Background: The sexual dimorphism represents one of the triggers of the metabolic disparities between the organisms, advising about wild implications in research or diagnostics contexts. Despite the mounting recognition of the importance of sex consideration in the biomedical fields, the identification of male- and female-specific metabolic signatures has not been achieved. Main body: This review pointed the focus on the metabolic differences related to the sex, evidenced by metabolomics studies performed on healthy populations, with the leading aim of understanding how the sex influences the baseline metabolome. The main shared signatures and the apparent dissimilarities between males and females were extracted and highlighted from the metabolome of the most commonly analyzed biological fluids, such as serum, plasma, and urine. Furthermore, the influence of age and the significant interactions between sex and age have been taken into account. Conclusions: The recognition of sex patterns in human metabolomics has been defined in diverse biofluids. The detection of sex- and age-related differences in the metabolome of healthy individuals are helpful for translational applications from the bench to the bedside to set targeted diagnostic and prevention approaches in the context of personalized medicine. Graphical

Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene–environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.

Omics-based technologies have been largely adopted during this unprecedented global COVID-19 pandemic, allowing the scientific community to perform research on a large scale to understand the pathobiology of the SARS-CoV-2 infection and its replication into human cells. The application of omics techniques has been addressed to every level of application, from the detection of mutations, methods of diagnosis or monitoring, drug target discovery, and vaccine generation, to the basic definition of the pathophysiological processes and the biochemical mechanisms behind the infection and spread of SARS-CoV-2. Thus, the term COVIDomics wants to include those efforts provided by omics-scale investigations with application to the current COVID-19 research. This review summarizes the diverse pieces of knowledge acquired with the application of COVIDomics techniques, with the main focus on proteomics and metabolomics studies, in order to capture a common signature in terms of proteins, metabolites, and pathways dysregulated in COVID-19 disease. Exploring the multiomics perspective and the concurrent data integration may provide new suitable therapeutic solutions to combat the COVID-19 pandemic.

Inborn errors of metabolism are genetic disorders due to impaired activity of enzymes, transporters, or cofactors resulting in accumulation of abnormal metabolites proximal to the metabolic block, lack of essential products or accumulation of by-products. Many of these disorders have serious clinical consequences for affected neonates, and an early diagnosis allows presymptomatic treatment which can prevent severe permanent sequelae and in some cases death. Expanded newborn screening for these diseases is a promising field of targeted metabolomics. Here we report the application, between 2007 and 2014, of this approach to the identification of newborns in southern Italy at risk of developing a potentially fatal disease. The analysis of amino acids and acylcarnitines in dried blood spots by tandem mass spectrometry revealed 24 affected newborns among 45 466 infants evaluated between 48 and 72 hours of life (overall incidence: 1 : 1894). Diagnoses of newborns with elevated metabolites were confirmed by gas chromatography-mass spectrometry, biochemical studies, and genetic analysis. Five infants were diagnosed with medium-chain acyl CoA dehydrogenase deficiency, 1 with methylmalonic acidemia with homocystinuria type CblC, 2 with isolated methylmalonic acidemia, 1 with propionic acidemia, 1 with isovaleric academia, 1 with isobutyryl-CoA dehydrogenase deficiency, 1 with beta ketothiolase deficiency, 1 with short branched chain amino acid deficiency, 1 with 3-methlycrotonyl-CoA carboxylase deficiency, 1 with formimino-transferase cyclodeaminase deficiency, and 1 with cystathionine-beta-synthase deficiency. Seven cases of maternal vitamin B₁₂ deficiency and 1 case of maternal carnitine uptake deficiency were detected. This study supports the widespread application of metabolomic-based newborn screening for these genetic diseases.

COVID-19 is a global threat that has spread since the end of 2019, causing severe clinical sequelae and deaths, in the context of a world pandemic. The infection of the highly pathogenetic and infectious SARS-CoV-2 coronavirus has been proven to exert systemic effects impacting the metabolism. Yet, the metabolic pathways involved in the pathophysiology and progression of COVID-19 are still unclear. Here, we present the results of a mass spectrometry-based targeted metabolomic analysis on a cohort of 52 hospitalized COVID-19 patients, classified according to disease severity as mild, moderate, and severe. Our analysis defines a clear signature of COVID-19 that includes increased serum levels of lactic acid in all the forms of the disease. Pathway analysis revealed dysregulation of energy production and amino acid metabolism. Globally, the variations found in the serum metabolome of COVID-19 patients may reflect a more complex systemic perturbation induced by SARS-CoV-2, possibly affecting carbon and nitrogen liver metabolism.

The pathogenic effects of Clostridium difficile are primarily attributable to the production of the large protein toxins (C difficile toxins [Tcd]) A (TcdA) and B (TcdB). These toxins monoglucosylate Rho GTPases in the cytosol of host cells, causing destruction of the actin cytoskeleton with cytotoxic effects. Low human serum albumin (HSA) levels indicate a higher risk of acquiring and developing a severe C difficile infection (CDI) and are associated with recurrent and fatal disease. We used a combined approach based on docking simulation and biochemical analyses that were performed in vitro on purified proteins and in human epithelial colorectal adenocarcinoma cells (Caco-2), and in vivo on stem cell-derived human intestinal organoids and zebrafish embryos. Our results show that HSA specifically binds via its domain II to TcdA and TcdB and thereby induces their autoproteolytic cleavage at physiological concentrations. This process impairs toxin internalization into the host cells and reduces the toxin-dependent glucosylation of Rho proteins. Our data provide evidence for a specific HSA-dependent self-defense mechanism against C difficile toxins and provide an explanation for the clinical correlation between CDI severity and hypoalbuminemia.