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Epithelioid sarcoma (ES) is a rare tumor hallmarked by the loss of INI1/SMARCB1 expression. Apart from this alteration, little is known about the biology of ES. Despite recent advances in treatment, the prognosis of ES remains unsatisfactory. To elucidate the molecular underpinnings of ES, and to identify diagnostic biomarkers and potential therapeutic vulnerabilities, we performed an integrated omics profiling (RNA sequencing and methylation array) of 24 primary, untreated ESs. Transcriptome and methylome analysis identified two distinct molecular clusters that essentially corresponded to the morphologic variants of ES, classic ES (C-ES) and the more aggressive proximal ES (P-ES). The P-ES group was characterized by hyperactivation of GATA3 and MYC pathways, with extensive epigenetic rewiring associated with EZH2 overexpression. Both DNA methylation and gene expression analysis indicated a striking similarity with the "MYC subgroup" of ATRT, another SMARCB1-deficient tumor, implying a shared molecular background and potential therapeutic vulnerabilities. Conversely, the C-ES group exhibited an endothelial-like molecular profile, with expression of vascular genes and elevated pro-angiogenic SOX17 signaling. Immunohistochemistry validated the overexpression of the chromatin regulators GATA3 (9/12 vs. 0/16) and EZH2 (7/7 vs. 2/6) in P-ESs, and of the vascular factors SOX17 (8/8 vs. 1/10) and N-cadherin (5/9 vs 0/10) in C-ESs. Therefore, these molecules emerge as potential diagnostic tools to fill the gap represented by the lack of ES subtype-specific biomarkers. In summary, our study shows that P-ES and C-ES represent distinct molecular entities defined by MYC/GATA3 and SOX17/endothelial molecular traits, respectively. Besides providing insights into the biology of ES, our study pinpoints subtype-specific biomarkers and potential therapeutic vulnerabilities., (Copyright © 2024 THE AUTHORS. Published by Elsevier Inc. All rights reserved.)

Background: Exercise can be used as a model to understand immunometabolism. Biological data on elite athletes are limited, especially for female athletes, including relevant data on acute-phase proteins and amino acid metabolism., Methods: We analyzed acute-phase proteins and amino acids collected at South American, Pan-American, and Olympic Games for 16 Olympic sports. We compared female and male elite athletes (447 vs. 990 samples) across four states (fasting, pre-exercise, post-exercise, and resting) to understand sex-specific immunometabolic responses in elite athletes., Results: Considering all states and sports, we found that elite female athletes exhibited higher concentrations of C-reactive protein, lipopolysaccharide-binding protein, myeloperoxidase, haptoglobin, and IGF1, with ratios ranging from 1.2 to 2.0 ( p < 0.001). Women exhibited lower concentrations of most amino acids, except for glutamate and alanine. Although almost 30% lower in women, branched-chain amino acids (BCAAs) showed a similar pattern in all states (ρ ≥ 0.9; p < 0.001), while aromatic amino acids (AAAs) showed higher consumption during exercise in women., Conclusion: We established sex dimorphism in elite athletes' metabolic and inflammatory responses during training and competition. Our data suggest that female athletes present a lower amino acid response towards central fatigue development than male athletes. Understanding these differences can lead to insights into sex-related immuno-metabolic responses in sports or other inflammatory conditions.

Objectives: In this study, we employ a multiomic approach to identify major cell types and subsets, and their transcriptomic profiles within the infrapatellar fat pad (IFP), and to determine differences in the IFP based on knee osteoarthritis (KOA), sex and obesity status., Methods: Single-nucleus RNA sequencing of 82 924 nuclei from 21 IFPs (n=6 healthy control and n=15 KOA donors), spatial transcriptomics and bioinformatic analyses were used to identify contributions of the IFP to KOA. We mapped cell subclusters from other white adipose tissues using publicly available literature. The diversity of fibroblasts within the IFP was investigated by bioinformatic analyses, comparing by KOA, sex and obesity status. Metabolomics was used to further explore differences in fibroblasts by obesity status., Results: We identified multiple subclusters of fibroblasts, macrophages, adipocytes and endothelial cells with unique transcriptomic profiles. Using spatial transcriptomics, we resolved distributions of cell types and their transcriptomic profiles and computationally identified putative cell-cell communication networks. Furthermore, we identified transcriptomic differences in fibroblasts from KOA versus healthy control donor IFPs, female versus male KOA-IFPs and obese versus normal body mass index (BMI) KOA-IFPs. Finally, using metabolomics, we defined differences in metabolite levels in supernatants of naïve, profibrotic stimuli-treated and proinflammatory stimuli-treated fibroblasts from obese compared to normal BMI KOA-IFPs., Conclusions: Overall, by employing a multiomic approach, this study provides the first comprehensive map of the cellular and transcriptomic diversity of human IFP and identifies IFP fibroblasts as key cells contributing to transcriptomic and metabolic differences related to KOA disease, sex or obesity., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ on behalf of EULAR.)

Introduction: Kidney transplantation is the optimal treatment for end-stage kidney disease; however, premature allograft loss remains a serious issue. While many high-throughput omics studies have analyzed patient allograft biospecimens, integration of these datasets is challenging, which represents a considerable barrier to advancing our understanding of the mechanisms of allograft loss., Methods: To facilitate integration, we have created a curated database containing all open-access high-throughput datasets from human kidney transplant studies, termed NephroDIP (Nephrology Data Integration Portal). PubMed was searched for high-throughput transcriptomic, proteomic, single nucleotide variant, metabolomic, and epigenomic studies in kidney transplantation, which yielded 9,964 studies., Results: From these, 134 studies with available data detailing 260 comparisons and 83,262 molecules were included in NephroDIP v1.0. To illustrate the capabilities of NephroDIP, we have used the database to identify common gene, protein, and microRNA networks that are disrupted in patients with chronic antibody-mediated rejection, the most important cause of late allograft loss. We have also explored the role of an immunomodulatory protein galectin-1 (LGALS1), along with its interactors and transcriptional regulators, in kidney allograft injury. We highlight the pathways enriched among LGALS1 interactors and transcriptional regulators in kidney fibrosis and during immunosuppression., Discussion: NephroDIP is an open access data portal that facilitates data visualization and will help provide new insights into existing kidney transplant data through integration of distinct studies and modules (https://ophid.utoronto.ca/NephroDIP)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Boshart, Petrovic, Abovsky, Pastrello, Farkona, Manion, Neupane, Allen, Jurisica and Konvalinka.)

Technological advances and high-throughput bio-chemical assays are rapidly changing ways how we formulate and test biological hypotheses, and how we treat patients. Most complex diseases arise on a background of genetics, lifestyle and environment factors, and manifest themselves as a spectrum of symptoms. To fathom intricate biological processes and their changes from healthy to disease states, we need to systematically integrate and analyze multi-omics datasets, ontologies, and diverse annotations. Without proper management of such complex biological and clinical data, artificial intelligence (AI) algorithms alone cannot be effectively trained, validated, and successfully applied to provide trustworthy and patient-centric diagnosis, prognosis and treatment. Precision medicine requires to use multi-omics approaches effectively, and offers many opportunities for using AI, "big data" analytics, and integrative computational biology workflows. Advances in optical and biochemical assay technologies including sequencing, mass spectrometry and imaging modalities have transformed research by empowering us to simultaneously view all genes expressed, identify proteome-wide changes, and assess interacting partners of each individual protein within a dynamically changing biological system, at an individual cell level. While such views are already having an impact on our understanding of healthy and disease conditions, it remains challenging to extract useful information comprehensively and systematically from individual studies, ensure that signal is separated from noise, develop models, and provide hypotheses for further research. Data remain incomplete and are often poorly connected using fragmented biological networks. In addition, statistical and machine learning models are developed at a cohort level and often not validated at the individual patient level. Combining integrative computational biology and AI has the potential to improve understanding and treatment of diseases by identifying biomarkers and building explainable models characterizing individual patients. From systematic data analysis to more specific diagnostic, prognostic and predictive biomarkers, drug mechanism of action, and patient selection, such analyses influence multiple steps from prevention to disease characterization, and from prognosis to drug discovery. Data mining, machine learning, graph theory and advanced visualization may help identify diagnostic, prognostic and predictive biomarkers, and create causal models of disease. Intertwining computational prediction and modeling with biological experiments leads to faster, more biologically and clinically relevant discoveries. However, computational analysis results and models are going to be only as accurate and useful as correct and comprehensive are the networks, ontologies and datasets used to build them. High quality, curated data portals provide the necessary foundation for translational research. They help to identify better biomarkers, new drugs, precision treatments, and should lead to improved patient outcomes and their quality of life. Intertwining computational prediction and modeling with biological experiments, efficiently and effectively leads to more useful findings faster., Competing Interests: Declaration of competing interest No relevant conflict of interest., (Copyright © 2024. Published by Elsevier Ltd.)

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 (log 2 -fold-change 0.71, 95%CI 0.22,1.20) and 6 weeks (log 2 -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 (log 2 -fold-change 0.77, 95%CI 0.06,1.48) and hsa-miR-143-5p at 6 weeks (log 2 -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., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

DDR1 interacts with fibrillar collagen and can affect β1 integrin-dependent signaling, but the mechanism that mediates functional interactions between these two different receptors is not defined. We searched for molecules that link DDR1 and β1 integrin-dependent signaling in response to collagen binding. The activation of DDR1 by binding to fibrillar collagen reduced by 5-fold, β1 integrin-dependent ERK phosphorylation that leads to MMP1 expression. In contrast, pharmacological inhibition of DDR1 or culturing cells on fibronectin restored ERK phosphorylation and MMP1 expression mediated by the β1 integrin. A phospho-site screen indicated that collagen-induced DDR1 activation inhibited β1 integrin-dependent ERK signaling by regulating autophosphorylation of focal adhesion kinase (FAK). Immunoprecipitation, mass spectrometry, and protein-protein interaction mapping showed that while DDR1 and FAK do not interact directly, the major vault protein (MVP) binds DDR1 and FAK depending on the substrate. MVP associated with DDR1 in cells expressing β1 integrin that were cultured on collagen. Knockdown of MVP restored ERK activation and MMP1 expression in DDR1-expressing cells cultured on collagen. Immunostaining of invasive cancers in human colon showed colocalization of DDR1 with MVP. These data indicate that MVP interactions with DDR1 and FAK contribute to the regulation of β1 integrin-dependent signaling pathways that drive collagen degradation., Competing Interests: Declaration of competing interest The authors of this manuscript declare no conflict of interest with supporting institutions or individuals in the conduct of this research., (Copyright © 2024. Published by Elsevier Inc.)

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., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

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., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

The hallmarks of spondyloarthritis (SpA) are type 3 immunity-driven inflammation and new bone formation (NBF). Macrophage migration inhibitory factor (MIF) was found to be a key driver of the pathogenesis of SpA by amplifying type 3 immunity, yet MIF-interacting molecules and networks remain elusive. Herein, we identified hypoxia-inducible factor-1 alpha (HIF1A) as an interacting partner molecule of MIF that drives SpA pathologies, including inflammation and NBF. HIF1A expression was increased in the joint tissues and synovial fluid of SpA patients and curdlan-injected SKG (curdlan-SKG) mice compared to the respective controls. Under hypoxic conditions in which HIF1A was stabilized, human and mouse neutrophils exhibited substantially increased expression of MIF and IL-23, an upstream type 3 immunity-related cytokine. Similar to MIF, systemic overexpression of IL-23 induced SpA pathology in SKG mice, while the injection of a HIF1A-selective inhibitor (PX-478) into curdlan-SKG mice prevented or attenuated SpA pathology, as indicated by a marked reduction in the expression of MIF and IL-23. Furthermore, genetic deletion of MIF or HIF1A inhibition with PX-478 in IL-23-overexpressing SKG mice did not induce evident arthritis or NBF, despite the presence of psoriasis-like dermatitis and blepharitis. We also found that MIF- and IL-23-expressing neutrophils infiltrated areas of the NBF in curdlan-SKG mice. These neutrophils potentially increased chondrogenesis and cell proliferation via the upregulation of STAT3 in periosteal cells and ligamental cells during endochondral ossification. Together, these results provide supporting evidence for an MIF/HIF1A regulatory network, and inhibition of HIF1A may be a novel therapeutic approach for SpA by suppressing type 3 immunity-mediated inflammation and NBF., (© 2024. The Author(s), under exclusive licence to CSI and USTC.)

Caffeine is a well-described ergogenic aid used to enhance athletic performance. Using animal models can greatly increase our understanding of caffeine's mechanisms in performance. Here, we adapted an animal weight-lifting exercise model to demonstrate caffeine's ergogenic effect in rats. Male Wistar rats (315 ± 35 g) were randomly divided into two groups: one group received 5 mg·kg -1 of caffeine (0.5 mL; CEx; n = 5) and the other 0.9% NaCl (0.5 mL; PEx; n = 4) through an orogastric probe (gavage) one hour before exercise. Weight-lifting exercise sessions were performed over three subsequent days, and the number of complete squats performed was counted. Analyses of the area under the curve in all three experiments showed that the CEx group responded more to stimuli, performing more squats (1.7-, 2.0-, and 1.6-fold; p < 0.05) than the control group did. These three days' data were analyzed to better understand the cumulative effect of this exercise, and a hyperbolic curve was fitted to these data. Data fitting from the caffeine-supplemented group, CEx, also showed larger S max and K d (2.3-fold and 1.6-fold, respectively) than the PEx group did. Our study demonstrated an acute ergogenic effect of caffeine in an animal weight-lifting exercise model for the first time, suggesting potential avenues for future research.

Objective: Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades., Design: We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease., Results: Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues., Conclusions: Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions., Competing Interests: Conflict of interest None., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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.

Introduction: Dengue virus infection is a global health problem lacking specific therapy, requiring an improved understanding of DENV immunity and vaccine responses. Considering the recent emerging of new dengue vaccines, here we performed an integrative systems vaccinology characterization of molecular signatures triggered by the natural DENV infection (NDI) and attenuated dengue virus infection models (DVTs)., Methods and Results: We analyzed 955 samples of transcriptomic datasets of patients with NDI and attenuated dengue virus infection trials (DVT1, DVT2, and DVT3) using a systems vaccinology approach. Differential expression analysis identified 237 common differentially expressed genes (DEGs) between DVTs and NDI. Among them, 28 and 60 DEGs were up or downregulated by dengue vaccination during DVT2 and DVT3, respectively, with 20 DEGs intersecting across all three DVTs. Enriched biological processes of these genes included type I/II interferon signaling, cytokine regulation, apoptosis, and T-cell differentiation. Principal component analysis based on 20 common DEGs (overlapping between DVTs and our NDI validation dataset) distinguished dengue patients by disease severity, particularly in the late acute phase. Machine learning analysis ranked the ten most critical predictors of disease severity in NDI, crucial for the anti-viral immune response., Conclusion: This work provides insights into the NDI and vaccine-induced overlapping immune response and suggests molecular markers (e.g., IFIT5, ISG15, and HERC5 ) for anti-dengue-specific therapies and effective vaccination development., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. This study received funding from IBM. The funder had the following involvement in the study: production of figures, revision, and manuscript editing. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Plaça, Fonseca, Marques, Zaki Pour, Usuda, Baiocchi, Prado, Salgado, Filgueiras, Freire, Rocha, Camara, Catar, Moll, Jurisica, Calich, Giil, Rivino, Ochs, Cabral-Miranda, Schimke and Cabral-Marques.)

Tangential growth of the human cerebral cortex is driven by cell proliferation during the first and second trimester of pregnancy. Fetal growth peaks in mid-gestation. Here, we explore how genes associated with fetal growth relate to cortical growth. We find that both maternal and fetal genetic variants associated with higher birthweight predict larger cortical surface area. The relative dominance of the maternal vs. fetal variants in these associations show striking variations across birth years (1943 to 1966). The birth-year patterns vary as a function of the epigenetic status near genes differentially methylated in individuals exposed (or not) to famine during the Dutch Winter of 1944/1945. Thus, it appears that the two sets of molecular processes contribute to early cortical development to a different degree in times of food scarcity or its abundance., (© 2024. The Author(s).)

Introduction: Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management., Objectives: To identify metabolites capable of classifying patients with PsA according to their disease activity., Methods: An in-house solid-phase microextraction (SPME)-liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance., Results: The best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids., Conclusion: Several lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified., (© 2024. The Author(s).)

Pathway Data Integration Portal (PathDIP) is an integrated pathway database that was developed to increase functional gene annotation coverage and reduce bias in pathway enrichment analysis. PathDIP 5 provides multiple improvements to enable more interpretable analysis: users can perform enrichment analysis using all sources, separate sources or by combining specific pathway subsets; they can select the types of sources to use or the types of pathways for the analysis, reducing the number of resulting generic pathways or pathways not related to users' research question; users can use API. All pathways have been mapped to seven representative types. The results of pathway enrichment can be summarized through knowledge-based pathway consolidation. All curated pathways were mapped to 53 pathway ontology-based categories. In addition to genes, pathDIP 5 now includes metabolites. We updated existing databases, included two new sources, PathBank and MetabolicAtlas, and removed outdated databases. We enable users to analyse their results using Drugst.One, where a drug-gene network is created using only the user's genes in a specific pathway. Interpreting the results of any analysis is now improved by multiple charts on all the results pages. PathDIP 5 is freely available at https://ophid.utoronto.ca/pathDIP., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

This article explores the progressive integration of -omics methods, including genomics, metabolomics, and proteomics, into sports research, highlighting the development of the concept of "sportomics." We discuss how sportomics can be used to comprehend the multilevel metabolism during exercise in real-life conditions faced by athletes, enabling potential personalized interventions to improve performance and recovery and reduce injuries, all with a minimally invasive approach and reduced time. Sportomics may also support highly personalized investigations, including the implementation of n -of-1 clinical trials and the curation of extensive datasets through long-term follow-up of athletes, enabling tailored interventions for athletes based on their unique physiological responses to different conditions. Beyond its immediate sport-related applications, we delve into the potential of utilizing the sportomics approach to translate Big Data regarding top-level athletes into studying different human diseases, especially with nontargeted analysis. Furthermore, we present how the amalgamation of bioinformatics, artificial intelligence, and integrative computational analysis aids in investigating biochemical pathways, and facilitates the search for various biomarkers. We also highlight how sportomics can offer relevant information about doping control analysis. Overall, sportomics offers a comprehensive approach providing novel insights into human metabolism during metabolic stress, leveraging cutting-edge systems science techniques and technologies.

Introduction: Recent advances in understanding the biology of ankylosing spondylitis (AS) using innovative genomic and proteomic approaches offer the opportunity to address current challenges in AS diagnosis and management. Altered expression of genes, microRNAs (miRNAs) or proteins may contribute to immune dysregulation and may play a significant role in the onset and persistence of inflammation in AS. The ability of exosomes to transport miRNAs across cells and alter the phenotype of recipient cells has implicated exosomes in perpetuating inflammation in AS. This study reports the first proteomic and miRNA profiling of plasma-derived exosomes in AS using comprehensive computational biology analysis., Methods: Plasma samples from patients with AS and healthy controls (HC) were isolated via ultracentrifugation and subjected to extracellular vesicle flow cytometry analysis to characterise exosome surface markers by a multiplex immunocapture assay. Cytokine profiling of plasma-derived exosomes and cell culture supernatants was performed. Next-generation sequencing was used to identify miRNA populations in exosomes enriched from plasma fractions. CD4+ T cells were sorted, and the frequency and proliferation of CD4+ T-cell subsets were analysed after treatment with AS-exosomes using flow cytometry., Results: The expression of exosome marker proteins CD63 and CD81 was elevated in the patients with AS compared with HC (q<0.05). Cytokine profiling in plasma-derived AS-exosomes demonstrated downregulation of interleukin (IL)-8 and IL-10 (q<0.05). AS-exosomes cocultured with HC CD4+ T cells induced significant upregulation of IFNα2 and IL-33 (q<0.05). Exosomes from patients with AS inhibited the proliferation of regulatory T cells (Treg), suggesting a mechanism for chronically activated T cells in this disease. Culture of CD4+ T cells from healthy individuals in the presence of AS-exosomes reduced the proliferation of FOXP3+ Treg cells and decreased the frequency of FOXP3+IRF4+ Treg cells. miRNA sequencing identified 24 differentially expressed miRNAs found in circulating exosomes of patients with AS compared with HC; 22 of which were upregulated and 2 were downregulated., Conclusions: Individuals with AS have different immunological and genetic profiles, as determined by evaluating the exosomes of these patients. The inhibitory effect of exosomes on Treg in AS suggests a mechanism contributing to chronically activated T cells in this disease., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Psoriatic arthritis (PsA) is a chronic, systemic, immune-mediated inflammatory disease causing cutaneous and musculoskeletal inflammation that affects 25% of patients with psoriasis. Current methods for evaluating PsA disease activity are not accurate enough for precision medicine. A metabolomics-based approach can elucidate psoriatic disease pathogenesis, providing potential objective biomarkers. With the hypothesis that serum metabolites are associated with skin disease activity, we aimed to identify serum metabolites associated with skin activity in PsA patients. We obtained serum samples from patients with PsA (n = 150) who were classified into mild, moderate and high disease activity groups based on the Psoriasis Area Severity Index. We used solid-phase microextraction (SPME) for sample preparation, followed by data acquisition via an untargeted liquid chromatography-mass spectrometry (LC-MS) approach. Disease activity levels were predicted using identified metabolites and machine learning algorithms. Some metabolites tentatively identified include eicosanoids with anti- or pro-inflammatory properties, like 12-Hydroxyeicosatetraenoic acid, which was previously implicated in joint disease activity in PsA. Other metabolites of interest were associated with dysregulation of fatty acid metabolism and belonged to classes such as bile acids, oxidized phospholipids, and long-chain fatty acids. We have identified potential metabolites associated with skin disease activity in PsA patients.

The transcription factor c-Myb is overexpressed in many different types of solid tumors, including colorectal cancer. However, its exact role in tumorigenesis is unclear. In this study, we show that tumor-intrinsic c-Myb expression in mouse models of colon cancer and melanoma suppresses tumor growth. Although no differences in proliferation, apoptosis, and angiogenesis of tumors were evident in tumors with distinct levels of c-Myb expression, we observed changes in intratumoral immune cell infiltrates. MC38 tumors with upregulated c-Myb expression showed increased numbers of CD103+ dendritic cells and eosinophils, but decreased tumor-associated macrophages (TAM). Concomitantly, an increase in the number of activated cytotoxic CD8+ T cells upon c-Myb upregulation was observed, which correlated with a pro-inflammatory tumor microenvironment and increased numbers of M1 polarized TAMs. Mechanistically, c-Myb upregulation in immunogenic MC38 colon cancer cells resulted in enhanced expression of immunomodulatory genes, including those encoding β2-microglobulin and IFNβ, and decreased expression of the gene encoding the chemokine receptor CCR2. The increased numbers of activated cytotoxic CD8+ T cells contributed to tumor growth attenuation. In poorly immunogenic CT26, LLC, and B16-BL6 tumor cells, c-Myb upregulation did not affect the immunomodulatory gene expression. Despite this, c-Myb upregulation led to reduced B16-BL6 tumor growth but it did not affect tumor growth of CT26 and LLC tumors. Altogether, we postulate that c-Myb functions as a tumor suppressor in a tumor cell-type specific manner and modulates antitumor immunity., (©2023 The Authors; Published by the American Association for Cancer Research.)

The interplay between the intestinal microbiota and host is critical to intestinal ontogeny and homeostasis. MicroRNAs (miRNAs) may be an underlying link. Intestinal miRNAs are microbiota-dependent and, when shed in the lumen, affect resident microorganisms. Yet, longitudinal relationships between intestinal tissue miRNAs, luminal miRNAs, and luminal microorganisms have not been elucidated, especially in early life. Here, we investigated the postnatal cecal miRNA and microbiota populations, their relationship, and their impact on intestinal maturation in specific pathogen-free mice; we also assessed if they can be modified by intervention with allochthonous probiotic lactobacilli. We report that cecal and cecal content miRNA and microbiota signatures are temporally regulated, correlated, and modifiable by probiotics with implications for intestinal maturation. These findings help understand causal relationships within the gut ecosystem and provide a basis for preventing and managing their alterations in diseases throughout life. IMPORTANCE The gut microbiota affects intestinal microRNA (miRNA) signatures and is modified by host-derived luminal miRNA. This suggests the existence of close miRNA-microbiota relationships that are critical to intestinal homeostasis. However, an integrative analysis of these relationships and their evolution during intestinal postnatal maturation is lacking. We provide a system-level longitudinal analysis of miRNA-microbiota networks in the intestine of mice at the weaning transition, including tissue and luminal miRNA and luminal microbiota. To address causality and move toward translational applications, we used allochthonous probiotic lactobacilli to modify these longitudinal relationships and showed that they are critical for intestinal maturation in early life. These findings contribute to understand mechanisms that underlie the maturation of the intestinal ecosystem and suggest that interventions aiming at maintaining, or restoring, homeostasis cannot prescind from considering relationships among its components., Competing Interests: E.M.C. has received research support from the Lallemand Health Solutions and Ocean Spray and has received consultant fees from Danone. All other authors declare no conflict of interests. The probiotic strains utilized in this study were provided by the Lallemand Health Solutions (LHS), Inc.

Motivation: Many real-world problems can be modeled as annotated graphs. Scalable graph algorithms that extract actionable information from such data are in demand since these graphs are large, varying in topology, and have diverse node/edge annotations. When these graphs change over time they create dynamic graphs, and open the possibility to find patterns across different time points. In this article, we introduce a scalable algorithm that finds unique dense regions across time points in dynamic graphs. Such algorithms have applications in many different areas, including the biological, financial, and social domains., Results: There are three important contributions to this manuscript. First, we designed a scalable algorithm, USNAP, to effectively identify dense subgraphs that are unique to a time stamp given a dynamic graph. Importantly, USNAP provides a lower bound of the density measure in each step of the greedy algorithm. Second, insights and understanding obtained from validating USNAP on real data show its effectiveness. While USNAP is domain independent, we applied it to four non-small cell lung cancer gene expression datasets. Stages in non-small cell lung cancer were modeled as dynamic graphs, and input to USNAP. Pathway enrichment analyses and comprehensive interpretations from literature show that USNAP identified biologically relevant mechanisms for different stages of cancer progression. Third, USNAP is scalable, and has a time complexity of O(m+mc log nc+nc log nc), where m is the number of edges, and n is the number of vertices in the dynamic graph; mc is the number of edges, and nc is the number of vertices in the collapsed graph., Availability and Implementation: The code of USNAP is available at https://www.cs.utoronto.ca/~juris/data/USNAP22., (© The Author(s) 2023. Published by Oxford University Press.)

Rectal cancer (RC) accounts for one-third of colorectal cancers (CRC), and 40% of these are locally advanced rectal cancers (LARC). The use of neoadjuvant chemoradiotherapy (nCRT) significantly reduces the rate of local recurrence compared to adjuvant therapy or surgery alone. However, after nCRT, up to 40%-60% of patients show a poor pathological response, while only about 20% achieve a pathological complete response. In this scenario, the identification of novel predictors of tumor response to nCRT is urgently needed to reduce LARC mortality and to spare poorly responding patients from unnecessary treatments. Therefore, by combining gene and microRNA expression datasets with proteomic data from LARC patients, we developed an integrated network centered on seven hub-genes putatively involved in the response to nCRT. In an independent validation cohort of LARC patients, we confirmed that differential expression of NFKB1, TRAF6 and STAT3 is correlated with the response to nCRT. In addition, the functional enrichment analysis also revealed that these genes are strongly related to hallmarks of cancer and inflammation, whose dysfunction may causatively affect LARC patient's response to nCRT. Furthermore, by constructing the transcription factor-module network, we hypothesized a protective role of POU2F3 gene, which could be used as a new drug target in LARC patients. Finally, we identified and tested in vitro entinostat, a histone deacetylase inhibitor, as a chemical compound that could be combined with a classical therapeutic regimen in order to design more efficient therapeutic strategies in LARC management., (© 2023 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: Acute ST-elevation myocardial infarction (STEMI) can lead to adverse cardiac remodeling, resulting in left ventricular systolic dysfunction (LVSd) and heart failure. Epigenetic regulators, such as microRNAs, may be involved in the physiopathology of LVSd., Objective: This study explored microRNAs in peripheral blood mononuclear cells (PBMC) of post-myocardial infarction patients with LVSd., Methods: Post-STEMI patients were grouped as having (LVSd, n  = 9) or not LVSd (non-LVSd, n  = 16). The expression of 61 microRNAs was analyzed in PBMC by RT-qPCR and the differentially expressed microRNAs were identified. Principal Component Analysis stratified the microRNAs based on the development of dysfunction. Predictive variables of LVSd were investigated through logistic regression analysis. A system biology approach was used to explore the regulatory molecular network of the disease and an enrichment analysis was performed., Results: The let-7b-5p (AUC: 0.807; 95% CI: 0.63-0.98; p  = 0.013), miR-125a-3p (AUC: 0.800; 95% CI: 0.61-0.99; p  = 0.036) and miR-326 (AUC: 0.783; 95% CI: 0.54-1.00; p  = 0.028) were upregulated in LVSd ( p  < 0.05) and discriminated LVSd from non-LVSd. Multivariate logistic regression analysis showed let-7b-5p (OR: 16.00; 95% CI: 1.54-166.05; p  = 0.020) and miR-326 (OR: 28.00; 95% CI: 2.42-323.70; p  = 0.008) as predictors of LVSd. The enrichment analysis revealed association of the targets of these three microRNAs with immunological response, cell-cell adhesion, and cardiac changes., Conclusion: LVSd alters the expression of let-7b-5p, miR-326, and miR-125a-3p in PBMC from post-STEMI, indicating their potential involvement in the cardiac dysfunction physiopathology and highlighting these miRNAs as possible LVSd biomarkers., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Dantas-Komatsu, Cruz, Freire, Diniz, Bortolin, Cabral-Marques, Souza, Hirata, Hirata, Reis, Jurisica, Silbiger and Luchessi.)

History of traumatic brain injury (TBI) represents a significant risk factor for development of dementia and neurodegenerative disorders in later life. While histopathological sequelae and neurological diagnostics of TBI are well defined, the molecular events linking the post-TBI signaling and neurodegenerative cascades remain unknown. It is not only due to the brain's inaccessibility to direct molecular analysis but also due to the lack of well-defined and highly informative peripheral biomarkers. MicroRNAs (miRNAs) in blood are promising candidates to address this gap. Using integrative bioinformatics pipeline including miRNA:target identification, pathway enrichment, and protein-protein interactions analysis we identified set of genes, interacting proteins, and pathways that are connected to previously reported peripheral miRNAs, deregulated following severe traumatic brain injury (sTBI) in humans. This meta-analysis revealed a spectrum of genes closely related to critical biological processes, such as neuroregeneration including axon guidance and neurite outgrowth, neurotransmission, inflammation, proliferation, apoptosis, cell adhesion, and response to DNA damage. More importantly, we have identified molecular pathways associated with neurodegenerative conditions, including Alzheimer's and Parkinson's diseases, based on purely peripheral markers. The pathway signature after acute sTBI is similar to the one observed in chronic neurodegenerative conditions, which implicates a link between the post-sTBI signaling and neurodegeneration. Identified key hub interacting proteins represent a group of novel candidates for potential therapeutic targets or biomarkers., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Importance: Head impacts resulting in traumatic brain injury (TBI) lead to the elevation of phosphorylated tau protein (p-tau181) in plasma. To our knowledge, this study is the first to investigate dynamics of p-tau181 levels and the ratio of p-tau181 to total tau in individuals after nonconcussive head impacts., Objective: To determine the association of repetitive low-intensity head impacts on p-tau181 and total tau protein levels in the plasma of young adult elite soccer players and assess the possible association of head impacts with focused attention and cognitive flexibility., Design, Setting, and Participants: In this cohort study, young elite soccer players performed intense physical activity with and without heading the ball. The study was conducted at a university facility in Slovakia from October 1, 2021, to May 31, 2022. Eligible participants were selected based on similarities in demographic variables, excluding those with a history of TBI., Main Outcomes and Measures: The primary study outcomes were the levels of total tau protein and p-tau181 in plasma samples and the cognitive status of the study participants., Results: A total of 37 male athletes participated in the study (mean [SD] age: exercise group, 21.6 [1.6] years; heading group, 21.2 [1.5] years). We found significantly elevated levels of total tau and p-tau181 in the plasma of soccer players 1 hour after physical exercise (tau, 1.4-fold; 95% CI, 1.2-1.5; P < .001; p-tau181, 1.4-fold; 95% CI, 1.3-1.5, P < .001) and repetitive head impacts (tau, 1.3-fold; 95% CI, 1.2-1.4; P < .001; p-tau181, 1.5-fold; 95% CI, 1.4-1.7 P < .001). The ratio of p-tau181 to tau was significantly higher 1 hour after exercise and heading training, and remained elevated specifically in the heading group even after 24 hours (1.2-fold; 95% CI, 1.1-1.3; P = .002). Performance in cognitive tests revealed a significant decline in focused attention and cognitive flexibility after physical exercise and heading training; physical exercise of higher intensity without heading training was associated with a greater negative cognitive performance than heading only., Conclusions and Relevance: In this cohort study of young elite soccer players, the elevation of p-tau181 and tau was observed after acute intense physical activity and nonconcussive repetitive head impacts. The increase of p-tau181 levels relative to tau after 24 hours indicated an acute enrichment of phosphorylated tau fraction in the periphery when compared with preimpact levels; an imbalance of tau proteins may have long-lasting consequences in the brain of head-impacted individuals.

Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention., (© 2023 The Authors. Journal of Medical Virology published by Wiley Periodicals LLC.)

The chronic inflammatory disease ankylosing spondylitis (AS) is marked by back discomfort, spinal ankylosis, and extra-articular symptoms. In AS, inflammation is responsible for both pain and spinal ankylosis. However, the processes that sustain chronic inflammation remain unknown. Despite the years of research conducted to decipher the intricacy of AS, little progress has been made in identifying the signaling events that lead to the development of this disease. T cells, an immune cell type that initiates and regulates the body's response to infection, have been established to substantially impact the development of AS. T lymphocytes are regarded as a crucial part of adaptive immunity for the control of the immune system. A highly coordinated interaction involving antigen-presenting cells (APCs) and T cells that regulate T cell activation constitutes an immunological synapse (IS). This first phase leads to the controlled trafficking of receptors and signaling mediators involved in folding endosomes to the cellular interface, which allows the transfer of information from T cells to APCs through IS formation. Discrimination of self and nonself antigen is somatically learned in adaptive immunity. In an autoimmune condition such as AS, there is a disturbance of self/nonself antigen discrimination; available findings imply that the IS plays a preeminent role in the adaptive immune response. In this paper, we provide insights into the genesis of AS by evaluating recent developments in the function of vesicular trafficking in IS formation and the targeted release of exosomes enriched microRNAs (miRNA) at the synaptic region in T cells., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Tavasolian, Pastrello, Ahmed, Jurisica and Inman.)

MirDIP is a well-established database that aggregates microRNA-gene human interactions from multiple databases to increase coverage, reduce bias, and improve usability by providing an integrated score proportional to the probability of the interaction occurring. In version 5.2, we removed eight outdated resources, added a new resource (miRNATIP), and ran five prediction algorithms for miRBase and mirGeneDB. In total, mirDIP 5.2 includes 46 364 047 predictions for 27 936 genes and 2734 microRNAs, making it the first database to provide interactions using data from mirGeneDB. Moreover, we curated and integrated 32 497 novel microRNAs from 14 publications to accelerate the use of these novel data. In this release, we also extend the content and functionality of mirDIP by associating contexts with microRNAs, genes, and microRNA-gene interactions. We collected and processed microRNA and gene expression data from 20 resources and acquired information on 330 tissue and disease contexts for 2657 microRNAs, 27 576 genes and 123 651 910 gene-microRNA-tissue interactions. Finally, we improved the usability of mirDIP by enabling the user to search the database using precursor IDs, and we integrated miRAnno, a network-based tool for identifying pathways linked to specific microRNAs. We also provide a mirDIP API to facilitate access to its integrated predictions. Updated mirDIP is available at https://ophid.utoronto.ca/mirDIP., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Objective: Synovial fibrosis contributes to osteoarthritis (OA) pathology, but the underlying mechanisms remain unknown. We have observed increased microRNA-27b-3p (miR-27b-3p) levels in synovial fluid of patients with late-stage radiographic knee OA. Here, we investigated the contribution of miR-27b-3p to synovial fibrosis in patients with severe knee OA and in a mouse model of knee OA., Methods: We stained synovium sections obtained from patients with radiographic knee OA scored according to the Kellgren/Lawrence scale and mice that underwent destabilization of the medial meniscus (DMM) for miR-27b-3p using in situ hybridization. We examined the effects of intraarticular injection of miR-27b-3p mimic into naive mouse knee joints and intraarticular injection of a miR-27b-3p inhibitor into mouse knee joints after DMM. We performed transfection with miR-27b-3p mimic and miR-27b-3p inhibitor in human OA fibroblast-like synoviocytes (FLS) using reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) array, RNA sequencing, RT-qPCR, Western blotting, immunofluorescence, and migration assays., Results: We observed increased miR-27b-3p expression in the synovium from patients with knee OA and in mice with DMM-induced arthritis. Injection of the miR-27b-3p mimic in mouse knee joints induced a synovial fibrosis-like phenotype, increased synovitis scores, and increased COL1A1 and α-smooth muscle actin (α-SMA) expression. In the mouse model of DMM-induced arthritis, injection of the miR-27b-3p inhibitor decreased α-SMA but did not change COL1A1 expression levels or synovitis scores. Transfection with the miR-27b-3p mimic in human OA FLS induced profibrotic responses, including increased migration and expression of key extracellular matrix (ECM) genes, but transfection with the miR-27b-3p inhibitor had the opposite effects. RNA sequencing identified a PPARG/ADAMTS8 signaling axis regulated by miR-27b-3p in OA FLS. Human OA FLS transfected with miR-27b-3p mimic and then treated with the PPARG agonist rosiglitazone or with ADAMTS8 small interfering RNA exhibited altered expression of select ECM genes., Conclusion: Our findings demonstrate that miR-27b-3p has a key role in ECM regulation associated with synovial fibrosis during OA., (© 2022 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Objectives: To define imaging sub-phenotypes in patients with PsA; determine their association with whole blood gene expression and identify biological pathways characterizing the sub-phenotypes., Methods: Fifty-five patients with PsA ready to initiate treatment for active disease were prospectively recruited. We performed musculoskeletal ultrasound assessment of the extent of inflammation in the following domains: synovitis, peritenonitis, tenosynovitis and enthesitis. Peripheral whole blood was profiled with RNAseq, and gene expression data were obtained. First, unsupervised cluster analysis was performed to define imaging sub-phenotypes that reflected the predominant tissue involved. Subsequently, principal component analysis was used to determine the association between imaging-defined sub-phenotypes and peripheral blood gene expression profile. Pathway enrichment analysis was performed to identify underlying mechanisms that characterize individual sub-phenotypes., Results: Cluster analysis revealed three imaging sub-phenotypes: (i) synovitis predominant [n = 31 (56%)]; (ii) enthesitis predominant [n = 13 (24%)]; (iii) peritenonitis predominant [n = 11 (20%)]. The peritenonitis-predominant sub-phenotype had the most severe clinical joint involvement, whereas the enthesitis-predominant sub-phenotype had the highest tender entheseal count. Unsupervised clustering of gene expression data identified three sub-phenotypes that partially overlapped with the imaging sub-phenotypes suggesting biological and clinical relevance of these sub-phenotypes. We therefore characterized enriched differential pathways, which included: immune system (innate system, B cells and neutrophil degranulation), complement system, platelet activation and coagulation function., Conclusions: We identified three sub-phenotypes based on the predominant tissue involved in patients with active PsA. Distinct biological pathways may underlie these imaging sub-phenotypes seen in PsA, suggesting their biological and clinical importance., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Sportomics is a subject-centered holistic method similar to metabolomics focusing on sports as the metabolic challenge. Dried blood spot is emerging as a technique due to its simplicity and reproducibility. In addition, mass spectrometry and integrative computational biology enhance our ability to understand exercise-induced modifications. We studied inflammatory blood proteins (Alpha-1-acid glycoprotein-A1AG1; Albumin; Cystatin C; C-reactive protein-CRP; Hemoglobin-HBA; Haptoglobin-HPT; Insulin-like growth factor 1; Lipopolysaccharide binding protein-LBP; Mannose-binding lectin-MBL2; Myeloperoxidase-PERM and Serum amyloid A1-SAA1), in 687 samples from 97 World-class and Olympic athletes across 16 sports in nine states. Data were analyzed with Spearman's rank-order correlation. Major correlations with CRP, LBP; MBL2; A1AG1, and SAA1 were found. The pairs CRP-SAA1 and CRP-LBP appeared with a robust positive correlation. Other pairs, LBP-SAA1; A1AG1-CRP; A1AG1-SAA1; A1AG1-MBL, and A1AG1-LBP, showed a broader correlation across the sports. The protein-protein interaction map revealed 1500 interactions with 44 core proteins, 30 of them linked to immune system processing. We propose that the inflammation follow-up in exercise can provide knowledge for internal cargo management in training, competition, recovery, doping control, and a deeper understanding of health and disease., (© 2022. The Author(s).)

Met is an oncogene aberrantly activated in multiple cancers. Therefore, to better understand Met biology and its role in disease we applied the Ma mmalian M embrane T wo- H ybrid (MaMTH) to generate a targeted interactome map of its interactions with human SH2/PTB-domain-containing proteins. We identified thirty interaction partners, including sixteen that were previously unreported. Non-small cell lung cancer (NSCLC)-focused functional characterization of a Met-interacting protein, BLNK, revealed that BLNK is a positive regulator of Met signaling, and modulates localization, including ligand-dependent trafficking of Met in NSCLC cell lines. Furthermore, the interaction between Met and GRB2 is increased in the presence of BLNK, and the constitutive interaction between BLNK and GRB2 is increased in the presence of active Met. Tumor phenotypical assays uncovered roles for BLNK in anchorage-independent growth and chemotaxis of NSCLC cell lines. Cumulatively, this study provides a Met-interactome and delineates a role for BLNK in regulating Met biology in NSCLC context., Competing Interests: Authors declare no competing financial interests., (© 2022 The Authors.)

Most patients with Post COVID Syndrome (PCS) present with a plethora of symptoms without clear evidence of organ dysfunction. A subset of them fulfills diagnostic criteria of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Symptom severity of ME/CFS correlates with natural regulatory autoantibody (AAB) levels targeting several G-protein coupled receptors (GPCR). In this exploratory study, we analyzed serum AAB levels against vaso- and immunoregulatory receptors, mostly GPCRs, in 80 PCS patients following mild-to-moderate COVID-19, with 40 of them fulfilling diagnostic criteria of ME/CFS. Healthy seronegative (n=38) and asymptomatic post COVID-19 controls (n=40) were also included in the study as control groups. We found lower levels for various AABs in PCS compared to at least one control group, accompanied by alterations in the correlations among AABs. Classification using random forest indicated AABs targeting ADRB2, STAB1, and ADRA2A as the strongest classifiers (AABs stratifying patients according to disease outcomes) of post COVID-19 outcomes. Several AABs correlated with symptom severity in PCS groups. Remarkably, severity of fatigue and vasomotor symptoms were associated with ADRB2 AAB levels in PCS/ME/CFS patients. Our study identified dysregulation of AAB against various receptors involved in the autonomous nervous system (ANS), vaso-, and immunoregulation and their correlation with symptom severity, pointing to their role in the pathogenesis of PCS., Competing Interests: The authors declare that HH and KS-F are managing directors of CellTrend. CellTrend holds together with Charité a patent for the diagnostic use of AABs against ADRB2. CS has a consulting agreement with CellTrend. FP reports grants from the Guthy Jackson Charitable Foundation, during the conduct of the study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor MD declared a past co-authorship with the author YS., (Copyright © 2022 Sotzny, Filgueiras, Kedor, Freitag, Wittke, Bauer, Sepúlveda, Mathias da Fonseca, Baiocchi, Marques, Kim, Lange, Plaça, Luebber, Paulus, De Vito, Jurisica, Schulze-Forster, Paul, Bellmann-Strobl, Rust, Hoppmann, Shoenfeld, Riemekasten, Heidecke, Cabral-Marques and Scheibenbogen.)

Biological pathways are a broadly used formalism for representing and interpreting the cascade of biochemical reactions underlying cellular and biological mechanisms. Pathway representation provides an ontological link among biomolecules such as RNA, DNA, small molecules, proteins, protein complexes, hormones and genes. Frequently, pathway annotations are used to identify mechanisms linked to genes within affected biological contexts. This important role and the simplicity and elegance in representing complex interactions led to an explosion of pathway representations and databases. Unfortunately, the lack of overlap across databases results in inconsistent enrichment analysis results, unless databases are integrated. However, due to absence of consensus, guidelines or gold standards in pathway definition and representation, integration of data across pathway databases is not straightforward. Despite multiple attempts to provide consolidated pathways, highly related, redundant, poorly overlapping or ambiguous pathways continue to render pathways analysis inconsistent and hard to interpret. Ontology-based integration will promote unbiased, comprehensive yet streamlined analysis of experiments, and will reduce the number of enriched pathways when performing pathway enrichment analysis. Moreover, appropriate and consolidated pathways provide better training data for pathway prediction algorithms. In this manuscript, we describe the current methods for pathway consolidation, their strengths and pitfalls, and highlight directions for future improvements to this research area., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

We have been using sportomics to understand hypermetabolic stress. Cross Combat (CCombat) has recently been initiated as a high-intensity functional training method inspired by CrossFit. We used a CCombat session to induce metabolic stress and evaluated its effects on hydration and kidney function. Blood samples were collected from 16 elite-level professional male athletes engaged in training sessions over a 96-h protocol. Blood myoglobin increased by ~ 3.5-fold (119 ± 21 to 369 ± 62 nmol/L; p = .001) in response to the protocol, returning to the pre-exercise level within 48 h. Furthermore, D-dimer levels increased from 6.5 ± 0.6 to 79.4 ± 21.3 μmol/L (p < .001) in response to exercise decreasing during recovery with high variability among the studied athletes. Albuminemia and creatininemia increased ~ 10% and cystatin C increased ~ 240% (1.7 ± 0.1 to 5.7 ± 0.5 mg/L; p < .001; effect size = 2.4) in response to the protocol. We measured albuminuria (HuA) to assess kidney permeability to albumin caused by exercise. HuA increased ~ 16-fold (0.16 ± 0.03 to 2.47 ± 0.41 μmol/L; p < .001; effect size = 1.4) in response to exercise, dropping and reaching basal levels during 48 h. Here, we suggest that microalbuminuria can be used as an early, sensitive, easy, and inexpensive biomarker to evaluate hydration status changes during intensive exercise, decreasing chronic impairment in renal function., (© 2022. The Author(s).)

Aim: To explore the short-term effects of accidental head impacts and repetitive headers on circulating microRNAs, accounting for the effects of high-intensity exercise alone., Methods: Blood samples were collected from professional soccer players at rest. Repeat samples were drawn 1 h and 12 h after three conditions: (1) accidental head impacts in a match, (2) repetitive headers during training, and (3) high-intensity exercise. 89 samples were screened to detect microRNAs expressed after each exposure. Identified microRNAs were then validated in 98 samples to determine consistently deregulated microRNAs. Deregulated microRNAs were further explored using bioinformatics to identify target genes and characterize their involvement in biological pathways., Results: Accidental head impacts led to deregulation of eight microRNAs that were unaffected by high-intensity exercise; target genes were linked to 12 specific signaling pathways, primarily regulating chromatin organization, Hedgehog and Wnt signaling. Repetitive headers led to deregulation of six microRNAs that were unaffected by high-intensity exercise; target genes were linked to one specific signaling pathway (TGF-β). High-intensity exercise led to deregulation of seven microRNAs; target genes were linked to 31 specific signaling pathways., Conclusion: We identified microRNAs specific to accidental head impacts and repetitive headers in soccer, potentially being useful as brain injury biomarkers.

COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity., (© 2022. The Author(s).)

Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaki disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19&#95;nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflammatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at the protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride and bicarbonate channel in secretory epithelia with a critical role in maintaining fluid homeostasis. Mutations in CFTR are associated with Cystic Fibrosis (CF), the most common lethal autosomal recessive disorder in Caucasians. While remarkable treatment advances have been made recently in the form of modulator drugs directly rescuing CFTR dysfunction, there is still considerable scope for improvement of therapeutic effectiveness. Here, we report the application of a high-throughput screening variant of the Mammalian Membrane Two-Hybrid (MaMTH-HTS) to map the protein-protein interactions of wild-type (wt) and mutant CFTR (F508del), in an effort to better understand CF cellular effects and identify new drug targets for patient-specific treatments. Combined with functional validation in multiple disease models, we have uncovered candidate proteins with potential roles in CFTR function/CF pathophysiology, including Fibrinogen Like 2 (FGL2), which we demonstrate in patient-derived intestinal organoids has a significant effect on CFTR functional expression., (© 2022 The Authors. Published under the terms of the CC BY 4.0 license.)

Objective: OsteoDIP aims to collect and provide, in a simple searchable format, curated high throughput RNA expression data related to osteoarthritis., Design: Datasets are collected annually by searching "osteoarthritis gene expression profile" in PubMed. Only publications containing patient data and a list of differentially expressed genes are considered. From 2020, the search has expanded to include non-coding RNAs. Moreover, a search in GEO for "osteoarthritis" datasets has been performed using ' Homo sapiens ' and 'Expression profiling by array' filters. Annotations for genes linked to osteoarthritis have been downloaded from external databases., Results: Out of 1204 curated papers, 63 have been included in OsteoDIP, while GEO curation led to the collection of 28 datasets. Literature data provides a snapshot of osteoarthritis research derived from 1924 human samples, while GEO datasets provide expression for additional 1012 patients. Similar to osteoarthritis literature, OsteoDIP data has been created mostly from studies focused on knee, and the tissue most frequently investigated is cartilage. GEO data sets were fully integrated with associated clinical data. We showcase examples and use cases applicable for translational research in osteoarthritis., Conclusions: OsteoDIP is publicly available at http://ophid.utoronto.ca/OsteoDIP. The website is easy to navigate and all the data is available for download. Data consolidation allows researchers to perform comparisons across studies and to combine data from different datasets. Our examples show how OsteoDIP can integrate with and improve osteoarthritis researchers' pipelines., Competing Interests: At the end of the text, under a subheading “Conflict of interest statement” all authors must disclose any financial and personal relationships with other people or organisations that could inappropriately influence (bias) their work. Examples of potential conflicts of interest include employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and research grants or other funding., (© 2022 The Authors.)

Improved bioassays have significantly increased the rate of identifying new protein-protein interactions (PPIs), and the number of detected human PPIs has greatly exceeded early estimates of human interactome size. These new PPIs provide a more complete view of disease mechanisms but precise understanding of how PPIs affect phenotype remains a challenge. It requires knowledge of PPI context (e.g. tissues, subcellular localizations), and functional roles, especially within pathways and protein complexes. The previous IID release focused on PPI context, providing networks with comprehensive tissue, disease, cellular localization, and druggability annotations. The current update adds developmental stages to the available contexts, and provides a way of assigning context to PPIs that could not be previously annotated due to insufficient data or incompatibility with available context categories (e.g. interactions between membrane and cytoplasmic proteins). This update also annotates PPIs with conservation across species, directionality in pathways, membership in large complexes, interaction stability (i.e. stable or transient), and mutation effects. Enrichment analysis is now available for all annotations, and includes multiple options; for example, context annotations can be analyzed with respect to PPIs or network proteins. In addition to tabular view or download, IID provides online network visualization. This update is available at http://ophid.utoronto.ca/iid., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Motivation: Functional annotation is a common part of microRNA (miRNA)-related research, typically carried as pathway enrichment analysis of the selected miRNA targets. Here, we propose miRAnno, a fast and easy-to-use web application for miRNA annotation., Results: miRAnno uses comprehensive molecular interaction network and random walks with restart to measure the association between miRNAs and individual pathways. Independent validation shows that miRAnno achieves higher signal-to-noise ratio compared to the standard enrichment analysis., Availability and Implementation: miRAnno is freely available at https://ophid.utoronto.ca/miRAnno/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Physical activity is fundamental in the management of axial spondyloarthritis (SpA); however, evidence suggests that patients with axial SpA are not adhering to physical activity recommendations. E-health technology (e.g., telephone reminders and mobile text messaging) can increase participation in physical activity. The aims of this study were as follows: 1) to understand perspectives of the importance of physical activity in the management of axial SpA; 2) to describe factors associated with physical activity adherence; and 3) to explore the role of e-health technology to facilitate physical activity in patients with axial SpA., Methods: Semistructured interviews were conducted with axial SpA patients attending an urban academic rheumatology clinic. Interviews were audio recorded and transcribed verbatim. Data were analyzed using thematic principles. Systematic labeling of the data set was completed using an inductive approach until saturation of emergent themes., Results: Twelve patient interviews were completed. Most respondents were male (83.3%) with a mean ± SD age of 45.5 ± 12.5 years and a mean ± SD disease duration of 21.5 ± 14.9 years. Participants defined physical as any activity involving physical exertion. The role of physical activity in axial SpA management was well recognized and included symptom relief, pharmacologic synergy, and impact on general health. Motivators included a growth mindset, social support networks, and facility access. Barriers included fear of disease progression, life demands, and environmental restrictions. Feedback, electronic reminders, and virtual support networks were key components of e-health technology to facilitate engagement in physical activity., Conclusion: The results of this study provide a foundation to guide development of patient-centered e-health technology interventions to increase physical activity uptake in patients with axial SpA., (© 2021, American College of Rheumatology.)

Gene expression microarrays are one of the most widely used high-throughput technologies in molecular biology, with applications such as identification of disease mechanisms and development of diagnostic and prognostic gene signatures. However, the success of these tasks is often limited because microarray analysis does not account for the complex relationships among genes, their products, and overall signaling and regulatory cascades. Incorporating protein-protein interaction data into microarray analysis can help address these challenges. This chapter reviews how protein-protein interactions can help with microarray analysis, leading to benefits such as better explanations of disease mechanisms, more complete gene annotations, improved prioritization of genes for future experiments, and gene signatures that generalize better to new data., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)