Short non-coding RNA biology and neurodegenerative disorders: novel disease targets and therapeutics

Oxidative Stress and Its Modulation by Ladostigil Alter the Expression of Abundant Long Non-Coding RNAs in SH-SY5Y Cells

Neurodegenerative disorders, brain injury, and the decline in cognitive function with aging are accompanied by a reduced capacity of cells in the brain to cope with oxidative stress and inflammation. In this study, we focused on the response to oxidative stress in SH-SY5Y, a human neuroblastoma cell line. We monitored the viability of the cells in the presence of oxidative stress. Such stress was induced by hydrogen peroxide or by Sin1 (3-morpholinosydnonimine) that generates reactive oxygen and nitrogen species (ROS and RNS). Both stressors caused significant cell death. Our results from the RNA-seq experiments show that SH-SY5Y cells treated with Sin1 for 24 h resulted in 94 differently expressed long non-coding RNAs (lncRNAs), including many abundant ones. Among the abundant lncRNAs that were upregulated by exposing the cells to Sin1 were those implicated in redox homeostasis, energy metabolism, and neurodegenerative diseases (e.g., MALAT1, MIAT, GABPB1-AS1, NEAT1, MIAT, GABPB1-AS1, and HAND2-AS1). Another group of abundant lncRNAs that were significantly altered under oxidative stress included cancer-related SNHG family members. We tested the impact of ladostigil, a bifunctional reagent with antioxidant and anti-inflammatory properties, on the lncRNA expression levels. Ladostigil was previously shown to enhance learning and memory in the brains of elderly rats. In SH-SY5Y cells, several lncRNAs involved in transcription regulation and the chromatin structure were significantly induced by ladostigil. We anticipate that these poorly studied lncRNAs may act as enhancers (eRNA), regulating transcription and splicing, and in competition for miRNA binding (ceRNA). We found that the induction of abundant lncRNAs, such as MALAT1, NEAT-1, MIAT, and SHNG12, by the Sin1 oxidative stress paradigm specifies only the undifferentiated cell state. We conclude that a global alteration in the lncRNA profiles upon stress in SH-SY5Y may shift cell homeostasis and is an attractive in vitro system to characterize drugs that impact the redox state of the cells and their viability.

Deep-belief network for predicting potential miRNA-disease associations

MicroRNA (miRNA) plays an important role in the occurrence, development, diagnosis and treatment of diseases. More and more researchers begin to pay attention to the relationship between miRNA and disease. Compared with traditional biological experiments, computational method of integrating heterogeneous biological data to predict potential associations can effectively save time and cost. Considering the limitations of the previous computational models, we developed the model of deep-belief network for miRNA-disease association prediction (DBNMDA). We constructed feature vectors to pre-train restricted Boltzmann machines for all miRNA-disease pairs and applied positive samples and the same number of selected negative samples to fine-tune DBN to obtain the final predicted scores. Compared with the previous supervised models that only use pairs with known label for training, DBNMDA innovatively utilizes the information of all miRNA-disease pairs during the pre-training process. This step could reduce the impact of too few known associations on prediction accuracy to some extent. DBNMDA achieves the AUC of 0.9104 based on global leave-one-out cross validation (LOOCV), the AUC of 0.8232 based on local LOOCV and the average AUC of 0.9048 ± 0.0026 based on 5-fold cross validation. These AUCs are better than other previous models. In addition, three different types of case studies for three diseases were implemented to demonstrate the accuracy of DBNMDA. As a result, 84% (breast neoplasms), 100% (lung neoplasms) and 88% (esophageal neoplasms) of the top 50 predicted miRNAs were verified by recent literature. Therefore, we could conclude that DBNMDA is an effective method to predict potential miRNA-disease associations.

MicroRNAs and complex diseases: from experimental results to computational models

Plenty of microRNAs (miRNAs) were discovered at a rapid pace in plants, green algae, viruses and animals. As one of the most important components in the cell, miRNAs play a growing important role in various essential and important biological processes. For the recent few decades, amounts of experimental methods and computational models have been designed and implemented to identify novel miRNA-disease associations. In this review, the functions of miRNAs, miRNA-target interactions, miRNA-disease associations and some important publicly available miRNA-related databases were discussed in detail. Specially, considering the important fact that an increasing number of miRNA-disease associations have been experimentally confirmed, we selected five important miRNA-related human diseases and five crucial disease-related miRNAs and provided corresponding introductions. Identifying disease-related miRNAs has become an important goal of biomedical research, which will accelerate the understanding of disease pathogenesis at the molecular level and molecular tools design for disease diagnosis, treatment and prevention. Computational models have become an important means for novel miRNA-disease association identification, which could select the most promising miRNA-disease pairs for experimental validation and significantly reduce the time and cost of the biological experiments. Here, we reviewed 20 state-of-the-art computational models of predicting miRNA-disease associations from different perspectives. Finally, we summarized four important factors for the difficulties of predicting potential disease-related miRNAs, the framework of constructing powerful computational models to predict potential miRNA-disease associations including five feasible and important research schemas, and future directions for further development of computational models.

Decoding the Role of Platelets and Related MicroRNAs in Aging and Neurodegenerative Disorders

Platelets are anucleate cells that circulate in blood and are essential components of the hemostatic system. During aging, platelet numbers decrease and their aggregation capacity is reduced. Platelet dysfunctions associated with aging can be linked to molecular alterations affecting several cellular systems that include cytoskeleton rearrangements, signal transduction, vesicular trafficking, and protein degradation. Age platelets may adopt a phenotype characterized by robust secretion of extracellular vesicles that could in turn account for about 70-90% of blood circulating vesicles. Interestingly these extracellular vesicles are loaded with messenger RNAs and microRNAs that may have a profound impact on protein physiology at the systems level. Age platelet dysfunction is also associated with accumulation of reactive oxygen species. Thereby understanding the mechanisms of aging in platelets as well as their age-dependent dysfunctions may be of interest when evaluating the contribution of aging to the onset of age-dependent pathologies, such as those affecting the nervous system. In this review we summarize the findings that link platelet dysfunctions to neurodegenerative diseases including Alzheimer's Disease, Parkinson's Disease, Multiple Sclerosis, Huntington's Disease, and Amyotrophic Lateral Sclerosis. We discuss the role of platelets as drivers of protein dysfunctions observed in these pathologies, their association with aging and the potential clinical significance of platelets, and related miRNAs, as peripheral biomarkers for diagnosis and prognosis of neurodegenerative diseases.

Inferring microRNA-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network

More and more research works have indicated that microRNAs (miRNAs) play indispensable roles in exploring the pathogenesis of diseases. Detecting miRNA-disease associations by experimental techniques in biology is expensive and time-consuming. Hence, it is important to propose reliable and accurate computational methods to exploring potential miRNAs related diseases. In our work, we develop a novel method (BRWHNHA) to uncover potential miRNAs associated with diseases based on hybrid recommendation algorithm and unbalanced bi-random walk. We first integrate the Gaussian interaction profile kernel similarity into the miRNA functional similarity network and the disease semantic similarity network. Then we calculate the transition probability matrix of bipartite network by using hybrid recommendation algorithm. Finally, we adopt unbalanced bi-random walk on the heterogeneous network to infer undiscovered miRNA-disease relationships. We tested BRWHNHA on 22 diseases based on five-fold cross-validation and achieves reliable performance with average AUC of 0.857, which an area under the ROC curve ranging from 0.807 to 0.924. As a result, BRWHNHA significantly improves the performance of inferring potential miRNA-disease association compared with previous methods. Moreover, the case studies on lung neoplasms and prostate neoplasms also illustrate that BRWHNHA is superior to previous prediction methods and is more advantageous in exploring potential miRNAs related diseases. All source codes can be downloaded from https://github.com/myl446/BRWHNHA.

Circular RNA profiling reveals that circular RNAs from ANXA2 can be used as new biomarkers for multiple sclerosis

Multiple sclerosis is an autoimmune disease, with higher prevalence in women, in whom the immune system is dysregulated. This dysregulation has been shown to correlate with changes in transcriptome expression as well as in gene-expression regulators, such as non-coding RNAs (e.g. microRNAs). Indeed, some of these have been suggested as biomarkers for multiple sclerosis even though few biomarkers have reached the clinical practice. Recently, a novel family of non-coding RNAs, circular RNAs, has emerged as a new player in the complex network of gene-expression regulation. MicroRNA regulation function through a 'sponge system' and a RNA splicing regulation function have been proposed for the circular RNAs. This regulating role together with their high stability in biofluids makes them seemingly good candidates as biomarkers. Given the dysregulation of both protein-coding and non-coding transcriptome that have been reported in multiple sclerosis patients, we hypothesised that circular RNA expression may also be altered. Therefore, we carried out expression profiling of 13.617 circular RNAs in peripheral blood leucocytes from multiple sclerosis patients and healthy controls finding 406 differentially expressed (P-value < 0.05, Fold change > 1.5) and demonstrate after validation that, circ_0005402 and circ_0035560 are underexpressed in multiple sclerosis patients and could be used as biomarkers of the disease.

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction

Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases’ statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L₁-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the model’s superior prediction accuracy; and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction.

Discovering miRNA-disease associations promotes the understanding towards the molecular mechanisms of various human diseases at the miRNA level, and contributes to the development of diagnostic biomarkers and treatment tools for diseases. Computational models can make the discovery more efficient and experiments more productive. LRSSLMDA was proposed to computationally infer potential miRNA-disease associations via adopting sparse subspace learning with Laplacian regularization on the known miRNA-disease association network and the informative feature profiles extracted from the integrated miRNA/disease similarity networks. Experimental results in global and local leave-one-out cross validation and 5-fold cross validation showed a superior prediction performance of LRSSLMDA over previous models. Moreover, three types of case studies on five important human diseases were carried out to further demonstrate the model’s predictive power: respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predicted miRNAs were confirmed by experimental literatures. So, we believe that LRSSLMDA could make reliable predictions and might guide future experimental studies on miRNA-disease associations.

Inferring microRNA-disease associations by random walk on a heterogeneous network with multiple data sources

Since the discovery of the regulatory function of microRNA (miRNA), increased attention has focused on identifying the relationship between miRNA and disease. It has been suggested that computational method are an efficient way to identify potential disease-related miRNAs for further confirmation using biological experiments. In this paper, we first highlighted three limitations commonly associated with previous computational methods. To resolve these limitations, we established disease similarity subnetwork and miRNA similarity subnetwork by integrating multiple data sources, where the disease similarity is composed of disease semantic similarity and disease functional similarity, and the miRNA similarity is calculated using the miRNA-target gene and miRNA-lncRNA (long non-coding RNA) associations. Then, a heterogeneous network was constructed by connecting the disease similarity subnetwork and the miRNA similarity subnetwork using the known miRNA-disease associations. We extended random walk with restart to predict miRNA-disease associations in the heterogeneous network. The leave-one-out cross-validation achieved an average area under the curve (AUC) of 0:8049 across 341 diseases and 476 miRNAs. For five-fold cross-validation, our method achieved an AUC from 0:7970 to 0:9249 for 15 human diseases. Case studies further demonstrated the feasibility of our method to discover potential miRNA-disease associations. An online service for prediction is freely available at http://ifmda.aliapp.com.

Evaluation of Compound Optical Interference in High-Content Screening

Compound optical interference remains an inherent problem in chemical screening and has been well documented for biochemical assays and less so for automated microscopy-based assays. It has also been the assumption that the latter should not suffer from such interference because of the washing steps involved in the process, thus eliminating the residual nonspecific compound effects. Instead, these compounds may have no relevance to the actual target, and as such, compound optical interference contributes to a number of false-positives, resulting in a high attrition rate during subsequent follow-up studies. In this report, we analyze the outcome of a high-content screen using enhanced green fluorescent protein as a reporter in a gain-of-function cell-based assay in search of modulators of the micro RNA (miRNA) biogenesis pathway. Using a previously validated image-based biosensor, we screened a diverse library collection of ~315,000 compounds covering natural and synthetic derivatives in which 1130 positives were identified to enhance green fluorescence expression. Lateral confirmation and dose-response studies revealed that all of these compounds were the result of optical interference and not specific inhibition of miRNA biogenesis. Here, we highlight the chemical classes that are susceptible to compound optical interference and discuss their implications in automated microscopy-based assays.

The involvement of Eag1 potassium channels and miR-34a in rotenone-induced death of dopaminergic SH-SY5Y cells

The loss of dopaminergic neurons and the resultant motor impairment are hallmarks of Parkinson's disease. The SH‑SY5Y cell line is a model of dopaminergic neurons, and allows for the study of dopaminergic neuronal injury. Previous studies have revealed changes in Ether à go‑go 1 (Eag1) potassium channel expression during p53-induced SH‑SY5Y apoptosis, and the regulatory involvement of microRNA‑34a (miR‑34a) was demonstrated. In the present study, the involvement of Eag1 and miR‑34a in rotenone‑induced SH‑SY5Y cell injury was investigated. Rotenone is a neurotoxin, which is often used to generate models of Parkinson's disease, since it causes the death of nigrostriatal neurons by inducing intracellular aggregation of alpha synuclein and ubiquitin. In the present study, rotenone resulted in a dose‑dependent decrease in cell viability, as revealed by 3‑(4,5‑dimethylthiazol‑2‑yl)‑2,5‑diphenyltetrazolium bromide (MTT) and trypan blue cell counting assays. In addition, Eag1 was demonstrated to be constitutively expressed by SH‑SY5Y cells, and involved in cell viability. Suppression of Eag1 with astemizole resulted in a dose‑dependent decrease in cell viability, as revealed by MTT assay. Astemizole also enhanced the severity of rotenone‑induced injury in SH‑SY5Y cells. RNA interference against Eag1, using synthetic small interfering RNAs (siRNAs), corroborated this finding, as siRNAs potentiated rotenone‑induced injury. Eag1‑targeted siRNAs (kv10.1‑3 or EAG1hum_287) resulted in a statistically significant 16.4‑23.5% increase in vulnerability to rotenone. An increased number of apoptotic nuclei were observed in cells transfected with EAG1hum_287. Notably, this siRNA intensified rotenone‑induced apoptosis, as revealed by an increase in caspase 3/7 activity. Conversely, a miR‑34a inhibitor was demonstrated to exert neuroprotective effects. The viability of cells exposed to rotenone for 24 or 48 h and treated with miR‑34a inhibitor was restored by 8.4‑8.8%. In conclusion, Eag1 potassium channels and miR‑34a are involved in the response to rotenone-induced injury in SH‑SY5Y cells. The neuroprotective effect of mir‑34a inhibitors merits further investigations in animal models of Parkinson's disease.

A novel computational model based on super-disease and miRNA for potential miRNA–disease association prediction

Considering the various disadvantages of previous computational models, we proposed a novel computational model based on super-disease and miRNA for potential miRNA–disease association prediction (SDMMDA) to predict potential miRNA–disease associations by integrating known associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity for diseases and miRNAs.

Fluid-Based Biomarkers for Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a highly heterogeneous disease with no effective treatment. Drug development has been hampered by the lack of biomarkers that aid in early diagnosis, demonstrate target engagement, monitor disease progression, and can serve as surrogate endpoints to assess the efficacy of treatments. Fluid-based biomarkers may potentially address these issues. An ideal biomarker should exhibit high specificity and sensitivity for distinguishing ALS from control (appropriate disease mimics and other neurologic diseases) populations and monitor disease progression within individual patients. Significant progress has been made using cerebrospinal fluid, serum, and plasma in the search for ALS biomarkers, with urine and saliva biomarkers still in earlier stages of development. A few of these biomarker candidates have demonstrated use in patient stratification, predicting disease course (fast vs slow progression) and severity, or have been used in preclinical and clinical applications. However, while ALS biomarker discovery has seen tremendous advancements in the last decade, validating biomarkers and moving them towards the clinic remains more elusive. In this review, we highlight biomarkers that are moving towards clinical utility and the challenges that remain in order to implement biomarkers at all stages of the ALS drug development process.

Analysis of piRNA-Like Small Non-coding RNAs Present in Axons of Adult Sensory Neurons

Small non-coding RNAs (sncRNAs) have been shown to play pivotal roles in spatiotemporal-specific gene regulation that is linked to many different biological functions. PIWI-interacting RNAs (piRNAs), typically 25-34-nucleotide long, are originally identified and thought to be restricted in germline cells. However, recent studies suggest that piRNAs associate with neuronal PIWI proteins, contributing to neuronal development and function. Here, we identify a cohort of piRNA-like sncRNAs (piLRNAs) in rat sciatic nerve axoplasm and directly contrast temporal changes of piLRNA levels in the nerve following injury, as compared with those in an uninjured nerve using deep sequencing. We find that 32 of a total of 53 annotated piLRNAs show significant changes in their levels in the regenerating nerve, suggesting that individual axonal piLRNAs may play important regulatory roles in local messenger RNA (mRNA) translation during regeneration. Bioinformatics and biochemical analyses show that these piLRNAs carry characteristic features of mammalian piRNAs, including sizes, a sequence bias for uracil at the 5'-end and a 2'-O-methylation at the 3'-end. Their axonal expression is directly visualized by fluorescence in situ hybridization in cultured dorsal root ganglion neurons as well as immunoprecipitation with MIWI. Further, depletion of MIWI protein using RNAi from cultured sensory neurons increases axon growth rates, decreases axon retraction after injury, and increases axon regrowth after injury. All these data suggest more general roles for MIWI/piLRNA pathway that could confer a unique advantage for coordinately altering the population of proteins generated in growth cones and axons of neurons by targeting mRNA cohorts.

Recent developments in circulating biomarkers in Parkinson’s disease: the potential use of miRNAs in a clinical setting

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting 5% of the elderly population. PD diagnosis is still based on the identification of neuromotor symptoms although nonmotor manifestations emerge years prior to diagnosis. The discovery of biomarkers at the earliest stages of PD is of extreme interest. miRNAs have been considered potential biomarkers for neurodegenerative diseases, but only a limited number have been found to be PD related. This review focuses on the current findings in the field of circulating miRNAs in PD and the challenges surrounding clinical utility and validation. We briefly describe the more established circulating biomarkers in PD and provide a more thorough review of miRNAs differentially expressed in PD. We highlight their potential for being considered as biomarkers for diagnosis while emphasizing the challenges for adequate validation of the findings and how miRNAs can be envisioned in a clinical setting satisfying regulatory bodies.

MicroRNA screening identifies a link between NOVA1 expression and a low level of IKAP in familial dysautonomia

Familial dysautonomia (FD) is a rare neurodegenerative disease caused by a mutation in intron 20 of the IKBKAP gene (c.2204+6T>C), leading to tissue-specific skipping of exon 20 and a decrease in the synthesis of the encoded protein IKAP (also known as ELP1). Small non-coding RNAs known as microRNAs (miRNAs) are important post-transcriptional regulators of gene expression and play an essential role in the nervous system development and function. To better understand the neuronal specificity of IKAP loss, we examined expression of miRNAs in human olfactory ecto-mesenchymal stem cells (hOE-MSCs) from five control individuals and five FD patients. We profiled the expression of 373 miRNAs using microfluidics and reverse transcription coupled to quantitative PCR (RT-qPCR) on two biological replicate series of hOE-MSC cultures from healthy controls and FD patients. This led to the total identification of 26 dysregulated miRNAs in FD, validating the existence of a miRNA signature in FD. We then selected the nine most discriminant miRNAs for further analysis. The signaling pathways affected by these dysregulated miRNAs were largely within the nervous system. In addition, many targets of these dysregulated miRNAs had been previously demonstrated to be affected in FD models. Moreover, we found that four of our nine candidate miRNAs target the neuron-specific splicing factor NOVA1. We demonstrated that overexpression of miR-203a-3p leads to a decrease of NOVA1, counter-balanced by an increase of IKAP, supporting a potential interaction between NOVA1 and IKAP. Taken together, these results reinforce the choice of miRNAs as potential therapeutic targets and suggest that NOVA1 could be a regulator of FD pathophysiology.

Summary: A miRNA screening conducted in olfactory stem cells from patients links the neuron-specific splicing factor NOVA1 to neurodegeneration in familial dysautonomia.

microRNAs Databases: Developmental Methodologies, Structural and Functional Annotations

microRNA (miRNA) is an endogenous and evolutionary conserved non-coding RNA, involved in post-transcriptional process as gene repressor and mRNA cleavage through RNA-induced silencing complex (RISC) formation. In RISC, miRNA binds in complementary base pair with targeted mRNA along with Argonaut proteins complex, causes gene repression or endonucleolytic cleavage of mRNAs and results in many diseases and syndromes. After the discovery of miRNA lin-4 and let-7, subsequently large numbers of miRNAs were discovered by low-throughput and high-throughput experimental techniques along with computational process in various biological and metabolic processes. The miRNAs are important non-coding RNA for understanding the complex biological phenomena of organism because it controls the gene regulation. This paper reviews miRNA databases with structural and functional annotations developed by various researchers. These databases contain structural and functional information of animal, plant and virus miRNAs including miRNAs-associated diseases, stress resistance in plant, miRNAs take part in various biological processes, effect of miRNAs interaction on drugs and environment, effect of variance on miRNAs, miRNAs gene expression analysis, sequence of miRNAs, structure of miRNAs. This review focuses on the developmental methodology of miRNA databases such as computational tools and methods used for extraction of miRNAs annotation from different resources or through experiment. This study also discusses the efficiency of user interface design of every database along with current entry and annotations of miRNA (pathways, gene ontology, disease ontology, etc.). Here, an integrated schematic diagram of construction process for databases is also drawn along with tabular and graphical comparison of various types of entries in different databases. Aim of this paper is to present the importance of miRNAs-related resources at a single place.

SncRNA (microRNA &snoRNA) opposite expression pattern found in multiple sclerosis relapse and remission is sex dependent

Multiple sclerosis (MS) is a common inflammatory and degenerative disease that causes neurological disability. It affects young adults and its prevalence is higher in women. The most common form is manifested as a series of acute episodes of neurological disability (relapses) followed by a recovery phase (remission). Recently, non-coding RNAs have emerged as new players in transcriptome regulation, and in turn, they could have a significant role in MS pathogenesis. In this context, our aim was to investigate the involvement of microRNAs and snoRNAs in the relapse-remission dynamics of MS in peripheral blood leucocytes, to shed light on the molecular and regulatory mechanisms that underlie this complex process. With this approach, we found that a subset of small non-coding RNAs (sncRNA) is altered in relapse and remission, revealing unexpected opposite changes that are sex dependent. Furthermore, we found that a relapse-related miRNA signature regulated general metabolism processes in leucocytes, and miRNA altered in remission are involved in the regulation of innate immunity. We observed that sncRNA dysregulation is different in relapse and remission leading to differences in transcriptome regulation, and that this process is sex dependent. In conclusion, relapse and remission have a different molecular background in men and women.

miREFRWR: a novel disease-related microRNA-environmental factor interactions prediction method

miREFRWR was developed to uncover the hidden disease-related miRNA–EF interactions by implementing random walks on an miRNA similarity network and EF similarity network, respectively.

Dynamic Change and Target Prediction of Axon-Specific MicroRNAs in Regenerating Sciatic Nerve

Injury to axons in the peripheral nervous system induces rapid and local regenerative responses to form a new growth cone, and to generate a retrogradely transporting injury signal. The evidence for essential roles of intra-axonal protein synthesis during regeneration is now compelling. MicroRNA (miRNA) has recently been recognized as a prominent player in post-transcriptional regulation of axonal protein synthesis. Here, we directly contrast temporal changes of miRNA levels in the sciatic nerve following injury, as compared to those in an uninjured nerve using deep sequencing. Small RNAs (<200 nucleotides in length) were fractionated from the proximal nerve stumps to improve the representation of differential miRNA levels. Of 141 axoplasmic miRNAs annotated, 63 rat miRNAs showed significantly differential levels at five time points following injury, compared to an uninjured nerve. The differential changes in miRNA levels responding to injury were processed for hierarchical clustering analyses, and used to predict target mRNAs by Targetscan and miRanda. By overlapping these predicted targets with 2,924 axonally localizing transcripts previously reported, the overlapping set of 214 transcripts was further analyzed by the Gene Ontology enrichment and Ingenuity Pathway Analyses. These results suggest the possibility that the potential targets for these miRNAs play key roles in numerous neurological functions involved in ER stress response, cytoskeleton dynamics, vesicle formation, and neuro-degeneration and-regeneration. Finally, our results suggest that miRNAs could play a direct role in regenerative response and may be manipulated to promote regenerative ability of injured nerves.

Identifying human microRNA–disease associations by a new diffusion-based method

Identifying the microRNA–disease relationship is vital for investigating the pathogenesis of various diseases. However, experimental verification of disease-related microRNAs remains considerable challenge to many researchers, particularly for the fact that numerous new microRNAs are discovered every year. As such, development of computational methods for disease-related microRNA prediction has recently gained eminent attention. In this paper, first, we construct a miRNA functional network and a disease similarity network by integrating different information sources. Then, we further introduce a new diffusion-based method (NDBM) to explore global network similarity for miRNA–disease association inference. Even though known miRNA–disease associations in the database are rare, NDBM still achieves an area under the ROC curve (AUC) of 85.62% in the leave-one-out cross-validation in improving the prediction accuracy of previous methods significantly. Moreover, our method is applicable to diseases with no known related miRNAs as well as new miRNAs with unknown target diseases. Some associations who strongly predicted by our method are confirmed by public databases. These superior performances suggest that NDBM could be an effective and important tool for biomedical research.

Identification of precursor microRNAs within distal axons of sensory neuron

A set of specific precursor microRNAs (pre-miRNAs) are reported to localize into neuronal dendrites, where they could be processed locally to control synaptic protein synthesis and plasticity. However, it is not clear whether specific pre-miRNAs are also transported into distal axons to autonomously regulate intra-axonal protein synthesis. Here, we show that a subset of pre-miRNAs, whose mature miRNAs are enriched in axonal compartment of sympathetic neurons, are present in axons of neurons both in vivo and in vitro by quantitative PCR and by in situ hybridization. Some pre-miRNAs (let 7c-a and pre-miRs-16, 23a, 25, 125b-1, 433, and 541) showed elevated axonal levels, while others (pre-miRs-138-2, 185, and 221) were decreased in axonal levels following injury. Dicer and KSRP proteins are also present in distal axons, but Drosha is found restricted to the cell body. These findings suggest that specific pre-miRNAs are selected for localization into distal axons of sensory neurons and are presumably processed to mature miRNAs in response to extracellular stimuli. This study supports the notion that local miRNA biogenesis effectively provides another level of temporal control for local protein synthesis in axons.

miR-338-3p is over-expressed in blood, CFS, serum and spinal cord from sporadic amyotrophic lateral sclerosis patients

Amyotrophic lateral sclerosis (ALS) is a progressive and seriously disabling adult-onset neurological disease. Ninety percent of ALS patients are sporadic cases (sALS) with no clear genetic linkage. Accumulating evidence indicates that various microRNAs (miRNAs), expressed in a spatially and temporally controlled manner in the brain, play a key role in neuronal development. In addition, microRNA dysregulation contributes to some mental disorders and neurodegeneration diseases. In our research, the expression of one selected miRNA, miR-338-3p, which previously we have found over-expressed in blood leukocytes, was studied in several different tissues from sALS patients. For the first time, we detected a specific microRNA disease-related upregulation, miR-338-3p, in blood leukocytes as well in cerebrospinal fluid, serum, and spinal cord from sALS patients. Besides, staining of in situ hybridization showed that the signals of miR-338-3p were localized in the grey matter of spinal cord tissues from sALS autopsied patients. We propose that miRNA profiles found in tissue samples from sALS patients can be relevant to understand sALS pathogenesis and lead to set up effective biomarkers for sALS early diagnosis.

Current understanding of the role of microRNAs in spinocerebellar ataxias

The number of studies highlighting the role of microRNAs (miRNAs) in human physiology and diseases is growing, but many miRNA-driven regulatory mechanisms remain elusive. A proper understanding of the exact functions of individual miRNAs and their interaction with specific targets is vitally important because such knowledge might help cure diseases for which no effective treatment currently exists. Herein, we present current views on the role of the miRNA-mediated regulation of gene expression in the case of select spinocerebellar ataxias (SCAs) and their potential involvement in the pathogenesis of these diseases. Specifically, we summarize published data showing the known links between miRNAs and CAG repeat-dependent SCAs. Moreover, using the example of SCA type 3 (SCA3), we refer to the issue of prediction and validation of miRNA targets, and we demonstrate that miR-181a-1 may regulate the 3'-UTR of the ATXN3 gene.

Semi-supervised learning for potential human microRNA-disease associations inference

MicroRNAs play critical role in the development and progression of various diseases. Predicting potential miRNA-disease associations from vast amount of biological data is an important problem in the biomedical research. Considering the limitations in previous methods, we developed Regularized Least Squares for MiRNA-Disease Association (RLSMDA) to uncover the relationship between diseases and miRNAs. RLSMDA can work for diseases without known related miRNAs. Furthermore, it is a semi-supervised (does not need negative samples) and global method (prioritize associations for all the diseases simultaneously). Based on leave-one-out cross validation, reliable AUC have demonstrated the reliable performance of RLSMDA. We also applied RLSMDA to Hepatocellular cancer and Lung cancer and implemented global prediction for all the diseases simultaneously. As a result, 80% (Hepatocellular cancer) and 84% (Lung cancer) of top 50 predicted miRNAs and 75% of top 20 potential associations based on global prediction have been confirmed by biological experiments. We also applied RLSMDA to diseases without known related miRNAs in golden standard dataset. As a result, in the top 3 potential related miRNA list predicted by RLSMDA for 32 diseases, 34 disease-miRNA associations were successfully confirmed by experiments. It is anticipated that RLSMDA would be a useful bioinformatics resource for biomedical researches.

Approaches to the modulation of miRNA maturation

The therapeutic importance of microRNA (miRNA) regulation has recently been realized as these small, noncoding RNAs have been demonstrated to be involved with a plethora of diseases and disorders. Due to the complex miRNA maturation process, the expression of these important biomolecules can be manipulated at various stages of the pathway. This review examines both in vivo and in vitro mechanisms and assays that have been developed to regulate miRNA levels. Modulation of miRNA maturation can be accomplished via several therapeutic agents, including small molecules and oligonucleotides, in both specific and nonspecific fashions. Due to the relevance of miRNAs, these novel therapeutic approaches represent new tools for the treatment of various cancers and other deleterious disorders.

MicroRNAs act complementarily to regulate disease-related mRNA modules in human diseases

MicroRNAs (miRNAs) play a key role in regulating mRNA expression, and individual miRNAs have been proposed as diagnostic and therapeutic candidates. The identification of such candidates is complicated by the involvement of multiple miRNAs and mRNAs as well as unknown disease topology of the miRNAs. Here, we investigated if disease-associated miRNAs regulate modules of disease-associated mRNAs, if those miRNAs act complementarily or synergistically, and if single or combinations of miRNAs can be targeted to alter module functions. We first analyzed publicly available miRNA and mRNA expression data for five different diseases. Integrated target prediction and network-based analysis showed that the miRNAs regulated modules of disease-relevant genes. Most of the miRNAs acted complementarily to regulate multiple mRNAs. To functionally test these findings, we repeated the analysis using our own miRNA and mRNA expression data from CD4+ T cells from patients with seasonal allergic rhinitis. This is a good model of complex diseases because of its well-defined phenotype and pathogenesis. Combined computational and functional studies confirmed that miRNAs mainly acted complementarily and that a combination of two complementary miRNAs, miR-223 and miR-139-3p, could be targeted to alter disease-relevant module functions, namely, the release of type 2 helper T-cell (Th2) cytokines. Taken together, our findings indicate that miRNAs act complementarily to regulate modules of disease-related mRNAs and can be targeted to alter disease-relevant functions.

Genomics and proteomics in solving brain complexity

The human brain is extraordinarily complex, composed of billions of neurons and trillions of synaptic connections. Neurons are organized into circuit assemblies that are modulated by specific interneurons and non-neuronal cells, such as glia and astrocytes. Data on human genome sequences predicts that each of these cells in the human brain has the potential of expressing ∼20 000 protein coding genes and tens of thousands of noncoding RNAs. A major challenge in neuroscience is to determine (1) how individual neurons and circuitry utilize this potential during development and maturation of the nervous system, and for higher brain functions such as cognition, and (2) how this potential is altered in neurological and psychiatric disorders. In this review, we will discuss how recent advances in next generation sequencing, proteomics and bioinformatics have transformed our understanding of gene expression and the functions of neural circuitry, memory storage, and disorders of cognition.

RWRMDA: predicting novel human microRNA-disease associations

Recently, more and more research has shown that microRNAs (miRNAs) play critical roles in the development and progression of various diseases, but it is not easy to predict potential human miRNA-disease associations from the vast amount of biological data. Computational methods for predicting potential disease-miRNA associations have gained a lot of attention based on their feasibility, guidance and effectiveness. Differing from traditional local network similarity measures, we adopted global network similarity measures and developed Random Walk with Restart for MiRNA-Disease Association (RWRMDA) to infer potential miRNA-disease interactions by implementing random walk on the miRNA-miRNA functional similarity network. We tested RWRMDA on 1616 known miRNA-disease associations based on leave-one-out cross-validation, and achieved an area under the ROC curve of 86.17%, which significantly improves previous methods. The method was also applied to three cancers for accuracy evaluation. As a result, 98% (Breast cancer), 74% (Colon cancer), and 88% (Lung cancer) of top 50 predicted miRNAs are confirmed by published experiments. These results suggest that RWRMDA will represent an important bioinformatics resource in biomedical research of both miRNAs and diseases.

A miRNA signature in leukocytes from sporadic amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive and seriously disabling adult-onset neurological disease. Accumulating evidence indicates that various miRNAs, expressed in a spatially and temporally controlled manner in the brain, play a key role in neuronal development. In addition, misregulation of microRNAs contributes to some mental disorders and neurodegeneration diseases. Here, we analyzed the expression profiles of 911 human miRNAs using microarray technology in leukocytes, the most readily available human tissue cells, obtained from 8 patients affected by sporadic amyotrophic lateral sclerosis (sALS) and 12 healthy controls. An independent group of 14 sALS patients and 14 controls was used for validation by TaqMan real-time polymerase chain reaction assay. We identified 8 miRNAs that were significantly up- or downregulated in sALS patients as compared to healthy controls. The significant variations in miRNAs profiles detected in leukocytes have been related to miRNAs predominantly expressed in the nervous system. One of these miRNAs, miR-338-3p, has previously been shown to be de-regulated in ALS brains. This study, for the first time, detected specific microRNAs disease-related changes at an earlier stage of sALS. We suggest that miRNAs profiles found in the peripheral blood leukocytes from sALS patients can be relevant to understand the pathogenesis of sALS and/or used as biomarkers of the disease.

RNA-Seq and human complex diseases: recent accomplishments and future perspectives

The availability of the human genome sequence has allowed identification of disease-causing mutations in many Mendelian disorders, and detection of significant associations of nucleotide polymorphisms to complex diseases and traits. Despite these progresses, finding the causative variations for most of the common diseases remains a complex task. Several studies have shown gene expression analyses provide a quite unbiased way to investigate complex traits and common disorders' pathogenesis. Therefore, whole-transcriptome analysis is increasingly acquiring a key role in the knowledge of mechanisms responsible for complex diseases. Hybridization- and tag-based technologies have elucidated the involvement of multiple genes and pathways in pathological conditions, providing insights into the expression of thousand of coding and noncoding RNAs, such as microRNAs. However, the introduction of Next-Generation Sequencing, particularly of RNA-Seq, has overcome some drawbacks of previously used technologies. Identifying, in a single experiment, potentially novel genes/exons and splice isoforms, RNA editing, fusion transcripts and allele-specific expression are some of its advantages. RNA-Seq has been fruitfully applied to study cancer and host-pathogens interactions, and it is taking first steps for studying neurodegenerative diseases (ND) as well as neuropsychiatric diseases. In addition, it is emerging as a very powerful tool to study quantitative trait loci associated with gene expression in complex diseases. This paper provides an overview on gene expression profiling of complex diseases, with emphasis on RNA-Seq, its advantages over conventional technologies for studying cancer and ND, and for linking nucleotide variations to gene expression changes, also discussing its limitations.

Regulation of a truncated form of tropomyosin-related kinase B (TrkB) by Hsa-miR-185* in frontal cortex of suicide completers

Background

TrkB-T1 is a BDNF receptor lacking a tyrosine kinase domain that is highly expressed in astrocytes and regulates BDNF-evoked calcium transients. Previous studies indicate that downregulation of TrkB-T1 in frontal cortex may be involved in neurobiological processes underlying suicide.

Methods

In a microarray screening study (N = 8), we interrogated all known microRNA in the frontal cortex of suicide completers with low expression of TrkB-T1 and normal controls. These findings were validated and followed up in a larger sample of cases and controls (N = 55). Functional analyses included microRNA silencing, microRNA overexpression and luciferase assays to investigate specificity and to validate interactions between differentially expressed microRNA and TrkB-T1.

Results

MicroRNAs Hsa-miR-185* and Hsa-miR-491-3p were upregulated in suicide completers with low expression of TrkB.T1 (P_nominal: 9.10⁻⁵ and 1.8.10⁻⁴ respectively; FDR-corrected p = 0.031). Bioinformatic analyses revealed five putative binding sites for the DiGeorge syndrome linked microRNA Hsa-miR-185*in the 3′UTR of TrkB-T1, but none for Hsa-miR-491-3P. The increase of Hsa-miR-185* in frontal cortex of suicide completers was validated then confirmed in a larger, randomly selected group of suicide completers, where an inverse correlation between Hsa-miR-185* and TrkB-T1 expression was observed (R = −0.439; p = 0.001). Silencing and overexpression studies performed in human cell lines confirmed the inverse relationship between hsa-mir-185* and trkB-T1 expression. Luciferase assays demonstrated that Hsa-miR-185* binds to sequences in the 3′UTR of TrkB-T1.

Conclusion

These results suggest that an increase of Hsa-miR-185* expression levels regulates, at least in part, the TrkB-T1 decrease observed in the frontal cortex of suicide completers and further implicate the 22q11 region in psychopathology.

MicroRNA expression in mouse oligodendrocytes and regulation of proteolipid protein gene expression

Overexpression of the major myelin proteolipid protein (PLP) is detrimental to brain development and function and is the most common cause of Pelizaeus-Merzbacher disease. microRNA (miRNA), small, noncoding RNAs, have been shown to play critical roles in oligodendrocyte lineage. In this study, we sought to investigate whether miRNAs control PLP abundance. To identify candidate miRNAs involved in this regulation, we have examined differentiation-induced changes in the expression of miRNAs in the oligodendroglial cell line Oli-neu and in enhanced green fluorescent protein positive oligodendrocytes ex vivo. We have identified 145 miRNAs that are expressed in oligodendrocyte cell lineage progression. Dicer1 expression decreases in differentiated oligodendrocytes, and knock down of Dicer1 results in changes in miRNAs similar to those associated with differentiation. To identify miRNAs that control the PLP expression, we have selected miRNAs whose expression is lower in differentiated vs. undifferentiated Oli-neu cells and that have one or more binding site(s) in the PLP 3'-untranslated region (3'UTR). The PLP 3'UTR fused to the luciferase gene reduces the activity of the reporter, suggesting that it negatively regulates message stability or translation. Such suppression is relieved by knock down of miR-20a. Overexpression of miR-20a decreases expression of the endogenous PLP in primary oligodendrocytes and of the reporter gene. Deletion or mutation of the putative binding site for miR-20a in the PLP 3'UTR abrogated such effects. Our data indicate that miRNA expression is regulated by Dicer1 levels in differentiated oligodendrocytes and that miR-20a, a component of the cluster that controls oligodendrocyte cell number, regulates PLP gene expression through its 3'UTR.

Non-coding RNAs with essential roles in neurodegenerative disorders

The importance of various classes of regulatory non-protein-coding RNA molecules (ncRNAs) in the normal functioning of the CNS is becoming increasingly evident. ncRNAs are involved in neuronal cell specification and patterning during development, but also in higher cognitive processes, such as structural plasticity and memory formation in the adult brain. We discuss advances in understanding of the function of ncRNAs in the CNS, with a focus on the potential involvement of specific species, such as microRNAs, endogenous small interfering RNAs, long intergenic non-coding RNAs, and natural antisense transcripts, in various neurodegenerative disorders. This emerging field is anticipated to profoundly affect clinical research, diagnosis, and therapy in neurology.

RNA therapy for polyglutamine neurodegenerative diseases

Polyglutamine neurodegenerative diseases result from the expansion of a trinucleotide CAG repeat, encoding a polyglutamine tract in the disease-causing protein. The process by which each polyglutamine protein exerts its toxicity is complex, involving a variety of mechanisms including transcriptional dysregulation, proteasome impairment and mitochondrial dysfunction. Thus, the most effective and widely applicable therapies are likely to be those designed to eliminate production of the mutant protein upstream of these deleterious effects. RNA-based approaches represent promising therapeutic strategies for polyglutamine diseases, offering the potential to suppress gene expression in a sequence-specific manner at the transcriptional and post-transcriptional levels. In particular, gene silencing therapies capable of discrimination between mutant and wildtype alleles, based on disease-linked polymorphisms or CAG repeat length, might prove crucial in cases where a loss of wild type function is deleterious. Novel methods, such as gene knockdown and replacement, seek to eliminate the technical difficulties associated with allele-specific silencing by avoiding the need to target specific mutations. With a variety of RNA technologies currently being developed to target multiple facets of polyglutamine pathogenesis, the emergence of an effective therapy seems imminent. However, numerous technical obstacles associated with design, discrimination and delivery must be overcome before RNA therapy can be effectively applied in the clinical setting.

Impaired neurosteroid synthesis in multiple sclerosis

High-throughput technologies have led to advances in the recognition of disease pathways and their underlying mechanisms. To investigate the impact of micro-RNAs on the disease process in multiple sclerosis, a prototypic inflammatory neurological disorder, we examined cerebral white matter from patients with or without the disease by micro-RNA profiling, together with confirmatory reverse transcription-polymerase chain reaction analysis, immunoblotting and gas chromatography-mass spectrometry. These observations were verified using the in vivo multiple sclerosis model, experimental autoimmune encephalomyelitis. Brains of patients with or without multiple sclerosis demonstrated differential expression of multiple micro-RNAs, but expression of three neurosteroid synthesis enzyme-specific micro-RNAs (miR-338, miR-155 and miR-491) showed a bias towards induction in patients with multiple sclerosis (P < 0.05). Analysis of the neurosteroidogenic pathways targeted by micro-RNAs revealed suppression of enzyme transcript and protein levels in the white matter of patients with multiple sclerosis (P < 0.05). This was confirmed by firefly/Renilla luciferase micro-RNA target knockdown experiments (P < 0.05) and detection of specific micro-RNAs by in situ hybridization in the brains of patients with or without multiple sclerosis. Levels of important neurosteroids, including allopregnanolone, were suppressed in the white matter of patients with multiple sclerosis (P < 0.05). Induction of the murine micro-RNAs, miR-338 and miR-155, accompanied by diminished expression of neurosteroidogenic enzymes and allopregnanolone, was also observed in the brains of mice with experimental autoimmune encephalomyelitis (P < 0.05). Allopregnanolone treatment of the experimental autoimmune encephalomyelitis mouse model limited the associated neuropathology, including neuroinflammation, myelin and axonal injury and reduced neurobehavioral deficits (P < 0.05). These multi-platform studies point to impaired neurosteroidogenesis in both multiple sclerosis and experimental autoimmune encephalomyelitis. The findings also indicate that allopregnanolone and perhaps other neurosteroid-like compounds might represent potential biomarkers or therapies for multiple sclerosis.

The miRNA pathway in neurological and skeletal muscle disease: implications for pathogenesis and therapy

RNA interference (RNAi) represents a powerful post-transcriptional gene silencing network which fine-tunes gene expression in all eukaryotic cells. The endogenous triggers of RNAi, microRNAs (miRNAs), are proposed to regulate expression of up to a third of all protein-coding genes, and have been shown to have critical roles in developmental processes including in the central nervous system and skeletal muscle. Further, many have been reported to display differential expression in various disease states. Here we describe present understanding of the biogenesis and function of miRNAs, review current knowledge of miRNA abnormalities in both human neurological and skeletal muscle disease and discuss their potential as novel disease biomarkers. Finally, we highlight the many ways in which the miRNA pathway may be targeted for therapeutic benefit.

Identification of blood microRNAs associated to Parkinsonĭs disease

The present study demonstrates that blood samples can be used as a source of miRNA identification associated to Parkinson's disease (PD). A set of six differentially expressed microRNAs were identified. They form two groups according to their expression profile in control, non-treated, early-onset and treated Parkinson's disease subjects. While miR-1, miR-22* and miR-29 expression levels allowed to distinguish non-treated PD from healthy subjects, miR-16-2*, miR-26a2* and miR30a differentiated treated from untreated patients. This study is innovative in contributing to the development of effective PD biomarkers.

Amyotrophic lateral sclerosis: applications of stem cells - an update

Neurodegenerative diseases are a growing public health challenge, and amyotrophic lateral sclerosis (ALS) remains a fatal incurable disease. The advent of stem cell therapy has opened new horizons for both researchers and ALS patients, desperately looking for a treatment. ALS must be considered a systemic disease affecting many cell phenotypes besides motor neurons, even outside the central nervous system. Cell replacement therapy needs to address the specific neurobiological issues of ALS to safely and efficiently reach clinical settings. Moreover, the enormous potential of induced pluripotent cells directly derived from patients for modeling and understanding the pathological mechanisms, in correlation with the discoveries of new genes and animal models, provides new opportunities that need to be integrated with previously described transplantation strategies. Finally, a careful evaluation of preclinical data in conjunction with wary patient choice in clinical trials needs to be established in order to generate meaningful results.

MicroRNAs as effectors of brain function with roles in ischemia and injury, neuroprotection, and neurodegeneration

MicroRNAs are small RNAs that function as regulators of posttranscriptional gene expression. MicroRNAs are encoded by genes, and processed to form ribonucleoprotein complexes that bind to messenger RNA (mRNA) targets to repress translation or degrade mRNA transcripts. The microRNAs are particularly abundant in the brain where they serve as effectors of neuronal development and maintenance of the neuronal phenotype. They are also expressed in dendrites where they regulate spine structure and function as effectors in synaptic plasticity. MicroRNAs have been evaluated for their roles in brain ischemia, traumatic brain injury, and spinal cord injury, and in functional recovery after ischemia. They also serve as mediators in the brain's response to ischemic preconditioning that leads to endogenous neuroprotection. In addition, microRNAs are implicated in neurodegenerative disorders, including Alzheimer's, Huntington, Parkinson, and Prion disease. The discovery of microRNAs has expanded the potential for human diseases to arise from genetic mutations in microRNA genes or sequences within their target mRNAs. This review discusses microRNA discovery, biogenesis, mechanisms of gene regulation, their expression and function in the brain, and their roles in brain ischemia and injury, neuroprotection, and neurodegeneration.

Regulatory RNAs in brain function and disorders

Regulatory RNAs are being increasingly investigated in neurons, and important roles in brain function have been revealed. Regulatory RNAs are non-protein-coding RNAs (npcRNAs) that comprise a heterogeneous group of molecules, varying in size and mechanism of action. Regulatory RNAs often exert post-transcriptional control of gene expression, resulting in gene silencing or gene expression stimulation. Here, we review evidence that regulatory RNAs are implicated in neuronal development, differentiation, and plasticity. We will also discuss npcRNA dysregulation that may be involved in pathological states of the brain such as neurodevelopmental disorders, neurodegeneration, and epilepsy.

Prioritization of disease microRNAs through a human phenome-microRNAome network

Background

The identification of disease-related microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. Experimental identification of disease-related microRNAs poses considerable difficulties. Computational analysis of microRNA-disease associations is an important complementary means for prioritizing microRNAs for further experimental examination.

Results

Herein, we devised a computational model to infer potential microRNA-disease associations by prioritizing the entire human microRNAome for diseases of interest. We tested the model on 270 known experimentally verified microRNA-disease associations and achieved an area under the ROC curve of 75.80%. Moreover, we demonstrated that the model is applicable to diseases with which no known microRNAs are associated. The microRNAome-wide prioritization of microRNAs for 1,599 disease phenotypes is publicly released to facilitate future identification of disease-related microRNAs.

Conclusions

We presented a network-based approach that can infer potential microRNA-disease associations and drive testable hypotheses for the experimental efforts to identify the roles of microRNAs in human diseases.

Novel RNA-based strategies for therapeutic gene silencing

The past decade has seen intense scientific interest in non-coding RNAs. In particular, the discovery and subsequent exploitation of gene silencing via RNA interference (RNAi) has revolutionized the way in which gene expression is now studied and understood. It is now well established that post-transcriptional gene silencing (PTGS) by the microRNA (miRNA) and other RNAi-associated pathways represents an essential layer of complexity to gene regulation. Gene silencing using RNAi additionally demonstrates huge potential as a therapeutic strategy for eliminating pathogenic gene expression. Yet despite the early promise and excitement of gene-specific silencing, several critical hurdles remain to be overcome before widespread clinical adoption. These include off-target effects, toxicity due to saturation of the endogenous RNAi functions, limited duration of silencing, and effective targeted delivery. In recent years, a range of novel strategies for producing RNA-mediated silencing have been developed that can circumvent many of these hurdles, including small internally segmented interfering RNAs, tandem hairpin RNAs, and pri-miRNA cluster mimics. This review discusses RNA-mediated silencing in light of this recent research, and highlights the benefits and limitations conferred by these novel gene-silencing strategies.

The Role of MicroRNAs in Human Diseases

MicroRNAs (miRNAs) are short RNA molecules which bind to target mRNAs, resulting in translational repression and gene silencing and are found in all eukaryotic cells. Approximately 2200 miRNA genes have been reported to exist in the mammalian genome, from which over 1000 belong to the human genome. Many major cellular functions such as development, differentiation, growth, and metabolism are known to be regulated by miRNAs. Proximity to other genes in the genome and their locations in introns of coding genes, noncoding genes and exons have been reported to have a major influence on the level of gene expressions in eukaryotic cells. miRNAs are well conserved in eukaryotic system and are believed to be an essential and evolutionary ancient component of gene regulatory networks. Therefore, in recent years miRNAs have been studied as a likely candidate for involvement in most biologic processes and have been implicated in many human diseases.