Diagnostic Value of microRNA for Alzheimer's Disease: A Systematic Review and Meta-Analysis

CircRNA and lncRNA-associated competing endogenous RNA networks in medulloblastoma: a scoping review

BACKGROUND

Medulloblastoma is one of the common primary central nervous system (CNS) malignancies in pediatric patients. The main treatment is surgical resection preceded and/or followed by chemoradiotherapy. However, their serious side effects necessitate a better understanding of medulloblastoma biology to develop novel therapeutic options.

MAIN BODY

Circular RNA (circRNA) and long non-coding RNA (lncRNA) regulate gene expression via microRNA (miRNA) pathways. Although growing evidence has highlighted the significance of circRNA and lncRNA-associated competing endogenous RNA (ceRNA) networks in cancers, no study has comprehensively investigated them in medulloblastoma. For this aim, the Web of Science, PubMed, Scopus, and Embase were systematically searched to obtain the relevant papers published before 16 September 2023, adhering to the PRISMA-ScR statement. HOTAIR, NEAT1, linc-NeD125, HHIP-AS1, CRNDE, and TP73-AS1 are the oncogenic lncRNAs, and Nkx2-2as is a tumor-suppressive lncRNA that develop lncRNA-associated ceRNA networks in medulloblastoma. CircSKA3 and circRNA_103128 are upregulated oncogenic circRNAs that develop circRNA-associated ceRNA networks in medulloblastoma.

CONCLUSION

In summary, this study has provided an overview of the existing evidence on circRNA and lncRNA-associated ceRNA networks and their impact on miRNA and mRNA expression involved in various signaling pathways of medulloblastoma. Suppressing the oncogenic ceRNA networks and augmenting tumor-suppressive ceRNA networks can provide ample opportunities for medulloblastoma treatment.

Non-coding RNAs involved in the molecular pathology of Alzheimer's disease: a systematic review

Alzheimer's disease (AD) is the leading cause of dementia globally, having a pathophysiology that is complex and multifactorial. Recent findings highlight the significant role of non-coding RNAs (ncRNAs), specifically microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and piwi-interacting RNAs (piRNAs) in the molecular mechanisms underlying AD. These ncRNAs are involved in critical biological processes such as cell proliferation, apoptosis, oxidative stress, amyloid-beta aggregation, tau phosphorylation, neuroinflammation, and autophagy, which are pivotal in AD development and progression. This systematic review aims to consolidate current scientific knowledge on the role of ncRNAs in AD, making it the first to encompass the four types of ncRNAs associated with the disease. Our comprehensive search and analysis reveal that ncRNAs not only play crucial roles in the pathogenesis of AD but also hold potential as biomarkers for its early detection and as novel therapeutic targets. Specifically, the findings underscore the significance of miRNAs in regulating genes involved in key AD pathways such as activin receptor signaling pathway, actomyosin contractile ring organization, and advanced glycation endproducts-receptor advanced glycation endproducts (AGE-RAGE) signaling pathway. This review also highlights the potential of ncRNAs in unveiling novel diagnostic and therapeutic strategies, emphasizing the need for further research to validate their clinical utility. Our systematic exploration provides a foundation for future bioinformatic analyses and the development of ncRNA-based precision medicine approaches for AD, offering new insights into the disease's molecular pathology and paving the way for innovative treatment strategies.

Systematic review registration

PROSPERO, https://www.crd.york.ac.uk/prospero/, CRD42022355307.

Patient-derived neuron model: Capturing age-dependent adult-onset degenerative pathology in Huntington's disease

MicroRNAs play a crucial role in directly reprogramming (converting) human fibroblasts into neurons. Specifically, miR-9/9* and miR-124 (miR-9/9*-124) display neurogenic and cell fate-switching activities when ectopically expressed in human fibroblasts by erasing fibroblast identity and inducing a pan-neuronal state. These converted neurons maintain the biological age of the starting fibroblasts and thus provide a human neuron-based platform to study cellular properties in aged neurons and model adult-onset neurodegenerative disorders using patient-derived cells. Furthermore, the expression of striatal-enriched transcription factors in conjunction with miR-9/9*-124 guides the identity of medium spiny neurons (MSNs), the primary targets in Huntington's disease (HD). Converted MSNs from HD patient-derived fibroblasts (HD-MSNs) can replicate HD-related phenotypes including neurodegeneration associated with age-related declines in critical cellular functions such as autophagy. Here, we review the role of microRNAs in the direct conversion of patient-derived fibroblasts into MSNs and the practical application of converted HD-MSNs as a model for studying adult-onset neuropathology in HD. We provide valuable insights into age-related, cell-intrinsic changes contributing to neurodegeneration in HD-MSNs. Ultimately, we address a comprehensive understanding of the complex molecular landscape underlying HD pathology, offering potential avenues for therapeutic application.

The role of microRNAs in understanding sex-based differences in Alzheimer's disease

BACKGROUND

The incidence of Alzheimer's disease (AD)-the most frequent cause of dementia-is expected to increase as life expectancies rise across the globe. While sex-based differences in AD have previously been described, there remain uncertainties regarding any association between sex and disease-associated molecular mechanisms. Studying sex-specific expression profiles of regulatory factors such as microRNAs (miRNAs) could contribute to more accurate disease diagnosis and treatment.

METHODS

A systematic review identified six studies of microRNA expression in AD patients that incorporated information regarding the biological sex of samples in the Gene Expression Omnibus repository. A differential microRNA expression analysis was performed, considering disease status and patient sex. Subsequently, results were integrated within a meta-analysis methodology, with a functional enrichment of meta-analysis results establishing an association between altered miRNA expression and relevant Gene Ontology terms.

RESULTS

Meta-analyses of miRNA expression profiles in blood samples revealed the alteration of sixteen miRNAs in female and 22 miRNAs in male AD patients. We discovered nine miRNAs commonly overexpressed in both sexes, suggesting a shared miRNA dysregulation profile. Functional enrichment results based on miRNA profiles revealed sex-based differences in biological processes; most affected processes related to ubiquitination, regulation of different kinase activities, and apoptotic processes in males, but RNA splicing and translation in females. Meta-analyses of miRNA expression profiles in brain samples revealed the alteration of six miRNAs in female and four miRNAs in male AD patients. We observed a single underexpressed miRNA in female and male AD patients (hsa-miR-767-5p); however, the functional enrichment analysis for brain samples did not reveal any specifically affected biological process.

CONCLUSIONS

Sex-specific meta-analyses supported the detection of differentially expressed miRNAs in female and male AD patients, highlighting the relevance of sex-based information in biomedical data. Further studies on miRNA regulation in AD patients should meet the criteria for comparability and standardization of information.

MicroRNAs in Parkinson's disease: a systematic review and diagnostic accuracy meta-analysis

Current clinical tests for Parkinson's disease (PD) provide insufficient diagnostic accuracy leading to an urgent need for improved diagnostic biomarkers. As microRNAs (miRNAs) are promising biomarkers of various diseases, including PD, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of biofluid miRNAs in PD. All studies reporting data on miRNAs expression in PD patients compared to controls were included. Gene targets and significant pathways associated with miRNAs expressed in more than 3 biofluid studies with the same direction of change were analyzed using target prediction and enrichment analysis. A bivariate model was used to calculate sensitivity, specificity, likelihood ratios, and diagnostic odds ratio. While miR-24-3p and miR-214-3p were the most reported miRNA (7 each), miR-331-5p was found to be consistently up regulated in 4 different biofluids. Importantly, miR-19b-3p, miR-24-3p, miR-146a-5p, and miR-221-3p were reported in multiple studies without conflicting directions of change in serum and bioinformatic analysis found the targets of these miRNAs to be associated with pathways important in PD pathology. Of the 102 studies from the systematic review, 15 studies reported sensitivity and specificity data on combinations of miRNAs and were pooled for meta-analysis. Studies (17) reporting sensitivity and specificity data on single microRNA were pooled in a separate meta-analysis. Meta-analysis of the combinations of miRNAs (15 studies) showed that biofluid miRNAs can discriminate between PD patients and controls with good diagnostic accuracy (sensitivity = 0.82, 95% CI 0.76-0.87; specificity = 0.80, 95% CI 0.74-0.84; AUC = 0.87, 95% CI 0.83-0.89). However, we found multiple studies included more males with PD than any other group therefore possibly introducing a sex-related selection bias. Overall, our study captures key miRNAs which may represent a point of focus for future studies and the development of diagnostic panels whilst also highlighting the importance of appropriate study design to develop representative biomarker panels for the diagnosis of PD.

Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases

Micro-RNAs (miRNAs) are short (∼21 nt) non-coding RNAs that regulate gene expression through the degradation or translational repression of mRNAs. Accumulating evidence points to a role of miRNA regulation in the pathogenesis of a wide range of neurodegenerative (ND) diseases such as, for example, Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and Huntington disease (HD). Several systems level studies aimed to explore the role of miRNA regulation in NDs, but these studies remain challenging. Part of the problem may be related to the lack of sufficiently rich or homogeneous data, such as time series or cell-type-specific data obtained in model systems or human biosamples, to account for context dependency. Part of the problem may also be related to the methodological challenges associated with the accurate system-level modeling of miRNA and mRNA data. Here, we critically review the main families of machine learning methods used to analyze expression data, highlighting the added value of using shape-analysis concepts as a solution for precisely modeling highly dimensional miRNA and mRNA data such as the ones obtained in the study of the HD process, and elaborating on the potential of these concepts and methods for modeling complex omics data.

Differential expression of MicroRNAs in Alzheimer's disease: a systematic review and meta-analysis

Alzheimer's disease (AD) results in progressive cognitive decline owing to the accumulation of amyloid plaques and hyperphosphorylated tau. MicroRNAs (miRNAs) have attracted attention as a putative diagnostic and therapeutic target for neurodegenerative diseases. However, existing meta-analyses on AD and its association with miRNAs have produced inconsistent results. The primary objective of this study is to evaluate the magnitude and consistency of differences in miRNA levels between AD patients, mild cognitive impairment (MCI) patients and healthy controls (HC). Articles investigating miRNA levels in blood, brain tissue, or cerebrospinal fluid (CSF) of AD and MCI patients versus HC were systematically searched in PubMed/Medline from inception to February 16^th, 2021. Fixed- and random-effects meta-analyses were complemented with the I² statistic to measure the heterogeneity, assessment of publication bias, sensitivity subgroup analyses (AD severity, brain region, post-mortem versus ante-mortem specimen for CSF and type of analysis used to quantify miRNA) and functional enrichment pathway analysis. Of the 1512 miRNAs included in 61 articles, 425 meta-analyses were performed on 334 miRNAs. Fifty-six miRNAs were significantly upregulated (n = 40) or downregulated (n = 16) in AD versus HC and all five miRNAs were significantly upregulated in MCI versus HC. Functional enrichment analysis confirmed that pathways related to apoptosis, immune response and inflammation were statistically enriched with upregulated pathways in participants with AD relative to HC. This study confirms that miRNAs' expression is altered in AD and MCI compared to HC. These findings open new diagnostic and therapeutic perspectives for this disorder.

Exposure to a mixture of heavy metals induces cognitive impairment: Genes and microRNAs involved

Converging evidence demonstrates that microRNAs (miRNAs) play an important role in the etiology of cognitive impairment. Thus, we aim to: (i) identify the molecular mechanisms of heavy metals, particularly miRNAs involved in the development of cognitive impairment; and (ii) generate miRNA sponges to prevent them from binding with their target messenger RNAs. The Comparative Toxicogenomics Database (CTD; http://ctd.mdibl.org), MicroRNA ENrichment TURned NETwork (MIENTURNET, http://userver.bio.uniroma1.it/apps/mienturnet/) and the microRNA sponge generator and tester (miRNAsong, http://www.med.muni.cz/histology/miRNAsong) were used as the core data-mining approaches in the current study. We observed that lead acetate, arsenic, gold, copper, iron, and aluminum, as well as their mixtures, had significant effects on the development of cognitive impairment. Although prevalent genes obtained from investigated heavy metals of cognitive impairment were different, the "PI3K-Akt signaling pathway", "pathways of neurodegeneration-multiple diseases", "apoptosis", "apoptosis-multiple species", "p53 signaling pathway", "NF-kappa B signaling pathway", and "Alzheimer's disease pathway" were highlighted. The mixed heavy metals altered the genes BAX, CASP3, BCL2, TNF, and IL-1B, indicating the significance of apoptosis and pro-inflammatory cytokines in the pathogenesis of cognitive impairment and the possibility of targeting these genes in future neuroprotective therapy. In addition, we used a network-based approach to identify key genes, miRNAs, pathways, and diseases related to the development of cognitive impairment. We also found 16 significant miRNAs related to cognitive impairment (hsa-miR-1-3p, hsa-let-7a-5p, hsa-miR-9-5p, hsa-miR-16-5p, hsa-miR-17-5p, hsa-miR-20a-5p, hsa-miR-26a-5p, hsa-miR-26b-5p, hsa-miR-34a-5p, hsa-miR-101-3p, hsa-miR-106a-5p, hsa-miR-128-3p, hsa-miR-144-3p, hsa-miR-199a-3p, hsa-miR-204-5p, and hsa-miR-335-5p). Finally, we created and evaluated miRNA sponge sequences for these miRNAs in silico. Further studies, including in vivo and in vitro, are needed to assess the link between these genes, miRNAs, pathways, and cognitive impairment.

Evaluation of hsa-let-7d-5p, hsa-let-7g-5p and hsa-miR-15b-5p plasma levels in patients with Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder MicroRNAs (miRNAs) may be promising diagnostic biomarkers for AD. Previous evidence shows that miR-15b-5p, hsa-let7g-5p and hsa-let7d-5p might confer potential blood biomarkers for timely diagnosis of AD. Therefore, in this replication study, we aimed to investigate the serum transcript level of these miRNAs to assess for their potential as diagnostic or prognostic biomarker in AD patients.

METHODS

Blood samples were obtained from 50 AD patients and 50 age- and sex-matched healthy individuals. Then, total RNA was extracted from serum samples, cDNA was synthesized, and the expression level of miRNAs was measured by the real-time PCR method.

RESULTS

The expression level of hsa-let7d-5p (fold change = 2.14, P = 0.007) and hsa-let7g-5p (fold change = 1.94; P = 0.013) was significantly increased in the AD patients compared to control individuals. However, the difference in the transcription of miR-15b-5p between the two groups was not statistically significant (fold change = 1.08; P = 0.76). The AROC for transcript levels of hsa-let-7d-5p was 0.68 (P = 0.014; 95% CI, 0.39-0.88) and it was 0.64 for hsa-let-7g-5p (P = 0.028; 95% CI, 0.27-0.89). The cut-off value for let-7d-5p had 0.82 sensitivity and 0.34 specificity. Moreover, the cut-off value for hsa-let-7g-5p indicated a 0.79 sensitivity and 0.28 specificity.

CONCLUSION

Our findings suggest the potential of measuring the transcript levels of hsa-let7d-5p and hsa-let7g-5p miRNAs as a diagnostic biomarker for AD.

The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives

Multi-pathway approaches for the treatment of complex polygenic disorders are emerging as alternatives to classical monotarget therapies and microRNAs are of particular interest in that regard. MicroRNA research has come a long way from their initial discovery to the cumulative appreciation of their regulatory potential in healthy and diseased brain. However, systematic interrogation of putative therapeutic or toxic effects of microRNAs in (models of) Alzheimer's disease is currently missing and fundamental research findings are yet to be translated into clinical applications. Here, we review the literature to summarize the knowledge on microRNA regulation in Alzheimer's pathophysiology and to critically discuss whether and to what extent these increasing insights can be exploited for the development of microRNA-based therapeutics in the clinic.

DNA-Based Smart Reagent for Detecting Alzheimer's Associated MicroRNAs

Alzheimer's disease (AD) is the most common neurodegenerative disorder, with significant research efforts devoted to identifying new biomarkers for clinical diagnosis and treatment. MicroRNAs have emerged as likely disease regulators and biomarkers for AD, now implicated as having roles in several biological processes related to progression of the disease. In this work, we use the miRacles assay (microRNA activated conditional looping of engineered switches) for single-step detection of AD-related microRNAs. The technology is based on conformationally responsive DNA nanoswitches that loop upon recognition of a target microRNA and report their on/off status through an electrophoretic readout. Unlike many methods, our approach directly detects native microRNAs without amplification or labeling, eliminating the need for expensive enzymes, reagents, and equipment. For known AD-related microRNA miR-107, we demonstrated sensitivity of ∼8 fM, specificity among four similar microRNAs of the same family, and simultaneous multiplexed detection of those four microRNA targets. Toward clinical use, we screened 56 AD-related microRNAs and found four that showed detectable differences between total RNA extracts derived from human healthy and AD brain samples. In the context of AD, this "smart reagent" could facilitate biomarker discovery, accelerate efforts to understand the role of microRNAs in AD, and have clinical potential as a diagnostic or monitoring tool for validated biomarkers.

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and discrimination of each neurodegenerative disorder a priority. Several investigations have revealed the importance of microRNAs and long non-coding RNAs in neurodevelopment, brain function, maturation, and neuronal activity, as well as its dysregulation involved in many types of neurological diseases. Therefore, the expression pattern of these molecules in the different NDs have gained significant attention to improve the diagnostic and treatment at earlier stages. In this sense, we gather the different microRNAs and long non-coding RNAs that have been reported as dysregulated in each disorder. Since there are a vast number of non-coding RNAs altered in NDs, some sort of synthesis, filtering and organization method should be applied to extract the most relevant information. Hence, machine learning is considered as an important tool for this purpose since it can classify expression profiles of non-coding RNAs between healthy and sick people. Therefore, we deepen in this branch of computer science, its different methods, and its meaningful application in the diagnosis of NDs from the dysregulated non-coding RNAs. In addition, we demonstrate the relevance of machine learning in NDs from the description of different investigations that showed an accuracy between 85% to 95% in the detection of the disease with this tool. All of these denote that artificial intelligence could be an excellent alternative to help the clinical diagnosis and facilitate the identification diseases in early stages based on non-coding RNAs.

MiR-340 Reduces the Accumulation of Amyloid-β Through Targeting BACE1 (β-site Amyloid Precursor Protein Cleaving Enzyme 1) in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is the most common neurodegenerative disease, and the accumulation of amyloid-β is the initial process in AD. MicroRNAs (miRNAs) are widely known as key regulators of the accumulation of amyloid-β in AD. This study analyzed the potential effects and possible internal mechanisms of miR-340 on AD.

METHODS

The expression of miR-340 in senescence-accelerated mouse prone-8 (SAMP8) mouse and senescence-accelerated mice/resistant-1 (SAMR1) mouse was evaluated by qRT-PCR (quantitative real-time polymerase chain reaction). The expression of β-site amyloid precursor protein cleaving enzyme 1 (BACE1) was determined by qRT-PCR and western blot. The binding ability between miR-340 and BACE1 was verified by dual-luciferase reporter assay. In vitro cell model of AD was established in human neuroblastoma SH-SY5Y cells transfected with Swedish mutant form of amyloid precursor protein (APPswe). The effect of miR-340 on the accumulation of amyloid- β was investigated by western blot analysis. Flow cytometry was conducted to detect cell apoptosis.

RESULTS

MiR-340 was down-regulated in the hippocampus of AD model SAMP8 mouse compared to SAMR1 mouse, while BACE1 was up-regulated in SAMP8, suggesting a negative correlation between miR-340 and BACE1 in SAMP8 mouse. MiR-340 could directly bind with BACE1, and over-expression of miR-340 decreased expression of BACE1 in SH-SY5Y/APPswe cells. MiR- 340 reduced the accumulation of amyloid-β and suppressed cell apoptosis through targeting BACE1 in SH-SY5Y/APPswe cells.

CONCLUSION

MiR-340 was downregulated in AD and reduced the accumulation of amyloid-β through targeting BACE1, suggesting a potential therapeutic target for AD.

Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer's disease by meta-analysis and adaptive boosting ensemble learning

BACKGROUND

Blood circulating microRNAs that are specific for Alzheimer's disease (AD) can be identified from differentially expressed microRNAs (DEmiRNAs). However, non-reproducible and inconsistent reports of DEmiRNAs hinder biomarker development. The most reliable DEmiRNAs can be identified by meta-analysis. To enrich the pool of DEmiRNAs for potential AD biomarkers, we used a machine learning method called adaptive boosting for miRNA disease association (ABMDA) to identify eligible candidates that share similar characteristics with the DEmiRNAs identified from meta-analysis. This study aimed to identify blood circulating DEmiRNAs as potential AD biomarkers by augmenting meta-analysis with the ABMDA ensemble learning method.

METHODS

Studies on DEmiRNAs and their dysregulation states were corroborated with one another by meta-analysis based on a random-effects model. DEmiRNAs identified by meta-analysis were collected as positive examples of miRNA-AD pairs for ABMDA ensemble learning. ABMDA identified similar DEmiRNAs according to a set of predefined criteria. The biological significance of all resulting DEmiRNAs was determined by their target genes according to pathway enrichment analyses. The target genes common to both meta-analysis- and ABMDA-identified DEmiRNAs were collected to construct a network to investigate their biological functions.

RESULTS

A systematic database search found 7841 studies for an extensive meta-analysis, covering 54 independent comparisons of 47 differential miRNA expression studies, and identified 18 reliable DEmiRNAs. ABMDA ensemble learning was conducted based on the meta-analysis results and the Human MicroRNA Disease Database, which identified 10 additional AD-related DEmiRNAs. These 28 DEmiRNAs and their dysregulated pathways were related to neuroinflammation. The dysregulated pathway related to neuronal cell cycle re-entry (CCR) was the only statistically significant pathway of the ABMDA-identified DEmiRNAs. In the biological network constructed from 1865 common target genes of the identified DEmiRNAs, the multiple core ubiquitin-proteasome system, that is involved in neuroinflammation and CCR, was highly connected.

CONCLUSION

This study identified 28 DEmiRNAs as potential AD biomarkers in blood, by meta-analysis and ABMDA ensemble learning in tandem. The DEmiRNAs identified by meta-analysis and ABMDA were significantly related to neuroinflammation, and the ABMDA-identified DEmiRNAs were related to neuronal CCR.

Differential Expression and miRNA-Gene Interactions in Early and Late Mild Cognitive Impairment

Mild cognitive impairment (MCI) and Alzheimer's Disease (AD) are complex diseases with their molecular architecture not elucidated. APOE, Amyloid Beta Precursor Protein (APP), and Presenilin-1 (PSEN1) are well-known genes associated with both MCI and AD. Recently, epigenetic alterations and dysregulated regulatory elements, such as microRNAs (miRNAs), have been reported associated with neurodegeneration. In this study, differential expression analysis (DEA) was performed for genes and miRNAs based on microarray and RNA-Seq data. Global gene profile of healthy individuals, early and late mild cognitive impairment (EMCI and LMCI, respectively), and AD was obtained from ADNI Cohort. miRNA global profile of healthy individuals and AD patients was extracted from public RNA-Seq data. DEA performed with limma package on ADNI Cohort data highlighted eight differential expressed (DE) genes (AGER, LINC00483, MMP19, CATSPER1, ARFGAP1, GPER1, PHLPP2, TRPM2) (false discovery rate (FDR) p-value < 0.05) between EMCI and LMCI patients. Previous molecular studies showed associations between these genes with dementia and neurological-related pathways. Five dysregulated miRNAs were identified by DEA performed with RNA-Seq data and edgeR (FDR p-value < 0.002). All reported miRNAs in AD interact with the aforementioned genes. Our integrative transcriptomic analysis was able to identify a set of miRNA-gene interactions that may be involved in cognitive and neurodegeneration processes.

Gene biomarker discovery at different stages of Alzheimer using gene co-expression network approach

Alzheimer's disease (AD) is a chronic neurodegenerative disorder. It is the most common type of dementia that has remained as an incurable disease in the world, which destroys the brain cells irreversibly. In this study, a systems biology approach was adopted to discover novel micro-RNA and gene-based biomarkers of the diagnosis of Alzheimer's disease. The gene expression data from three AD stages (Normal, Mild Cognitive Impairment, and Alzheimer) were used to reconstruct co-expression networks. After preprocessing and normalization, Weighted Gene Co-Expression Network Analysis (WGCNA) was used on a total of 329 samples, including 145 samples of Alzheimer stage, 80 samples of Mild Cognitive Impairment (MCI) stage, and 104 samples of the Normal stage. Next, three gene-miRNA bipartite networks were reconstructed by comparing the changes in module groups. Then, the functional enrichment analyses of extracted genes of three bipartite networks and miRNAs were done, respectively. Finally, a detailed analysis of the authentic studies was performed to discuss the obtained biomarkers. The outcomes addressed proposed novel genes, including MBOAT1, ARMC7, RABL2B, HNRNPUL1, LAMTOR1, PLAGL2, CREBRF, LCOR, and MRI1and novel miRNAs comprising miR-615-3p, miR-4722-5p, miR-4768-3p, miR-1827, miR-940 and miR-30b-3p which were related to AD. These biomarkers were proposed to be related to AD for the first time and should be examined in future clinical studies.

Downregulated Platelet miR-1233-5p in Patients with Alzheimer's Pathologic Change with Mild Cognitive Impairment is Associated with Aβ-Induced Platelet Activation via P-Selectin

MicroRNAs (miRNAs) have been proposed as a promising biomarker for various diseases including Alzheimer's disease (AD). More attention has recently been focused on the diagnosis and treatment at earlier stage of mild cognitive impairment (MCI) for preventing its progression to AD. To identify potential pathologic markers for Aβ(+)MCI (Alzheimer's pathologic change with MCI), we investigated miRNA expression profiles in the platelets from patients with Aβ(+)MCI, in comparison with those from Aβ(-)MCI (Non-Alzheimer's pathologic change with MCI) and CNI (cognitively normal individuals). We found that let-7i-5p, miR-125a, miR-1233-5p, and miR-6787-5p were significantly downregulated, while miR-6880-5p expression was upregulated. Of these, only miR-1233-5p was significantly downregulated by Aβ treatment in both human platelets and their precursor megakaryocytes (MEG-01 cells). We explored the role of miRNAs by using miRNA mimics or inhibitors, and found that the diminished level of miR-1233-5p was associated with Aβ-induced increase in the expression of P-selectin and cell adhesion to fibronectin. Our results further indicated that Aβ-induced increase in platelet/MEG adhesion to fibronectin is likely mediated via P-selectin. In conclusion, this study suggests the downregulation of platelet-derived miR-1233-5p as a pathologic marker for Aβ(+)MCI.

Meta-analyses identify differentially expressed micrornas in Parkinson's disease

OBJECTIVE

MicroRNA (miRNA)-mediated (dys)regulation of gene expression has been implicated in Parkinson's disease (PD), although results of miRNA expression studies remain inconclusive. We aimed to identify miRNAs that show consistent differential expression across all published expression studies in PD.

METHODS

We performed a systematic literature search on miRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen, we performed meta-analyses across miRNAs assessed in three or more independent data sets. Meta-analyses were performed using effect-size- and p-value-based methods, as applicable.

RESULTS

After screening 599 publications, we identified 47 data sets eligible for meta-analysis. On these, we performed 160 meta-analyses on miRNAs quantified in brain (n = 125), blood (n = 31), or CSF (n = 4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α = 3.13 × 10^-4 ) differentially expressed miRNAs in brain (n = 3) and blood (n = 10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p = 6.37 × 10^-5 ), hsa-miR-497-5p (p = 1.35 × 10^-4 ), and hsa-miR-133b (p = 1.90 × 10^-4 ) in brain and with hsa-miR-221-3p (p = 4.49 × 10^-35 ), hsa-miR-214-3p (p = 2.00 × 10^-34 ), and hsa-miR-29c-3p (p = 3.00 × 10^-12 ) in blood. No significant signals were found in CSF. Analyses of genome-wide association study data for target genes of brain miRNAs showed significant association (α = 9.40 × 10^-5 ) of genetic variants in nine loci.

INTERPRETATION

We identified several miRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood miRNAs as biomarkers for diagnosis, progression, or prediction of PD. ANN NEUROL 2019;85:835-851.

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previously, we published high-throughput sequencing based microRNA (miRNA) signatures in Alzheimer’s disease (AD) patients in the United States (US) and Germany. Here, we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR. We computed models to assess the relation between miRNA expression and phenotypes, gender, age, or disease severity (Mini-Mental State Examination; MMSE). Of the 21 miRNAs, expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts. 18 miRNAs were significantly correlated with neurodegeneration (Benjamini-Hochberg adjusted P < 0.05) with highest significance for miR-532-5p (Benjamini-Hochberg adjusted P = 4.8 × 10⁻³⁰). Machine learning models reached an area under the curve (AUC) value of 87.6% in differentiating AD patients from controls. Further, ten miRNAs were significantly correlated with MMSE, in particular miR-26a/26b-5p (adjusted P = 0.0002). Interestingly, the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells, while those up-regulated in AD were enriched in serum, exosomes, cytotoxic t-cells, and B-cells. Our study represents the next important step in translational research for a miRNA-based AD test.

Exploratory study on microRNA profiles from plasma-derived extracellular vesicles in Alzheimer's disease and dementia with Lewy bodies

Background

Because of the increasing life expectancy in our society, aging-related neurodegenerative disorders are one of the main issues in global health. Most of these diseases are characterized by the deposition of misfolded proteins and a progressive cognitive decline. Among these diseases, Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) are the most common types of degenerative dementia. Although both show specific features, an important neuropathological and clinical overlap between them hampers their correct diagnosis. In this work, we identified molecular biomarkers aiming to improve the misdiagnosis between both diseases.

Methods

Plasma extracellular vesicles (EVs) -from DLB, AD and healthy controls- were isolated using size-exclusion chromatography (SEC) and characterized by flow cytometry, Nanoparticle Tracking Analysis (NTA) and cryo-electron microscopy. Next Generation Sequencing (NGS) and related bibliographic search was performed and a selected group of EV-associated microRNAs (miRNAs) was analysed by qPCR.

Results

Results uncovered two miRNAs (hsa-miR-451a and hsa-miR-21-5p) significantly down-regulated in AD samples respect to DLB patients, and a set of four miRNAs (hsa-miR-23a-3p, hsa-miR-126-3p, hsa-let-7i-5p, and hsa-miR-151a-3p) significantly decreased in AD respect to controls. The two miRNAs showing decreased expression in AD in comparison to DLB provided area under the curve (AUC) values of 0.9 in ROC curve analysis, thus suggesting their possible use as biomarkers to discriminate between both diseases. Target gene analysis of these miRNAs using prediction online tools showed accumulation of phosphorylation enzymes, presence of proteasome-related proteins and genes involved in cell death among others.

Conclusion

Our data suggest that plasma-EV associated miRNAs may reflect a differential profile for a given dementia-related disorder which, once validated in larger cohorts of patients, could help to improve the differential diagnosis of DLB versus AD.

Electronic supplementary material

The online version of this article (10.1186/s40035-019-0169-5) contains supplementary material, which is available to authorized users.

Identification of molecular signatures and pathways to identify novel therapeutic targets in Alzheimer's disease: Insights from a systems biomedicine perspective

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. However, there are no peripheral biomarkers available that can detect AD onset. This study aimed to identify the molecular signatures in AD through an integrative analysis of blood gene expression data. We used two microarray datasets (GSE4226 and GSE4229) comparing peripheral blood transcriptomes of AD patients and controls to identify differentially expressed genes (DEGs). Gene set and protein overrepresentation analysis, protein-protein interaction (PPI), DEGs-Transcription Factors (TFs) interactions, DEGs-microRNAs (miRNAs) interactions, protein-drug interactions, and protein subcellular localizations analyses were performed on DEGs common to the datasets. We identified 25 common DEGs between the two datasets. Integration of genome scale transcriptome datasets with biomolecular networks revealed hub genes (NOL6, ATF3, TUBB, UQCRC1, CASP2, SND1, VCAM1, BTF3, VPS37B), common transcription factors (FOXC1, GATA2, NFIC, PPARG, USF2, YY1) and miRNAs (mir-20a-5p, mir-93-5p, mir-16-5p, let-7b-5p, mir-708-5p, mir-24-3p, mir-26b-5p, mir-17-5p, mir-193-3p, mir-186-5p). Evaluation of histone modifications revealed that hub genes possess several histone modification sites associated with AD. Protein-drug interactions revealed 10 compounds that affect the identified AD candidate biomolecules, including anti-neoplastic agents (Vinorelbine, Vincristine, Vinblastine, Epothilone D, Epothilone B, CYT997, and ZEN-012), a dermatological (Podofilox) and an immunosuppressive agent (Colchicine). The subcellular localization of molecular signatures varied, including nuclear, plasma membrane and cytosolic proteins. In the present study, it was identified blood-cell derived molecular signatures that might be useful as candidate peripheral biomarkers in AD. It was also identified potential drugs and epigenetic data associated with these molecules that may be useful in designing therapeutic approaches to ameliorate AD.

Evaluation of the Common Molecular Basis in Alzheimer's and Parkinson's Diseases

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.

Understanding Epigenetics in the Neurodegeneration of Alzheimer's Disease: SAMP8 Mouse Model

Epigenetics is emerging as the missing link among genetic inheritance, environmental influences, and body and brain health status. In the brain, specific changes in nucleic acids or their associated proteins in neurons and glial cells might imprint differential patterns of gene activation that will favor either cognitive enhancement or cognitive loss for more than one generation. Furthermore, derangement of age-related epigenetic signaling is appearing as a significant risk factor for illnesses of aging, including neurodegeneration and Alzheimer’s disease (AD). In addition, better knowledge of epigenetic mechanisms might provide hints and clues in the triggering and progression of AD. Intense research in experimental models suggests that molecular interventions for modulating epigenetic mechanisms might have therapeutic applications to promote cognitive maintenance through an advanced age. The SAMP8 mouse is a senescence model with AD traits in which the study of epigenetic alterations may unveil epigenetic therapies against the AD.

MicroRNAs and mild cognitive impairment: A systematic review

BACKGROUND

Mild cognitive impairment (MCI) is usually described as an intermediate phase between normal cognition and dementia. Identifying the subjects at a higher risk of progressing from MCI to AD is essential to manage this condition. The diagnosis of MCI is mainly clinical. Several biomarkers have been proposed, but mostly for research purposes, as they are based on an invasive procedure to obtain the sample, such as cerebrospinal fluid (CSF). As a consequence, rapid and non-invasive biomarkers are needed to improve diagnosis. The objective of this systematic review is to summarize available evidence on the use of miRNAs as biomarkers in subjects with MCI.

METHODS

Relevant literature published up to June 2018 was retrieved searching the databases PubMed, ISI Web of Knowledge and the Cochrane Database. Only studies considering microRNAs (miRNAs) and a diagnosis of MCI were included. Data were extracted using a specifically-designed standardized form, and their methodological quality was assessed using QUADAS-2 and QUIPS.

RESULTS

Twenty-one studies of 153 retrieved articles met the predefined inclusion/exclusion criteria. Studies included participants ranging from 6 to 330. More than 40 miRNAs resulted as dysregulated, and miR-206 was the only miRNA that was found as differentially expressed in patients with MCI by more than two studies. However, these results have either not yet been confirmed in other independent cohorts, or data are still inconsistent. Inconsistencies among included studies could be due to several issues including the selection of participants, pre-analytical and analytical procedures, and statistical analyses.

microRNA diagnostic panel for Alzheimer's disease and epigenetic trade-off between neurodegeneration and cancer

microRNAs (miRNAs) have been extensively studied as potential biomarkers for Alzheimer's disease (AD). Their profiles have been analyzed in blood, cerebrospinal fluid (CSF) and brain tissue. However, due to the high variability between the reported data, stemming from the lack of methodological standardization and the heterogeneity of AD, the most promising miRNA biomarker candidates have not been selected. Our literature review shows that out of 137 miRNAs found to be altered in AD blood, 36 have been replicated in at least one independent study, and out of 166 miRNAs reported as differential in AD CSF, 13 have been repeatedly found. Only 3 miRNAs have been consistently reported as altered in three analyzed specimens: blood, CSF and the brain (hsa-miR-146a, hsa-miR-125b, hsa-miR-135a). Nonetheless, all 36 repeatedly differential miRNAs in AD blood are promising as components of the diagnostic panel. Given their predicted functions, such miRNA panel may report multiple pathways contributing to AD pathology, enabling the design of personalized therapies. In addition, the analysis revealed that the miRNAs dysregulated in AD overlap highly with miRNAs implicated in cancer. However, the directions of the miRNA changes are usually opposite in cancer and AD, indicative of an epigenetic trade-off between the two diseases.

Network-based approach to identify molecular signatures and therapeutic agents in Alzheimer's disease

Alzheimer's disease (AD) is a dynamic degeneration of the brain with progressive dementia. Considering the uncertainties in its molecular mechanism, in the present study, we employed network-based integrative analyses, and aimed to explore the key molecules and their associations with small drugs to identify potential biomarkers and therapeutic agents for the AD. First of all, we studied a transcriptome dataset and identified 1521 differentially expressed genes (DEGs). Integration of transcriptome data with protein-protein and transcriptional regulatory interactions resulted with central (hub) proteins (UBA52, RAC1, CREBBP, AR, RPS11, SMAD3, RPS6, RPL12, RPL15, and UBC), regulatory transcription factors (FOXC1, GATA2, YY1, FOXL1, NFIC, E2F1, USF2, SRF, PPARG, and JUN) and microRNAs (mir-335-5p, mir-26b-5p, mir-93-5p, mir-124-3p, mir-17-5p, mir-16-5p, mir-20a-5p, mir-92a-3p, mir-106b-5p, and mir-192-5p) as key signaling and regulatory molecules associated with transcriptional changes for the AD. Considering these key molecules as potential therapeutic targets and Connectivity Map (CMap) architecture, candidate small molecular agents (such as STOCK1N-35696) were identified as novel potential therapeutics for the AD. This study presents molecular signatures at RNA and protein levels which might be useful in increasing discernment of the molecular mechanisms, and potential drug targets and therapeutics to design effective treatment strategies for the AD.

Research Progress in the Pathogenesis of Alzheimer's Disease

Objective:

Alzheimer's disease (AD) is a kind of chronic degenerative disease of the central nervous system, characteristics of cognitive dysfunction, and behavioral disability. The pathological changes include the formation of senile plaques-containing beta-amyloid (Aβ), neurofibrillary tangles (NFTs), loss of neurons, and synapses. So far, the pathogenesis of AD is still unclear. This study was aimed to review the major pathogenesis of AD-related to the published AD studies in recent 20 years.

Data Sources:

The author retrieved information from the PubMed database up to January 2018, using various search terms and their combinations, including AD, Aβ, NFTs, pathogenesis, and genetic mutation.

Study Selection:

The author included data from peer-reviewed journals printed in English and Chinese on pathophysiological factors in AD. He organized these informations to explain the possible pathogenesis in AD.

Results:

There are many amounts of data supporting the view that AD pathogenesis so far there mainly are Aβ toxicity, tau protein, gene mutation, synaptic damages, intermediate neurons and network abnormalities, changes in mitochondrial function, chemokines, etc., Its nosogenesis may be involved in multiple theories and involved in multiple molecular signaling pathways, including Aβ, tau protein, and synaptic anomaly; mutual relationship between the mechanisms urge jointly neuronal degeneration.

Conclusions:

This review highlights the research advances in the pathogenesis of AD. Future research has needed to fully disclose the association between multiple pathogenesis at the same time to interdict multiple signaling pathways, etc.

Temporal Integrative Analysis of mRNA and microRNAs Expression Profiles and Epigenetic Alterations in Female SAMP8, a Model of Age-Related Cognitive Decline

A growing body of research shows that epigenetic mechanisms are critically involved in normal and pathological aging. The Senescence-Accelerated Mouse Prone 8 (SAMP8) can be considered a useful tool to better understand the dynamics of the global epigenetic landscape during the aging process since its phenotype is not fully explained by genetic factors. Here we investigated dysfunctional age-related transcriptional profiles and epigenetic programming enzymes in the hippocampus of 2- and 9-month-old SAMP8 female mice using the Senescent-Accelerated Resistant 1 (SAMR1) mouse strain as control. SAMP8 mice presented 1,062 genes dysregulated at 2 months of age, and 1,033 genes at 9 months, with 92 genes concurrently dysregulated at both ages compared to age-matched SAMR1. SAMP8 mice showed a significant decrease in global DNA methylation (5-mC) at 2 months while hydroxymethylation (5-hmC) levels were increased in SAMP8 mice at 2 and 9 months of age compared to SAMR1. These changes were accompanied by changes in the expression of several enzymes that regulate 5-mC and methylcytosine oxidation. Acetylated H3 and H4 histone levels were significantly diminished in SAMP8 mice at 2-month-old compared to SAMR1 and altered Histone DeACetylase (HDACs) profiles were detected in both young and old SAMP8 mice. We analyzed 84 different mouse miRNAs known to be altered in neurological diseases or involved in neuronal development. Compared with SAMR1, SAMP8 mice showed 28 and 17 miRNAs differentially expressed at 2 and 9 months of age, respectively; 6 of these miRNAs overlapped at both ages. We used several bioinformatic approaches to integrate our data in mRNA:miRNA regulatory networks and functional predictions for young and aged animals. In sum, our study reveals interplay between epigenetic mechanisms and gene networks that seems to be relevant for the progression toward a pathological aging and provides several potential markers and therapeutic candidates for Alzheimer's Disease (AD) and age-related cognitive impairment.

Photochemical Ligation to Ultrasensitive DNA Detection with Upconverting Nanoparticles

In this work, we explore a photochemical ligation reaction to covalently modify oligonucleotide-conjugated upconverting nanoparticles (UCNPs) in the presence of a specific target DNA sequence. The target sequence acts as a hybridization template, bringing together a biotinylated photoactivatable oligonucleotide probe and the oligonucleotide probe that is attached to UCNPs. The illumination of the UCNPs by NIR light to generate UV emission internally or illuminating the photoactivatable probe directly by an external UV light promotes the photochemical ligation reaction, yielding covalently biotin functionalized UCNPs that can be selectively captured in streptavidin-coated microwells. Following this strategy, we developed a DNA sensor with a limit of detection of 1 × 10^-18 mol per well (20 fM). In addition, we demonstrate the possibility to create UCNP patterns on the surface of solid supports upon NIR illumination that are selectively formed under the presence of the target oligonucleotide.

Herpesviruses and MicroRNAs: New Pathogenesis Factors in Oral Infection and Disease?

The oral cavity incessantly encounters a plethora of microorganisms. Effective and efficient oral innate and adaptive immune responses are incumbent to maintain healthy mucosa. A higher prevalence of Human Herpesviruses (HHV), a family of large enveloped DNA viruses, has been reported in multiple oral inflammatory diseases suggesting their involvement in disease progression. However, the viral components contributing to oral disease remain obscure. MicroRNAs (miRNA) are non-protein coding, single stranded ribonucleic acid (RNA) molecules that post-transcriptionally regulate diverse messenger RNAs. Thus, miRNAs can control large repertoire of biological processes. Changes in miRNA expression are associated with various oral infections and diseases. Cellular miRNAs can act as pro- or anti-viral factors and dysregulation of host miRNA expression occurs during herpesviruses infection. This strongly suggest a critical role of cellular miRNAs in host-herpesvirus interaction. Interestingly, HHV also encode multiple miRNAs (called viral miRNAs) that may play key role in host-pathogen interaction by modulating both host biological pathways and controlling viral life cycle. Recent studies from our laboratory have identified viral miRNAs (v-miRs) in diseased oral tissue biopsies and demonstrate their immunomodulatory roles. This review discusses the association of miRNAs (both host and viral) and herpesviruses in the pathogenesis of oral inflammatory diseases.

miR-103 Promotes Neurite Outgrowth and Suppresses Cells Apoptosis by Targeting Prostaglandin-Endoperoxide Synthase 2 in Cellular Models of Alzheimer's Disease

miR-103 has been reported to be decreased in brain of transgenic mouse model of Alzheimer’s disease (AD) and in cerebrospinal fluid (CSF) of AD patients, while the detailed mechanism of its effect on AD is obscure, thus this study aimed to investigate the effect of miR-103 expression on neurite outgrowth and cells apoptosis as well as its targets in cellular models of AD. Blank mimic (NC1-mimic), miR-103 mimic, blank inhibitor (NC2-mimic) and miR-103 inhibitor plasmids were transferred into PC12 cellular AD model and Cellular AD model of cerebral cortex neurons which were established by Aβ1–42 insult. Rescue experiment was subsequently performed by transferring Prostaglandin-endoperoxide synthase 2 (PTGS2) and miR-103 mimic plasmid. mRNA and protein expressions were detected by qPCR and Western Blot assays. Total neurite outgrowth was detected by microscope, cells apoptosis was determined by Hoechst/PI assay, and apoptotic markers Caspase 3 and p38 expressions were determined by Western Blot assay. In both PC12 and cerebral cortex neurons cellular AD models, miR-103 mimic increases the total neurite outgrowth compared with NC1-mimic, while miR-103 inhibitor decreases the total neurite outgrowth than NC2-inhibitor. The apoptosis rate was decreased in miR-103 mimic group than NC1-mimic group while increased in miR-103 inhibitor group than NC2-inhibitor group. PTGS2, Adisintegrin and metalloproteinase 10 (ADAM10) and neprilysin (NEP) were selected as target genes of miR-103 by bioinformatics analysis. And PTGS2 was found to be conversely regulated by miR-103 expression while ADAM10 and NEP were not affected. After transfection by PTGS2 and miR-103 mimic plasmid in PC12 cellular AD model, the total neurite growth was shortened compared with miR-103 mimic group, and cells apoptosis was enhanced which indicated PTGS2 mimic attenuated the influence of miR-103 mimic on progression of AD. In conclusion, miR-103 promotes total neurite outgrowth and inhibits cells apoptosis by targeting PTGS2 in cellular models of AD.

Classification of miRNA-related sequence variations

miRNA regulome is whole set of regulatory elements that regulate miRNA expression or are under control of miRNAs. Its understanding is vital for comprehension of miRNA functions. Classification of miRNA-related genetic variability is challenging because miRNA interact with different genomic elements and are studied at different omics levels. In the present study, miRNA-associated genetic variability is presented at three levels: miRNA genes and their upstream regulation, miRNA silencing machinery and miRNA targets. Several types of miRNA-associated genetic variations are known, including short and structural polymorphisms and epimutations. Differential expression can also affect miRNA regulome function. Classification of miRNA-associated genetic variability presents a baseline for complementing sequence variant nomenclature, planning of experiments, protocols for multi-omics data integration and development of biomarkers.

Detecting Circulating MicroRNAs as Biomarkers in Alzheimer's Disease

Alzheimer's disease is the most common form of dementia and is characterized by a progressive loss of cognitive functions. As the result of predicted demographic changes over the next decades, Alzheimer's disease is expected to be one of the most pressing medical and social challenges facing our generation. Current treatment strategies remain symptomatic. However, new approaches have shown promise in clinical trials, particularly in patients with only mild or moderate symptoms. Early detection of Alzheimer's disease is therefore of critical importance. Currently available diagnostic approaches (such as protein analysis in cerebrospinal fluid or neuroimaging), however, are expensive and invasive and therefore unsuitable for the screening of a large population. Consequently, Alzheimer's disease is generally diagnosed too late for effective intervention. MicroRNAs-readily measurable in biofluids and resistant to freeze-thaw and pH changes, have shown encouraging diagnostic potential in Alzheimer's disease. Several studies have attempted to correlate changes of specific microRNAs to disease progression using different approaches and profiling platforms including micro-arrays, RNA sequencing, and qPCR-based systems. In the present book chapter, we will describe the different steps involved in how to determine the microRNA profile in plasma samples from patients using the OpenArray platform.

Diagnostic value of blood-derived microRNAs for schizophrenia: results of a meta-analysis and validation

There is an increasing interest in searching biomarkers for schizophrenia (SZ) diagnosis, which overcomes the drawbacks inherent with the subjective diagnostic methods. MicroRNA (miRNA) fingerprints have been explored for disease diagnosis. We performed a meta-analysis to examine miRNA diagnostic value for SZ and further validated the meta-analysis results. Using following terms: schizophrenia/SZ, microRNA/miRNA, diagnosis, sensitivity and specificity, we searched databases restricted to English language and reviewed all articles published from January 1990 to October 2016. All extracted data were statistically analyzed and the results were further validated with peripheral blood mononuclear cells (PBMNCs) isolated from patients and healthy controls using RT-qPCR and receiver operating characteristic (ROC) analysis. A total of 6 studies involving 330 patients and 202 healthy controls were included for meta-analysis. The pooled sensitivity, specificity and diagnostic odds ratio were 0.81 (95% CI: 0.75-0.86), 0.81 (95% CI: 0.72-0.88) and 18 (95% CI: 9-34), respectively; the positive and negative likelihood ratio was 4.3 and 0.24 respectively; the area under the curve in summary ROC was 0.87 (95% CI: 0.84-0.90). Validation revealed that miR-181b-5p, miR-21-5p, miR-195-5p, miR-137, miR-346 and miR-34a-5p in PBMNCs had high diagnostic sensitivity and specificity in the context of schizophrenia. In conclusion, blood-derived miRNAs might be promising biomarkers for SZ diagnosis.

Small RNA sequencing revealed dysregulated piRNAs in Alzheimer's disease and their probable role in pathogenesis

PIWI-interacting RNAs (piRNAs), ∼23-36 nucleotide-long small non-coding RNAs, earlier believed to be germline-specific, have now been identified in somatic cells including neural cells. However, piRNAs have not yet been studied in the human brain (HB) and Alzheimer's disease (AD)-affected brain. In this study, by next-generation small RNA sequencing, 564 and 451 piRNAs were identified in the HB and AD-affected brain respectively. The majority of the neuronal piRNAs have intronic origin wherein primary piRNAs are mostly from the negative strand. piRNAs originating from the coding sequence of mRNAs and tRNAs are highly conserved compared to other genomic contexts. We found 1923 mRNAs significantly down-regulated in AD as the predicted targets of 125 up-regulated piRNAs. The filtering of targets based on our criteria coupled with pathway enrichment analysis of all the predicted targets resulted in five most significant AD-associated pathways enriched with four genes (CYCS, LIN7C, KPNA6, and RAB11A) found to be regulated by four piRNAs. The qRT-PCR study verified the reciprocal expression of piRNAs and their targets. This study provides the first evidence of piRNAs in the HB and AD which will provide the foundation for future studies to unravel the regulatory role of piRNAs in the human brain and associated diseases. The sequencing data have been submitted to the GEO database (Accession no. GSE85075).

Regulatory mechanisms of microRNA expression

MicroRNAs (miRs, miRNAs) are small molecules of 18-22 nucleotides that serve as important regulators of gene expression at the post-transcriptional level. One of the mechanisms through which miRNAs regulate gene expression involves the interaction of their "seed" sequences primarily with 3'-end and more rarely with 5'-end, of mRNA transcribed from target genes. Numerous studies over the past decade have been devoted to quantitative and qualitative assessment of miRNAs expression and have shown remarkable changes in miRNA expression profiles in various diseases. Thus, profiling of miRNA expression can be an important tool for diagnostics and treatment of disease. However, less attention has been paid towards understanding the underlying reasons for changes in miRNA expression, especially in cancer cells. The purpose of this review is to analyze and systematize current data that explains reasons for changes in the expression of miRNAs. The review will cover both transcriptional (changes in gene expression and promoter hypermethylation) and post-transcriptional (changes in miRNA processing) mechanisms of regulation of miRNA expression, as well as effects of endogenous (hormones, cytokines) and exogenous (xenobiotics) compounds on the miRNA expression. The review will summarize the complex multilevel regulation of miRNA expression, in relation to cell type, physiological state of the body and various external factors.