Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort

INTRODUCTION: The objective of this study is to identify circulating microRNAs that distinguish fast-progressing radiographic knee osteoarthritis (OA) in the Osteoarthritis Initiative cohort by applying microRNA-sequencing. METHODS: Participants with Kellgren-Lawrence (KL) grade 0/1 at baseline were included (N = 106). Fast-progressors were defined by an increase to KL 3/4 by 4-year follow-up (N = 20), whereas slow-progressors showed an increase to KL 2/3/4 only at 8-year follow-up (N = 35). Non-progressors remained at KL 0/1 by 8-year follow-up (N = 51). MicroRNA-sequencing was performed on plasma collected at baseline and 4-year follow-up from the same participants. Negative binomial models were fitted to identify differentially expressed (DE) microRNAs. Penalized logistic regression (PLR) analyses were performed to select combinations of DE microRNAs that distinguished fast-progressors. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate predictive ability. RESULTS: DE analyses revealed 48 microRNAs at baseline and 2 microRNAs at 4-year follow-up [false discovery rate (FDR) \u3c 0.05] comparing fast-progressors with both slow-progressors and non-progressors. Among these were hsa-miR-320b, hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e, which were predicted to target gene families, including members of the 14-3-3 gene family, involved in signal transduction. PLR models included miR-320 members as top predictors of fast-progressors and yielded AUC ranging from 82.6 to 91.9, representing good accuracy. CONCLUSION: The miR-320 family is associated with fast-progressing radiographic knee OA and merits further investigation as potential biomarkers and mechanistic drivers of knee OA

肾透明细胞癌差异表达基因的筛选及其核心基因相应miRNA和lncRNA预测分析

【目的】筛选肾透明细胞癌(ccRCC)中差异表达基因并其相关miRNA和lncRNA,寻找可作为ccRCC诊断及治疗的生物标志物。【方法】通过从TCGA数据库和GEO数据库筛选ccRCC差异表达基因并取交集,对差异表达基因进行GO功能分析和KEGG通路富集分析,使用MCODE软件筛选出差异表达基因中的核心基因,并利用mirDIP数据库和STARBASE数据库对核心基因上游的miRNA和lncRNA进行预测。【结果】共筛选出427个差异表达基因,这些差异表达基因在GO功能分析上主要与催化活性、受体活性和细胞黏附分子活性等功能相关,KEGG信号通路富集结果则表明其主要与PPAR、Rap1以及细胞因子受体相互作用等信号通路相关。从这些差异表达基因中筛选出11个核心基因,并预测到134个相应miRNA,接着对5个与ccRCC总体生存率相关的miRNA在STARBASE中共预测到6个相应lncRNA。最后将lncRNA、miRNA、核心基因以及相应信号通路在CYTOSCAPE中构建出一个互作网络。【结论】利用生物信息学技术将TCGA数据库与GEO数据库结合起来,筛选出ccRCC中差异表达基因,并对其中的核心基因进行miRNA与lncRNA预测分析,为后续找到可用于ccRCC临床诊断的靶标与治疗的靶点提供了有力帮助。国家自然科学基金(81570748);;福州总医院杰出青年培养专项(2017Q05

A preliminary integrated analysis of miRNA-mRNA expression profiles reveals a role of miR-146a-3p/TRAF6 in plasma from gestational diabetes mellitus patients

Objectives: To utilize an integrative strategy to construct functional miRNA-mRNA regulatory networks by combining the reverse expression relationships between miRNAs and targets and computational predictions for gestational diabetes mellitus (GDM). Material and methods: A total of three microarray or RNA-seq datasets (GSE98043, GSE19649 and GSE92772) of plasma samples comparing GDM pregnant women and healthy control pregnant women were downloaded from the GEO database. The differentially expressed genes (DEmRNAs) and the differentially expressed miRNAs (DEmiRNAs) was performed. The target genes of DEmiRNAs were identified using two independent and complementary types of information: computational target predictions and expression relationships. An interaction network was constructed to identify hub genes of GDM. Another dataset (GSE92772) was used to externally verify the predictive ability of the hub genes. Results: A total of 264 DEmiRNAs and 1217 DEmRNAs were identified with Hsa-miR-146a-3p ranked first of DEmiRNAs. Functions of GDM-related miRNAs were mainly enriched in the glypican pathway, proteoglycan syndecan-mediated signaling events, and syndecan-1-mediated signaling events. A total of 47 target genes, including TRAF6, were shared between the computational target predictions and DEmRNAs and were identified as target genes of hsa-miR-146a-3p. The interaction network analysis identified TRAF6, CASP8, PTPN6, and CHD3 as hub genes involved in the pathophysiological process of GDM. Next, independent external validation was performed using the GSE19649 dataset. The expression of TRAF6, CASP8 and CHD3 in eight pairs of GDM blood samples was confirmed to be higher than that in healthy pregnant women blood samples with a AUC of 0.813, 0.813, and 0.703, respectively. Conclusions: Our preliminary analysis revealed that miR-146a-3p/TRAF6 might play a central role in the pathogenesis of GDM. Three hub genes, TRAF6, CASP8, and CHD3, were identified and independently externally validated as potential GDM noninvasive serum markers for future biomarkers research

Modulector: a platform-as-a-service for access to microRNA databases

El notable crecimiento del volumen de datos genómicos y la enorme variedad de bases de datos que los almacenan, hacen indispensable disponer de mecanismos eficientes y eficaces de integración. En la actualidad se encuentran disponibles varias herramientas que ofrecen APIs (Interfaz de programación de aplicaciones) que permiten acceder a dicha información, que pueden ser utilizados tanto a través de lenguajes de programación como de navegadores a partir de servicios web. Sin embargo, en dominios específicos de la bioinformática como el caso de los micro ARN -pequeñas moléculas de ARN de gran interés por su capacidad de regular la actividad de otros genes- la mayoría de las soluciones recurren en problemas que dificultan su uso, incluyendo la falta de procesos que simplifiquen la actualización de sus bases de datos a medida que se publica nueva información, tiempos de respuesta inadecuados, dificultad para garantizar la escalabilidad, falta de consistencia en el formato de intercambio de datos, funcionalidad extremadamente limitada, errores por falta de mantenimiento, entre otros problemas frecuentes. En el presente trabajo se presenta Modulector, una solución que integra información de bases de datos genómicas, con bases de datos de micro ARNs (microARNs), para simplificar el acceso a las distintas dimensiones de información de los microARNs de interés (secuencias, fármacos y patologías asociadas, genes regulados, publicaciones científicas), poniendo especial énfasis en resolver las problemáticas técnicas comunes descritas anteriormente. Modulector brinda acceso a través de una API REST (API para la transferencia de estado representacional), garantiza tiempos de respuesta adecuados y escalabilidad, tiene capacidad de ordenamiento, filtro, búsqueda y paginado de resultados. La solución utiliza contenedores, simplificando el despliegue en cualquier servidor, lo que la hace adaptable para la mayoría de los casos de uso donde se quiere utilizar Modulector de manera privada. Toda la información retornada por Modulector se encuentra normalizada en formato JSON, haciéndola eficiente para su manipulación mediante cualquier herramienta de desarrollo. El código fuente de Modulector está disponible en https://github.com/omics-datascience/modulector.The remarkable growth in the volume of genomic data and the enormous variety of databases that store them make it essential to have efficient and effective integration mechanisms. Several tools are currently available that offer APIs (Application Programming Interfaces) that allow access to this information, which can be used both through programming languages and browsers from web services. However, in specific domains of bioinformatics such as the case of MicroRNAs -small RNA molecules of great interest due to their ability to regulate the activity of other genes- most of the solutions fall back on problems that make them difficult to use, including the lack of processes that simplify the updating of their databases as new information is published, inadequate response times, difficulty to guarantee scalability, lack of consistency in the data exchange format, extremely limited functionality, errors due to lack of maintenance, among other frequent problems. This paper presents Modulector, a solution that integrates information from genomic databases with microARN (miRNA) databases to simplify access to the different dimensions of microRNA information of interest (sequences, drugs and associated pathologies, regulated genes, scientific publications), with special emphasis on solving the common technical problems described above. Modulector provides access through a REST API (API Representational State Transfer), guarantees adequate response times and scalability, has sorting, filtering, searching, and pagination capabilities. The solution uses containers, simplifying deployment on any server, which makes it adaptable for most use cases where Modulector is to be used privately. All information returned by Modulector is normalized in JSON format, making it efficient for manipulation by any development tool. Modulector source code is available at https://github.com/omics-datascience/modulector.Secretaría de Ciencia y Técnic

In Silico Approach to Identify the Relationships between COVID-19 and Coronary Artery Disease/Rheumatoid Arthritis

Global public has been threatened by the coronavirus disease 2019 (COVID-19) pandemic which led to nearly 15 million deaths around the world. People with complex and chronic diseases usually have more severe COVID-19 symptoms than the general population. Mounting evidence indicates individuals with coronary artery disease (CAD) and rheumatoid arthritis (RA) have worse COVID-19 outcomes yet the underlying mechanism still needs to be explored. The aim of our study is to reveal in silico evidence for the molecular mechanisms shared by COVID-19, CAD and RA pathogenesis which may aggravate the COVID-19 disease severity. Public datasets (GSE164805 and GSE23561) were downloaded from the Gene Expression Omnibus (GEO) database and analyzed for differential expression analysis (DEG). Identified differential expressed genes (DEGs) were further analyzed to find common DEGs, common pathways, hub genes, transcription factors (TFs) and microRNAs (miRNAs). Our study identified common hub genes, miRNAs, TFs and shared mechanisms in both mild and severe COVID-19-CAD patients and mild and severe COVID-19-RA patients. We also uncovered that mild and severe forms of COVID-19 differ in potential biomarkers, mechanisms, miRNAs and TFs in both CAD and RA patients. Our study is the first study investigating the potential shared mechanisms, biomarkers, TFs and miRNAs between COVID-19 and CAD patients and COVID-19 and RA patients. Our results could shed on light to the patient management strategies with CAD with COVID-19 and patients with RA with COVID-19 based on the severity of the COVID-19 disease. © 2023 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY NC) license (https://creativecommons.org/licenses/by-nc/4.0/)

Hsa-miR-143-3p inhibits Wnt-β-catenin and MAPK signaling in human corneal epithelial stem cells

Our previous study demonstrated hsa-miR-143-3p as one of the highly expressed miRNAs in enriched corneal epithelial stem cells (CESCs). Hence this study aims to elucidate the regulatory role of hsa-miR-143-3p in the maintenance of stemness in CESCs. The target genes of hsa-miR-143-3p were predicted and subjected to pathway analysis to select the targets for functional studies. Primary cultured limbal epithelial cells were transfected with hsa-miR-143-3p mimic, inhibitor or scrambled sequence using Lipofectamine 3000. The transfected cells were analysed for (i) colony forming potential, (ii) expression of stem cell (SC) markers/ transcription factors (ABCG2, NANOG, OCT4, KLF4, ΔNp63), (iii) differentiation marker (Cx43), (iv) predicted five targets of hsa-miR-143-3p (DVL3, MAPK1, MAPK14, KRAS and KAT6A), (v) MAPK signaling regulators and (vi) Wnt-β-catenin signaling regulators by qPCR, immunofluorescence staining and/or Western blotting. High expression of hsa-miR-143-3p increased the colony forming potential (10.04 ± 1.35%, p < 0.001) with the ability to form holoclone-like colonies in comparison to control (3.33 ± 0.71%). The mimic treated cells had increased expression of SC markers but reduced expression of Cx43 and hsa-miR-143-3p targets involved in Wnt-β-catenin and MAPK signaling pathways. The expression of β-catenin, active β-catenin and ERK2 in hsa-miR-143-3p inhibitor transfected cells were higher than the control cells and the localized nuclear expression indicated the activation of Wnt and MAPK signaling. Thus, the probable association of hsa-miR-143-3p in the maintenance of CESCs through inhibition of Wnt and MAPK signaling pathways was thus indicated

Modulector: una plataforma como servicio para el acceso a bases de datos de micro ARNs

The remarkable growth in the volume of genomic data and the enormous variety of databases that store them make it essential to have efficient and effective integration mechanisms. Several tools are currently available that offer APIs (Application Programming Interfaces) that allow access to this information, which can be used both through programming languages and browsers from web services. However, in specific domains of bioinformatics such as the case of MicroRNAs -small RNA molecules of great interest due to their ability to regulate the activity of other genes- most of the solutions fall back on problems that make them difficult to use, including the lack of processes that simplify the updating of their databases as new information is published, inadequate response times, difficulty to guarantee scalability, lack of consistency in the data exchange format, extremely limited functionality, errors due to lack of maintenance, among other frequent problems. This paper presents Modulector, a solution that integrates information from genomic databases with microARN (miRNA) databases to simplify access to the different dimensions of microRNA information of interest (sequences, drugs and associated pathologies, regulated genes, scientific publications), with special emphasis on solving the common technical problems described above. Modulector provides access through a REST API (API Representational State Transfer), guarantees adequate response times and scalability, has sorting, filtering, searching, and pagination capabilities. The solution uses containers, simplifying deployment on any server, which makes it adaptable for most use cases where Modulector is to be used privately. All information returned by Modulector is normalized in JSON format, making it efficient for manipulation by any development tool. Modulector source code is available at https://github.com/omics-datascience/modulector.El notable crecimiento del volumen de datos genómicos y la enorme variedad de bases de datos que los almacenan, hacen indispensable disponer de mecanismos eficientes y eficaces de integración. En la actualidad se encuentran disponibles varias herramientas que ofrecen APIs (Interfaz de programación de aplicaciones) que permiten acceder a dicha información, que pueden ser utilizados tanto a través de lenguajes de programación como de navegadores a partir de servicios web. Sin embargo, en dominios específicos de la bioinformática como el caso de los micro ARN -pequeñas moléculas de ARN de gran interés por su capacidad de regular la actividad de otros genes- la mayoría de las soluciones recurren en problemas que dificultan su uso, incluyendo la falta de procesos que simplifiquen la actualización de sus bases de datos a medida que se publica nueva información, tiempos de respuesta inadecuados, dificultad para garantizar la escalabilidad, falta de consistencia en el formato de intercambio de datos, funcionalidad extremadamente limitada, errores por falta de mantenimiento, entre otros problemas frecuentes. En el presente trabajo se presenta Modulector, una solución que integra información de bases de datos genómicas, con bases de datos de micro ARNs (microARNs), para simplificar el acceso a las distintas dimensiones de información de los microARNs de interés (secuencias, fármacos y patologías asociadas, genes regulados, publicaciones científicas), poniendo especial énfasis en resolver las problemáticas técnicas comunes descritas anteriormente. Modulector brinda acceso a través de una API REST (API para la transferencia de estado representacional), garantiza tiempos de respuesta adecuados y escalabilidad, tiene capacidad de ordenamiento, filtro, búsqueda y paginado de resultados. La solución utiliza contenedores, simplificando el despliegue en cualquier servidor, lo que la hace adaptable para la mayoría de los casos de uso donde se quiere utilizar Modulector de manera privada. Toda la información retornada por Modulector se encuentra normalizada en formato JSON, haciéndola eficiente para su manipulación mediante cualquier herramienta de desarrollo. El código fuente de Modulector está disponible en https://github.com/omics-datascience/modulector

Hsa-miR-150-5p inhibits Wnt-beta-catenin signaling in human corneal epithelial stem cells

Purpose: In our earlier study, we identified hsa-miR-150-5p as a highly expressed miRNA in enriched corneal epithelial stem cells (CESCs). In this study, we aimed to understand the molecular regulatory function of hsa-miR-150-5p in association with the maintenance of stemness in CESCs. Methods: The target mRNAs of hsa-miR-150-5p were predicted and subjected to pathway analysis to identify targets for functional studies. Primary cultured limbal epithelial cells were transfected with hsa-miR-150-5p mimic, inhibitor, or scrambled sequence using Lipofectamine 3000. The transfected cells were analyzed to determine (i) their colony-forming potential; (ii) the expression levels of stem cell (SC) markers/transcription factors (ABCG2, NANOG, OCT4, KLF4, and ΔNp63), the differentiation marker (Cx43), and the hsa-miR-150-5p predicted targets (JARID2, INHBA, AKT3, and CTNNB1) by qPCR; and (iii) the expression levels of ABCG2, p63α, Cx43, JARID2, AKT3, p-AKT3, β-catenin, and active β-catenin by immunofluorescence staining and/or western blotting. Results: The ectopic expression level of hsa-miR-150-5p increased the colony-forming potential (8.29% ± 0.47%, p < 0.001) with the ability to form holoclone-like colonies compared with the control (1.8% ± 0.47%). The mimic-treated cells had higher expression levels of the SC markers but reduced expression levels of Cx43 and the targets of hsa-miR-150-5p that are involved in the Wnt-β-catenin signaling pathway. The expression levels of β-catenin and active β-catenin in the inhibitor-transfected cells were higher than those in the control cells, and the localized nuclear expression indicated the activation of Wnt signaling. Conclusions: Our results indicate a regulatory role for hsa-miR-150-5p in the maintenance of CESCs by inhibiting the Wnt signaling pathway

Sequencing identifies a distinct signature of circulating microRNAs in early radiographic knee osteoarthritis

OBJECTIVE: MicroRNAs act locally and systemically to impact osteoarthritis (OA) pathophysiology, but comprehensive profiling of the circulating miRNome in early vs late stages of OA has yet to be conducted. Sequencing has emerged as the preferred method for microRNA profiling since it offers high sensitivity and specificity. Our objective is to sequence the miRNome in plasma from 91 patients with early [Kellgren-Lawrence (KL) grade 0 or 1 (n = 41)] or late [KL grade 3 or 4 (n = 50)] symptomatic radiographic knee OA to identify unique microRNA signatures in each disease state. DESIGN: MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq 550.Counts were produced for microRNAs captured in miRBase and for novel microRNAs. Statistical, bioinformatics, and computational biology approaches were used to refine and interpret the final list of microRNAs. RESULTS: From 215 differentially expressed microRNAs (FDR \u3c 0.01), 97 microRNAs showed an increase or decrease in expression in ≥85% of samples in the early OA group as compared to the median expression in the late OA group. Increasing this threshold to ≥95%, seven microRNAs were identified: hsa-miR-335-3p, hsa-miR-199a-5p, hsa-miR-671-3p, hsa-miR-1260b, hsa-miR-191-3p, hsa-miR-335-5p, and hsa-miR-543. Four novel microRNAs were present in ≥50% of early OA samples and had 27 predicted gene targets in common with the prioritized set of predicted gene targets from the 97 microRNAs, suggesting common underlying mechanisms. CONCLUSION: Applying sequencing to well-characterized patient cohorts produced unbiased profiling of the circulating miRNome and identified a unique panel of 11 microRNAs in early radiographic knee OA