Circulating microRNAs as Potential Diagnostic Biomarkers for Poor Sleep Quality

Metabolic profiles of saliva in male mouse models of chronic sleep disorders induced by psychophysiological stress

Disordered sleep is a global social problem and an established significant risk factor for psychological and metabolic diseases. We profiled non-targeted metabolites in saliva from mouse models of chronic sleep disorder (CSD). We identified 288 and 55 metabolites using CE-FTMS and LC-TOFMS, respectively, among which concentrations of 58 (CE-FTMS) and three (LC-TOFMS) were significantly changed by CSD. Pathway analysis revealed that CSD significantly suppressed glycine, serine and threonine metabolism. Arginine and proline metabolic pathways were among those that were both upregulated and downregulated. Pathways of alanine, aspartate and glutamate metabolism, genetic information processing, and the TCA cycle tended to be downregulated, whereas histidine metabolism tended to be upregulated in mice with CSD. Pyruvate, lactate, malate, succinate and the glycemic amino acids alanine, glycine, methionine, proline, and threonine were significantly decreased, whereas 3-hydroxybutyric and 2-hydroxybutyric acids associated with ketosis were significantly increased, suggesting abnormal glucose metabolism in mice with CSD. Increases in the metabolites histamine and kynurenic acid that are associated with the central nervous system- and decreased glycine, might be associated with sleep dysregulation and impaired cognitive dysfunction in mice with CSD. Our findings suggested that profiling salivary metabolites could be a useful strategy for diagnosing CSD.

Identification of extremely GC-rich micro RNAs for RT-qPCR data normalization in human plasma

We aimed at extending the repertoire of high-quality miRNA normalizers for reverse transcription-quantitative PCR (RT-qPCR) of human plasma with special emphasis on the extremely guanine-cytosine-rich portion of the miRNome. For high-throughput selection of stable candidates, microarray technology was preferred over small-RNA sequencing (sRNA-seq) since the latter underrepresented miRNAs with a guanine-cytosine (GC) content of at least 75% (p = 0.0002, n = 2). miRNA abundances measured on the microarray were ranked for consistency and uniformity using nine normalization approaches. The eleven most stable sequences included miRNAs of moderate, but also extreme GC content (45%-65%: miR-320d, miR-425-5p, miR-185-5p, miR-486-5p; 80%-95%: miR-1915-3p, miR-3656-5p, miR-3665-5p, miR-3960-5p, miR-4488-5p, miR-4497 and miR-4787-5p). In contrast, the seven extremely GC-rich miRNAs were not found in the two plasma miRNomes screened by sRNA-seq. Stem-loop RT-qPCR was employed for stability verification in 32 plasma samples of healthy male Caucasians (age range: 18-55 years). In general, inter-individual variance of miRNA abundance was low or very low as indicated by coefficient of variation (CV) values of 0.6%-8.2%. miR-3665 and miR-1915-3p outperformed in this analysis (CVs: 0.6 and 2.4%, respectively). The eight most stable sequences included four extremely GC-rich miRNAs (miR-1915-3p, miR-3665, miR-4787-5p and miR-4497). The best-performing duo normalization factor (NF) for the condition of human plasma, miR-320d and miR-4787-5p, also included a GC-extreme miRNA. In summary, the identification of extremely guanine-cytosine-rich plasma normalizers will help to increase accuracy of PCR-based miRNA quantification, thus raise the potential that miRNAs become markers for psychological stress reactions or early and precise diagnosis of clinical phenotypes. The novel miRNAs might also be useful for orthologous contexts considering their conservation in related animal genomes.

Identification of salivary microRNA profiles in male mouse model of chronic sleep disorder

Chronic sleep disorders (CSD) comprise a potential risk factor for metabolic and cardiovascular diseases, obesity and stroke. Thus, the identification of biomarkers for CSD is an important step in the early prevention of metabolic dysfunctions induced by sleep dysfunction. Diagnostic saliva samples can be easily and noninvasively collected. Thus, we aimed to identify whole microRNA (miRNA) profiles of saliva in control and psychophysiologically stressed CSD mouse models and compare them at Zeitgeber time (ZT) 0 (lights on) and ZT12 (lights off). The findings of two-way ANOVA revealed that the expression of 342 and 109 salivary miRNAs was affected by CSD and the time of day, respectively. Interactions were found in 122 miRNAs among which, we identified 197 (ZT0) and 62 (ZT12) upregulated, and 40 (ZT0) and seven (ZT12) downregulated miRNAs in CSD mice. We showed that miR-30c-5p, which is elevated in the plasma of patients with hypersomnia, was upregulated in the saliva of CSD mice collected at ZT0. The miRNAs, miR-10a-5p, miR-146b-5p, miR-150-5p, and miR-25-3p are upregulated in the serum of humans with poor sleep quality, and these were also upregulated in the saliva of CSD mice collected at ZT0. The miRNAs miR-30c, miR146b-5p, miR150, and miR-25-5p are associated with cardiovascular diseases, and we found that plasma concentrations of brain natriuretic peptides were significantly increased in CSD mice. The present findings showed that salivary miRNA profiles could serve as useful biomarkers for predicting CSD.

Role and Dysregulation of miRNA in Patients with Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative synucleinopathy that has a not yet fully understood molecular pathomechanism behind it. The role of risk genes regulated by small non-coding RNAs, or microRNAs (miRNAs), has also been highlighted in PD, where they may influence disease progression and comorbidities. In this case-control study, we analyzed miRNAs on peripheral blood mononuclear cells by means of RNA-seq in 30 participants, with the aim of identifying miRNAs differentially expressed in PD compared to age-matched healthy controls. Additionally, we investigated the pathways influenced by differentially expressed miRNAs and assessed whether a specific pathway could potentially be associated with PD susceptibility (enrichment analyses performed using the Ingenuity Pathway Analysis tools). Overall, considering that the upregulation of miRNAs might be related with the downregulation of their messenger RNA targets, and vice versa, we found several putative targets of dysregulated miRNAs (i.e., upregulated: hsa-miR-1275, hsa-miR-23a-5p, hsa-miR-432-5p, hsa-miR-4433b-3p, and hsa-miR-4443; downregulated: hsa-miR-142-5p, hsa-miR-143-3p, hsa-miR-374a-3p, hsa-miR-542-3p, and hsa-miR-99a-5p). An inverse connection between cancer and neurodegeneration, called "inverse comorbidity", has also been noted, showing that some genes or miRNAs may be expressed oppositely in neurodegenerative disorders and in some cancers. Therefore, it may be reasonable to consider these miRNAs as potential diagnostic markers and outcome measures.