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Plasma measurements using ponderomotive forces to perturb the translational motion of particles. Candidate gene studies in humans with chronic pain have been unconvincing, and confirmed candidate gene associations are still lacking reviewed in [4] and [7]. Two hypotheses were tested; that a single rare variant having large effect influences pain sensitivity and that the burden of variation would differ between sensitive and insensitive individuals.

Attempts to standardise and quantify pain sensibility in humans have led to the introduction of standardised thermal, mechanical or chemical stimuli that activate the nociceptive pain signalling system. Such quantitative sensory testing QST has been used to show that an individual's sensitivity to experimental pain predicts risk of developing chronic pain after surgical interventions such as hernia repair [8] and arthroscopy [9]. That pre-operative pain sensitivity is a major risk factor for chronic post-operative pain suggests that exploration of genetic variation underlying experimental pain might be a useful approach.

The pain stimulus, its site of application and methods of rating have all been standardised - unlike spontaneous pain in a disease state. A further benefit is that the genetic influence on pain sensitivity is studied, rather than its influences on disease and disease progression. In the present study, we sought to determine whether rare variants associate with extremes of pain sensitivity in healthy volunteers. Using heat as the stimulus for QST in a large sample of healthy twin volunteers www.

Our initial analysis sought to identify genes harbouring single nucleotide variants SNVs in either pain sensitive or insensitive subjects, with a focus on non-synonymous exonic and nonsense mutations. A large number of methods have been proposed for such an analysis [40] — [44]. We employed a battery of such tests including both old and new techniques, as well as tests examining a range of hypotheses; a difference between pain groups sensitive vs. We found no single rare variant to have a statistically significant association to heat sensitivity, after multiple testing correction. The strongest signal was found for GZMM, a serine protease from immune cell granules.

However, our network analysis identified up to 30 genes harbouring rare SNVs as belonging to the Angiotensin II pathway, which has previously been linked to the pain phenotype in a number of settings. Singleton females were drawn from same sex twin pairs included in the sample so that gender- and relatedness bias were removed; after quality control all subjects were of north European descent. Details of the study participants are shown in Table 1.

Details of the SNVs identified in the 2 datasets are shown in Table 2. The TUK2 set identified more variants of all types except partial codons, which were extremely infrequent , which likely reflected the different exome capture arrays used and was consistent with greater coverage captured for the TUK2 set. Results of comparison between the 21 tests for analysing rare variant association were represented using a heat map correlation matrix, Table S2. Using these 6 methods we identified genes containing variants associated with pain sensitivity, shown in Table 3 ranked by strength of evidence.

Of the 20, exonic gene regions tested, 17, from 14, unique genes gave consistently non-missing p-values across the 6 selected variant burden tests. Individuals insensitive to heat pain manifested rare variants more frequently than the sensitive, across GZMM Figure 2. Finally, the distribution of variants differed between the pain insensitive and sensitive groups, with the pain insensitive showing a relative enrichment of rare variants Figure S2.

Subject counts in blue are for pain insensitive subjects and in red, pain sensitive. Squares represent homozygous and ovals heterozygous mutations. Exons are shown as dark cylinders, UTRs pale grey rectangles and introns dotted line. The 2 nd lowest p-value among 6 gene-centric variant burden tests was used as a cut-off to prioritise genes for pathway analysis see Methods, statistical analysis.

Nine high level GO terms were nominally significantly enriched in the gene list eg. None reached significance after multiple testing correction or offered obvious insights into mechanisms of altered pain sensitivity results not shown. We applied causal reasoning to our data [11] , which uses a large curated database of directed regulatory molecular interactions to identify the most plausible upstream regulators of a gene set. Of the genes 86 were present in our database of causal interactions, from which we identified 4 nominally significant regulatory networks Table 4.

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One of the regulatory networks, angiotensin II Figure 3 , was highly enriched for a pain signal with 12 out of genes in the network also in the set of 86 genes with a nominal genetic burden. This yields an odds ratio of 7. Causal reasoning uses directed molecular interactions to work upstream from the genes in this study green to identify regulators such as angiotensin II blue that have a causally correct regulatory role for a significant number of input genes. Correctness is determined by giving each input gene a direction of effect.

Here, we presumed a loss of function e. Angiotensin II has direct causal connections to 12 of the genes from our , which can be increased to 30 if one intermediary node is allowed in the network Figure S1. We also investigated whether the genes identified were known to interact physically with proteins playing a role in pain. For this we used the BioGrid database of protein-protein interactions. Notable connections included the binding of synaptotagmin-9 SYT9 , a membrane trafficking protein activated by calcium, to TRPV1, the capsaicin receptor, which plays a key role in thermal nociception [12].

The extracellular matrix glycoprotein laminin B1 chain LAMB1 interacts with the voltage dependent calcium channel Cav2. Here the calcitonin receptor recognises the calcitonin gene related peptide CGRP , a hormone proposed to contribute to pain transmission and inflammation [14]. Patients with chronic pain have increased sensitivity to noxious stimuli such as heat and pressure compared to controls [19] as well as to non-noxious stimuli such as sound [20]. These observations support the notion that the processing of external stimuli is heightened or exaggerated in chronic pain states.

Thus, people harbouring gene variants associated with greater sensitivity to heat pain stimulus are thought to be at increased risk of developing chronic widespread pain. The premise of this work was that understanding better the genetic influence on normal pain processing would shed light on the biological pathways underlying the pathology of chronic pain.

In this project we adopted novel methods - biotechnological and statistical - to identify rare sequence variation contributing to pain sensitivity in normal individuals. The advent of high throughput genotyping technologies has helped to unravel the aetiology of many complex diseases and quantitative traits. In particular, genome-wide association GWA studies have uncovered many common variants associated with quantitative phenotypes. However, GWA is underpowered to detect association of rare variants, and the common variants identified so far explain only a fraction of the trait heritability.

As whole-genome sequencing has become more cost-efficient it is now feasible to examine the effect of rare variants. The hypothesis that multiple rare variants explain a proportion of the missing heritability is gaining more attention [21]. Rare variants with moderate to high penetrance have been associated with a number of extreme phenotypes summarised in [22]. For quantitative phenotypes, sampling and comparing the extremes of traits has become an accepted strategy for identifying disease-causing rare variants in exome sequencing [23].

In this novel exome project of pain perception in normal individuals, no genetic variants of large effect were identified. Considering that the statistical power after applying stringent multiple test correction was limited, we can't exclude moderate or small contributions by individual SNVs to the experimental pain phenotype. Indeed, we have noted a differential distribution of rare variants between the pain sensitive and insensitive subjects Figure S2 , which suggests enrichment of multiple SNVs of small effect at the extremes of the normal distribution.

This study also provides proof of principle of the utility of the exome sequencing method.

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Such an approach has been used successfully in the, albeit more limited, setting of sequencing ion channel genes in epilepsy [24]. The authors highlighted the need for cell and network analysis to optimise information obtained from such a study. A variety of statistical methods have been developed for analysis of association of rare variants with complex traits, but there remains a paucity of data regarding the genetic architecture underlying complex traits such as pain perception.

For this reason we elected to use a variety of tests based on different underlying assumptions so that no rare variant associated with pain perception would be missed. It encodes granzyme M, one of the serine proteases produced and stored in the granules of immune cells such as lymphocytes and natural killer cells [25]. While we could not find reports of association with pain in the literature, granzymes are known to play an important role in apoptosis [26] and in the initiation of inflammation: elevated levels have been detected in rheumatoid synovial fluid [27] and granzyme B expression increased in lesional atopic dermatitis skin [28].

Although both anti-nociceptive and pro-nociceptive roles of NO have been reported, overproduction of NO - together with free radicals - contribute to central sensitisation and the pathogenesis of abnormal pain states via association with NMDA receptor mediated signalling events.

In support of this, circulating NO has been shown to be elevated in chronic widespread pain patients [29]. To explore further the interplay between the SNV-containing genes identified we applied causal reasoning, an algorithm using directed molecular relationships between biological entities to identify up-stream regulators of a set of input genes [30]. Angiotensin II is a peptide hormone involved in the control of blood pressure.

This network connected 12 of our identified genes into a causal network Figure 3. Angiotensin II has been already been implicated in central pain: it has been shown to facilitate pain-related behaviours in experimental animals [31] including responses to thermal stimuli similar to those employed in the current studies.

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The mechanism appears to be via the modulation of descending brainstem pathways. Blocking the receptors for angiotensin II so called AT1 receptors reverses some pain-related behaviours in models of chronic pain, suggesting a role for endogenous angiotensin II. For example, AT-1 receptor antagonist telmisartan has been shown to abrogate pain in the sciatic nerve constriction model in rats [32].

Our causal reasoning analysis allowed for only one interaction upstream of the genes in our dataset to be included. However, allowing two interactions increased the number of genes from this study that may be causally linked to angiotensin II to 30 genes. Angiotensin II can also be causally linked to known pain relevant processes. This leads to post-translational modification of several target proteins within nerve terminals that regulate nociceptor excitability, including voltage-gated sodium channels [36].

The current study using novel exome sequencing methods supports the notion that the angiotensin II pathway is important in pain regulation in man and suggests that genetic variation in the pathway may influence sensitivity to heat pain, at least in the Northern European population. A third form of analysis examined the target genes in a network of all human protein-protein interactions from the BioGRID database. We asked if any of the proteins encoded by the genes identified in this study were known to interact directly with proteins having a role in pain.

We found known physical interactions with several pain-relevant proteins including ion channels TRPV1 and Cav2. It is clear therefore that although we did not identify any genes immediately associated with nociception, several play key roles in processes linked to the reception and transduction of pain signals by their physical and biochemical interactions with important pain mediating complexes. This study highlights the potential of using a combination of sophisticated analytical methods to identify associations underlying rare variants in quantitative traits.

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