FROM:
Science Translational Medicine 2022 (May 11); 14 (644): eabj9954
Marc Parisien, Lucas V Lima, Concetta Dagostino, Nehme El-Hachem, Gillian L Drury, et. al.
Faculty of Dental Medicine and Oral Health Sciences,
Department of Anesthesia, Faculty of Medicine,
Alan Edwards Centre for Research on Pain,
McGill University,
Montreal, Quebec H3A 1G1, Canada.
Editorial Comment:
This novel new study suggests that prolonged NSAIDs use may be a cause of persistent pain. The authors stated:
"Analysis of pain trajectories of human subjects reporting acute back pain in the UK Biobank identified elevated risk of pain persistence for subjects taking NSAIDs. Thus, despite analgesic efficacy at early time points, the management of acute inflammation may be counterproductive for long-term outcomes of LBP sufferers."
|
FROM: Pain Research Forum
Neutrophils Put the Brakes on Acute Pain Becoming Chronic
Neutrophils help prevent the transition from acute to chronic pain after injury.
Dampening their activity with anti-inflammatory drugs, like ibuprofen or diclofenac, can prolong pain duration.
by Fred Schwaller on 25 May 2022
|
In the last few weeks, several news outlets like The New York Times and The Guardian have published provocative stories warning their readers that taking analgesics, like ibuprofen, can lead to the development of chronic back pain.
These articles relate to new research from an interdisciplinary team led by Luda Diatchenko and Jeffrey Mogil at McGill University, Canada, and Massimo Allegri at the Pain Therapy Service in Monza, Italy.
The new study was published in Science Translational Medicine on 11 May 2022.
The study shows that neutrophils drive a transient anti-inflammatory response that is protective against the transition from acute to chronic pain. Data in patients with low back pain (LBP) show that an anti-inflammatory immune response driven by neutrophils early after injury facilitates pain resolution.
The study goes on to show that inhibiting inflammatory responses after injury with non-steroidal inflammatory drugs (NSAIDs), like diclofenac, but not analgesics like gabapentin or morphine, prolongs pain resolution in rodents. Moreover, LBP patients who regularly take NSAIDs were almost twice as likely to develop chronic pain than those who did not.
“The media interpretation of this paper is that you shouldn’t take NSAIDs after injury, but this totally misses the exciting point of this paper. The take-home message is really that neuroimmune interactions, via neutrophils, act early after acute injury to resolve pain. From a therapeutic perspective, we can look to exploit that mechanism to help people stop transitioning [from acute] to chronic pain,” offered Ted Price from the University of Texas at Dallas, US, who was not a part of the study.
Gene expression changes drive pain recovery
The mechanism through which acute pain transitions to chronic pain, and how to stop it, is one of the biggest questions in pain research. Initially, Diatchenko and her colleagues set out to use transcriptomics to understand how a subset of patients with acute LBP develop chronic pain, while other people’s pain is resolved.
This initial study compared the transcriptomic analysis of blood samples in two groups of LBP patients – those who developed chronic pain, and those who recovered. Patients were separated into these two groups based upon their pain scores at the time of their first acute LBP episode, and their follow-up visit three months later.
The team then assessed the genome-wide transcriptomic differences in the blood samples of these two patient groups.
“We didn’t know what transcriptional differences we would find between these patient groups, but we thought we might identify a set of genes with increased expression among patients who developed chronic pain,” said first author Marc Parisien.
In fact, this transcriptomic analysis showed something completely different.
“We found that it was these patients with resolved pain that had all of the gene expression changes, not those [patients] who developed chronic pain. This was totally unexpected,” said Diatchenko.
When comparing gene expression changes from the initiation of acute pain to three months later, the team found no differentially expressed genes in these chronic pain patients. Conversely, recovered patients had more than 5,500 genes with a differential expression between the two timepoints.
“The transcriptomics data are very robust. If you dive into the dataset, there’s a lot of very interesting stuff about the immune response in pain recovery – a lot to keep the field busy,” said Price.
Neutrophils are the key to pain recovery
These data showed that the active regulation of biological processes was stimulating this recovery from an acute LBP episode, preventing the transition to chronic pain. However, which cell types, which molecular pathways, and which genes were being upregulated?
First, the team estimated the changes in cell-type populations from their transcriptomics data. They found that a variety of immune cells decreased over time, and the decline of neutrophils was the most prevalent.
Next, analyzing changes among biological pathways, as opposed to individual genes, allowed the team to detect which cellular processes were likely driving pain recovery. The most differentially expressed pathways among recovered patients were those related to cell activation and immune responses. Specifically, degranulation pathways driven by neutrophil activation displayed the largest changes in expression.
“Nobody thought much about neutrophils when we were starting this research. Neutrophils seem to be critically important at the very beginning of a pain episode to initiate the healing process. We don’t know the entire process yet, but we think it’s so massive that the whole immune system is involved,” commented Diatchenko.
Elucidating this mechanism further, the authors identified several individual genes that showed the largest changes in expression. Among these genes, S100A8 and S100A9 were the team’s top hits. In support of their findings to this point, S100 genes are neutrophil-specific, and critical for the development and regulation of inflammation.
After these initial findings, the team persisted, and they also replicated these findings in a group of patients with temporomandibular pain, another subset of musculoskeletal pain.
Anti-inflammatory drugs block pain recovery in mice
With these findings in hand, the team began to formulate another hypothesis – if neutrophil-mediated anti-inflammatory responses are important for pain recovery, would the inhibition of this pathway lead to a prolonged pain state? More specifically, could anti-inflammatory drugs actually be driving chronic pain, instead of helping to alleviate it?
Diatchenko began to collaborate with Mogil to further investigate this hypothesis in animal models. Here, they tested whether the steroidal drug dexamethasone, and the NSAID diclofenac, delayed recovery post-injury in mice.
Dexamethasone or diclofenac was administered daily for six days following tissue inflammation (via injection of complete Freund’s adjuvant), and mechanical withdrawal thresholds were recorded as a measure of post-inflammatory pain.
As expected, dexamethasone and diclofenac caused moderate analgesia in the first six days after inflammation; however, the drugs also delayed recovery to baseline. Control animals took, on average, ~40 days to recover following initial inflammation. However, this recovery took ~80 days for those groups treated with anti-inflammatory drugs. The same results were also found by using a nerve injury model and a model of low back pain.
Importantly, this protracted pain state was only caused following the administration of the anti-inflammatory drugs dexamethasone and diclofenac, but not gabapentin, lidocaine, or morphine, all of which cause analgesia through other mechanisms.
NSAID usage linked to chronic pain
In a final set of experiments, the authors sought to validate these preclinical findings in a human cohort. To accomplish this, they examined the relationship between analgesic drug utilization and LBP in a large human study from the UK Biobank project.
They found that individuals who used NSAIDs to treat acute back pain were 1.76-fold more likely to develop chronic pain. While this is correlational data not performed in a randomized controlled trial setting, it nevertheless links NSAID use with chronic pain in patients.
Diatchenko was keen to point out a common criticism of this data – that those who suffer from chronic pain take a lot of NSAIDs. In that case, pain would be predictive for medication, rather than for the NSAIDs resulting in prolonged pain.
“We showed that non-anti-inflammatory drugs, like paracetamol and anti-depressants, weren’t linked with chronic pain. This suggests that downregulating the anti-inflammatory immune response drives chronic pain,” said Diatchenko.
NSAIDs still clinically useful – for now
“Do our data mean that there will be no NSAIDs, under any circumstances, ever again? No, we’re not saying that. Our data clearly imply [NSAIDs] are a double-edged sword in treating pain, but we need to do large, randomized controlled trials before making any medical recommendations,” Mogil told PRF.
Diatchenko and Allegri were also keen to stress that this paper does not come with any medical recommendations.
“It’s crucial that we understand the mechanism and timing of this neutrophil-mediated recovery. This would determine if, or when, we can give NSAIDs outside of this recovery window to still cause analgesia, but not prolong pain. We’re beginning some large-scale, randomized controlled trials to test this,” said Allegri.
However, Mogil was less optimistic about the future of NSAIDs as frontline analgesics.
“The data imply what they imply: NSAIDs have a negative effect on pain recovery. Once the results from trials are in, I would guess the days are numbered for NSAIDs, at least in their current context,” Mogil said.
How do neutrophils drive pain recovery?
Diatchenko was also eager to point out that the important findings in this paper have been overshadowed by press coverage regarding their NSAID data.
“When this paper came out, everyone concentrated on how you shouldn’t use NSAIDs to treat pain, but they didn’t think about the novel mechanism of pain relief we found. This paper tells us that if you upregulate the immune response to target acute pain, you could prevent chronic pain from developing,” Diatchenko said.
Price agreed, stating how this research opens up new possibilities for the pain research field.
“This paper paints a very clear picture that early neutrophil activation is very important for preventing the sensitization of pain pathways. [The authors] lay out a beautiful roadmap to explore this. I would want to know how S100A8 and S100A9 are eventually acting on neurons to resolve pain, and how we could exploit neutrophils in other ways to decrease the excitability of neurons in pain pathways,” said Price.
Fred Schwaller, PhD, is a freelance science writer based in Germany.
Featured image: Cover art for Science Translational Medicine – Volume 14, Issue 644, 11 May 2022.
Credit: Marjanovic and Tomic-Canic et al./Science Translational Medicine
References:
Parisien M, Lima LV, Dagostino C, El-Hachem N, Drury GL, Grant AV, Huising J, Verma V, Meloto CB, Silva JR, Dutra GGS, Markova T, Dang H, Tessier PA, Slade GD, Nackley AG, Ghasemlou N, Mogil JS, Allegri M, Diatchenko L
Acute Inflammatory Response via Neutrophil Activation Protects Against the Development of Chronic Pain
Sci Transl Med. 2022 May 11; 14(644):eabj9954.
|
The Abstract:
The transition from acute to chronic pain is critically important but not well understood. Here, we investigated the pathophysiological mechanisms underlying the transition from acute to chronic low back pain (LBP) and performed transcriptome-wide analysis in peripheral immune cells of 98 participants with acute LBP, followed for 3 months. Transcriptomic changes were compared between patients whose LBP was resolved at 3 months with those whose LBP persisted. We found thousands of dynamic transcriptional changes over 3 months in LBP participants with resolved pain but none in those with persistent pain. Transient neutrophil-driven up-regulation of inflammatory responses was protective against the transition to chronic pain.
In mouse pain assays, early treatment with a steroid or nonsteroidal anti-inflammatory drug (NSAID) also led to prolonged pain despite being analgesic in the short term; such a prolongation was not observed with other analgesics. Depletion of neutrophils delayed resolution of pain in mice, whereas peripheral injection of neutrophils themselves, or S100A8/A9 proteins normally released by neutrophils, prevented the development of long-lasting pain induced by an anti-inflammatory drug. Analysis of pain trajectories of human subjects reporting acute back pain in the UK Biobank identified elevated risk of pain persistence for subjects taking NSAIDs. Thus, despite analgesic efficacy at early time points, the management of acute inflammation may be counterproductive for long-term outcomes of LBP sufferers.
From the FULL TEXT Article:
INTRODUCTION
Chronic pain inflicts huge societal costs, in terms of management, loss of work productivity, and effects on quality of life. [1] Chronic low back pain (LBP) is the most frequently reported chronic pain condition. [2] LBP is a major problem worldwide: point, 1-month, and 1-year prevalence is 18, 31, and 38%, respectively. [3] LBP ranks the highest of all chronic conditions in terms of years lived with disability, with its prevalence and burden increasing with age. [4] Current treatments for LBP often target the immune system and include nonsteroidal anti-inflammatory drugs (NSAIDs), acetaminophen, and corticosteroids, although all of these drug classes are minimally effective at best. [5] Despite advances in the understanding of social, psychological, and genetic factors, as well as brain processes associated with chronic LBP [6], we understand very little of the molecular mechanisms underlying the acute-to-chronic pain transition that might lead to more efficacious analgesic strategies.
Previous human genetic association studies and transcriptomic analysis of chronic LBP have been performed using candidate gene and genome-wide approaches, and they have provided evidence for the involvement of a variety of genes in many biological pathways. [7–11] Increasing evidence suggests that the pathophysiology of chronic pain involves a complex interplay between the nervous and immune systems; that is, chronic pain is a neuroinflammatory disorder mediated by neuronal and non-neuronal cells alike. [12] Circulating immune cells such as neutrophils, monocytes, and T cells are recruited to sites of tissue damage and/or inflammation and often also infiltrate the peripheral and central nervous systems. [13, 14]
Activation of these cells results in the expression of various inflammatory mediators, including cytokines/chemokines, lipids, and proteases, that act both directly on peripheral sensory or central second order neurons and indirectly on other immune or local cells to regulate pain. Microglia and astrocytes in the central nervous system act in a similar fashion, contributing to central sensitization and pain. [15–18] The presence of these activated immune cells and glia, peripherally or centrally, is thought to contribute to the transition from acute to chronic pain. [19–21]
Here, we used transcriptome-wide data to investigate the molecular pathophysiological mechanisms in peripheral blood immune cells at the transcriptome-wide level that underlie the transition of acute to chronic LBP, and we identified the protective effect of acute inflammatory responses against the development of chronic pain. We replicated our finding in an independent cohort of patients with another musculoskeletal pain condition, temporomandibular disorder (TMD). We then used rodent pain models to elucidate the mechanism mediating the transition from acute to chronic pain. Last, we analyzed a large human cohort (UK Biobank) to investigate the relationship between back pain and the use of anti-inflammatory drugs.
RESULTS
Differential gene expression in the LBP cohort
We assessed genome-wide transcriptomics in a cohort of 98 patients with LBP at the acute episode (t0) and a follow-up visit (t1) 3 months later. Study design, demographics, and patient characteristics are presented in
Figure S1 (A and B) and Table S1, and transcriptomics statistics are presented in Table S2. Patients reported substantial, self-declared pain [0 to 10 numeric rating scale (NRS)] in their lower back at enrollment (t0: mean = 6.8, SD = 1.8, min = 4, and max = 10), but a much broader pain spectrum was observed at follow-up (t1: mean = 3.2, SD = 3.2, min = 0, and max = 10). We dichotomized study participants into two groups based on their pain scores at the second visit: those with resolved pain (“R”; n = 49) and those with persistent pain (“P”; n = 49) (Figure S1B). No differences were found on the pain outcome with drug classes either consumed between the clinical visits or used prophylactically (Table S1).
Figure 1
|
We then tested differences between patient groups at the transcriptomics-wide level. At the first visit, there were no differentially expressed genes that reached genome-wide statistical significance between R and P patients (Figure 1A, column “uncorrected,” and Table S3A). By the time of the second visit, more than 1700 differentially expressed genes were detected at the genome-wide scale between R and P patients (Figure 1B and Table S3B). When time trajectories were considered, contrasting gene expression between the two visits in P patients identified no differentially expressed genes (Figure 1C and Table S3C), whereas in R patients, more than 5500 genes were differentially expressed (Figure 1D and Table S3D). This pattern remained after controlling for blood cell-type abundances, when we repeated analyses of differential expression of genes using estimated fractions of cell-type populations as additional covariables. [22] A total of 1700 genes remained differentially expressed in those with resolved pain, whereas in those with persistent pain, there were still no changes (Figure 1, column “corrected,” and Table S4). Together, our genome-wide transcriptomics analyses suggest that the subjects who resolved pain over time have an abundance of active biological processes underlying recovery and these processes are partially driven by changes in blood cell composition.
Differential blood cell-type populations
Figure 2
|
We next estimated the changes in relative cell-type population fractions from our multiplexed RNA sequencing experiments [22], tracking cell-type population changes in different contrasts (Figure 2A and
Table S5). In P participants, we did not detect any changes in blood cell-type populations over time (Figure 2, column I). However, in R patients, we found statistically significant differences between the two visits in four cell types, with the largest difference observed in the numbers of neutrophils decreasing over time (P = 1.4 × 10-3; Figure 2B). The other significant differences included increased number of CD8+ T cells (P = 1.5 × 10-3; Figure 2C) and resting natural killer cells (P = 1.7 × 10-3; Figure 2D) and decreased number of resting mast cells (P = 4.4 × 10-2; Figure 2E).
We also built a list of genes expressed by each cell type using CIBERSORT’s LM22 “pure” cell-type expression matrix. A gene was retained in the list if the expression level in that cell type was greater than the average across all other cell types (Figure 2A and Figure S2). These genes are highlighted for differential expression in the volcano plots (Figure 2, column III). Thus, changes in cell-type fractions can be tracked down to changes in gene expression, with matching change directions between fraction estimates and gene levels, with, again, the largest, most consistent, and most substantial contribution from neutrophil-specific genes down-regulated between visit t0 and t1.
Pathway analyses
Figure 3
|
We next analyzed biological pathways instead of individual differentially expressed genes (Figure 3 and Table S6). We found many biological pathways differentially expressed at a genome-wide level even in the comparisons where no individual genome-wide significant differentially expressed genes were identified, which can occur when a substantial amount of genes of the same pathway change expression in the same direction. Because we observed that active transcriptional processes underlay pain recovery over time, we focused on biological pathways at the acute stage that will yield the follow-up changes.
At the first visit (t0), the most differentially expressed pathways were related to cell activation and immune responses, and they were elevated in the R group. These processes seemed to be driven by neutrophil activation and degranulation, and by elevated inflammatory response. Although some of the leading-edge genes are shared between these two pathways, for the most part, they describe two different biological processes (Figure S3). This unexpected enhanced inflammatory response in R participants was consistently observed for other related inflammatory pathways (A, column I, and Table S6, A and B). With time, there were barely any changes in the inflammatory response pathways in the P group (Figure 3A, column III, and Table S6, E and F). However, in the R group, the inflammatory response pathways were convincingly down-regulated over time, at t1 compared to t0 (Figure 3A, column IV, and Table S6, G and H).
The enhanced inflammatory pathways seemed to be driven by neutrophil activation through degranulation. We found leukocyte activation and degranulation pathways noticeably activated at t0 in R patients. Among leukocytes, neutrophils were the most activated, followed by macrophages and mast cells (Figure 3B, column I, and Table S6B). Degranulation of neutrophils showed the largest changes compared to platelet or natural killer cells (Figure 3C, column I, and Table S6B). Neutrophil activation and degranulation pathways were decreasing with time in both pain groups, although this decrease was more noticeable in R compared to P patients (Figure 3 and Table S6). The key molecules contributing to this dynamic regulation of cellular responses, with the largest expression at the acute stage and the fastest down-regulation by the second visit in the R group, are presented in Table S7. Within the top hits, we found SLC11A1, a divalent metal transporter that is specific to myelomonocytic cells including neutrophils, monocytes, and macrophages (23, 24), and S100A8 and S100A9, neutrophil-specific genes coding for calcium-binding “alarmins” critical in the development and regulation of inflammation, which are known to comprise about 45% of the cytoplasmic proteins in neutrophils and function as homo- or heterodimers (25).
We found a positive correlation in transcriptional changes over time between R and P patients (Figure S4 and Table S6), indicating that all individuals displayed similar biological responses and pathways, regardless of the pain outcome at the second visit (slope = +0.57, P < 2.2 × 10-16, r2 = 42%). The difference between groups was in the magnitude of the response: The R group response intensity was about 75% larger than that of the P group.
Replication of findings in an independent cohort
We replicated our findings using a prospective cohort of similar design (Figure S5A). The replication cohort comprised subjects with another musculoskeletal pain condition, TMD. Although the pathophysiology of TMD is likely not identical to LBP, we hypothesized that the active contribution of the immune system in the transition to chronic pain could be shared. At the first visit, all subjects displayed acute symptoms of TMD, whereas at a second visit, some subjects had their pain resolved (R), and in others, pain persisted (P). In this cohort as well, we observed a larger number of differentially expressed genes in subjects in the R group than in the P group (Figure S5, B and C) and elevated activity of inflammatory and neutrophil activation and degranulation pathways in the R group (Figure S5D and Table S8). From CIBERSORT’s gene expression input matrix, we identified 100 genes whose expression in neutrophils is greater than the average across all other cell types. At t0, we found 80% of these genes to be more expressed in the R group in both LBP and TMD cohorts (Table S8G) and about 75% of these genes to be more expressed at t0 than t1 in the resolved pain group, in both LBP and TMD cohorts (Table S8H).
In addition, the TMD cohort allowed comparison with healthy controls and patients with chronic TMD (Figure S8 and Table S8I). In comparison with healthy controls, the R group displayed a significantly higher inflammatory response at the acute stage [fgsea pathway enrichment score (ES) = +0.32 > 0, P = 1.1 × 10-5], whereas the P group displayed a significantly lower response (ES = -0.32 < 0, P = 1.3 × 10-7). By the time of the second visit, each pain group displayed a significantly reduced inflammatory response compared to the healthy group (P = 3.1 × 10-4 in R and P = 1.1 × 10-7 in P). The same pattern was observed for neutrophil activation and degranulation pathways.
We also observed up-regulated neutrophil activation and degranulation pathways in subjects with chronic TMD in comparison with healthy controls (ES = +0.19 > 0, P = 1.9 × 10-2 and 3.3 × 10-2, respectively; Figure S6), although to a lesser degree than for the R group at t0 (ES = +34 > 0, P = 4.6 × 10-7). These results indicate the importance of the up-regulation of inflammatory response at the acute stage of musculoskeletal pain as a protective mechanism against the development of chronic pain.
Impaired inflammatory response prolongs resolution
of painful behavior in preclinical assays
Our human transcriptomics results suggested that active inflammatory responses, particularly those regulated by neutrophils, contribute to pain resolution. We hypothesized that inhibition of this active immune response will lead to the prolongation of pain and designed experiments to test this hypothesis in mice using pain assays featuring evidence of pain that is persistent but of finite duration.
Figure 4
|
Initial experiments used the classic steroidal anti-inflammatory drug, dexamethasone. Mechanical pain sensitivity was assessed before and at multiple time points after chronic constriction injury (CCI) of the sciatic nerve, injection of nerve growth factor (NGF) into the muscles of the low back, or inflammatory injury using the cell-mediated immunity stimulator, complete Freund’s adjuvant (CFA; inactivated Mycobacteria tuberculosis in oils). Dexamethasone or saline vehicle was administered daily for 6 days after CCI or CFA. All three injuries produced mechanical allodynia, that is, hypersensitivity to the evoking mechanical stimulus, lasting about 30 to 60 days (depending on the assay) in saline-treated mice, respectively (Figure 4, A, D, and G). We observed that the steroid had no effect on hind paw allodynia at the end of the treatment period after CCI (t11 = 0.5, P = 0.63; Figure 4B), as might be expected given that CCI does not produce hind paw inflammation. By contrast, dexamethasone produced robust inhibition of allodynia from NGF (t10 = 2.4, P = 0.04; Figure 4D) and CFA (t13 = 3.0, P = 0.009; Figure 4H) on day 6 after injection. However, dexamethasone delayed the recovery to baseline after CCI (t11 = 2.3, P = 0.04; Figure 4, A and C), NGF (t10 = 2.5, P = 0.03; Figure 4, D and F), and CFA (t13 = 2.7, P = 0.02; Figura 4, G and I) such that the duration of the overall pain episode was increased by the steroid treatment, by twofold on average after CFA. To assess whether it was the anti-inflammatory or purely analgesic actions of dexamethasone that were responsible for this prolongation, we tested four other drugs: the NSAID diclofenac, and three analgesics with no known anti-inflammatory action, systemically administered gabapentin and morphine, and peripherally administered lidocaine. All four drugs reduced allodynia during their administration period (F4,49 = 6.1, P < 0.001; Figure 4, J and K), but only diclofenac significantly prolonged the duration of the overall allodynia episode produced by CFA (F4,49 = 7.5, P < 0.001; Figure 4, J and L). Diclofenac was also able to prolong the duration of CCI-induced allodynia (t13 = 3.0, P = 0.01; Figure S7).
Figure 5
|
To directly assess the hypothesis that neutrophils are responsible for these effects, we performed two complementary experiments. First, we depleted neutrophils using an anti-Ly6G antibody, which causes specific but incomplete depletion. [26] Whereas acute depletion of neutrophils using this antibody does not affect mechanical allodynia [27], prolonged administration of the antibody exacerbated allodynia (day 9: t10 = 2.4, P = 0.04; Figure 5, A and B) and prolonged its duration (t10 = 8.7, P < 0.001; Figure 5, A and C) in a fashion identical to that of dexamethasone. Next, we endeavored to determine whether the dexamethasone effect was neutrophil dependent by injecting neutrophils isolated from peripheral blood or the neutrophil-released proteins S100A8 or S100A9 into the hind paw (ipsilateral to CFA injection) of dexamethasone-treated mice. Neutrophil injection or injection of S100A8 or S100A9 prevented the development of allodynia entirely (comparison of dexamethasone-injected groups: F3,24 = 8.7, P < 0.001; Figure 5, D and E) despite the administration of dexamethasone. Note that this experiment, performed in a different laboratory, also serves as a direct replication of the data shown in Figure 4G. In the absence of dexamethasone, neither neutrophils nor S100A8/A9 significantly affected the duration of CFA allodynia (F15,130 = 1.1, P = 0.36; fig. S8). All reported mouse experiments were performed in both sexes, and no detectable interactions with sex were observed in any experiment (all P > 0.05).
Analgesic usage in human population studies
Figure 6
|
Finally, we examined the relationship between analgesic drug usage and back pain in a large human study from the UK Biobank project. We posited that drugs that inhibit inflammation might interfere with the natural recovery process, thus increasing the odds for chronic pain. To test this hypothesis, we compared several analgesic drug classes with available use information, including NSAIDs, paracetamol (acetaminophen), and antidepressants (Figure 6 and Table S9).
We found that individuals with acute back pain were at 1.76-fold greater risk of developing chronic back pain if they reported NSAID usage (P = 2.0 × 10-5) than if they were not taking NSAIDs, adjusting for age, sex, ethnicity, and time interval between measurements (model 1).
The increased risk for the development of chronic pain was maintained in the model that accounted for all drugs simultaneously [odds ratio (OR) = 1.78, P = 3.9 × 10-5; model 4].
No other analgesic medication category showed an association with the development of chronic back pain, either across models with the corresponding medication class variable adjusted for demographic covariates alone (models 2 and 3) or in the full model (model 4).
We then considered further potential confounders for the development of chronic pain. Measures of pain intensity and higher psychological distress at the acute stage are two factors that have been shown repeatedly to be associated with the development of chronic pain. [28, 29]
Because pain intensity was not collected in the full UK Biobank cohort, we used the number of reported chronic pain body sites as a substitute for chronic pain intensity. Although pain intensity and anatomical extent of pain sites are different phenotypes, they are highly correlated and have been used previously in this capacity. [30–32] When we adjusted our models using covariates that captured these potential confounders, all of the above observations held up, namely, a significantly elevated risk for chronic pain with NSAID usage (OR = 1.67, P = 3.0 × 10-4; model 5).
Last, given the identification here of the crucial role of neutrophils in inflammatory mechanisms implicated in pain outcomes, we tested across leukocyte subset percentages at the acute pain state for association with the development of chronic back pain later in life by adding this explanatory variable to the full model.
As expected, neutrophil percentage at the acute stage was inversely associated with chronic back pain
(OR = 0.98; P = 0.02) after adjusting for usage of medications (model 6).
DISCUSSION
This study was designed and implemented to identify cellular and molecular mechanisms underlying acute-to-chronic pain transition in humans using data from a cohort of subjects with LBP. Our initial bioinformatics results indicated that there was a substantial difference in the time courses of transcriptomic changes in subjects with resolved pain compared to those with persistent pain. The trajectories show substantial differences: In the resolved pain group, several thousand genes were found to be differentially expressed over time, whereas there were no differences in the persistent pain group. Thus, our data suggest that active biological processes protect from transitioning to chronic pain after an acute pain episode.
To identify the initial processes that drive these differences in trajectories between the resolved and the persistent pain groups at the gene level, we compared functionally related sets of genes at the pathway level. We found neutrophil activation–dependent elevation of the inflammatory response at the acute stage of pain in subjects with resolved pain, which was decreased by the time of the second visit. Conversely, subjects with persistent pain did not show any changes in their inflammatory response. We replicated these findings in an independent TMD cohort. The shared pathophysiology between different chronic pain conditions has been argued through both high clinical comorbidity and shared genetic heritability. [28, 33] The replication of our findings in the TMD cohort also suggests that our findings are likely to be applicable to other chronic pain conditions.
We did not identify any pathways with large negative correlations between the resolved and the persistent pain groups; the two pain groups showed strongly correlated processes. Instead, the difference between the two groups was in the magnitude of the regression slope, again suggesting that the resolved pain group’s response intensity was substantially larger than that of the persistent pain group. These results were in line with the observed differences in the number of differentially expressed genes over time between the groups, and reemphasized the perhaps counterintuitive concept that an active biological process underlies pain resolution rather than pain progression to chronic status. Our results suggest that this process is impaired in those who do not resolve acute pain over time and suggest time stratification of a cascade of processes resulting in a return to a normal, no-pain state [34] — in a fashion similar to timely processes involved in wound healing [35, 36] — and thus would require gene expression probing at many more time points to decipher the complete phenomenon of pain resolution. Nonetheless, our findings are in line with the observation that the beginning of the inflammatory process programs its resolution [34], and it is thus the failure to initiate an appropriate inflammatory response that may lead to chronic pain. This notion was further illustrated by our TMD cohort, which provided the advantage of the availability of a control no-pain group not available in the LBP cohort. We were able to confirm sharp up-regulation of neutrophil-related inflammatory response at the acute stage of the TMD pain-persisting group but not the TMD pain-resolving group and higher inflammatory states in patients with chronic pain.
Using three different assays of prolonged but resolving pain in the mouse, we confirmed that the acute treatment of inflammation with either the steroid dexamethasone, or the NSAID diclofenac, — although both effectively reducing pain behavior during their administration — greatly prolonged the resolution of neuropathic, myofascial, and especially inflammatory pain states.
Three analgesics without anti-inflammatory properties (gabapentin, morphine, and lidocaine) produced short-term analgesic effects without affecting the overall duration of the painful (allodynic) episode.
We further showed the neutrophil dependence of these effects, with steroid-like pain prolongation being produced by neutrophil depletion and a complete blockade of allodynia produced by peripheral injection of neutrophils themselves. Furthermore, our mouse data confirmed the important roles of two neutrophil-specific proteins identified via human transcriptomics data, the alarmin proteins S100A8 and S100A9.
Last, we validated the negative consequences of anti-inflammatory drugs in a large human cohort from the UK Biobank project. In human subjects who reported acute back pain, we found that NSAIDs but not two other analgesic medications available for analyses increased risk to still report back pain 2 to 6 years later.
Antidepressants were not associated with transition from acute to chronic pain despite the fact that patients who take antidepressants will generally have higher pain and higher psychological distress [37], two major risk factors for the development of chronic pain, in comparison with patients who take NSAIDs.
Furthermore, even after these two variables were included as covariates in all logistic regression models considered, our findings that NSAID use (but no other analgesic class) increases risk of subsequent development of chronic back pain did not change. Last, consistent with our bioinformatics and animal model results, higher percentages of neutrophils at the acute pain state protected against chronic pain development.
Our study has several limitations. First, the LBP cohort did not have control subjects without any pain, preventing the comparison of transcriptomes of people who resolved pain to those never experiencing pain. Second, we did not evaluate pain in the LBP cohort before or after the 3-month time point, so it is possible that some subjects in the persisting pain group saw their pain resolve after 3 months but before 6 months. To better understand the inflammatory and pain trajectories, a new study with more frequent pain ratings and blood sampling would be required. Furthermore, to test the long-term consequences of NSAID use with regard to chronic pain development, a clinical trial on patients with acute pain specifically designed to address the question is needed. Although we controlled for potential confounders in our UK Biobank analysis, we did not have access to many important details such as pain intensities at various body sites and drug dosing.
Together, our results suggest that active immune processes confer adaptation at the acute pain stage, and impairment of such inflammatory responses in subjects with acute LBP (or TMD) increases the risk of developing chronic pain.
These adaptive inflammatory responses are intrinsically transcriptionally driven, probably modified by both genetics and environmental factors, and can be inhibited by steroids and NSAIDs. These responses are transient, which is probably the main reason why they were previously overlooked. Our conclusions may have a substantial impact on medical treatment of the most common presenting complaints to health care professionals. Specifically, our data suggest that the long-term effects of anti-inflammatory drugs should be further investigated in the treatment of acute LBP and likely other pain conditions.
MATERIALS AND METHODS
Study design
The human LBP cohort is part of a larger study, PainOMICs, registered on clinicaltrials.gov (NCT02037763) and funded by the European Community in the Seventh Framework Programme (FP7)—THEME (HEALTH.2013.2.2.1–5—Understanding and controlling pain) to evaluate biomarkers related to pain. The protocol was approved by the Ethical Committee at the University Hospital of Parma (protocol number 43543; version 8). All patients signed a written informed consent before the enrolment and were followed up for 1 year.
The primary objective of this study was to investigate associations between genome-wide transcriptomics and the development of persistent chronic LBP in patients developing persistent chronic pain symptoms 3 months after an episode of acute LBP. Subjects enrolled in this study were a part of a larger protocol that follows the same design. For the current study, we retrospectively selected the first 50 patients with resolved pain and the first 50 patients with persistent pain. The patients were all Caucasian adults. Sample sizes were not estimated because of the hypothesis-free approach taken here, but our LBP cohort is similarly sized to other human transcriptomics studies in pain-identified group differences. [10, 39–42]
The criterion for enrollment was the presence of acute LBP, that is, pain between the costal margins and the gluteal fold. All patients were evaluated using an NRS, a scale to assess pain from 0 to 10, where 0 is “no pain” and 10 is “worst pain imaginable,” and the painDETECT Questionnaire [43] to evaluate the neuropathic pain component. Inclusion criteria included a back pain level of ≥4 on the NRS, with a duration of no more than 6 weeks before the first visit, thus defining an acute phase. Exclusion criteria were history (in the past 6 months) of persistent chronic or acute LBP episodes, recent history (<1 year) of spinal fracture, pain in the back due to spinal tumor or infection, evidence of clinically unstable disease, severe psychiatric disorder (excluding mild depression) or mental impairment, and pregnancy.
Each patient was classified by clinical evaluation and diagnostic blocks to determine the pain generator using these six classes: facet joint pain, sacroiliac pain, discogenic pain, spinal stenosis, back pain with predominant radiculopathy, and nonspecific LBP. [44] Patients were medically assessed and treated accordingly to physician’s decision, independently of the protocol. Drugs used and medical history were also recorded.
Clinicians followed a standardized protocol for treating acute LBP with drugs reducing acute inflammatory flare (NSAIDs and systemic steroids) plus opioids if the pain was severe and/or if it had a greater impairment on daily activity. The choice of drugs was driven only by clinical signs and not by any measures of inflammatory flare. Thus, all patients had the same treatment.
Patients were seen at two time points: at the time of enrollment (t0) and at a follow-up visit (t1) 3 months later. We defined the resolved pain group (R) patients as those who self-reported day-averaged pain of less than 4 on the NRS in the week before the follow-up visit; those reporting levels of 4 or higher were defined as the persistent pain group (P). The value of 4 was previously defined as an optimal cut point for “clinically significant” pain [45, 46], and in clinical practice, this cutoff is used to decide if pain may lead to functional and clinical disability and thus should be treated. The researcher who performed the laboratory analysis was masked to the group of patient analyzed.
Statistical analysis
Differential expression of genes in both LBP and TMD cohorts was assessed using moderated statistical tests implemented in the R statistical package DESeq2. [47] Each test was performed with the following covariables: sex, age, smoking status, and RNA Integrity number (RIN). Pathway enrichment scores were estimated using “fgsea,” with statistical significance assessed using a fast permutation scheme. [48]
The meta-analysis was performed using a sample size–based analytical strategy, following the formula proposed by METAL. [49] The sample sizes were n = 98 for LBP and n = 30 for TMD. For each pathway and study, the sign of the enrichment score combined with its associated P value was converted into a Z statistic. The overall Z statistic was obtained using a sample size–based weighted scheme. An overall P value was calculated from the overall Z.
Pain outcomes in the LBP cohort were regressed to blood cell-type fractions using the R statistical package function “glm,” using sex, age, and smoking status as covariables. Pain outcomes in the UK Biobank cohort were regressed to various drug classes and neutrophil fractions using the R statistical package function glm, individually and in combination, with age, sex, and ethnicity as covariables.
For transcriptomics, we relied on the false discovery rate (FDR) to correct for multiple testing because tests are not independent of one another. Significance levels are indicated in the text.
For animal experiments, a criterion α = 0.05 was used to determine statistical significance. Data were analyzed by Student’s t test or analysis of variance (ANOVA) followed by Tukey’s or Dunnett’s post hoc testing, as appropriate.
Supplementary Material
Figures S1-S8, Table S1 (1.1MB, pdf)
Table S2 (48.5KB, xlsx)
Table S3 (5.8MB, xlsx)
Table S4 (5.8MB, xlsx)
Table S5 (54.6KB, xlsx)
Table S6 (5.7MB, xlsx)
Table S7 (190.7KB, xlsx)
Table S8 (5.3MB, xlsx)
Table S9 (36.6KB, xlsx)
Acknowledgments:
We would like to thank all participants enrolled in this study through the Anesthesia, Critical Care and Pain Medicine Unit, Department of Medicine and Surgery at University of Parma. We also thank I. King for fruitful discussions. The current study was conducted under UK Biobank application 20802.
Funding:
This work was supported by Pfizer Canada Professorship in Pain Research (to L.D.); Canadian Excellence Research Chairs grant CERC09 (to L.D.); Canadian Institutes of Health Research grant 136975 (to P.A.T.); Canadian Institutes of Health Research Foundation grant 154281 (to J.S.M.); National Institute of Dental and Craniofacial Research grant R56DE025298 (to A.G.N. and G.D.S.); National Institute of Dental and Craniofacial Research grant U01DE017018 (to A.G.N., G.D.S., and L.D.); Canadian Institutes of Health Research grants PJT-173288, PJT-169671, and SCA-145102 (to N.G.); European Commission in the context of the Seventh Framework Program grant 602736 (to C.D. and M.A.); and Canadian Institutes of Health Research Strategy for Patient-Oriented Research in Chronic Pain grant SCA-145102 (to L.D.).
Competing interests:
L.D. was/is a consultant for Duke University, ONO PHARMA USA Inc., Releviate Inc., and Orthogen
AG. M.A. was/is a consultant for Health&RCB Srl and Clover Orthopedics Srl.
P.A.T. is a shareholder of InflammatoRx Inc., a company developing an anti-S100A9 drug for the treatment of inflammatory bowel disease.
All other authors declare that they have no competing interests.
References:
Gereau IV RW, Sluka KA, Maixner W, Savage SR, Price TJ
A pain research agenda for the 21st century.
J. Pain 15, 1203–1214 (2014).
Schopflocher D, Taenzer P, Jovey R,
The prevalence of chronic pain in Canada.
Pain Res. Manag 16, 445–450 (2011).
Hoy D, Bain C, Williams G, March L, Brooks P, Blyth F,
A systematic review of the global prevalence of low back pain.
Arthritis Rheum 64, 2028–2037 (2012)
GBD 2017 Disease and Injury Incidence and Prevalence Collaborators,
Global, 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 392, 1789–1858 (2018)
Chou R, Deyo R, Friedly J, Skelly A, Weimer M, Fu R, Dana T
Systemic Pharmacologic Therapies for Low Back Pain:
A Systematic Review for an American College
of Physicians Clinical Practice Guideline
Annals of Internal Medicine 2017 (Apr 4); 166 (7): 480–492
Vlaeyen JWS, Maher CG, Wiech K, Van Zundert J, Meloto CB,
Low back pain.
Nat. Rev. Dis. Primers 4, 52 (2018).
Freidin MB, Tsepilov YA, Palmer M, Karssen LC, Suri P
Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals.
Pain 160, 1361–1373 (2019).
Ramesh D, D’Agata A, Starkweather AR, Young EE,
Contribution of endocannabinoid gene expression and genotype on low back pain susceptibility and chronicity.
Clin. J. Pain 34, 8–14 (2018).
Starkweather AR, Ramesh D, Lyon DE, Siangphoe U, Deng X
Acute low back pain: Differential somatosensory function and gene expression compared with healthy no-pain controls.
Clin. J. Pain 32, 933–939 (2016).
Dorsey SG, Renn CL, Griffioen M, Lassiter CB, Zhu S,
Whole blood transcriptomic profiles can differentiate vulnerability to chronic low back pain.
PLOS ONE 14, e0216539 (2019)
Freidin MB, Tsepilov YA, Stanaway IB, Meng W, Hayward C,
Pain HA-I, Sex- and age-specific genetic analysis of chronic back pain.
Pain 162, 1176–1187 (2021).
Ji R-R, Chamessian A, Zhang Y-Q,
Pain regulation by non-neuronal cells and inflammation.
Science 354, 572–577 (2016).
Kavelaars A, Heijnen CJ,
Immune regulation of pain: Friend and foe.
Sci. Transl. Med 13, eabj7152 (2021).
Scholz J, Woolf CJ,
The neuropathic pain triad: Neurons, immune cells and glia.
Nat. Neurosci 10, 1361–1368 (2007).
Ji RR, Berta T, Nedergaard M,
Glia and pain: Is chronic pain a gliopathy?
Pain 154, S10–S28 (2013).
Grace PM, Hutchinson MR, Maier SF, Watkins LR,
Pathological pain and the neuroimmune interface.
Nat. Rev. Immunol 14, 217–231 (2014).
Grace PM, Tawfik VL, Svensson CI, Burton MD, Loggia ML
The neuroimmunology of chronic pain: From rodents to humans.
J. Neurosci 41, 855–865 (2021).
Ji RR, Nackley A, Huh Y, Terrando N, Maixner W,
Neuroinflammation and central sensitization in chronic and widespread pain.
Anesthesiology 129, 343–366 (2018).
Chapman CR, Vierck CJ,
The transition of acute postoperative pain to chronic pain: An integrative overview of research on mechanisms.
J. Pain 18, 359.e1–359.e38 (2017).
Mifflin KA, Kerr BJ,
The transition from acute to chronic pain: Understanding how different biological systems interact.
Can. J. Anaesth 61, 112–122 (2014).
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y
Robust enumeration of cell subsets from tissue expression profiles.
Nat. Methods 12, 453–457 (2015).
Cellier M, Shustik C, Dalton W, Rich E, Hu J, Malo D
Expression of the human NRAMP1 gene in professional primary phagocytes: Studies in blood cells and in HL-60 promyelocytic leukemia. J. Leukoc. Biol 61, 96–105 (1997).
Canonne-Hergaux F, Calafat J, Richer E, Cellier M
Expression and subcellular localization of NRAMP1 in human neutrophil granules.
Blood 100, 268–275 (2002
Wang S, Song R, Wang Z, Jing Z, Wang S, Ma J,
S100A8/A9 in inflammation.
Front. Immunol 9, 1298 (2018
Pollenus E, Malengier-Devlies B, Vandermosten L, Pham T-T
Limitations of neutrophil depletion by anti-Ly6G antibodies in two heterogenic immunological models.
Immunol. Lett 212, 30–36 (2019).
Ghasemlou N, Chiu IM, Julien JP, Woolf CJ,
CD11b+Ly6G? myeloid cells mediate mechanical inflammatory pain hypersensitivity.
Proc. Natl. Acad. Sci. U.S.A 112, E6808–E6817 (2015).
Diatchenko L, Fillingim RB, Smith SB, Maixner W,
The phenotypic and genetic signatures of common musculoskeletal pain conditions.
Nat. Rev. Rheumatol 9, 340–350 (2013).
Borsook D, Youssef AM, Simons L, Elman I, Eccleston C,
When pain gets stuck: The evolution of pain chronification and treatment resistance.
Pain 159, 2421–2436 (2018).
Wolfe F,
Pain extent and diagnosis: Development and validation of the regional pain scale in 12,799 patients with rheumatic disease.
J. Rheumatol 30, 369–378 (2003).
Barbero M, Fernandez-de-Las-Penas C, Palacios-Cena M
Pain extent is associated with pain intensity but not with widespread pressure or thermal pain sensitivity in women with fibromyalgia syndrome.
Clin. Rheumatol 36, 1427–1432 (2017).
Martin LJ, Smith SB, Khoutorsky A, Magnussen CA, Samoshkin A
Epiregulin and EGFR interactions are involved in pain processing.
J. Clin. Invest 127, 3353–3366 (2017).
Meloto CB, Benavides R, Lichtenwalter RN, Wen X, Tugarinov N
Human pain genetics database: A resource dedicated to human pain genetics research.
Pain 159, 749–763 (2018).
Serhan CN, Savill J,
Resolution of inflammation: The beginning programs the end.
Nat. Immunol 6, 1191–1197 (2005).
St Laurent G 3rd, Seilheimer B, Tackett M, Zhou J, Shtokalo D
Deep sequencing transcriptome analysis of murine wound healing: Effects of a multicomponent, multitarget natural product therapy-Tr14.
Front. Mol. Biosci 4, 57 (2017).
Seifert AW, Monaghan JR, Voss SR, Maden M,
Skin regeneration in adult axolotls: A blueprint for scar-free healing in vertebrates.
PLOS ONE 7, e32875 (2012).
Roughan WH, Campos AI, Garcia-Marin LM, Cuellar-Partida G
Comorbid chronic pain and depression: Shared risk factors and differential antidepressant effectiveness.
Front. Psych 12, 643609 (2021).
Bratus-Neuenschwander A, Castro-Giner F, Frank-Bertoncelj M
Pain-associated transcriptome changes in synovium of knee osteoarthritis patients.
Genes (Basel) 9, (2018).
Guo Y, Walsh AM, Fearon U, Smith MD, Wechalekar MD, Yin X, Cole S
CD40L-dependent pathway is active at various stages of rheumatoid arthritis disease progression.
J. Immunol 198, 4490–4501 (2017).
Held M, Karl F, Vlckova E, Rajdova A, Escolano-Lozano F
Sensory profiles and immune-related expression patterns of patients with and without neuropathic pain after peripheral nerve lesion.
Pain 160, 2316–2327 (2019).
Theken KN, Hersh EV, Lahens NF, Lee HM, Li X, Granquist EJ
Variability in the analgesic response to ibuprofen is associated with cyclooxygenase activation in inflammatory pain.
Clin. Pharmacol. Ther 106, 632–641 (2019).
Freynhagen R, Baron R, Gockel U, Tolle TR,
painDETECT: A new screening questionnaire to identify neuropathic components in patients with back pain.
Curr. Med. Res. Opin 22, 1911–1920 (2006).
Allegri M, Montella S, Salici F, Valente A, Marchesini M
Mechanisms of low back pain: A guide for diagnosis and therapy.
F1000Res 5, F1000 (2016).
Hirschfeld G, Zernikow B,
Variability of “optimal” cut points for mild, moderate, and severe pain: Neglected problems when comparing groups.
Pain 154, 154–159 (2013).
Shafshak TS, Elnemr R,
The visual analogue scale versus numerical rating scale in measuring pain severity and predicting disability in low back pain.
J. Clin. Rheumatol 27, 282–285 (2021).
Love MI, Huber W, Anders S,
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
Genome Biol 15, 550 (2014).
Sergushichev A,
An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation.
bioRxiv 10.1101/060012 [Preprint]. 2016.
Willer CJ, Li Y, Abecasis GR,
METAL: Fast and efficient meta-analysis of genomewide association scans.
Bioinformatics 26, 2190–2191 (2010).
Dagostino C, De Gregori M, Gieger C, Manz J, Gudelj I, Lauc G
Validation of standard operating procedures in a multicenter retrospective study to identify -omics biomarkers for chronic low back pain.
PLOS ONE 12, e0176372 (2017).
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C
STAR: Ultrafast universal RNA-seq aligner.
Bioinformatics 29, 15–21 (2013).
Liao Y, Smyth GK, Shi W,
featureCounts: An efficient general purpose program for assigning sequence reads to genomic features.
Bioinformatics 30, 923–930 (2014
O’Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D, McVeigh R
Reference sequence (RefSeq) database at NCBI: Current status, taxonomic expansion, and functional annotation.
Nucleic Acids Res 44, D733–D745 (2016).
George NI, Bowyer JF, Crabtree NM, Chang CW,
An iterative leave-one-out approach to outlier detection in RNA-seq data.
PLOS ONE 10, e0125224 (2015).
The Gene Ontology Consortium,
The gene ontology resource: 20 years and still Going strong.
Nucleic Acids Res 47, D330–D338 (2019).
Ashburner M, Ball CA, Blake JA, Botstein D,
Gene ontology: Tool for the unification of biology. The gene ontology consortium.
Nat. Genet 25, 25–29 (2000).
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles.
Proc. Natl. Acad. Sci. U.S.A 102, 15545–15550 (2005).
Heberle H, Meirelles GV, da Silva FR, Telles GP, Minghim R,
InteractiVenn: A web-based tool for the analysis of sets through Venn diagrams.
BMC Bioinformatics 16, 169 (2015).
Slade GD, Ohrbach R, Greenspan JD, Fillingim RB, Bair E
Painful temporomandibular disorder: Decade of discovery from OPPERA Studies.
J. Dent. Res 95, 1084–1092 (2016).
Schiffman E, Ohrbach R, Truelove E, Look J, Anderson G, Goulet JP
International RDC/TMD Consortium Network, International Association for Dental Research; Orofacial Pain Special Interest Group, International Association for the Study of Pain, Diagnostic criteria for temporomandibular disorders (DC/TMD) for clinical and research applications: Recommendations of the International RDC/TMD Consortium Network* and orofacial pain special interest groupdagger.
J. Oral Facial Pain Headache 28, 6–27 (2014).
Slade GD, Greenspan JD, Fillingim RB, Maixner W, Sharma S, Ohrbach R,
Overlap of five chronic pain conditions: Temporomandibular disorders, headache, back pain, irritable bowel syndrome, and fibromyalgia.
J. Oral Facial Pain Headache 34, s15–s28 (2020).
Bennett GJ, Xie YK,
A peripheral mononeuropathy in rat that produces disorders of pain sensation like those seen in man.
Pain 33, 87–107 (1988).
La Porta C, Tappe-Theodor A,
Differential impact of psychological and psychophysical stress on low back pain in mice.
Pain 161, 1442–1458 (2020).
Chaplan SR, Bach FW, Pogrel JW, Chung JM, Yaksh TL,
Quantitative assessment of tactile allodynia in the rat paw.
J. Neurosci. Meth 53, 55–63 (1994).
Mogil JS, Ritchie J, Sotocinal SG, Smith SB, Croteau S
Screening for pain phenotypes: Analysis of three congenic mouse strains on a battery of nine nociceptive assays.
Pain 126, 24–34 (2006).
Allen NE, Sudlow C, Peakman T, Collins R, Biobank UK,
UK Biobank data: Come and get it.
Sci. Transl. Med 6, 224ed224 (2014).
Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J
UK Biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age.
PLOS Med 12, e1001779 (2015).
Brown LF, Kroenke K, Theobald DE, Wu J, Tu W,
The association of depression and anxiety with health-related quality of life in cancer patients with depression and/or pain.
Psychooncology 19, 734–741 (2010).
Verma V, Khoury S, Parisien M, Cho C, Maixner W, Martin LJ
The dichotomous role of epiregulin in pain.
Pain 161, 1052–1064 (2020).
Return to LOW BACK PAIN
Return to CHRONIC NECK PAIN
Return to SPINAL PAIN MANAGEMENT
Since 6-11-2022
|