Circulating acetylated polyamines correlate with Covid-19 severity in cancer patients

Impact of COVID-19 on sperm quality and the prostaglandin and polyamine systems in the seminal fluid

BACKGROUND

The implications of SARS-CoV-2 infection on male fertility remain largely unknown. Besides their well-known pro- and anti-inflammatory actions, prostaglandins and polyamines are present in semen, where they play key roles in sperm quality.

OBJECTIVES

To analyze semen parameters, oxidative profile and the seminal fluid prostaglandin and polyamine systems in samples collected from individuals without coronavirus disease 2019 diagnosis and men who recovered from coronavirus disease 2019.

MATERIALS AND METHODS

This study compared semen collected from men without positive coronavirus disease 2019 diagnosis with samples obtained from individuals 1-6 months and 7-30 months post SARS-CoV-2 infection. Semen parameters, thiobarbituric acid reactive substances, cyclooxygenase 2 expression by fluorescence immunocytochemistry and immunoblotting, prostaglandin levels by enzyme immunoassay, ornithine decarboxylase activity by a radioactive assay, and polyamine and acetylated polyamine levels by thin-layer chromatography were assessed.

RESULTS

In both groups of semen samples from coronavirus disease 2019 recovered men, sperm vitality, total and progressive sperm motility, and putrescine levels were significantly decreased when compared with samples from the uninfected group. In contrast, lipid peroxidation, leukocyte-associated cyclooxygenase 2 expression, and prostaglandin D2 levels were higher in semen from coronavirus disease 2019 recovered men than in samples from uninfected individuals. While sperm concentration and morphology, ornithine decarboxylase activity, and N-acetylputrescine levels were statistically diminished in semen obtained up to 6 months after coronavirus disease 2019 recovery, these parameters remained unchanged when samples were collected 7-30 months after coronavirus disease 2019 recovery. Coronavirus disease 2019 vaccination did not show negative effects on any of the parameters evaluated.

DISCUSSION AND CONCLUSION

Our work provides insights into the detrimental impact of coronavirus disease 2019 on several sperm parameters, in some cases, even more than a year after SARS-CoV-2 infection, which would be accompanied by alterations in the seminal fluid prostaglandin and polyamine profiles. Therefore, future treatments targeting the prostaglandin and polyamine pathways in coronavirus disease 2019 recovered men could lead to a successful reinstatement of semen parameters.

Investigating the pathogenesis of vitreous in postmortem COVID patients via untargeted metabolomics based bioinformatics model

SARS-CoV-2 virus has become a worldwide pandemic causing millions of death. This severe disaster lead to a immense panic and stress all over the world. Several studies were dedicated to understand its mechanism, pathogenesis and spreading characteristics. By this way, scientists try to develop different therapy and diagnose strategies. For these reasons, several metabolomics, proteomics and genomics studies were also carried out to improve knowledge in this newly identified virus. In this study, we are aimed to explain the pathogenesis of SARS-CoV-2 exposure on postmortem COVID (+) patients via untargeted metabolomics analysis. To carry out this study, a Data Independent Acquisition SWATH method is optimized and performed. Vitreous samples were analyzed in both MS1 and MS2 ESI(+) mode. An orthogonal Partial Least Square Discriminant Analysis were performed for classification. It was observed that lipid metabolism, several amino acids and oxidative stress biomarkers were strongly affected due to high inflammation and possible cytokine storm.

Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography-Mass Spectrometry (LC-MS)

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.

COVID-19 and Comorbidities: What Has Been Unveiled by Metabolomics?

The COVID-19 pandemic has brought about diverse impacts on the global population. Individuals with comorbidities were more susceptible to the severe symptoms caused by the virus. Within the crisis scenario, metabolomics represents a potential area of science capable of providing relevant information for understanding the metabolic pathways associated with the intricate interaction between the viral disease and previous comorbidities. This work aims to provide a comprehensive description of the scientific production pertaining to metabolomics within the specific context of COVID-19 and comorbidities, while highlighting promising areas for exploration by those interested in the subject. In this review, we highlighted the studies of metabolomics that indicated a variety of metabolites associated with comorbidities and COVID-19. Furthermore, we observed that the understanding of the metabolic processes involved between comorbidities and COVID-19 is limited due to the urgent need to report disease outcomes in individuals with comorbidities. The overlap of two or more comorbidities associated with the severity of COVID-19 hinders the comprehension of the significance of each condition. Most identified studies are observational, with a restricted number of patients, due to challenges in sample collection amidst the emergent situation.

Human trials exploring anti-aging medicines

Here, we summarize the current knowledge on eight promising drugs and natural compounds that have been tested in the clinic: metformin, NAD+ precursors, glucagon-like peptide-1 receptor agonists, TORC1 inhibitors, spermidine, senolytics, probiotics, and anti-inflammatories. Multiple clinical trials have commenced to evaluate the efficacy of such agents against age-associated diseases including diabetes, cardiovascular disease, cancer, and neurodegenerative diseases. There are reasonable expectations that drugs able to decelerate or reverse aging processes will also exert broad disease-preventing or -attenuating effects. Hence, the outcome of past, ongoing, and future disease-specific trials may pave the way to the development of new anti-aging medicines. Drugs approved for specific disease indications may subsequently be repurposed for the treatment of organism-wide aging consequences.

Lipidomics for diagnosis and prognosis of pulmonary hypertension

Background

Pulmonary hypertension (PH) poses a significant health threat with high morbidity and mortality, necessitating improved diagnostic tools for enhanced management. Current biomarkers for PH lack functionality and comprehensive diagnostic and prognostic capabilities. Therefore, there is a critical need to develop biomarkers that address these gaps in PH diagnostics and prognosis.

Methods

To address this need, we employed a comprehensive metabolomics analysis in 233 blood based samples coupled with machine learning analysis. For functional insights, human pulmonary arteries (PA) of idiopathic pulmonary arterial hypertension (PAH) lungs were investigated and the effect of extrinsic FFAs on human PA endothelial and smooth muscle cells was tested in vitro.

Results

PA of idiopathic PAH lungs showed lipid accumulation and altered expression of lipid homeostasis-related genes. In PA smooth muscle cells, extrinsic FFAs caused excessive proliferation and endothelial barrier dysfunction in PA endothelial cells, both hallmarks of PAH.In the training cohort of 74 PH patients, 30 disease controls without PH, and 65 healthy controls, diagnostic and prognostic markers were identified and subsequently validated in an independent cohort. Exploratory analysis showed a highly impacted metabolome in PH patients and machine learning confirmed a high diagnostic potential. Fully explainable specific free fatty acid (FFA)/lipid-ratios were derived, providing exceptional diagnostic accuracy with an area under the curve (AUC) of 0.89 in the training and 0.90 in the validation cohort, outperforming machine learning results. These ratios were also prognostic and complemented established clinical prognostic PAH scores (FPHR4p and COMPERA2.0), significantly increasing their hazard ratios (HR) from 2.5 and 3.4 to 4.2 and 6.1, respectively.

Conclusion

In conclusion, our research confirms the significance of lipidomic alterations in PH, introducing innovative diagnostic and prognostic biomarkers. These findings may have the potential to reshape PH management strategies.

Metabolomics-directed nanotechnology in viral diseases management: COVID-19 a case study

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently regarded as the twenty-first century's plague accounting for coronavirus disease 2019 (COVID-19). Besides its reported symptoms affecting the respiratory tract, it was found to alter several metabolic pathways inside the body. Nanoparticles proved to combat viral infections including COVID-19 to demonstrate great success in developing vaccines based on mRNA technology. However, various types of nanoparticles can affect the host metabolome. Considering the increasing proportion of nano-based vaccines, this review compiles and analyses how COVID-19 and nanoparticles affect lipids, amino acids, and carbohydrates metabolism. A search was conducted on PubMed, ScienceDirect, Web of Science for available information on the interrelationship between metabolomics and immunity in the context of SARS-CoV-2 infection and the effect of nanoparticles on metabolite levels. It was clear that SARS-CoV-2 disrupted several pathways to ensure a sufficient supply of its building blocks to facilitate its replication. Such information can help in developing treatment strategies against viral infections and COVID-19 based on interventions that overcome these metabolic changes. Furthermore, it showed that even drug-free nanoparticles can exert an influence on biological systems as evidenced by metabolomics.

Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy

Oncogenesis is associated with intestinal dysbiosis, and stool shotgun metagenomic sequencing in individuals with this condition might constitute a non-invasive approach for the early diagnosis of several cancer types. The prognostic relevance of antibiotic intake and gut microbiota composition urged investigators to develop tools for the detection of intestinal dysbiosis to enable patient stratification and microbiota-centred clinical interventions. Moreover, since the advent of immune-checkpoint inhibitors (ICIs) in oncology, the identification of biomarkers for predicting their efficacy before starting treatment has been an unmet medical need. Many previous studies addressing this question, including a meta-analysis described herein, have led to the description of Gut OncoMicrobiome Signatures (GOMS). In this Review, we discuss how patients with cancer across various subtypes share several GOMS with individuals with seemingly unrelated chronic inflammatory disorders who, in turn, tend to have GOMS different from those of healthy individuals. We discuss findings from the aforementioned meta-analysis of GOMS patterns associated with clinical benefit from or resistance to ICIs across different cancer types (in 808 patients), with a focus on metabolic and immunological surrogate markers of intestinal dysbiosis, and propose practical guidelines to incorporate GOMS in decision-making for prospective clinical trials in immuno-oncology.

Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis

Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Integrated proteomics and metabolomics analysis revealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our integrated analysis provides a multidimensional understanding of SA-AKI and identifies potential pathways for this condition.

Diagnostic, Prognostic and Mechanistic Biomarkers of COVID-19 Identified by Mass Spectrometric Metabolomics

A number of studies have assessed the impact of SARS-CoV-2 infection and COVID-19 severity on the metabolome of exhaled air, saliva, plasma, and urine to identify diagnostic and prognostic biomarkers. In spite of the richness of the literature, there is no consensus about the utility of metabolomic analyses for the management of COVID-19, calling for a critical assessment of the literature. We identified mass spectrometric metabolomic studies on specimens from SARS-CoV2-infected patients and subjected them to a cross-study comparison. We compared the clinical design, technical aspects, and statistical analyses of published studies with the purpose to identify the most relevant biomarkers. Several among the metabolites that are under- or overrepresented in the plasma from patients with COVID-19 may directly contribute to excessive inflammatory reactions and deficient immune control of SARS-CoV2, hence unraveling important mechanistic connections between whole-body metabolism and the course of the disease. Altogether, it appears that mass spectrometric approaches have a high potential for biomarker discovery, especially if they are subjected to methodological standardization.

Psychotropic drugs interaction with the lipid nanoparticle of COVID-19 mRNA therapeutics

The messenger RNA (mRNA) vaccines for COVID-19, Pfizer-BioNTech and Moderna, were authorized in the US on an emergency basis in December of 2020. The rapid distribution of these therapeutics around the country and the world led to millions of people being vaccinated in a short time span, an action that decreased hospitalization and death but also heightened the concerns about adverse effects and drug-vaccine interactions. The COVID-19 mRNA vaccines are of particular interest as they form the vanguard of a range of other mRNA therapeutics that are currently in the development pipeline, focusing both on infectious diseases as well as oncological applications. The Vaccine Adverse Event Reporting System (VAERS) has gained additional attention during the COVID-19 pandemic, specifically regarding the rollout of mRNA therapeutics. However, for VAERS, absence of a reporting platform for drug-vaccine interactions left these events poorly defined. For example, chemotherapy, anticonvulsants, and antimalarials were documented to interfere with the mRNA vaccines, but much less is known about the other drugs that could interact with these therapeutics, causing adverse events or decreased efficacy. In addition, SARS-CoV-2 exploitation of host cytochrome P450 enzymes, reported in COVID-19 critical illness, highlights viral interference with drug metabolism. For example, patients with severe psychiatric illness (SPI) in treatment with clozapine often displayed elevated drug levels, emphasizing drug-vaccine interaction.