RNAi-based therapeutic strategies for metabolic disease.
ABSTRACT RNA interference (RNAi) is a robust gene silencing mechanism that degrades mRNAs complementary to the antisense strands of double-stranded, short interfering RNAs (siRNAs). As a therapeutic strategy, RNAi has an advantage over small-molecule drugs, as virtually all genes are susceptible to targeting by siRNA molecules. This advantage is, however, counterbalanced by the daunting challenge of achieving safe, effective delivery of oligonucleotides to specific tissues in vivo. Lipid-based carriers of siRNA therapeutics can now target the liver in metabolic diseases and are being assessed in clinical trials for the treatment of hypercholesterolemia. For this indication, a chemically modified oligonucleotide that targets endogenous small RNA modulators of gene expression (microRNAs) is also under investigation in clinical trials. Emerging 'self-delivery' siRNAs that are covalently linked to lipophilic moieties show promise for the future development of therapies. Besides the liver, inflammation of the adipose tissue in patients with obesity and type 2 diabetes mellitus may be an attractive target for siRNA therapeutics. Administration of siRNAs encapsulated within glucan microspheres can silence genes in inflammatory phagocytic cells, as can certain lipid-based carriers of siRNA. New technologies that combine siRNA molecules with antibodies or other targeting molecules also appear encouraging. Although still at an early stage, the emergence of RNAi-based therapeutics has the potential to markedly influence our clinical future.
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ABSTRACT: MicroRNAs (miRNAs) are short endogenous noncoding RNAs that bind to target mRNAs, usually resulting in degradation and translational repression. Identification of miRNA targets is crucial for deciphering functional roles of the numerous miRNAs that are rapidly generated by sequencing efforts. Computational prediction methods are widely used for high-throughput generation of putative miRNA targets. We review a comprehensive collection of 38 miRNA sequence-based computational target predictors in animals that were developed over the past decade. Our in-depth analysis considers all significant perspectives including the underlying predictive methodologies with focus on how they draw from the mechanistic basis of the miRNA-mRNA interaction. We also discuss ease of use, availability, impact of the considered predictors and the evaluation protocols that were used to assess them. We are the first to comparatively and comprehensively evaluate seven representative methods when predicting miRNA targets at the duplex and gene levels. The gene-level evaluation is based on three benchmark data sets that rely on different ways to annotate targets including biochemical assays, microarrays and pSILAC. We offer practical advice on selection of appropriate predictors according to certain properties of miRNA sequences, characteristics of a specific application and desired levels of predictive quality. We also discuss future work related to the design of new models, data quality, improved usability, need for standardized evaluation and ability to predict mRNA expression changes. © The Author 2014. Published by Oxford University Press. For Permissions, please email: email@example.com.Briefings in Bioinformatics 12/2014; DOI:10.1093/bib/bbu044 · 5.92 Impact Factor
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ABSTRACT: MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression and, therefore, biological processes in different tissues. A major function of miRNAs in adipose tissue is to stimulate or inhibit the differentiation of adipocytes, and to regulate specific metabolic and endocrine functions. Numerous miRNAs are present in human adipose tissue; however, the expression of only a few is altered in individuals with obesity and type 2 diabetes mellitus or are differentially expressed in various adipose depots. In humans, obesity is associated with chronic low-grade inflammation that is regulated by signal transduction networks, in which miRNAs, either directly or indirectly (through regulatory elements such as transcription factors), influence the expression and secretion of inflammatory proteins. In addition to their diverse effects on signalling, miRNAs and transcription factors can interact to amplify the inflammatory effect. Although additional miRNA signal networks in human adipose tissue are not yet known, similar regulatory circuits have been described in brown adipose tissue in mice. miRNAs can also be secreted from fat cells into the circulation and serve as markers of disturbed adipose tissue function. Given their role in regulating transcriptional networks, miRNAs in adipose tissue might offer tangible targets for treating metabolic disorders.Nature Reviews Endocrinology 03/2015; DOI:10.1038/nrendo.2015.25 · 12.96 Impact Factor
Osteoarthritis and Cartilage 04/2013; 21:S303-S304. DOI:10.1016/j.joca.2013.02.633 · 4.66 Impact Factor