Updates & Features
The future of pain management: Exploring the genome to identify new targets and inform treatment selection
November 2018
Does current research represent the dawn of precision medicine in pain management?
PainSolve Editorial Team
Pain – an individual experience
Pain is a subjective experience. It is influenced by multiple factors including sex, race, ethnicity, psychological and social contexts and interpretation of pain, not to mention the environment.1 There exists interindividual variability in pain sensitivity, tolerance, the response to treatments and the propensity to develop chronic pain conditions.1–3 It is, therefore, challenging both to study pain and to manage it effectively.
Current pain-relieving treatments can be rather blunt tools and are often associated with side effects.4 There is a need to identify targets and treatments that are as individual as the experience of pain. Studies of twins have provided insight into the interindividual variability that can be explained by genetic factors.2,5 Thus, innovation in this area will likely come via a deeper understanding of the genetic contribution to individual differences in the pain experience, as well as the molecular mechanisms underlying chronic pain conditions. This article aims to summarise some of the current approaches.
Exploring the genome for novel pain targets
Currently, the genetics of pain is investigated in three main ways. Firstly, there is the study of rare inherited pain conditions. This has led to the identification of some specific important mutations. For example, mutations in the gene for the sodium channel Nav1.7 (SCN9A) have been associated with insensitivity to pain, informing the development of sodium channel blockers with greater selectivity.5,6 In addition, loss-of-function mutations in the gene encoding the neurotrophic receptor tyrosine kinase 1 (TrkA), a receptor tyrosine kinase for NGF, have been associated with an absence of small diameter sensory neurons, leading to the development of TrkA inhibitors.5,7
Secondly, there is linkage analysis to determine which genes are linked, i.e. inherited together based on their proximity on the same chromosome, through the study of large families.8 Family members who do and do not have pain are phenotyped and genotyped to determine which genes separate out with the disease.8
Finally, there are genetic association studies of large cohorts of matched, but unrelated, individuals to identify genetic variants that are distributed unevenly in those with pain and those without.5 Association studies test either a limited number of pre-selected genes (a candidate gene approach) or all variants in an unbiased screen (a genome-wide approach). These approaches are more relevant to the general population than is the study of rare conditions. While the study of familial pain conditions reveals ‘rare, high-impact mutations’, most genetic association studies reveal common single nucleotide polymorphisms (SNPs), found in >1% of the population, that modulate susceptibility to a given pain condition rather than cause it.8
In the public GWAS databases, numerous genes have been reported in genetic association studies across multiple chronic pain conditions, including cancer pain, low back pain, migraine, peripheral neuropathy, postoperative pain and temporomandibular disorder.8 The most recent studies have presented associations with neuropathic pain in post total joint replacement surgery for osteoarthritis9 and head and neck cancer10 (see the GWAS Catalog, GWAS Central, Human Genome Variation Database and National Human Genome Research Institute). However, to date, the results of association studies have been largely difficult to reproduce. This can reflect the large interindividual variability, suggesting the need for more rigorous phenotyping, use of a broader spectrum of -omics methods, cutting-edge analysis methods, as well as more homogeneous populations.5
Grünenthal’s expertise in pain research
Grünenthal is focused on improving the understanding of the biology of pain to uncover insights for patient stratification and biomarkers, identify pathways in which existing drugs are likely to be effective, and identify and validate new targets for treatment. Researchers are currently concentrating on genetic linkage studies, conducting detailed phenotyping and collecting tissue that undergoes multiple ‘omics’ analyses to identify which genes, RNAs, proteins or metabolites are associated with which phenotypical characteristics. In a next step, the so called ‘omics’ findings are enriched via pathway analysis to understand the underlying relevant biological pathways that are linked to the respective phenotypical characteristics. Examples of Grünenthal’s research can be accessed through links to the posters below.
- Preliminary Results of Comparative Proteomic Profiling of Sciatic Nerve, Plasma and Csf in a Rat Model of Neuropathic Pain
- Pain Testing@Home – The Cold Pressor Test as a first example
- Validity of online, self-administered Pain Sensitivity Questionnaire
In line with this strategy, the paper of Themistocleous et al. (2018) describes the ways in which patients with neuropathic pain may be stratified and the benefits of this stratification to reduce the uncertainty in diagnosis and help improve prevention, prognostication, and treatment selection.11 Figure 1 summarises some of the ways in which patients can be stratified.11
Figure 1.11 Schematic representations of some of the techniques that can be used to stratify patients with neuropathic pai. QST: quantitative sensory testing
The recent findings of Cobos et al. (2018) who correlated gene expression with behaviour following nerve injury in a mouse model validate this approach.12 They found that two common manifestations of neuropathic pain, cold and tactile allodynia, which develop at different timepoints after injury are associated with two distinct cellular and molecular mechanisms. One mechanism occurs in neurons, leading to cold allodynia, and the other includes immune cells and neurons, leading to tactile allodynia. The authors describe the potential to target drug development to each of these types of allodynia.12
As a basis to start this approach, Grünenthal conducted research using specific search terms combining -omics results with disease indications in pain to extract knowledge from relevant literature. This database has been used for gene set enrichment analysis to identify relevant biological pathways, which enhances the understanding of pathophysiologies of pain at the molecular level. Grünenthal is building a big picture of relevant biological pathways that enables the identification of unique and overlapping pathways for several pain indications that we will share with the PainSolve community in Q1 2019. As an example, we have shared a relevant pathway from our chronic constriction injury (CCI) experiments, which was reported at the IASP meeting in September (Figure 2). Such information can also be used to determine where existing drugs may be repurposed; we will report on our approach to drug repurposing in a future article. To date, a pilot in complex regional pain syndrome (CRPS) has been completed and analyses are ongoing for several other pain indications, with a particular focus on the processes behind molecular mechanisms of chronification in pain.
Figure 2: Pathway analysis of data sets revealed several proteins within the complement system that highlight neuropathic and postoperative pain involvement
Future directions – looking towards precision medicine for pain
While -omics studies in pain indications are still at their beginning, results to date suggest it may lead to promising new strategies for the assessment and treatment of pain conditions in the future. New patient stratification techniques and novel treatment options may translate into the development of drugs targeted to molecular pathways unique to particular conditions and pathologies, and the realisation of precision medicine in pain.
References
- James S. Br J Pain 2013; 7: 171–8
- Coghil RC. Headache 2010; 50: 1531–5
- LaCroix-Fralish ML, et al. Annu Rev Pharmacol Toxicol 2009; 49: 97–121
- Mayo Clinic (2018). Available at: https://www.mayoclinic.org/chronic-pain-medication-decisions/art-20360371
- Crow M, et al. Genome Medicine 2013; 5:12
- Versavel M. J. Pain Relief 2015; 4:3
- Bagal SK, et al. J Med Chem 2018; 61: 6779–800
- Zorina-Lichtenwalter K, et al. Neuroscience 2016; 338: 36–62
- Warner SC, et al. Eur J Hum Genet 2017; 25(4): 446-451
- Reyes-Gibby CC, et al. Sci Rep 2018; 8(1): 8789
- Themistocleous AC, et al. Pain 2018; 159: S31–S42
- Cobos EJ, et al. Cell Rep 2018; 22: 1301–12