Fibromyalgia syndrome (FMS) is a clinically well-characterized chronic widespread pain condition, regularly accompanied by symptoms such as chronic fatigue, sleep disturbances, and depressive episodes.35 However the pathophysiology of pain in FMS is still incompletely understood. Factors that are possibly involved in the pathophysiology of pain in FMS are impairment of central pain processing pathways, a dysfunctional hypothalamic–pituitary–adrenal axis,77 an imbalance of the immune system,11,83,89 and the recently described alterations in small nerve fibers (A-δ and C-fibers). So far, no differences in clinical or electrophysiological aspects have been found between patients with FMS with normal and reduced intraepidermal nerve fiber density (IENFD). This may be due to the low numbers of patients with FMS who have been investigated with regard to IENFD in the individual studies, hindering adequate statistical analysis. Indeed, several recent studies focused on small fiber impairment in patients with FMS and found a reduction of the IENFD in a subgroup of about 50% of patients.14,21,22,49,60,84 The exact mechanism behind this observation still remains elusive, and the question is which systemic or local factors may contribute to nerve fiber damage.
Noncoding RNAs, including microRNAs (miRNAs, miR-) have been implicated in normal cellular functioning as well as pathological processes.39,58 MiRNAs are small noncoding RNAs that posttranscriptionally regulate gene expression. Various diseases, including neuropathic pain disorders, appear to posses unique miRNA expression signatures.50 MiRNAs control multiple cellular pathways and act as “master switches,” including the control of genes that encode cellular enzymes, receptor proteins and ion channels, all being involved in the pathophysiology of chronic pain. Several pain conditions have recently been shown to be associated with deregulated expression levels of distinct miRNAs in specific pain pathways, from primary afferent nociceptors in the periphery to brain areas associated with the emotional components of pain perception.1,2,42,52,88 Furthermore, aberrant systemic miRNA expression patterns in patients with FMS have been reported and shown to correlate with the various comorbidities associated with FMS.8,9 However, so far no study focused on the connection between miRNA expression and small fiber pathology in FMS. Here, we investigated systemic and cutaneous miRNA expression in blood and skin samples of clinically well-characterized patients with FMS and compared our results with age- and gender-matched healthy controls. We hypothesized that patients with FMS show a unique systemic miRNA expression profile, which in turn might translate to impaired skin miRNA homeostasis as the basis of peripheral nerve fiber pathology in FMS.
2. Materials and methods
2.1. Patients and controls
Thirty patients (28 women, and 2 men; Table 1) with a diagnosis of FMS attending the pain center “Klinik Am Arkauwald,” Bad Mergentheim, Germany (16/30) or the day care pain clinic of the Department of Anesthesiology, University of Würzburg (14/30) were prospectively recruited between 2013 and 2014. Diagnosis was based on the 1990 American College of Rheumatology diagnostic criteria.91 Data from 26 of these patients were included in a previous study on the dermal nerve fiber ultrastructure.22 In addition, 34 age- and gender-matched healthy controls (30 women, and 4 men; Table 1) were recruited between 2013 and 2014 for blood miRNA analysis at the Department of Neurology, University of Würzburg (supplemental Fig. 1, available online at http://links.lww.com/PAIN/A315). Our study was approved by the Ethics Committee of the University of Würzburg Medical Faculty. All patients and controls gave written informed consent to take part in the study.
2.2. Clinical examination, questionnaire assessment, and laboratory tests
All patients underwent neurological examination and were assessed with questionnaires for pain and impairment due to FMS symptoms. These questionnaires included the German versions of the following: the Neuropathic Pain Symptom Inventory (NPSI-G),12,78 the Graded Chronic Pain Scale (GCPS),87 and the Fibromyalgia Impact Questionnaire (FIQ).13,61 The NPSI-G analyses neuropathic pain intensity and quality resulting in a sum score between 0 (no pain) and 1 (maximum pain) in combination with subscores for different pain characteristics. The NPSI-G discriminative score was used to distinguish neuropathic from nonneuropathic pain, resulting in a score ranging from 42.4 to 80, with a cutoff value at 53.5 for neuropathic pain.78 The GCPS rates pain intensity on a scale from 0 to 10 and grades the pain disability from 0 to 4. The FIQ rates the impact of FMS symptoms on the health status of a patient, scores range from 50 (moderately affected patient with FMS) to ≥70 (severely affected patient with FMS). In addition, all patients were examined for depressive symptoms using the German translation of the Center for Epidemiologic Studies Depression Scale (“Allgemeine Depressionsskala,” ADS).69 The ADS ranges from 0 to 60 with a cutoff score of ≥16, implying clinically significant depressive symptoms. Questionnaire data were compared with data of the n = 34 healthy controls recruited for blood miRNA analysis. To exclude large fiber involvement and other peripheral nerve pathology, nerve conduction studies of the right tibial (motor) and sural (sensory) nerve were performed in patients with FMS according to standard procedures.47 For evaluation of small fiber involvement, patients underwent quantitative sensory testing (QST) and a 5-mm skin punch biopsy was obtained for IENFD assessment and cutaneous miRNA expression analysis from the lateral lower leg and the lateral upper thigh. In addition, an oral glucose tolerance test was conducted in all study participants to exclude pathological glucose tolerance or diabetes mellitus.
2.3. Quantitative sensory testing
The quantitative sensory testing was performed following a standardized procedure in all patients (Somedic, Hörby, Sweden).71 Test values of all patients were compared with separately investigated age- and gender-matched healthy controls of our laboratory by transforming the obtained raw values for each QST item into a z-score sensory profile. This control group consisted of 56 age- and gender-matched healthy volunteers from our database (52 women, and 4 men; median age range 52 years, 23-78 years). Z-scores were calculated as follows: z-score = (value of the subject − mean value of controls)/SD of controls. Negative z-scores represent loss of function; positive z-scores indicate gain of function. The following parameters were assessed: cold and heat detection thresholds (CDT, and HDT), the ability to detect temperature changes (thermal sensory limen, TSL), mechanical detection and pain thresholds (MDT and MPT), mechanical pain sensitivity, pressure pain threshold (PPT), paradoxical heat sensation, and vibration detection threshold.
2.4. Blood withdrawal and miRNA isolation
To reduce circadian variation, venous blood was collected from all subjects between 8:00 AM and 9:00 AM after overnight fasting. None of the tested subjects had any clinical signs of ongoing infection. For quantitative real-time PCR (qRT-PCR), 9 mL of whole blood was withdrawn in EDTA-containing tubes, and the total white blood cell (WBC) fraction was extracted. Isolated WBCs were resuspended in the RNAProtect Cell Reagent (Qiagen, Hilden, Germany) and stored at −80°C until further processing. MiRNAs were isolated from all WBC samples using the miRNeasy kit (Qiagen) and following the manufacturer's protocol.
2.5. Skin biopsies and cutaneous miRNA isolation
For the assessment of IENFD, skin punch biopsies of 5-mm diameter (distal lateral lower leg and proximal lateral upper thigh) were obtained in 27 of 30 patients and processed as described earlier81; 2 patients refused to undergo biopsy. To determine IENFD, 50-μm skin sections were prepared and immunostained with the antibodies against the pan-axonal marker protein-gene product 9.5 (1:1000; Ultraclone, Isle of Wight, United Kingdom) and reacted with an appropriate fluorescent secondary antibody (Cy3, 1:100; Dianova, Hamburg, Germany). The intraepidermal nerve fiber density was quantified by an observer blinded to subject's diagnosis and following published rules,53 using a fluorescence microscope (Axiophot 2; Zeiss, Oberkochen, Germany) with an Axiocam MRm camera (Zeiss), and SPOT software (Diagnostic Instruments, Inc, Sterming Heights, MI). As reference values, we used our laboratory normative values obtained from 54 control subjects for the lower leg (50 women, and 4 men; median age: 43 years, range 16-70 years, IENFD 8.5 fibers/mm, range 6.1-15.3) and 34 control subjects for the upper thigh (30 women, and 4 men; median age 44 years, range 22-79 years, IENFD 12.5 fibers/mm, range 9.0-19.9).
For the analysis of both cutaneous miRNA and target gene expression, 10 cryosections of 10 μm, were obtained and frozen at −80°C until further processing. For the extraction of total mRNA, frozen cryosections were processed using the RNeasy Micro kit (Qiagen) and on-column miRNA fraction enrichment following the manufacturer's recommendation with modifications.
2.6. MicroRNA array profiling
We used the Exiqon miRCURY LNA miRNA array profiling service (Exiqon Services, Vedbaek, Denmark) to obtain WBC miRNA expression profiles of 12 patients with FMS and 12 healthy age-matched controls. Selection of 12 patients with FMS for miRNA array profiling was based on age (median age 48 years, range: 39-60), disease duration (median disease duration 18 years, 10-27), current pain intensity (GCPS; median pain intensity 6, 3-8), and IENFD status (lower leg IENFD <6 fibers/mm, ie, reduced IENFD). Exiqon verified the quality of total RNA with an Agilent 2100 Bionanalyzer profile. Total RNA of 750 ng was labeled with Hy3 and Hy5 fluorescent labels, using the miRCURY LNA miRNA Hi-Power Labeling Kit, Hy3/Hy5 (Exiqon). The labeled samples were hybridized to the miRCURY LNA miRNA Array seventh gen (Exiqon), registered in the miRBase 19.0 version that covered 2042 human miRNA probes. The miRNA array slides were scanned using the Agilent G2565BA Microarray Scanner System (Agilent Technologies, Inc, Santa Clara, CA), and the image analysis was performed using the ImaGene 9 (miRCURY LNA miRNA Array Analysis Software; Exiqon). The quantified signals were background corrected (Normexp with offset value 10) and normalized using the global Lowess (LOcally WEighted Scatterplot Smoothing) regression algorithm. The criteria for candidate selection and individual validation were miRNA fold change (FC; ±1 log-fold change), statistical significance after Benjamini–Hochberg correction, and sufficient array signal intensity (7.5-14.5). For individual target analysis of differentially expressed miRNAs and to identify genes that represent putative targets, a prediction analysis was performed by comprehensively using 4 state-of-art algorithms, namely TargetScan,29 miRNA.org,6 miRTarBase,38 and DIANAmicroT.64 We chose miR candidates who showed the highest significance (P < 0.05) for intergroup differences after Benjamini–Hochberg correction and were found to be associated with pain and nerve fiber degeneration in the literature.
2.7. MicroRNA expression analysis
For the generation of miRNA-specific first-strand cDNA of RNA extracted from WBC and skin, 5 ng of total RNA was reverse transcribed using the Universal cDNA Synthesis kit II (Exiqon) following manufacturer's recommendations. For each reaction, 4 μL of diluted (1:80) cDNA was PCR amplified using the corresponding miRNA and reference primer sets, using the miCURY LNA Universal miRNA PCR (Exiqon). To determine expression level of the following miRNAs, specific miCURY LNA assays with the respective assay IDs were used: hsa-miR-let-7d (5′-3′AGAGGUAGUAGGUUGCAUAGUU, MIMAT0000065), hsa-miR-103 (5′-3′AGCAGCAUUGUACAGGGCUAUGA, MIMAT0000101), hsa-miR-151 (5′-3′CUAGACUGAAGCUCCUUGAGG, MIMAT0000757), and hsa-miR-199a (MIMAT0000232, ACAGUAGUCUGCACAUUGGUUA), and normalized to the expression of endogenous 5 seconds RNA (5 seconds RNA, V00589). Each miRNA was amplified in triplicate and Ct values were obtained. Fold changes in miRNA expression among groups were calculated using interplate calibrators by means of the delta-delta Ct method. For individual target verification, we tested different endogenous controls (U6, snord48, snord44, and 5sRNA) of which 5sRNA was the most stable in both groups and was further used.
2.8. Gene expression analysis and downstream target verification
For gene expression analysis of miRNA downstream targets, TaqMan qRT-PCR (Applied Biosystems, Darmstadt, Germany) was used. All PCR reagents and cyclers were used from Life Technologies (Carlsbad, CA). One hundred ng of RNA was reverse transcribed to cDNA using TaqMan Reverse Transcription Reagents, following manufacturer's protocol. For each sample, 5-μL cDNA was used in qRT-PCR, which was performed using a StepOnePlus cycler (Applied Biosystems). Gene expression of insulin-like growth factor-1 receptor (IGF-1R, Assay ID: Hs00609566_m1) was investigated in skin biopsies of all patients with FMS and healthy controls. As an endogenous control, 18sRNA (Assay ID: Hs99999901_s1) was used.
To visualize cutaneous IGF-1R expression, we applied an antibody against IGF-1R (IGFR-I, 1:200; Abcam, Cambridge, United Kingdom). Frozen sections of 16 μm were stained using standard immunohistochemistry (ABC kit; Vector, Westheim, Germany). The amount of epidermal IGF-1R expressed as mean intensity per area was measured using ImageJ 1.49 software (http://imagej.nih.gov/ij/) in accordance with a previously described method.86 The expression of IGF-1R in distal skin of all patients with FMS was compared with those of healthy age- and gender-matched controls.
2.9. Statistical analysis
SPSS Statistics 22 software (IBM, Ehningen, Germany) was used for statistical analysis. The nonparametric Mann–Whitney U test was applied when data were not normally distributed, which was the case for IENFD and qRT-PCR measurements. A t test was used for comparison of z-scores of QST data. Correlations were assessed, using the bivariate Spearman correlation. After quantile background correction and global Lowess normalization to correct for systematic differences between arrays and experimental groups,10,17 Benjamini–Hochberg correction was performed to obtain significantly differentially expressed miRNAs in the miRNA array. Data were expressed as FC (2^logFC). Statistical significance was accepted with P < 0.05.
3.1. Clinical and laboratory findings
Table 1 gives demographic and baseline data of the patients with FMS cohort and healthy controls. No study participant had any indicator of ongoing infection, and no patient had diabetes or prediabetes. Neurological examination was normal in all cases. Patients with FMS had higher NPSI-G median sum scores (0.3; range 0.05-0.78; P < 0.0001) and NPSI-G discriminative scores (57; range 39-80.4; P < 0.0001) than healthy controls (NPSI-G sum score: 0; NPSI-G discriminative score: 42), higher median pain ratings as averaged over 4 weeks (6.5, 3-9 of 10 on a numeric rating scale; P < 0.0001) and higher FIQ scores (65, range 36-84; P < 0.0001) than healthy controls (GCPS and FIQ: 0). In addition, patients with FMS revealed higher ADS scores (25; range 7-51; P < 0.0001) than healthy controls (ADS: 0). Nerve conduction studies showed normal values for all parameters analyzed; in 1 patient (#16), tibial nerve conduction studies were technically hampered by patient's constitution: because of a high body mass index of 42 kg/m2, supramaximal stimulation of the tibial nerve was not possible; however, sural nerve conduction studies were normal, and the patient had no clinical signs of large fiber neuropathy.
3.2. Patients with FMS have impaired small fiber function
Detailed sensory examination revealed thermal hypesthesia in 12 of 30 patients (supplemental Table 1, available online at http://links.lww.com/PAIN/A315) as measured with QST. Patients with FMS had elevated CDT (P < 0.01), warm (WDT; P < 0.05), and MDT (Fig. 1A, P < 0.01) at the dorsal foot when compared with healthy controls. As expected,22,70,84 PPTs were decreased when compared with healthy controls (Fig. 1A, PPT; P < 0.001). To control for an influence of opioid intake on QST results, we compared QST data of patients who were treated with opioids at the time of the investigation (n = 11) with those who were not (n = 19). No intergroup difference was found except for TSL, which was lower in patients using opioids compared with those who did not (P = 0.036), ie, patients using opioids detected temperature differences faster. Since both subgroups individually were not different from controls, this intergroup difference may not be clinically relevant.
3.3. Skin innervation is reduced in patients with FMS
We previously reported a reduction of epidermal innervation in approximately 50% of our FMS study cohort.84 Here, we confirm this finding: in 50% of the patients with FMS, we found a reduction of lower leg skin innervation (<6 fibers/mm, 14/28 patients with FMS, median 4.7 fibers/mm, range 1.8-6.0) compared with a normal (≥6 fibers/mm, 14/28, median 9.3 fibers/mm, range 6.6-15.9) IENFD in the other subgroup. At the lower leg, IENFD of patients with FMS was reduced compared with healthy controls (FMS: 6.3 fibers/mm, range 1.8-15.9, control subjects: 8.5 fibers/mm, range 6.1-15.3, P < 0.01). Also at the upper thigh, IENFD of patients with FMS was lower than that in healthy controls (FMS: 10.4 fibers/mm, range 3.7-20.5, control subjects: 12.5 fibers/mm, range 9.0-19.9; P < 0.01).
3.4. Impaired small fiber function in patients with FMS is related to reduced intraepidermal nerve fiber density
Patients were not different for any questionnaire parameter analyzed when subgrouped into those with reduced (14/28) and those with normal IENFD (14/28). However, when subgrouped, CDT and MDT were elevated only in patients with reduced IENFD (Fig. 1B, P < 0.01). Moreover, PPT was reduced in patients with FMS with reduced IENFD when compared with patients with normal IENFD (Fig. 1B, P < 0.05). Interestingly, WDT was not different between patients with FMS with normal and reduced IENFD (Fig. 1B); 10/14 patients with FMS with reduced IENFD and 10/14 patients with FMS with normal IENFD showed increased WDT.
3.5. Patients with FMS show aberrant genome-wide miRNA expression in white blood cell
Next, we measured the genome-wide expression of miRNAs in WBC of 12 patients with reduced IENFD (<6 IENFD) and 12 age- and gender-matched healthy controls (see miRNA array profiling). Supplemental Table 2 provides an overview of the individual data on RNA quality (available online at http://links.lww.com/PAIN/A315). The overall RNA integrity number values were ≥7, indicating good quality and low fragmentation of total RNA. Mean signal intensities for each miRNA were compared across WBCs obtained from patients with FMS with the group of healthy controls. Since 114 miRNAs showed differential expression with a P-value <0.05, we sought to identify the most prominent changes by focusing on miRNAs which showed the highest FC (upregulation or downregulation) in expression and with most stringent array and biological replicate standards. Fifty-one miRNAs survived these standards and are depicted by a heat plot (supplemental Table 3, available online at http://links.lww.com/PAIN/A315; Fig. 2) comparing patients with FMS with healthy controls. Four miRNAs were prominently downregulated and 47 were upregulated in WBC of patients with FMS compared with healthy controls. Microarray profiling data were validated with independent qRT-PCR for those targets (Table 2 and Fig. 3) that showed promising literature-based association with pathways in the pathophysiology of pain. We tested the potential impact of poor RNA quality on the observed differences and did not find any correlation between individual RNA integrity number data and FCs of the selected candidates.
3.6. MiR-let-7d in white blood cell correlates with pain and impairment of small fiber function in patients with FMS
Figure 3 depicts individual miRNA validation of the predicted targets in WBC of patients with FMS when compared with healthy controls. All the following analyzed targets: miR-103 (Fig. 3A, −0.52 FC, P < 0.001), miR-146a (Fig. 3B, −0.5 FC, P < 0.01), and miR-let-7d (Fig. 3C, −0.7 FC, P < 0.001) were downregulated when measured in the entire FMS cohort. MiR-151 did not show any differential expression (data not shown). Although the microarray data (n = 12 patients with FMS with reduced IENFD vs n = 12 controls) suggested an upregulation of miR-let-7d, the individual validation using the same patient group indicated lower expression. Interestingly, in patients with FMS, miR-let-7d gene expression in WBC positively correlated with IENFD (P < 0.05, n = 30, r 2 = 0.2) and the mean pain intensity over the last 4 weeks (GCPS, P < 0.05, n = 30, r 2 = 0.23), the latter in particular among patients with reduced IENFD (P < 0.05, n = 14, r 2 = 0.4).
3.7. MiR-let-7d expression is higher in skin biopsies of patients with FMS with reduced intraepidermal nerve fiber density
To assess a potential influence of miR-let-7d on IENFD in patients with FMS, we set out to measure miR-let-7d expression directly in skin biopsies of patients with FMS and healthy controls. MiR-let-7d expression was higher in patients with FMS than that in healthy controls (Fig. 4A, 1.72 FC, P < 0.001), in particular in the subgroup with reduced distal IENFD (Fig. 4B, 2.64 FC, P < 0.05). No difference was observed in miR-let-7d expression when compared with normal IENFD (data not shown). In addition, no differential expression was observed for miR-103 when comparing patients with FMS and healthy controls. Next, we followed an unbiased and comprehensive approach to predict the mRNA targets for miR-let-7d by adapting different state-of-art algorithms.16,33,64,85 The respective results of the individual prediction algorithms are provided by the following links:
TargetScan (http://www.targetscan.org/cgi-bin/targetscan/vert_71/view_gene.cgi?rs=ENST00000268035.6&taxid=9606&showcnc=0&shownc=0&shownc_nc=&showncf1=&showncf2=&subset=1), microRNA.org (http://www.microrna.org/microrna/getMrna.do?gene=3480&utr=31402&organism=9606#hd) and miRTarBase (http://mirtarbase.mbc.nctu.edu.tw/php/detail.php?mirtid=MIRT005364#target). Among the different targets, IGF-1R presented an interesting protein that is known to be regulated by miR-let-7d.44,95 Indeed, when comparing the expression of IGF-1R in patients with FMS, IGF-1R mRNA levels were lower in skin biopsies from the lower leg of patients with FMS compared with skin biopsies from the upper thigh (Fig. 4C, P < 0.001). When comparing distal to proximal IGF-1R expression in healthy controls, no difference was observed. Moreover, patients with FMS with reduced IENFD (n = 14) had lower IGF-1R expression in the skin of the distal leg compared with patients with normal IENFD (n = 13, Fig. 4D, P < 0.01) and skin from the distal leg of healthy controls (Fig. 4D, n = 19 controls, P < 0.05). No difference in IGF-1R expression was observed between distal and proximal skin biopsies of healthy controls (data not shown).
3.8. Patients with FMS with reduced IENFD have lower skin insulin-like growth factor-1 receptor immunoreactivity than healthy controls
Figure 5A shows a representative image of IGF-1R immunofluorescence in the epidermal skin from the lower leg of a patient with FMS. Epidermal IGF-1R immunoreactivity appears to be membranous, mainly staining keratinocytes. The quantification of IGF-1R revealed lower IGF-1R immunoreactivity in skin samples of patients with FMS with reduced IENFD compared with healthy controls (Fig. 5B, P < 0.05), which might be linked to increased distal miR-let-7d expression. In addition, IGF-1R was lower in patients with FMS with reduced IENFD when compared with patients with FMS with normal IENFD (Fig. 5B, P < 0.05).
Despite recent advances, understanding and treating chronic pain remains a major challenge for clinicians and preclinical scientists. Using a comprehensive method of combining patient data with molecular approaches in a clinically well-characterized patient cohort, this study showed that aberrant systemic miRNA expression profiles allow stratifying patients with FMS on the basis of specific regulatory miRNAs. We furthermore demonstrated the possible role of miRNAs in the reduction of intraepidermal innervation and regeneration of nerve fibers in patients with FMS.
In this study, we used a standardized and validated QST protocol71 allowing the assessment of small fiber function, and found increased perception thresholds for thermal and mechanical stimuli indicating small nerve fiber malfunction. As expected, we also found reduced PPT in patients with FMS, without differences between the subgroups with and without reduced IENFD. One caveat is that QST was performed under regular analgesic medication in the patient cohort, and although statistical analysis only revealed a difference in QST results for TSL between patients with and without opioids, data need to be interpreted with caution. Skin innervation as quantified in skin punch biopsies was reduced in 50% of the patients with FMS, and in line with previous reports,22,31,60,74,84 this reduction was observed in the distal and proximal skin biopsies.
The elevated MDTs in our patients with FMS might be caused by functional changes in or loss of mechanosensitive C-fiber afferents. What is more difficult to understand are decreased pain thresholds in patients with a reduced density of nociceptive endings. Although some studies suggest central mechanisms to allow for this apparent discrepancy,19,59 others suggest local factors such as proinflammatory and algesic cytokines82 or reduced small fiber diameters as a correlate of nerve fiber lesion22 that may influence peripheral hyperalgesia. In this study, we pursued the hypothesis of local factors influencing peripheral nerve homeostasis and proposed altered local and systemic miRNA expression as rationale for reduced nerve fiber density and associated symptoms in FMS.
Indeed, in a first attempt to characterize FMS based on altered miRNA expression profiles, others reported the dysregulation of several miRNAs in cerebrospinal fluid, serum, and peripheral blood mononuclear cells and surprisingly found individual correlations of selected miRNAs with FMS symptoms.8,9,15 We took the screening of miRNAs in FMS to the next level, and first screened the expression of WBC miRNAs in a well-characterized group of patients with FMS. We show that FMS is associated with dysregulation of 55 miRNAs in WBC. Of these, 51 aberrantly expressed miRNAs, interestingly several miRNAs (miR-let-7d, miR-103, and miR-151) were in common with those reported previously.8,9,15 Second, we show that 3 of our 5 selected candidates are differentially expressed when compared over the entire FMS cohort. All selected candidates have been shown to be associated with a variety of human diseases such as cancer,26 neurodegenerative diseases,51,54,55 stroke,57 cardiovascular diseases,3 and chronic pain.27 Especially, the association with preclinical and clinical chronic pain is intriguing.7,50,62,65 Of particular interest is miR-let-7d which was not only found to be dysregulated in FMS but also correlated with the mean pain intensity (GCPS) over the last 4 weeks and with a reduction of IENFD in patients with FMS. We thus measured the expression of miR-let-7d in distal and proximal skin biopsies of patients with FMS and found that miR-let-7d expression was higher in the distal skin of patients with FMS when IENFD was reduced.
Let-7d miRNAs are among the first miRNAs described to play important roles in cell proliferation, differentiation, and brain development and have recently been shown to be prognostic markers in several malignancies.72 Aberrant miR-let-7d expression has been associated with chronic pain before62 and shown to affect the endogenous opioid system and opioid tolerance.37 We hypothesized that downregulated miR-let-7d in distal skin in FMS may account for reduced nerve fiber innervation in patients with FMS. Nerve regeneration is a complex spatiotemporal sequence of specific events involving the IGF-1/IGF-1R signaling pathway.40,92 Insulin-like growth factor-1 is involved in muscle regeneration,36,41 and also plays a key role in the peripheral nervous system,25,34,43 controlling Schwann cell viability,79 promoting motor neuron neurite outgrowth,56,63 and regulating peripheral nerve regeneration46,48,67,93 and inflammation.76 Indeed, FMS has been associated with impaired growth hormone responses leading to reduced IGF-1 production,4,5,20 but supplemental therapies have only been partially successful. Several miRNAs have been reported to regulate different components of the IGF pathway,45 in which miR-let-7 arguably plays a key role. Indeed, IGFs-1/IGF-1Rs have been validated as downstream targets of miR-let-7d by others before. We thus measured miR-let-7d and IGF-1R mRNA in skin biopsies of patients with FMS and showed an increased miR-let-7d expression and a reciprocal decrease in IGF-1R mRNA, selectively in patients with reduced IENFD. Coherently, we found a reduction in IGF-1R immunoreactivity when IENFD was reduced. Furthermore, the downstream targets of miR-let-7d, IGFs-1/IGF-1Rs are major players in muscle regeneration.23,66,68,90 Since pain in FMS is mostly described as deep muscle pain, muscle in patients with FMS has been investigated with various methods (histology, electromyography, metabolism, and imaging), however, so far without specific findings.19 Our data might open a new avenue of studying the role of muscle in patients with FMS.
Taken together, there is strong evidence for small nerve fiber impairment in a subgroup of patients suffering from FMS, which is possibly linked to altered miRNA expression and concurrent decreased cutaneous IGF-1R signaling. However, since miR-let-7d is involved in a variety of physiological and pathophysiological processes, we cannot exclude actions on alternative pathways independent of IGF-1R. Interestingly, reduced axon diameters were recently reported in patients with FMS,22 similarly to what had been observed in IGF-1–knockout mice.30 Another intriguing possibility of individual variability in the severity of FMS symptoms and/or associated comorbidities may be explained by miRNA-related single nucleotide polymorphisms (SNPs). As for other diseases, SNPs could significantly alter the biogenesis and thus function of a given miRNA.75 Indeed, SNPs in the let-7 gene have been shown to alter individual susceptibility to type 2 diabetes,94 and SNPs in the miR-146a gene were shown to contribute to susceptibility to peripheral neuropathy.18 Moreover, SNPs in the miRNA binding site of IGF-1R have been shown for other miRNAs before,32 however, not for let-7 yet. Nonetheless, there is thus increasing evidence that genetic variants altering miRNA function point toward individual susceptibility in symptom-related diseases, which thus raises the interest in future studies on SNP-related miRNA changes in FMS.
Our study has several limitations, such as small sample size and different treatment regimens of patients with FMS. The fact that IENFD does not correlate with all QST parameters of small nerve fiber function is not surprising, since the pan-axonal marker protein-gene product 9.5 does not differentiate for nerve fiber function but gives a mere information on nerve fiber quantity. Thus, a “normal” IENFD may be associated with elevated perception thresholds if these fibers are functionally impaired, and a few but intact epidermal nerve fibers may be sufficient to maintain normal perception thresholds.24,73,84 The currently applied techniques for bioinformatical prediction analyses using commercially available algorithms may lead to an overestimation and to the identification of nonfunctional targets. Interestingly, we observed many more increases than decreases of miRNA expression in our microarray analysis. One possibility to explain this finding is that miR-let-7d may be causally involved in miRNA metabolism and that the impact of its increase extends to many other miRNAs.28,80 It furthermore remains elusive if and how reduced epidermal IGF-1R leads to decreased nerve fiber terminals in the distal skin of patients with FMS, and one can only speculate that decreased receptor expression leads to decreased peripheral nerve regeneration as has been shown before.43 Further research is needed to provide direct evidence for if and how cells in the epidermal layer, such as keratinocytes may influence the regeneration of intraepidermal nerve fibers. Nonetheless, given the data detailed above, we assume a pathophysiologic role of miRNAs in a subgroup of patients with FMS. Moreover, our study together with previous findings22,74,83,84 also may have important implications in improving diagnostic criteria of FMS. So far, FMS diagnosis is based on the subjective report of patients on painful areas and pain intensity. An objective biomarker would dramatically improve FMS diagnostics and also open new possibilities for targeted treatment. At present, it is too early to either use IENFD or miRNA measurements as a diagnosis for FMS, and more research is needed.
Conflicts of interest statement
M. Leinders was supported by a stipend from the Research Training Group “Emotions,” RTG 1253/1 (German Research Foundation, DFG) of the Graduate School of the University of Würzburg, Germany. K. Doppler has received honoraria for educational talks from Baxter, for educational material from Grifols and has received research support from Kedrion. T. Klein, M. Deckart, H. Rittner have no conflicts of interest. C. Sommer has received consultancy fees from Astellas, Baxalta, CSL Behring, and Genzyme, and honoraria for educational talks from Baxter, Genzyme, Grifols, Kedrion, and Pfizer. N. Üçeyler has received honoraria for consultancy from Grünenthal GmbH and for presentations from Baxalta, Genzyme Corp, Shire Corp, and Astellas; she has received travel grants from Pfizer Inc, Genzyme Corp, Shire Corp, Astellas, Grünenthal GmbH, and CSL Behring; she has received research support from Grünenthal GmbH and Genzyme Corp. C. Sommer and N. Üçeyler received funding by the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 602133.
The authors thank Beatrice Ballarin, Andrew Branstetter, Barbara Broll, and Sonja Mildner for expert technical assistance. This work is part of the doctoral thesis of M. Leinders.
Supplemental Digital Content
Supplemental Digital Content associated with this article can be found online at http://links.lww.com/PAIN/A315.
. Aldrich BT, Frakes EP, Kasuya J, Hammond DL, Kitamoto T. Changes in expression of sensory organ-specific microRNAs in rat dorsal root ganglia in association with mechanical hypersensitivity induced by spinal nerve ligation. Neuroscience 2009;164:711–23.
. Bai G, Ambalavanar R, Wei D, Dessem D. Downregulation of selective microRNAs in trigeminal ganglion neurons following inflammatory muscle pain. Mol Pain 2007;3:15.
. Bao MH, Feng X, Zhang YW, Lou XY, Cheng Y, Zhou HH. Let-7 in cardiovascular diseases, heart development and cardiovascular differentiation from stem cells. Int J Mol Sci 2013;14:23086–102.
. Bennett RM. Adult growth hormone deficiency in patients with fibromyalgia. Curr Rheumatol Rep 2002;4:306–12.
. Bennett RM, Cook DM, Clark SR, Burckhardt CS, Campbell SM. Hypothalamic-pituitary-insulin-like growth factor-I axis dysfunction in patients with fibromyalgia. J Rheumatol 1997;24:1384–9.
. Betel D, Wilson M, Gabow A, Marks DS, Sander C. The microRNA.org
resource: targets and expression. Nucleic Acids Res 2008;36(Database issue):D149–53.
. Beyer C, Zampetaki A, Lin NY, Kleyer A, Perricone C, Iagnocco A, Distler A, Langley SR, Gelse K, Sesselmann S, Lorenzini R, Niemeier A, Swoboda B, Distler JH, Santer P, Egger G, Willeit J, Mayr M, Schett G, Kiechl S. Signature of circulating microRNAs in osteoarthritis. Ann Rheum Dis 2015;74:e18.
. Bjersing JL, Bokarewa MI, Mannerkorpi K. Profile of circulating microRNAs in fibromyalgia and their relation to symptom severity: an exploratory study. Rheumatol Int 2015;35:635–42.
. Bjersing JL, Lundborg C, Bokarewa MI, Mannerkorpi K. Profile of cerebrospinal microRNAs in fibromyalgia. PLoS One 2013;8:e78762.
. Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 2003;19:185–93.
. Bote ME, Garcia JJ, Hinchado MD, Ortega E. Fibromyalgia: anti-inflammatory and stress responses after acute moderate exercise. PLoS One 2013;8:e74524.
. Bouhassira D, Attal N, Fermanian J, Alchaar H, Gautron M, Masquelier E, Rostaing S, Lanteri-Minet M, Collin E, Grisart J, Boureau F. Development and validation of the neuropathic pain symptom Inventory. PAIN 2004;108:248–57.
. Burckhardt CS, Clark SR, Bennett RM. The fibromyalgia impact questionnaire: development and validation. J Rheumatol 1991;18:728–33.
. Caro XJ, Winter EF. Evidence of abnormal epidermal nerve fiber density in fibromyalgia: clinical and immunologic implications. Arthritis Rheumatol 2014;66:1945–54.
. Cerda-Olmedo G, Mena-Duran AV, Monsalve V, Oltra E. Identification of a microRNA
signature for the diagnosis of fibromyalgia. PLoS One 2015;10:e0121903.
. Chou CH, Chang NW, Shrestha S, Hsu SD, Lin YL, Lee WH, Yang CD, Hong HC, Wei TY, Tu SJ, Tsai TR, Ho SY, Jian TY, Wu HY, Chen PR, Lin NC, Huang HT, Yang TL, Pai CY, Tai CS, Chen WL, Huang CY, Liu CC, Weng SL, Liao KW, Hsu WL, Huang HD. miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database. Nucleic Acids Res 2016;44:D239–47.
. Chudin E, Kruglyak S, Baker SC, Oeser S, Barker D, McDaniel TK. A model of technical variation of microarray
signals. J Comput Biol 2006;13:996–1003.
. Ciccacci C, Morganti R, Di Fusco D, D'Amato C, Cacciotti L, Greco C, Rufini S, Novelli G, Sangiuolo F, Marfia GA, Borgiani P, Spallone V. Common polymorphisms in MIR146a, MIR128a and MIR27a genes contribute to neuropathy susceptibility in type 2 diabetes. Acta Diabetol 2014;51:663–71.
. Clauw DJ. Fibromyalgia and related conditions. Mayo Clin Proc 2015;90:680–92.
. Cuatrecasas G, Gonzalez MJ, Alegre C, Sesmilo G, Fernandez-Sola J, Casanueva FF, Garcia-Fructuoso F, Poca-Dias V, Izquierdo JP, Puig-Domingo M. High prevalence of growth hormone deficiency in severe fibromyalgia syndromes. J Clin Endocrinol Metab 2010;95:4331–7.
. de Tommaso M, Nolano M, Iannone F, Vecchio E, Ricci K, Lorenzo M, Delussi M, Girolamo F, Lavolpe V, Provitera V, Stancanelli A, Lapadula G, Livrea P. Update on laser-evoked potential findings in fibromyalgia patients in light of clinical and skin biopsy
features. J Neurol 2014;261:461–72.
. Doppler K, Rittner HL, Deckart M, Sommer C. Reduced dermal nerve fiber diameter in skin biopsies of patients with fibromyalgia. PAIN 2015;156:2319–25.
. Drummond MJ, McCarthy JJ, Sinha M, Spratt HM, Volpi E, Esser KA, Rasmussen BB. Aging and microRNA
expression in human skeletal muscle: a microarray
and bioinformatics analysis. Physiol Genomics 2011;43:595–603.
. EFNS/PNS. JTFo. European Federation of Neurological Societies/Peripheral Nerve Society Guideline on the use of skin biopsy
in the diagnosis of small fiber neuropathy. Report of a joint task force of the European Federation of Neurological Societies and the Peripheral Nerve Society. J Peripher Nerv Syst 2010;15:79–92.
. English AW. Cytokines, growth factors and sprouting at the neuromuscular junction. J Neurocytol 2003;32:943–60.
. Esteller M. Non-coding RNAs in human disease. Nat Rev Genet 2011;12:861–74.
. Favereaux A, Thoumine O, Bouali-Benazzouz R, Roques V, Papon MA, Salam SA, Drutel G, Leger C, Calas A, Nagy F, Landry M. Bidirectional integrative regulation of Cav1.2 calcium channel by microRNA miR
-103: role in pain. EMBO J 2011;30:3830–41.
. Forman JJ, Legesse-Miller A, Coller HA. A search for conserved sequences in coding regions reveals that the let-7 microRNA
targets Dicer within its coding sequence. Proc Natl Acad Sci U S A 2008;105:14879–84.
. Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res 2009;19:92–105.
. Gao WQ, Shinsky N, Ingle G, Beck K, Elias KA, Powell-Braxton L. IGF-I deficient mice show reduced peripheral nerve conduction velocities and decreased axonal diameters and respond to exogenous IGF-I treatment. J Neurobiol 1999;39:142–52.
. Giannoccaro MP, Donadio V, Incensi A, Avoni P, Liguori R. Small nerve fiber involvement in patients referred for fibromyalgia. Muscle Nerve 2014;49:757–9.
. Gilam A, Edry L, Mamluk-Morag E, Bar-Ilan D, Avivi C, Golan D, Laitman Y, Barshack I, Friedman E, Shomron N. Involvement of IGF-1R
regulation by miR
-515-5p modifies breast cancer risk among BRCA1 carriers. Breast Cancer Res Treat 2013;138:753–60.
. Griffiths-Jones S. The microRNA
Registry. Nucleic Acids Res 2004;32(Database issue):D109–11.
. Hansson HA, Nilsson A, Isgaard J, Billig H, Isaksson O, Skottner A, Andersson IK, Rozell B. Immunohistochemical localization of insulin-like growth factor I in the adult rat. Histochemistry 1988;89:403–10.
. Hauser W, Zimmer C, Felde E, Kollner V. What are the key symptoms of fibromyalgia? Results of a survey of the German Fibromyalgia Association [in German]. Schmerz 2008;22:176–83.
. Hayashi S, Aso H, Watanabe K, Nara H, Rose MT, Ohwada S, Yamaguchi T. Sequence of IGF-I, IGF-II, and HGF expression in regenerating skeletal muscle. Histochem Cell Biol 2004;122:427–34.
. He Y, Yang C, Kirkmire CM, Wang ZJ. Regulation of opioid tolerance by let-7 family microRNA
targeting the mu opioid receptor. J Neurosci 2010;30:10251–8.
. Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, Tsai WT, Chen GZ, Lee CJ, Chiu CM, Chien CH, Wu MC, Huang CY, Tsou AP, Huang HD. miRTarBase: a database curates experimentally validated microRNA
-target interactions. Nucleic Acids Res 2011;39(Database issue):D163–69.
. Huttenhofer A, Schattner P. The principles of guiding by RNA: chimeric RNA-protein enzymes. Nat Rev Genet 2006;7:475–82.
. Ide C. Peripheral nerve regeneration. Neurosci Res 1996;25:101–21.
. Iida K, Itoh E, Kim DS, del Rincon JP, Coschigano KT, Kopchick JJ, Thorner MO. Muscle mechano growth factor is preferentially induced by growth hormone in growth hormone-deficient lit/lit mice. J Physiol 2004;560(Pt 2):341–9.
. Imai S, Saeki M, Yanase M, Horiuchi H, Abe M, Narita M, Kuzumaki N, Suzuki T, Narita M. Change in microRNAs associated with neuronal adaptive responses in the nucleus accumbens under neuropathic pain. J Neurosci 2011;31:15294–9.
. Ishii DN, Glazner GW, Pu SF. Role of insulin-like growth factors in peripheral nerve regeneration. Pharmacol Ther 1994;62:125–44.
. Jiang L, Liu X, Chen Z, Jin Y, Heidbreder CE, Kolokythas A, Wang A, Dai Y, Zhou X. MicroRNA
-7 targets IGF1R (insulin-like growth factor 1 receptor) in tongue squamous cell carcinoma cells. Biochem J 2010;432:199–205.
. Jung HJ, Suh Y. Regulation of IGF -1 signaling by microRNAs. Front Genet 2014;5:472.
. Kanje M, Skottner A, Sjoberg J, Lundborg G. Insulin-like growth factor I (IGF-I) stimulates regeneration of the rat sciatic nerve. Brain Res 1989;486:396–8.
. Kimura J. Principles and practice. In: Electrodiagnosis in diseases of nerve and muscle. 3rd ed. New York: Oxford University Press, 2001.
. Kiryakova S, Sohnchen J, Grosheva M, Schuetz U, Marinova T, Dzhupanova R, Sinis N, Hubbers CU, Skouras E, Ankerne J, Fries JW, Irintchev A, Dunlop SA, Angelov DN. Recovery of whisking function promoted by manual stimulation of the vibrissal muscles after facial nerve injury requires insulin-like growth factor 1 (IGF-1). Exp Neurol 2010;222:226–34.
. Kosmidis ML, Koutsogeorgopoulou L, Alexopoulos H, Mamali I, Vlachoyiannopoulos PG, Voulgarelis M, Moutsopoulos HM, Tzioufas AG, Dalakas MC. Reduction of Intraepidermal Nerve Fiber Density (IENFD) in the skin biopsies of patients with fibromyalgia: a controlled study. J Neurol Sci 2014;347:143–7.
. Kress M, Huttenhofer A, Landry M, Kuner R, Favereaux A, Greenberg D, Bednarik J, Heppenstall P, Kronenberg F, Malcangio M, Rittner H, Uceyler N, Trajanoski Z, Mouritzen P, Birklein F, Sommer C, Soreq H. MicroRNAs in nociceptive circuits as predictors of future clinical applications. Front Mol Neurosci 2013;6:33.
. Kumar P, Dezso Z, MacKenzie C, Oestreicher J, Agoulnik S, Byrne M, Bernier F, Yanagimachi M, Aoshima K, Oda Y. Circulating miRNA biomarkers for Alzheimer's disease. PLoS One 2013;8:e69807.
. Kusuda R, Cadetti F, Ravanelli MI, Sousa TA, Zanon S, De Lucca FL, Lucas G. Differential expression of microRNAs in mouse pain models. Mol Pain 2011;7:17.
. Lauria G, Cornblath DR, Johansson O, McArthur JC, Mellgren SI, Nolano M, Rosenberg N, Sommer C; European Federation of Neurological S. EFNS guidelines on the use of skin biopsy
in the diagnosis of peripheral neuropathy. Eur J Neurol 2005;12:747–58.
. Lehmann SM, Kruger C, Park B, Derkow K, Rosenberger K, Baumgart J, Trimbuch T, Eom G, Hinz M, Kaul D, Habbel P, Kalin R, Franzoni E, Rybak A, Nguyen D, Veh R, Ninnemann O, Peters O, Nitsch R, Heppner FL, Golenbock D, Schott E, Ploegh HL, Wulczyn FG, Lehnardt S. An unconventional role for miRNA: let-7 activates Toll-like receptor 7 and causes neurodegeneration. Nat Neurosci 2012;15:827–35.
. Leidinger P, Backes C, Deutscher S, Schmitt K, Mueller SC, Frese K, Haas J, Ruprecht K, Paul F, Stahler C, Lang CJ, Meder B, Bartfai T, Meese E, Keller A. A blood based 12-miRNA signature of Alzheimer disease patients. Genome Biol 2013;14:R78.
. Lewis ME, Neff NT, Contreras PC, Stong DB, Oppenheim RW, Grebow PE, Vaught JL. Insulin-like growth factor-I: potential for treatment of motor neuronal disorders. Exp Neurol 1993;124:73–88.
. Long G, Wang F, Li H, Yin Z, Sandip C, Lou Y, Wang Y, Chen C, Wang DW. Circulating miR
-126 and let-7b as biomarker for ischemic stroke in humans. BMC Neurol 2013;13:178.
. Mattick JS. RNA regulation: a new genetics? Nat Rev Genet 2004;5:316–23.
. Mense S. Neurobiological concepts of fibromyalgia–the possible role of descending spinal tracts. Scand J Rheumatol Suppl 2000;113:24–9.
. Oaklander AL, Herzog ZD, Downs HM, Klein MM. Objective evidence that small-fiber polyneuropathy underlies some illnesses currently labeled as fibromyalgia. PAIN 2013;154:2310–16.
. Offenbaecher M, Waltz M, Schoeps P. Validation of a German version of the fibromyalgia impact questionnaire (FIQ-G). J Rheumatol 2000;27:1984–8.
. Orlova IA, Alexander GM, Qureshi RA, Sacan A, Graziano A, Barrett JE, Schwartzman RJ, Ajit SK. MicroRNA
modulation in complex regional pain syndrome. J Transl Med 2011;9:195.
. Ozdinler PH, Macklis JD. IGF-I specifically enhances axon outgrowth of corticospinal motor neurons. Nat Neurosci 2006;9:1371–81.
. Paraskevopoulou MD, Georgakilas G, Kostoulas N, Vlachos IS, Vergoulis T, Reczko M, Filippidis C, Dalamagas T, Hatzigeorgiou AG. DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Res 2013;41(Web Server issue):W169–73.
. Pauley KM, Satoh M, Chan AL, Bubb MR, Reeves WH, Chan EK. Upregulated miR
-146a expression in peripheral blood mononuclear cells from rheumatoid arthritis patients. Arthritis Res Ther 2008;10:R101.
. Philippou A, Maridaki M, Halapas A, Koutsilieris M. The role of the insulin-like growth factor 1 (IGF-1) in skeletal muscle physiology. In Vivo 2007;21:45–54.
. Pierson CR, Zhang W, Murakawa Y, Sima AA. Insulin deficiency rather than hyperglycemia accounts for impaired neurotrophic responses and nerve fiber regeneration in type 1 diabetic neuropathy. J Neuropathol Exp Neurol 2003;62:260–71.
. Rabinovsky ED. The multifunctional role of IGF-1 in peripheral nerve regeneration. Neurol Res 2004;26:204–10.
. Radloff L. The CES-D: a self-report symptom scale to detect depression in the general population. Appl Psychol Meas 1977;3:385–401.
. Ritchie ME, Silver J, Oshlack A, Holmes M, Diyagama D, Holloway A, Smyth GK. A comparison of background correction methods for two-colour microarrays. Bioinformatics 2007;23:2700–7.
. Rolke R, Baron R, Maier C, Tölle TR, Treede RD, Beyer A, Binder A, Birbaumer N, Birklein F, Botefur IC, Braune S, Flor H, Huge V, Klug R, Landwehrmeyer GB, Magerl W, Maihofner C, Rolko C, Schaub C, Scherens A, Sprenger T, Valet M, Wasserka B. Quantitative sensory testing in the German Research Network on Neuropathic Pain (DFNS): standardized protocol and reference values. PAIN 2006;123:231–43.
. Roush S, Slack FJ. The let-7 family of microRNAs. Trends Cell Biol 2008;18:505–16.
. Saperstein DS, Levine TD, Levine M, Hank N. Usefulness of skin biopsies in the evaluation and management of patients with suspected small fiber neuropathy. Int J Neurosci 2013;123:38–41.
. Serra J, Collado A, Sola R, Antonelli F, Torres X, Salgueiro M, Quiles C, Bostock H. Hyperexcitable C nociceptors in fibromyalgia. Ann Neurol 2014;75:196–208.
. Slaby O, Bienertova-Vasku J, Svoboda M, Vyzula R. Genetic polymorphisms and microRNAs: new direction in molecular epidemiology of solid cancer. J Cell Mol Med 2012;16:8–21.
. Smith TJ. Insulin-like growth factor-I regulation of immune function: a potential therapeutic target in autoimmune diseases? Pharmacol Rev 2010;62:199–236.
. Sommer C, Hauser W, Burgmer M, Engelhardt R, Gerhold K, Petzke F, Schmidt-Wilcke T, Spath M, Tolle T, Uceyler N, Wang H, Winkelmann A, Thieme K; Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen F. Etiology and pathophysiology of fibromyalgia syndrome
[in German]. Schmerz 2012;26:259–67.
. Sommer C, Richter H, Rogausch JP, Frettloh J, Lungenhausen M, Maier C. A modified score to identify and discriminate neuropathic pain: a study on the German version of the Neuropathic Pain Symptom Inventory (NPSI). BMC Neurol 2011;11:104.
. Syroid DE, Zorick TS, Arbet-Engels C, Kilpatrick TJ, Eckhart W, Lemke G. A role for insulin-like growth factor-I in the regulation of Schwann cell survival. J Neurosci 1999;19:2059–68.
. Tokumaru S, Suzuki M, Yamada H, Nagino M, Takahashi T. let-7 regulates Dicer expression and constitutes a negative feedback loop. Carcinogenesis 2008;29:2073–7.
. Üçeyler N, Kafke W, Riediger N, He L, Necula G, Toyka KV, Sommer C. Elevated proinflammatory cytokine expression in affected skin in small fiber neuropathy. Neurology 2010;74:1806–13.
. Üçeyler N, Kewenig S, Kafke W, Kittel-Schneider S, Sommer C. Skin cytokine expression in patients with fibromyalgia syndrome
is not different from controls. BMC Neurol 2014;14:185.
. Üçeyler N, Valenza R, Stock M, Schedel R, Sprotte G, Sommer C. Reduced levels of antiinflammatory cytokines in patients with chronic widespread pain. Arthritis Rheum 2006;54:2656–64.
. Üçeyler N, Zeller D, Kahn AK, Kewenig S, Kittel-Schneider S, Schmid A, Casanova-Molla J, Reiners K, Sommer C. Small fibre pathology in patients with fibromyalgia syndrome
. Brain 2013;136(Pt 6):1857–67.
. Vlachos IS, Paraskevopoulou MD, Karagkouni D, Georgakilas G, Vergoulis T, Kanellos I, Anastasopoulos IL, Maniou S, Karathanou K, Kalfakakou D, Fevgas A, Dalamagas T, Hatzigeorgiou AG. DIANA-TarBase v7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions. Nucleic Acids Res 2015;43(Database issue):D153–59.
. Vlckova-Moravcova E, Bednarik J, Dusek L, Toyka KV, Sommer C. Diagnostic validity of epidermal nerve fiber densities in painful sensory neuropathies. Muscle Nerve 2008;37:50–60.
. Von Korff M, Ormel J, Keefe FJ, Dworkin SF. Grading the severity of chronic pain. PAIN 1992;50:133–49.
. von Schack D, Agostino MJ, Murray BS, Li Y, Reddy PS, Chen J, Choe SE, Strassle BW, Li C, Bates B, Zhang L, Hu H, Kotnis S, Bingham B, Liu W, Whiteside GT, Samad TA, Kennedy JD, Ajit SK. Dynamic changes in the microRNA
expression profile reveal multiple regulatory mechanisms in the spinal nerve ligation model of neuropathic pain. PLoS One 2011;6:e17670.
. Wang H, Moser M, Schiltenwolf M, Buchner M. Circulating cytokine levels compared to pain in patients with fibromyalgia—a prospective longitudinal study over 6 months. J Rheumatol 2008;35:1366–70.
. Wang XH. MicroRNA
in myogenesis and muscle atrophy. Curr Opin Clin Nutr Metab Care 2013;16:258–66.
. Wolfe F, Smythe HA, Yunus MB, Bennett RM, Bombardier C, Goldenberg DL, Tugwell P, Campbell SM, Abeles M, Clark P, Fam AG, Farber SJ, Fiechter JJ, Franklin CM, Gatter RA, Hamaty D, Lessard J, Lichtbroun AS, Masi AT, McCain GA, Reynolds WJ, Romano TJ, Russell IJ, Sheon RP. The American College of Rheumatology 1990 criteria for the classification of fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum 1990;33:160–72.
. Xu G, Sima AA. Altered immediate early gene expression in injured diabetic nerve: implications in regeneration. J Neuropathol Exp Neurol 2001;60:972–83.
. Xu QG, Li XQ, Kotecha SA, Cheng C, Sun HS, Zochodne DW. Insulin as an in vivo growth factor. Exp Neurol 2004;188:43–51.
. Zhang J, Zhang L, Fan R, Guo N, Xiong C, Wang L, Jin S, Li W, Lu J. The polymorphism in the let-7 targeted region of the Lin28 gene is associated with increased risk of type 2 diabetes mellitus. Mol Cell Endocrinol 2013;375:53–7.
. Zhao X, Dou W, He L, Liang S, Tie J, Liu C, Li T, Lu Y, Mo P, Shi Y, Wu K, Nie Y, Fan D. MicroRNA
-7 functions as an anti-metastatic microRNA
in gastric cancer by targeting insulin-like growth factor-1 receptor. Oncogene 2013;32:1363–72.