miEAA 2023: updates, new functional microRNA sets and improved enrichment visualizations

Integration of miRNA expression analysis of purified leukocytes and whole blood reveals blood-borne candidate biomarkers for lung cancer

Changes in leukocyte populations may confound the disease-associated miRNA signals in the blood of cancer patients. We aimed to develop a method to detect differentially expressed miRNAs from lung cancer whole blood samples that are not influenced by variations in leukocyte proportions. The Ref-miREO method identifies differential miRNAs unaffected by changes in leukocyte populations by comparing the within-sample relative expression orderings (REOs) of miRNAs from healthy leukocyte subtypes and those from lung cancer blood samples. Over 77% of the differential miRNAs observed between lung cancer and healthy blood samples overlapped with those between myeloid-derived and lymphoid-derived leukocytes, suggesting the potential impact of changes in leukocyte populations on miRNA profile. Ref-miREO identified 16 differential miRNAs that target 19 lung adenocarcinoma-related genes previously linked to leukocytes. These miRNAs showed enrichment in cancer-related pathways and demonstrated high potential as diagnostic biomarkers, with the LASSO regression models effectively distinguishing between healthy and lung cancer blood or serum samples (all AUC > 0.85). Additionally, 12 of these miRNAs exhibited significant prognostic correlations. The Ref-miREO method offers valuable candidates for circulating biomarker detection in cancer that are not affected by changes in leukocyte populations.

Circulating miRNAs modulating systemic low-grade inflammation and affecting neurodegeneration

OBJECTIVE AND DESIGN

Inflammatory processes are an important part of the etiology of many chronic diseases across various medical domains, including neurodegeneration. Understanding their regulation on the molecular level represents a major challenge. Regulatory microRNAs (miRNAs), have been recognized for their role in post-transcriptionally modulating immune-related pathways serving as biomarkers for numerous diseases.

SUBJECTS AND METHODS

This study aims to investigate the association between 176 plasma-circulating miRNAs and the blood-based immune markers C-reactive protein and fibrinogen within the general population-based SHIP-TREND-0 cohort (N = 801) and assess their impact on neurodegeneration in linear regression and moderation analyses.

RESULTS

We provide strong evidence for miRNA-mediated regulation, particularly in relation to fibrinogen, identifying 48 significant miRNAs with a pronounced over-representation in chronic inflammatory and neurological diseases. Additional moderation analyses explored the influence of the APOE ε4 genotype and brain white matter neurodegeneration on the association between miRNAs and inflammation. Again, significant associations were observed for fibrinogen with special emphasize on hsa-miR-148a-3p, known to impact on neuroinflammation.

CONCLUSIONS

Our study suggests the involvement of several plasma-circulating miRNAs in regulating immunological markers while also being linked to neurodegeneration. The strong interplay between miRNAs and inflammation holds promising potential for clinical application in many immune-related neurodegenerative diseases.

Global microRNA profiling of bone marrow-MSC derived extracellular vesicles identifies miRNAs associated with hematopoietic dysfunction in aplastic anemia

Recently, we have reported that extracellular vesicles (EVs) from the bone marrow mesenchymal stromal cells (BM-MSC) of aplastic anemia (AA) patients inhibit hematopoietic stem and progenitor cell (HSPC) proliferative and colony-forming ability and promote apoptosis. One mechanism by which AA BM-MSC EVs might contribute to these altered HSPC functions is through microRNAs (miRNAs) encapsulated in EVs. However, little is known about the role of BM-MSC EVs derived miRNAs in regulating HSPC functions in AA. Therefore, we performed miRNA profiling of EVs from BM-MSC of AA (n = 6) and normal controls (NC) (n = 6) to identify differentially expressed miRNAs. The Integrated DEseq2 analysis revealed 34 significantly altered mature miRNAs, targeting 235 differentially expressed HSPC genes in AA. Hub gene analysis revealed 10 HSPC genes such as IGF-1R, IGF2R, PAK1, PTPN1, etc., which are targeted by EV miRNAs and had an enrichment of chemokine, MAPK, NK cell-mediated cytotoxicity, Rap1, PI3k-Akt, mTOR signalling pathways which are associated with hematopoietic homeostasis. We further showed that miR-139-5p and its target, IGF-1R (hub-gene), might regulate HSPC proliferation and apoptosis, which may serve as potential therapeutic targets in AA. Overall, the study highlights that AA BM-MSC EV miRNAs could contribute to impaired HSPC functions in AA.

In-depth analysis of transcriptomes in ovarian cortical follicles from children and adults reveals interfollicular heterogeneity

The ovarian cortical reserve of follicles is vital for fertility. Some medical treatments are toxic to follicles, leading to premature ovarian insufficiency. Ovarian tissue cryopreservation is an established method to preserve fertility in adults and even applied in prepuberty despite unproven efficacy. Here, we analyze transcriptomes of 120 cortical follicles from children and adults for detailed comparison. We discover heterogeneity with two main types of follicles in both age groups: one with expected oocyte-granulosa profiles and another with predicted role in signaling. Transcriptional changes during growth to the secondary stage are similar overall in children and adults, but variations related to extracellular matrix, theca cells, and miRNA profiles are found. Notably, cyclophosphamide dose correlates with interferon signaling in child follicles. Additionally, morphology alone is insufficient for follicle categorization suggesting a need for additional markers. Marker genes for early follicle activation are determined. These findings will help refine follicular classification and fertility preservation techniques across critical ages.

Reduced ovarian cholesterol and steroid biosynthesis along with increased inflammation are associated with high DEHP metabolite levels in human ovarian follicular fluids

The plasticizer di(2-ethylhexyl) phthalate (DEHP) is known to have endocrine-disrupting properties mediated by its many metabolites that form upon exposure in biological systems. In a previous study, we reported an inverse association between DEHP metabolites in the human ovarian follicular fluid (FF) and the responsiveness of the follicles to controlled ovarian stimulation during in vitro fertilization (IVF) treatments. Here, we explored this association further through molecular analysis of the ovarian FF samples. Ninety-six IVF patients from Swedish (N = 48) and Estonian (N = 48) infertility clinics were selected from the previous cohort (N = 333) based on the molar sum of DEHP metabolites in their FF samples to arrive at "high" (mean 7.7 ± SD 2.3 nM, N = 48) and "low" (0.8 ± 0.4 nM, N = 48) exposure groups. Extracellular miRNA levels and concentrations of 15 steroid hormones were measured across FF samples. In addition, FF somatic cells, available for the Estonian patients, were used for RNA sequencing. Differential expression (DE) and interactions between miRNA and mRNA networks revealed that the expression levels of genes in the cholesterol biosynthesis and steroidogenesis pathways were significantly decreased in the high compared to the low DEHP group. In addition, the DE miRNAs were predicted to target key enzymes within these pathways (FDR < 0.05). A decreased 17-OH-progesterone to progesterone ratio was observed in the FF of the high DEHP group (p < 0.05). Additionally, the expression levels of genes associated with inflammatory processes were elevated in the FF somatic cells, and a computational cell-type deconvolution analysis suggested an increased immune cell infiltration into the high DEHP follicles (p < 0.05). In conclusion, elevated DEHP levels in FF were associated with a significantly altered follicular milieu within human ovaries, involving a pro-inflammatory environment and reduced cholesterol metabolism, including steroid synthesis. These results contribute to our understanding of the molecular mechanisms of female reprotoxic effects of DEHP.

A Holistic Analysis of Alzheimer's Disease-Associated lncRNA Communities Reveals Enhanced lncRNA-miRNA-RBP Regulatory Triad Formation Within Functionally Segregated Clusters

Recent studies on the regulatory networks implicated in Alzheimer's disease (AD) evince long non-coding RNAs (lncRNAs) as crucial regulatory players, albeit a poor understanding of the mechanism. Analyzing differential gene expression in the RNA-seq data from the post-mortem AD brain hippocampus, we categorized a list of AD-dysregulated lncRNA transcripts into functionally similar communities based on their k-mer profiles. Using machine-learning-based algorithms, their subcellular localizations were mapped. We further explored the functional relevance of each community through AD-dysregulated miRNA, RNA-binding protein (RBP) interactors, and pathway enrichment analyses. Further investigation of the miRNA-lncRNA and RBP-lncRNA networks from each community revealed the top RBPs, miRNAs, and lncRNAs for each cluster. The experimental validation community yielded ELAVL4 and miR-16-5p as the predominant RBP and miRNA, respectively. Five lncRNAs emerged as the top-ranking candidates from the RBP/miRNA-lncRNA networks. Further analyses of these networks revealed the presence of multiple regulatory triads where the RBP-lncRNA interactions could be augmented by the enhanced miRNA-lncRNA interactions. Our results advance the understanding of the mechanism of lncRNA-mediated AD regulation through their interacting partners and demonstrate how these functionally segregated but overlapping regulatory networks can modulate the disease holistically.

Identifying miRNA as biomarker for breast cancer subtyping using association rule

- This paper presents a comprehensive study focused on breast cancer subtyping, utilizing a multifaceted approach that integrates feature selection, machine learning classifiers, and miRNA regulatory networks. The feature selection process begins with the CFS algorithm, followed by the Apriori algorithm for association rule generation, resulting in the identification of significant features tailored to Luminal A, Luminal B, HER-2 enriched, and Basal-like subtypes. The subsequent application of Random Forest (RF) and Support Vector Machine (SVM) classifiers yielded promising results, with the SVM model achieving an overall accuracy of 76.60 % and the RF model demonstrating robust performance at 80.85 %. Detailed accuracy metrics revealed strengths and areas for refinement, emphasizing the potential for optimizing subtype-specific recall. To explore the regulatory landscape in depth, an analysis of selected miRNAs was conducted using MIENTURNET, a tool for visualizing miRNA-target interactions. While FDR analysis raised concerns for HER-2 and Basal-like subtypes, Luminal A and Luminal B subtypes showcased significant miRNA-gene interactions. Functional enrichment analysis for Luminal A highlighted the role of Ovarian steroidogenesis, implicating specific miRNAs such as hsa-let-7c-5p and hsa-miR-125b-5p as potential diagnostic biomarkers and regulators of Luminal A breast cancer. Luminal B analysis uncovered associations with the MAPK signaling pathway, with miRNAs like hsa-miR-203a-3p and hsa-miR-19a-3p exhibiting potential diagnostic and therapeutic significance. In conclusion, this integrative approach combines machine learning techniques with miRNA analysis to provide a holistic understanding of breast cancer subtypes. The identified miRNAs and associated pathways offer insights into potential diagnostic biomarkers and therapeutic targets, contributing to the ongoing efforts to improve breast cancer diagnostics and personalized treatment strategies.

Differential Expression of Circulating miRNAs and Carfilzomib-Related Cardiovascular Adverse Events in Patients with Multiple Myeloma

This study investigates the association between circulating microRNA (miRNA) expression and cardiovascular adverse events (CVAE) in multiple myeloma (MM) patients treated with a carfilzomib (CFZ)-based regimen. A cohort of 60 MM patients from the Prospective Observation of Cardiac Safety with Proteasome Inhibitor (PROTECT) study was analyzed. Among these, 31 patients (51.6%) developed CVAE post-CFZ treatment. The Taqman OpenArray Human microRNA panels were used for miRNA profiling. We identified 13 differentially expressed miRNAs at baseline, with higher expressions of miR-125a-5p, miR-15a-5p, miR-18a-3p, and miR-152-3p and lower expression of miR-140-3p in patients who later developed CVAE compared to those free of CVAE, adjusting for age, gender, race, and higher B-type natriuretic peptide levels. We also identified three miRNAs, including miR-150-5p, that were differentially expressed in patients with and without CVAE post-treatment. Additionally, five miRNAs responded differently to CFZ treatment in CVAE vs. non-CVAE patients, including significantly elevated post-treatment expression of miR-140-3p and lower expressions of miR-598, miR-152, miR-21, and miR-323a in CVAE patients. Pathway enrichment analysis highlighted the involvement of these miRNAs in cardiovascular diseases and vascular processes. These findings suggest that specific miRNAs could serve as predictive biomarkers for CVAE and provide insights into the underlying mechanisms of CFZ-CVAE. Further investigation is warranted before these findings can be applied in clinical settings.

Unraveling the MicroRNA tapestry: exploring the molecular dynamics of locoregional recurrent rectal cancer

Introduction

Colorectal cancer (CRC) ranks as the third most prevalent malignancy globally, with a concerning rise in incidence among young adults. Despite progress in understanding genetic predispositions and lifestyle risk factors, the intricate molecular mechanisms of CRC demand exploration. MicroRNAs (miRNAs) emerge as key regulators of gene expression and their deregulation in tumor cells play pivotal roles in cancer progression.

Methods

NanoString's nCounter technology was utilized to measure the expression of 827 cancer-related miRNAs in tumor tissue and adjacent non-involved normal colon tissue from five patients with locoregional CRC progression. These expression profiles were then compared to those from the primary colon adenocarcinoma (COAD) cohort in The Cancer Genome Atlas (TCGA).

Results and discussion

Intriguingly, 156 miRNAs showed a contrasting dysregulation pattern in reccurent tumor compared to their expression in the TCGA COAD cohort. This observation implies dynamic alterations in miRNA expression patterns throughout disease progression. Our exploratory study contributes to understanding the regulatory landscape of recurrent CRC, emphasizing the role of miRNAs in disease relapse. Notable findings include the prominence of let-7 miRNA family, dysregulation of key target genes, and dynamic changes in miRNA expression patterns during progression. Univariate Cox proportional hazard models highlighted miRNAs associated with adverse outcomes and potential protective factors. The study underscores the need for more extensive investigations into miRNA dynamics during tumor progression and the value of stage specific biomarkers for prognosis.

SingmiR: a single-cell miRNA alignment and analysis tool

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

Constructing diagnostic signature of serum microRNAs using machine learning for early pan-cancer detection

BACKGROUND

Cancer is a major public health concern and the second leading cause of death worldwide. Various studies have reported the use of serum microRNAs (miRNAs) as non-invasive biomarkers for cancer detection. However, large-scale pan-cancer studies based on serum miRNAs have been relatively scarce.

METHODS

An optimized machine learning workflow, combining least absolute shrinkage and selection operator (LASSO) analyses, recursive feature elimination (RFE), and fourteen kinds of machine learning algorithms, was use to screen out candidate miRNAs from 2540 serum miRNAs and constructed a potent diagnostic signature (Cancer-related Serum miRNA Signatures) for pan-cancer detection, based on a serum miRNA expression dataset of 38,223 samples.

RESULT

Cancer-related Serum miRNA Signatures performed well in pan-cancer detection with an area under curve (AUC) of 0.999, 94.51% sensitivity, and 99.49% specificity in the external validation cohort, and represented an acceptable diagnostic performance for identifying early-stage tumors. Furthermore, the ability of multi-classification of tumors by serum miRNAs in pancreatic, colorectal, and biliary tract cancers was lower than that in other cancers, which showed accuracies of 59%, 58.5%, and 28.9%, respectively, indicating that the difference in serum miRNA expression profiles among a small number of tumor subtypes was not as significant as that between cancer samples and non-cancer controls.

CONCLUSION

We have developed a serum miRNA signature using machine learning that may be a cost-effective risk tool for pan-cancer detection. Our findings will benefit not only the predictive diagnosis of cancer but also a preventive and more personalized screening plan.

Small RNA signatures of acute ischemic stroke in L1CAM positive extracellular vesicles

L1CAM-positive extracellular vesicles (L1EV) are an emerging biomarker that may better reflect ongoing neuronal damage than other blood-based biomarkers. The physiological roles and regulation of L1EVs and their small RNA cargoes following stroke is unknown. We sought to characterize L1EV small RNAs following stroke and assess L1EV RNA signatures for diagnosing stroke using weighted gene co-expression network analysis and random forest (RF) machine learning algorithms. Interestingly, small RNA sequencing of plasma L1EVs from patients with stroke and control patients (n = 28) identified micro(mi)RNAs known to be enriched in the brain. Weighted gene co-expression network analysis (WGCNA) revealed small RNA transcript modules correlated to diagnosis, initial NIH stroke scale, and age. L1EV RNA signatures associated with the diagnosis of AIS were derived from WGCNA and RF classification. These small RNA signatures demonstrated a high degree of accuracy in the diagnosis of AIS with an area under the curve (AUC) of the signatures ranging from 0.833 to 0.932. Further work is necessary to understand the role of small RNA L1EV cargoes in the response to brain injury, however, this study supports the utility of L1EV small RNA signatures as a biomarker of stroke.

miRNA signatures underlie chemoresistance in the gemcitabine-resistant pancreatic ductal adenocarcinoma cell line MIA PaCa-2 GR

Introduction: Chemotherapy resistance remains a significant challenge in the treatment of pancreatic adenocarcinoma (PDAC), particularly in relation to gemcitabine (Gem), a commonly used chemotherapeutic agent. MicroRNAs (miRNAs) are known to influence cancer progression and chemoresistance. This study investigates the association between miRNA expression profiles and gemcitabine resistance in PDAC. Methods: The miRNA expression profiles of a gemcitabine-sensitive (GS) PDAC cell line, MIA PaCa-2, and its gemcitabine-resistant (GR) progeny, MIA PaCa-2 GR, were analyzed. miRNA sequencing (miRNA-seq) was employed to identify miRNAs expressed in these cell lines. Differential expression analysis was performed, and Ingenuity Pathway Analysis (IPA) was utilized to elucidate the biological functions of the differentially expressed miRNAs. Results: A total of 1867 miRNAs were detected across both cell lines. Among these, 97 (5.2%) miRNAs showed significant differential expression between the GR and GS cell lines, with 65 (3.5%) miRNAs upregulated and 32 (1.7%) miRNAs downregulated in the GR line. The most notably altered miRNAs were implicated in key biological processes such as cell proliferation, migration, invasion, chemosensitization, alternative splicing, apoptosis, and angiogenesis. A subset of these miRNAs was further analyzed in patient samples to identify potential markers for recurrent tumors. Discussion: The differential miRNA expression profiles identified in this study highlight the complex regulatory roles of miRNAs in gemcitabine resistance in PDAC. These findings suggest potential targets for improving prognosis and tailoring treatment strategies in PDAC patients, particularly those showing resistance to gemcitabine. Future research should focus on validating these miRNAs as biomarkers for resistance and exploring their therapeutic potential in overcoming chemoresistance.

Circulating Hsa-miR499a-5p as markers in dysmobility syndrome patients: a new index for diagnosing dysmobility syndrome based on osteoporosis and predicting fracture risk

BACKGROUND

Dysmobility syndrome based on osteoporosis (ODS) is a disease characterized by low bone mass and low muscle mass. Its features are high fracture and high fall risk. Falls and fractures are the most important factors affecting the quality of life and lifespan of ODS. However, there is no serum marker for the evaluation of ODS patients.Our previous studies have shown that the expression of circulating miRNA is stable and is a good marker for disease diagnosis. Therefore, this study aims to explore potential serum markers of ODS.

METHODS

A total of 78 subjects were included in this study. The data including appendicular skeletal muscle mass index, bone mineral density, bone metabolism markers, and other relevant information were collected for analysis. Real-time quantitative polymerase chain reaction was used to detect 19 miRNAs associated with muscle mass reduction. The correlation of quantitative data was analyzed by Pearson. The receiver operating characteristic curve was used to evaluate the performance of miRNA as a biomarker.

RESULTS

In this study, we found that the muscle mass and strength of patients with ODS are significantly reduced and are negatively correlated with the risk of fracture. The hsa-miR-499a-5p is specifically downregulated in ODS, and is positively correlated with muscle mass and strength, and negatively correlated with the risk of fracture. Compared with muscle mass and strength, hsa-miR-499a-5p has better sensitivity and specificity as a diagnostic marker.

CONCLUSION

hsa-miR-499a-5p is a potential serum biomarker for assessing muscle function and predicting fall or fracture risk in the ODS population.

Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease

Hirschsprung's disease (HSCR) is a rare developmental disorder in which enteric ganglia are missing along a portion of the intestine. HSCR has a complex inheritance, with RET as the major disease-causing gene. However, the pathogenesis of HSCR is still not completely understood. Therefore, we applied a computational approach based on multi-omics network characterization and clustering analysis for HSCR-related gene/miRNA identification and biomarker discovery. Protein-protein interaction (PPI) and miRNA-target interaction (MTI) networks were analyzed by DPClusO and BiClusO, respectively, and finally, the biomarker potential of miRNAs was computationally screened by miRNA-BD. In this study, a total of 55 significant gene-disease modules were identified, allowing us to propose 178 new HSCR candidate genes and two biological pathways. Moreover, we identified 12 key miRNAs with biomarker potential among 137 predicted HSCR-associated miRNAs. Functional analysis of new candidates showed that enrichment terms related to gene ontology (GO) and pathways were associated with HSCR. In conclusion, this approach has allowed us to decipher new clues of the etiopathogenesis of HSCR, although molecular experiments are further needed for clinical validations.

Circulating microRNA miR-425-5p Associated with Brain White Matter Lesions and Inflammatory Processes

White matter lesions (WML) emerge as a consequence of vascular injuries in the brain. While they are commonly observed in aging, associations have been established with neurodegenerative and neurological disorders such as dementia or stroke. Despite substantial research efforts, biological mechanisms are incomplete and biomarkers indicating WMLs are lacking. Utilizing data from the population-based Study of Health in Pomerania (SHIP), our objective was to identify plasma-circulating micro-RNAs (miRNAs) associated with WMLs, thus providing a foundation for a comprehensive biological model and further research. In linear regression models, direct association and moderating factors were analyzed. In 648 individuals, we identified hsa-miR-425-5p as directly associated with WMLs. In subsequent analyses, hsa-miR-425-5p was found to regulate various genes associated with WMLs with particular emphasis on the SH3PXD2A gene. Furthermore, miR-425-5p was found to be involved in immunological processes. In addition, noteworthy miRNAs associated with WMLs were identified, primarily moderated by the factors of sex or smoking status. All identified miRNAs exhibited a strong over-representation in neurodegenerative and neurological diseases. We introduced hsa-miR-425-5p as a promising candidate in WML research probably involved in immunological processes. Mir-425-5p holds the potential as a biomarker of WMLs, shedding light on potential mechanisms and pathways in vascular dementia.

miRNA Expression Profiles in Ovarian Endometriosis and Two Types of Ovarian Cancer-Endometriosis-Associated Ovarian Cancer and High-Grade Ovarian Cancer

Endometriosis-associated ovarian cancer (EOC) consisting of endometrioid cancer and clear-cell ovarian cancer could be promoted by many factors. miRNAs, which are small, non-coding molecules of RNA, are among them. The aim of this study was to detect miRNAs connected with the malignant transformation of endometriosis. FFPE (formalin-fixed, paraffin-embedded) samples of 135 patients operated on for endometriosis and different types of ovarian cancer (EOC and HGSOC-high-grade serous ovarian cancer) were studied. Healthy ovarian tissue was used as a control group. From the expression panel of 754 miRNAs, 7 were chosen for further tests according to their ROC (receiver operating characteristic) curves: miR-1-3p, miR-125b-1-3p, miR-31-3p, miR-200b-3p, miR-502-5p, miR-503-5p and miR-548d-5p. Furthermore, other potentially important clinical data were analysed, which included age, BMI, Ca-125 concentration, miscarriages and deliveries and concomitant diseases such as hypertension, type 2 diabetes and smoking. Among the miRNAs, miR200b-3p had the lowest expression in neoplastic tissues. miR31-3p had the highest expression in women without any lesions in the ovaries. miR-502-5p and miR-548-5p did not differ between the studied groups. The examined miRNA panel generally distinguished significantly normal ovarian tissue and endometriosis, normal ovarian tissue and cancer, and endometriosis and cancer. The malignant transformation of endometriosis is dependent on different factors. miRNA changes are among them. The studied miRNA panel described well the differences between endometriosis and EOC but had no potential to differentiate types of ovarian cancer according to their origin. Therefore, examination of a broader miRNA panel is needed and might prove itself advantageous in clinical practice.

Circulating miRNA profiles in COVID-19 patients and meta-analysis: implications for disease progression and prognosis

We compared circulating miRNA profiles of hospitalized COVID-positive patients (n = 104), 27 with acute respiratory distress syndrome (ARDS) and age- and sex-matched healthy controls (n = 18) to identify miRNA signatures associated with COVID and COVID-induced ARDS. Meta-analysis incorporating data from published studies and our data was performed to identify a set of differentially expressed miRNAs in (1) COVID-positive patients versus healthy controls as well as (2) severe (ARDS+) COVID vs moderate COVID. Gene ontology enrichment analysis of the genes these miRNAs interact with identified terms associated with immune response, such as interferon and interleukin signaling, as well as viral genome activities associated with COVID disease and severity. Additionally, we observed downregulation of a cluster of miRNAs located on chromosome 14 (14q32) among all COVID patients. To predict COVID disease and severity, we developed machine learning models that achieved AUC scores between 0.81-0.93 for predicting disease, and between 0.71-0.81 for predicting severity, even across diverse studies with different sample types (plasma versus serum), collection methods, and library preparations. Our findings provide network and top miRNA feature insights into COVID disease progression and contribute to the development of tools for disease prognosis and management.

Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches

Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasizing their actions, signaling pathways, regulatory biomarkers for diagnosing RD and candidate drugs for treating RD. In this paper we used integrated bioinformatics approaches (such as, gene ontology (GO) and KEGG pathway enrichment analysis, molecular docking, molecular dynamic simulation and network-based molecular interaction analysis). We discovered 73 common DEGs (CDEGs) and ten HubGs (ATAD2B, PPP1CB, FOXO1, AKT3, BCR, PDE4D, ITGB1, PCBP2, CD44 and SMARCA2). Several significant functions and signaling pathways were strongly related to RD. We recognized six transcription factor (TF) proteins (FOXC1, GATA2, FOXL1, YY1, POU2F2 and HINFP) and five microRNAs (hsa-mir-218-5p, hsa-mir-335-5p, hsa-mir-16-5p, hsa-mir-106b-5p and hsa-mir-15b-5p) as the important transcription and post-transcription regulators of RD. Ten HubGs and six major TF proteins were considered drug-specific receptors. Their binding energy analysis study was carried out with the 63 drug agents detected from network analysis. Finally, the five complexes (the PDE4D-benzo[a]pyrene, SMARCA2-benzo[a]pyrene, HINFP-benzo[a]pyrene, CD44-ketotifen and ATAD2B-ponatinib) were selected for RD based on their strong binding affinity scores and stable performance as the most probable repurposable protein-drug complexes. We believe our findings will give readers, wet-lab scientists, and pharmaceuticals a thorough grasp of the biology behind RD.

Serum polychlorinated biphenyl levels and circulating miRNAs in non-obese women with and without polycystic ovary syndrome

Introduction

Polychlorinated biphenyls (PCBs), organic lipophilic pollutants that accumulate through diet and increase with age, have been associated with polycystic ovary syndrome (PCOS) and shown to affect microRNA (miRNA) expression. This work aimed to determine if PCBs were associated with circulating miRNAs and whether there were any correlations with serum PCB/miRNA levels and hormonal changes.

Methods

29 non-obese PCOS and 29 healthy control women, with similar age and body mass index (BMI), had their serum miRNAs measured together with 7 indicator PCBs (PCB28, PCB52, PCB101, PCB118, PCB138, PCB153, PCB180) using high resolution gas chromatography coupled with high resolution mass spectrometry.

Results

In the combined study cohort, four miRNAs (hsa-miR-139-5p, hsa-miR-424-5p, hsa-miR-195-5p, hsa-miR-335-5p) correlated with PCBs, but none correlated with metabolic parameters. hsa-miR-335-5p correlated with FSH. When stratified, 25 miRNAs correlated with PCBs in controls compared to only one (hsa-miR-193a-5p) in PCOS; none of these miRNAs correlated with the metabolic parameters of BMI, insulin resistance, or inflammation (C-reactive protein, CRP). However, of these 25 miRNAs in controls, hsa-miR-26a-5p, hsa-miR-193a-5p, hsa-miR-2110 and hsa-miR-195-5p positively correlated with luteinizing hormone (LH), hsa-miR-99b-5p and hsa-miR-146b-5p correlated with estradiol, hsa-miR-193a-5p correlated with progesterone, hsa-miR-195-5p correlated with follicle stimulating hormone (FSH), and hsa-miR-139-5p and hsa-miR-146b-5p negatively correlated with anti-müllerian hormone (AMH) (all p<0.05). hsa-miR-193a-5p in PCOS cases correlated with estradiol.

Conclusion

In this cohort of women, with no difference in age and BMI, and with similar PCB levels, the miRNAs correlating to PCBs associated with menstrual cycle factors in healthy menstruating controls versus the anovulatory PCOS subjects. The PCB-associated miRNAs did not correlate with non-reproductive hormonal and metabolic parameters. This suggests that PCB effects on miRNAs may result in changes to the hypothalamo-ovarian axis that may thus affect fertility.