Pain is believed to affect approximately 20% of adults globally.36 The heterogeneous nature of pain-associated disease necessitates precise understanding of molecular mechanisms behind distinct disorders to improve diagnostic ability and analgesic production. Initially, analgesic identification occurred through empirical observation, as with ancient opioid use,74 or by serendipity as with acetaminophen, which is used widely as an analgesic despite its unclear mechanisms.34 Over time, a focus on experimentally targeted analgesic development has led to therapeutics including ziconotide, a voltage-gated calcium channel inhibitor,66,98 therapies created to block nerve growth factor signalling cascades,81 and new inhibitory treatments of calcitonin gene-related peptide signaling28 (Table 1). Presently, unbiased genome screens are used to agnostically decipher apex pain signalling cascades and targets, guided only by primary data. Despite this extraordinary progress, there remains much to uncover regarding molecular mechanisms in chronic pain. This review is not intended to describe each pain gene identified by association methods, as these are effectively reviewed elsewhere.56,63,80,97,114 Rather, we wish to outline developments allowing for improved gene identification and targeting, while discussing advances towards achieving a rational process for analgesic design (Fig. 1).
2. Gene identification
2.1. Genetic linkage
Traditionally, genetic linkage has been used to understand the role of genetic variation in disease etiology. Linkage studies compare inheritance patterns of Mendelian disease phenotypes with genetic markers across family members. Markers include microsatellites (repeated noncoding sequences) and, more recently, single-nucleotide polymorphisms (SNPs). These single genomic alterations differ from a population's “average sequence” and occur approximately every 300 nucleotides.1 Genomic regions that cosegregate with a phenotype are termed quantitative trait loci (QTL) and exist within or outside of a gene, possibly containing multiple genes.41 Linkage is evaluated using a logarithm of the odds score, with larger positive scores representing greater cosegregation between phenotype and QTL.92 On locating a disease QTL, identifying mutated genes by sequencing or determining transcript expression within the QTL by tissue screening help identify and locate causative mutants.41
Linkage techniques have helped identify affected genetic locations in pain disorders. Family studies correlate gain-of-function SCN11 mutations with chronic joint pain112 and infantile familial episodic pain,70 whereas murine models link neuropathic pain to CACNG2.68 Mogil et al.62 correlated thermal perception to calcitonin gene-related peptide, proving this connection with additional pharmacological investigation. Moreover, mechanical sensitivity is linked with Cacna2d1, Csnk1e, and Ift27.111 The TRESK potassium channel is additionally linked to migraine with aura.46
Despite notable successes, linkage studies are limited because they require pedigrees containing sufficient documentation to trace genes of interest,27 although such data permit this in countries such as Iceland.37 In mice, developing specific combinations of inbred strains has also aided trait discovery.93 Although genetic contributions often strongly affect behavior in laboratory animals, where environmental influences and background genetics are tightly controlled, calculating genetic influence in human disease is more challenging because of life experience and complex genotypes.23,62
2.2. Genome-wide association studies
Emerging in 2001, genome-wide association studies (GWAS) identify genetic differences across a wider population that produces variable phenotypes. Participants are often categorized into disease (case) or nondisease (control) phenotypes. Large sample sizes are required to prevent misidentifying genes from false positives, such as with multiple testing.38 Unlike linkage, which is useful for diseases impacted by single penetrant genes,92 GWAS permit identification of multiple loci, which may together influence complex disease phenotypes.57
Recent notable GWAS of chronic pain include analyses of the UK Biobank, containing approximately 500,000 individuals.9 These have correlated IL-10 variants with postoperative pain, associated a MAT2B SNP with hip, knee, dorsal, and neck pain,115 and associated 3343 SNPs at 28 loci with headache, including 14 loci newly associated with pain.60 The recent OPPERA project (Orofacial Pain Prospective Evaluation and Risk Assessment Study) examined genetic and environmental risk factors for temporomandibular disorder (TMD), correlating poor sleep and perceived stress with TMD incidence.85 Multiple genes have been associated with TMD,86 revealing a functional link with MRAS in males87 and EGF signaling.58 Meta-analyses of multiple GWAS cohorts have also verified data reproducibility. Such studies have identified significant associations between SOX5, DCC, and intergenic variants with chronic back pain, and potentially height, depression, and osteoarthritis.91 Another associated an SNP insertion at the 9p22.3 NFIB locus with sciatica in Finnish patients.49 In addition, GWAS association and functional analysis of FAM173B demonstrated a role in chronic pain etiology.101
Such whole-genome–based studies often produce large quantities of data, which are difficult to manage. One processing method is pathway analysis,56 where algorithms sort genes into predefined regulatory cascades. As multiple genes with related action accumulate, the likelihood of functional association increases; although owing to multiple hypothesis testing, caution must be ascribed to marginally associated data. Pathway analyses are highly useful in identifying association between genes and new or known signaling cascades.15,58 It is important to recognize these associations are a gateway to additional necessary independent experiments to further demonstrate these genetic links.
Despite the utility of GWAS, limitations remain. Large samples may produce uncoordinated phenotyping and poor association data if different study groups are combined.97 An accurate study must also thoroughly consider the mixed etiology of pain conditions, including the anatomical diversity of symptoms and risk factors for development.4,5 In addition, the inherent subjectivity in categorizing individual cases by researchers or clinicians may unintentionally confound associations. Furthermore, by only defining disease SNPs as those meeting the high level of GWAS significance, other genes influencing complex phenotypes will be missed45,108; although with the advent of machine learning, these algorithms should improve.19 Nevertheless, well-performed studies can be extremely powerful. For instance, multiple large-scale migraine studies reveal TRPM8, PRDM16, and LRP1 as strongly associated loci.3 How identified leads evolve into therapies remains to be seen, although such strategies are already shifting focus to nonopioid analgesics.24,48,80
2.3. Genomic sequencing
An individual's genetic makeup may now be determined through improved genome-reading techniques. DNA sequencing has evolved remarkably since the 1970s, supported by progressively faster and more affordable next-generation techniques.7,79 Although traditional sequencing has aided discovery in molecular genetics, more advanced deep sequencing offers new possibilities related to the high-definition maps of individual genomes. With these improvements, SNPs will likely become outdated genomic markers or may represent the first stage of a process using genome sequencing to efficiently elucidate causative mutations. Ideally, every patient's genome will be sequenced in the near future to assess genetic risk of disease or aid identification of new pharmaceutical targets. In addition, certain tissues may be targeted to determine the pathogenicity of somatic mutations.32 However, issues of patient privacy and their responses to implications of these data must be considered.76
3. Gene modification
3.1. Genetic manipulation
Once genetic association identifies potential molecular pain mechanisms, additional methods are required to verify causation. Common strategies are pharmacological targeting, gene manipulation, and mRNA knockdown.25 Tissue-specific conditional knockout and overexpression studies use the Cre recombinase enzyme, which on activation targets tagged loci for genomic recombination and expression alteration.96 Alternatively, transcript knockdown has been investigated through RNA interference (RNAi) and microRNA (miRNA) studies.55,103
We have used such methods to examine the role of tetrahydrobiopterin (BH4) in chronic pain. By extending our initial association of less ongoing pain with a GCH1 haplotype,94 we further functionally validated this association.47,48 This relatively common haplotype (present in 25% of Caucasians) results in diminished GCH1 upregulation in response to cellular stress.94 The decreased GCH1 enzyme proportionally reduces intracellular BH4 production.48 As BH4 is an essential cofactor for dopamine, serotonin, norepinephrine, epinephrine, and nitric oxide, this reduction during somatosensory stress may be expected to decrease ongoing pain. Appropriately, mice with targeted reductions in sensory and immune BH4 levels experience less chronic pain.47 In addition, recent work has defined a new functional link between BH4 and T-cell amplification.18
Diatchenko et al.21 showed that Catechol-O-methyltransferase (COMT) correlated with differential levels of experimental and chronic pain in TMD, where associated SNPs directly contributed to enzyme stability and function.22 In humans, variants coding for decreased COMT metabolism of catecholaminergic neurotransmitters resulted in increased sensitivity to noxious stimuli and chronic pain risk, which was supported in mice.78 Interestingly, the GCH1 and COMT haplotypes are consistent mechanistically, although determining the degree of this similarity requires further work.
Purinergic signaling has been highly relevant in recent pain research.8 Sorge et al. used genome-wide linkage analysis to demonstrate mutations that alter P2X7 pore size affect chronic pain sensitivity in both mice and humans.8,88 Further work demonstrated differential sex-linked chronic pain phenotypes involving P2X7 and altered microglial and T-cell responses to nerve injury.88
3.2. RNA silencing
First observed in plants and eukaryotes in the 1990s, RNAi and miRNA regulate gene signaling by reducing transcription, destabilizing mRNA, or repressing translation. In RNAi, host cell RNA-induced silencing complexes knockdown their sequence-specific gene expression using small interfering RNA (siRNA) and have antiviral capabilities.10 Meanwhile, highly conserved miRNA perform endogenous gene silencing during development and tightly regulate transcript expression.6 They can also limit inflammatory signaling in neuropathic pain.40
A full genome screen using RNAi in Drosophila determined that the α2δ calcium channel straightjacket subunit, among other genes, was necessary in thermal nociception.67 In addition, viral RNA silencing constructs enable gene silencing through extrachromosomal expression or integration into host genomes.39,43 Recent RNAi work in rodents includes targeting the N-methyl-d-aspartate receptor GluN2B subunit,104 silencing TLR4 to decrease bone cancer pain,71 and elucidating NaV1.7 as a mediator of postoperative pain sensitivity.90
Nanoparticle encapsulation of small inhibitory RNAs for precise systemic delivery112 has allowed targeting TRPV1 transcripts to reduce thermal nociception,82 p38 siRNA silencing of microglial activation,84 and reduced IRF5-mediated hyperalgesia in microglia.95 In addition, siRNA studies implicate long noncoding RNAs (lncRNAs), which regulate transcription and signaling processes,72 in diabetic neuropathic pain. Knockdown of lncRNA reduces P2X751,53 and TRPV1-mediated52 pain signaling in rat sensory neurons. Clinical trials demonstrate the therapeutic potential of RNA silencing for several diseases, although utility in pain remains unreported.11 However, antisense constructs were recently used as spinal muscular atrophy and Duchenne muscular dystrophy treatments. By removing exons harboring disease-causing mutations from pre-mRNA transcripts, this technique functionally restores nondiseased gene expression.50
3.3. CRISPR/Cas9 genome editing
The rapid development of CRISPR/Cas9 genome editing since 2012 has enhanced gene mutation and expression studies.16,33,35,73 The system uses a modified bacterial CRISPR-Associated-Protein-9 (Cas9)-endonuclease. Postulated as a prokaryotic form of acquired immunity, bacterial Cas9 cleaves and incorporates viral DNA into its genome, permitting recognition and neutralization of future attacks.33 Researchers have modified type II CRISPR/Cas9 machinery to target specific eukaryotic bases in mice,99,107 embryonic stem cells,13 and other organisms.30
The type II CRISPR/Cas9 system uses a synthesized single-guide RNA (sgRNA), directing the complex to its complementary genomic region14 (Fig. 2). A 3 base pair protospacer-adjacent-motif (PAM) sequence immediately downstream of the complementary sequence permits identification, binding, and cleavage at the target site.73 In nature, bacteria target the foreign PAM present on invading viral or plasmid DNA.64 In model organisms, algorithms search a eukaryotic genome for a PAM sequence downstream of a target sequence to obtain a complete targeting construct.102 The sgRNA then hybridizes with the host DNA target site, allowing the coupled Cas9 to cleave DNA 3 nucleotides upstream from the PAM sequence. This produces a double-stranded break and triggers endogenous DNA repair mechanisms.2
Repair includes non-homologous end joining, in which random base pair insertions or deletions at cleavage sites create point or frame-shift mutations that unpredictably mutate genomic sequences.75 A mutated coding region may produce premature stop codons and subsequent gene knockouts, although this process is relatively uncontrolled.113 Alternatively, homology-directed repair inserts double- or single-stranded DNA (dsDNA; ssDNA) templates at cleavage sites.44,107 A donor sequence containing a small number of intentional mismatches can be used to alter specific genomic nucleotide pairings.42 Recently, longer ssDNA oligonucleotides have been used to increase integration efficiency and reduce off-target effects.61,110 Templates may include precise loxP-flanked sites for conditional knockout, overexpression, knock-in, protein tags including fluorescence, and genetic control elements.75 Alternatively, applying catalytically inactive Cas9 to repress or activate site transcription provides another approach to selectively manipulate expression.35,54 Notably, unpredictable offsite mutations often occur with CRISPR/Cas9 editing; thus, it is necessary to limit these effects.83 A useful control is to modify a gene to demonstrate a phenotype, with subsequent CRISPR/Cas9 reversal to wild type to exhibit phenotypic normalization.12,20
Among the natural changes that can be replicated through CRISPR/Cas9 editing are point mutations that cause congenital disease, including hypersensitive and hyposensitive pain syndromes. These mutations may change one functionally relevant amino acid, cause a frame shift with premature protein termination,89,100 or inactivate pre-mRNA splice sites producing intron retention and aberrant translation.69 Ultimately, each functionally alters the gene's cellular role and creates a modified protein. Rare congenic diseases often occur in individuals because of de novo dominant negative mutations. In heterozygous individuals, dominant negative proteins override their healthy counterparts by impeding normal protein function.89 CRISPR/Cas9-mediated insertion of known patient mutations into animals allows for investigation of the phenotypic effects of modified genes.
CRISPR/Cas9 modeling of rat neurofibromatosis type I revealed increased CRMP2-mediated signaling as a regulator of hyperalgesia in this disease.65 Recently, nanoparticle administration of CRISPR/Cas9 was used to knockout NLRP3 expression in murine macrophages, reducing IL-1β cleavage in acute septic shock, peritonitis, and diabetic models.105 A removal of 8 conserved amino acids in MeCP2 increased insensitivity to noxious heat, heightened anxiety, and lowered motor and cognitive activity in male mice, mirroring symptoms of human autism and Rett syndrome also caused by MECP2 mutations.106 In addition, a CRISPR/Cas9-mediated homologous knockout of PIEZO2 in human embryonic stem cell–derived neurons demonstrated its necessity in low-threshold mechanosensation.77
We can gain insight from these studies to identify novel drug targets. A well-known example is NaV1.7, genetically linked with multiple hyposensitive and hypersensitive pain phenotypes.17,26 This has generated a concerted drug discovery effort, which has yet to unveil potent analgesics.29,109 The reasons for the misalignment of genetic phenotype with drug target efficacy remain unclear, but continued effort should produce more successful translation.29 For instance, employment of CRISPR/Cas9-edited induced pluripotent stem cell nociceptors by Bennett et al.59 has recently localized NaV1.7 expression within nociceptors, revealed trafficking of these channels to specific neuronal compartments, and verified NaV1.7's significance in modulating nociceptor excitability. In addition, with respect to novel sodium channel inhibitors, Vertex Pharmaceuticals recently announced 2 successful phase 2 trials of VX-150, a NaV1.8 blocker targeting acute and chronic pain. NaV1.8, like NaV1.7, is expressed specifically in the sensory system, and its mutations are linked with congenic pain syndromes.31 Thus, if VX-150 is truly selective, this new class of inhibitors may be highly significant clinically.
As experimental methods evolve, genomic contributions to pain disorders may be systematically studied and distinct molecular cascades effectively targeted. When coupled with efficient patient phenotyping, these methods will introduce an age of truly personalized care. Genetic linkage, GWAS, and sequencing have contributed significantly to understanding heritability and associations between genetic loci and human pain conditions. These data suggest multiple genetic mechanisms in chronic pain, an unsurprising result given its mixed etiology. As techniques, including RNA silencing and CRISPR/Cas9 editing, evolve and transition from laboratory to clinic, they will become increasingly influential. However developed these methods become, it remains crucial to consider environmental influences in chronic pain. Nevertheless, we stand at the frontier of a spectacular era in genetics, which will greatly enhance our understanding and management of chronic pain.
Conflict of interest statement
The authors have no conflicts of interest to declare.
The authors thank Mantu Bhaumik, PhD, and Alexander Davies, PhD, for advice on the content of this article. The authors thank Amgen, Inc, for financial support.
R. González-Cano was supported by Alfonso Martin Escudero Fellowship.
Supplemental video content
Video content associated with this article can be found online at http://links.lww.com/PAIN/A804.
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