) and mechanical ventilation (MV) ≥ 3 days (OR 5.5 CI 2.3–13.5 p < 0.01) were the variables with positive association with AKI. The hierarchical cluster analysis reinforced the relation between AKI, MV and duration of pain.

Conclusions

Pain is an especially important issue in critically ill patients and in this exploratory study it appears to be associated with AKI development. The search for more rigorous pain control in ICU is crucial and can influence organ dysfunction.

Graphical Abstract

Making Biomarkers Relevant to Healthcare Innovation and Precision Medicine

Translational medicine, the exchange between laboratory (bench) and the clinic (bedside), is decidedly taking on a vital role. Many companies are now focusing on a translational medicinal approach as a therapeutic strategy in decision making upon realizing the expenses of drug attrition in late-stage advancement. In addition, the utility of biomarkers in clinical decision and therapy guidance seeks to improve the patient outcomes and decrease wasteful and harmful treatment. Efficient biomarkers are crucial for the advancement of diagnoses, better molecular targeted therapy, along with therapeutic advantages in a broad spectrum of various diseases. Despite recent advances in the discovery of biomarkers, the advancement route to a clinically validated biomarker remains intensely challenging, and many of the candidate biomarkers do not progress to clinical applications, thereby widening the innovation gap between research and application. The present article will focus on the clinical view of biomarkers in a reverse design, addressing how a biomarker program should appear if it is expected to create an impact on personalized medicine and patient care.

Genetic and epigenetic mechanisms influencing acute to chronic postsurgical pain transitions in pediatrics: Preclinical to clinical evidence

Background

Chronic postsurgical pain (CPSP) in children remains an important problem with no effective preventive or therapeutic strategies. Recently, genomic underpinnings explaining additional interindividual risk beyond psychological factors have been proposed.

Aims

We present a comprehensive review of current preclinical and clinical evidence for genetic and epigenetic mechanisms relevant to pediatric CPSP.

Methods

Narrative review.

Results

Animal models are relevant to translational research for unraveling genomic mechanisms. For example, Cacng2, p2rx7, and bdnf mutant mice show altered mechanical hypersensitivity to injury, and variants of the same genes have been associated with CPSP susceptibility in humans; similarly, differential DNA methylation (H1SP) and miRNAs (miR-96/7a) have shown translational implications. Animal studies also suggest that crosstalk between neurons and immune cells may be involved in nociceptive priming observed in neonates. In children, differential DNA methylation in regulatory genomic regions enriching GABAergic, dopaminergic, and immune pathways, as well as polygenic risk scores for enhanced prediction of CPSP, have been described. Genome-wide studies in pediatric CPSP are scarce, but pathways identified by adult gene association studies point to potential common mechanisms.

Conclusions

Bench-to-bedside genomics research in pediatric CPSP is currently limited. Reverse translational approaches, use of other -omics, and inclusion of pediatric/CPSP endophenotypes in large-scale biobanks may be potential solutions. Time of developmental vulnerability and longitudinal genomic changes after surgery warrant further investigation. Emergence of promising precision pain management strategies based on gene editing and epigenetic programing emphasize need for further research in pediatric CPSP-related genomics.

Patient Selection for Spinal Cord Stimulation in Treatment of Pain: Sequential Decision-Making Model - A Narrative Review

Despite the well-known efficacy of spinal cord stimulation (SCS) in chronic pain management, patient selection in clinical practice remains challenging. The aim of this review is to provide an overview of the factors that can influence the process of patient selection for SCS treatment. A sequential decision-making model is presented within a tier system that operates in clinical practice. The first level incorporates the underlying disease as a primary indication for SCS, country-related reimbursement rules, and SCS screening-trial criteria in combination with underlying psychological factors as initial selection criteria in evaluating patient eligibility for SCS. The second tier is aligned with the individualized approach within precision pain medicine, whereby individual goals and expectations and the potential need for preoperative optimizations are emphasized. Additionally, this tier relies on results from prediction models to provide an estimate of the efficacy of SCS in the long term. In the third tier, selection bias, MRI compatibility, and ethical beliefs are included, together with recent technological innovations, superiority of specific stimulation paradigms, and new feedback systems that could indirectly influence the decision-making of the physician. Both patients and physicians should be aware of the different aspects that influence patient selection in relation to SCS for pain management to make an independent decision on whether or not to initiate a treatment trajectory with SCS.

Drug Repurposing to Target Neuroinflammation and Sensory Neuron-Dependent Pain

Around 20% of the American population have chronic pain and estimates in other Western countries report similar numbers. This represents a major challenge for global health care systems. Additional problems for the treatment of chronic and persistent pain are the comparably low efficacy of existing therapies, the failure to translate effects observed in preclinical pain models to human patients and related setbacks in clinical trials from previous attempts to develop novel analgesics. Drug repurposing offers an alternative approach to identify novel analgesics as it can bypass various steps of classical drug development. In recent years, several approved drugs were attributed analgesic properties. Here, we review available data and discuss recent findings suggesting that the approved drugs minocycline, fingolimod, pioglitazone, nilotinib, telmisartan, and others, which were originally developed for the treatment of different pathologies, can have analgesic, antihyperalgesic, or neuroprotective effects in preclinical and clinical models of inflammatory or neuropathic pain. For our analysis, we subdivide the drugs into substances that can target neuroinflammation or substances that can act on peripheral sensory neurons, and highlight the proposed mechanisms. Finally, we discuss the merits and challenges of drug repurposing for the development of novel analgesics.

Role of Brain Imaging in Drug Development for Psychiatry

Background:

Over the last decades, many brain imaging studies have contributed to new insights in the pathogenesis of psychiatric disease. However, in spite of these developments, progress in the development of novel therapeutic drugs for prevalent psychiatric health conditions has been limited.

Objective:

In this review, we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I units.

Conclusion:

Brain imaging technology has revolutionized the study of psychiatric illnesses, and during the last decade, neuroimaging has provided valuable insights at different levels of analysis and brain organization, such as effective connectivity (anatomical), functional connectivity patterns and neurochemical information that may support both preclinical and clinical drug development. Since there is no unifying pathophysiological theory of individual psychiatric syndromes and since many symptoms cut across diagnostic boundaries, a new theoretical framework has been proposed that may help in defining new targets for treatment and thus enhance drug development in CNS diseases. In addition, it is argued that new proposals for data-mining and mathematical modelling as well as freely available databanks for neural network and neurochemical models of rodents combined with revised psychiatric classification will lead to new validated targets for drug development.

A neuropsychosocial signature predicts longitudinal symptom changes in women with irritable bowel syndrome

Irritable bowel syndrome (IBS) is a common disorder of brain-gut interactions characterized by chronic abdominal pain, altered bowel movements, often accompanied by somatic and psychiatric comorbidities. We aimed to test the hypothesis that a baseline phenotype composed of multi-modal neuroimaging and clinical features predicts clinical improvement on the IBS Symptom Severity Scale (IBS-SSS) at 3 and 12 months without any targeted intervention. Female participants (N = 60) were identified as "improvers" (50-point decrease on IBS-SSS from baseline) or "non-improvers." Data integration analysis using latent components (DIABLO) was applied to a training and test dataset to determine whether a limited number of sets of multiple correlated baseline'omics data types, including brain morphometry, anatomical connectivity, resting-state functional connectivity, and clinical features could accurately predict improver status. The derived predictive models predicted improvement status at 3-months and 12-months with 91% and 83% accuracy, respectively. Across both time points, non-improvers were classified as having greater correlated morphometry, anatomical connectivity and resting-state functional connectivity characteristics within salience and sensorimotor networks associated with greater pain unpleasantness, but lower default mode network integrity and connectivity. This suggests that non-improvers have a greater engagement of attentional systems to perseverate on painful visceral stimuli, predicting IBS exacerbation. The ability of baseline multimodal brain-clinical signatures to predict symptom trajectories may have implications in guiding integrative treatment in the age of precision medicine, such as treatments targeted at changing attentional systems such as mindfulness or cognitive behavioral therapy.

A candidate neuroimaging biomarker for detection of neurotransmission-related functional alterations and prediction of pharmacological analgesic response in chronic pain

Chronic pain is a world-wide clinical challenge. Response to analgesic treatment is limited and difficult to predict. Functional MRI has been suggested as a potential solution. However, while most analgesics target specific neurotransmission pathways, functional MRI-based biomarkers are not specific for any neurotransmitter system, limiting our understanding of how they might contribute to predict treatment response. Here, we sought to bridge this gap by applying Receptor-Enriched Analysis of Functional Connectivity by Targets to investigate whether neurotransmission-enriched functional connectivity mapping can provide insights into the brain mechanisms underlying chronic pain and inter-individual differences in analgesic response after a placebo or duloxetine. We performed secondary analyses of two openly available resting-state functional MRI data sets of 56 patients with chronic knee osteoarthritis pain who underwent pre-treatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-week single-blinded placebo pill trial. Study 2 (n = 39) was a 3-month double-blinded randomized trial comparing placebo to duloxetine, a dual serotonin–noradrenaline reuptake inhibitor. Across two independent studies, we found that patients with chronic pain present alterations in the functional circuit related to the serotonin transporter, when compared with age-matched healthy controls. Placebo responders in Study 1 presented with higher pre-treatment functional connectivity enriched by the dopamine transporter compared to non-responders. Duloxetine responders presented with higher pre-treatment functional connectivity enriched by the serotonin and noradrenaline transporters when compared with non-responders. Neurotransmission-enriched functional connectivity mapping might hold promise as a new mechanistic-informed biomarker for functional brain alterations and prediction of response to pharmacological analgesia in chronic pain.

How Well Do Current Laboratory Biomarkers Inform Clinical Decision-Making in Chronic Pain Management?

OBJECTIVE

Decision-making in chronic pain patients involves a combination of subjective and objective criteria, including patient history, physical examination, imaging, and patient response to prior treatments, clinical experience, probabilities, and recognition of patterns. However, there is a distinct lack of objective laboratory biomarkers in use in routine clinical care. The objective was to review the literature to identify and describe specific biomarkers in chronic pain management.

METHODS

This is a narrative review of the literature regarding the use of laboratory biomarkers in chronic pain. A librarian-assisted literature search of the PubMed, Science Direct, and Google Scholar databases was performed and resulted in 304 possible manuscripts. We included manuscripts assessing laboratory collected biomarkers from urine, serum, cerebrospinal fluid, and saliva. After screening and review of the initial literature search results, a total of 75 manuscripts were included in the narrative review.

CONCLUSION

The studies reviewed suggested that specific biomarkers may help identify those patients at risk of disease development and function as a prognostic indicator for disease progression and treatment response. However, additional research is necessary before specific recommendations can be made, and current clinical decision-making is modified.

Mapping vitamin B6 metabolism by hydrazoCEST magnetic resonance imaging

A new CEST-MRI contrast agent, 2-HYNIC, capable of sensing aromatic aldehydes is reported. Pyridoxal 5'-phosphate, a key Vitamin B₆ metabolite necessary for >140 biotransformations was mapped by CEST-MRI in vitro and in vivo in lung cancer. 2-HYNIC provided access to this key biomarker associated with a variety of human diseases.

Pain Experience in Pancreatitis: Strong Association of Genetic Risk Loci for Anxiety and PTSD in Patients With Severe, Constant, and Constant-Severe Pain

INTRODUCTION

Recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP) are progressive inflammatory syndromes with variable features. Pain is the primary feature that contributes to low physical and mental quality of life with a third of patients reporting severe pain. Pain experience is worsened by depression. Here, we tested the hypothesis that genetic risk of the psychiatric conditions of anxiety and post-traumatic stress disorder (PTSD) is associated with pain in CP and RAP + CP subjects.

METHODS

The study cohort included phenotyped and genotyped RAP and CP patients from the North American Pancreatitis Study II of European Ancestry. Candidate genetic association studies were based on the absence of pain vs pain that is constant, constant-severe, or severe. Twenty-eight candidate genetic loci for anxiety and PTSD risk were identified in the literature and were the focus of this study.

RESULTS

We identified 24 significant pain-associated single nucleotide polymorphisms within 13 loci across the 3 pain patterns in CP and RAP + CP (P < 0.002). Thirteen anxiety or PTSD genes were within these pain loci indicating nonrandom associations (P < 4.885 × 10-23). CTNND2 was associated with all pain categories and all pancreatitis etiologies. Implicated systems include neuronal signaling (HTR2A, DRD3, NPY, and BDNF), hypothalamic-pituitary-adrenal axis (NR3C1 and FKBP5), and cell-cell interaction (CTNND2 and THBS2).

DISCUSSION

A component of constant and severe pain in patients with RAP and CP is associated with genetic predisposition to anxiety and PTSD. Identification of patients at risk eligible for trials of targeted treatment as a component of a multidisciplinary pain management strategy should be formally evaluated.

The Interplay between Chronic Pain, Opioids, and the Immune System

Chronic pain represents one of the most serious worldwide medical problems, in terms of both social and economic costs, often causing severe and intractable physical and psychological suffering. The lack of biological markers for pain, which could assist in forming clearer diagnoses and prognoses, makes chronic pain therapy particularly arduous and sometimes harmful. Opioids are used worldwide to treat chronic pain conditions, but there is still an ambiguous and inadequate understanding about their therapeutic use, mostly because of their dual effect in acutely reducing pain and inducing, at the same time, tolerance, dependence, and a risk for opioid use disorder. In addition, clinical studies suggest that opioid treatment can be associated with a high risk of immune suppression and the development of inflammatory events, worsening the chronic pain status itself. While opioid peptides and receptors are expressed in both central and peripheral nervous cells, immune cells, and tissues, the role of opioids and their receptors, when and why they are activated endogenously and what their exact role is in chronic pain pathways is still poorly understood. Thus, in this review we aim to highlight the interplay between pain and immune system, focusing on opioids and their receptors.

Implementation of the Uniformed Services University Pain Registry Biobank: A Military and Veteran Population Focused Biobank and Registry

OBJECTIVE

The objective of this overview is to discuss the development, implementation, data content, and structure of the Uniformed Services University Pain Registry Biobank. Additionally, procedures and policies for accessing samples for pain-related research purposes are detailed.

DESIGN

Cross-sectional overview.

SETTING

Multiple military treatment facilities.

SUBJECTS

Adult beneficiaries seeking care within the Military Health System.

METHODS

Participants complete a baseline battery of biopsychosocial survey measures, including PROMIS® measures, provide biologic samples (e.g. blood and saliva), and relevant health history, including medications and surgical history, is extracted from medical records. During the course of the next year, enrolled participants complete surveys and provide biologic samples at 3-months, 6-months, and 12-months. Thereafter, participants are contacted once annually to complete self-reported assessments and provide biologic samples.

RESULTS

In the first year alone 86 subjects have participated in the Uniformed Services University Pain Registry Biobank and provided 390 observations (e.g. biological samples and biopsychosocial patient-reported outcomes). The Uniformed Services University Pain Registry Biobank's integration of biological samples, patient-reported outcomes, and health record data over a longitudinal period across a diverse sample recruited from multiple military facilities addresses many of the limitations faced by other pain-related registries or biorepositories.

CONCLUSIONS

The Uniformed Services University Pain Registry Biobank will serve as a platform for conducting research closely aligned with the Federal Pain Research Strategy. The inclusion of active duty service members, beneficiaries, and civilians living with and without acute or chronic pain provides a unique data repository for all investigators interested in advancing pain science.

Opportunities and challenges for nonaddictive interventions in chronic pain

The worlds of chronic pain and addiction continue to intersect too often in many ways. Chronic pain significantly impairs and disrupts the quality of life of millions of people worldwide. Opioids remain the most prescribed pharmacotherapy offered to patients to alleviate chronic pain. The extensive and often unnecessary prescription of opioids has created a surge in the prevalence of opioid use disorders and opioid overdose-related deaths. In this brief review, we aim to provide a bench-to-bedside overview of promising biomarkers, therapeutic targets, and challenges related to treating patients with chronic pain. We hope this review will inspire new opportunities and insights into the development of novel, nonaddictive treatments for chronic pain that will be available to patients in the near future.

Severe Pain in Chronic Pancreatitis Patients: Considering Mental Health and Associated Genetic Factors

Pain is the most distressing and disruptive feature of recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP) resulting in low quality of life (QOL) and disabilities. There is no single, characteristic pain pattern in patients with RAP and CP. Abdominal imaging features of CP accurately reflect morphologic features but they do not correlate with pain. Pain is the major driver of poor quality of life (QOL) and it is the constant pain, rather than intermittent pain that drives poor QOL. Furthermore, the most severe constant pain experience in CP is also a complex condition. The ability to target the etiopathogenesis of severe pain requires new methods to detect the exact pain mechanisms in an individual at cellular, tissue, system and psychiatric levels. In patients with complex and severe disease, it is likely that multiple overlapping mechanisms are simultaneously driving pain, anxiety and depression. Quantitative sensory testing (QST) shows promise in detecting alterations in central processing of pain signals and to classify patients for mechanistic and therapeutic studies. New genetic research suggests that genetic loci for severe pain in CP overlap with genetic loci for depression and other psychiatric disorders, providing additional insights and therapeutic targets for individual patients with severe CP pain. Well-designed clinical trials that integrate clinical features, QST, genetics and psychological assessments with targeted treatment and assessment of responses are required for a quantum leap forward. A better understanding of the context and mechanisms contributing to severe pain experiences in individual patients is predicted to lead to better therapies and quality of life.

Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody. The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising [1], and validated by others [2]. Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality) [3-6]. These studies showed good reproducibility with subsequent independent genetic studies [7]. More recently, we have conducted such studies also for pain [8], for stress disorders [9], and for memory/Alzheimer's Disease [10]. We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients. First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7). Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field. Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff. Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth. Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women. Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder. Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies. Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications. Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders.

Elevated MicroRNA 183 Impairs Trophoblast Migration and Invasiveness by Downregulating FOXP1 Expression and Elevating GNG7 Expression during Preeclampsia

Preeclampsia (PE) is a hypertensive disorder of uncertain etiology that is the leading cause of maternal and fetal morbidity or mortality. The dysregulation of microRNAs (miRNAs) has been highlighted as a potential factor involved in the development of PE. Therefore, our study investigated a novel miRNA, miRNA 183 (miR-183), and its underlying association with PE. Expression of miR-183, forkhead box P1 (FOXP1), and G protein subunit gamma 7 (GNG7) in placental tissues of patients with PE was determined. Gain- and loss-of-function experiments were conducted to explore modulatory effects of miR-183, FOXP1, and GNG7 on the viability, invasion, and angiogenesis of trophoblast cells in PE. Finally, we undertook in vivo studies to explore effects of FOXP1 in the PE model. The results revealed suppressed expression of FOXP1 and significant elevations in miR-183 and GNG7 expression in placental tissues of PE patients. FOXP1 was observed to promote proliferation, invasion, and angiogenesis in human chorionic trophoblastic cells. miR-183 resulted in depletion of FOXP1 expression, while FOXP1 was capable of restraining GNG7 expression and promoting the mTOR pathway. The findings confirmed the effects of FOXP1 on PE. In conclusion, miR-183 exhibits an inhibitory role in PE through suppression of FOXP1 and upregulation of GNG7.

Bioimpedance Sensor and Methodology for Acute Pain Monitoring

The paper aims to revive the interest in bioimpedance analysis for pain studies in communicating and non-communicating (anesthetized) individuals for monitoring purpose. The plea for exploitation of full potential offered by the complex (bio)impedance measurement is emphasized through theoretical and experimental analysis. A non-invasive, low-cost reliable sensor to measure skin impedance is designed with off-the-shelf components. This is a second generation prototype for pain detection, quantification, and modeling, with the objective to be used in fully anesthetized patients undergoing surgery. The 2D and 3D time-frequency, multi-frequency evaluation of impedance data is based on broadly available signal processing tools. Furthermore, fractional-order impedance models are implied to provide an indication of change in tissue dynamics correlated with absence/presence of nociceptor stimulation. The unique features of the proposed sensor enhancements are described and illustrated here based on mechanical and thermal tests and further reinforced with previous studies from our first generation prototype.

COMT Genotype and Efficacy of Propranolol for TMD Pain: A Randomized Trial

Propranolol is a nonselective β-adrenergic receptor antagonist that is efficacious in reducing facial pain. There is evidence that its analgesic efficacy might be modified by variants of the catechol-O-methyltransferase (COMT) gene. We tested the hypothesis in a subset of 143 non-Hispanic Whites from a randomized controlled trial of patients with painful temporomandibular disorder (TMD). Patients were genotyped for rs4680, a single nucleotide polymorphism of COMT, and randomly allocated to either propranolol 60 mg twice daily or placebo. During the 9-wk follow-up period, patients recorded daily ratings of facial pain intensity and duration; the product was computed as an index of facial pain. Postbaseline change in the index at week 9 (the primary endpoint) was analyzed as a continuous variable and dichotomized at thresholds of ≥30% and ≥50% reduction. Mixed models for repeated measures tested for the genotype × treatment group interaction and estimated means, odds ratios (ORs), and 95% confidence limits (95% CLs) of efficacy within COMT genotypes assuming an additive genetic model. In secondary analysis, the cumulative response curves were plotted for dichotomized reductions ranging from ≥20% to ≥70%, and genotype differences in area under the curve percentages (%AUC) were calculated to signify efficacy. Mean index reduction did not differ significantly (P = 0.277) according to genotype, whereas the dichotomized ≥30% reduction revealed greater efficacy among G:G homozygotes (OR = 10.9, 95%CL = 2.4, 50.7) than among A:A homozygotes (OR = 0.8, 95%CL = 0.2, 3.2) with statistically significant interaction (P = 0.035). Cumulative response curves confirmed greater (P = 0.003) efficacy for G:G homozygotes (%AUC difference = 43.7, 95%CL = 15.4, 72.1) than for A:A homozygotes (%AUC difference = 6.5, 95%CL = -30.2, 43.2). The observed antagonistic effect of the A allele on propranolol’s efficacy was opposite the synergistic effect hypothesized a priori. This unexpected result highlights the need for better knowledge of COMT’s role in pain pathogenesis if the gene is to be used for precision-medicine treatment of TMD (ClinicalTrials.gov NCT02437383).

The Relationship between Pain and Vascular Function Biomarkers in Dysmenorrheal University Students

Our aim was to establish if the secretion of contactin 1 (CNTN-1), a widely researched pain biomarker correlates with the severity of dysmenorrhea and circulating levels of vascular cell adhesion molecule 1 (VCAM-1) and angiotensin II (ANG-II). This study was a longitudinal randomized clinical study that involved 95 female students between 17–25 years. The control participant group were students who, without medications, had not experienced dysmenorrhea, while the inclusion criteria were primary dysmenorrhea without medications. Data was collected using demographic questionnaires that also contained the Numeric Rating Scale (NRS-11), while blood samples were collected for analysis of CNTN-1, VCAM-1 and ANG-II by ELISA. The participants' mean BMI's across the four pain strata were between 16.60–38.43 kg/m² and in addition to age and menarche, showed no correlation to either the NRS-11 scale (r=−0.01214) or their CNTN-1 levels (r=0.009622). The severe dysmenorrhea group showed statistically higher (p<0.0001) and positive correlation to systolic (r=0.7304) and diastolic (0.6588) blood pressures. The contactin 1 levels (7.00-55.70 ng/mL) increased with higher menstrual pain and as the pain increased, so did the mean VCAM-1 and ANG-II levels (p<0.0001). A positive linear correlation (r=0.9691) was observed between the NRS-11 scale of the participants and their CNTN-1 activities while the CNTN-1 levels positively correlated with their VCAM-1 (r=0.9334) and ANG-II (r=0.8746) secretion. In summary, the severity of dysmenorrheal pain elevates the contactin 1 levels which affects their vascular health and blood pressure.

Convergent Functional Genomics approach to prioritize molecular targets of risk in early life stress-related psychiatric disorders

There is an overwhelming evidence proving that mental disorders are not the product of a single risk factor - i.e. genetic variants or environmental factors, including exposure to maternal perinatal mental health problems or childhood adverse events - rather the product of a trajectory of cumulative and multifactorial insults occurring during development, such as exposures during the foetal life to adverse mental condition in the mother, or exposures to adverse traumatic events during childhood or adolescence. In this review, we aim to highlight the potential utility of a Convergent Functional Genomics (CFG) approach to clarify the complex brain-relevant molecular mechanisms and alterations induced by early life stress (ELS). We describe different studies based on CFG in psychiatry and neuroscience, and we show how this 'hypothesis-free' tool can prioritize a stringent number of genes modulated by ELS, that can be tested as potential candidates for Gene x Environment (GxE) interaction studies. We discuss the results obtained by using a CFG approach identifying FoxO1 as a gene where genetic variability can mediate the effect of an adverse environment on the development of depression. Moreover, we also demonstrate that FoxO1 has a functional relevance in stress-induced reduction of neurogenesis, and can be a potential target for the prevention or treatment of stress-related psychiatric disorders. Overall, we suggest that CFG approach could include trans-species and tissues data integration and we also propose the application of CFG to examine in depth and to prioritize top candidate genes that are affected by ELS across lifespan and generations.

Blood biomarkers for memory: toward early detection of risk for Alzheimer disease, pharmacogenomics, and repurposed drugs

Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

Randomized Trial on the Clinical Utility of a Novel Biomarker Panel to Identify Treatable Determinants of Chronic Pain

Millions suffer daily from chronic pain diagnosed anatomically and treated with opioids. Research shows that underlying nutritional, metabolic and oxidative stressors, which drive the development or worsening of chronic pain, are not diagnosed despite the fact that treatment of these primary pain pathways relieves pain and increases function. One of the main reasons for this gap in care is the lack of a simple diagnostic assay to help clinicians make these diagnoses. We examined the clinical utility of a urine-based pain biomarker panel. Primary care physicians were randomized into the test group and compared to controls. We measured their ability to make the diagnosis and treat a total of nine standardized patients, with common but challenging cases of chronic pain, over two rounds of data collection in a pre–post design using a fixed-effects model. Intervention doctors received educational materials on a novel pain biomarker panel after the baseline round and had access to biomarker test results. Provider responses were measured against evidence-based criteria. The two study arms at baseline provided similar, poor care for three different primary pain pathways: nutritional deficiencies (5.0% control versus 9.2% intervention treated, p = 0.208), metabolic abnormalities (1.0% control versus 0% for intervention treated, p = 0.314), and oxidative stress (1.2% control versus 0% intervention treated, p = 0.152). After the introduction of the Foundation Pain Index (FPI) biomarker test, physicians in the intervention group were 41.5% more likely to make the diagnosis of a micronutrient deficiency, 29.4% more likely to identify a treatable metabolic abnormality and 26.1% more likely to identify an oxidative stressor. These diagnostic and treatment improvements were seen across all three case types, ranging from a relative +54% (p = 0.004) for chronic neuropathic pain to +35% (p = 0.007) in chronic pain from other causes to +38% (p = 0.002) in chronic pain with associated mental health issues. Intervention doctors were also 75.1% more likely to provide a non-opioid treatment to patients on chronic opioids (O.R. 1.8, 95% C.I. 0.8–3.7), 62% less likely to order unnecessary imaging for their patients with low back pain (O.R. 0.38, 95% C.I. 0.15–0.97) and 66% less likely to order an unnecessary pain referral (O.R. 0.34, 95% C.I. 0.13–0.90). This experimental study showed significant clinical utility of a validated pain biomarker panel that determines nutritional deficiencies, metabolic abnormalities and oxidative stressors that drive underlying treatable causes of pain. When integrated into routine primary care practice, this testing approach could considerably improve diagnostic accuracy and provide more targeted, non-opioid treatments for patients suffering from chronic pain.

Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.

Signaling pathways and gene co-expression modules associated with cytoskeleton and axon morphology in breast cancer survivors with chronic paclitaxel-induced peripheral neuropathy

Background

The major dose-limiting toxicity of paclitaxel, one of the most commonly used drugs to treat breast cancer, is peripheral neuropathy (paclitaxel-induced peripheral neuropathy). Paclitaxel-induced peripheral neuropathy, which persists into survivorship, has a negative impact on patient’s mood, functional status, and quality of life. Currently, no interventions are available to treat paclitaxel-induced peripheral neuropathy. A critical barrier to the development of efficacious interventions is the lack of understanding of the mechanisms that underlie paclitaxel-induced peripheral neuropathy. While data from preclinical studies suggest that disrupting cytoskeleton- and axon morphology-related processes are a potential mechanism for paclitaxel-induced peripheral neuropathy, clinical evidence is limited. The purpose of this study in breast cancer survivors was to evaluate whether differential gene expression and co-expression patterns in these pathways are associated with paclitaxel-induced peripheral neuropathy.

Methods

Signaling pathways and gene co-expression modules associated with cytoskeleton and axon morphology were identified between survivors who received paclitaxel and did (n = 25) or did not (n = 25) develop paclitaxel-induced peripheral neuropathy.

Results

Pathway impact analysis identified four significantly perturbed cytoskeleton- and axon morphology-related signaling pathways. Weighted gene co-expression network analysis identified three co-expression modules. One module was associated with paclitaxel-induced peripheral neuropathy group membership. Functional analysis found that this module was associated with four signaling pathways and two ontology annotations related to cytoskeleton and axon morphology.

Conclusions

This study, which is the first to apply systems biology approaches using circulating whole blood RNA-seq data in a sample of breast cancer survivors with and without chronic paclitaxel-induced peripheral neuropathy, provides molecular evidence that cytoskeleton- and axon morphology-related mechanisms identified in preclinical models of various types of neuropathic pain including chemotherapy-induced peripheral neuropathy are found in breast cancer survivors and suggests pathways and a module of genes for validation and as potential therapeutic targets.

Pain in neuropsychiatry: Insights from animal models

Pain is the most common symptom reported in clinical practice, meaning that it is associated with many pathologies as either the origin or a consequence of other illnesses. Furthermore, pain is a complex emotional and sensorial experience, as the correspondence between pain and body damage varies considerably. While these issues are widely acknowledged in clinical pain research, until recently they have not been extensively considered when exploring animal models, important tools for understanding pain pathophysiology. Interestingly, chronic pain is currently considered a risk factor to suffer psychiatric disorders, mainly stress-related disorders like anxiety and depression. Conversely, pain appears to be altered in many psychiatric disorders, such as depression, anxiety and schizophrenia. Thus, pain and psychiatric disorders have been linked in epidemiological and clinical terms, although the neurobiological mechanisms involved in this pathological bidirectional relationship remain unclear. Here we review the evidence obtained from animal models about the co-morbidity of pain and psychiatric disorders, placing special emphasis on the different dimensions of pain.

Pain Detection with Bioimpedance Methodology from 3-Dimensional Exploration of Nociception in a Postoperative Observational Trial

Although the measurement of dielectric properties of the skin is a long-known tool for assessing the changes caused by nociception, the frequency modulated response has not been considered yet. However, for a rigorous characterization of the biological tissue during noxious stimulation, the bioimpedance needs to be analyzed over time as well as over frequency. The 3-dimensional analysis of nociception, including bioimpedance, time, and frequency changes, is provided by ANSPEC-PRO device. The objective of this observational trial is the validation of the new pain monitor, named as ANSPEC-PRO. After ethics committee approval and informed consent, 26 patients were monitored during the postoperative recovery period: 13 patients with the in-house developed prototype ANSPEC-PRO and 13 with the commercial device MEDSTORM. At every 7 min, the pain intensity was measured using the index of Anspec-pro or Medstorm and the 0-10 numeric rating scale (NRS), pre-surgery for 14 min and post-anesthesia for 140 min. Non-significant differences were reported for specificity-sensitivity analysis between ANSPEC-PRO (AUC = 0.49) and MEDSTORM (AUC = 0.52) measured indexes. A statistically significant positive linear relationship was observed between Anspec-pro index and NRS (r2 = 0.15, p < 0.01). Hence, we have obtained a validation of the prototype Anspec-pro which performs equally well as the commercial device under similar conditions.

Identification of MOR-Positive B Cell as Possible Innovative Biomarker (Mu Lympho-Marker) for Chronic Pain Diagnosis in Patients with Fibromyalgia and Osteoarthritis Diseases

Fibromyalgia (FM) diagnosis follows the American College of Rheumatology (ACR) criteria, based on clinical evaluation and written questionnaires without any objective diagnostic tool. The lack of specific biomarkers is a tragic aspect for FM and chronic pain diseases in general. Interestingly, the endogenous opioid system is close to the immune one because of the expression of opioid receptors on lymphocytes membrane. Here we analyzed the role of the Mu opioid receptor on B lymphocytes as a specific biomarker for FM and osteoarthritis (OA) patients. We enrolled three groups of females: FM patients, OA patients (chronic pain control group) and healthy subjects (pain-free negative control group). We collected blood samples to apply immunophenotyping analysis. Written tests were administrated for psychological analysis. Data were statistically analyzed. Final results showed that the percentage of Mu-positive B cells were statistically lower in FM and OA patients than in pain-free subjects. A low expression of Mu-positive B cell was not associated with the psychological characteristics investigated. In conclusion, here we propose the percentage of Mu-positive B cells as a biological marker for an objective diagnosis of chronic pain suffering patients, also contributing to the legitimacy of FM as a truly painful disease.

Applying Serum Cytokine Levels to Predict Pain Severity in Cancer Patients

Background and Aim

Cancers originating in the breast, lung and prostate often metastasize to the bone, frequently resulting in cancer-induced bone pain that can be challenging to manage despite conventional analgesic therapy. This exploratory study’s aim was to identify potential biomarkers associated with cancer-induced pain by examining a sample population of breast cancer patients undergoing bisphosphonate therapy.

Methods

A secondary analysis of the primary study was performed to quantify serum cytokine levels for correlation to pain scores. Cytokines with statistically significant correlations were then input into a stepwise regression analysis to generate a predictive equation for a patient’s pain severity. In an effort to find additional potential biomarkers, correlation analysis was performed between these factors and a more comprehensive panel of cytokines and chemokines from breast, lung, and prostate cancer patients.

Results

Statistical analysis identified nine cytokines (GM-CSF, IFNγ, IL-1β, IL-2, IL-4, IL-5, IL-12p70, IL-17A, and IL-23) that had significant negative correlations with pain scores and they could best predict pain severity through a predictive equation generated for this specific evaluation. After performing a correlation analysis between these factors and a larger panel of cytokines and chemokines, samples from breast, lung and prostate patients showed distinct correlation profiles, highlighting the clinical challenge of applying pain-associated cytokines related to more defined nociceptive states, such as arthritis, to a cancer pain state.

Conclusion

Exploratory analyses such as the ones presented here will be a beneficial tool to expand insights into potential cancer-specific nociceptive mechanisms and to develop novel therapeutics.