Omics approaches to discover pathophysiological pathways contributing to human pain

Abstract

1. Introduction There exist limited data to inform mechanism-based understanding and management of chronic pain, and thus, there is a clear unmet need to better define the molecular mechanisms of pain to develop novel treatment strategies. Generating knowledge regarding molecular pathophysiology of pain states using human cohorts has an obvious advantage over animal models, and it can be achieved using molecular and cellular genome-wide approaches in cohorts that have been characterized for different pain states and different pain-related intermediate phenotypes. Crucially, such approaches are hypothesis free, and thus both heuristic and resulting in the unbiased interpretation of data, not restricted by or funneled through specific hypotheses or gene candidates. There has been tremendous progress lately in the development of unbiased molecular screening approaches and analytic tools.67 These multiomics approaches include molecular assays of DNA, RNA, proteins, and small molecules in a high-throughput, comprehensive manner. Their use has advanced and even changed our understanding of the pathophysiology of many diseases, including stroke, diabetes, and cancer.27 Importantly, -omics approaches permit the systematic use and integration of multiple data sets, creating further dimensionality in the interpretation of the results that can lead to the development of new conceptual approaches and treatment strategies. In this review, we will discuss these approaches for studying the molecular pathophysiology of pain states at molecular and genetic levels using 3 recent examples from our laboratories, describing both the -omic techniques identifying hypotheses and the animal model mechanistic studies that follow. Overall, these findings support the critical role of neuroimmune interactions in pain resolution processes that involve, over time, different subsets of immune cells. 2. Genome-wide association analysis of pain phenotypes At the level of DNA, whole-genome or exome sequencing,23 genome-wide genotyping,80 and DNA methylation assays2,89 have been rapidly developing. Genotyping platform development for genome-wide association studies (GWASs) was the first-developed high-throughput -omics approach, and as such, today, there exist a large number of published pain-relevant GWASs. The GWAS approach identifies genetic variants with relatively high frequency in the population and associates them statistically with either the presence or severity of a particular disease. The genetic variants, called alleles, are either single-nucleotide polymorphisms (SNPs) or indels (insertion or deletion of nucleotides). Variants considered in GWAS studies generally appear in the study population at relatively high frequencies, typically >1%, whereas lower-frequency alleles would be termed rare variants, which are usually identified using direct DNA sequencing approaches. Functional annotation of the variants establishes the consequences of each allele at each variant that are found inside a gene's locus. Examples of the impacts of variants in a protein-coding gene—which can be dramatic or subtle—include single amino acid substitution, insertion of a premature stop codon, or alteration in the expression levels (so-called expression quantitative trait loci). The first pain GWAS was published in 2010, on migraineurs.1 Multiple published migraine GWASs, each bigger than the last, have to date identified 38 genetic variants and 123 genetic susceptibility loci.14 In the beginning, emphasis was placed on the genome-wide significance of the finding and tying each genetic variant to a particular gene. Over time, the substantial polygenic nature of pain phenotypes (similar to other complex phenotypes) became apparent, undermining the importance of any individual genes and demanding new types of integrative analyses. For migraine, a meta-analysis of 22 migraine GWASs24 first allowed an unbiased reconstructing of the pathophysiology of migraine. Because strong arguments for both vascular and neuronal mechanisms of migraine existed,62 it was tempting to use GWAS results to try to determine the exclusive or at least major driver of migraine development. The first migraine-associated variants provided much stronger support for the involvement of vascular and smooth muscle dysfunction in migraine, with only 5 loci of 38 containing neuronal (ion channel) genes. However, the latest even larger GWAS meta-analysis on 102,084 migraine cases and 771,257 control subjects28 showed equal support for both vascular and neuronal contribution to the pathophysiology of migraine, suggesting that instead of contrasting these hypotheses, we perhaps should embrace the possibility of their interacting contribution or that migraine may have more substantial heterogeneity than previously believed. Existing GWASs for other chronic pain syndromes include back pain,6,20,73 shoulder pain,10,49 temporomandibular disorder (TMD),66,70 multisite pain,33–35 neuropathic pain,55,64 and other chronic musculoskeletal pain conditions.61,63,72,79 Functional analyses of these GWASs has provided critical information on the pathophysiology of chronic pain. These functional analyses are derived mostly from annotating the corresponding genes60,88; partitioning heritability,18,19 a method that estimates enrichment of corresponding gene expression in specific tissues; and pathway analysis, an approach that tests for the enrichment of the corresponding genes in predefined biological pathways like those in the Gene Ontology (GO) data set.3 Such functional analyses revealed the strong contribution of the central nervous system to the pathophysiology of back pain,20 neck/shoulder pain,49 and multisite pain.33 Genes expressed in the muscle and skeletal tissues were found to contribute to the pathophysiology of back pain6,20 and chronic widespread musculoskeletal pain.63 Finally, immune system genes were found to contribute to back pain,6,57 temporomandibular disorder,57,70 and shoulder impingement syndrome.10 The most recent GWAS meta-analysis on 17 pain susceptibility traits reveals equal neuronal and immunological etiology for pain susceptibility.51 Further analyses of different subclusters of human pain conditions have provided additional critical information on the pathophysiology of chronic pain. It seems that chronic vs acute pain, as well as chronic overlapping pain conditions (COPC) vs pain at a single body site, are mediated by different biological pathways. For example, genes mapped to variants associated with chronic back pain, but not acute back pain, were found to be significantly enriched in the pathways for neurogenesis and synaptic plasticity. In contrast, connective tissue and bone remodeling pathways, cardiac muscle depolarization, and immune response via Th2-helper cells were enriched in acute back pain, but not at all in chronic pain back.6 Although a report of chronic single-site pain did not identify enrichment in any GO biological process pathway, the GWAS on COPC identified a total of 60 pathways, with the overwhelming majority of the pathways involved in neural function and development.35 The other significant pathways included the contribution of the immune system, such as regulation of monocyte differentiation, and vascular system development, such as aorta morphogenesis. Importantly, a further functional analysis pointed to axonogenesis in brain tissues as a major contributor to COPC. This observation was also supported by multimodal structural brain imaging, demonstrating that the top associated gene in this analysis, DCC netrin-1 receptor (DCC), is strongly expressed in subcortical limbic regions and is associated with alterations in the uncinate fasciculus microstructure, suggesting that DCC-dependent axonogenesis may contribute to COPC via corticolimbic circuits (Fig. 1).35Figure 1.: The contribution of axonogenesis to chronic overlapping pain conditions based on the results from genome-wide association studies and brain imaging data (based on Khoury et al).35 Genome-wide association studies were conducted in human subjects reporting chronic pain at a single body site (N = 1 site, blue) or multiple body sites (N ≥ 2 sites, purple), compared with human subjects not reporting any pain (N = 0). The DCC Netrin 1 Receptor (also known as colorectal cancer suppressor) gene was found to be strongly associated with multisite chronic pain but not with single-site chronic pain. DCC is a gene that critically contributes to axonogenesis, the process of steered development of neuronal axons toward their synaptic targets. Consistent with the association of DCC gene with chronic multisite pain, the genome-wide association study-based pathways analyses identified axonogenesis in brain tissues as the major contributing pathway to chronic multisite pain. Genetic partitioned heritability (h2) analysis indicated a significant enrichment of heritability in single-nucleotide polymorphisms at loci of genes exclusively expressed in brain regions for multisite chronic pain but not for single-site chronic pain. Brain imaging data identified increased neurite orientation dispersion with an increased number of chronic pain sites. The orientation dispersion of neurites can range from highly parallel (coherently oriented white matter structures) to highly dispersed (grey matter structures characterized by sprawlig dendritic processes in all directions), as suggested by the neuronal networks inside the bar plot's bars. Orientation dispersion is shown for the uncinate fasciculus brain sub-structure. The background brain image shows evidence for DCC expression in the uncinate fasciculus. Together, our results suggest that genetically determined DCC-dependent disorganization in axonal tracks in patients with chronic overlapping pain conditions may contribute to pathogenesis of disease through corticolimbic circuits.In addition to understanding biological pathways contributing to pain states, GWAS-derived heritability estimates—the proportion of variation in pain phenotypes due to genes vs the environment—has provided valuable information. Contrasting chronic and acute back pain6 demonstrates that the heritability of chronic back pain (4.6%) is much higher than that of acute back pain (0.8%), and, similarly, the heritability of COPC (19%) is much higher than that of chronic pain in any single body site (1%-10%).35 Among other insights provided by the analyses of human GWASs to the pathophysiology of chronic pain is a strong genetic correlation between different chronic pain conditions. In line with existing epidemiological data on the comorbidity between different pain conditions,69 this genetic correlation was the strongest for the physically proximal pain sites.35 Also, in line with previous observations in twin studies,82 headaches demonstrated the smallest genetic correlations with any other chronic pain site, suggestive of distinct pathophysiology relative to other chronic pain conditions. Furthermore, genetic correlations between chronic pain and other comorbid conditions have been reported. Psychiatric phenotypes showed the strongest genetic correlations, including depressive symptoms, neuroticism, anxiety, schizophrenia, and posttraumatic Importantly, an analysis that between identified an of chronic multisite pain on major depressive but not the other genetic correlations with chronic pain include immune and These results a molecular genetic for pain-related previously by epidemiological analyses of GWASs of pain conditions have also provided For both back and multisite the genetic correlation between and association results were and the of statistically significant different between and the these results suggest that the genetic mechanisms contributing to chronic pain susceptibility are by and the other the results suggest that different pathways contribute to pain with different relative in a have been in these 2 studies to on the of identified the relative of in pain mechanisms to be identified in animal models, and further in identifying genetic are In it will be to not only at the but also at the pathway, and even at the tissue level as Furthermore, have been from the analyses of with analyses of the in their in analyses may more insights pain Finally, many more genetic are to be for a understanding of pain. polygenic have to the at or of genetic loci a single The are not only for and but also for the genetic of the also has a of in the of pain and in the development of conditions. there are also interactions between and which are to using For pain, to known to the nervous or immune and of any are of particular At the level of the single even a for response was for and large cohorts have on of but arguments for of have been in GWAS in or in of pain phenotypes of gene expression at the level of all expressed in a was first demonstrated in by et using a method that allowed on date back to the by the development of human sequencing at the of the an approach to acid or in a high-throughput was which is usually to as for Although both the approach has many of gene expression data from pain phenotypes in the Gene indicated the of in pain-relevant with the toward as gene expression analysis at the level of the single in a particular called single even more is the that gene not only at the level of but also at the level via sequencing of or The of analyses as a for direct or is suggested by their highly the method is to and gene studies have human characterized for pain conditions at the level in with the level DNA that the only tissue for human not to pain conditions. 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