The Genetics of Neuropathic Pain from Model Organisms to Clinical Application
Authors: Margarita Calvo, Alexander J. Davies, Harry L. Hébert, Greg A. Weir, Elissa J. Chesler, Nanna B. Finnerup, Roy C. Levitt, Blair H. Smith, G. Gregory Neely, Michael Costigan, David L. Bennett
Journal: Neuron (2019)

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. 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. Neuropathic pain (NeuP) arises as a consequence of a lesion or disease of the somatosensory nervous system (Jensen et al., 2011Jensen T.S. Baron R. Haanpää M. Kalso E. Loeser J.D. Rice A.S.C. Treede R.-D. A new definition of neuropathic pain.Pain. 2011; 152: 2204-2205Abstract Full Text Full Text PDF PubMed Scopus (553) Google Scholar). It is common, affecting 7%–10% of the general population, and its prevalence is projected to increase with the aging population, diabetes epidemic, and improved cancer survival (van Hecke et al., 2014van Hecke O. Austin S.K. Khan R.A. Smith B.H. Torrance N. Neuropathic pain in the general population: a systematic review of epidemiological studies.Pain. 2014; 155: 654-662Abstract Full Text Full Text PDF PubMed Scopus (349) Google Scholar). Unfortunately, current drug treatments for NeuP are inadequate due to both poor efficacy and tolerability (Finnerup et al., 2015Finnerup N.B. Attal N. Haroutounian S. McNicol E. Baron R. Dworkin R.H. Gilron I. Haanpää M. Hansson P. Jensen T.S. et al.Pharmacotherapy for neuropathic pain in adults: a systematic review and meta-analysis.Lancet Neurol. 2015; 14: 162-173Abstract Full Text Full Text PDF PubMed Scopus (1020) Google Scholar). NeuP is also associated with a high level of disability and a large socio-economic cost: the global burden of disease survey showed that chronic pain is the third most important cause of disability-adjusted life-years worldwide (GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, 2018GBD 2017 Disease and Injury Incidence and Prevalence CollaboratorsGlobal, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017.Lancet. 2018; 392: 1789-1858Abstract Full Text Full Text PDF PubMed Scopus (188) Google Scholar, Rice et al., 2016Rice A.S. Smith B.H. Blyth F.M. Pain and the global burden of disease.Pain. 2016; 157: 791-796Crossref PubMed Scopus (58) Google Scholar). The current opioid epidemic exemplifies the problems associated with long term treatment of NeuP and the need for alternative non-addictive therapeutics (Jones et al., 2018Jones M.R. Viswanath O. Peck J. Kaye A.D. Gill J.S. Simopoulos T.T. A Brief History of the Opioid Epidemic and Strategies for Pain Medicine.Pain Ther. 2018; 7: 13-21Crossref PubMed Google Scholar). We do not yet have a full understanding of the drivers of NeuP and the extent to which they depend on the specific underlying etiology. For example, are the factors that precipitate NeuP in traumatic nerve injury and post-herpetic neuralgia the same? Nor do we have a full explanation as to why, following the same insult, some patients develop NeuP and others do not. Why for instance do only 30%–50% of diabetic polyneuropathy patients develop NeuP (Feldman et al., 2017Feldman E.L. Nave K.A. Jensen T.S. Bennett D.L.H. New Horizons in Diabetic Neuropathy: Mechanisms, Bioenergetics, and Pain.Neuron. 2017; 93: 1296-1313Abstract Full Text Full Text PDF PubMed Scopus (98) Google Scholar)? Differences here are likely to depend on a complex interaction between environmental and genetic factors that alter both the vulnerability and resilience of the somatosensory nervous system. A better understanding of the genetic architecture of NeuP will therefore provide fundamental insights into disease pathophysiology, help us understand inter-individual variation in NeuP, and reveal new drug targets. Despite great efforts, the development of new and effective treatments for NeuP has proved difficult, with a number of promising pharmacological targets identified in preclinical studies failing to achieve clinical efficacy (Percie du Sert and Rice, 2014Percie du Sert N. Rice A.S. Improving the translation of analgesic drugs to the clinic: animal models of neuropathic pain.Br. J. Pharmacol. 2014; 171: 2951-2963Crossref PubMed Scopus (52) Google Scholar). The reasons for this are complex, spanning the whole process of drug development but broadly falling into two categories: the sensitivity of clinical trials for NeuP therapies due to the subjectivity of pain reporting, the placebo effect and case mix (Finnerup et al., 2018Finnerup N.B. Haroutounian S. Baron R. Dworkin R.H. Gilron I. Haanpaa M. Jensen T.S. Kamerman P.R. McNicol E. Moore A. et al.Neuropathic pain clinical trials: factors associated with decreases in estimated drug efficacy.Pain. 2018; 159: 2339-2346Crossref PubMed Scopus (10) Google Scholar) and the ability of animal models to predict clinical efficacy (Percie du Sert and Rice, 2014Percie du Sert N. Rice A.S. Improving the translation of analgesic drugs to the clinic: animal models of neuropathic pain.Br. J. Pharmacol. 2014; 171: 2951-2963Crossref PubMed Scopus (52) Google Scholar). There have been major advances in gene sequencing technology and the informatics required to deal with large data volumes. These are now being applied at a national scale to health services, for instance, the sequencing of 100,000 whole genomes by the National Health Service (NHS) in the UK (Samuel and Farsides, 2017Samuel G.N. Farsides B. The UK's 100,000 Genomes Project: manifesting policymakers' expectations.New Genet. Soc. 2017; 36: 336-353Crossref Scopus (4) Google Scholar). The sensory phenotyping of NeuP has become more precise and can now be combined with large clinical and research cohorts such as the UK-Biobank of 500,000 people (Sudlow et al., 2015Sudlow C. Gallacher J. Allen N. Beral V. Burton P. Danesh J. Downey P. Elliott P. Green J. Landray M. et al.UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.PLoS Med. 2015; 12: e1001779Crossref PubMed Scopus (803) Google Scholar). The HEAL initiative in the USA (https://heal.nih.gov) is also collecting pain outcome measures and genetic data (Volkow and Koroshetz, 2019Volkow N.D. Koroshetz W.J. The role of neurologists in tackling the opioid epidemic.Nat. Rev. Neurol. 2019; 15: 301-305Crossref PubMed Scopus (0) Google Scholar) providing opportunities to create large-scale international consortia (Pascal et al., 2019Pascal M.M.V. Themistocleous A.C. Baron R. Binder A. Bouhassira D. Crombez G. Finnerup N.B. Gierthmühlen J. Granovsky Y. Groop L. et al.DOLORisk: study protocol for a multi-centre observational study to understand the risk factors and determinants of neuropathic pain.Wellcome Open Res. 2019; 3: 63Crossref PubMed Scopus (1) Google Scholar). Complementary advances in mouse genetics have improved the precision of basic research into the discovery of pain mechanisms. The speed with which we can manipulate the genome of model organisms such as the fruit fly and mouse, or even human sensory neurons derived from stem cells, means we can rapidly interrogate gene function once genes of interest are identified. Given the multi-disciplinary expertise needed to make full use of these resources, we organized a joint satellite meeting of the NeuP and Genetics Special Interest Groups (SIGs) of the International Association for the Study of Pain (IASP) at The Jackson Laboratory, Bar Harbor, ME (September 10 and 11, 2018), which inspired many of the ideas presented in this review. The past decade has seen great improvements in the techniques used to define the sensory profile of NeuP patients (Figure 1). These include questionnaires to assess pain quality, psychophysical tools to assess sensory perception, and alteration of experimental pain through conditioned pain modulation (CPM). These questionnaires e.g., NPSI, DN4, painDETECT, and LANSS (Bennett et al., 2007Bennett M.I. Attal N. Backonja M.M. Baron R. Bouhassira D. Freynhagen R. Scholz J. Tölle T.R. Wittchen H.U. Jensen T.S. Using screening tools to identify neuropathic pain.Pain. 2007; 127: 199-203Abstract Full Text Full Text PDF PubMed Scopus (358) Google Scholar) incorporate descriptors of sensory symptoms to generate a score that helps predict whether the pain is likely to be neuropathic or not, and to characterize distinct dimensions of NeuP. Psychophysical tools to test the function of the somatosensory nervous system have benefited from standardization of quantitative sensory testing (QST) protocols. This consistency of reporting enables the generation of large cohorts of patients from different centers, so enhancing statistical power (Rolke et al., 2006Rolke R. Magerl W. Campbell K.A. Schalber C. Caspari S. Birklein F. Treede R.D. Quantitative sensory testing: a comprehensive protocol for clinical trials.Eur. J. Pain. 2006; 10: 77-88Crossref PubMed Scopus (660) Google Scholar). Conditioned pain modulation are dynamic psychophysical protocols that aim to explore an individual's descending pain modulatory system, although the complexity of the protocols and the variability in the size and stability of the response remains a challenge (Kennedy et al., 2016Kennedy D.L. Kemp H.I. Ridout D. Yarnitsky D. Rice A.S. Reliability of conditioned pain modulation: a systematic review.Pain. 2016; 157: 2410-2419Crossref PubMed Scopus (77) Google Scholar). Deployment of a combination of the above techniques now enables the stratification of NeuP patients according to sensory profile, providing a much richer dataset than simply classifying patients according to etiology (e.g., polyneuropathy versus post-herpetic neuralgia) and enabling for selection of patients with specific phenotypes to empower clinical trials (Attal et al., 2018Attal N. Bouhassira D. Baron R. Diagnosis and assessment of neuropathic pain through questionnaires.Lancet Neurol. 2018; 17: 456-466Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar). There have also been significant advances in the development of biomarkers which assess neurobiological processes underlying pain but are not dependent on patient report, such as neurophysiology (microneurography and evoked potentials) and neuro-imaging (Tracey et al., 2019Tracey I. Woolf C.J. Andrews N.A. Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment.Neuron. 2019; 101: 783-800Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar). When different biomarkers are used in combination they can become objective indicators with adequate specificity and sensitivity to aid diagnosis and prognosis (Tracey et al., 2019Tracey I. Woolf C.J. Andrews N.A. Composite Pain Biomarker Signatures for Objective Assessment and Effective Treatment.Neuron. 2019; 101: 783-800Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar). Combining such sensory phenotyping and biomarkers with genetics should provide significant added value in understanding the pathophysiology of NeuP and be of clinical relevance in terms of diagnosis, prognosis, and treatment choice. Their use will depend on the cohort being studied. For example, questionnaires can be applied at population level, while QST is only feasible in patients attending specialized services. However, standardization of QST protocols has enabled increased cohort size. These methods have associated gene variants with particular aspects of the NeuP sensory phenotype, such as paradoxical heat sensation (the perception of warmth/heat as the skin is cooled) (Binder et al., 2011Binder A. May D. Baron R. Maier C. Tölle T.R. Treede R.D. Berthele A. Faltraco F. Flor H. Gierthmühlen J. et al.Transient receptor potential channel polymorphisms are associated with the somatosensory function in neuropathic pain patients.PLoS ONE. 2011; 6: e17387Crossref PubMed Scopus (0) Google Scholar). Brain imaging is now also being used at the population level; for instance, UK-Biobank plans to image 100,000 predominantly healthy genome-sequenced individuals, who will then be followed longitudinally. An initial analysis has already shown that structural and functional brain imaging phenotypes are heritable (Elliott et al., 2018Elliott L.T. Sharp K. Alfaro-Almagro F. Shi S. Miller K.L. Douaud G. Marchini J. Smith S.M. Genome-wide association studies of brain imaging phenotypes in UK Biobank.Nature. 2018; 562: 210-216Crossref PubMed Scopus (32) Google Scholar), with over 100 genomic regions showing associations with imaging phenotypes. Although such imaging studies are not undertaken using an experimental pain model, clinical pain data are being collected, and they do begin to provide insight into the genetic basis of brain structure/connectivity. This will help inform on the brain's response to disease and explore the hypothesis that brain circuitry confers resilience or vulnerability to NeuP (Denk et al., 2014Denk F. McMahon S.B. Tracey I. Pain vulnerability: a neurobiological perspective.Nat. Neurosci. 2014; 17: 192-200Crossref PubMed Scopus (154) Google Scholar). Genetic epidemiology—the study of the role genetic factors play in determining health-related states or events in a population—is a useful tool to help understand NeuP as it can reveal genetic variants associated with disease risk (Manolio, 2010Manolio T.A. Genomewide association studies and assessment of the risk of disease.N. Engl. J. Med. 2010; 363: 166-176Crossref PubMed Scopus (937) Google Scholar). Genetic epidemiology studies of NeuP have presented a number of challenges (Figure 2). The first is sample size. In order to detect genetic associations, particularly those of small effect size, a study must have sufficient statistical power. In genome-wide association studies (GWASs) of other conditions, well-powered cohorts usually exceed ten thousand participants. A recent example of this is in type 2 diabetes where one study used a cohort of 74,124 cases and 824,006 controls by combining genetic data from 32 different studies. This enabled the authors to identify 243 loci that reached significance (p < 5 × 10−8) and accounted for approximately 18% of the variance in risk and around a half of the estimated overall heritability (Mahajan et al., 2018Mahajan A. Taliun D. Thurner M. Robertson N.R. Torres J.M. Rayner N.W. Payne A.J. Steinthorsdottir V. Scott R.A. Grarup N. et al.Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.Nat. Genet. 2018; 50: 1505-1513Crossref PubMed Scopus (4) Google Scholar). To date, genetic studies of NeuP have typically analyzed cohorts with fewer than a thousand cases, which has resulted in only suggestive associations (Hébert et al., 2017Hébert H.L. Veluchamy A. Torrance N. Smith B.H. Risk factors for neuropathic pain in diabetes mellitus.Pain. 2017; 158: 560-568Crossref PubMed Scopus (2) Google Scholar). One reason that genetic studies in NeuP lack sufficient sample sizes is the costs associated with recruiting, adequately phenotyping, and genotyping the cohort. A solution to this problem lies in cross-institution collaboration where cohorts can be combined and meta-analyses can be conducted to boost sample size and power. Combining such cohorts requires harmonization between them, which brings us onto the next challenge. A recent systematic review of genetic studies of NeuP identified 29 studies, with no two studies using the same NeuP case definition (Veluchamy et al., 2018Veluchamy A. Hébert H.L. Meng W. Palmer C.N.A. Smith B.H. Systematic review and meta-analysis of genetic risk factors for neuropathic pain.Pain. 2018; 159: 825-848Crossref PubMed Google Scholar). This has made it difficult to compare the genetic variants and their effect size estimates across studies, and to combine data to conduct meta-analyses (Evangelou and Ioannidis, 2013Evangelou E. Ioannidis J.P.A. Meta-analysis methods for genome-wide association studies and beyond.Nat. Rev. Genet. 2013; 14: 379-389Crossref PubMed Scopus (258) Google Scholar). A robust phenotypic definition of NeuP is needed, that all researchers adhere to, in order to accurately identify cases and controls. A consensus definition on NeuP has led to international harmony on clinical NeuP assessment, but these methods are not necessarily amenable to large populations (Finnerup et al., 2016Finnerup N.B. Haroutounian S. Kamerman P. Baron R. Bennett D.L.H. Bouhassira D. Cruccu G. Freeman R. Hansson P. Nurmikko T. et al.Neuropathic pain: an updated grading system for research and clinical practice.Pain. 2016; 157: 1599-1606Crossref PubMed Scopus (200) Google Scholar). In a research setting, a good NeuP definition and classification into specific subgroups should be valid (identifying people with and without NeuP), feasible to use (in terms of the study time, ethics, and cost), accurate and precise (having high sensitivity and specificity), and, above all, reproducible. To address this issue, NeuP SIG have published a set of recommendations for phenotyping NeuP (van Hecke et al., 2015van Hecke O. Kamerman P.R. Attal N. Baron R. Bjornsdottir G. Bennett D.L. Bennett M.I. Bouhassira D. Diatchenko L. Freeman R. et al.Neuropathic pain phenotyping by international consensus (NeuroPPIC) for genetic studies: a NeuPSIG systematic review, Delphi survey, and expert panel recommendations.Pain. 2015; 156: 2337-2353Crossref PubMed Scopus (23) Google Scholar). The NeuP Phenotyping by International Consensus (NeuroPPIC) guidelines provide a set of entry-level criteria with which to assess participants for NeuP, including use of a validated NeuP screening tool, anatomical distribution of pain using a body chart or checklist, and pain history (including intensity, duration, underlying etiology, and demographics). However, preliminary analysis of the feasibility of NeuroPPIC suggests that it may currently be overly stringent, meaning that larger cohorts than are currently available would be required to produce a sample size that has adequate statistical power (unpublished data). This demonstrates the trade-off between feasibility and validity of phenotyping criteria. A further complication is the fact that the standard validated NeuP screening tools do not always agree. A study of the agreement of the Self-report Leeds Assessment of Neuropathic Symptoms and Signs (S-LANSS) (Bennett et al., 2005Bennett M.I. Smith B.H. Torrance N. Potter J. The S-LANSS score for identifying pain of predominantly neuropathic origin: validation for use in clinical and postal research.J. Pain. 2005; 6: 149-158Abstract Full Text Full Text PDF PubMed Scopus (347) Google Scholar) and Douleur Neuropathique 4 Questions (DN4) (Bouhassira et al., 2005Bouhassira D. Attal N. Alchaar H. Boureau F. Brochet B. Bruxelle J. Cunin G. Fermanian J. Ginies P. Grun-Overdyking A. et al.Comparison of pain syndromes associated with nervous or somatic lesions and development of a new neuropathic pain diagnostic questionnaire (DN4).Pain. 2005; 114: 29-36Abstract Full Text Full Text PDF PubMed Scopus (1144) Google Scholar) screening tools in 45 patients with low back pain or related leg pain revealed only a moderate correlation, albeit statistically significant (Walsh et al., 2012Walsh J. Rabey M.I. Hall T.M. Agreement and correlation between the self-report leeds assessment of neuropathic symptoms and signs and Douleur Neuropathique 4 Questions neuropathic pain screening tools in subjects with low back-related leg pain.J. Manipulative Physiol. Ther. 2012; 35: 196-202Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar). Despite these shortcomings, a number of molecular, candidate-gene, and genome-wide studies have been conducted in humans that are comprehensively summarized in a recent systematic review (Veluchamy et al., 2018Veluchamy A. Hébert H.L. Meng W. Palmer C.N.A. Smith B.H. Systematic review and meta-analysis of genetic risk factors for neuropathic pain.Pain. 2018; 159: 825-848Crossref PubMed Google Scholar). Investigations eligible for inclusion were those that examined genetic variants in people with NeuP compared to people without NeuP. These studies identified 28 genes that show study-wide association with the presence of NeuP. Together, these genes provide important clues as to the biological mechanisms involved in the onset and persistence of NeuP (Figure 3). The association of variants in COMT, OPRM1, SCN9A, SLC6A4, and CACNG2 demonstrates the involvement of neurotransmission. Major histocompatibility complex and cytokine genes including HLA-A, HLA-B, HLA-DQB1, HLA-DRB1, B2M, IL6, IL1R2, IL10, and TNF-a represent the immune response pathway, and it is interesting to note that these genes are also associated with underlying diabetic neuropathy and post-herpetic neuralgia etiologies. Finally the identification of genes involved in iron metabolism including ACO1, BMP6, FXN, TF, CP, TFRC, SLC11A2, and GCH1 illustrates the role of metabolic pathways in neuropathic sensory dysfunction. Of the genes that were identified in candidate gene-studies, variants in HLA genes, COMT, OPRM1, TNF-a, IL6, and GCH1 were found to have an association with NeuP in more than one study (Veluchamy et al., 2018Veluchamy A. Hébert H.L. Meng W. Palmer C.N.A. Smith B.H. Systematic review and meta-analysis of genetic risk factors for neuropathic pain.Pain. 2018; 159: 825-848Crossref PubMed Google Scholar). While other genes including SCN9A have been associated with pain intensity in neuropathy (Reimann et al., 2010Reimann F. Cox J.J. Belfer I. Diatchenko L. Zaykin D.V. McHale D.P. Drenth J.P. Dai F. Wheeler J. Sanders F. et al.Pain perception is altered by a nucleotide polymorphism in SCN9A.Proc. Natl. Acad. Sci. USA. 2010; 107: 5148-5153Crossref PubMed Scopus (193) Google Scholar), only the HLA genes (A, B, and DRB1) have been replicated consistently as associated with the presence or absence of NeuP in the same etiology (post herpetic neuralgia) (Sato-Takeda et al., 2004Sato-Takeda M. Ihn H. Ohashi J. Tsuchiya N. Satake M. Arita H. Tamaki K. Hanaoka K. Tokunaga K. Yabe T. The human histocompatibility leukocyte antigen (HLA) haplotype is associated with the onset of postherpetic neuralgia after herpes zoster.Pain. 2004; 110: 329-336Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar, Ozawa et al., 1999Ozawa A. Sasao Y. Iwashita K. Miyahara M. Sugai J. Iizuka M. Kawakubo Y. Ohkido M. Naruse T. Anzai T. et al.HLA-A33 and -B44 and susceptibility to postherpetic neuralgia (PHN).Tissue Antigens. 1999; 53: 263-268Crossref PubMed Scopus (0) Google Scholar, Sumiyama et al., 2008Sumiyama D. Kikkawa E.F. Kita Y.F. Shinagawa H. Mabuchi T. Ozawa A. Inoko H. HLA alleles are associated with postherpetic neuralgia but not with herpes zoster.Tokai J. Exp. Clin. Med. 2008; 33: 150-153PubMed Google Scholar). In addition, polymorphisms in GCH1 that were originally identified as risk factors in persistent lumbar root pain (Tegeder et al., 2006Tegeder I. Costigan M. Griffin R.S. Abele A. Belfer I. Schmidt H. Ehnert C. Nejim J. Marian C. Scholz J. et al.GTP cyclohydrolase and tetrahydrobiopterin regulate pain sensitivity and persistence.Nat. Med. 2006; 12: 1269-1277Crossref PubMed Scopus (406) Google Scholar) have been associated with NeuP in a further two different etiologies (HIV-induced sensory neuropathy and persistent postsurgical pain) suggesting that the recently discovered role of GCH1 in energy metabolism may potentially lie at a key intersection in NeuP development (Cronin et al., 2018Cronin S.J.F. Seehus C. Weidinger A. Talbot S. Reissig S. Seifert M. Pierson Y. McNeill E. Longhi M.S. Turnes B.L. et al.The metabolite BH4 controls T cell proliferation in autoimmunity and cancer.Nature. 2018; 563: 564-568Crossref PubMed Scopus (12) Google Scholar). Furthermore, three GWASs of NeuP have been conducted to date. Two used a prescription-based phenotype for NeuP (572 and 961 cases) (Meng et al., 2015aMeng W. Deshmukh H.A. Donnelly L.A. Torrance N. Colhoun H.M. Palmer C.N. Smith B.H. Wellcome Trust Case Control Consortium 2 (WTCCC2)Surrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools (SUMMIT) study groupA genome-wide association study provides evidence of sex-specific involvement of chr1p35.1 (ZSCAN20-TLR12P) and chr8p23.1 (HMGB1P46) with diabetic neuropathic pain.EBioMedicine. 2015; 2: 1386-1393Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar, Meng et al., 2015bMeng W. Deshmukh H.A. van Zuydam N.R. Liu Y. Donnelly L.A. Zhou K. Morris A.D. Colhoun H.M. Palmer C.N. Smith B.H. Wellcome Trust Case Control Consortium 2 (WTCCC2)Surrogate Markers for Micro- and Macro-Vascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) Study GroupA genome-wide association study suggests an association of Chr8p21.3 (GFRA2) with diabetic neuropathic pain.Eur. J. Pain. 2015; 19: 392-399Crossref PubMed Google Scholar) and another used knee pain cohorts screened for NeuP using the painDETECT questionnaire (331 cases) (Warner et al., 2017Warner S.C. van Meurs J.B.J. Schiphof D. Bierma-Zeinstra S.M. Hofman A. Uitterlinden A.G. Richardson H. Jenkins W. Doherty M. Valdes A.M. Genome-wide association scan of neuropathic pain symptoms post total joint replacement highlights a variant in the protein-kinase C gene.Eur. J. Hum. Genet. 2017; 25: 446-451Crossref PubMed Scopus (0) Google Scholar). However, none of the loci identified by these studies (GFRA2, ZSCAN20-TLR12P, HMGB1P46, or PRKCA) reached genome-wide significance, again highlighting the importance of sample size and phenotype harmonization. Such factors are currently being addressed by the DOLORisk study (http://dolorisk.eu/) (Pascal et al., 2019Pascal M.M.V. Themistocleous A.C. Baron R. Binder A. Bouhassira D. Crombez G. Finnerup N.B. Gierthmühlen J. Granovsky Y. Groop L. et al.DOLORisk: study protocol for a multi-centre observational study to understand the risk factors and determinants of neuropathic pain.Wellcome Open Res. 2019; 3: 63Crossref PubMed Scopus (1) Google Scholar), a European consortium that aims to identify risk factors for NeuP. For this study, a core group of questionnaires has been developed, based on the NeuroPPIC guidelines. This has been used to phenotype two Scottish cohorts covering 33,000 individuals. Furthermore, consenting participants of the UK Biobank cohort are currently being re-phenotyped for pain using the DN4 questionnaire (originally ∼500,000). Although the survey is still being completed, it is expected that responses will be received from around 175,000 participants. Assuming a NeuP prevalence of 7% (van Hecke et al., 2014van Hecke O. Austin S.K. Khan R.A. Smith B.H. Torrance N. Neuropathic pain in the general population: a systematic review of epidemiological studies.Pain. 2014; 155: 654-662Abstract Full Text Full Text PDF PubMed Scopus (349) Google Scholar), which is at the lower end of estimations, it is predicted that the number of people with NeuP will be over 12,000, providing the power to identify novel genetic variants. Requiring such a stringent p value threshold (p < 5 × 10−8) to deal with multiple testing and protect against type I error (false association) is in tension with the greater chance of a type II error (overlooked associated genes). Pathway or gene set enrichment analysis that combines the association statistics of genes co-involved in defined signaling pathways can be one way to deal with this issue. This can be informative on the basis of aggregate data from multiple SNPs that show suggestive association but which individually do not reach the nominal threshold of 5 × 10−8 (Lötsch et al., 2013Lötsch J. Doehring A. Mogil J.S. Arndt T. Geisslinger G. Ultsch A. Functional genomics of pain in analgesic drug development and therapy.Pharmacol. Ther. 2013; 139: 60-70Crossref PubMed Scopus (0) Google Scholar, Parisien et al., 2019Parisien M. Samoshkin A. Tansley S.N. Piltonen M.H. Martin L.J. El-Hachem N. Dagostino