Association of Genetic Variant at Chromosome 12q23.1 With Neuropathic Pain Susceptibility

Veluchamy, Abirami; Hébert, Harry L.; Zuydam, Natalie R. van; Pearson, Ewan R.; Campbell, Archie; Hayward, Caroline; Wang, Meng; McCarthy, Mark; Bennett, David; Palmer, Colin N.A.; Smith, Blair H.

doi:10.1001/jamanetworkopen.2021.36560

Cited by 23 publications

(21 citation statements)

References 63 publications

(128 reference statements)

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“…Although genetic factors have not been analysed in this study, they have been studied separately elsewhere in DOLORisk Dundee [ 77 ]. These two components should be brought together to analyse the relative contribution of genetic and environmental factors to neuropathic pain.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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“…Therefore, this should be a focus of future work. Similarly, future studies will explore the wealth of genetic data that is available within UK Biobank, both to validate recent findings and to potential identify novel associations [55,56].…”

Section: Discussionmentioning

confidence: 99%

The epidemiology of neuropathic pain: an analysis of prevalence and associated factors in UK Biobank

Baskozos

Hébert

Pascal

et al. 2022

Preprint

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Previous epidemiological studies of neuropathic pain have reported a range of prevalences and factors associated with the disorder. This study aimed to verify these characteristics in a large UK cohort. A cross sectional analysis was conducted of 148,828 UK Biobank participants who completed a detailed questionnaire on chronic pain. The Douleur Neuropathique en Quatre Questions (DN4) was used to distinguish between neuropathic pain (NeuP) and non-neuropathic pain (Non-NeuP) in participants with pain of at least 3 months duration. Participants were also identified with less than 3 months pain or without pain (NoCP). Binomial and multinomial regression were used to identify factors associated with NeuP compared to Non-NeuP and NoCP respectively. Chronic pain was present in 76,095 participants (51.1%). The overall prevalence of NeuP was 9.2% (13,744/148,828. NeuP was significantly associated with worse health-related quality of life, having a manual or personal service type occupation and younger age compared to NoCP. As expected NeuP was associated with diabetes and neuropathy, but also other pains (pelvic, post-surgical and migraine) and musculoskeletal disorders (rheumatoid arthritis, osteoarthritis and fibromyalgia). Additionally, NeuP was associated with pain in the limbs and greater pain intensity and higher BMI compared to Non-NeuP. Female gender was associated with NeuP when compared to NoCP, whilst male gender was associated with NeuP when compared to Non-NeuP. This is the largest epidemiological study of neuropathic pain to date. The results confirm that the disorder is common in the general population and is associated with a higher health impact than non-neuropathic pain.

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“…Experimental models have suggested that SLC25A3 is believed to have a role in developing neuropathic pain; however, further research is required to better understand the underlying mechanisms implicated with these findings. 91 This study illustrates the use of common-effect models to provide important insights into the potential genetic associations to neuropathic pain.…”

Section: Meta-analysis Modelsmentioning

confidence: 95%

“…Veluchamy et al performed meta-analyses investigating the association of genetic variants on the susceptibility to neuropathic pain. 91 The authors performed meta-analyses of genome-wide association studies from 3 large comparable cohorts of patients with neuropathic pain in the United Kingdom. Using common-effect meta-analyses of each single-nucleotide polymorphism, 60 they identified a novel genome-wide significant locus at chromosome 12q23.1 mapping to SLC25A3 (odds ratio = 1.68, 95% confidence interval [CI]: 1.40–2.02).…”

Section: Meta-analysis Modelsmentioning

confidence: 99%

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

Fundaun

Thomas

Schmid

et al. 2022

PR9

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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.

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Association of Genetic Variant at Chromosome 12q23.1 With Neuropathic Pain Susceptibility

Cited by 23 publications

References 63 publications

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

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

The epidemiology of neuropathic pain: an analysis of prevalence and associated factors in UK Biobank

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

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