Mariana Recamonde-Mendoza

MicroRNA expression profiles and type 1 diabetes mellitus: systematic review and bioinformatic analysis

Growing evidence indicates that microRNAs (miRNAs) have a key role in processes involved in type 1 diabetes mellitus (T1DM) pathogenesis, including immune system functions and beta-cell metabolism and death. Although dysregulated miRNA profiles have been identified in T1DM patients, results are inconclusive; with only few miRNAs being consistently dysregulated among studies. Thus, we performed a systematic review of the literature on the subject, followed by bioinformatic analysis, to point out which miRNAs are dysregulated in T1DM-related tissues and in which pathways they act. PubMed and EMBASE were searched to identify all studies that compared miRNA expressions between T1DM patients and non-diabetic controls. Search was completed in August, 2017. Those miRNAs consistently dysregulated in T1DM-related tissues were submitted to bioinformatic analysis, using six databases of miRNA–target gene interactions to retrieve their putative targets and identify potentially affected pathways under their regulation. Thirty-three studies were included in the systematic review: 19 of them reported miRNA expressions in human samples, 13 in murine models and one in both human and murine samples. Among 278 dysregulated miRNAs reported in these studies, 25.9% were reported in at least 2 studies; however, only 48 of them were analyzed in tissues directly related to T1DM pathogenesis (serum/plasma, pancreas and peripheral blood mononuclear cells (PBMCs)). Regarding circulating miRNAs, 11 were consistently dysregulated in T1DM patients compared to controls: miR-21-5p, miR-24-3p, miR-100-5p, miR-146a-5p, miR-148a-3p, miR-150-5p, miR-181a-5p, miR-210-5p, miR-342-3p, miR-375 and miR-1275. The bioinformatic analysis retrieved a total of 5867 validated and 2979 predicted miRNA–target interactions for human miRNAs. In functional enrichment analysis of miRNA target genes, 77 KEGG terms were enriched for more than one miRNA. These miRNAs are involved in pathways related to immune system function, cell survival, cell proliferation and insulin biosynthesis and secretion. In conclusion, eleven circulating miRNAs seem to be dysregulated in T1DM patients in different studies, being potential circulating biomarkers of this disease.

Social choice in distributed classification tasks

In many situations, a centralized, conventional classification task can not be performed because the data is not available in a central facility. In such cases, we are dealing with distributed data mining problems, in which local models must be individually built and later combined into a consensus, global model. In this paper, we are particularly interested in distributed classification tasks with vertically partitioned data, i.e., when features are distributed among several sources. This restriction implies a challenging scenario given that the development of an accurate model usually requires access to all the features that are relevant for classification. To deal with such a situation, we propose an agent-based classification system, in which the preference orderings of each agent regarding the probability of an instance to belong to the target class are aggregated by means of social choice functions. We employ this method to classify microRNA target genes, an important bioinformatics problem, showing that the predictions derived from the social choice tend to outperform local models in this application. This performance gain is accompanied by other interesting advantages: the aggregation methods herein proposed are extremely simple, do not require transfer of large volumes of data, do not assume an offline training process or parameters setup, and preserve data privacy.

MicroRNAs and diabetic kidney disease: Systematic review and bioinformatic analysis

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. Emerging evidence has suggested a role for miRNAs in the development of diabetic kidney disease (DKD), indicating that miRNAs may represent potential biomarkers of this disease. However, results are still inconclusive. Therefore, we performed a systematic review of the literature on the subject, followed by bioinformatic analysis. PubMed and EMBASE were searched to identify all studies that compared miRNA expressions between patients with DKD and diabetic patients without this complication or healthy subjects. MiRNA expressions were analyzed in kidney biopsies, urine/urinary exosomes or total blood/plasma/serum. MiRNAs consistently dysregulated in DKD patients were submitted to bioinformatic analysis to retrieve their putative target genes and identify potentially affected pathways under their regulation. As result, twenty-seven studies were included in the systematic review. Among 151 dysregulated miRNAs reported in these studies, 6 miRNAs were consistently dysregulated in DKD patients compared to controls: miR-21-5p, miR-29a-3p, miR-126-3p, miR-192-5p, miR-214-3p, and miR-342-3p. Bioinformatic analysis indicated that these 6 miRNAs are involved in pathways related to DKD pathogenesis, such as apoptosis, fibrosis, and extracellular matrix accumulation. In conclusion, six miRNAs seem to be dysregulated in patients with different stages of DKD, constituting potential biomarkers of this disease.

MicroRNA expression profile in plasma from type 1 diabetic patients: Case-control study and bioinformatic analysis

AIMS To investigate a miRNA expression profile in plasma of type 1 diabetes (T1DM) patients and control subjects and analyze the putative pathways involved. METHODS Expressions of 48 miRNAs were analyzed in plasma of 33 T1DM patients and 26 age-and-gender-matched controls using Stem-loop RT-PreAmp PCR and TaqMan Low Density Arrays (Thermo Fisher Scientific). Five dysregulated miRNAs were then chosen for validation in an independent sample of 27 T1DM patients and 14 controls, using RT-qPCR. Bioinformatic analyses were performed to determine in which pathways these miRNAs are involved. RESULTS Nine miRNAs were differentially expressed between recently-diagnosed T1DM patients (<5 years of diagnosis) and controls. No differences were observed between patients with ≥5 years of diagnosis and controls. After validation in an independent sample of T1DM patients, miR-103a-3p, miR-155-5p, miR-200a-3p, and miR-210-3p were confirmed as being upregulated in recently-diagnosed T1DM patients compared with controls or patients with ≥5 years of diagnosis. Moreover, miR-146a-5p was downregulated in recently-diagnosed T1DM patients compared with the other groups. These five miRNAs regulate several genes from innate immune system-, MAPK-, apoptosis-, insulin- and cancer-related pathways. CONCLUSION Five miRNAs are dysregulated in recently-diagnosed T1DM patients and target several genes involved in pathways related to T1DM pathogenesis, thus representing potential T1DM biomarkers.

The role of protein intrinsic disorder in major psychiatric disorders

Although new candidate genes for Autism Spectrum Disorder (ASD), Schizophrenia (SCZ), Attention‐Deficit/Hyperactivity Disorder (ADHD), and Bipolar Disorder (BD) emerged from genome‐wide association studies (GWAS), their underlying molecular mechanisms remain poorly understood. Evidences of the involvement of intrinsically disordered proteins in diseases have grown in the last decade. These proteins lack tridimensional structure under physiological conditions and are involved in important cellular functions such as signaling, recognition and regulation. The aim of the present study was to identify the role and abundance of intrinsically disordered proteins in a set of psychiatric diseases and to test whether diseases are different regarding protein intrinsic disorder. Our hypothesis is that differences across psychiatric illnesses phenotypes and symptoms may arise from differences in intrinsic protein disorder content and properties of each group. A bioinformatics prediction of intrinsic disorder was performed in proteins retrieved based on top findings from GWAS, Copy Number Variation and candidate gene investigations for each disease. This approach revealed that about 80% of studied proteins presented long stretches of disorder. This amount was significantly higher than that observed in general eukaryotic proteins, and those involved in cardiovascular diseases. These results suggest that proteins with intrinsic disorder are a common feature of neurodevelopment and synaptic transmission processes which are potentially involved in the etiology of psychiatric diseases. Moreover, we identified differences between ADHD and ASD when the binary prediction of structure and putative binding sites were compared. These differences may be related to variation in symptom complexity between both diseases.

Circulating miRNAs in diabetic kidney disease: case–control study and in silico analyses

AimsThe aim of this study was to investigate a miRNA expression profile in type 1 diabetes mellitus (T1DM) patients with DKD (cases) or without this complication (controls).MethodsExpression of 48 miRNAs was screened in plasma of 58 T1DM patients (23 controls, 18 with moderate DKD, and 17 with severe DKD) using TaqMan Low Density Array cards (Thermo Fisher Scientific). Then, five of the dysregulated miRNAs were selected for validation in an independent sample of 10 T1DM controls and 19 patients with DKD (10 with moderate DKD and 9 with severe DKD), using RT-qPCR. Bioinformatic analyses were performed to explore the putative target genes and biological pathways regulated by the validated miRNAs.ResultsAmong the 48 miRNAs investigated in the screening analysis, 9 miRNAs were differentially expressed between DKD cases and T1DM controls. Among them, the five most dysregulated miRNAs were chosen for validation in an independent sample. In the validation sample, miR-21-3p and miR-378-3p were confirmed to be upregulated in patients with severe DKD, while miR-16-5p and miR-29a-3p were downregulated in this group compared to T1DM controls and patients with moderate DKD. MiR-503-3p expression was not validated. Bioinformatic analyses indicate that the four validated miRNAs regulate genes from PI3K/Akt, fluid shear stress and atherosclerosis, AGE-RAGE, TGF-β1, and relaxin signaling pathways.ConclusionsOur study found four miRNAs differentially expressed in patients with severe DKD, providing significant information about the biological pathways in which they are involved.