Circulating microRNA profiles for detection of peripheral arterial disease: small new biomarkers for cardiovascular disease

MicroRNAs as Diagnostic and Prognostic Biomarkers in Ischemic Stroke-A Comprehensive Review and Bioinformatic Analysis

Stroke is the second-most common cause of death worldwide. The pathophysiology of ischemic stroke (IS) is related to inflammation, atherosclerosis, blood coagulation, and platelet activation. MicroRNAs (miRNAs) play important roles in physiological and pathological processes of neurodegenerative diseases and progression of certain neurological diseases, such as IS. Several different miRNAs, and their target genes, are recognized to be involved in the pathophysiology of IS. The capacity of miRNAs to simultaneously regulate several target genes underlies their unique value as diagnostic and prognostic markers in IS. In this review, we focus on the role of miRNAs as diagnostic and prognostic biomarkers in IS. We discuss the most common and reliable detection methods available and promising tests currently under development. We also present original results from bioinformatic analyses of published results, identifying the ten most significant genes (HMGB1, YWHAZ, PIK3R1, STAT3, MAPK1, CBX5, CAPZB, THBS1, TNFRSF10B, RCOR1) associated with inflammation, blood coagulation, and platelet activation and targeted by miRNAs in IS. Additionally, we created miRNA-gene target interaction networks based on Gene Ontology (GO) information derived from publicly available databases. Among our most interesting findings, miR-19a-3p is the most widely modulated miRNA across all selected ontologies and might be proposed as novel biomarker in IS to be tested in future studies.

MiR-125a-3p timely inhibits oligodendroglial maturation and is pathologically up-regulated in human multiple sclerosis

In the mature central nervous system (CNS), oligodendrocytes provide support and insulation to axons thanks to the production of a myelin sheath. During their maturation to myelinating cells, oligodendroglial precursors (OPCs) follow a very precise differentiation program, which is finely orchestrated by transcription factors, epigenetic factors and microRNAs (miRNAs), a class of small non-coding RNAs involved in post-transcriptional regulation. Any alterations in this program can potentially contribute to dysregulated myelination, impaired remyelination and neurodegenerative conditions, as it happens in multiple sclerosis (MS). Here, we identify miR-125a-3p, a developmentally regulated miRNA, as a new actor of oligodendroglial maturation, that, in the mammalian CNS regulates the expression of myelin genes by simultaneously acting on several of its already validated targets. In cultured OPCs, over-expression of miR-125a-3p by mimic treatment impairs while its inhibition with an antago-miR stimulates oligodendroglial maturation. Moreover, we show that miR-125a-3p levels are abnormally high in the cerebrospinal fluid of MS patients bearing active demyelinating lesions, suggesting that its pathological upregulation may contribute to MS development, at least in part by blockade of OPC differentiation leading to impaired repair of demyelinated lesions.

Universal disease biomarker: can a fixed set of blood microRNAs diagnose multiple diseases?

BACKGROUND

The selection of disease biomarkers is often difficult because of their unstable identification, i.e., the selection of biomarkers is heavily dependent upon the set of samples analyzed and the use of independent sets of samples often results in a completely different set of biomarkers being identified. However, if a fixed set of disease biomarkers could be identified for the diagnosis of multiple diseases, the difficulties of biomarker selection could be reduced.

RESULTS

In this study, the previously identified universal disease biomarker (UDB) consisting of blood miRNAs that could discriminate between patients with multiple diseases and healthy controls was extended to the recently reported independent measurements of blood microRNAs (miRNAs). The performance achieved by UDB in an independent set of samples was competitive with performances achieved with biomarkers selected using lasso, a standard, heavily sample-dependent procedure. Furthermore, the development of stable feature extraction was suggested to be a key factor in constructing more efficient and stable (i.e., sample- and disease-independent) UDBs.

CONCLUSIONS

The previously proposed UDB was successfully extended to an additional seven diseases and is expected to be useful for the diagnosis of other diseases.