What is associated with painful polyneuropathy? A cross-sectional analysis of symptoms and signs in patients with painful and painless polyneuropathy.

ABSTRACT: It is still unclear how and why some patients develop painful and others painless polyneuropathy. The aim of this study was to identify multiple factors associated with painful polyneuropathies (NeuP). A total of 1181 patients of the multicenter DOLORISK database with painful (probable or definite NeuP) or painless (unlikely NeuP) probable or confirmed neuropathy were investigated clinically, with questionnaires and quantitative sensory testing. Multivariate logistic regression including all variables (demographics, medical history, psychological symptoms, personality items, pain-related worrying, life-style factors, as well as results from clinical examination and quantitative sensory testing) and machine learning was used for the identification of predictors and final risk prediction of painful neuropathy. Multivariate logistic regression demonstrated that severity and idiopathic etiology of neuropathy, presence of chronic pain in family, Patient-Reported Outcomes Measurement Information System Fatigue and Depression T-Score, as well as Pain Catastrophizing Scale total score are the most important features associated with the presence of pain in neuropathy. Machine learning (random forest) identified the same variables. Multivariate logistic regression archived an accuracy above 78%, random forest of 76%; thus, almost 4 out of 5 subjects can be classified correctly. This multicenter analysis shows that pain-related worrying, emotional well-being, and clinical phenotype are factors associated with painful (vs painless) neuropathy. Results may help in the future to identify patients at risk of developing painful neuropathy and identify consequences of pain in longitudinal studies.

Prevalence of weakness and factors mediating discrepancy between reported and observed leg weakness in people with sciatica.

PURPOSE: To establish the prevalence and agreement between reported and observed leg weakness in people with sciatica. To establish which factors mediate any identified difference between reported and observed leg weakness in people with sciatica. METHODS: 68 people with a clinical diagnosis of sciatica, records from spinal service, secondary care NHS Hospital, England, UK reviewed. Primary outcome measures were the sciatica bothersome index for reported leg weakness and the Medical Research Council scale for observed weakness. Agreement was established with Cohen's Kappa and intraclass correlation coefficient. Potential factors that may mediate a difference between reported and observed weakness included leg pain, sciatica bothersome index sensory subscale, age, hospital anxiety and depression subscale for anxiety. RESULTS: 85% of patients reported weakness but only 34% had observed weakness. Cohen's Kappa (0.066, 95% CI - 0.53, 0.186; p = 0.317)] and ICC 0.213 (95% CI - 0.26, 0.428, p = 0.040) both showed poor agreement between reported and observed weakness. The difference between reported and observed measures of weakness was mediated by the severity of leg pain (b = 0.281, p = 0.024) and age (b = 0.253, p = 0.042). CONCLUSION: There is a high prevalence of reported leg weakness in people with sciatica, which is not reflected in observed clinical measures of weakness. Differences between reported and observed weakness may be driven by the severity of leg pain and age. Further work needs to establish whether other objective measures can detect patient reported weakness.

Reliability of a clinical sensory test battery in patients with spine-related leg and arm pain.

BACKGROUND: The current standard to evaluate the presence of somatosensory dysfunctions is quantitative sensory testing, but its clinical utility remains limited. Low-cost and time-efficient clinical sensory testing (CST) batteries have thus been developed. Recent studies show moderate to substantial reliability in populations with neuropathic pain. This study evaluates the inter- and intra-tester reliability of people with spine-related leg and arm pain, representing mixed pain mechanisms. METHODS: Fifty-three patients with spine-related leg (n = 41) and arm pain (n = 12) attended three CST sessions. The CST battery consisted of eleven tests, determining loss and gain of sensory nerve function. CST was performed by the same investigator twice and by an additional investigator to determine inter- and intra-tester reliability. Fleiss' (inter-tester) and Cohen's (intra-tester) kappa were calculated for dichotomized and intraclass correlation coefficients (ICC) for continuous outcomes. RESULTS: Fleiss' kappa varied among modalities from fair to substantial (κ = 0.23-0.66). Cold, warm, and vibration detection thresholds and cold and pressure pain thresholds reached kappa >0.4 (moderate to substantial reliability). Cohen's kappa ranged from moderate to substantial (κ = 0.45-0.66). The reliability of the windup ratio was poor (ICC <0.18). CONCLUSION: CST modalities with moderate to substantial inter-tester reliability could be of benefit as a screening tool. The moderate to substantial intra-tester reliability for all sensory modalities (except windup ratio) supports their potential use in clinical practice and research to monitor somatosensory changes over time in patients with spine-related limb pain of mixed pain mechanisms. SIGNIFICANCE: We already know that most modalities of clinical sensory test (CST) batteries achieve moderate to substantial inter- and intra-tester reliability in populations with neuropathic pain. This study evaluates the reliability of a CST battery in populations with mixed pain mechanisms. We found inter-tester reliability varied from poor to substantial for sensory modalities, questioning the value of some CST modalities. The CST battery showed moderate to substantial intra-tester reliability, suggesting its usefulness to monitor sensory changes over time in this cohort.

Introduction to a special issue on big data and pain.

This special issue comprised 7 articles from leaders in the field that focus on "big pain data", the large datasets and the associated methods for data analysis that are currently emerging in pain research. This collection of articles highlights the power and potential as well as points of caution that multi-disciplinary research utilising big data and their associated methods and interpretations present for pain research.

Deep RNA-seq of male and female murine sensory neuron subtypes after nerve injury.

ABSTRACT: Dorsal root ganglia (DRG) neurons have been well described for their role in driving both acute and chronic pain. Although nerve injury is known to cause transcriptional dysregulation, how this differs across neuronal subtypes and the impact of sex is unclear. Here, we study the deep transcriptional profiles of multiple murine DRG populations in early and late pain states while considering sex. We have exploited currently available transgenics to label numerous subpopulations for fluorescent-activated cell sorting and subsequent transcriptomic analysis. Using bulk tissue samples, we are able to circumvent the issues of low transcript coverage and drop-outs seen with single-cell data sets. This increases our power to detect novel and even subtle changes in gene expression within neuronal subtypes and discuss sexual dimorphism at the neuronal subtype level. We have curated this resource into an accessible database for other researchers ( https://livedataoxford.shinyapps.io/drg-directory/ ). We see both stereotyped and unique subtype signatures in injured states after nerve injury at both an early and late timepoint. Although all populations contribute to a general injury signature, subtype enrichment changes can also be seen. Within populations, there is not a strong intersection of sex and injury, but previously unknown sex differences in naïve states-particularly in Aß-RA + Aδ-low threshold mechanoreceptors-still contribute to differences in injured neurons.

Utilising clinical parameters to improve the selection of nerve biopsy candidates.

BACKGROUND: Peripheral nerve biopsy is a valuable final diagnostic tool; however, histopathological results can be non-diagnostic. AIMS: We aim to identify quality improvement measures by evaluating the pre-biopsy assessment and diagnostic yield of specific histopathological diagnosis. METHODS: This was a retrospective study based on 10 years of experience with peripheral nerve biopsies at a single centre. Clinical data were obtained regarding pre-biopsy history, examination, serum and cerebrospinal fluid (CSF) investigations, neurophysiology and peripheral nerve imaging. Based upon a histopathological outcome, patients were grouped into vasculitis, granulomatous and infiltrative (diagnostic) group, or a comparison group of non-specific axonal neuropathy and normal (non-specific/normal) group. RESULTS: From a cohort of 64 patients, 21 (32.8%) were included in the diagnostic group and 30 (46.9%) in the non-specific/normal group. Clinical parameters associated with the diagnostic group were shorter history (mean 10.2 months vs 38.1), stepwise progression (81% vs 20%), neuropathic pain (85.7% vs 56.7%), vasculitic rash (23.8% vs 0%), mononeuritis multiplex (57.1% vs 10%), asymmetry (90.5% vs 60%), raised white cell count (47.6% vs 16.7%), myeloperoxidase antibody (19.1% vs 0%) and abnormal peripheral nerve imaging (33.3% vs 10%). CONCLUSION: Selection of patients undergoing nerve biopsy requires careful consideration of clinical parameters, including peripheral nerve imaging. Several quality improvement measures are proposed to improve yield of clinically actionable information from nerve biopsy.

Factors predicting the transition from acute to persistent pain in people with 'sciatica': the FORECAST longitudinal prognostic factor cohort study protocol.

INTRODUCTION: Sciatica is a common condition and is associated with higher levels of pain, disability, poorer quality of life, and increased use of health resources compared with low back pain alone. Although many patients recover, a third develop persistent sciatica symptoms. It remains unclear, why some patients develop persistent sciatica as none of the traditionally considered clinical parameters (eg, symptom severity, routine MRI) are consistent prognostic factors.The FORECAST study (factors predicting the transition from acute to persistent pain in people with 'sciatica') will take a different approach by exploring mechanism-based subgroups in patients with sciatica and investigate whether a mechanism-based approach can identify factors that predict pain persistence in patients with sciatica. METHODS AND ANALYSIS: We will perform a prospective longitudinal cohort study including 180 people with acute/subacute sciatica. N=168 healthy participants will provide normative data. A detailed set of variables will be assessed within 3 months after sciatica onset. This will include self-reported sensory and psychosocial profiles, quantitative sensory testing, blood inflammatory markers and advanced neuroimaging. We will determine outcome with the Sciatica Bothersomeness Index and a Numerical Pain Rating Scale for leg pain severity at 3 and 12 months.We will use principal component analysis followed by clustering methods to identify subgroups. Univariate associations and machine learning methods optimised for high dimensional small data sets will be used to identify the most powerful predictors and model selection/accuracy.The results will provide crucial information about the pathophysiological drivers of sciatica symptoms and may identify prognostic factors of pain persistence. ETHICS AND DISSEMINATION: The FORECAST study has received ethical approval (South Central Oxford C, 18/SC/0263). The dissemination strategy will be guided by our patient and public engagement activities and will include peer-reviewed publications, conference presentations, social media and podcasts. TRIAL REGISTRATION NUMBER: ISRCTN18170726; Pre-results.

Investigating genotype-phenotype relationship of extreme neuropathic pain disorders in a UK national cohort.

The aims of our study were to use whole genome sequencing in a cross-sectional cohort of patients to identify new variants in genes implicated in neuropathic pain, to determine the prevalence of known pathogenic variants and to understand the relationship between pathogenic variants and clinical presentation. Patients with extreme neuropathic pain phenotypes (both sensory loss and gain) were recruited from secondary care clinics in the UK and underwent whole genome sequencing as part of the National Institute for Health and Care Research Bioresource Rare Diseases project. A multidisciplinary team assessed the pathogenicity of rare variants in genes previously known to cause neuropathic pain disorders and exploratory analysis of research candidate genes was completed. Association testing for genes carrying rare variants was completed using the gene-wise approach of the combined burden and variance-component test SKAT-O. Patch clamp analysis was performed on transfected HEK293T cells for research candidate variants of genes encoding ion channels. The results include the following: (i) Medically actionable variants were found in 12% of study participants (205 recruited), including known pathogenic variants: SCN9A(ENST00000409672.1): c.2544T>C, p.Ile848Thr that causes inherited erythromelalgia, and SPTLC1(ENST00000262554.2):c.340T>G, p.Cys133Tr variant that causes hereditary sensory neuropathy type-1. (ii) Clinically relevant variants were most common in voltage-gated sodium channels (Nav). (iii) SCN9A(ENST00000409672.1):c.554G>A, pArg185His variant was more common in non-freezing cold injury participants than controls and causes a gain of function of NaV1.7 after cooling (the environmental trigger for non-freezing cold injury). (iv) Rare variant association testing showed a significant difference in distribution for genes NGF, KIF1A, SCN8A, TRPM8, KIF1A, TRPA1 and the regulatory regions of genes SCN11A, FLVCR1, KIF1A and SCN9A between European participants with neuropathic pain and controls. (v) The TRPA1(ENST00000262209.4):c.515C>T, p.Ala172Val variant identified in participants with episodic somatic pain disorder demonstrated gain-of-channel function to agonist stimulation. Whole genome sequencing identified clinically relevant variants in over 10% of participants with extreme neuropathic pain phenotypes. The majority of these variants were found in ion channels. Combining genetic analysis with functional validation can lead to a better understanding as to how rare variants in ion channels lead to sensory neuron hyper-excitability, and how cold, as an environmental trigger, interacts with the gain-of-function NaV1.7 p.Arg185His variant. Our findings highlight the role of ion channel variants in the pathogenesis of extreme neuropathic pain disorders, likely mediated through changes in sensory neuron excitability and interaction with environmental triggers.

Development and external validation of multivariable risk models to predict incident and resolved neuropathic pain: a DOLORisk Dundee study.

Neuropathic pain is difficult to treat, and an understanding of the risk factors for its onset and resolution is warranted. This study aimed to develop and externally validate two clinical risk models to predict onset and resolution of chronic neuropathic pain. Participants of Generation Scotland: Scottish Family Health Study (GS; general Scottish population; n = 20,221) and Genetic of Diabetes Audit and Research in Tayside Scotland (GoDARTS; n = 5236) were sent a questionnaire on neuropathic pain and followed- -up 18 months later. Chronic neuropathic pain was defined using DN4 scores (≥ 3/7) and pain for 3 months or more. The models were developed in GS using logistic regression with backward elimination based on the Akaike information criterion. External validation was conducted in GoDARTS and assessed model discrimination (ROC and Precision-Recall curves), calibration and clinical utility (decision curve analysis [DCA]). Analysis revealed incidences of neuropathic pain onset (6.0% in GS [236/3903] and 10.7% in GoDARTS [61/571]) and resolution (42.6% in GS [230/540] and 23.7% in GoDARTS [56/236]). Psychosocial and lifestyle factors were included in both onset and resolved prediction models. In GoDARTS, these models showed adequate discrimination (ROC = 0.636 and 0.699), but there was evidence of miscalibration (Intercept = - 0.511 and - 0.424; slope = 0.623 and 0.999). The DCA indicated that the models would provide clinical benefit over a range of possible risk thresholds. To our knowledge, these are the first externally validated risk models for neuropathic pain. The findings are of interest to patients and clinicians in the community, who may take preventative or remedial measures.

Types and Concentrations of Blood-Based Biomarkers in Adults With Peripheral Neuropathies: A Systematic Review and Meta-analysis.

Importance: Peripheral neuropathies are common conditions and can result in numbness, paresthesia, motor deficits, and pain. There is increasing evidence for the use of biomarkers as clinical indicators of the presence, severity, and prognosis of nerve lesions; however, biomarker identification has largely been focused on disorders of the central nervous system, and less is known about their role in the peripheral nervous system. Objective: To assess blood-based biomarker concentrations associated with nerve involvement in patients with peripheral neuropathy compared with control participants. Data Sources: Ovid, MEDLINE, Embase, and CINAHL were searched from inception to September 23, 2021. Study Selection: Observational studies reporting on blood biomarkers in patients diagnosed with peripheral neuropathy were included. This review was preregistered on PROSPERO and followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Data were abstracted by 1 investigator and independently reviewed by a second. Data Extraction and Synthesis: Data were meta-analyzed when at least 2 studies reported the same biomarker with comparable methodology. Fixed-effects models were used when only 2 studies were included; random-effects models were used when more than 2 studies were included. Main Outcomes and Measures: The outcome of interest was concentration of biomarkers. Results: This review included 36 studies reporting on 4414 participants, including 2113 control participants and 2301 patients with peripheral neuropathy with 13 distinct peripheral neuropathy diagnoses. Diabetic neuropathy was the most common neuropathy diagnosis (13 studies), followed by Charcot-Marie-Tooth disease (6 studies) and Guillain-Barre syndrome (6 studies). Overall, 16 different blood-based biomarkers associated with nerve involvement were evaluated. The most used were neurofilament light chain, S100B, brain-derived neurotrophic factor, and neuron-specific enolase. Patients with peripheral neuropathy demonstrated significantly higher levels of neurofilament light chain compared with controls (standardized mean difference [SMD], 0.93 [95% CI, 0.82 to 1.05]; P < .001). There were no significant differences in levels of S100B (SMD, 1.10 [95% CI, -3.08 to 5.28]; P = .38), brain-derived neurotrophic factor (SMD, -0.52 [95% CI, -2.23 to 1.19]; P = .40), or neuron-specific enolase (SMD, -0.00 [95% CI, -1.99 to 1.98]; P = .10) in patients with peripheral neuropathy compared with control participants. Conclusions and Relevance: The findings of this systematic review and meta-analysis support the use of neurofilament light chain as a blood-based measure associated with the presence of neuronal injury in patients with peripheral neuropathy.

Cutaneous expression of growth-associated protein 43 is not a compelling marker for human nerve regeneration in carpal tunnel syndrome.

Growth-associated protein 43 (GAP-43) has long been used as a marker for nerve regeneration following nerve injury, with numerous in vitro and animal studies showing its upregulation in regenerating neurons. In humans, expression of GAP-43 has predominantly been examined in skin biopsies from patients with peripheral neuropathies; with several studies showing a reduction in GAP-43 immunoreactive cutaneous nerve fibres. However, it remains elusive whether cutaneous GAP-43 is a valid marker for human nerve regeneration. Here, we present a cohort of 22 patients with electrodiagnostically confirmed carpal tunnel syndrome (CTS), used as a model system for focal nerve injury and neural regeneration after decompression surgery. We evaluate GAP-43 immunoreactivity and RNA expression levels in finger skin biopsies taken before and 6 months after surgery, relative to healthy controls. We further classify patients as 'regenerators' or 'non-regenerators' based on post-surgical epidermal re-innervation. We demonstrate that patients with CTS have lower GAP-43 positive intra-epidermal nerve fibre density (IENFD) before surgery than healthy controls. However, this difference disappears when normalising for total IENFD. Of note, we found surgery did not change GAP-43 expression in IENF, with no differences both in patients who were classified as regenerators and non-regenerators. We also did not identify pre-post surgical differences in cutaneous GAP-43 gene expression or associations with regeneration. These findings suggest cutaneous GAP-43 may not be a compelling marker for nerve regeneration in humans.

The power of integrating data: advancing pain research using meta-analysis.

Publications related to pain research have increased significantly in recent years. The abundance of new evidence creates challenges staying up to date with the latest information. A comprehensive understanding of the literature is important for both clinicians and investigators involved in pain research. One commonly used method to combine and analyse data in health care research is meta-analysis. The primary aim of a meta-analysis is to quantitatively synthesise the results of multiple studies focused on the same research question. Meta-analysis is a powerful tool that can be used to advance pain research. However, there are inherent challenges when combining data from multiple sources. There are also numerous models and statistical considerations when undertaking a meta-analysis. This review aims to discuss the planning and preparation for completing a meta-analysis, review commonly used meta-analysis models, and evaluate the clinical implications of meta-analysis in pain research.

Shared genetic susceptibility between trigger finger and carpal tunnel syndrome: a genome-wide association study.

Background: Trigger finger and carpal tunnel syndrome are the two most common non-traumatic connective tissue disorders of the hand. Both of these conditions frequently co-occur, often in patients with rheumatoid arthritis. However, this phenotypic association is poorly understood. Hypothesising that the co-occurrence of trigger finger and carpal tunnel syndrome might be explained by shared germline predisposition, we aimed to identify a specific genetic locus associated with both diseases. Methods: In this genome-wide association study (GWAS), we identified 2908 patients with trigger finger and 436579 controls from the UK Biobank prospective cohort. We conducted a case-control GWAS for trigger finger, followed by co-localisation analyses with carpal tunnel syndrome summary statistics. To identify putative causal variants and establish their biological relevance, we did fine-mapping analyses and expression quantitative trait loci (eQTL) analyses, using fibroblasts from healthy donors (n=79) and tenosynovium samples from patients with carpal tunnel syndrome (n=77). We conducted a Cox regression for time to trigger finger and carpal tunnel syndrome diagnosis against plasma IGF-1 concentrations in the UK Biobank cohort. Findings: Phenome-wide analyses confirmed a marked association between carpal tunnel syndrome and trigger finger in the participants from UK Biobank (odds ratio [OR] 11·97, 95% CI 11·1-13·0; p<1 × 10-300). GWAS for trigger finger identified five independent loci, including one locus, DIRC3, that was co-localised with carpal tunnel syndrome and could be fine-mapped to rs62175241 (0·76, 0·68-0·84; p=5·03 × 10-13). eQTL analyses found a fibroblast-specific association between the protective T allele of rs62175241 and increased DIRC3 and IGFBP5 expression. Increased plasma IGF-1 concentrations were associated with both carpal tunnel syndrome and trigger finger in participants from UK Biobank (hazard ratio >1·04, p<0·02). Interpretation: In this GWAS, the DIRC3 locus on chromosome 2 was significantly associated with both carpal tunnel syndrome and trigger finger, possibly explaining their co-occurrence. The disease-protective allele of rs62175241 was associated with increased expression of long non-coding RNA DIRC3 and its transcriptional target, IGBP5, an antagonist of IGF-1 signalling. These findings suggest a model in which IGF-1 is a driver of both carpal tunnel syndrome and trigger finger, and in which the DIRC3-IGFBP5 axis directly antagonises fibroblastic IGF-1 signalling. Funding: Wellcome Trust, National Institute for Health Research, Medical Research Council.

Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts.

BACKGROUND: To improve the treatment of painful Diabetic Peripheral Neuropathy (DPN) and associated co-morbidities, a better understanding of the pathophysiology and risk factors for painful DPN is required. Using harmonised cohorts (N = 1230) we have built models that classify painful versus painless DPN using quality of life (EQ5D), lifestyle (smoking, alcohol consumption), demographics (age, gender), personality and psychology traits (anxiety, depression, personality traits), biochemical (HbA1c) and clinical variables (BMI, hospital stay and trauma at young age) as predictors. METHODS: The Random Forest, Adaptive Regression Splines and Naive Bayes machine learning models were trained for classifying painful/painless DPN. Their performance was estimated using cross-validation in large cross-sectional cohorts (N = 935) and externally validated in a large population-based cohort (N = 295). Variables were ranked for importance using model specific metrics and marginal effects of predictors were aggregated and assessed at the global level. Model selection was carried out using the Mathews Correlation Coefficient (MCC) and model performance was quantified in the validation set using MCC, the area under the precision/recall curve (AUPRC) and accuracy. RESULTS: Random Forest (MCC = 0.28, AUPRC = 0.76) and Adaptive Regression Splines (MCC = 0.29, AUPRC = 0.77) were the best performing models and showed the smallest reduction in performance between the training and validation dataset. EQ5D index, the 10-item personality dimensions, HbA1c, Depression and Anxiety t-scores, age and Body Mass Index were consistently amongst the most powerful predictors in classifying painful vs painless DPN. CONCLUSIONS: Machine learning models trained on large cross-sectional cohorts were able to accurately classify painful or painless DPN on an independent population-based dataset. Painful DPN is associated with more depression, anxiety and certain personality traits. It is also associated with poorer self-reported quality of life, younger age, poor glucose control and high Body Mass Index (BMI). The models showed good performance in realistic conditions in the presence of missing values and noisy datasets. These models can be used either in the clinical context to assist patient stratification based on the risk of painful DPN or return broad risk categories based on user input. Model's performance and calibration suggest that in both cases they could potentially improve diagnosis and outcomes by changing modifiable factors like BMI and HbA1c control and institute earlier preventive or supportive measures like psychological interventions.

Nerve pathology and neuropathic pain after whiplash injury: a systematic review and meta-analysis.

ABSTRACT: There is no clear understanding of the mechanisms causing persistent pain in patients with whiplash-associated disorder (WAD). The aim of this systematic review was to assess the evidence for nerve pathology and neuropathic pain in patients with WAD. EMBASE, PubMed, CINAHL (EBSCO), and MEDLINE were searched from inception to September 1, 2020. Study quality and risk of bias were assessed using the Newcastle-Ottawa Quality Assessment Scales. Fifty-four studies reporting on 390,644 patients and 918 controls were included. Clinical questionnaires suggested symptoms of predominant neuropathic characteristic in 34% of patients (range 25%-75%). The mean prevalence of nerve pathology detected with neurological examination was 13% (0%-100%) and 32% (10%-100%) with electrodiagnostic testing. Patients independent of WAD severity (Quebec Task Force grades I-IV) demonstrated significantly impaired sensory detection thresholds of the index finger compared with controls, including mechanical (SMD 0.65 [0.30; 1.00] P < 0.005), current (SMD 0.82 [0.25; 1.39] P = 0.0165), cold (SMD -0.43 [-0.73; -0.13] P = 0.0204), and warm detection (SMD 0.84 [0.25; 1.42] P = 0.0200). Patients with WAD had significantly heightened nerve mechanosensitivity compared with controls on median nerve pressure pain thresholds (SMD -1.10 [-1.50; -0.70], P < 0.0001) and neurodynamic tests (SMD 1.68 [0.92; 2.44], P = 0.0004). Similar sensory dysfunction and nerve mechanosensitivity was seen in WAD grade II, which contradicts its traditional definition of absent nerve involvement. Our findings strongly suggest a subset of patients with WAD demonstrate signs of peripheral nerve pathology and neuropathic pain. Although there was heterogeneity among some studies, typical WAD classifications may need to be reconsidered and include detailed clinical assessments for nerve integrity.

Nav1.7 is required for normal C-low threshold mechanoreceptor function in humans and mice.

Patients with bi-allelic loss of function mutations in the voltage-gated sodium channel Nav1.7 present with congenital insensitivity to pain (CIP), whilst low threshold mechanosensation is reportedly normal. Using psychophysics (n = 6 CIP participants and n = 86 healthy controls) and facial electromyography (n = 3 CIP participants and n = 8 healthy controls), we found that these patients also have abnormalities in the encoding of affective touch, which is mediated by the specialized afferents C-low threshold mechanoreceptors (C-LTMRs). In the mouse, we found that C-LTMRs express high levels of Nav1.7. Genetic loss or selective pharmacological inhibition of Nav1.7 in C-LTMRs resulted in a significant reduction in the total sodium current density, an increased mechanical threshold and reduced sensitivity to non-noxious cooling. The behavioural consequence of loss of Nav1.7 in C-LTMRs in mice was an elevation in the von Frey mechanical threshold and less sensitivity to cooling on a thermal gradient. Nav1.7 is therefore not only essential for normal pain perception but also for normal C-LTMR function, cool sensitivity and affective touch.

Systemic inflammatory markers in neuropathic pain, nerve injury, and recovery.

ABSTRACT: The role that inflammation plays in human nerve injury and neuropathic pain is incompletely understood. Previous studies highlight the role of inflammation in the generation and maintenance of neuropathic pain, but the emerging evidence from the preclinical literature for its role in the resolution of neuropathic pain remains to be explored in humans. Here, we use carpal tunnel syndrome (CTS) as a human model system of nerve injury and neuropathic pain to determine changes in serum cytokine protein levels and gene expression levels before (active stage of disease) and after carpal tunnel decompression surgery (recovery). Fifty-five patients with CTS were studied, and 21 healthy age-matched and gender-matched participants served as controls. In the active stage of the disease (CTS before surgery vs healthy controls), PTGES2 mRNA was decreased in patients (adjusted P = 0.013), while transforming growth factor-ß and C-C motif chemokine ligand 5 protein levels were increased (adjusted P = 0.016 and P = 0.047, respectively). In the resolution phase (CTS before surgery vs after surgery), IL-9 mRNA was increased after surgery (adjusted P = 0.014) and expression of IL-6 mRNA and IL-4 protein levels were increased before surgery (adjusted P = 0.034 and P = 0.002, respectively). IL-9 mRNA expression negatively correlated with several (neuropathic) pain scores. By contrast, protein levels of IL-4 positively correlated with pain scores. In conclusion, we demonstrate specific dysregulation of systemic cytokine expression in both the active and resolution phases of nerve injury and neuropathic pain. IL-9 represents an interesting candidate associated with resolution of nerve injury and neuropathic pain.

The effectiveness of Non-pharmaceutical interventions in reducing the COVID-19 contagion in the UK, an observational and modelling study.

Epidemiological models used to inform government policies aimed to reduce the contagion of COVID-19, assume that the reproduction number is reduced through Non-Pharmaceutical Interventions (NPIs) leading to physical distancing. Available data in the UK show an increase in physical distancing before the NPIs were implemented and a fall soon after implementation. We aimed to estimate the effect of people's behaviour on the epidemic curve and the effect of NPIs taking into account this behavioural component. We have estimated the effects of confirmed daily cases on physical distancing and we used this insight to design a behavioural SEIR model (BeSEIR), simulated different scenaria regarding NPIs and compared the results to the standard SEIR. Taking into account behavioural insights improves the description of the contagion dynamics of the epidemic significantly. The BeSEIR predictions regarding the number of infections without NPIs were several orders of magnitude less than the SEIR. However, the BeSEIR prediction showed that early measures would still have an important influence in the reduction of infections. The BeSEIR model shows that even with no intervention the percentage of the cumulative infections within a year will not be enough for the epidemic to resolve due to a herd immunity effect. On the other hand, a standard SEIR model significantly overestimates the effectiveness of measures. Without taking into account the behavioural component, the epidemic is predicted to be resolved much sooner than when taking it into account and the effectiveness of measures are significantly overestimated.

An iPSC model of hereditary sensory neuropathy-1 reveals L-serine-responsive deficits in neuronal ganglioside composition and axoglial interactions.

Hereditary sensory neuropathy type 1 (HSN1) is caused by mutations in the SPTLC1 or SPTLC2 sub-units of the enzyme serine palmitoyltransferase, resulting in the production of toxic 1-deoxysphingolipid bases (DSBs). We used induced pluripotent stem cells (iPSCs) from patients with HSN1 to determine whether endogenous DSBs are neurotoxic, patho-mechanisms of toxicity and response to therapy. HSN1 iPSC-derived sensory neurons (iPSCdSNs) endogenously produce neurotoxic DSBs. Complex gangliosides, which are essential for membrane micro-domains and signaling, are reduced, and neurotrophin signaling is impaired, resulting in reduced neurite outgrowth. In HSN1 myelinating cocultures, we find a major disruption of nodal complex proteins after 8 weeks, which leads to complete myelin breakdown after 6 months. HSN1 iPSC models have, therefore, revealed that SPTLC1 mutation alters lipid metabolism, impairs the formation of complex gangliosides, and reduces axon and myelin stability. Many of these changes are prevented by l-serine supplementation, supporting its use as a rational therapy.