MicroRNA as a diagnostic biomarker and therapeutic agent for small fiber neuropathy

Abstract

This patent application describes miRNAs in the diagnosis of small fiber neuropathy (SFN) and miRNAs as therapeutic agents for small fiber neuropathy (SFN).

Description

[Technical Field]

[0001] Small fiber neuropathy (SFN) is a multifactorial condition affecting Aδ and C fibers. Typical clinical symptoms include symmetrical, length-dependent, and autonomic sensory symptoms, often accompanied by chronic neuropathic pain that significantly impairs the patient's daily life. 1 .

[0002] Due to its complexity and lack of evidence regarding its pathophysiological mechanisms, existing treatment strategies are symptom-limited, insufficient, and based on trial-and-error approaches.

[0003] Due to their pleiotropic nature and ability to regulate multiple molecular pathways and mediate intercellular communication, microRNAs (miRNAs) are potential therapeutic targets in complex diseases. [Background technology]

[0004] To date, preclinical and clinical studies have identified various miRNAs involved in axonal degeneration that influence axonal guidance signals and mediate local post-transcriptional and post-translational changes in the axonal microenvironment. 2,3 However, the role of each miRNA is strongly dependent on the microenvironment in which it is expressed, especially in multifactorial diseases.

[0005] The paper by Huang Chen et al., "MicroRNAs in autoimmune liver diseases: from diagnosis to potential therapeutic targets," BIOMEDICINE & PHARMACOTHERAPY, ELSEVIER, FR, vol. 130, (2020-08-09), and the international patent application WO 2016 / 144265, describe microRNA-26b-5p and microRNA-20a-5p. [Overview of the project]

[0006] The inventors of this patent application have surprisingly revealed that a specific miRNA is significantly correlated with the degree of intraepidermal nerve fiber (IENF) degeneration in the pathophysiology of SFN. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 shows the design of the research that led to the present invention.

[0008] [Figure 2] Figure 2 shows the morphological and molecular profiles of skin biopsy samples from SFN patients. (A) Model of cutaneous innervation of the lower extremities in healthy subjects (HC) and patients with SFN of unknown cause. Skin biopsy samples were immunostained with an antibody against phosphoglycolate phosphatase 9.5 (PGP9.5) and obtained by bright-field microscopy. Patients with SFN show a decrease in IENF. (B) An unsupervised heatmap shows the different miRNA expression profiles, expressed by ΔCq values, between SFN patients and HC patients.

[0009] [Figure 3]Figure 3 shows that miR-26b-5p miRNA and miR-20a-5p miRNA are downregulated in the epidermis of SFN patients. A) Box plots of miR-26b-5p in the exploratory and validation cohorts showing downregulation in SFN compared to HC. Comparison was performed by applying the Wilcoxon-Mann-Whitney test. P values ​​corrected for BH are shown in the graph; B) and C) Correlation between delta IENFD values ​​and miR-26b-5p expression in subjects recruited in the exploratory (B) and validation (C) stages. D) Correlation between miR26b-5p expression and miR20a-5p expression. E) Box plots of miR-20a-5p in the exploratory and validation cohorts showing downregulation in SFN compared to HC. Comparison was performed by applying the Wilcoxon rank-sum test. Uncorrected p values ​​are reported because miRNAs did not survive the multiple test corrected analysis. F) and G) Spearman correlation between miR-20a-5p expression and delta IENFD value in subjects recruited in the exploration (F) and validation (G) steps. Spearman correlation coefficients and p-values ​​are shown in the graph. H) ROC analysis shows significant discriminative ability of SFNs.

[0010] [Figure 4] Figure 4 shows the Pearson correlation, which illustrates the functional relationship between miR-20a-5p miRNA and miR-26b-5p miRNA and their gene targets.

[0011] [Figure 5] Figure 5 shows in situ hybridization revealing that miR-26b-5p is mainly expressed in the epidermis. [Modes for carrying out the invention]

[0012] Object of the invention In its first purpose, the present invention describes the use of miRNA in the diagnosis of small fiber neuropathy (SFN).

[0013] For a second purpose, the miRNA of the present invention is described for pharmaceutical use in the treatment of small fiber neuropathy (SFN).

[0014] For a third purpose, the use of the same miRNA for identifying a compound for the treatment of small fiber neuropathy is described.

[0015] Detailed Description of the Invention In accordance with a first purpose, the present invention describes the use of miRNA in the diagnosis of small fiber neuropathy (SFN).

[0016] In particular, said miRNA is as follows: [Table 1]

[0017] In a first aspect of the present invention, when one or both of the above two miRNAs are identified and downregulated, it is diagnosed as small fiber neuropathy.

[0018] In a preferred aspect, when miR-26b-5p is downregulated, it is diagnosed as small fiber neuropathy.

[0019] In a more preferred aspect, when at least miR-26b-5p and optionally miR-20a-5p are identified and downregulated, it is diagnosed as small fiber neuropathy.

[0020] In particular, the concentration of said miRNA is measured in an isolated sample represented by the epidermis of a patient suspected of having the disease.

[0021] More particularly, the fact of being downregulated is determined in comparison with healthy controls (HC).

[0022] For a second purpose, the miRNA of the present invention is described for pharmaceutical use in the treatment of small fiber neuropathy (SFN).

[0023] For this purpose, each of the two miRNAs mentioned above can be used in therapy, or both can be used together.

[0024] In a third objective, the use of the miRNA to identify compounds for the treatment of small fiber neuropathy is described.

[0025] Research objectives and design This study revealed the epidermal molecular profile associated with severe degeneration of intraepidermal nerve fiber (IENF) density. Skin biopsy samples were collected from SFN patients and healthy controls (HC). miRNA profiling was performed in two independent steps: exploration (N=13) and validation (N=20), which allowed for the identification of two closely related miRNAs with significantly different expression in SFN patients. Correlation analysis of gene expression profiling at the mRNA level and miRNA expression levels was performed to investigate the effects of the two candidate miRNAs on their target transcripts.

[0026] In situ hybridization was used to identify the cellular location of miRNAs (Figure 5). Furthermore, homogeneous selection of the cohort allowed for the identification of epidermal-specific miRNAs, which are a powerful element for characterizing small-diameter fiber neuropathy and could serve as an additional marker in clinical trials.

[0027] Target recruitment Patients (n=18) were recruited sequentially from the SFN outpatient clinic at Fondazione IRCCS Istituto Neurologico Carlo Besta (Milan, Italy). Healthy controls (HC, n=15) were recruited through the PAIN-Net project (grant contract number 721841).

[0028] The selection criteria for SFN of unknown cause are as follows: the presence of pain or sensory disturbance with both length-dependent and diffusive distributions, decreased intraepidermal nerve fiber density degeneration, and the absence of an underlying clinical condition.

[0029] Skin biopsy samples are used in the standard procedure for the diagnostic assessment of intraepidermal nerve fiber density from all registered subjects. 5 The samples were collected in accordance with the guidelines. All subjects provided written informed consent and participated in the study.

[0030] Figure 1 shows the study. Specifically, skin biopsy samples from two test groups (small fiber neuropathy, SFN, and healthy controls, HC) were analyzed in two independent steps: exploration and validation. Two miRNAs were downregulated in patients with small fiber neuropathy and acted synergistically with each other in SFN patients compared to HC. The remaining RNA samples (13 SFN and 10 HC available) were used for gene transcript profiling with miRNA targets, making it possible to identify genes (DEGs) expressed in different ways in SFN patients compared to the HC group. Subsequently, experimental data of miRNAs and mRNAs were used to predict in silico the biological processes, gene ontology (GO) terms, and potentially altered pathways in the cutaneous microenvironment of SFN disease. Finally, functional miRNA-mRNA networks in SFN patients were reconstructed using experimental and computational data.

[0031] Skin biopsy and evaluation of intraepidermal nerve fiber density (IENFD). For the evaluation of IENFD, 3 mm diameter skin biopsy samples were obtained from the distal lower extremities of all subjects, following the previously reported protocol. 5The samples were processed accordingly. Briefly, the samples were fixed in a 2% paraformaldehyde-lysine-periodate solution at 4°C for 24 hours, cryoprotected overnight at 4°C, sequentially cut into 50 μm sections using a cryostat, and stored at -20°C until further processing. To evaluate IENFD, the 50 μm sections were immunostained with antibody against protein gene product 9.5 (1:500, Ultraclone). IENFD was quantified using a Zeiss bright-field microscope and compared to previously reported standards. 5、6 The calculation was performed using [the specified method].

[0032] Isolation of RNA from skin biopsy tissue From the epidermis of two 50 μm skin biopsy sections of each subject, excised under a microscope, TruXtract FFPE total RNA kit (Covaris, cat. no. PN520220) was used for the exploratory cohort, and PureLink was used for the validation cohort. 商標 Total RNA was isolated using the FFPE Total RNA Isolation Kit (Invitrogen, cat. no. K1560-02) according to the manufacturer's instructions. RNA purity, concentration, and integrity were measured using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific) before preparing the miRNA array. All RNA samples that achieved a suitable purity ratio (A260 / A280 = 1.7-2.0) were used for subsequent analysis.

[0033] Quantification The quantification of miRNA expression was pre-amplified and used a pre-designed TaqMan containing 754 miRNAs. 商標 The procedure was performed using Array Human MicroRNA A+B cards (Thermo Fisher) according to the manufacturer's instructions. In short, 15 ng of total RNA was reverse transcribed, followed by pre-amplification of cDNA. The pre-amplification product was diluted in 75 μl of 0.1xTE buffer, pH 8.0, and used for the RT-qPCR reaction. The PCR reaction mixture consisted of 9 μl of diluted pre-amplification product and 450 μl of TaqMan 商標It was prepared using Fast Advanced Master Mix and 441 μl of nuclease-free water. 100 μl of the PCR mixture was filled into each card tank and centrifuged. The RT-qPCR experiment was performed on a ViiATM 7 Fast Real-Time PCR System (Thermo Fisher Scientific). The following cycle protocol was used: enzyme activation at 92 °C for 10 minutes, followed by 40 cycles of denaturation at 95 °C for 1 second and annealing at 60 °C for 20 seconds. The reaction volume for each microwell was 1 μl.

[0034] Gene expression quantification Gene transcript expression was quantified by means of a custom TaqMan 商標 microfluidic card array. 95 preferentially selected gene transcripts were selected due to their involvement in neuropathic pain-related pathways. Each custom array was used to analyze 4 subjects at a time. The RNA remaining after miRNA analysis was reused and new quality control was performed. 23 subjects (13 SFN and 10 HC) with sufficient samples were analyzed. Invitrogen 商標 SuperScript 商標 VILO 商標 Reverse transcription was performed using an Invitrogen SuperScript VILO cDNA Synthesis Kit (Thermo Fisher Scientific) to reverse transcribe 50 ng of total RNA into cDNA. Subsequently, the pre-amplification step was performed simultaneously on all samples. The pre-amplification PCR reaction was carried out under the following thermal cycle conditions: enzyme activation at 95 °C for 10 minutes, followed by 14 cycles of denaturation at 95 °C for 15 seconds and annealing at 60 °C for 4 minutes. The enzyme was inactivated at 99 °C for 10 minutes. Subsequently, the samples were diluted with 1X TE buffer (dilution factor of 1:20) and a PCR mixture was prepared. The card tanks were filled with 100 μl of the prepared mixture and run on a ViiATM 7 Fast Real-Time PCR System (Thermo Fisher Scientific) with the following thermal protocol: enzyme activation at 95 °C for 10 minutes, followed by 40 cycles of denaturation at 95 °C for 15 seconds and annealing at 60 °C for 1 second. The reaction volume for each microwell was 1 μl.

[0035] Relative thresholding method The manufacturer indicated that the "relative thresholding" (CRT) method was the most robust method for analyzing the data. 7 All PCR raw data was imported into the DataConnect cloud in real time, and an automated CRT threshold was applied using design analysis software (DA2) (Thermo Fisher Scientific, online version). This ensured that only miRNAs with good amplification quality (Ampscore > 1 and Cqconf > 0.8) were included in the analysis.

[0036] NormFinder analysis Accurate determination of relative miRNA levels ideally requires normalization using a reference or endogenous control that is constant, stable, uncontrolled, and unaffected by experimental conditions. For this reason, the quality and stability of the reference or control must be considered and selected within the sample of interest and the group being tested. NormFinder software was used for the selection of endogenous miRNAs for both the exploratory and validation steps in both pools (A+B). In the exploratory step, normalization was performed using hsa-miR-200b-002251 for pool A and hsa-miR-1201-002781 for pool B. In the validation step, the miRNAs used as references were hsa-miR-320-002277 (pool A) and hsa-miR-1247-002893 (pool B). The non-human exogenous ath-miR159a served as a negative control.

[0037] Relative expression analysis 2-ΔΔct using HC tissue as a reference group for differential expression of miRNAs 8 Quantification was performed using relative quantification by approach (QR). ΔΔCt was calculated as the mean ΔCt value of the target miRNA in the target group minus the mean ΔCt value of the target miRNA in the reference group. Therefore, the fold change in expression was 2 -(ΔΔCq) It was calculated as follows.

[0038] In silico analysis of target genes To identify candidate target genes for differentially expressed miRNAs, in silico predictive analysis was performed by fully obtaining information from miRTarBase, TargetScan, and Tarbase resources. Furthermore, Cytoscape 3.9.1 9 ClueGO app (v2.5.8) and DAVID 10 Using software, we identified pathways and enriched biological processes from a list of target genes or genes known to be involved in axonal degeneration and maintenance.

[0039] miRNAscope and immunofluorescence analysis miRNAscope 商標 In-situ hybridization (ISH) of microRNAs using the LS Reagent Kit red (Advanced Cell Diagnostics, Hayward, CA, USA) was performed to localize miR-26b-5p in skin biopsy tissue. ISH was performed according to the kit guidelines. Briefly, on day 1, tissue adhesion was performed according to the manufacturer's instructions to create a hydrophobic barrier. The slides were dried overnight, and on day 2, ISH was performed using a human-specific miRNA probe (miR-26b-5p). Subsequently, a fluorescent probe was incubated to identify cell nuclei (DAPI, Invitrogen, cat.no. D1306).

[0040] statistical analysis The association between miRNA levels and clinical phenotype (SFN vs. HC) was analyzed using the Wilcoxon-Mann-Whitney U test. The FDR-Benjamini-Hochberg method was applied as a correction for multiple testing. Correlation analysis between candidate miRNA expression and putative target gene expression was performed using the Spearman correlation test, where a coefficient of ≥0.5 or ≤-0.5 and p<0.05 were considered statistically significant. Receiver operational characteristic (ROC) curves and area under the curve (AUC) were calculated to evaluate the ability of each miRNA to distinguish between SFN and HC patients in the validation process. To investigate the diagnostic accuracy of multiple miRNA combinations, combined ROC curves were calculated using multiple logistic regression analysis.

[0041] Statistical analysis was completed using the statistical programming language R, version 3.6, and STATA11 software.

[0042] result Searching for and validating novel epidermal miRNA candidates related to SFN.

[0043] Research design and samples To investigate the epidermal molecular profile of SFN compared to HC patients, a combined analysis of miRNA and mRNA expression was performed (Figure 1). This study included an initial exploration cohort of 6 patients with SFN of unknown cause and 7 HC patients, analyzed using TaqMan Human MicroRNA cards containing 754 miRNAs. Furthermore, an independent validation cohort of 11 SFN patients and 8 HC patients was included to confirm the miRNA profiling results, using the same methodology. In addition, mRNA expression analysis of 95 gene targets involved in pathways related to neuropathic pain was performed in 13 SFN patients and 10 HC patients for whom biological material was still available.

[0044] Table 1 shows the demographic and clinical characteristics of the test group.

[0045] There were no significant differences between SFN patients and HC patients in terms of sex (p=0.59 in the exploration stage, p=0.55 in the validation stage) and age (p=1 in the exploration stage, p=0.20 in the validation stage).

[0046] All participants underwent skin biopsy sampling for evaluation of IENFD, and IENFD was significantly reduced in patients (Table 1 and Figure 2A). Only patients with a clear diagnosis of SFN were included in the study.

[0047] [Table 2] ["Eta" = age; "Sesso" = gender; "Distribuzione" = distribution; "Allodinia meccanica" = mechanical allodynia; "iperalgesia da puntura di spillo" = pinprick hyperalgesia; "Dolore (sintomi)" = Pain (symptom); "Prurito (sintomi)" = Itch (symptom); "Evocato" = Evocation; "Iperalgesia termica" = thermal hyperalgesia; "Disfunzione vasomotoria / sudomotoria (segni)" = Vasomotor / sweating dysfunction (signs); "Sensory profile" = Sensory profile; "Perdita sensoriale (segni)" = loss of sensation (sign); "Dolore profondo" = deep pain; "Freddo doloroso" = Painful cold; "Bruciore dolorante" = Painful burning sensation; "Bruciante" = Burning; "Pungente parossistico" = Paroxysmal stinging] Table 1. Demographic and clinical characteristics of the study population. Patients SFN1–SFN6 were analyzed in the exploratory phase, and patients SFN7–SFN18 were included in the validation phase. IENFD: Intraepidermal nerve fiber density; LD: Length-dependent pain distribution; N-LD: Non-length-dependent pain distribution; NRS: Pain rating scale; Sensory profile: TH: Thermal hyperalgesia; MH: Mechanical hyperalgesia; SL: Anesthesia.

[0048] miRNA profiling: the exploration process The microfluidic array contains 754 miRNAs to be evaluated in all samples. After quality filtering, expression data for 111 miRNAs present in over 90% of the samples are obtained using relative expression analysis. 11 The analysis was performed by applying the following method. Changes in the levels of 20 miRNAs that survived after multiple correction were observed in the epidermis of 6 SFN patients compared with 7 HC subjects, showing 13 downregulated miRNAs and 7 upregulated miRNAs that strongly distinguished the phenotypic groups (Figure 2B).

[0049] miRNA profiling: Verification process Next, a validation study was conducted using the same profiling approach on skin biopsy samples in independent cohorts of 12 SFN patients and 8 HC patients (Table 1 and Figure 1). Significantly different expression of miR-26b-5p was confirmed (corrected p-value BH = 3.28E-02, magnification change = -2.55), and the same downregulation pattern was confirmed in SFN patients at both stages (Figure 3A).

[0050] To investigate the relationship between miR-26b-5p expression and nerve innervation, Spearman analysis was performed. In both the exploratory phase (r=0.77, p=0.0053) and the validation phase (r=0.63, p=0.0055), a strong correlation was found between miR-26b-5p and denervation levels, calculated as the difference between the measured IENFD and the cutoff value (delta IENFD) (Figure 3B-C).

[0051] Considering the synergistic effects of miRNAs, we extended our study to include other miRNA candidates that did not survive statistical correction to clarify possible relationships with the miR-26-5p candidate. Expression correlation analysis revealed a strong linear relationship with miR-20a-5p (p=4.7e-07, R=0.88) (Figure 3D). miR-20a-5p showed a downward regulatory trend in SFN patients in both the exploratory phase (HR=-1.48, unadjusted p=4.80E-02) and the validation phase (HR=-2.08, unadjusted p=7.18E-03) (Figure 3E), and also showed a strong correlation with delta IENFD in both the exploratory phase (r=0.62, p=0.037) and the validation phase (r=0.66, p=0.0031) (Figures 3F-G).

[0052] In the epidermis, miR-26b-5p and miR-20a-3p exhibit strong discrimination ability against SFN. To test the ability of the two miRNA candidates to identify SFNs, ROC analysis was performed and the area under the curve (AUC) was calculated. miR-26b-5p achieved an AUC of 96.4% with a sensitivity of 91.7% and a specificity of 85.7%, while miR-20a-5p achieved an AUC of 86.9% with a sensitivity of 91.7% and a specificity of 81.4% (Figure 3H).

[0053] Identification and validation of miRNA targets To further investigate the potential roles of miR-26b-5p and miR-20a-5p, in silico predictive analysis of target transcripts was performed by searching three databases (miRTarBase, Tarbase, and TargetScan). The identified genes were then used for enrichment of biological pathways and processes (BPs). Significantly enriched terms (p<0.05) that were considered valid for neurodevelopment and maintenance, neuronal microenvironment homeostasis, and neurotrophic factor signaling were selected.

[0054] Gene expression analysis was performed using a custom panel of pain-related genes. Significant abnormal regulation of the expression of 8 genes was observed (Table 2A): 4 were downregulated (IKBKAP, MKNK2, PTGER3, and EDN1), and 4 were upregulated (MEF2C, SLC25A36, NTRK2, and PIK3CG).

[0055] Table 2A [Table 3]

[0056] Gene expression analysis revealed changes in the epidermal expression of eight genes.

[0057] We used paired Pearson correlations to identify the functional relationship between miRNA and target mRNA expression. Correlation analysis applied to each miRNA and its putative target revealed significant changes in SFN patients (Tables 2A and 2B and Figure 4). Our analysis showed correlations between IKBKAP expression levels and miR-26b-5p (r=-0.75) and miR-20a-5p (r=-0.62), with miR-26b-5p (r=0.75) and miR-20a-5p (r=0.67) being significantly correlated with MEF2C. Both miRNAs were also correlated with MKNK2 (miR-20a-5p (r=-0.52)). miR-26b-5p (r=-0.53) correlated with PIK3CG (miR-20a-5p (r=0.53), miR-26b-5p (r=0.53)) and SLC25A36 (miR-20a-5p (r=0.48), miR-26b-5p (r=0.56)), and miR-20a-5p expression was shown to correlate with NTRK2 (r=0.59).

[0058] Table 2B [Table 4]

[0059] Genetic annotation analysis To identify the biological terms associated with the abnormally regulated genes, in silico gene annotation analysis was performed. The abnormally regulated genes that survived the Benjamini-Hochberg correction were imported into the software, and the most appropriate terms (pathways and biological processes) were selected from the relevant terms, taking into account the analyzed tissues.

[0060] In situ hybridization of miR-26b Our miRNA profiling revealed a novel molecule that plays a role in regulating SFN progression; to investigate its cellular location, we performed the miRNAscope in situ hybridization assay, a technique known for its high sensitivity in miRNA detection. In this experiment, we show that miR-26b-5p is highly concentrated in human epidermis (Figure 5).

[0061] The advantages of the present invention will become immediately apparent from the above.

[0062] In particular, the roles of miR-26b-5p and miR-20a-5p were confirmed in distinguishing between patients with small-diameter fiber neuropathy and healthy controls. ROC analysis confirmed their predictive ability, showing diagnostic accuracy of 96.4% and 86.9%, respectively.

[0063] The strong correlation observed between nerve innervation density (delta IENFD) and miR-26b-5p or miR-20a-5p expression supports the hypothesis that miRNAs are involved in the maintenance of intraepidermal fibers, and significant downregulation of the two miRNAs is consistent with a decrease in cutaneous innervation.

[0064] The roles of these two miRNAs also provide an important foundation for the development of preventive strategies and drug therapies.

[0065] References 1. Devigili, G., Cazzato, D. & Lauria, G. Clinical diagnosis and management of small fiber neuropathy: an update on best practice. Expert Rev Neurother 20, 967-980 (2020). https: / / doi.org:10.1080 / 14737175.2020.1794825 2. Wang, B. & Bao, L. Axonal microRNAs: localization, function and regulatory mechanism during axon development. J Mol Cell Biol 9, 82-90 (2017). https: / / doi.org:10.1093 / jmcb / mjw050 3. Maimon, R. et al. miR126-5p Downregulation Facilitates Axon Degeneration and NMJ Disruption via a Non-Cell-Autonomous Mechanism in ALS. J Neurosci 38, 5478-5494 (2018). https: / / doi.org:10.1523 / JNEUROSCI.3037-17.2018 4. Chakraborty, C., Sharma, A. R., Sharma, G. & Lee, S. S. Therapeutic advances of miRNAs: A preclinical and clinical update. J Adv Res 28, 127-138 (2021). https: / / doi.org:10.1016 / j.jare.2020.08.012 5. Lauria, G. et al. Intraepidermal nerve fiber density at the distal leg: a worldwide normative reference study. J Peripher Nerv Syst 15, 202-207 (2010). https: / / doi.org:10.1111 / j.1529-8027.2010.00271.x 6. Lauria, G. & Devigili, G. Skin biopsy as a diagnostic tool in peripheral neuropathy. Nat Clin Pract Neurol 3, 546-557 (2007). https: / / doi.org:10.1038 / ncpneuro0630 7. Biosystems, A. 8. Schmittgen, T. D. & Livak, K. J. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc 3, 1101-1108 (2008). https: / / doi.org:10.1038 / nprot.2008.73 9. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13, 2498-2504 (2003). https: / / doi.org:10.1101 / gr.1239303 10. Huang, d. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4, 44-57 (2009). https: / / doi.org:10.1038 / nprot.2008.211 11. Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25, 402-408 (2001). https: / / doi.org:10.1006 / meth.2001.1262

Claims

1. The use of miRNAs in the diagnosis of small fiber neuropathy (SFN) in patients, wherein the miRNA is any or both of the following: Table 1

2. The use of miRNAs in the diagnosis of small fiber neuropathy (SFN) in a patient according to a preceding claim, wherein either or both of the miRNAs are downregulated compared to a healthy control.

3. The use of miRNA in the diagnosis of small fiber neuropathy (SFN) in a patient according to prior claim 1 or 2, wherein the concentration of the miRNA is measured in an isolated epidermal sample from the patient.

4. miRNAs for medicinal use in the treatment of small fiber neuropathy (SFN) in patients, wherein the miRNA is any or both of the following: Table 2

5. Use of miRNA to identify therapeutic compounds for the treatment of small fiber neuropathy (SFN) in patients, wherein the miRNA is any or both of the following: Table 3

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