Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals.

BACKGROUND: Human viruses released into the environment can be detected and characterized in wastewater. The study of wastewater virome offers a consolidated perspective on the circulation of viruses within a population. Because the occurrence and severity of viral infections can vary across a person's lifetime, studying the virome in wastewater samples contributed by various demographic segments can provide valuable insights into the prevalence of viral infections within these segments. In our study, targeted enrichment sequencing was employed to characterize the human virome in wastewater at a building-level scale. This was accomplished through passive sampling of wastewater in schools, university settings, and nursing homes in two cities in Catalonia. Additionally, sewage from a large urban wastewater treatment plant was analysed to serve as a reference for examining the collective excreted human virome. RESULTS: The virome obtained from influent wastewater treatment plant samples showcased the combined viral presence from individuals of varying ages, with astroviruses and human bocaviruses being the most prevalent, followed by human adenoviruses, polyomaviruses, and papillomaviruses. Significant variations in the viral profiles were observed among the different types of buildings studied. Mamastrovirus 1 was predominant in school samples, salivirus and human polyomaviruses JC and BK in the university settings while nursing homes showed a more balanced distribution of viral families presenting papillomavirus and picornaviruses and, interestingly, some viruses linked to immunosuppression. CONCLUSIONS: This study shows the utility of building-level wastewater-based epidemiology as an effective tool for monitoring the presence of viruses circulating within specific age groups. It provides valuable insights for public health monitoring and epidemiological studies.

Predicting the Predicted: A Comparison of Machine Learning-Based Collision Cross-Section Prediction Models for Small Molecules.

The application of machine learning (ML) to -omics research is growing at an exponential rate owing to the increasing availability of large amounts of data for model training. Specifically, in metabolomics, ML has enabled the prediction of tandem mass spectrometry and retention time data. More recently, due to the advent of ion mobility, new ML models have been introduced for collision cross-section (CCS) prediction, but those have been trained with different and relatively small data sets covering a few thousands of small molecules, which hampers their systematic comparison. Here, we compared four existing ML-based CCS prediction models and their capacity to predict CCS values using the recently introduced METLIN-CCS data set. We also compared them with simple linear models and with ML models that used fingerprints as regressors. We analyzed the role of structural diversity of the data on which the ML models are trained with and explored the practical application of these models for metabolite annotation using CCS values. Results showed a limited capability of the existing models to achieve the necessary accuracy to be adopted for routine metabolomics analysis. We showed that for a particular molecule, this accuracy could only be improved when models were trained with a large number of structurally similar counterparts. Therefore, we suggest that current annotation capabilities will only be significantly altered with models trained with heterogeneous data sets composed of large homogeneous hubs of structurally similar molecules to those being predicted.

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies.

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

Brain N-Glycosylation and Lipidomic Profile Changes Induced by a High-Fat Diet in Dyslipidemic Hamsters.

The consumption of diets rich in saturated fats is known to be associated with higher mortality. The adoption of healthy habits, for instance adhering to a Mediterranean diet, has proved to exert a preventive effect towards cardiovascular diseases and dyslipidemia. Little is known about how a suboptimal diet can affect brain function, structure, and the mechanisms involved. The aims of this study were to examine how a high-fat diet can alter the brain N-glycan and lipid profile in male Golden Syrian hamsters and to evaluate the potential of a Mediterranean-like diet to reverse this situation. During twelve weeks, hamsters were fed a normal fat diet (CTRL group), a high-fat diet (HFD group), and a high-fat diet followed by a Mediterranean-like diet (MED group). Out of seventy-two identified N-glycans, fourteen were significant (p < 0.05) between HFD and CTRL groups, nine between MED and CTRL groups, and one between MED and HFD groups. Moreover, forty-nine lipids were altered between HFD and CTRL groups, seven between MED and CTRL groups, and five between MED and HFD groups. Our results suggest that brain N-glycan composition in high-fat diet-fed hamsters can produce events comparable to those found in some neurodegenerative diseases, and may promote brain ageing.

Single and Joined Behaviour of Circulating Biomarkers and Metabolic Parameters in High-Fit and Low-Fit Healthy Females.

Biomarkers are important in the assessment of health and disease, but are poorly studied in still healthy individuals with a (potential) different risk for metabolic disease. This study investigated, first, how single biomarkers and metabolic parameters, functional biomarker and metabolic parameter categories, and total biomarker and metabolic parameter profiles behave in young healthy female adults of different aerobic fitness and, second, how these biomarkers and metabolic parameters are affected by recent exercise in these healthy individuals. A total of 102 biomarkers and metabolic parameters were analysed in serum or plasma samples from 30 young, healthy, female adults divided into a high-fit (V̇O2peak ≥ 47 mL/kg/min, N = 15) and a low-fit (V̇O2peak ≤ 37 mL/kg/min, N = 15) group, at baseline and overnight after a single bout of exercise (60 min, 70% V̇O2peak). Our results show that total biomarker and metabolic parameter profiles were similar between high-fit and low-fit females. Recent exercise significantly affected several single biomarkers and metabolic parameters, mostly related to inflammation and lipid metabolism. Furthermore, functional biomarker and metabolic parameter categories corresponded to biomarker and metabolic parameter clusters generated via hierarchical clustering models. In conclusion, this study provides insight into the single and joined behavior of circulating biomarkers and metabolic parameters in healthy females, and identified functional biomarker and metabolic parameter categories that may be used for the characterisation of human health physiology.

Gut Microbiome and Small RNA Integrative-Omic Perspective of Meconium and Milk-FED Infant Stool Samples.

The human gut microbiome plays an important role in health, and its initial development is conditioned by many factors, such as feeding. It has also been claimed that this colonization is guided by bacterial populations, the dynamic virome, and transkingdom interactions between host and microbial cells, partially mediated by epigenetic signaling. In this article, we characterized the bacteriome, virome, and smallRNome and their interaction in the meconium and stool samples from infants. Bacterial and viral DNA and RNA were extracted from the meconium and stool samples of 2- to 4-month-old milk-fed infants. The bacteriome, DNA and RNA virome, and smallRNome were assessed using 16S rRNA V4 sequencing, viral enrichment sequencing, and small RNA sequencing protocols, respectively. Data pathway analysis and integration were performed using the R package mixOmics. Our findings showed that the bacteriome differed among the three groups, while the virome and smallRNome presented significant differences, mainly between the meconium and stool of milk-fed infants. The gut environment is rapidly acquired after birth, and it is highly adaptable due to the interaction of environmental factors. Additionally, transkingdom interactions between viruses and bacteria can influence host and smallRNome profiles. However, virome characterization has several protocol limitations that must be considered.

Optimization of a GC-MS Injection-Port Derivatization Methodology to Enhance Metabolomics Analysis Throughput in Biological Samples.

Advances in metabolomics analysis and data treatment increase the knowledge of complex biological systems. One of the most used methodologies is gas chromatography-mass spectrometry (GC-MS) due to its robustness, high separation efficiency, and reliable peak identification through curated databases. However, methodologies are not standardized, and the derivatization steps in GC-MS can introduce experimental errors and take considerable time, exposing the samples to degradation. Here, we propose the injection-port derivatization (IPD) methodology to increase the throughput in plasma metabolomics analysis by GC-MS. The IPD method was evaluated and optimized for different families of metabolites (organic acids, amino acids, fatty acids, sugars, sugar phosphates, etc.) in terms of residence time, injection-port temperature, and sample/derivatization reagent ratio. Finally, the method's usefulness was validated in a study consisting of a cohort of obese patients with or without nonalcoholic steatohepatitis. Our results show a fast, reproducible, precise, and reliable method for the analysis of biological samples by GC-MS. Raw data are publicly available at MetaboLights with Study Identifier MTBLS5151.

Effects of hesperidin in orange juice on blood and pulse pressures in mildly hypertensive individuals: a randomized controlled trial (Citrus study).

PURPOSE: To assess the sustained and acute effects, as well as the influence of sustained consumption on the acute effects, of orange juice (OJ) with a natural hesperidin content and hesperidin-enriched OJ (EOJ) on blood (BP) and pulse (PP) pressures in pre- and stage-1 hypertensive individuals. METHODS: In a randomized, parallel, double-blind, placebo-controlled trial, participants (n = 159) received 500 mL/day of control drink, OJ, or EOJ for 12 weeks. Two dose-response studies were performed at baseline and after 12 weeks. RESULTS: A single EOJ dose (500 mL) reduced systolic BP (SBP) and PP, with greater changes after sustained treatment where a decrease in diastolic BP (DBP) also occurred (P < 0.05). SBP and PP decreased in a dose-dependent manner relative to the hesperidin content of the beverages throughout the 12 weeks (P < 0.05). OJ and EOJ decreased homocysteine levels at 12 weeks versus the control drink (P < 0.05). After 12 weeks of EOJ consumption, four genes related to hypertension (PTX3, NLRP3, NPSR1 and NAMPT) were differentially expressed in peripheral blood mononuclear cells (P < 0.05). CONCLUSION: Hesperidin in OJ reduces SBP and PP after sustained consumption, and after a single dose, the chronic consumption of EOJ enhances its postprandial effect. Decreases in systemic and transcriptomic biomarkers were concomitant with BP and PP changes. EOJ could be a useful co-adjuvant tool for BP and PP management in pre- and stage-1 hypertensive individuals.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis.

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

Gelsolin: a new biomarker of disease activity in SLE patients associated with HDL-c.

OBJECTIVES: To identify potential biomarkers of disease activity analysing the proteome of high-density lipoprotein (HDL) particles from SLE patients in clinical remission and when they develop a flare compared with a healthy control group. METHODS: Quantitative proteomic analyses of purified HDL were performed using Tandem Mass Tag isobaric tag-labelling and nanoLC-Orbitrap (nLC-MS/MS) from nine SLE patients in clinical remission when they developed a flare and from nine healthy controls (9-9-9). We verified the identified proteins by Western blot and ELISA in a cohort of 104 SLE women patients, 46 healthy women and 14 SLE patients when a flare developed. RESULTS: We found 17 proteins with a significant fold-change (>1.1) compared with the control group. In lupus patients experiencing a flare compared with those in remission, we identified four proteins with a significant fold-change (C4, Indian Hedgehog protein, S100A8 and gelsolin). Plasma gelsolin (pGSN) levels were decreased in the 104 SLE patients (176.02(74.9) mcg/l) compared with the control group (217.13(86.7) mcg/l); P=0.005 and when they developed a clinical flare (104.84(41.7) mcg/l); P=0.002). pGSN levels were associated with HDL cholesterol levels (r = 0.316, P<0.001). Antimalarial treated patients showed significant higher levels of pGSN (214.56(88.94) mcg/l regarding 170.35(66.36) mcg/l); P = 0.017. CONCLUSION: Decreased pGSN are associated with clinical disease activity in SLE patients. Antimalarial treatment and HDL cholesterol are associated with higher levels of pGSN.

Multi-omics approach to elucidate the gut microbiota activity: Metaproteomics and metagenomics connection.

Over the last few years, the application of high-throughput meta-omics methods has provided great progress in improving the knowledge of the gut ecosystem and linking its biodiversity to host health conditions, offering complementary support to classical microbiology. Gut microbiota plays a crucial role in relevant diseases such as obesity or cardiovascular disease (CVD), and its regulation is closely influenced by several factors, such as dietary composition. In fact, polyphenol-rich diets are the most palatable treatment to prevent hypertension associated with CVD, although the polyphenol-microbiota interactions have not been completely elucidated. For this reason, the aim of this study was to evaluate microbiota effect in obese rats supplemented by hesperidin, after being fed with cafeteria or standard diet, using a multi meta-omics approaches combining strategy of metagenomics and metaproteomics analysis. We reported that cafeteria diet induces obesity, resulting in changes in the microbiota composition, which are related to functional alterations at proteome level. In addition, hesperidin supplementation alters microbiota diversity and also proteins involved in important metabolic pathways. Overall, going deeper into strategies to integrate omics sciences is necessary to understand the complex relationships between the host, gut microbiota, and diet.

Proteomic Profile of Unstable Atheroma Plaque: Increased Neutrophil Defensin 1, Clusterin, and Apolipoprotein E Levels in Carotid Secretome.

Because of the clinical significance of carotid atherosclerosis, the search for novel biomarkers has become a priority. The aim of the present study was to compare the protein secretion profile of the carotid atherosclerotic plaque (CAP, n = 12) and nonatherosclerotic mammary artery (MA, n = 10) secretomes. We used a nontargeted proteomic approach that incorporated tandem immunoaffinity depletion, iTRAQ labeling, and nanoflow liquid chromatography coupled to high-resolution mass spectrometry. In total, 162 proteins were quantified, of which 25 showed statistically significant differences in secretome levels between carotid atherosclerotic plaque and nondiseased mammary artery. We found increased levels of neutrophil defensin 1, apolipoprotein E, clusterin, and zinc-alpha-2-glycoprotein in CAP secretomes. Results were validated by ELISA assays. Also, differentially secreted proteins are involved in pathways such as focal adhesion and leukocyte transendothelial migration. In conclusion, this study provides a subset of identified proteins that are differently expressed in secretomes of clinical significance.

New insights into circulating FABP4: Interaction with cytokeratin 1 on endothelial cell membranes.

Fatty acid-binding protein 4 (FABP4) is an adipose tissue-secreted adipokine that is involved in the regulation of energetic metabolism and inflammation. Increased levels of circulating FABP4 have been detected in individuals with cardiovascular risk factors. Recent studies have demonstrated that FABP4 has a direct effect on peripheral tissues, specifically promoting vascular dysfunction; however, its mechanism of action is unknown. The objective of this work was to assess the specific interactions between exogenous FABP4 and the plasma membranes of endothelial cells. Immunofluorescence assays showed that exogenous FABP4 localized along the plasma membranes of human umbilical vein endothelial cells (HUVECs), interacting specifically with plasma membrane proteins. Anti-FABP4 immunoblotting revealed two covalent protein complexes containing FABP4 and its putative receptor; these complexes were approximately 108 kDa and 77 kDa in size. Proteomics and mass spectrometry experiments revealed that cytokeratin 1 (CK1) was the FABP4-binding protein. An anti-CK1 immunoblot confirmed the presence of CK1. FABP4-CK1 complexes were also detected in HAECs, HCASMCs, HepG2 cells and THP-1 cells. Pharmacological FABP4 inhibition by BMS309403 results in a slight decrease in the formation of these complexes, indicating that fatty acids may play a role in FABP4 functionality. In addition, we demonstrated that exogenous FABP4 crosses the plasma membrane to enter the cytoplasm and nucleus in HUVECs. These findings indicate that exogenous FABP4 interacts with plasma membrane proteins, specifically CK1. These data contribute to our current knowledge regarding the mechanism of action of circulating FABP4.

Foodomics imaging by mass spectrometry and magnetic resonance.

This work explores the use of advanced imaging MS (IMS) and magnetic resonance imaging (MRI) techniques in food science and nutrition to evaluate food sensory characteristics, nutritional value and health benefits. Determining the chemical content and applying imaging tools to food metabolomics offer detailed information about food quality, safety, processing, storage and authenticity assessment. IMS and MRI are powerful analytical systems with an excellent capability for mapping the distribution of many molecules, and recent advances in these platforms are reviewed and discussed, showing the great potential of these techniques for small molecule-based food metabolomics research.

Exploring the Relationship between Diamine Oxidase and Psychotropic Medications in Fibromyalgia Treatment, Finding No Reduction in Diamine Oxidase Levels and Activity except with Citalopram.

Background: Histamine intolerance manifests when there is an imbalance between the production of histamine and the body's capacity to metabolise it. Within the gastrointestinal tract, diamine oxidase (DAO) plays a pivotal role in breaking down ingested histamine. Insufficient levels of DAO have been linked to various diseases affecting the respiratory, cardiovascular, nervous, muscular, and digestive systems; some of these symptoms are evidenced in fibromyalgia syndrome. This underscores the crucial role of DAO in maintaining the histamine balance and highlights its association with diverse physiological systems and health conditions. The management of fibromyalgia commonly involves the use of psychotropic medications; however, their potential interactions with DAO remain not fully elucidated. Methods: This study delved into the influence of various psychotropic medications on DAO activity through in vitro experiments. Additionally, we explored their impact on the human intestinal cell line Caco-2, examining alterations in DAO expression at both the mRNA and protein levels along with DAO activity. Results: Notably, the examined drugs-sertraline, pregabalin, paroxetine, alprazolam, and lorazepam-did not exhibit inhibitory effects on DAO activity or lead to reductions in DAO levels. In contrast, citalopram demonstrated a decrease in DAO activity in in vitro assays without influencing DAO levels and activity in human enterocytes. Conclusions: These findings imply that a collaborative approach involving psychotropic medications and DAO enzyme supplementation for individuals with fibromyalgia and a DAO deficiency could offer potential benefits for healthcare professionals in their routine clinical practice.

Target enrichment metaviromics enables comprehensive surveillance of coronaviruses in environmental and animal samples.

The COVID-19 pandemic has underscored the importance of understanding the role of animals in the transmission of coronaviruses (CoVs) and their impact on human health. A One Health approach, integrating human, animal, and environmental health, is essential for effective CoVs control. Next-generation sequencing has played a pivotal role in identifying and monitoring the evolution of novel CoVs strains, like SARS-CoV-2. However, viral occurrence and diversity studies in environmental and animal samples are challenging because of the complexity of viral communities and low abundance of viruses in these samples. Target enrichment sequencing (TES) has emerged as a valuable tool for investigating viral families in challenging samples. This approach involves the specific capture and enrichment of viral genomes using sequence-specific probes, thereby enhancing the efficiency of detection and characterization. In this study, we aimed to develop and validate a TES panel to study CoVs in various complex environmental and animal derived samples. The results demonstrated the panel's effectiveness in capturing and sequencing a wide diversity of CoVs providing valuable insights into their abundance and host diversity in urban wastewater, farm animal corpses lixiviates and bat guano samples. In sewage samples, CoVs were detected solely when TES was employed while in guano samples, sequencing of CoVs species was achieved in 2 out of 4 samples showing an almost three-logarithmic increase in the number of reads obtained in comparison with the untargeted approach. For animal lixiviates, only the TES application enabled the acquisition of CoVs reads. The information obtained can significantly contribute to early detection, surveillance, and control measures for CoVs, including viral discovery and potential spillover events. Additionally, this sequencing panel shows potential for studying other significant viral families and monitoring viral diversity in different animal populations.

A red-fleshed apple rich in anthocyanins improves endothelial function, reduces inflammation, and modulates the immune system in hypercholesterolemic subjects: the AppleCOR study.

The study determines the sustained and acute effects of a red-fleshed apple (RFA), rich in anthocyanins (ACNs), a white-fleshed apple (WFA) without ACNs, and an infusion from Aronia melanocarpa (AI) with an equivalent content of ACNs as RFA, on different cardiometabolic risk biomarkers in hypercholesterolemic subjects. A randomized, parallel study was performed for 6 weeks and two dose-response studies were performed at the baseline and after intervention. At 6 weeks, RFA consumption improved ischemic reactive hyperemia and decreased C-reactive protein and interleukine-6 compared to WFA consumption. Moreover, at 6 weeks, AI decreased P-selectin compared to WFA and improved the lipid profile. Three products reduced C1q, C4 and Factor B, and RFA and AI reduced C3. Although both RFA and AI have a similar ACN content, RFA, by a matrix effect, induced more improvements in inflammation, whereas AI improved the lipid profile. Anti-inflammatory protein modulation by proteomic reduction of the complement system and immunoglobulins were verified after WFA, AI and RFA consumption.

A single-blinded, randomized, parallel intervention to evaluate genetics and omics-based personalized nutrition in general population via an e-commerce tool: The PREVENTOMICS e-commerce study.

BACKGROUND: Personalized nutrition (PN) has been proposed as a strategy to increase the effectiveness of dietary recommendations and ultimately improve health status. OBJECTIVES: We aimed to assess whether including omics-based PN in an e-commerce tool improves dietary behavior and metabolic profile in general population. METHODS: A 21-wk parallel, single-blinded, randomized intervention involved 193 adults assigned to a control group following Mediterranean diet recommendations (n = 57, completers = 36), PN (n = 70, completers = 45), or personalized plan (PP, n = 68, completers = 53) integrating a behavioral change program with PN recommendations. The intervention used metabolomics, proteomics, and genetic data to assist participants in creating personalized shopping lists in a simulated e-commerce retailer portal. The primary outcome was the Mediterranean diet adherence screener (MEDAS) score; secondary outcomes included biometric and metabolic markers and dietary habits. RESULTS: Volunteers were categorized with a scoring system based on biomarkers of lipid, carbohydrate metabolism, inflammation, oxidative stress, and microbiota, and dietary recommendations delivered accordingly in the PN and PP groups. The intervention significantly increased MEDAS scores in all volunteers (control-3 points; 95% confidence interval [CI]: 2.2, 3.8; PN-2.7 points; 95% CI: 2.0, 3.3; and PP-2.8 points; 95% CI: 2.1, 3.4; q < 0.001). No significant differences were observed in dietary habits or health parameters between PN and control groups after adjustment for multiple comparisons. Nevertheless, personalized recommendations significantly (false discovery rate < 0.05) and selectively enhanced the scores calculated with biomarkers of carbohydrate metabolism (ß: -0.37; 95% CI: -0.56, -0.18), oxidative stress (ß: -0.37; 95% CI: -0.60, -0.15), microbiota (ß: -0.38; 95% CI: -0.63, -0.15), and inflammation (ß: -0.78; 95% CI: -1.24, -0.31) compared with control diet. CONCLUSIONS: Integration of personalized strategies within an e-commerce-like tool did not enhance adherence to Mediterranean diet or improved health markers compared with general recommendations. The metabotyping approach showed promising results and more research is guaranteed to further promote its application in PN. This trial was registered at clinicaltrials.gov as NCT04641559 (https://clinicaltrials.gov/study/NCT04641559?cond=NCT04641559&rank=1).

Fucosylated N-glycans as early biomarkers of COVID-19 severity.

Background: The pathological mechanisms of SARS-CoV-2 in humans remain unclear and the unpredictability of COVID-19 progression may be attributed to the absence of biomarkers that contribute to the prognosis of this disease. Therefore, the discovery of biomarkers is needed for reliable risk stratification and to identify patients who are more likely to progress to a critical stage. Methods: Aiming to identify new biomarkers we analysed N-glycan traits in plasma from 196 patients with COVID-19. Samples were classified into three groups according to their severity (mild, severe and critical) and obtained at diagnosis (baseline) and at 4 weeks of follow-up (postdiagnosis), to evaluate their behaviour through disease progression. N-glycans were released with PNGase F and labelled with Rapifluor-MS, followed by their analysis by LC-MS/MS. The Simglycan structural identification tool and Glycostore database were employed to predict the structure of glycans. Results: We determined that plasma from SARS-CoV-2-infected patients display different N-glycosylation profiles depending on the disease severity. Specifically, levels of fucosylation and galactosylation decreased with increasing severity and Fuc1Hex5HexNAc5 was identified as the most suitable biomarker to stratify patients at diagnosis and distinguish mild from critical outcomes. Conclusion: In this study we explored the global plasma glycosignature, reflecting the inflammatory state of the organs during the infectious disease. Our findings show the promising potential of glycans as biomarkers of COVID-19 severity.

Interaction of Diamine Oxidase with Psychostimulant Drugs for ADHD Management.

Histamine intolerance occurs when there is an imbalance between histamine production and the capacity for histamine degradation. Diamine oxidase (DAO) is the main enzyme for the catabolism of ingested histamine degradation in the gastrointestinal tract and its deficiency has been linked to allergy-like symptoms. Psychostimulant drugs are commonly used to treat Attention Deficit Hyperactivity Disorder (ADHD), but their interaction with DAO is not well characterized. In this work, we evaluated the effects of psychostimulant drugs (methylphenidate and lisdexamfetamine) on in vitro DAO activity and in the human cell line of enterocytes (Caco-2), evaluating DAO expression (mRNA and protein) and DAO activity. Methylphenidate and lisdexamfetamine did not repress the in vitro DAO activity. In addition, in Caco-2 cells, lisdexamfetamine promoted a strong upregulation of DAO mRNA levels, whereas methylphenidate tended to induce DAO activity. To sum up, methylphenidate and lisdexamfetamine treatments do not reduce DAO activity. These findings could be useful for physicians prescribing these two drugs to ADHD patients affected by DAO deficiency.