Neuropathic pain (NeuP) arises due to injury of the somatosensory nervous system and is both common and disabling, rendering an urgent need for non-addictive, effective new therapies. Given the high ...evolutionary conservation of pain, investigative approaches from Drosophila mutagenesis to human Mendelian genetics have aided our understanding of the maladaptive plasticity underlying NeuP. Successes include the identification of ion channel variants causing hyper-excitability and the importance of neuro-immune signaling. Recent developments encompass improved sensory phenotyping in animal models and patients, brain imaging, and electrophysiology-based pain biomarkers, the collection of large well-phenotyped population cohorts, neurons derived from patient stem cells, and high-precision CRISPR generated genetic editing. We will discuss how to harness these resources to understand the pathophysiological drivers of NeuP, define its relationship with comorbidities such as anxiety, depression, and sleep disorders, and explore how to apply these findings to the prediction, diagnosis, and treatment of NeuP in the clinic.
Calvo et al. discuss how applying genetic techniques, from model organisms to human populations, can help us understand the pathophysiology of neuropathic pain. These strategies could soon reveal novel analgesic drug targets and aid both personalized risk prediction and treatment.
Neuropathic pain (NP) is an increasingly common chronic pain state and a major health burden, affecting approximately 7% to 10% of the general population. Emerging evidence suggests that genetic ...factors could partially explain individual susceptibility to NP and the estimated heritability in twins is 37%. The aim of this study was to systematically review and summarize the studies in humans that have investigated the influence of genetic factors associated with NP. We conducted a comprehensive literature search and performed meta-analyses of all the potential genetic variants associated with NP. We reviewed 29 full-text articles and identified 28 genes that were significantly associated with NP, mainly involved in neurotransmission, immune response, and metabolism. Genetic variants in HLA genes, COMT, OPRM1, TNFA, IL6, and GCH1, were found to have an association with NP in more than one study. In the meta-analysis, polymorphisms in HLA-DRB1*13 (odds ratio OR, 2.96; confidence interval CI, 1.93-4.56), HLA-DRB1*04 (OR, 1.40; CI, 1.02-1.93), HLA-DQB1*03 (OR, 2.86; CI, 1.57-5.21), HLA-A*33 (OR, 2.32; CI, 1.42-3.80), and HLA-B*44 (OR, 3.17; CI, 2.22-4.55) were associated with significantly increased risk of developing NP, whereas HLA-A*02 (OR, 0.64; CI, 0.47-0.87) conferred reduced risk and neither rs1799971 in OPRM1 (OR, 0.55; CI, 0.27-1.11) nor rs4680 in COMT (OR, 0.95; CI, 0.81-1.13) were significantly associated with NP. These findings demonstrate an important and specific contribution of genetic factors to the risk of developing NP. However, large-scale replication studies are required to validate these candidate genes. Our review also highlights the need for genome-wide association studies with consistent case definition to elucidate the genetic architecture underpinning NP.
Gabapentinoid drugs (gabapentin and pregabalin) are effective in neuropathic pain, which has a prevalence of ∼7%. Concerns about increased prescribing have implications for patient safety, misuse, ...and diversion. Drug-related deaths (DRDs) have increased and toxicology often implicates gabapentinoids. We studied national and regional prescribing rates (2006–2016) and identified associated sociodemographic factors, co-prescriptions and mortality, including DRDs.
National data from the Information Service Division, NHS Scotland were analysed for prescribing, sociodemographic, and mortality data from the Health Informatics Centre, University of Dundee. DRDs in which gabapentinoids were implicated were identified from National Records of Scotland and Tayside Drug Death Databases.
From 2006 to 2016, the number of gabapentin prescriptions in Scotland increased 4-fold (164 630 to 694 293), and pregabalin 16-fold (27 094 to 435 490). In 2016 ‘recurrent users’ (three or more prescriptions) had mean age 58.1 yr, were mostly females (62.5%), and were more likely to live in deprived areas. Of these, 60% were co-prescribed an opioid, benzodiazepine, or both (opioid 49.9%, benzodiazepine 26.8%, both 17.1%). The age-standardised death rate in those prescribed gabapentinoids was double that in the Scottish population (relative risk 2.16, 95% confidence interval 2.08–2.25). Increases in gabapentinoids contributing to cause of DRDs were reported regionally and nationally (gabapentin 23% vs 15%; pregabalin 21% vs 7%). In Tayside, gabapentinoids were implicated in 22 (39%) of DRDs, 17 (77%) of whom had not received a prescription.
Gabapentinoid prescribing has increased dramatically since 2006, as have dangerous co-prescribing and death (including DRDs). Older people, women, and those living in deprived areas were particularly likely to receive prescriptions. Their contribution to DRDs may be more related to illegal use with diversion of prescribed medication.
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.
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.
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.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Current guidelines for perioperative management of coronavirus disease 19 (COVID-19) are mainly based on extrapolated evidence or expert opinion. We aimed to systematically investigate how COVID-19 ...affects perioperative management and clinical outcomes, to develop evidence-based guidelines.
First, we conducted a rapid literature review in EMBASE, MEDLINE, PubMed, Scopus, and Web of Science (January 1 to July 1, 2020), using a predefined protocol. Second, we performed a retrospective cohort analysis of 166 women undergoing Caesarean section at Tongji Hospital, Wuhan during the COVID-19 pandemic. Demographic, imaging, laboratory, and clinical data were obtained from electronic medical records.
The review identified 26 studies, mainly case reports/series. One large cohort reported greater mortality in elective surgery patients diagnosed after, rather than before surgery. Higher 30 day mortality was associated with emergency surgery, major surgery, poorer preoperative condition and surgery for malignancy. Regional anaesthesia was favoured in most studies and personal protective equipment (PPE) was generally used by healthcare workers (HCWs), but its use was poorly described for patients. In the retrospective cohort study, duration of surgery, oxygen therapy and hospital stay were longer in suspected or confirmed patients than negative patients, but there were no differences in neonatal outcomes. None of the 262 participating HCWs was infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) when using level 3 PPE perioperatively.
When COVID-19 is suspected, testing should be considered before non-urgent surgery. Until further evidence is available, HCWs should use level 3 PPE perioperatively for suspected or confirmed patients, but research is needed on its timing and specifications. Further research must examine longer-term outcomes.
CRD42020182891 (PROSPERO).
Headache is the most common neurological symptom and a leading cause of years lived with disability. We sought to identify the genetic variants associated with a broadly-defined headache phenotype in ...223,773 subjects from the UK Biobank cohort.
We defined headache based on a specific question answered by the UK Biobank participants. We performed a genome-wide association study of headache as a single entity, using 74,461 cases and 149,312 controls.
We identified 3343 SNPs which reached the genome-wide significance level of P<5×10−8. The SNPs were located in 28 loci, with the top SNP of rs11172113 in the LRP1 gene having a P value of 4.92×10−47. Of the 28 loci, 14 have previously been associated with migraine. Among 14 new loci, rs77804065 with a P value of 5.87×10−15 in the LINC02210-CRHR1 gene was the top SNP. Significant relationships between multiple brain tissues and genetic associations were identified through tissue expression analysis. We also identified significant positive genetic correlations between headache and many psychological traits.
Our results suggest that brain function is closely related to broadly-defined headache. In addition, we found that many psychological traits have genetic correlations with headache.
•This genome-wide association study identified 28 genomic loci for broadly-defined headache, among which, 14 are new.•Through tissue expression analysis, brain tissues showed significant relationships to broadly-defined headache.•Broadly-defined headache shared common genetic components with many psychological traits such as neuroticism.
This genetic study using the UK Biobank resource has identified 28 genomic loci for broadly-defined headache, among which, 14 are new loci. In addition, it has provided extra evidence that the functions of brain tissues are closely related to headache. Moreover, it has suggested that headache and many psychological disorders share common genetic factors. These findings will not only contribute to the understanding of the causes of headache (and its subtypes) and its relationships with psychological disorders, it might also bring potential genetic targets for drug treatment for patients with headache and psychological disorders.
Psoriatic arthritis (PsA) is a chronic inflammatory arthritis associated with psoriasis and, despite the larger estimated heritability for PsA, the majority of genetic susceptibility loci identified ...to date are shared with psoriasis. Here, we present results from a case-control association study on 1,962 PsA patients and 8,923 controls using the Immunochip genotyping array. We identify eight loci passing genome-wide significance, secondary independent effects at three loci and a distinct PsA-specific variant at the IL23R locus. We report two novel loci and evidence of a novel PsA-specific association at chromosome 5q31. Imputation of classical HLA alleles, amino acids and SNPs across the MHC region highlights three independent associations to class I genes. Finally, we find an enrichment of associated variants to markers of open chromatin in CD8(+) memory primary T cells. This study identifies key insights into the genetics of PsA that could begin to explain fundamental differences between psoriasis and PsA.
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