578771
research-article2015
MSJ0010.1177/1352458515578771Multiple Sclerosis JournalR Gandhi
MULTIPLE SCLEROSIS MSJ JOURNAL
Topical Review
miRNA in multiple sclerosis: search for novel biomarkers
Multiple Sclerosis Journal 1–9 DOI: 10.1177/ 1352458515578771 © The Author(s), 2015. Reprints and permissions: http://www.sagepub.co.uk/ journalsPermissions.nav
Roopali Gandhi
Abstract: A major challenge in multiple sclerosis (MS) is to develop biomarkers that could help in understanding individual MS patients, i.e. whether they are a responder or non-responder to therapy, which medicine is more effective, and the degree to which they may be entering the progressive phase of disease. In the last few years, a lot of attention has been drawn toward identification of diagnostic, prognostic, process-specific, and treatment-related biomarkers for MS. In this review, we will focus on the micro RNAs (miRNAs) as potential candidates for MS biomarkers. Keywords: miRNAs, biomarkers, multiple sclerosis Date received: 17 December 2014; revised: 19 February 2015; accepted: 1 March 2015
miRNA as potential biomarkers miRNAs are a class of endogenous small, on average 22 nt long, non-coding RNAs that regulate gene expression at the post-transcriptional level by binding to complementary sequences in the 3′ or 5′ UTR (untranslated region) of the target mRNA.1–3 This usually results in translational repression or mRNA degradation leading to a decrease in encoded protein.4 In mammals, miRNAs are transcribed by RNA polymerase II as a monocistronic or polycistronic long primary transcript named primary miRNA (primiRNA). Pri-miRNAs are hairpin structures that have imperfect base-paired stems and range from about 200 nt to several kilobases in length. In the nucleus, the pri-miRNAs are cleaved by RNA polymerase III type endonucleases (Drosha), into premiRNAs. These pre-miRNAs are then transported to the cytoplasm by exportin-5 where they are cleaved by RNA polymerase III (Dicer) to produce a duplex of 20–22 nt. The duplex is unwound by helicase and the guide strand is loaded into the RNA-induced silencing complex (RISC) while the passenger strand is released. It has been thought that the passenger strand is degraded following release, though recent results from sequencing studies have provided evidence that the passenger strand itself may also target gene expression (Figure 1).5,6 The current update of miRbase (http://www.mirbase. org), the central repository of all miRNAs, reports 1900 identified mature human miRNAs.7 The
miRNAs nomenclature is very interesting. The letters preceding the miR such as hsa (Homo sapiens) or mmu (murine) represent the species of origin. The “miR” represents the mature and the “mir” represents the immature forms of miRNAs. The number after the “miR” denotes the order in which the miR was identified. For instance, hsa-miR-30e was discovered before the hsa-miR-125b. The letters after the number, such as a and b, represent similar miRNA sequences that are encoded by separate regions, e.g. hsa-miR30a, miR30b, and miR30c. These miRNAs with similar sequences could target the same genes due to the presence of a common binding sequence (seed sequence). Two mature miRNAs could originate from the same hairpin precursor and are named as miR-30a-5p and miR-30a-3p to indicate the strand of origin.
Correspondence to: Roopali Gandhi Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. [email protected]. edu
miRNAs play a critical role in multiple phenomena including development, organogenesis, and homeostasis.8 Dysregulated expression of miRNAs is associated with the onset of diseases such as immune disease, neurological disease, cardiovascular disease and cancer.9 Besides their existence within cells, miRNAs have been detected in several body fluids, including plasma, serum, cerebrospinal fluid (CSF), breast milk, urine, tears, semen, and saliva.10 Interestingly, researchers have observed significant differences in serum miRNA levels during disease and certain physiological states such as pregnancy.11
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Multiple Sclerosis Journal
Figure 1. Model showing miRNA biogenesis and function.
It is not clear whether circulating miRNAs are a byproduct of cellular degradation or if they are actively secreted into body fluids to regulate intercellular gene expression.12 miRNAs are highly stable in the blood, being resistant to circulating ribonucleases and severe conditions such as extended storage, freeze-thaw, and extreme pH due to their packaging in lipid vesicles such as exosomes, binding to RNA-binding protein, and association with high-density lipoprotein.13,14 Their stability, along with the development of sensitive methods of detection and quantification such as miRNA microarray, TaqMan low-density array (TLDA), beadbased assay, NanoString technique, and deep sequencing,15 makes them ideal candidates for a novel class of non-invasive, sensitive biomarkers. The quantitative polymerase chain reaction (qPCR) platform is a reliable and powerful method to measure low levels of circulating miRNAs. Microarrays are also commonly used but require more RNA. In a recent paper, Mestdagh et al. systematically compared 12 commercially available platforms for an identical set of 20 positive and negative control samples. These results provided metrics to objectively assess platform performance for reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The
results shown in Figure 2 (obtained from Mestdagh et al.) suggest that each platform has its weakness and strengths and that the platform should be selected based upon the study goals.16 miRNA and multiple sclerosis miRNA expression in MS lesions The use of miRNAs as biomarkers in MS is still evolving. The few studies that are published to date have used either whole blood, peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF), T cells, or multiple sclerosis lesions for miRNA expression analysis. In the first and only report of a comprehensive miRNA expression analysis in MS lesions, Junker et al. analyzed the expression level of 365 mature miRNAs by qPCR in 16 active and five inactive white matter MS brain lesions, and in nine control white matter specimens.17 The 10 most strongly upregulated miRNAs in active MS lesions were expressed by astrocytes. Among these, upregulated miRNAs, miR-34a, miR155, and miR-326 could putatively target CD47 and
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R Gandhi
Figure 2 (obtained from Mestdagh, Nature Method, 2014). Radial plot of performance metric z-score, obtained from Mestdagh et al.16 Platforms are divided into four technologies: qPCR, low-volume qPCR, hybridization and sequencing (as TM and TMp are essentially based on the same technology, only TMp is shown). Z-scores for eight metrics are shown. Ml, reproducibility; M2, titration response; M3, accuracy; M4, accuracy low-input RNA; M5, sensitivity; M6, sensitivity lowinput RNA; M7, specificity MS2 RNA; M8, assay cross-reactivity. Metrics were transformed in such way that a higher metric value (z-score) corresponds to a better performance (online methods). Each radial plot has an identical scale, which makes plots directly comparable. EX-miRCury (Exiqon), QU-qScript (Quanta BioSciences), QI-miScript (Qiagen), TMp-Taqman Cards preAmp (Life Technologies), WA-Smartchip (WaferGen), OA-Open Array (Life Technologies), AG-Microarray (Agilent), NS-nCounter (Nanostring), AF-Microarray (Affymetrix), IL-TruSeq (Illumina), IT-Ion Torrent (Life Technologies).
play a role in MS pathology by releasing macrophages from inhibitory control.17 miR-155 is involved in Th17 cell development and has been linked to MS.17,18 miR326 is also increased in PBMCs and CD4+ T cells isolated from relapsing MS patients and may play a role in the disease by increasing pathogenic Th17 cell development via targeting of the transcription factor ets-1.19
miRNA expression in blood Otaegui et al. isolated PBMCs from a group of MS patients (4 in relapse, 9 in remission, and 8 healthy controls (HCs)) and analyzed the expression patterns of
364 miRNAs using real time (RT)-qPCR.20 Results from this study showed that the expression of miR-18b, miR-493, and miR-599 was increased in relapsing patients compared to the control group. Validation of these results in a separate group (MS 3 remission, 4 relapse, and 7 HC) revealed that miR-18b and miR-599 may be relevant at the time of relapse. miR-96 was linked to remission and has putative gene targets in interleukin and wnt signaling.20. In another study using paxgene tubes, miRNA screening was performed by microarray to analyze the miRNA expression patterns from relapsing–remitting
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Multiple Sclerosis Journal MS (RRMS; n = 20) and HCs (n = 19). Significantly, dysregulated miR-145 could differentiate MS patients and HCs with an accuracy, specificity, and sensitivity of 89.7%, 89.5%, and 90.0%, respectively. However, some of the MS patients in this study were treated with either glatiramer acetate or interferon-β.21 Other studies, discussed later, have also found that miR-145 is significantly associated with MS patients.22,23 In a another study,24 the same group also used next generation sequencing (NGS), microarray analysis, and RT-qPCR in whole blood samples from treatmentnaïve patients with clinically isolated syndrome (CIS; n = 25), RRMS (n = 25), and 50 HCs to study miRNA expression patterns. Two miRNAs were found to be significantly downregulated (miR-20a-5p, miR-71-3p) and one miRNA was upregulated (miR-162-3p) by using both RNA Seq and microarray methods.24 In another study,25 the expression profile of 1145 miRNAs in PBMCs of 19 MS patients including RRMS (n = 7), secondary progressive MS (SPMS; n = 6), primary progressive MS (PPMS; n = 6), and 14 controls was analyzed using Illumina BeadArray. Some of the patients involved in this study had been treated with immunosuppressive drugs, interferon-β, or both. This study found a dysregulated expression of a total of 104 miRNAs in MS patients compared to the controls. However, during validation in a separate group of individuals using qPCR, only 2 miRNAs, let-7g and miR-150, were found to be different.25 Altered expression of let-7g was also found in another study with 18 PPMS, 17 SPMS, and 24 RRMS patients using miRNA microarrays.26 In addition, this same study confirmed a significantly decreased expression of miR-20a and miR-17 using qPCR. These miRNAs are involved in T cell activation and the target genes for these miRNAs were upregulated in MS whole blood RNA.26 The observed downregulation of miR-20a in this study has also been reported in other MS studies,21,24 as discussed above. In a more recent study, Sondergaard et al. analyzed miRNA expression profiles of PBMCs isolated from 20 treatment-naïve RRMS patients and 21 HCs using miRNA microarrays and identified 46 differentially expressed miRNAs in MS patients,22 of which 17 miRNAs were upregulated and 29 miRNAs downregulated. Selected miRNAs were analyzed again in a validation group using qPCR in 12 treatment-naïve RRMS patients and 20 HCs. However, in the validation cohort, only 2 miRNAs, let-7d and miR-744, showed significant upregulation in MS patients compared to the controls. In another study, Waschbisch et al. obtained PBMCs from patients with RRMS and analyzed the relative
expression of five selected miRNAs (miR-20b, miR142-3p, miR-146a, miR-155, and miR-326) by qPCR.27 These miRNAs were selected based upon their previous reported function in Th17 cell differentiation (miR-326 and miR-155, discussed in previous section), regulation of immune tolerance (miR-142-3p and miR-146a), or innate immunity (miR-146a). They compared the miRNA expression levels between treatment-naive patients (n = 36) and healthy controls (n = 32). They observed the expression of miR142-3p, miR-146a, miR-155, and miR-326 was remarkably increased in untreated RRMS patients compared to HCs. Further, they showed that the combination of miR-142-3p, miR-146a, and miR-155 yielded the best results in predicting disease with a sensitivity of 77.8% and a specificity of 88.0% (AUC 0.77).27 miRNA expression in circulating T cells of MS patients MS is an inflammatory disease associated with IFN-γproducing Th1 and IL-17- producing Th17 cells.28–30 miRNAs play a role in both T cell development in the thymus and their differentiation in periphery. De Santis et al. profiled regulatory CD4+CD25high T cells from 12 untreated RRMS patients and 14 HCs using an miRNA microarray and found differential expression of 23 miRNAs in regulatory CD4+CD25high T cells from MS patients compared to HCs.31 These results were validated using real time-PCR and CD4+CD25highCD127low cells, these results confirmed the upregulation of miR106b, miR-19a, miR-19b, and miR-25 in CD4+CD25high of MS subjects compared to healthy subjects. miR106b and miR-25 modulate the TGF-β signaling pathway and dysregulated expression of these miRNAs may alter regulatory T cell biology in MS.31 In another study, Lindberg et al. used CD4+, CD8+ T cells, and B cells from 8 RRMS and 10 HCs to analyze the miRNA expression profile by TaqMan array and found that the miR-17-5p was upregulated in CD4+ T cells isolated from MS patients.32 The miR-17-5p belongs to the miR-17-92 cluster and plays an important role in the development of autoimmunity and lymphoproliferative diseases in mice.32,33 Another study by Guerau-deArellano et al. suggested increased expression of miR128 and miR-27b in naïve T cells and miR-340 in memory T cells isolated from MS patients.34 All of these miRNAs are involved in suppressing Th2 differentiation and enhancing Th1 mediated autoimmune responses.34 Another similar study showed altered expression of miR-29b in MS T cells and its involvement in controlling expression of IFN-γ and Th1 transcription factor, T-bet.35 A more recent study on miRNA analysis in T cells by miRNA microarray by Jernas et
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R Gandhi al. used 11 RRMS patients (treated with interferon β) and 9 HCs,36 identifying 21 miRNAs that were decreased in MS patients. Of these 21 differentially expressed miRNAs, 20 miRNAs have immune system related target genes. They confirmed the expression of two selected miRNAs (miR-494 and miR-197) by using quantitative PCR.36 miRNA expression in serum or plasma of MS patients The stable expression of miRNAs in serum and plasma makes them an important candidate for a biomarker study. However, in the case of MS, there are only two reported studies that have analyzed circulating miRNA. In the first study on circulating miRNA in MS, Siegel et al. conducted a miRNA microarray analysis of over 900 known miRNA transcripts from plasma samples collected from four MS patients and four HCs.37 They identified six plasma miRNAs (miR-614, miR-572, miR-648, miR-1826, miR-422a and miR-22) that were significantly upregulated and one plasma miRNA (miR-1979) that was significantly downregulated in MS patients.37 In a more recent study by our group, we analyzed a total of 368 miRNAs in plasma samples of 10 RRMS, 9 SPMS, and 9 HCs using miRNA RT-qPCR.38 We found that twenty-nine miRNAs distinguished RRMS from HCs, 35 miRNAs distinguished SPMS from HCs, and 16 miRNAs distinguished RRMS from SPMS. The 20 selected miRNAs were further validated on a larger cohort of 100 MS patients, 15 amyotrophic lateral sclerosis (ALS) and 32 controls using RT-qPCR. Among the validated miRNAs, we identified miR-92a-1* in the largest number of comparisons. It was different in RRMS versus SPMS, and RRMS versus HCs, and showed an association with EDSS and disease duration. The miRNA miR-92 has target genes involved in cell cycle regulation and cell signaling.38 let-7a differentiated SPMS from HCs and RRMS from SPMS. The let-7 family of miRNAs is known to regulate stem cell differentiation and T cell activation, activate Toll-like receptor 7, and are linked to neurodegeneration.39–43 The miR-454 differentiated RRMS from SPMS, and miR-145 differentiated RRMS from HCs and RRMS from SPMS. miR-145 findings were in consensus with previous studies in MS.21,22 Interestingly, the same circulating miRNAs (let-7 and miR-92) that were differentially expressed in RRMS versus SPMS also differentiated ALS from RRMS subjects, but were not different between SPMS and ALS, suggesting that similar processes may occur in SPMS and ALS.23 Sondergaard et al. study discussed miRNA expression in blood, also measured
miRNA expression in plasma samples from 22 MS patients and 22 HCs. They found that the expression of miR145 was most significantly different in MS compared with controls (22). miRNA expression in CSF of MS patient In the only published study involving miRNA analysis in CSF of MS patients, Haghikia et al. tested global miRNA profiles to screen for reported miRNAs,44 followed by single selected RT-qPCR to validate candidate miRNAs. They used the CSF of 53 patients with MS and 39 patients with other neurologic diseases (OND) for global miRNA profiling. This study showed that miR-922, miR-181c, and miR-633 are differentially regulated in patients with MS as compared with OND. Importantly, miR-181c and miR633 differentiated RRMS from SPMS with 82% specificity and 69% sensitivity.44 miRNAs as treatment response biomarkers in MS Several studies have evaluated the effect of MS therapies on the regulation of mRNAs;45–47 however, studies involving the effect of MS treatments on the regulation of miRNAs are lacking. Such studies are not only important in identifying a marker to analyze treatment response, but also to understand the molecular mechanism of treatment. To date, there are only three published reports on the expression of miRNAs upon treatment in MS patients. In the first published study, Waschbisch et al. obtained PBMCs from patients with RRMS, and analyzed the relative expression of five selected miRNAs (miR-20b, miR-142-3p, miR-146a, miR-155, and miR-326) by qPCR (also discussed in miRNA expression in blood section).27 They compared the miRNA levels between treatmentnaive patients (n = 36), IFN-β-treated patients (n = 18: IFN-β1a i.m. n = 5, IFN-β1a s.c. n = 8, IFN-β1b s.c. n = 5), and patients treated with glatiramer acetate (n = 20). They excluded patients that were treated with glucocorticoids during the last four weeks before study entry. They observed the expression of the selected five miRNAs did not differ between treatment-naïve and IFN-β treated RRMS patients, the expression of miR-142-3p and miR-146a was significantly decreased in glatiramer acetate treated RRMS patients compared to the treatment naive MS patients.27 In another treatment response study, Sievers et al. tested 1059 miRNAs in B cells isolated from 10 untreated MS patients, 10 natalizumab treated MS patients, and 10 HCs using microarrays.48 These results showed that 10 miRNAs were differentially
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Multiple Sclerosis Journal expressed in B cells from natalizumab-treated patients compared to untreated patients. Expression of the miR-106b-25 and miR-17-92 clusters was dysregulated both in untreated and natalizumab-treated patients suggesting a role for these miRNAs in MS pathogenesis. Functional cooperation among these two miRNA clusters, characterized by a reduction in pre-B cells and increased apoptosis, was suggested previously in mice.48,49 In a recent study, Hecker et al. used microarrays to investigate the expression of miRNAs and mRNAs in PBMCs of patients with CIS or RRMS in response to IFN-β therapy.50 The blood samples were obtained longitudinally from six patients at four time points in the early phase of therapy, namely before the first (baseline), after second, and third IFN-β injection, as well as after one month of treatment. Upon comparing the expression levels at the three time points during therapy to the expression levels at baseline, 20 different miRNAs were filtered at various time points using MAID filtering method. This filtered method was previously discussed by Hecker et al. BMC Bioinformatics, 2009 and utilizes a t-statistic in conjunction with an MA-plot-based signal intensity-dependent fold-change criterion (referred to as MAID filtering) to select mRNA or miRNA with expression changes upon therapy. Of these 20 selected miRNAs, seven miRNAs appeared as upregulated and 13 miRNAs appeared as downregulated in response to the therapy. Two of the 20 miRNAs, miR-149-5p and miR-708-5p, were filtered at two different time points. For the remaining miRNAs, the expression changes were not very stable over the course of therapy. Most of the miRNAs (n = 14) were filtered as upregulated or downregulated one month after IFN-β treatment initiation, which corresponded with gene expression profiling. They used Affymetrix miRNA microarrays to replicate the miRNA measurements of the PBMC samples from three patients before the start of IFN-β therapy as well as after one month. These microarrays had a lower measurement range than the TaqMan miRNA arrays and 13 of the 20 filtered miRNAs showed the same trend of upregulation (let-7a-5p, let-7b-5p, miR-16-5p, miR-342-5p, miR-346, miR-518b) or downregulation (miR-29a-3p, miR-29b-1-5p, miR-29c-3p, miR-95, miR-149-5p, miR-181c-3p, miR-708-5p) with a significance threshold alpha = 0.10. Four miRNAs (miR29a-3p, miR-29c-3p, miR-193a-3p, and miR-532-5p) were confirmed to be downregulated during treatment. For further validation, they selected five of the 20 filtered miRNAs to quantify their expression in PBMCs of an independent cohort of 12 patients (8 RRMS/4 CIS) using TaqMan single-tube assays. The PBMCs were obtained in a longitudinal manner before the first
drug injection and after one month of treatment. During this step of validation, miR-29a-3p and miR-29c-3p could be confirmed as differentially expressed in response to IFN-β therapy. Expression of both miR29c-3P and miR-532-5P was significantly decreased compared to the pre-treatment sample. Although, miR16-5p and miR-149-5p showed the same trend of expression change as in the other data sets, but this was not statistically significant.50 Conclusion There is considerable excitement regarding the use of miRNAs in the biomarker field, which is well founded due to their stability and relative ease of detection. In this paper, we have reviewed the miRNA based studies carried out in MS patients in order to evaluate their potential as biomarkers. We observed a wide variety of results obtained by different groups (summarized in Table 1), which may reflect limitations associated with some studies, potentially due to the lack of a reliable assay platform, a low number of patients and the lack of strong validation using an alternative platform or set of patients. In general, we find that there is a paucity of comprehensive studies to evaluate miRNAs as biomarkers in MS. In order to develop a miRNA-based biomarker for MS or any disease, a most important prerequisite is the ability to quantify miRNAs from a variety of samples with sufficient sensitivity, accuracy and reproducibility. A number of variables such as specimen collection, RNA extraction, RT-qPCR, data analysis and normalization are some of the major challenges associated with miRNA-based studies. There is also considerable inter-sample variability in both the protein and lipid content of each individual’s serum and plasma, which can affect the efficiency of RNA extraction and introduce potential inhibitors to RT-qPCR. Another major issue associated with miRNA based study is normalization, amplification and contamination. Due to the low concentration of miRNAs in body fluids, their quantitation is not only difficult, but also requires occasional amplification, which in turn creates an additional variable. Most importantly, there is no consensus on suitable small RNA reference genes that could be used as internal controls for biological variability. A common practice is to process an identical input volume of samples, which is later corrected for technical variability using spiked-in synthetic nonhuman miRNA as a normalizing control.14,51 In addition, the quantification of miRNAs in serum/plasma can be altered by contamination by miRNAs leaked from cellular components of blood, either through hemolysis during sampling, processing, or by carryover of whole cells in the serum/plasma.
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PBMC, CD4+ T cells PBMC Whole blood
Whole blood PBMC Whole blood PBMC, Plasma CD4+ CD25+ T cells CD4+ T cells Naïve CD4+ T cells CD4+CD45RO+ T cells T cells
Plasma Plasma CSF PBMC B cells PBMC
RRMS
RRMS RRMS
CIS, RRMS
RRMS, SPMS, PPMS
RRMS, SPMS, PPMS RRMS
RRMS
RRMS
RRMS, SPMS, PPMS
RRMS, SPMS, PPMS
RRMS
Unspecified
RRMS, SPMS, PPMS RRMS, SPMS, PPMS
RRMS
RRMS CIS, RRMS
Otaegui et al.20 Keller et al.21
Keller et al.24
MartinelliBoneschi et al.25 Cox et al.26 Sondergaard et al.22
De Santis et al.31
Lindberg et al.32
Guerau-deArellano et al.34 Smith et al.35
Jernas et al.36
Siegel et al.37
Gandhi et al.23 Haghikia et al.44
Waschbisch et al.27
Sievers et al.48 Hecker et al.50
Tissue
Du et al.19
MS type MS brain lesions
al.17
SPMS, RRMS, PPMS
Junker et
Author
Table 1. miRNA-based biomarker studies in multiple sclerosis.
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Microarray TLDA
TLDA PCR array, RTqPCR Real-time PCR
Microarray
NanoString nCounter Microarray, Realtime PCR
TLDA
TLDA
Microarray LNA Microarray, Real-time PCR Microarray
NGS, Microarray, Real-time PCR BeadArray
TLDA Microarray
Real-time PCR
TLDA
Method
Treatment naïve, IFN-β, glatiramer acetate Natalizumab IFNβ
Untreated Unspecified
Unspecified
IFN-β
Treatment naïve
Treatment naïve
Treatment naïve and steroid free for 6 months No treatment for 6 months
Immunosuppressive, IFNβ, or both No treatment for 3 months Treatment naïve
Treatment naïve
Unspecified Glatiramer acetate, IFN-β, or none
Unspecified
Unspecified
Treatment
miR-19b, miR-551a, miR-106b, and miR-191 miR-29a-3p, miR-29c-3p, and miR-532-5p
miR-142-3p, miR-146a, miR-155, and miR-326
miR-494, miR-15b, miR-30c, miR-23a, miR-197, miR-1260b, miR-125a-5p, miR-361-5p, miR-320d, miR-423-3p, miR-1280, miR-663, miR-423-5p, miR99b, miR-339-5p, let-7a, miR-1979, miR-3178, miR625, miR-150, and miR-3153 miR-614, miR-572, miR-648, miR-1826, miR-422a, miR-22, and miR-1979 miR-30e, miR-92a-1*, Let-7a, miR-454, and miR-145 miR-922, miR-181c, and miR-633
miR-29b
miR-485-3p, miR-376a, miR-497, miR-193a, miR126, miR-17-5p, and miR-34a miR-128, miR-27b, and miR-340
miR-106b, miR-93, miR-19a, miR-19b, and miR-25
miR-17 and miR-20a let-7d, miR-744, and miR-145
miR-18b, miR-493, miR-96, and miR-599 miR-145, miR-186, miR-664, miR-20b, miR-422a, miR-142-3p, miR-584, miR-223, miR-1275, and miR491-5p miR-146b-5p, miR-7-1-3p, miR-20a-5p, miR-3653, miR-20b, miR-16-2-3p, miR-574-5p, and miR-1202 let-7g, miR-150
miR-650, miR-155, miR-326, miR-142-3p, miR-146a, miR-34a, miR-21, miR-23a, miR-199a, and miR-27a miR-326
Key miRNAs
R Gandhi
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Multiple Sclerosis Journal However, the studies published to date point towards miRNAs having a role in the future of MS biomarkers and to design proof of concept studies. It will require considerable effort from researchers in different fields to develop consensus protocols. The National Institutes of Health (NIH) is supporting these efforts by granting funds specifically to address these challenges in the field of miRNA as a disease biomarker. We believe it will not be long before the current challenges are overcome and a miRNA-based biomarker is established for MS. Conflict of interest The author declares that there is no conflict of interest. Funding This research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.
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38. Tsuchida A, Ohno S, Wu W, et al. miR-92 is a key oncogenic component of the miR-17–92 cluster in colon cancer. Cancer Sci 2011; 102: 2264–2271. 39. Grigoryev YA, Kurian SM, Hart T, et al. MicroRNA regulation of molecular networks mapped by global microRNA, mRNA, and protein expression in activated T lymphocytes. J Immunol 2011; 187: 2233–2243.
26. Cox MB, Cairns MJ, Gandhi KS, et al. MicroRNAs miR-17 and miR-20a inhibit T cell activation genes and are under-expressed in MS whole blood. PLoS One 2010; 5: e12132.
40. Kumar M, Ahmad T, Sharma A, et al. Let-7 microRNA-mediated regulation of IL-13 and allergic airway inflammation. J Allergy Clin Immunol 2011; 128: 1077–1085.
27. Waschbisch A, Atiya M, Linker RA, et al. Glatiramer acetate treatment normalizes deregulated microRNA expression in relapsing–remitting multiple sclerosis. PLoS One 2011; 6: e24604.
41. Lehmann SM, Kruger C, Park B, et al. An unconventional role for miRNA: let-7 activates Tolllike receptor 7 and causes neurodegeneration. Nat Neurosci 2012; 15: 827–835.
28. Olsson T, Zhi WW, Hojeberg B, et al. Autoreactive T lymphocytes in multiple sclerosis determined by antigen-induced secretion of interferon-gamma. J Clin Invest 1990; 86: 981–985.
42. Roush S and Slack FJ. The let-7 family of microRNAs. Trends Cell Biol 2008; 18: 505–516.
29. Lock C, Hermans G, Pedotti R, et al. Genemicroarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis. Nat Med 2002; 8: 500–508. 30. Voskuhl RR, Martin R, Bergman C, et al. T helper 1 (Th1) functional phenotype of human myelin basic protein-specific T lymphocytes. Autoimmunity 1993; 15: 137–143. 31. De Santis G, Ferracin M, Biondani A, et al. Altered miRNA expression in T regulatory cells in course of multiple sclerosis. J Neuroimmunol 2010; 226: 165–171. 32. Lindberg RL, Hoffmann F, Mehling M, et al. Altered expression of miR-17–5p in CD4+ lymphocytes of relapsing-remitting multiple sclerosis patients. Eur J Immunol 2010; 40: 888–898. 33. Xiao C, Srinivasan L, Calado DP, et al. Lymphoproliferative disease and autoimmunity in mice with increased miR-17–92 expression in lymphocytes. Nat Immunol 2008; 9: 405–414. 34. Guerau-de-Arellano M, Smith KM, Godlewski J, et al. Micro-RNA dysregulation in multiple sclerosis favours pro-inflammatory T-cell-mediated autoimmunity. Brain 2011; 134: 3578–3589. 35. Smith KM, Guerau-de-Arellano M, Costinean S, et al. miR-29ab1 deficiency identifies a negative feedback loop controlling Th1 bias that is dysregulated in multiple sclerosis. J Immunol 2012; 189: 1567–1576. 36. Jernas M, Malmestrom C, Axelsson M, et al. MicroRNA regulate immune pathways in T-cells in multiple sclerosis (MS). BMC Immunol 2013; 14: 32. 37. Siegel SR, Mackenzie J, Chaplin G, et al. Circulating microRNAs involved in multiple sclerosis. Mol Biol Rep 2012; 39: 6219–6225.
43. Swaminathan S, Suzuki K, Seddiki N, et al. Differential regulation of the Let-7 family of microRNAs in CD4+ T cells alters IL-10 expression. J Immunol 2012; 188: 6238–6246. 44. Haghikia A, Haghikia A, Hellwig K, et al. Regulated microRNAs in the CSF of patients with multiple sclerosis: a case-control study. Neurology 2012; 79: 2166–2170. 45. Minagar A. Current and future therapies for multiple sclerosis. Scientifica 2013; 2013: 249101. 46. Comabella M, Lunemann JD, Rio J, et al. A type I interferon signature in monocytes is associated with poor response to interferon-beta in multiple sclerosis. Brain 2009; 132: 3353–3365. 47. Rudick RA, Rani MR, Xu Y, et al. Excessive biologic response to IFNbeta is associated with poor treatment response in patients with multiple sclerosis. PLoS One 2011; 6: e19262. 48. Sievers C, Meira M, Hoffmann F, et al. Altered microRNA expression in B lymphocytes in multiple sclerosis: towards a better understanding of treatment effects. Clin Immunol 2012; 144: 70–79. 49. Ventura A, Young AG, Winslow MM, et al. Targeted deletion reveals essential and overlapping functions of the miR-17 through 92 family of miRNA clusters. Cell 2008; 132: 875–886. 50. Hecker M, Thamilarasan M, Koczan D, et al. MicroRNA expression changes during interferonbeta treatment in the peripheral blood of multiple sclerosis patients. Int J Mol Sci 2013; 14: 16087–16110. 51. Kroh EM, Parkin RK, Mitchell PS, et al. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods 2010; 50: 298–301.
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research-article2015
MSJ0010.1177/1352458515578771Multiple Sclerosis JournalR Gandhi
MULTIPLE SCLEROSIS MSJ JOURNAL
Topical Review
miRNA in multiple sclerosis: search for novel biomarkers
Multiple Sclerosis Journal 1–9 DOI: 10.1177/ 1352458515578771 © The Author(s), 2015. Reprints and permissions: http://www.sagepub.co.uk/ journalsPermissions.nav
Roopali Gandhi
Abstract: A major challenge in multiple sclerosis (MS) is to develop biomarkers that could help in understanding individual MS patients, i.e. whether they are a responder or non-responder to therapy, which medicine is more effective, and the degree to which they may be entering the progressive phase of disease. In the last few years, a lot of attention has been drawn toward identification of diagnostic, prognostic, process-specific, and treatment-related biomarkers for MS. In this review, we will focus on the micro RNAs (miRNAs) as potential candidates for MS biomarkers. Keywords: miRNAs, biomarkers, multiple sclerosis Date received: 17 December 2014; revised: 19 February 2015; accepted: 1 March 2015
miRNA as potential biomarkers miRNAs are a class of endogenous small, on average 22 nt long, non-coding RNAs that regulate gene expression at the post-transcriptional level by binding to complementary sequences in the 3′ or 5′ UTR (untranslated region) of the target mRNA.1–3 This usually results in translational repression or mRNA degradation leading to a decrease in encoded protein.4 In mammals, miRNAs are transcribed by RNA polymerase II as a monocistronic or polycistronic long primary transcript named primary miRNA (primiRNA). Pri-miRNAs are hairpin structures that have imperfect base-paired stems and range from about 200 nt to several kilobases in length. In the nucleus, the pri-miRNAs are cleaved by RNA polymerase III type endonucleases (Drosha), into premiRNAs. These pre-miRNAs are then transported to the cytoplasm by exportin-5 where they are cleaved by RNA polymerase III (Dicer) to produce a duplex of 20–22 nt. The duplex is unwound by helicase and the guide strand is loaded into the RNA-induced silencing complex (RISC) while the passenger strand is released. It has been thought that the passenger strand is degraded following release, though recent results from sequencing studies have provided evidence that the passenger strand itself may also target gene expression (Figure 1).5,6 The current update of miRbase (http://www.mirbase. org), the central repository of all miRNAs, reports 1900 identified mature human miRNAs.7 The
miRNAs nomenclature is very interesting. The letters preceding the miR such as hsa (Homo sapiens) or mmu (murine) represent the species of origin. The “miR” represents the mature and the “mir” represents the immature forms of miRNAs. The number after the “miR” denotes the order in which the miR was identified. For instance, hsa-miR-30e was discovered before the hsa-miR-125b. The letters after the number, such as a and b, represent similar miRNA sequences that are encoded by separate regions, e.g. hsa-miR30a, miR30b, and miR30c. These miRNAs with similar sequences could target the same genes due to the presence of a common binding sequence (seed sequence). Two mature miRNAs could originate from the same hairpin precursor and are named as miR-30a-5p and miR-30a-3p to indicate the strand of origin.
Correspondence to: Roopali Gandhi Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. [email protected]. edu
miRNAs play a critical role in multiple phenomena including development, organogenesis, and homeostasis.8 Dysregulated expression of miRNAs is associated with the onset of diseases such as immune disease, neurological disease, cardiovascular disease and cancer.9 Besides their existence within cells, miRNAs have been detected in several body fluids, including plasma, serum, cerebrospinal fluid (CSF), breast milk, urine, tears, semen, and saliva.10 Interestingly, researchers have observed significant differences in serum miRNA levels during disease and certain physiological states such as pregnancy.11
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Multiple Sclerosis Journal
Figure 1. Model showing miRNA biogenesis and function.
It is not clear whether circulating miRNAs are a byproduct of cellular degradation or if they are actively secreted into body fluids to regulate intercellular gene expression.12 miRNAs are highly stable in the blood, being resistant to circulating ribonucleases and severe conditions such as extended storage, freeze-thaw, and extreme pH due to their packaging in lipid vesicles such as exosomes, binding to RNA-binding protein, and association with high-density lipoprotein.13,14 Their stability, along with the development of sensitive methods of detection and quantification such as miRNA microarray, TaqMan low-density array (TLDA), beadbased assay, NanoString technique, and deep sequencing,15 makes them ideal candidates for a novel class of non-invasive, sensitive biomarkers. The quantitative polymerase chain reaction (qPCR) platform is a reliable and powerful method to measure low levels of circulating miRNAs. Microarrays are also commonly used but require more RNA. In a recent paper, Mestdagh et al. systematically compared 12 commercially available platforms for an identical set of 20 positive and negative control samples. These results provided metrics to objectively assess platform performance for reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The
results shown in Figure 2 (obtained from Mestdagh et al.) suggest that each platform has its weakness and strengths and that the platform should be selected based upon the study goals.16 miRNA and multiple sclerosis miRNA expression in MS lesions The use of miRNAs as biomarkers in MS is still evolving. The few studies that are published to date have used either whole blood, peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF), T cells, or multiple sclerosis lesions for miRNA expression analysis. In the first and only report of a comprehensive miRNA expression analysis in MS lesions, Junker et al. analyzed the expression level of 365 mature miRNAs by qPCR in 16 active and five inactive white matter MS brain lesions, and in nine control white matter specimens.17 The 10 most strongly upregulated miRNAs in active MS lesions were expressed by astrocytes. Among these, upregulated miRNAs, miR-34a, miR155, and miR-326 could putatively target CD47 and
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R Gandhi
Figure 2 (obtained from Mestdagh, Nature Method, 2014). Radial plot of performance metric z-score, obtained from Mestdagh et al.16 Platforms are divided into four technologies: qPCR, low-volume qPCR, hybridization and sequencing (as TM and TMp are essentially based on the same technology, only TMp is shown). Z-scores for eight metrics are shown. Ml, reproducibility; M2, titration response; M3, accuracy; M4, accuracy low-input RNA; M5, sensitivity; M6, sensitivity lowinput RNA; M7, specificity MS2 RNA; M8, assay cross-reactivity. Metrics were transformed in such way that a higher metric value (z-score) corresponds to a better performance (online methods). Each radial plot has an identical scale, which makes plots directly comparable. EX-miRCury (Exiqon), QU-qScript (Quanta BioSciences), QI-miScript (Qiagen), TMp-Taqman Cards preAmp (Life Technologies), WA-Smartchip (WaferGen), OA-Open Array (Life Technologies), AG-Microarray (Agilent), NS-nCounter (Nanostring), AF-Microarray (Affymetrix), IL-TruSeq (Illumina), IT-Ion Torrent (Life Technologies).
play a role in MS pathology by releasing macrophages from inhibitory control.17 miR-155 is involved in Th17 cell development and has been linked to MS.17,18 miR326 is also increased in PBMCs and CD4+ T cells isolated from relapsing MS patients and may play a role in the disease by increasing pathogenic Th17 cell development via targeting of the transcription factor ets-1.19
miRNA expression in blood Otaegui et al. isolated PBMCs from a group of MS patients (4 in relapse, 9 in remission, and 8 healthy controls (HCs)) and analyzed the expression patterns of
364 miRNAs using real time (RT)-qPCR.20 Results from this study showed that the expression of miR-18b, miR-493, and miR-599 was increased in relapsing patients compared to the control group. Validation of these results in a separate group (MS 3 remission, 4 relapse, and 7 HC) revealed that miR-18b and miR-599 may be relevant at the time of relapse. miR-96 was linked to remission and has putative gene targets in interleukin and wnt signaling.20. In another study using paxgene tubes, miRNA screening was performed by microarray to analyze the miRNA expression patterns from relapsing–remitting
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Multiple Sclerosis Journal MS (RRMS; n = 20) and HCs (n = 19). Significantly, dysregulated miR-145 could differentiate MS patients and HCs with an accuracy, specificity, and sensitivity of 89.7%, 89.5%, and 90.0%, respectively. However, some of the MS patients in this study were treated with either glatiramer acetate or interferon-β.21 Other studies, discussed later, have also found that miR-145 is significantly associated with MS patients.22,23 In a another study,24 the same group also used next generation sequencing (NGS), microarray analysis, and RT-qPCR in whole blood samples from treatmentnaïve patients with clinically isolated syndrome (CIS; n = 25), RRMS (n = 25), and 50 HCs to study miRNA expression patterns. Two miRNAs were found to be significantly downregulated (miR-20a-5p, miR-71-3p) and one miRNA was upregulated (miR-162-3p) by using both RNA Seq and microarray methods.24 In another study,25 the expression profile of 1145 miRNAs in PBMCs of 19 MS patients including RRMS (n = 7), secondary progressive MS (SPMS; n = 6), primary progressive MS (PPMS; n = 6), and 14 controls was analyzed using Illumina BeadArray. Some of the patients involved in this study had been treated with immunosuppressive drugs, interferon-β, or both. This study found a dysregulated expression of a total of 104 miRNAs in MS patients compared to the controls. However, during validation in a separate group of individuals using qPCR, only 2 miRNAs, let-7g and miR-150, were found to be different.25 Altered expression of let-7g was also found in another study with 18 PPMS, 17 SPMS, and 24 RRMS patients using miRNA microarrays.26 In addition, this same study confirmed a significantly decreased expression of miR-20a and miR-17 using qPCR. These miRNAs are involved in T cell activation and the target genes for these miRNAs were upregulated in MS whole blood RNA.26 The observed downregulation of miR-20a in this study has also been reported in other MS studies,21,24 as discussed above. In a more recent study, Sondergaard et al. analyzed miRNA expression profiles of PBMCs isolated from 20 treatment-naïve RRMS patients and 21 HCs using miRNA microarrays and identified 46 differentially expressed miRNAs in MS patients,22 of which 17 miRNAs were upregulated and 29 miRNAs downregulated. Selected miRNAs were analyzed again in a validation group using qPCR in 12 treatment-naïve RRMS patients and 20 HCs. However, in the validation cohort, only 2 miRNAs, let-7d and miR-744, showed significant upregulation in MS patients compared to the controls. In another study, Waschbisch et al. obtained PBMCs from patients with RRMS and analyzed the relative
expression of five selected miRNAs (miR-20b, miR142-3p, miR-146a, miR-155, and miR-326) by qPCR.27 These miRNAs were selected based upon their previous reported function in Th17 cell differentiation (miR-326 and miR-155, discussed in previous section), regulation of immune tolerance (miR-142-3p and miR-146a), or innate immunity (miR-146a). They compared the miRNA expression levels between treatment-naive patients (n = 36) and healthy controls (n = 32). They observed the expression of miR142-3p, miR-146a, miR-155, and miR-326 was remarkably increased in untreated RRMS patients compared to HCs. Further, they showed that the combination of miR-142-3p, miR-146a, and miR-155 yielded the best results in predicting disease with a sensitivity of 77.8% and a specificity of 88.0% (AUC 0.77).27 miRNA expression in circulating T cells of MS patients MS is an inflammatory disease associated with IFN-γproducing Th1 and IL-17- producing Th17 cells.28–30 miRNAs play a role in both T cell development in the thymus and their differentiation in periphery. De Santis et al. profiled regulatory CD4+CD25high T cells from 12 untreated RRMS patients and 14 HCs using an miRNA microarray and found differential expression of 23 miRNAs in regulatory CD4+CD25high T cells from MS patients compared to HCs.31 These results were validated using real time-PCR and CD4+CD25highCD127low cells, these results confirmed the upregulation of miR106b, miR-19a, miR-19b, and miR-25 in CD4+CD25high of MS subjects compared to healthy subjects. miR106b and miR-25 modulate the TGF-β signaling pathway and dysregulated expression of these miRNAs may alter regulatory T cell biology in MS.31 In another study, Lindberg et al. used CD4+, CD8+ T cells, and B cells from 8 RRMS and 10 HCs to analyze the miRNA expression profile by TaqMan array and found that the miR-17-5p was upregulated in CD4+ T cells isolated from MS patients.32 The miR-17-5p belongs to the miR-17-92 cluster and plays an important role in the development of autoimmunity and lymphoproliferative diseases in mice.32,33 Another study by Guerau-deArellano et al. suggested increased expression of miR128 and miR-27b in naïve T cells and miR-340 in memory T cells isolated from MS patients.34 All of these miRNAs are involved in suppressing Th2 differentiation and enhancing Th1 mediated autoimmune responses.34 Another similar study showed altered expression of miR-29b in MS T cells and its involvement in controlling expression of IFN-γ and Th1 transcription factor, T-bet.35 A more recent study on miRNA analysis in T cells by miRNA microarray by Jernas et
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R Gandhi al. used 11 RRMS patients (treated with interferon β) and 9 HCs,36 identifying 21 miRNAs that were decreased in MS patients. Of these 21 differentially expressed miRNAs, 20 miRNAs have immune system related target genes. They confirmed the expression of two selected miRNAs (miR-494 and miR-197) by using quantitative PCR.36 miRNA expression in serum or plasma of MS patients The stable expression of miRNAs in serum and plasma makes them an important candidate for a biomarker study. However, in the case of MS, there are only two reported studies that have analyzed circulating miRNA. In the first study on circulating miRNA in MS, Siegel et al. conducted a miRNA microarray analysis of over 900 known miRNA transcripts from plasma samples collected from four MS patients and four HCs.37 They identified six plasma miRNAs (miR-614, miR-572, miR-648, miR-1826, miR-422a and miR-22) that were significantly upregulated and one plasma miRNA (miR-1979) that was significantly downregulated in MS patients.37 In a more recent study by our group, we analyzed a total of 368 miRNAs in plasma samples of 10 RRMS, 9 SPMS, and 9 HCs using miRNA RT-qPCR.38 We found that twenty-nine miRNAs distinguished RRMS from HCs, 35 miRNAs distinguished SPMS from HCs, and 16 miRNAs distinguished RRMS from SPMS. The 20 selected miRNAs were further validated on a larger cohort of 100 MS patients, 15 amyotrophic lateral sclerosis (ALS) and 32 controls using RT-qPCR. Among the validated miRNAs, we identified miR-92a-1* in the largest number of comparisons. It was different in RRMS versus SPMS, and RRMS versus HCs, and showed an association with EDSS and disease duration. The miRNA miR-92 has target genes involved in cell cycle regulation and cell signaling.38 let-7a differentiated SPMS from HCs and RRMS from SPMS. The let-7 family of miRNAs is known to regulate stem cell differentiation and T cell activation, activate Toll-like receptor 7, and are linked to neurodegeneration.39–43 The miR-454 differentiated RRMS from SPMS, and miR-145 differentiated RRMS from HCs and RRMS from SPMS. miR-145 findings were in consensus with previous studies in MS.21,22 Interestingly, the same circulating miRNAs (let-7 and miR-92) that were differentially expressed in RRMS versus SPMS also differentiated ALS from RRMS subjects, but were not different between SPMS and ALS, suggesting that similar processes may occur in SPMS and ALS.23 Sondergaard et al. study discussed miRNA expression in blood, also measured
miRNA expression in plasma samples from 22 MS patients and 22 HCs. They found that the expression of miR145 was most significantly different in MS compared with controls (22). miRNA expression in CSF of MS patient In the only published study involving miRNA analysis in CSF of MS patients, Haghikia et al. tested global miRNA profiles to screen for reported miRNAs,44 followed by single selected RT-qPCR to validate candidate miRNAs. They used the CSF of 53 patients with MS and 39 patients with other neurologic diseases (OND) for global miRNA profiling. This study showed that miR-922, miR-181c, and miR-633 are differentially regulated in patients with MS as compared with OND. Importantly, miR-181c and miR633 differentiated RRMS from SPMS with 82% specificity and 69% sensitivity.44 miRNAs as treatment response biomarkers in MS Several studies have evaluated the effect of MS therapies on the regulation of mRNAs;45–47 however, studies involving the effect of MS treatments on the regulation of miRNAs are lacking. Such studies are not only important in identifying a marker to analyze treatment response, but also to understand the molecular mechanism of treatment. To date, there are only three published reports on the expression of miRNAs upon treatment in MS patients. In the first published study, Waschbisch et al. obtained PBMCs from patients with RRMS, and analyzed the relative expression of five selected miRNAs (miR-20b, miR-142-3p, miR-146a, miR-155, and miR-326) by qPCR (also discussed in miRNA expression in blood section).27 They compared the miRNA levels between treatmentnaive patients (n = 36), IFN-β-treated patients (n = 18: IFN-β1a i.m. n = 5, IFN-β1a s.c. n = 8, IFN-β1b s.c. n = 5), and patients treated with glatiramer acetate (n = 20). They excluded patients that were treated with glucocorticoids during the last four weeks before study entry. They observed the expression of the selected five miRNAs did not differ between treatment-naïve and IFN-β treated RRMS patients, the expression of miR-142-3p and miR-146a was significantly decreased in glatiramer acetate treated RRMS patients compared to the treatment naive MS patients.27 In another treatment response study, Sievers et al. tested 1059 miRNAs in B cells isolated from 10 untreated MS patients, 10 natalizumab treated MS patients, and 10 HCs using microarrays.48 These results showed that 10 miRNAs were differentially
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Multiple Sclerosis Journal expressed in B cells from natalizumab-treated patients compared to untreated patients. Expression of the miR-106b-25 and miR-17-92 clusters was dysregulated both in untreated and natalizumab-treated patients suggesting a role for these miRNAs in MS pathogenesis. Functional cooperation among these two miRNA clusters, characterized by a reduction in pre-B cells and increased apoptosis, was suggested previously in mice.48,49 In a recent study, Hecker et al. used microarrays to investigate the expression of miRNAs and mRNAs in PBMCs of patients with CIS or RRMS in response to IFN-β therapy.50 The blood samples were obtained longitudinally from six patients at four time points in the early phase of therapy, namely before the first (baseline), after second, and third IFN-β injection, as well as after one month of treatment. Upon comparing the expression levels at the three time points during therapy to the expression levels at baseline, 20 different miRNAs were filtered at various time points using MAID filtering method. This filtered method was previously discussed by Hecker et al. BMC Bioinformatics, 2009 and utilizes a t-statistic in conjunction with an MA-plot-based signal intensity-dependent fold-change criterion (referred to as MAID filtering) to select mRNA or miRNA with expression changes upon therapy. Of these 20 selected miRNAs, seven miRNAs appeared as upregulated and 13 miRNAs appeared as downregulated in response to the therapy. Two of the 20 miRNAs, miR-149-5p and miR-708-5p, were filtered at two different time points. For the remaining miRNAs, the expression changes were not very stable over the course of therapy. Most of the miRNAs (n = 14) were filtered as upregulated or downregulated one month after IFN-β treatment initiation, which corresponded with gene expression profiling. They used Affymetrix miRNA microarrays to replicate the miRNA measurements of the PBMC samples from three patients before the start of IFN-β therapy as well as after one month. These microarrays had a lower measurement range than the TaqMan miRNA arrays and 13 of the 20 filtered miRNAs showed the same trend of upregulation (let-7a-5p, let-7b-5p, miR-16-5p, miR-342-5p, miR-346, miR-518b) or downregulation (miR-29a-3p, miR-29b-1-5p, miR-29c-3p, miR-95, miR-149-5p, miR-181c-3p, miR-708-5p) with a significance threshold alpha = 0.10. Four miRNAs (miR29a-3p, miR-29c-3p, miR-193a-3p, and miR-532-5p) were confirmed to be downregulated during treatment. For further validation, they selected five of the 20 filtered miRNAs to quantify their expression in PBMCs of an independent cohort of 12 patients (8 RRMS/4 CIS) using TaqMan single-tube assays. The PBMCs were obtained in a longitudinal manner before the first
drug injection and after one month of treatment. During this step of validation, miR-29a-3p and miR-29c-3p could be confirmed as differentially expressed in response to IFN-β therapy. Expression of both miR29c-3P and miR-532-5P was significantly decreased compared to the pre-treatment sample. Although, miR16-5p and miR-149-5p showed the same trend of expression change as in the other data sets, but this was not statistically significant.50 Conclusion There is considerable excitement regarding the use of miRNAs in the biomarker field, which is well founded due to their stability and relative ease of detection. In this paper, we have reviewed the miRNA based studies carried out in MS patients in order to evaluate their potential as biomarkers. We observed a wide variety of results obtained by different groups (summarized in Table 1), which may reflect limitations associated with some studies, potentially due to the lack of a reliable assay platform, a low number of patients and the lack of strong validation using an alternative platform or set of patients. In general, we find that there is a paucity of comprehensive studies to evaluate miRNAs as biomarkers in MS. In order to develop a miRNA-based biomarker for MS or any disease, a most important prerequisite is the ability to quantify miRNAs from a variety of samples with sufficient sensitivity, accuracy and reproducibility. A number of variables such as specimen collection, RNA extraction, RT-qPCR, data analysis and normalization are some of the major challenges associated with miRNA-based studies. There is also considerable inter-sample variability in both the protein and lipid content of each individual’s serum and plasma, which can affect the efficiency of RNA extraction and introduce potential inhibitors to RT-qPCR. Another major issue associated with miRNA based study is normalization, amplification and contamination. Due to the low concentration of miRNAs in body fluids, their quantitation is not only difficult, but also requires occasional amplification, which in turn creates an additional variable. Most importantly, there is no consensus on suitable small RNA reference genes that could be used as internal controls for biological variability. A common practice is to process an identical input volume of samples, which is later corrected for technical variability using spiked-in synthetic nonhuman miRNA as a normalizing control.14,51 In addition, the quantification of miRNAs in serum/plasma can be altered by contamination by miRNAs leaked from cellular components of blood, either through hemolysis during sampling, processing, or by carryover of whole cells in the serum/plasma.
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PBMC, CD4+ T cells PBMC Whole blood
Whole blood PBMC Whole blood PBMC, Plasma CD4+ CD25+ T cells CD4+ T cells Naïve CD4+ T cells CD4+CD45RO+ T cells T cells
Plasma Plasma CSF PBMC B cells PBMC
RRMS
RRMS RRMS
CIS, RRMS
RRMS, SPMS, PPMS
RRMS, SPMS, PPMS RRMS
RRMS
RRMS
RRMS, SPMS, PPMS
RRMS, SPMS, PPMS
RRMS
Unspecified
RRMS, SPMS, PPMS RRMS, SPMS, PPMS
RRMS
RRMS CIS, RRMS
Otaegui et al.20 Keller et al.21
Keller et al.24
MartinelliBoneschi et al.25 Cox et al.26 Sondergaard et al.22
De Santis et al.31
Lindberg et al.32
Guerau-deArellano et al.34 Smith et al.35
Jernas et al.36
Siegel et al.37
Gandhi et al.23 Haghikia et al.44
Waschbisch et al.27
Sievers et al.48 Hecker et al.50
Tissue
Du et al.19
MS type MS brain lesions
al.17
SPMS, RRMS, PPMS
Junker et
Author
Table 1. miRNA-based biomarker studies in multiple sclerosis.
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Microarray TLDA
TLDA PCR array, RTqPCR Real-time PCR
Microarray
NanoString nCounter Microarray, Realtime PCR
TLDA
TLDA
Microarray LNA Microarray, Real-time PCR Microarray
NGS, Microarray, Real-time PCR BeadArray
TLDA Microarray
Real-time PCR
TLDA
Method
Treatment naïve, IFN-β, glatiramer acetate Natalizumab IFNβ
Untreated Unspecified
Unspecified
IFN-β
Treatment naïve
Treatment naïve
Treatment naïve and steroid free for 6 months No treatment for 6 months
Immunosuppressive, IFNβ, or both No treatment for 3 months Treatment naïve
Treatment naïve
Unspecified Glatiramer acetate, IFN-β, or none
Unspecified
Unspecified
Treatment
miR-19b, miR-551a, miR-106b, and miR-191 miR-29a-3p, miR-29c-3p, and miR-532-5p
miR-142-3p, miR-146a, miR-155, and miR-326
miR-494, miR-15b, miR-30c, miR-23a, miR-197, miR-1260b, miR-125a-5p, miR-361-5p, miR-320d, miR-423-3p, miR-1280, miR-663, miR-423-5p, miR99b, miR-339-5p, let-7a, miR-1979, miR-3178, miR625, miR-150, and miR-3153 miR-614, miR-572, miR-648, miR-1826, miR-422a, miR-22, and miR-1979 miR-30e, miR-92a-1*, Let-7a, miR-454, and miR-145 miR-922, miR-181c, and miR-633
miR-29b
miR-485-3p, miR-376a, miR-497, miR-193a, miR126, miR-17-5p, and miR-34a miR-128, miR-27b, and miR-340
miR-106b, miR-93, miR-19a, miR-19b, and miR-25
miR-17 and miR-20a let-7d, miR-744, and miR-145
miR-18b, miR-493, miR-96, and miR-599 miR-145, miR-186, miR-664, miR-20b, miR-422a, miR-142-3p, miR-584, miR-223, miR-1275, and miR491-5p miR-146b-5p, miR-7-1-3p, miR-20a-5p, miR-3653, miR-20b, miR-16-2-3p, miR-574-5p, and miR-1202 let-7g, miR-150
miR-650, miR-155, miR-326, miR-142-3p, miR-146a, miR-34a, miR-21, miR-23a, miR-199a, and miR-27a miR-326
Key miRNAs
R Gandhi
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Multiple Sclerosis Journal However, the studies published to date point towards miRNAs having a role in the future of MS biomarkers and to design proof of concept studies. It will require considerable effort from researchers in different fields to develop consensus protocols. The National Institutes of Health (NIH) is supporting these efforts by granting funds specifically to address these challenges in the field of miRNA as a disease biomarker. We believe it will not be long before the current challenges are overcome and a miRNA-based biomarker is established for MS. Conflict of interest The author declares that there is no conflict of interest. Funding This research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.
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