Analysis of the Level of Adiponectin and Selected Cytokines in Patients with Knee Osteoarthritis.

Background and Objectives: Knee osteoarthritis (KOA) is a degenerative disease that is continuously targeting people of different ages, but especially the elderly population, the number of which tends to increase continuously at the global level. Apart from age, excess weight can influence the evolution of the disease, with obesity being associated with a weak inflammation stage and an imbalance between pro-inflammatory and anti-inflammatory cytokines. The present work aimed to analyze specific biomarkers, namely ACRP-30, IL-10, TNF-α, and IL-6, in knee synovial fluid, and correlate them with KOA patients' clinical data, radiographic changes, and functional and pain scores. Materials and Methods: 24 subjects with KOA and over 50 years of age participate in the present study. Synovial fluid was harvested using ultrasound guidance from the target knees of the enrolled KOA patients, and the levels of ACRP-30, IL-10, TNF-α, and IL-6 were measured using enzyme-linked immunosorbent assays (ELISA). All patients underwent a supine X-ray at the target knee and were classified using Kellgren-Lawrence (K-L) grading. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC) was used to assess self-reported physical function, pain, and stiffness. Results: The obtained results highlighted a significant correlation between age and adiponectin level (p = 0.0451, r = -0.412). Also, the IL-10 values are lower in cases where the intensity of the pain is more pronounced (p = 0.0405, r = -0.421). In addition, analyzing the data by gender, it was observed that in the case of males, stiffness is more related to age (p = 0.0079, r = 0.7993), compared to women (p = 0.0203, r = 0.6223). In the case of women, the progression of the disease tends to increase more intensively the WOMAC score's total values (p = 0.00031, r = 0.8342), compared with men (p = 0.0289, r = 7013). Regarding interleukins and BMI, significant correlations were observed only in the case of men. Conclusions: A significant correlation between age and adiponectin, and adiponectin and IL-6, suggests that advanced age may contribute to adiponectin reduction. Comparing men with women, it was observed that men's age is more related to rigidity, and IL-6 and IL-10 are directly correlated to BMI; in addition, women seem to be more sensitive to pain and stiffness.

Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling.

Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics.

Diagnostic Value of microRNA-375 as Future Biomarker for Prostate Cancer Detection: A Meta-Analysis.

Background and Objectives: Responding to the need for additional biomarkers for the diagnosis of prostate cancer (PCa), mounting studies show that microRNAs (miRNAs/miRs) possess great potential as future promising diagnostic tools. However, the usefulness of these miRNAs is still highly debated, as the degree of inconsistency between study designs and results is still elevated. Herein, we present a meta-analysis evaluating the diagnostic value and accuracy of circulating miR-375, as it is one of the most studied types of miRs in PCa. Materials and Methods: The diagnostic accuracy of miR-375 was evaluated using the QUADAS-2 tool, analyzing different statistical parameters. The seven studies (from six articles) that matched our selection included 422 PCa patients and 212 controls (70 healthy volunteers + 142 with benign prostate diseases). Results and Conclusion: We obtained a p-value of 0.76 for sensitivity, 0.83 for specificity, 16 for DOR, 4.6 for LR+, 0.29 for LR-, and 0.87 for AUC (95% CI 0.83-0.89). Our results confirm that miRNA-375 has high diagnostic potential for PCa, suggesting its usefulness as a powerful biomarker. More comprehensive studies are warranted to better assess its true value as a diagnostic biomarker for this urologic disease.

Long Non-Coding RNA Expression in Laser Micro-Dissected Luminal A and Triple Negative Breast Cancer Tissue Samples-A Pilot Study.

Background and Objectives: Breast cancer (BC) remains one of the major causes of cancer death in women worldwide. The difficulties in assessing the deep molecular mechanisms involved in this pathology arise from its high complexity and diverse tissue subtypes. Long non-coding RNAs (lncRNAs) were shown to have great tissue specificity, being differentially expressed within the BC tissue subtypes. Materials and Methods: Herein, we performed lncRNA profiling by PCR array in triple negative breast cancer (TNBC) and luminal A tissue samples from 18 BC patients (nine TNBC and nine luminal A), followed by individual validation in BC tissue and cell lines. Tissue samples were previously archived in formalin-fixed paraffin-embedded (FFPE) samples, and the areas of interest were dissected using laser capture microdissection (LCM) technology. Results: Two lncRNAs (OTX2-AS1 and SOX2OT) were differentially expressed in the profiling analysis (fold change of 205.22 and 0.02, respectively, p < 0.05 in both cases); however, they did not reach statistical significance in the individual validation measurement (p > 0.05) when analyzed with specific individual assays. In addition, GAS5 and NEAT1 lncRNAs were individually assessed as they were previously described in the literature as being associated with BC. GAS5 was significantly downregulated in both TNBC tissues and cell lines compared to luminal A samples, while NEAT1 was significantly downregulated only in TNBC cells vs. luminal A. Conclusions: Therefore, we identified GAS5 lncRNA as having a differential expression in TNBC tissues and cells compared to luminal A, with possible implications in the molecular mechanisms of the TNBC subtype. This proof of principle study also suggests that LCM could be a useful technique for limiting the sample heterogeneity for lncRNA gene expression analysis in BC FFPE tissues. Future studies of larger cohort sizes are needed in order to assess the biomarker potential of lncRNA GAS5 in BC.

Biomarker Potential of Plasma MicroRNA-150-5p in Prostate Cancer.

Background and Objectives: Over decades, prostate cancer (PCa) has become one of the leading causes of cancer mortality in men. Extensive evidence exists that microRNAs (miRNAs or miRs) are key players in PCa and a new class of non-invasive cancer biomarkers. Materials and Methods: We performed miRNA profiling in plasma and tissues of PCa patients and attempted the validation of candidate individual miRs as biomarkers. Results: The comparison of tissue and plasma profiling results revealed five commonly dysregulated miRs, namely, miR-130a-3p, miR-145-5p, miR-148a-3p, miR-150-5p, and miR-365a-3p, of which only three show concordant changes-miR-130a-3p and miR-150-5p were downregulated and miR-148a-3p was upregulated in both tissue and plasma samples, respectively. MiR-150-5p was validated as significantly downregulated in both plasma and tissue cancer samples, with a fold change of -2.697 (p < 0.001), and -1.693 (p = 0.035), respectively. ROC analysis showed an area under the curve (AUC) of 0.817 (95% CI: 0.680-0.995) for plasma samples and 0.809 (95% CI: 0.616-1.001) for tissue samples. Conclusions: We provide data indicating that miR-150-5p plasma variations in PCa patients are associated with concordant changes in prostate cancer tissues; however, given the heterogeneous nature of previous findings of miR-150-5p expression in PCa cells, additional future studies of a larger sample size are warranted in order to confirm the biomarker potential and role of miRNA-150-5p in PCa biology.

HB-EGF Plasmatic Level Contributes to the Development of Early Risk Prediction Nomogram for Severe COVID-19 Cases.

(1) Background: Heparin-Binding Epidermal Growth Factor-like Growth Factor (HB-EGF) is involved in wound healing, cardiac hypertrophy, and heart development processes. Recently, circulant HB-EGF was reported upregulated in severely hospitalized COVID-19 patients. However, the clinical correlations of HB-EGF plasma levels with COVID-19 patients' characteristics have not been defined yet. In this study, we assessed the plasma HB-EGF correlations with the clinical and paraclinical patients' data, evaluated its predictive clinical value, and built a risk prediction model for severe COVID-19 cases based on the resulting significant prognostic markers. (2) Methods: Our retrospective study enrolled 75 COVID-19 patients and 17 control cases from May 2020 to September 2020. We quantified plasma HB-EGF levels using the sandwich ELISA technique. Correlations between HB-EGF plasma levels with clinical and paraclinical patients' data were calculated using two-tailed Spearman and Point-Biserial tests. Significantly upregulated parameters for severe COVID-19 cases were identified and selected to build a multivariate logistic regression prediction model. The clinical significance of the prediction model was assessed by risk prediction nomogram and decision curve analyses. (3) Results: HB-EGF plasma levels were significantly higher in the severe COVID-19 subgroup compared to the controls (p = 0.004) and moderate cases (p = 0.037). In the severe COVID-19 group, HB-EGF correlated with age (p = 0.028), pulse (p = 0.016), dyspnea (p = 0.014) and prothrombin time (PT) (p = 0.04). The multivariate risk prediction model built on seven identified risk parameters (age p = 0.043, HB-EGF p = 0.0374, Fibrinogen p = 0.009, PT p = 0.008, Creatinine p = 0.026, D-Dimers p = 0.024 and delta miR-195 p < 0.0001) identifies severe COVID-19 with AUC = 0.9556 (p < 0.0001). The decision curve analysis revealed that the nomogram model is clinically relevant throughout a wide threshold probability range. (4) Conclusions: Upregulated HB-EGF plasma levels might serve as a prognostic factor for severe COVID-19 and help build a reliable risk prediction nomogram that improves the identification of high-risk patients at an early stage of COVID-19.

Lipidomic Signature of Plasma and Synovial Fluid in Patients with Osteoarthritis: Putative Biomarkers Determined by UHPLC-QTOF-ESI+MS.

BACKGROUND: Osteoarthritis (OA) is a prevalent joint condition causing pain and disability, especially in the elderly. Currently, OA diagnosis relies on clinical data and imaging, but recent interest in metabolomics suggests that early biochemical changes in biofluids, particularly synovial fluid (SF), could enable an earlier diagnosis and understanding of the disease. METHODS: In this regard, we conducted a lipidomics study in 33 plasma and SF samples from OA patients and 20 OA-free controls to assess the diagnostic value of various lipid metabolites, using UHPLC-QTOF-ESI+MS. RESULTS: In plasma samples, 25 metabolites had area-under-the-curve (AUC) values higher than 0.9, suggesting a very good diagnostic potential for phosphatidic acid PA (16:0/16:0), PA (34:0), phosphatidylethanolamine PE (34:2), glucosylceramide, phosphatidylcholine PC (32:1), and other metabolites while in SF 20, metabolites had AUC values higher than 0.8, the vast majority belonging to lipid metabolism as well. CONCLUSIONS: Although the results align with the previous literature, larger cohort studies are necessary to confirm the diagnostic value of the lipid metabolites.

Involvement of the Expression of G Protein-Coupled Receptors in Schizophrenia.

The expression of GPCRs has been associated with schizophrenia, and their expression may induce morphological changes in brain regions responsible for schizophrenia and disease-specific behavioral changes. The articles included in this review were selected using keywords and databases of scientific research websites. The expressions of GPRs have different involvements in schizophrenia, some increase the risk while others provide protection, and they may also be potential targets for new treatments. Proper evaluation of these factors is essential to have a better therapeutic response with a lower rate of chronicity and thus improve the long-term prognosis.

Plasma miR-195-5p predicts the severity of Covid-19 in hospitalized patients.

Predicting the clinical course of Covid-19 is a challenging task, given the multi-systemic character of the disease and the paucity of minimally invasive biomarkers of disease severity. Here, we evaluated the early (first two days post-admission) level of circulating hsa-miR-195-5p (miR-195, a known responder to viral infections and SARS-CoV-2 interactor) in Covid-19 patients and assessed its potential as a biomarker of disease severity. We show that plasma miR-195 correlates with several clinical and paraclinical parameters, and is an excellent discriminator between the severe and mild forms of the disease. Our Gene Ontology analysis of miR-195 targets differentially expressed in Covid-19 indicates a strong impact on cardiac mitochondria homeostasis, suggesting a possible role in long Covid and chronic fatigue syndrome (CFS) syndromes.

Adiponectin in Osteoarthritis: Pathophysiology, Relationship with Obesity and Presumptive Diagnostic Biomarker Potential.

Osteoarthritis (OA) is a multifactorial, irreversible age- and obesity-induced joint degenerative disease, with an increasing incidence in developed countries. With a pathophysiology and etiology that are currently under-investigated, the only available disease-modifying treatment relies solely on total joint arthroplasty, which entails major economic burdens. Recently, the research focus has shifted towards the evaluation of metabolically active mediators secreted by the adipose tissue, which could be potential targets for a better understanding of the mechanisms involved in OA onset and development. Of note, adiponectin has drawn a great deal of attention, since it is the most abundant type of circulating adipokine and has been highly associated with OA occurrence. Thus far, studies have been controversial in establishing whether adiponectin possesses a destructive or protective role in OA development. Therefore, we critically and systematically reviewed, herein, the roles of adiponectin in the pathophysiology of OA, the link between obesity, adiponectin expression and the progression of OA, as well as its potential role as a future biomarker for a more optimized and reliable diagnosis of this degenerative disorder.

Osteoarthritis and microRNAs: Do They Provide Novel Insights into the Pathophysiology of This Degenerative Disorder?

Osteoarthritis (OA) is one of the most prevalent degenerative joint diseases in older adults and a leading cause of disability. Recent research studies have evidenced the importance of mi-croRNAs (miRs) in the pathogenesis of OA. In the present review, we focused on current literature findings on dysregulated miRs involved in the pathophysiology of OA. From the 35 case-control studies including OA patients compared to healthy controls, a total of 54 human miRs were identified to be dysregulated in OA. In total, 41 miRs were involved in the pathophysiological processes of OA, including apoptosis, inflammation, and proliferation, having either a protective or a progressive role in OA. The discovery of altered miR levels in OA patients compared to healthy controls determines a better understanding of the molecular mechanisms involved in the pathophysiology of OA and could open novel horizons in the field of orthopedics.

Mannose-binding lectin 2 gene polymorphisms and predisposition to allergic bronchial asthma in a western Romanian children population: an observational study.

OBJECTIVES: To analyse: (1) the associations between different mannose-binding lectin 2 (MBL2) genotypes and susceptibility to bronchial asthma (BA) in Romanian children; and (2) the correlations between several patient sociodemographic variables and MBL2 polymorphisms. METHODS: This prospective observational case-control study included paediatric patients with symptomatic BA and healthy controls. Participants were genotyped for two MBL2 single-nucleotide polymorphisms (SNPs): exon 1 codon 54 A/B variant rs1800450, and -550 promoter H/L variant rs11003125 (GenBank accession). Associations between MBL2 genotypes and susceptibility to BA were determined by calculated odds ratios, and Kendall Tau's correlations were used to investigate the associations between sociodemographic variables and SNPs. RESULTS: Among 59 patients with BA and 65 healthy controls, associations between MBL2 polymorphisms and susceptibility to BA were not found to be statistically significant. Statistically significant weak positive correlations were found between age at diagnosis and A/B genotype, and between the smoking status of biologically male and female parents. A statistically significant weak inverse association was found between male parent smoking status and family history of BA. CONCLUSION: These results may help guide future research into paediatric BA in Romania and Eastern Europe. Due to study limitations, the results require validation in future large-scale studies.

Metabolomic Analysis of Plasma from Breast Cancer Patients Using Ultra-High-Performance Liquid Chromatography Coupled with Mass Spectrometry: An Untargeted Study.

Breast cancer (BC) is one of the leading causes of cancer mortality in women worldwide, and therefore, novel biomarkers for early disease detection are critically needed. We performed herein an untargeted plasma metabolomic profiling of 55 BC patients and 55 healthy controls (HC) using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS). Pre-processed data revealed 2494 ions in total. Data matrices' paired t-tests revealed 792 ions (both positive and negative) which presented statistically significant changes (FDR < 0.05) in intensity levels between cases versus controls. Metabolites identified with putative names via MetaboQuest using MS/MS and mass-based approaches included amino acid esters (i.e., N-stearoyl tryptophan, L-arginine ethyl ester), dipeptides (ile-ser, met-his), nitrogenous bases (i.e., uracil derivatives), lipid metabolism-derived molecules (caproleic acid), and exogenous compounds from plants, drugs, or dietary supplements. LASSO regression selected 16 metabolites after several variables (TNM Stage, Grade, smoking status, menopausal status, and race) were adjusted. A predictive conditional logistic regression model on the 16 LASSO selected ions provided a high diagnostic performance with an area-under-the-curve (AUC) value of 0.9729 (95% CI 0.96−0.98) on all 55 samples. This study proves that BC possesses a specific metabolic signature that could be exploited as a novel metabolomics-based approach for BC detection and characterization. Future studies of large-scale cohorts are needed to validate these findings.

Body Mass Index Influence for the Personalization of the Monoclonal Antibodies Therapy for Psoriasis.

Psoriasis is a chronic inflammatory, autoimmune-mediated disease that affects millions of individuals worldwide. Advances in treatment with biological agents represented by monoclonal antibodies, such as TNF-α inhibitors (TNFI), IL-17A and IL-12/23 antagonists have not only benefited from outstanding clinical efficacy with lower side effects compared to conventional systemic therapy, but also raised the standards towards therapeutic success, fact reflected in the greater Psoriasis Area and Severity Index (PASI) response rates. However, due to their relatively recent introduction in clinical practice, and despite their proven superior efficacy, further research is needed for monitoring the eventual changes in treatment-induced parameters, especially of metabolic origin. In this respect, initial reports stress on one particular comorbidity associated with psoriasis-obesity-which seems to be not only a risk and result of the disease, but also an adverse effect of long-term therapy with some biologics. The consequent drug-induced increase in body mass index (BMI) of patients suffering from psoriasis undergoing biological treatment appears to contribute to the progression of the disease, promote drug discontinuation and reduce overall clinical efficacy of monoclonal antibodies. Therefore, we review herein the impact of body weight (BMI) increase on the biological treatment of psoriasis, to further investigate on its relationship with the disease and aid on the management of treatment schemes that take into account individual characteristics of patients, such as body mass, for a more efficient and personalized therapy approach.

Uncovering the Roles of MicroRNAs in Major Depressive Disorder: From Candidate Diagnostic Biomarkers to Treatment Response Indicators.

Major depressive disorder (MDD) is a recurrent debilitating illness that represents a major health burden due to its increasing worldwide prevalence, unclear pathological mechanism, nonresponsive treatment, and lack of reliable and specific diagnostic biomarkers. Recently, microRNA species (miRs) have gained particular interest because they have the ability to post-transcriptionally regulate gene expression by modulating mRNA stability and translation in a cohesive fashion. By regulating entire genetic circuitries, miRs have been shown to have dysregulated expression levels in blood samples from MDD patients, when compared to healthy subjects. In addition, antidepressant treatment (AD) also appears to alter the expression pattern of several miRs. Therefore, we critically and systematically reviewed herein the studies assessing the potential biomarker role of several candidate miRs for MDD, as well as treatment response monitoring indicators, in order to enrich the current knowledge and facilitate possible diagnostic biomarker development for MDD, which could aid in reducing both patients' burden and open novel avenues toward a better understanding of MDD neurobiology.

Distribution of microRNAs associated with major depressive disorder among blood compartments.

OBJECTIVE: Major depressive disorder (MDD) is a recurrent disorder with an increasing incidence. Alterations in key signaling pathways of the nervous system, such as the Wnt and MAPK pathways, mediated through microRNAs (miRNAs) provide crucial information regarding the etiopathology of MDD. We aimed to analyze whether the heterogeneity of literature findings regarding differential expression of miRNAs in the blood could arise from their different distributions among blood compartments. METHODS: We performed a pilot study analyzing the differential expression of miR-26a, miR-494, miR-30c, miR-93, and miR-101 and investigated their levels in white blood cells, total plasma (TP), exosomes from plasma, and exosome depleted plasma (EDP) in patients with MDD before and after antidepressant treatment with escitalopram and in healthy controls. RESULTS: MiR-494 was more abundant in EDP, and miR-26a and miR-30c were predominantly more abundant in TP relative to other blood compartments. Moreover, miR-30c, miR-101, and miR-26a, were significantly downregulated in TP of patients with MDD compared with controls. After antidepressant treatment, only miR-494 was significantly differently expressed in EDP. CONCLUSIONS: This proof-of-principle study suggests that identifying the miRNA abundance in different blood compartments is crucial for biomarker development and could enrich the current knowledge regarding MDD pathophysiology.

Untargeted Plasma Metabolomic Profiling in Patients with Major Depressive Disorder Using Ultra-High Performance Liquid Chromatography Coupled with Mass Spectrometry.

Major depressive disorder (MDD) is a neuropsychiatric illness with an increasing incidence and a shortfall of efficient diagnostic tools. Interview-based diagnostic tools and clinical examination often lead to misdiagnosis and inefficient systematic treatment selection. Diagnostic and treatment monitoring biomarkers are warranted for MDD. Thus, the emerging field of metabolomics is a promising tool capable of portraying the metabolic repertoire of biomolecules from biological samples in a minimally invasive fashion. Herein, we report an untargeted metabolomic profiling performed in plasma samples of 11 MDD patients, at baseline (MDD1) and at 12 weeks following antidepressant therapy with escitalopram (MDD2), and in 11 healthy controls (C), using ultra-high performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-(ESI+)-MS). We found two putative metabolites ((phosphatidylserine PS (16:0/16:1) and phosphatidic acid PA (18:1/18:0)) as having statistically significant increased levels in plasma samples of MDD1 patients compared to healthy subjects. ROC analysis revealed an AUC value of 0.876 for PS (16:0/16:1), suggesting a potential diagnostic biomarker role. In addition, PS (18:3/20:4) was significantly decreased in MDD2 group compared to MDD1, with AUC value of 0.785.

Long Noncoding RNA NEAT1 as a Potential Candidate Biomarker for Prostate Cancer.

Background: Prostate cancer (PCa) remains one of the leading causes of cancer-related mortality in men worldwide, mainly due to unsatisfactory diagnostic methods used at present, which lead to overdiagnosis, unnecessary biopsies and treatment, or misdiagnosis in early asymptomatic stages. New diagnostic biomarkers are needed for a correct and early diagnosis. Long noncoding RNAs (lncRNAs) have been broadly studied for their involvement in PCa biology, as well as for their potential role as diagnostic biomarkers. Methods: We conducted lncRNA profiling in plasma and microdissected formalin-fixed paraffin-embedded (FFPE) tissues of PCa patients and attempted validation for commonly dysregulated individual lncRNAs. Results: Plasma profiling revealed eight dysregulated lncRNAs, while microarray analysis revealed 717 significantly dysregulated lncRNAs, out of which only nuclear-enriched abundant transcript 1 (NEAT1) was commonly upregulated in plasma samples and FFPE tissues. NEAT1's individual validation revealed statistically significant upregulation (FC = 2.101, p = 0.009). Receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) value of 0.7298 for NEAT1 (95% CI = 0.5812-0.8785), suggesting a relatively high diagnostic value, thus having a potential biomarker role for this malignancy. Conclusions: We present herein data suggesting that NEAT1 could serve as a diagnostic biomarker for PCa. Additional studies of larger cohorts are needed to confirm our findings, as well as the oncogenic mechanism of NEAT1 in the development of PCa.