ABSTRACT
OBJECTIVES: Anterior cruciate ligament (ACL) reconstruction after injury does not prevent post-traumatic osteoarthritis (PTOA). Circulating microRNA (miRNA) and metabolite changes emerging shortly after ACL injury and reconstruction remain insufficiently defined, potentially harbouring early cues contributing to PTOA evolution. Moreover, their differential expression between females and males also may influence PTOA's natural trajectory. This study aims to determine alterations in plasma miRNA and metabolite levels in the early stages following ACL reconstruction and between females and males. METHODS: A cohort of 43 ACL reconstruction patients was examined. Plasma was obtained at baseline, 2 weeks, and 6 weeks post-surgery (129 biospecimens in total). High-throughput miRNA sequencing and metabolomics were conducted. Differentially expressed miRNAs and metabolites were identified using negative binomial and linear regression models, respectively. Associations between miRNAs and metabolites were explored using time and sex as co-variants, (pre-surgery versus 2 and 6 weeks post-surgery). Using computational biology, miRNA-metabolite-gene interaction and pathway analyses were performed. RESULTS: Levels of 46 miRNAs were increased at 2 weeks post-surgery compared to pre-surgery (baseline) using miRNA sequencing. Levels of 13 metabolites were significantly increased while levels of 6 metabolites were significantly decreased at 2 weeks compared to baseline using metabolomics. Hsa-miR-145-5p levels were increased in female subjects at both 2 weeks (log2-fold-change 0.71, 95%CI 0.22,1.20) and 6 weeks (log2-fold-change 0.75, 95%CI 0.07,1.43) post-surgery compared to males. In addition, hsa-miR-497-5p showed increased levels in females at 2 weeks (log2-fold-change 0.77, 95%CI 0.06,1.48) and hsa-miR-143-5p at 6 weeks (log2-fold-change 0.83, 95%CI 0.07,1.59). Five metabolites were decreased at 2 weeks post-surgery in females compared to males: L-leucine (-1.44, 95%CI -1.75,-1.13), g-guanidinobutyrate (-1.27, 95%CI 1.54,-0.99), creatinine (-1.17, 95%CI -1.44,-0.90), 2-methylbutyrylcarnitine (-1.76, 95%CI -2.17,-1.35), and leu-pro (-1.13, 95%CI -1.44,-0.83). MiRNA-metabolite-gene interaction analysis revealed key signalling pathways based on post-surgical time-point and in females versus males. CONCLUSION: MiRNA and metabolite profiles were modified by time and by sex early after ACL reconstruction surgery, which could influence surgical response and ultimately risk of developing PTOA.
Subject(s)
Anterior Cruciate Ligament Injuries , Anterior Cruciate Ligament Reconstruction , MicroRNAs , Humans , Male , Female , Adult , MicroRNAs/blood , Anterior Cruciate Ligament Injuries/surgery , Young Adult , Sex Factors , Biomarkers/blood , Metabolomics , Osteoarthritis, Knee/surgery , Osteoarthritis, Knee/genetics , Osteoarthritis, Knee/metabolism , Middle AgedABSTRACT
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.
Subject(s)
Drug Repositioning , Software , Drug Repositioning/methods , Humans , Internet , Drug Discovery/methods , Systems Biology/methods , Computational Biology/methodsABSTRACT
OBJECTIVE: Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease. DESIGN: In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients. RESULTS: Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease. CONCLUSIONS: Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.
Subject(s)
DNA Methylation , Epigenomics , Genomics , Osteoarthritis , Humans , Osteoarthritis/genetics , Genome-Wide Association Study , MicroRNAs/genetics , Genetic Predisposition to DiseaseABSTRACT
Diabetic kidney disease (DKD) is the main cause of chronic kidney disease (CKD) and progresses faster in males than in females. We identify sex-based differences in kidney metabolism and in the blood metabolome of male and female individuals with diabetes. Primary human proximal tubular epithelial cells (PTECs) from healthy males displayed increased mitochondrial respiration, oxidative stress, apoptosis, and greater injury when exposed to high glucose compared with PTECs from healthy females. Male human PTECs showed increased glucose and glutamine fluxes to the TCA cycle, whereas female human PTECs showed increased pyruvate content. The male human PTEC phenotype was enhanced by dihydrotestosterone and mediated by the transcription factor HNF4A and histone demethylase KDM6A. In mice where sex chromosomes either matched or did not match gonadal sex, male gonadal sex contributed to the kidney metabolism differences between males and females. A blood metabolomics analysis in a cohort of adolescents with or without diabetes showed increased TCA cycle metabolites in males. In a second cohort of adults with diabetes, females without DKD had higher serum pyruvate concentrations than did males with or without DKD. Serum pyruvate concentrations positively correlated with the estimated glomerular filtration rate, a measure of kidney function, and negatively correlated with all-cause mortality in this cohort. In a third cohort of adults with CKD, male sex and diabetes were associated with increased plasma TCA cycle metabolites, which correlated with all-cause mortality. These findings suggest that differences in male and female kidney metabolism may contribute to sex-dependent outcomes in DKD.