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

Decomposing the genetic background of chronic back pain

Chronic back pain (CBP) is a disabling condition with a lifetime prevalence of 40% and a substantial socioeconomic burden. Because of the high heterogeneity of CBP, subphenotyping may help to improve prediction and support personalized treatment of CBP. To investigate CBP subphenotypes, we decomposed its genetic background into a shared one common to other chronic pain conditions (back, neck, hip, knee, stomach, and head pain) and unshared genetic background specific to CBP. We identified and replicated 18 genes with shared impact across different chronic pain conditions and two genes that were specific for CBP. Among people with CBP, we demonstrated that polygenic risk scores accounting for the shared and unshared genetic backgrounds of CBP may underpin different CBP subphenotypes. These subphenotypes are characterized by varying genetic predisposition to diverse medical conditions and interventions such as diabetes mellitus, myocardial infarction, diagnostic endoscopic procedures, and surgery involving muscles, bones, and joints.

Knowledge of the genetics of human pain gained over the last decade from next-generation sequencing

Next-generation sequencing (NGS) technologies have revolutionized pain research by providing comprehensive insights into genetic variation across the genome. Recent studies have expanded the known spectrum of mutations in genes such as SCN9A and NTRK1, which are commonly mutated in hereditary sensory neuropathies. NGS has uncovered critical alternative splicing events and facilitated single-cell transcriptomics, revealing cellular heterogeneity within tissues. An NGS-based classifier predicted extremely high opioid requirements with 80 % accuracy, highlighting the importance of tailoring opioid therapy based on genetic profiles. Key genes such as GDF5, COL11A1, and TRPV1 have been linked to osteoarthritis risk and pain sensitivity, while HLA-DRB1, TNF, and P2X7 play critical roles in inflammation and pain modulation in rheumatoid arthritis. Innovative tools, such as an atlas of the somatosensory system in neuropathic pain, have been developed based on NGS data, focusing on the dorsal root and trigeminal ganglia. This approach allows the analysis of cellular changes during the development of chronic pain. In the study of rare variants, NGS outperforms single nucleotide variant candidate studies and classical genome-wide association approaches. The complex data generated by NGS enables integrated multi-omics approaches, allowing deeper exploration of the molecular and cellular basis of pain perception. In addition, the characterization of non-coding RNAs has opened new therapeutic avenues. NGS-based pain research faces challenges related to complex data analysis and interpretation of rare genetic variants with unknown biological functions. Nevertheless, NGS offers significant potential for improving personalized pain management and highlights the need for interdisciplinary collaboration to translate findings into clinical practice.

Single-cell characterization of the human C2 dorsal root ganglion recovered from C1-2 arthrodesis surgery: implications for neck pain

Neurons in the dorsal root ganglion (DRG) receive and transmit sensory information from the tissues they innervate and from the external environment. Upper cervical (C1-C2) DRGs are functionally unique as they receive input from the neck, head, and occipital cranial dura, the latter two of which are also innervated by the trigeminal ganglion (TG). The C2 DRG also plays an important role in neck pain, a common and disabling disorder that is poorly understood. Advanced transcriptomic approaches have significantly improved our ability to characterize RNA expression patterns at single-cell resolution in the DRG and TG, but no previous studies have characterized the C2 DRG. Our aim was to use single-nucleus and spatial transcriptomic approaches to create a molecular map of C2 DRGs from patients undergoing arthrodesis surgery with ganglionectomy. Patients with acute (<3 months) or chronic (≥3 months) neck pain were enrolled and completed patient-reported outcomes and quantitative sensory testing prior to surgery. C2 DRGs were characterized with bulk, single nucleus, and spatial RNA sequencing technologies from 22 patients. Through a comparative analysis to published datasets of the lumbar DRG and TG, neuronal clusters identified in both TG and DRG were identified in the C2 DRG. Therefore, our study definitively characterizes the molecular composition of human C2 neurons and establishes their similarity with unique characteristics of subsets of TG neurons. We identified differentially expressed genes in endothelial, fibroblast and myelinating Schwann cells associated with chronic pain, including FGFBP2, C8orf34 and EFNA1 which have been identified in previous genome and transcriptome wide association studies (GWAS/TWAS). Our work establishes an atlas of the human C2 DRG and identifies altered gene expression patterns associated with chronic neck pain. This work establishes a foundation for the exploration of painful disorders in humans affecting the cervical spine.

Introduction to Special Issue: Genomic Analysis of Common Disease

The development of NextGen or massive parallel sequencing [...].

Clinical and omics biomarkers in osteoarthritis diagnosis and treatment

Osteoarthritis (OA) is a prevalent degenerative joint disease that significantly impacts the quality of life for hundreds of millions, and is a major cause of disability. Despite this, diagnostic and therapeutic options for OA are still limited. With advances in molecular biology, an increasing number of OA biomarkers have been identified, which not only enhances our understanding of OA pathogenesis, but also offers new approaches for OA diagnosis and treatment. This review discussed the research progress on traditional OA biomarkers, and analyzed the application of various omics, including genomics, transcriptomics, proteomics, and metabolomics, in the diagnosis and treatment of OA. Furthermore, we explored how integrating multi-omics methods can reveal interactions among different biomolecules and their roles in the development of OA. This emerging interdisciplinary approach not only provides a more comprehensive understanding of the fundamental biological characteristics of OA, but also aids in identifying new integrated biomarkers, thereby allowing for more accurate predictions of disease progression and treatment responses. The identification and development of biomarkers offer new perspectives in understanding OA, enhancing the specificity and sensitivity of biological diagnostic markers, providing a basis for the design of targeted drugs, and ultimately advancing the development of precision diagnosis and treatment strategies in clinical OA. This study provides an overview of both commonly used and emerging biomarkers of OA which is beneficial for a more accurate, timely, effective clinical diagnosis and treatment for OA.

Identifying methamphetamine use predictors in HIV infection: Immune-dopaminergic signatures in peripheral leukocytes and the role of COMT genotype

The pursuit of translational biomarkers is complex due to the heterogeneous human pathophysiology, but critical for disease diagnosis, prognosis, monitoring therapeutic efficacy, and for patient stratification. In HIV-associated neurocognitive impairment (NCI), biomarkers that delineate the trajectory of neuropathogenesis and neurocognitive sequelae are critical, particularly considering confounders such as substance use, including Methamphetamine (METH). METH use is a significant health concern among persons living with HIV (PWH), aggravating cognitive deficits and neuroinflammation despite of antiretrovirals, introducing elements in the microenvironment that are fundamentally differerent in relation to non-METH users, such as high levels of dopamine (DA) affecting HIV-innate immune targets. Yet, current biomarkers do not detect these differences. We hypothesized that predefined DA-induced signatures detectable in peripheral blood leukocytes, can distinguish HIV+ METH users compared to HIV-negative or PWH that are non METH users. The elevated expression of CD8A, CREBBP, CCL5, and combinations of dopaminergic pathway transcripts clustered METH users with detectable CSF viral load and major depressive disorder (MDD), indicating neuroimmune-mechanistic links. Cathecol-o-methyltransferase (COMT) gene polymorphisms affecting DA metabolism improved the identification of PWH using METH with biomarkers. The results indicate that underlying immunedopaminergic mechanisms provide signatures and genotypes that can identify PWH that are METH users and their attributes.

Spatial, transcriptomic, and epigenomic analyses link dorsal horn neurons to chronic pain genetic predisposition

Key mechanisms underlying chronic pain occur within the dorsal horn. Genome-wide association studies (GWASs) have identified genetic variants predisposed to chronic pain. However, most of these variants lie within regulatory non-coding regions that have not been linked to spinal cord biology. Here, we take a multi-species approach to determine whether chronic pain variants impact the regulatory genomics of dorsal horn neurons. First, we generate a large rhesus macaque single-nucleus RNA sequencing (snRNA-seq) atlas and integrate it with available human and mouse datasets to produce a single unified, species-conserved atlas of neuron subtypes. Cellular-resolution spatial transcriptomics in mouse shows the precise laminar location of these neuron subtypes, consistent with our analysis of neuron-subtype-selective markers in macaque. Using this cross-species framework, we generate a mouse single-nucleus open chromatin atlas of regulatory elements that shows strong and selective relationships between the neuron-subtype-specific chromatin regions and variants from major chronic pain GWASs.

Remifentanil-induced hyperalgesia in healthy volunteers: a systematic review and meta-analysis of randomized controlled trials

ABSTRACT

Recent literature suggests that the withdrawal of remifentanil (RF) infusion can be associated with hyperalgesia in clinical and nonclinical settings. We performed a systematic review and a meta-analysis of randomized controlled trials with cross-over design, to assess the effect of discontinuing RF infusion on pain intensity and areas of hyperalgesia and allodynia in healthy volunteers. Nine studies were included. The intervention treatment consisted in RF infusion that was compared with placebo (saline solution). The primary outcome was pain intensity assessment at 30 ± 15 minutes after RF or placebo discontinuation, assessed by any pain scale and using any quantitative sensory testing. Moreover, postwithdrawal pain scores were compared with baseline scores in each treatment. Secondary outcomes included the areas (% of basal values) of hyperalgesia and allodynia. Subjects during RF treatment reported higher pain scores after discontinuation than during treatment with placebo [standardized mean difference (SMD): 0.50, 95% confidence interval (CI): 0.03-0.97; P = 0.04, I 2 = 71%]. A significant decrease in pain scores, compared with baseline values, was found in the placebo treatment (SMD: -0.87, 95% CI: -1.61 to -0.13; P = 0.02, I 2 = 87%), but not in the RF treatment (SMD: -0.28, 95% CI: -1.18 to 0.62; P = 0.54, I 2 = 91%). The area of hyperalgesia was larger after RF withdrawal (SMD: 0.55; 95% CI: 0.27-0.84; P = 0.001; I 2 = 0%). The area of allodynia did not vary between treatments. These findings suggest that the withdrawal of RF induces a mild but nonclinically relevant degree of hyperalgesia in HVs, likely linked to a reduced pain threshold.

Can we achieve pain stratification in musculoskeletal conditions? Implications for clinical practice

In the last few years there has been an increased appreciation that pain perception in rheumatic and musculoskeletal diseases (RMDs) has several mechanisms which include nociceptive, inflammatory, nociplastic and neuropathic components. Studies in specific patient groups have also demonstrated that the pain experienced by people with specific diagnoses can present with distinctive components over time. For example, the pain observed in rheumatoid arthritis has been widely accepted to be caused by the activation of nociceptors, potentiated by the release of inflammatory mediators, including prostaglandins, leukotrienes and cytokine networks in the joint environment. However, people with RA may also experience nociplastic and neuropathic pain components, particularly when treatments with disease modifying anti-rheumatic drugs (DMARDs) have been implemented and are insufficient to control pain symptoms. In other RMDs, the concept of pain sensitisation or nociplastic pain in driving ongoing pain symptoms e.g. osteoarthritis and fibromyalgia, is becoming increasingly recognised. In this review, we explore the hypothesis that pain has distinct modalities based on clinical, pathophysiological, imaging and genetic factors. The concept of pain stratification in RMD is explored and implications for future management are also discussed.