Genetic polymorphisms and prediction of chronic post-surgical pain after hysterectomy-a subgroup analysis of a multicenter cohort study

Prognostic models for chronic postsurgical pain-Current developments, trends, and challenges

PURPOSE OF REVIEW

Prognostic models for chronic postsurgical pain (CPSP) aim to predict the likelihood for development and severity of CPSP in individual patients undergoing surgical procedures. Such models might provide valuable information for healthcare providers, allowing them to identify patients at higher risk and implement targeted interventions to prevent or manage CPSP effectively. This review discusses the latest developments of prognostic models for CPSP, their challenges, limitations, and future directions.

RECENT FINDINGS

Numerous studies have been conducted aiming to develop prognostic models for CPSP using various perioperative factors. These include patient-related factors like demographic variables, preexisting pain conditions, psychosocial aspects, procedure-specific characteristics, perioperative analgesic strategies, postoperative complications and, as indicated most recently, biomarkers. Model generation, however, varies and performance and accuracy differ between prognostic models for several reasons and validation of models is rather scarce.

SUMMARY

Precise methodology of prognostic model development needs advancements in the field of CPSP. Development of more accurate, validated and refined models in large-scale cohorts is needed to improve reliability and applicability in clinical practice and validation studies are necessary to further refine and improve the performance of prognostic models for CPSP.

A systematic review of genome-wide association studies for pain, nociception, neuropathy, and pain treatment responses

ABSTRACT

Pain is the leading cause of disability worldwide, imposing an enormous burden on personal health and society. Pain is a multifactorial and multidimensional problem. Currently, there is (some) evidence that genetic factors could partially explain individual susceptibility to pain and interpersonal differences in pain treatment response. To better understand the underlying genetic mechanisms of pain, we systematically reviewed and summarized genome-wide association studies (GWASes) investigating the associations between genetic variants and pain/pain-related phenotypes in humans. We reviewed 57 full-text articles and identified 30 loci reported in more than 1 study. To check whether genes described in this review are associated with (other) pain phenotypes, we searched 2 pain genetic databases, Human Pain Genetics Database and Mouse Pain Genetics Database. Six GWAS-identified genes/loci were also reported in those databases, mainly involved in neurological functions and inflammation. These findings demonstrate an important contribution of genetic factors to the risk of pain and pain-related phenotypes. However, replication studies with consistent phenotype definitions and sufficient statistical power are required to validate these pain-associated genes further. Our review also highlights the need for bioinformatic tools to elucidate the function of identified genes/loci. We believe that a better understanding of the genetic background of pain will shed light on the underlying biological mechanisms of pain and benefit patients by improving the clinical management of pain.

Integrating mechanistic-based and classification-based concepts into perioperative pain management: an educational guide for acute pain physicians

Chronic pain begins with acute pain. Physicians tend to classify pain by duration (acute vs chronic) and mechanism (nociceptive, neuropathic and nociplastic). Although this taxonomy may facilitate diagnosis and documentation, such categories are to some degree arbitrary constructs, with significant overlap in terms of mechanisms and treatments. In clinical practice, there are myriad different definitions for chronic pain and a substantial portion of chronic pain involves mixed phenotypes. Classification of pain based on acuity and mechanisms informs management at all levels and constitutes a critical part of guidelines and treatment for chronic pain care. Yet specialty care is often siloed, with advances in understanding lagging years behind in some areas in which these developments should be at the forefront of clinical practice. For example, in perioperative pain management, enhanced recovery protocols are not standardized and tend to drive treatment without consideration of mechanisms, which in many cases may be incongruent with personalized medicine and mechanism-based treatment. In this educational document, we discuss mechanisms and classification of pain as it pertains to commonly performed surgical procedures. Our goal is to provide a clinical reference for the acute pain physician to facilitate pain management decision-making (both diagnosis and therapy) in the perioperative period.

Pain predict genetics: protocol for a prospective observational study of clinical and genetic factors to predict the development of postoperative pain

INTRODUCTION

Postoperative pain remains a challenging medical condition impacting the quality of life of every patient. Although several predictive factors for postoperative pain have been identified, an adequate prediction of postoperative pain in patients at risk has not been achieved yet.The primary objective of this study is to identify specific genetic risk factors for the development of acute and chronic postoperative pain to construct a prediction model facilitating a more personalised postoperative pain management for each individual. The secondary objectives are to build a databank enabling researchers to identify other risk factors for postoperative pain, for instance, demographic and clinical outcome indicators; provide insight into (genetic) factors that predict pharmacological pain relief; investigate the relationship between acute and chronic postoperative pain.

METHODS AND ANALYSIS

In this prospective, observational study, patients who undergo elective surgery will be recruited to a sample size of approximately 10 000 patients. Postoperative acute and chronic pain outcomes will be collected through questionnaires at different time points after surgery in the follow-up of 6 months. Potential genetic, demographic and clinical risk factors for prediction model construction will be collected through blood, questionnaires and electronic health records, respectively.Genetic factors associated with acute and/or chronic postoperative pain will be identified using a genome-wide association analysis. Clinical risk factors as stated in the secondary objectives will be assessed by multivariable regression. A clinical easy-to-use prediction model will be created for postoperative pain to allow clinical use for the stratification of patients.

ETHICS AND DISSEMINATION

The Institutional Review Board of the Radboud university medical centre approved the study (authorisation number: 2012/117). The results of this study will be made available through peer-reviewed scientific journals and presentations at relevant conferences, which will finally contribute to personalised postoperative pain management.

TRIAL REGISTRATION NUMBER

NCT02383342.

Prognostic prediction models for chronic postsurgical pain in adults: a systematic review

ABSTRACT

Chronic postsurgical pain (CPSP) affects an estimated 10% to 50% of adults depending on the type of surgical procedure. Clinical prediction models can help clinicians target preventive strategies towards patients at high risk for CPSP. Therefore, the objective of this systematic review was to identify and describe existing prediction models for CPSP in adults. A systematic search was performed in MEDLINE, Embase, PsychINFO, and the Cochrane Database of Systematic Reviews in March 2020 for English peer-reviewed studies that used data collected between 2000 and 2020. Studies that developed, validated, or updated a prediction model in adult patients who underwent any surgical procedure were included. Two reviewers independently screened titles, abstracts, and full texts for eligibility; extracted data; and assessed risk of bias using the Prediction model Risk of Bias Assessment Tool. The search identified 2037 records; 28 articles were reviewed in full text. Fifteen studies reporting on 19 prediction models were included; all were at high risk of bias. Model discrimination, measured by the area under receiver operating curves or c-statistic, ranged from 0.690 to 0.816. The most common predictors identified in final prediction models included preoperative pain in the surgical area, preoperative pain in other areas, age, sex or gender, and acute postsurgical pain. Clinical prediction models may support prevention and management of CPSP, but existing models are at high risk of bias that affects their reliability to inform practice and generalizability to wider populations. Adherence to standardized guidelines for clinical prediction model development is necessary to derive a prediction model of value to clinicians.

Computational Functional Genomics-Based AmpliSeq™ Panel for Next-Generation Sequencing of Key Genes of Pain

The genetic background of pain is becoming increasingly well understood, which opens up possibilities for predicting the individual risk of persistent pain and the use of tailored therapies adapted to the variant pattern of the patient's pain-relevant genes. The individual variant pattern of pain-relevant genes is accessible via next-generation sequencing, although the analysis of all "pain genes" would be expensive. Here, we report on the development of a cost-effective next generation sequencing-based pain-genotyping assay comprising the development of a customized AmpliSeq™ panel and bioinformatics approaches that condensate the genetic information of pain by identifying the most representative genes. The panel includes 29 key genes that have been shown to cover 70% of the biological functions exerted by a list of 540 so-called "pain genes" derived from transgenic mice experiments. These were supplemented by 43 additional genes that had been independently proposed as relevant for persistent pain. The functional genomics covered by the resulting 72 genes is particularly represented by mitogen-activated protein kinase of extracellular signal-regulated kinase and cytokine production and secretion. The present genotyping assay was established in 61 subjects of Caucasian ethnicity and investigates the functional role of the selected genes in the context of the known genetic architecture of pain without seeking functional associations for pain. The assay identified a total of 691 genetic variants, of which many have reports for a clinical relevance for pain or in another context. The assay is applicable for small to large-scale experimental setups at contemporary genotyping costs.

A Conceptual Model of Biopsychosocial Mechanisms of Transition from Acute to Chronic Postsurgical Pain in Children and Adolescents

Acute and chronic pain are highly prevalent and impactful consequences of surgery across the lifespan, yet a comprehensive conceptual model encompassing biopsychosocial factors underlying acute to chronic pain transition is lacking, particularly in youth. Building on prior chronic postsurgical pain models, we propose a new conceptual model of biopsychosocial mechanisms of transition from acute to chronic postsurgical pain. This review aims to summarize existing research examining key factors underlying acute to chronic postsurgical pain transition in order to guide prevention and intervention efforts aimed at addressing this health issue in children. As pain transitions from acute nociceptive pain to chronic pain, changes in the peripheral and central nervous system contribute to the chronification of pain after surgery. These changes include alterations in sensory pain processing and psychosocial processes (psychological, behavioral, and social components), which promote the development of chronic pain. Patient-related premorbid factors (eg, demographic factors, genetic profile, and medical factors such as premorbid pain) may further modulate these changes. Factors related to acute injury and recovery (eg, surgical and treatment factors), as well as biological response to surgery (eg, epigenetic, inflammatory, and endocrine factors), may also influence this process. Overall, longitudinal studies examining temporal pathways of biopsychosocial processes including both risk and resiliency factors will be essential to identify the mechanisms involved in the transition from acute to chronic pain. Research is also needed to unravel connections between the acute pain experience, opioid exposure, and sensory pain processing during acute to chronic pain transition. Furthermore, future studies should include larger and more diverse samples to more fully explore risk factors in a broader range of pediatric surgeries. The use of conceptual models to guide intervention approaches targeting mechanisms of transition from acute to chronic pain will significantly advance this field and improve outcomes for children and adolescents undergoing surgery.

COMT rs4818, pain sensitivity and duration, and alveolar bone grafting of oral clefts

PURPOSE

Verifying whether the mutation in COMT rs4818 could be involved in pain modulation.

METHODS

Thirty-two individuals born with cleft lip and palate that underwent bone graft from the iliac crest bone were assessed at 12, 24, 48, 72 h, and 7 days regarding their pain experience using a visual analogic scale. DNA from each participant was collected from saliva samples, and genotyping of rs4818 was performed using TaqMan chemistry. Overrepresentation of rs4818 alleles was tested using chi-square or Fisher's exact tests with an alpha of 0.05.

RESULTS

Of the 32 individuals, eighteen reported long pain duration, nine reported high pain intensity, and fourteen low pain intensity up to 48 h. No differences were found in the distribution of individuals depending on the reported pain by sex (p = 0.12), age (p = 0.42), or cleft type (p = 0.5). The distribution of COMT r4818 alleles was different depending on the intensity and duration of pain. Carriers of the C wild-type allele were four times more likely to show high pain intensity and duration (odds ratio = 4.29, 95% confidence interval 1.13-16.18), meaning that the G variant allele is protective.

CONCLUSION

COMT rs4818 is associated with postoperative pain after alveolar bone grafting.

Polygenic risk scores indicates genetic overlap between peripheral pain syndromes and chronic postsurgical pain

Chronic postsurgical pain (CPSP) is a debilitating chronic pain condition that has a substantial effect on quality of life. CPSP shows considerable clinical overlap with different chronic peripheral pain syndromes, suggesting a shared aetiology. This study aims to assess the genetic overlap between different chronic pain syndromes and CPSP, providing relevant biological context for potential chronic pain markers of CPSP. To analyse the genetic overlap between CPSP and chronic peripheral pain syndromes, recent GWAS studies were combined for polygenic risk scores (PRS) analysis, using a cohort of CPSP patients as starting point. Biological contextualisation of genetic marker, overlap between CPSP and chronic pain syndromes, was assessed through Gene Ontology (GO), using Pathway Scoring Algorithm (PASCAL) and REVIGO. PRS analyses suggest a significant genetic overlap between CPSP and 3 chronic pain disorders: chronic widespread pain (CWP, p value threshold = 0.003, R2 0.06, p = 0.003), rheumatoid arthritis (RA, p value threshold = 0.0177, R2 = 0.04, p = 0.017) and possibly sciatica (p value threshold = 0.00025, R2 = 0.03, p = 0.045). Whereas no significant genetic overlap was found with cluster headache and migraine, the outcome for osteoarthritis (OA) was inconsistent between the cohorts. This is likely related to cohort composition, as repeated random reallocation of patients' nullified CPSP/OA outcome variation between the discovery and replication cohorts. GO analyses suggested an aetiological involvement of genetic markers that control neurological signalling (specifically sodium channels) and inflammatory response. The current study reaffirms the impact of sample size, cohort composition and open data accessibility on the unbiased identification of genetic overlap across disorders. In conclusion, this study is the first to report genetic overlap between regulatory processes implicated in CPSP and chronic peripheral pain syndromes. Interaction between neurological signalling and inflammatory response may explain the genetic overlap between CPSP, CWP and RA. Enhanced understanding of mechanisms underlying chronification of pain will aid the development of new therapeutic strategies for CPSP with sodium channel biochemistry as a potential candidate.