Metabolic Signatures Associated with Severity in Hospitalized COVID-19 Patients

Metabolomic profiling of cannabis use and cannabis intoxication in humans

Acute intoxication from Δ9-tetrahydrocannabinol (THC, the primary active ingredient of cannabis) can lead to neurocognitive impairment and interference with day-to-day operations, such as driving. Present evaluations of THC-induced impairment in legal settings rely on biological drug tests that solely establish cannabis use, rather than cannabis impairment. The current study evaluated the metabolome in blood collected from occasional and chronic cannabis users (N = 35) at baseline and following treatments with cannabis (300 μg/kg THC) and placebo, with the aim to identify unique metabolic alterations that are associated with acute cannabis intoxication and cannabis use frequency. Blood samples were collected at baseline and repeatedly during 70 min after treatment. Sustained attention performance and ratings of subjective high were taken twice within 40 min after treatment. Metabolomic fingerprints of occasional and chronic cannabis users were distinctly different at baseline, when both groups were not intoxicated. A total of 14 metabolites, mainly related to endocannabinoid and amino acid metabolism, were identified that distinguished chronic from occasional cannabis users and that yielded a discriminant analysis model with an 80% classification rate (95% CI: 61-91%). Distinct metabolomic fingerprints were found for occasional cannabis users who, in contrast to chronic cannabis users, showed attentional impairment and elevated ratings of subjective high during cannabis intoxication. These included increments in organic acids, β-hydroxybutyrate and second messenger ceramides. The current study demonstrates the feasibility of the metabolomics approach to identify metabolic changes that are specific to the neurocognitive state of cannabis intoxication and to the history of cannabis use.

Profile of steroid metabolites in human breast milk in different stages of lactation

Breast milk (BM), as an optimal food, provides the newborn with a variety of minor compounds relevant for health and wellbeing. Endogenous steroids, also minor constituents, are mainly secreted in BM as conjugated metabolites. Recent research has revealed the relevance of steroid conjugates in many physiological processes. Thus, their presence in BM appears to be very intriguing, especially in relation to breastfeeding. The objective of our study was to profile conjugated steroid metabolites present in BM in relation to the lactation stage, and to promote further evaluation of their importance in breastfeeding. For this purpose, we developed and used a direct UHPLC-MS/MS metabolomics approach capable to detect more than 60 conjugated metabolites (mono-sulfated, mono-glucuronylated, bis-sulfated and sulfate-glucuronylated) from all steroid families. We compared the occurrence of these metabolites in samples collected from breastfeeding mothers and stratified by lactation stages: colostrum, transitional and mature milk. Our results showed that many biologically relevant conjugated steroids are secreted in BM. Their concentrations were highest in colostrum, decreased remarkably in transitional and were much lower in mature milk, with some exceptions. The profile of metabolites also differed considerably between lactation stages. The approximate daily secretion in BM indicated that infants are exposed to significant oral doses of steroid conjugates during the first week of lactation. The supply of these metabolites in BM declined and became constant after the second week postpartum. Overall, our data provide a foundation for further investigation on the physiological relevance of BM secreted steroid metabolites in relation to both mother and child.

Protective effects of psychiatric medications against COVID-19 mortality before vaccines

The coronavirus disease pandemic caused by the coronavirus SARS-CoV-2, which emerged in the United States in late 2019 to early 2020 and quickly escalated into a national public health crisis. Research has identified psychiatric conditions as possible risk factors associated with COVID-19 infection and symptom severity. This study aims to determine whether specific classes of psychiatric medications could reduce the likelihood of infection and alleviate the severity of the disease. The objective of this study is to investigate the relationship between neuropsychiatric medication usage and COVID-19 outcomes before the widespread utilization of COVID-19 vaccines. This cross-sectional study used Optum's de-identified Clinformatics Data Mart Database to identify patients diagnosed with COVID-19 in 2020 and their psychiatric medication prescriptions in the United States. Ordered logistic regression was used to predict the likelihood of a higher COVID-19 severity level for long-term and new users. Results were adjusted for demographic characteristics and medical and psychiatric comorbidities. Most users were classified into the long-term user analysis group. Long-term users were 9% less likely to have a higher severity score (CI: 0.89-0.93, p-value < 0.001) than non-users. SSRI antidepressant users, both long-term (OR: 1.09; CI: 1.06-1.12) and short-term (OR: 1.17; CI: 1.07-1.27) were significantly more likely to have a lower severity score. However, the results varied across long-term and short-term users for all medication classes. Results of the current study suggest that psychopharmacological agents are associated with reduced COVID-19 severity levels and that antidepressant medications may have a protective role against COVID-19.

ESPClust: unsupervised identification of modifiers for the effect size profile in omics association studies

MOTIVATION

High-throughput omics technologies have revolutionized the identification of associations between individual traits and underlying biological characteristics, but still use 'one effect-size fits all' approaches. While covariates are often used, their potential as effect modifiers often remains unexplored.

RESULTS

We propose ESPClust, a novel unsupervised method designed to identify covariates that modify the effect size of associations between sets of omics variables and outcomes. By extending the concept of moderators to encompass multiple exposures, ESPClust analyses the effect size profile (ESP) to identify regions in covariate space with different ESP, enabling the discovery of subpopulations with distinct associations. Applying ESPClust to synthetic data, insulin resistance and COVID-19 symptom manifestation, we demonstrate its versatility and ability to uncover nuanced effect size modifications that traditional analyses may overlook. By integrating information from multiple exposures, ESPClust identifies effect size modifiers in datasets that are too small for traditional univariate stratified analyses. This method provides a robust framework for understanding complex omics data and holds promise for personalised medicine.

AVAILABILITY AND IMPLEMENTATION

The source code ESPClust is available at https://github.com/fjpreche/ESPClust.git. It can be installed via Python package repositories as 'pip install ESPClust==1.1.0'.

Central and peripheral kynurenine pathway metabolites in COVID-19: Implications for neurological and immunological responses

Long-term symptoms such as pain, fatigue, and cognitive impairments are commonly observed in individuals affected by coronavirus disease 2019 (COVID-19). Metabolites of the kynurenine pathway have been proposed to account for cognitive impairment in COVID-19 patients. Here, cerebrospinal fluid (CSF) and plasma levels of kynurenine pathway metabolites in 53 COVID-19 patients and 12 non-inflammatory neurological disease controls in Sweden were measured with an ultra-performance liquid chromatography-tandem mass spectrometry system (UPLC-MS/MS) and correlated with immunological markers and neurological markers. Single cell transcriptomic data from a previous study of 130 COVID-19 patients was used to investigate the expression of key genes in the kynurenine pathway. The present study reveals that the neuroactive kynurenine pathway metabolites quinolinic acid (QUIN) and kynurenic acid (KYNA) are increased in CSF in patients with acute COVID-19. In addition, CSF levels of kynurenine, ratio of kynurenine/tryptophan (rKT) and QUIN correlate with neurodegenerative markers. Furthermore, tryptophan is significantly decreased in plasma but not in the CSF. In addition, the kynurenine pathway is strongly activated in the plasma and correlates with the peripheral immunological marker neopterin. Single-cell transcriptomics revealed upregulated gene expressions of the rate-limiting enzyme indoleamine 2,3- dioxygenase1 (IDO1) in CD14+ and CD16+ monocytes that correlated with type II-interferon response exclusively in COVID-19 patients. In summary, our study confirms significant activation of the peripheral kynurenine pathway in patients with acute COVID-19 and, notably, this is the first study to identify elevated levels of kynurenine metabolites in the central nervous system associated with the disease. Our findings suggest that peripheral inflammation, potentially linked to overexpression of IDO1 in monocytes, activates the kynurenine pathway. Increased plasma kynurenine, crossing the blood-brain barrier, serves as a source for elevated brain KYNA and neurotoxic QUIN. We conclude that blocking peripheral-to-central kynurenine transport could be a promising strategy to protect against neurotoxic effects of QUIN in COVID-19 patients.

Immune-Boosting and Antiviral Effects of Antioxidants in COVID-19 Pneumonia: A Therapeutic Perspective

The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has profoundly impacted global health, with pneumonia emerging as a major complication in severe cases. The pathogenesis of COVID-19 is marked by the overproduction of reactive oxygen species (ROS) and an excessive inflammatory response, resulting in oxidative stress and significant tissue damage, particularly in the respiratory system. Antioxidants have garnered considerable attention for their potential role in managing COVID-19 pneumonia by mitigating oxidative stress and modulating immune responses. This review provides a comprehensive overview of the literature on the use of antioxidants in hospitalized patients with mild-to-moderate COVID-19. Studies exploring antioxidants, including vitamins, trace elements, nitric oxide (NO), ozone (O3), glutathione (GSH), L-carnitine, melatonin, bromelain, N-acetylcysteine (NAC), and numerous polyphenols, have yielded promising outcomes. Through their ROS-scavenging properties, these molecules support endothelial function, reduce the thrombosis risk, and may help mitigate the effects of the cytokine storm, a key contributor to COVID-19 morbidity and mortality. Clinical evidence suggests that antioxidant supplementation may improve patient outcomes by decreasing inflammation, supporting immune cell function, and potentially shortening recovery times. Furthermore, these molecules may mitigate the symptoms of COVID-19 by exerting direct antiviral effects that inhibit the infection process and genomic replication of SARS-CoV-2 in host cells. Moreover, antioxidants may work synergistically with standard antiviral treatments to reduce viral-induced oxidative damage. By integrating findings from the literature with real-world data from our clinical experience, we gain a more profound understanding of the role of antioxidants in managing COVID-19 pneumonia. Further research combining comprehensive literature reviews with real-world data analysis is crucial to validate the efficacy of antioxidants and establish evidence-based guidelines for their use in clinical practice.

Metabolomic Insights into COVID-19 Severity: A Scoping Review

BACKGROUND

In 2019, SARS-CoV-2, the novel coronavirus, entered the world scene, presenting a global health crisis with a broad spectrum of clinical manifestations. Recognizing the significance of metabolomics as the omics closest to symptomatology, it has become a useful tool for predicting clinical outcomes. Several metabolomic studies have indicated variations in the metabolome corresponding to different disease severities, highlighting the potential of metabolomics to unravel crucial insights into the pathophysiology of SARS-CoV-2 infection.

METHODS

The PRISMA guidelines were followed for this scoping review. Three major scientific databases were searched: PubMed, the Directory of Open Access Journals (DOAJ), and BioMed Central, from 2020 to 2024. Initially, 2938 articles were identified and vetted with specific inclusion and exclusion criteria. Of these, 42 articles were retrieved for analysis and summary.

RESULTS

Metabolites were identified that were repeatedly noted to change with COVID-19 and its severity. Phenylalanine, glucose, and glutamic acid increased with severity, while tryptophan, proline, and glutamine decreased, highlighting their association with COVID-19 severity. Additionally, pathway analysis revealed that phenylalanine, tyrosine and tryptophan biosynthesis, and arginine biosynthesis were the most significantly impacted pathways in COVID-19 severity.

CONCLUSIONS

COVID-19 severity is intricately linked to significant metabolic alterations that span amino acid metabolism, energy production, immune response modulation, and redox balance.

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time

With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first real-time, reagent-free, portable analysis platform for viral detection in liquid saliva, using COVID-19 as a proof-of-concept. We show that vibrational molecular spectroscopy and machine learning (ML) detect biomolecular changes consistent with the presence of viral infection. Saliva samples were collected from 470 individuals, including 65 that were infected with COVID-19 (28 from hospitalized patients and 37 from a walk-in testing clinic) and 251 that had a negative polymerase chain reaction (PCR) test. A further 154 were collected from healthy volunteers. Saliva measurements were achieved in 6 minutes or less and led to machine learning models predicting COVID-19 infection with sensitivity and specificity reaching 90%, depending on volunteer symptoms and disease severity. Machine learning models were based on linear support vector machines (SVM). This platform could be deployed to manage future pandemics using the same hardware but using a tunable machine learning model that could be rapidly updated as new viral strains emerge.

The roles of the kynurenine pathway in COVID-19 neuropathogenesis

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the highly contagious respiratory disease Corona Virus Disease 2019 (COVID-19) that may lead to various neurological and psychological disorders that can be acute, lasting days to weeks or months and possibly longer. The latter is known as long-COVID or more recently post-acute sequelae of COVID (PASC). During acute COVID-19 infection, a strong inflammatory response, known as the cytokine storm, occurs in some patients. The levels of interferon-γ (IFN-γ), interferon-β (IFN-β), interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α) are particularly increased. These cytokines are known to activate the enzyme indoleamine 2,3-dioxygenase 1 (IDO-1), catalysing the first step of tryptophan (Trp) catabolism through the kynurenine pathway (KP) leading to the production of several neurotoxic and immunosuppressive metabolites. There is already data showing elevation in KP metabolites both acutely and in PASC, especially regarding cognitive impairment. Thus, it is likely that KP involvement is significant in SARS-CoV-2 pathogenesis especially neurologically.

Obesity-dependent molecular alterations in fatal COVID-19: A retrospective postmortem study of metabolomic profile of adipose tissue

We investigated the effects of obesity on metabolic, inflammatory, and oxidative stress parameters in the adipose tissue of patients with fatal COVID-19. Postmortem biopsies of subcutaneous adipose tissue were obtained from 25 unvaccinated inpatients who passed from COVID-19, stratified as nonobese (N-OB; body mass index [BMI], 26.5 ± 2.3 kg m-2) or obese (OB BMI 34.2 ± 5.1 kg m-2). Univariate and multivariate analyses revealed that body composition was responsible for most of the variations detected in the metabolome, with greater dispersion observed in the OB group. Fifteen metabolites were major segregation factors. Results from the OB group showed higher levels of creatinine, myo-inositol, O-acetylcholine, and succinate, and lower levels of sarcosine. The N-OB group showed lower levels of glutathione peroxidase activity, as well as higher content of IL-6 and adiponectin. We revealed significant changes in the metabolomic profile of the adipose tissue in fatal COVID-19 cases, with high adiposity playing a key role in these observed variations. These findings highlight the potential involvement of metabolic and inflammatory pathways, possibly dependent on hypoxia, shedding light on the impact of obesity on disease pathogenesis and suggesting avenues for further research and possible therapeutic targets.

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.

The Correlation Between Essential Amino Acid Tryptophan, Lysine, Phenylalanine and Chemotherapy of Breast Cancer

To investigate the differences in serum tryptophan, lysine, and phenylalanine levels in breast cancer patients, the correlation between the three amino acids with the chemotherapy regimen, and their significance in the clinical diagnosis and treatment of breast cancer.Clinical data were collected from the Department of Breast Surgery at Yunnan Cancer Hospital, encompassing 216 cases from July to December 2020, including 91 healthy individuals, 38 with benign tumors, and 87 with cancer. Amino acid levels were measured using liquid chromatography-tandem mass spectrometry. Statistical analyses, such as the Kruskal-Wallis H-test and Wilcoxon test, were conducted to compare the levels of these amino acids across the healthy group, benign tumor group, and breast cancer group. The χ2 test and Fisher's exact probability method were employed to assess the relationship between amino acid levels and breast cancer stage, grade, and chemotherapy regimen.The results indicated that there were significant differences in serum lysine (H = 36.13, P < .001) and phenylalanine (H = 34.03, P < .001) levels among the three groups. However, tryptophan levels did not show statistically significant variances. Specifically, lysine and phenylalanine levels were significantly different when comparing the healthy group with the breast cancer group and the benign tumor group with the breast cancer group. These differences were not significant when comparing the healthy group with the benign tumor group. Furthermore, there were no statistically significant distinctions observed in lysine (F = 0.836, P > .05) and phenylalanine (F = 1.466, P > .05) levels across different conventional chemotherapy regimens among the breast cancer cases studied.Serum lysine and phenylalanine levels might serve as potential biomarkers for breast cancer, and the choice of chemotherapy regimen is unlikely to impact significant changes in these amino acid levels.

Lipid compartments and lipid metabolism as therapeutic targets against coronavirus

Lipids perform a series of cellular functions, establishing cell and organelles' boundaries, organizing signaling platforms, and creating compartments where specific reactions occur. Moreover, lipids store energy and act as secondary messengers whose distribution is tightly regulated. Disruption of lipid metabolism is associated with many diseases, including those caused by viruses. In this scenario, lipids can favor virus replication and are not solely used as pathogens' energy source. In contrast, cells can counteract viruses using lipids as weapons. In this review, we discuss the available data on how coronaviruses profit from cellular lipid compartments and why targeting lipid metabolism may be a powerful strategy to fight these cellular parasites. We also provide a formidable collection of data on the pharmacological approaches targeting lipid metabolism to impair and treat coronavirus infection.

Prevalence of overweight and obesity and their effect on COVID-19 severity and hospitalization among younger than 50 years versus older than 50 years population: A systematic review and meta-analysis

Cohort studies have shown that both overweight and obesity have their impact by increasing hospitalization with COVID-19. We conducted a systematic literature search in PubMed, Google Scholar, and MedRxiv databases following the PRISMA guidelines. Statistical analyses were performed using STATA software version 16 MP (Stata Corp, College Station, TX, USA) and Med Calc software version 22.009(Med Calc software Ltd, Ostend, Belgium). The primary outcome was to measure the prevalence of overweight and obesity and their impact on the risk of hospitalization among COVID-19 patients under and above 50 years of age. In total, 184 studies involving 2,365,377 patients were included. The prevalence of overweight was highest among those younger than 50 years of age over those older than 50 years of age, (26.33% vs. 30.46%), but there was no difference in obesity (36.30% vs. 36.02%). Overall, the pooled prevalence of overweight and obesity among hospitalized COVID-19 patients was 31.0% and 36.26%, respectively. Compared with normal weight, the odds of hospitalization with overweight (odds ratio [OR] 2.186, 95% confidence interval [CI] [1.19, 3.99], p < 0.01) and obesity (OR 3.069, 95% CI [1.67, 5.61], p < 0.001) in those younger than 50 years and obesity (OR 3.977, 95% CI [2.75, 5.73], p < 0.001) in the older than 50 years age group were significantly high. The increased prevalence of overweight and obesity among the under 50 years age group and obesity among the older than 50 years age group significantly increased the rate of COVID-19 infections, severity and hospitalization.

Antipsychotic use and 28-day mortality in patients hospitalized with COVID-19: A multicenter observational retrospective study

Prior research has yielded conflicting results about the potential influence of antipsychotics in patients with COVID-19. In this multicenter retrospective study, we examined the association of antipsychotic use at admission with 28-day all-cause mortality in a sample of 59,021 adult patients hospitalized with COVID-19 from January 2020 to November 2021. In a 1:1 ratio matched analytic sample (N=1,454) accounting for age, sex, hospital, hospitalization period, the Elixhauser Comorbidity Index, other psychotropic medications, medications prescribed according to compassionate use or as part of a clinical trial, current diagnoses of psychiatric disorders, and clinical and biological markers of COVID-19 severity, antipsychotic use was not associated with 28-day mortality [23.5% (N=727) versus 18.6% (N=727); OR=1.16; 95%CI=0.89-1.51; p=0.280]. This association remained non-significant in exploratory analyses across all classes of antipsychotics and individual molecules, except for typical antipsychotics and loxapine, which were significantly linked to increased 28-day mortality, associations likely due to residual indication bias. Contrariwise, antipsychotics prescribed at daily doses higher than 200 mg of chlorpromazine-equivalents might be associated with reduced 28-day mortality when compared to patients not taking antipsychotics in the matched analytic sample [10.4% (N=154) versus 18.6% (N=727); AOR=0.56; 95%CI=0.31-0.96; p=0.040]. These results suggest that antipsychotic use, when prescribed at usual doses, are not be associated with 28-day mortality in patients hospitalized with COVID-19.

The Sphingolipid-Signaling Pathway as a Modulator of Infection by SARS-CoV-2

Ceramides and other related sphingolipids, important cellular components linked to metabolic homeostasis and cardiometabolic diseases, have been found to be involved in different steps of the SARS-CoV-2 life cycle. Hence, changes in their physiological levels are identified as predictors of COVID-19 severity and prognosis, as well as potential therapeutic targets. In this review, an overview of the SARS-CoV-2 life cycle is given, followed by a description of the sphingolipid metabolism and its role in viral infection, with a particular focus on those steps required to finalize the viral life cycle. Furthermore, the use and development of pharmaceutical strategies to target sphingolipids to prevent and treat severe and long-term symptoms of infectious diseases, particularly COVID-19, are reviewed herein. Finally, research perspectives and current challenges in this research field are highlighted. Although many aspects of sphingolipid metabolism are not fully known, this review aims to highlight how the discovery and use of molecules targeting sphingolipids with reliable and selective properties may offer new therapeutic alternatives to infectious and other diseases, including COVID-19.

The kynurenine pathway of tryptophan metabolism: a neglected therapeutic target of COVID-19 pathophysiology and immunotherapy

SARS-CoV-2 (COVID-19) exerts profound changes in the kynurenine (Kyn) pathway (KP) of tryptophan (Trp) metabolism that may underpin its pathophysiology. The KP is the main source of the vital cellular effector NAD+ and intermediate metabolites that modulate immune and neuronal functions. Trp metabolism is the top pathway influenced by COVID-19. Sixteen studies established virus-induced activation of the KP mediated mainly by induction of indoleamine 2,3-dioxygenase (IDO1) in most affected tissues and of IDO2 in lung by the increased release of proinflammatory cytokines but could additionally involve increased flux of plasma free Trp and induction of Trp 2,3-dioxygenase (TDO) by cortisol. The major Kyn metabolite targeted by COVID-19 is kynurenic acid (KA), the Kyn metabolite with the greatest affinity for the aryl hydrocarbon receptor (AhR), which is also activated by COVID-19. AhR activation initiates two important series of events: a vicious circle involving IDO1 induction, KA accumulation and further AhR activation, and activation of poly (ADP-ribose) polymerase (PARP) leading to NAD+ depletion and cell death. The virus further deprives the host of NAD+ by inhibiting its main biosynthetic pathway from quinolinic acid, while simultaneously acquiring NAD+ by promoting its synthesis from nicotinamide in the salvage pathway. Additionally, the protective effects of sirtuin 1 are minimised by the PARP activation. KP dysfunction may also underpin the mood and neurological disorders acutely and during 'long COVID'. More studies of potential effects of vaccination therapy on the KP are required and exploration of therapeutic strategies involving modulation of the KP changes are proposed.

Systematic Mendelian randomization study of the effect of gut microbiome and plasma metabolome on severe COVID-19

BACKGROUND

COVID-19 could develop severe respiratory symptoms in certain infected patients, especially in the patients with immune disorders. Gut microbiome and plasma metabolome act important immunological modulators in the human body and could contribute to the immune responses impacting the progression of COVID-19. However, the causal relationship between specific intestinal bacteria, metabolites and severe COVID-19 remains not clear.

METHODS

Based on two-sample Mendelian randomization (MR) framework, the causal effects of 131 intestinal taxa and 452 plasma metabolites on severe COVID-19 were evaluated. Single nucleotide polymorphisms (SNPs) strongly associated with the abundance of intestinal taxa and the concentration of plasma metabolites had been utilized as the instrument variables to infer whether they were causal factors of severe COVID-19. In addition, mediation analysis was conducted to find the potential association between the taxon and metabolite, and further colocalization analysis had been performed to validate the causal relationships.

RESULTS

MR analysis identified 13 taxa and 53 metabolites, which were significantly associated with severe COVID-19 as causal factors. Mediation analysis revealed 11 mediated relationships. Myo-inositol, 2-stearoylglycerophosphocholine, and alpha-glutamyltyrosine, potentially contributed to the association of Howardella and Ruminiclostridium 6 with severe COVID-19, respectively. Butyrivibrio and Ruminococcus gnavus could mediate the association of myo-inositol and N-acetylalanine, respectively. In addition, Ruminococcus torques abundance was colocalized with severe COVID-19 (PP.H4 = 0.77) and the colon expression of permeability related protein RASIP1 (PP.H4 = 0.95).

CONCLUSIONS

Our study highlights the potential causal relationships between gut microbiome, plasma metabolome and severe COVID-19, which potentially serve as clinical biomarkers for risk stratification and prognostication and benefit the mechanism mechanistic investigation of severe COVID-19.

Metabolomics Approaches for the Diagnosis, Treatment, and Better Disease Management of Viral Infections

Metabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.

Medications Modulating the Acid Sphingomyelinase/Ceramide System and 28-Day Mortality among Patients with SARS-CoV-2: An Observational Study

Prior evidence indicates the potential central role of the acid sphingomyelinase (ASM)/ceramide system in the infection of cells with SARS-CoV-2. We conducted a multicenter retrospective observational study including 72,105 adult patients with laboratory-confirmed SARS-CoV-2 infection who were admitted to 36 AP-HP (Assistance Publique-Hôpitaux de Paris) hospitals from 2 May 2020 to 31 August 2022. We examined the association between the ongoing use of medications functionally inhibiting acid sphingomyelinase (FIASMA), which reduces the infection of cells with SARS-CoV-2 in vitro, upon hospital admission with 28-day all-cause mortality in a 1:1 ratio matched analytic sample based on clinical characteristics, disease severity and other medications (N = 9714). The univariate Cox regression model of the matched analytic sample showed that FIASMA medication use at admission was associated with significantly lower risks of 28-day mortality (HR = 0.80; 95% CI = 0.72-0.88; p < 0.001). In this multicenter observational study, the use of FIASMA medications was significantly and substantially associated with reduced 28-day mortality among adult patients hospitalized with COVID-19. These findings support the continuation of these medications during the treatment of SARS-CoV-2 infections. Randomized clinical trials (RCTs) are needed to confirm these results, starting with the molecules with the greatest effect size in the study, e.g., fluoxetine, escitalopram, and amlodipine.

Plasma Sphingomyelin Disturbances: Unveiling Its Dual Role as a Crucial Immunopathological Factor and a Severity Prognostic Biomarker in COVID-19

SARS-CoV-2 infection triggers distinct patterns of disease development characterized by significant alterations in host regulatory responses. Severe cases exhibit profound lung inflammation and systemic repercussions. Remarkably, critically ill patients display a "lipid storm", influencing the inflammatory process and tissue damage. Sphingolipids (SLs) play pivotal roles in various cellular and tissue processes, including inflammation, metabolic disorders, and cancer. In this study, we employed high-resolution mass spectrometry to investigate SL metabolism in plasma samples obtained from control subjects (n = 55), COVID-19 patients (n = 204), and convalescent individuals (n = 77). These data were correlated with inflammatory parameters associated with the clinical severity of COVID-19. Additionally, we utilized RNAseq analysis to examine the gene expression of enzymes involved in the SL pathway. Our analysis revealed the presence of thirty-eight SL species from seven families in the plasma of study participants. The most profound alterations in the SL species profile were observed in patients with severe disease. Notably, a predominant sphingomyelin (SM d18:1) species emerged as a potential biomarker for COVID-19 severity, showing decreased levels in the plasma of convalescent individuals. Elevated SM levels were positively correlated with age, hospitalization duration, clinical score, and neutrophil count, as well as the production of IL-6 and IL-8. Intriguingly, we identified a putative protective effect against disease severity mediated by SM (d18:1/24:0), while ceramide (Cer) species (d18:1/24:1) and (d18:1/24:0)were associated with increased risk. Moreover, we observed the enhanced expression of key enzymes involved in the SL pathway in blood cells from severe COVID-19 patients, suggesting a primary flow towards Cer generation in tandem with SM synthesis. These findings underscore the potential of SM as a prognostic biomarker for COVID-19 and highlight promising pharmacological targets. By targeting sphingolipid pathways, novel therapeutic strategies may emerge to mitigate the severity of COVID-19 and improve patient outcomes.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

SARS-CoV-2 infection dysregulates NAD metabolism

Introduction

Severe COVID-19 results initially in pulmonary infection and inflammation. Symptoms can persist beyond the period of acute infection, and patients with Post-Acute Sequelae of COVID (PASC) often exhibit a variety of symptoms weeks or months following acute phase resolution including continued pulmonary dysfunction, fatigue, and neurocognitive abnormalities. We hypothesized that dysregulated NAD metabolism contributes to these abnormalities.

Methods

RNAsequencing of lungs from transgenic mice expressing human ACE2 (K18-hACE2) challenged with SARS-CoV-2 revealed upregulation of NAD biosynthetic enzymes, including NAPRT1, NMNAT1, NAMPT, and IDO1 6 days post-infection.

Results

Our data also demonstrate increased gene expression of NAD consuming enzymes: PARP 9,10,14 and CD38. At the same time, SIRT1, a protein deacetylase (requiring NAD as a cofactor and involved in control of inflammation) is downregulated. We confirmed our findings by mining sequencing data from lungs of patients that died from SARS-CoV-2 infection. Our validated findings demonstrating increased NAD turnover in SARS-CoV-2 infection suggested that modulating NAD pathways may alter disease progression and may offer therapeutic benefits. Specifically, we hypothesized that treating K18-hACE2 mice with nicotinamide riboside (NR), a potent NAD precursor, may mitigate lethality and improve recovery from SARS-CoV-2 infection. We also tested the therapeutic potential of an anti- monomeric NAMPT antibody using the same infection model. Treatment with high dose anti-NAMPT antibody resulted in significantly decreased body weight compared to control, which was mitigated by combining HD anti-NAMPT antibody with NR. We observed a significant increase in lipid metabolites, including eicosadienoic acid, oleic acid, and palmitoyl carnitine in the low dose antibody + NR group. We also observed significantly increased nicotinamide related metabolites in NR treated animals.

Discussion

Our data suggest that infection perturbs NAD pathways, identify novel mechanisms that may explain some pathophysiology of CoVID-19 and suggest novel strategies for both treatment and prevention.

Marked elevations in lung and plasma ceramide in COVID-19 linked to microvascular injury

The pathogenesis of the marked pulmonary microvasculature injury, a distinguishing feature of COVID-19 acute respiratory distress syndrome (COVID-ARDS), remains unclear. Implicated in the pathophysiology of diverse diseases characterized by endothelial damage, including ARDS and ischemic cardiovascular disease, ceramide and in particular palmitoyl ceramide (C16:0-ceramide) may be involved in the microvascular injury in COVID-19. Using deidentified plasma and lung samples from COVID-19 patients, ceramide profiling by mass spectrometry was performed. Compared with healthy individuals, a specific 3-fold C16:0-ceramide elevation in COVID-19 patient plasma was identified. Compared with age-matched controls, autopsied lungs of individuals succumbing to COVID-ARDS displayed a massive 9-fold C16:0-ceramide elevation and exhibited a previously unrecognized microvascular ceramide-staining pattern and markedly enhanced apoptosis. In COVID-19 plasma and lungs, the C16-ceramide/C24-ceramide ratios were increased and reversed, respectively, consistent with increased risk of vascular injury. Indeed, exposure of primary human lung microvascular endothelial cell monolayers to C16:0-ceramide-rich plasma lipid extracts from COVID-19, but not healthy, individuals led to a significant decrease in endothelial barrier function. This effect was phenocopied by spiking healthy plasma lipid extracts with synthetic C16:0-ceramide and was inhibited by treatment with ceramide-neutralizing monoclonal antibody or single-chain variable fragment. These results indicate that C16:0-ceramide may be implicated in the vascular injury associated with COVID-19.

Global prevalence and effect of comorbidities and smoking status on severity and mortality of COVID-19 in association with age and gender: a systematic review, meta-analysis and meta-regression

A COVID-19 patient often presents with multiple comorbidities and is associated with adverse outcomes. A comprehensive assessment of the prevalence of comorbidities in patients with COVID-19 is essential. This study aimed to assess the prevalence of comorbidities, severity and mortality with regard to geographic region, age, gender and smoking status in patients with COVID-19. A systematic review and multistage meta-analyses were reported using PRISMA guidelines. PubMed/MEDLINE, SCOPUS, Google Scholar and EMBASE were searched from January 2020 to October 2022. Cross-sectional studies, cohort studies, case series studies, and case-control studies on comorbidities reporting among the COVID-19 populations that were published in English were included. The pooled prevalence of various medical conditions in COVID-19 patients was calculated based on regional population size weights. Stratified analyses were performed to understand the variations in the medical conditions based on age, gender, and geographic region. A total of 190 studies comprising 105 million COVID-19 patients were included. Statistical analyses were performed using STATA software, version 16 MP (StataCorp, College Station, TX). Meta-analysis of proportion was performed to obtain pooled values of the prevalence of medical comorbidities: hypertension (39%, 95% CI 36-42, n = 170 studies), obesity (27%, 95% CI 25-30%, n = 169 studies), diabetes (27%, 95% CI 25-30%, n = 175), and asthma (8%, 95% CI 7-9%, n = 112). Moreover, the prevalence of hospitalization was 35% (95% CI 29-41%, n = 61), intensive care admissions 17% (95% CI 14-21, n = 106), and mortality 18% (95% CI 16-21%, n = 145). The prevalence of hypertension was highest in Europe at 44% (95% CI 39-47%, n = 68), obesity and diabetes at 30% (95% CI, 26-34, n = 79) and 27% (95%CI, 24-30, n = 80) in North America, and asthma in Europe at 9% (95% CI 8-11, n = 41). Obesity was high among the ≥ 50 years (30%, n = 112) age group, diabetes among Men (26%, n = 124) and observational studies reported higher mortality than case-control studies (19% vs. 14%). Random effects meta-regression found a significant association between age and diabetes (p < 0.001), hypertension (p < 0.001), asthma (p < 0.05), ICU admission (p < 0.05) and mortality (p < 0.001). Overall, a higher global prevalence of hypertension (39%) and a lower prevalence of asthma (8%), and 18% of mortality were found in patients with COVID-19. Hence, geographical regions with respective chronic medical comorbidities should accelerate regular booster dose vaccination, preferably to those patients with chronic comorbidities, to prevent and lower the severity and mortality of COVID-19 disease with novel SARS-CoV-2 variants of concern (VOC).

Acid sphingomyelinase (ASM) and COVID-19: A review of the potential use of ASM inhibitors against SARS-CoV-2

In the last 2 years, different pharmacological agents have been indicated as potential inhibitors of SARS-CoV-2 in vitro. Specifically, drugs termed as functional inhibitors of acid sphingomyelinase (FIASMAs) have proved to inhibit the SARS-CoV-2 replication using different types of cells. Those therapeutic agents share several chemical structure characteristics and some well-known representatives are fluoxetine, escitalopram, fluvoxamine, and others. Most of the FIASMAs are primarily used as effective therapeutic agents to treat different pathologies, therefore, they are natural drug candidates for repositioning strategy. In this review, we summarize the two main proposed mechanisms mediating acid sphingomyelinase (ASM) inhibition and how they can explain the inhibition of SARS-CoV-2 replication by FIASMAs. The first mechanism implies a disruption in the lysosomal pH fall as the endosome-lysosome moves toward the interior of the cell. In fact, changes in cholesterol levels in endosome-lysosome membranes, which are associated with ASM inhibition is thought to be mediated by lysosomal proton pump (ATP-ase) inactivation. The second mechanism involves the formation of an extracellular ceramide-rich domain, which is blocked by FIASMAs. The ceramide-rich domains are believed to facilitate the SARS-CoV-2 entrance into the host cells.

Metabolomics meets systems immunology

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Potential for Early Noninvasive COVID-19 Detection Using Electronic-Nose Technologies and Disease-Specific VOC Metabolic Biomarkers

The established efficacy of electronic volatile organic compound (VOC) detection technologies as diagnostic tools for noninvasive early detection of COVID-19 and related coronaviruses has been demonstrated from multiple studies using a variety of experimental and commercial electronic devices capable of detecting precise mixtures of VOC emissions in human breath. The activities of numerous global research teams, developing novel electronic-nose (e-nose) devices and diagnostic methods, have generated empirical laboratory and clinical trial test results based on the detection of different types of host VOC-biomarker metabolites from specific chemical classes. COVID-19-specific volatile biomarkers are derived from disease-induced changes in host metabolic pathways by SARS-CoV-2 viral pathogenesis. The unique mechanisms proposed from recent researchers to explain how COVID-19 causes damage to multiple organ systems throughout the body are associated with unique symptom combinations, cytokine storms and physiological cascades that disrupt normal biochemical processes through gene dysregulation to generate disease-specific VOC metabolites targeted for e-nose detection. This paper reviewed recent methods and applications of e-nose and related VOC-detection devices for early, noninvasive diagnosis of SARS-CoV-2 infections. In addition, metabolomic (quantitative) COVID-19 disease-specific chemical biomarkers, consisting of host-derived VOCs identified from exhaled breath of patients, were summarized as possible sources of volatile metabolic biomarkers useful for confirming and supporting e-nose diagnoses.

A metabolic blueprint of COVID-19 and long-term vaccine efficacy

Viruses are obligatory protein-coated units and often utilize the metabolic functions of the cells they infect. Viruses hijack cellular metabolic functions and cause consequences that can range from minor to devastating, as we have all witnessed during the COVID-19 pandemic. For understanding the virus-driven pathogenesis and its implications on the host, the cellular metabolism needs to be elucidated. How SARS-CoV-2 triggers metabolic functions and rewires the metabolism remains unidentified but the implications of the metabolic patterns are under investigation by several researchers. In this review, we have described the SARS-CoV-2-mediated metabolic alterations from in vitro studies to metabolic changes reported in victims of COVID-19. We have also discussed potential therapeutic targets to diminish the viral infection and suppress the inflammatory response, with respect to evidenced studies based on COVID-19 research. Finally, we aimed to explain how we could extend vaccine-induced immunity in people by targeting the immunometabolism.

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.

Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19

COVID-19 currently represents one of the major health challenges worldwide. Albeit its infectious character, with onset affectation mainly at the respiratory track, it is clear that the pathophysiology of COVID-19 has a systemic character, ultimately affecting many organs. This feature enables the possibility of investigating SARS-CoV-2 infection using multi-omic techniques, including metabolomic studies by chromatography coupled to mass spectrometry or by nuclear magnetic resonance (NMR) spectroscopy. Here we review the extensive literature on metabolomics in COVID-19, that unraveled many aspects of the disease including: a characteristic metabotipic signature associated to COVID-19, discrimination of patients according to severity, effect of drugs and vaccination treatments and the characterization of the natural history of the metabolic evolution associated to the disease, from the infection onset to full recovery or long-term and long sequelae of COVID.

Label-Free SERS for Rapid Differentiation of SARS-CoV-2-Induced Serum Metabolic Profiles in Non-Hospitalized Adults

COVID-19 represents a multi-system infectious disease with broad-spectrum manifestations, including changes in host metabolic processes connected to the disease pathogenesis. Understanding biochemical dysregulation patterns as a consequence of COVID-19 illness promises to be crucial for tracking disease course and clinical outcomes. Surface-enhanced Raman scattering (SERS) has attracted considerable interest in biomedical diagnostics for the sensitive detection of intrinsic profiles of unique fingerprints of serum biomolecules indicative of SARS-CoV-2 infection in a label-free format. Here, we applied label-free SERS and chemometrics for rapid interrogation of temporal metabolic dynamics in longitudinal sera of mildly infected non-hospitalized patients (n = 22), at 4 and 16 weeks post PCR-positive diagnosis, and compared them with negative controls (n = 8). SERS spectral markers revealed distinct metabolic profiles in patient sera that significantly deviated from the healthy metabolic state at the two sampling time intervals. Multivariate and univariate analyses of the spectral data identified abundance dynamics in amino acids, lipids, and protein vibrations as the key spectral features underlying the metabolic differences detected in convalescent samples and perhaps associated with patient recovery progression. A validation study performed using spontaneous Raman spectroscopy yielded spectral data results that corroborated SERS spectral findings and confirmed the detected disease-specific molecular phenotypes in clinical samples. Label-free SERS promises to be a valuable analytical technique for rapid screening of the metabolic phenotype induced by SARS-CoV-2 infection to allow appropriate healthcare intervention.

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4+ T/CD8+ T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3+ T,CD4+T and CD8+T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors.

An NMR-Based Model to Investigate the Metabolic Phenoreversion of COVID-19 Patients throughout a Longitudinal Study

After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts.

Selective serotonin reuptake inhibitors: New hope in the fight against COVID-19

The emerging COVID-19 pandemic led to a dramatic increase in global mortality and morbidity rates. As in most infections, fatal complications of coronavirus affliction are triggered by an untrammeled host inflammatory response. Cytokine storms created by high levels of interleukin and other cytokines elucidate the pathology of severe COVID-19. In this respect, repurposing drugs that are already available and might exhibit anti-inflammatory effects have received significant attention. With the in vitro and clinical investigation of several studies on the effect of antidepressants on COVID-19 prognosis, previous data suggest that selective serotonin reuptake inhibitors (SSRIs) might be the new hope for the early treatment of severely afflicted patients. SSRIs' low cost and availability make them potentially eligible for COVID-19 repurposing. This review summarizes current achievements and literature about the connection between SSRIs administration and COVID-19 prognosis.

The Cytokines CXCL10 and CCL2 and the Kynurenine Metabolite Anthranilic Acid Accurately Predict Patients at Risk of Developing Dengue With Warning Signs

BACKGROUND

The resolution or aggravation of dengue infection depends on the patient's immune response during the critical phase. Cytokines released by immune cells increase with the worsening severity of dengue infections. Cytokines activate the kynurenine pathway (KP) and the extent of KP activation then influences disease severity.

METHODS

KP metabolites and cytokines in plasma samples of patients with dengue infection (dengue without warning signs [DWS-], dengue with warning signs [DWS+], or severe dengue) were analyzed. Cytokines (interferon gamma [IFN-ɣ], tumor necrosis factor, interleukin 6, CXCL10/interferon-inducile protein 10 [IP-10], interleukin 18 [IL-18], CCL2/monocyte chemoattractant protein-1 [MCP-1], and CCL4/macrophage inflammatory protein-1beta [MIP-1β] were assessed by a Human Luminex Screening Assay, while KP metabolites (tryptophan, kynurenine, anthranilic acid [AA], picolinic acid, and quinolinic acid) were assessed by ultra-high-performance liquid chromatography and Gas Chromatography Mass Spectrophotometry [GCMS] assays.

RESULTS

Patients with DWS+ had increased activation of the KP where kynurenine-tryptophan ratio, anthranilic acid, and picolinic acid were elevated. These patients also had higher levels of the cytokines IFN-ɣ, CXCL10, CCL4, and IL-18 than those with DWS-. Further receiver operating characteristic analysis identified 3 prognostic biomarker candidates, CXCL10, CCL2, and AA, which predicted patients with higher risks of developing DWS+ with an accuracy of 97%.

CONCLUSIONS

The data suggest a unique biochemical signature in patients with DWS+. CXCL10 and CCL2 together with AA are potential prognostic biomarkers that discern patients with higher risk of developing DWS+ at earlier stages of infection.

Antiviral and Anti-Inflammatory Activities of Fluoxetine in a SARS-CoV-2 Infection Mouse Model

The coronavirus disease 2019 (COVID-19) pandemic continues to cause significant morbidity and mortality worldwide. Since a large portion of the world's population is currently unvaccinated or incompletely vaccinated and has limited access to approved treatments against COVID-19, there is an urgent need to continue research on treatment options, especially those at low cost and which are immediately available to patients, particularly in low- and middle-income countries. Prior in vitro and observational studies have shown that fluoxetine, possibly through its inhibitory effect on the acid sphingomyelinase/ceramide system, could be a promising antiviral and anti-inflammatory treatment against COVID-19. In this report, we evaluated the potential antiviral and anti-inflammatory activities of fluoxetine in a K18-hACE2 mouse model of SARS-CoV-2 infection, and against variants of concern in vitro, i.e., SARS-CoV-2 ancestral strain, Alpha B.1.1.7, Gamma P1, Delta B1.617 and Omicron BA.5. Fluoxetine, administrated after SARS-CoV-2 infection, significantly reduced lung tissue viral titres and expression of several inflammatory markers (i.e., IL-6, TNFα, CCL2 and CXCL10). It also inhibited the replication of all variants of concern in vitro. A modulation of the ceramide system in the lung tissues, as reflected by the increase in the ratio HexCer 16:0/Cer 16:0 in fluoxetine-treated mice, may contribute to explain these effects. Our findings demonstrate the antiviral and anti-inflammatory properties of fluoxetine in a K18-hACE2 mouse model of SARS-CoV-2 infection, and its in vitro antiviral activity against variants of concern, establishing fluoxetine as a very promising candidate for the prevention and treatment of SARS-CoV-2 infection and disease pathogenesis.

Antidepressant Use and Its Association with 28-Day Mortality in Inpatients with SARS-CoV-2: Support for the FIASMA Model against COVID-19

To reduce Coronavirus Disease 2019 (COVID-19)-related mortality and morbidity, widely available oral COVID-19 treatments are urgently needed. Certain antidepressants, such as fluvoxamine or fluoxetine, may be beneficial against COVID-19. We included 388,945 adult inpatients who tested positive for SARS-CoV-2 at 36 AP−HP (Assistance Publique−Hôpitaux de Paris) hospitals from 2 May 2020 to 2 November 2021. We compared the prevalence of antidepressant use at admission in a 1:1 ratio matched analytic sample with and without COVID-19 (N = 82,586), and assessed its association with 28-day all-cause mortality in a 1:1 ratio matched analytic sample of COVID-19 inpatients with and without antidepressant use at admission (N = 1482). Antidepressant use was significantly less prevalent in inpatients with COVID-19 than in a matched control group of inpatients without COVID-19 (1.9% versus 4.8%; Odds Ratio (OR) = 0.38; 95%CI = 0.35−0.41, p < 0.001). Antidepressant use was significantly associated with reduced 28-day mortality among COVID-19 inpatients (12.8% versus 21.2%; OR = 0.55; 95%CI = 0.41−0.72, p < 0.001), particularly at daily doses of at least 40 mg fluoxetine equivalents. Antidepressants with high FIASMA (Functional Inhibitors of Acid Sphingomyelinase) activity seem to drive both associations. These treatments may reduce SARS-CoV-2 infections and COVID-19-related mortality in inpatients, and may be appropriate for prophylaxis and/or COVID-19 therapy for outpatients or inpatients.

Untargeted plasma metabolomic fingerprinting highlights several biomarkers for the diagnosis and prognosis of coronavirus disease 19

Objectives

The COVID-19 pandemic has been a serious worldwide public health crisis since 2020 and is still challenging healthcare systems. New tools for the prognosis and diagnosis of COVID-19 patients remain important issues.

Design

Here, we studied the metabolome of plasma samples of COVID-19 patients for the identification of prognosis biomarkers.

Patients

Plasma samples of eighty-six SARS-CoV-2-infected subjects and 24 healthy controls were collected during the first peak of the COVID-19 pandemic in France in 2020.

Main results

Plasma metabolome fingerprinting allowed the successful discrimination of healthy controls, mild SARS-CoV-2 subjects, and moderate and severe COVID-19 patients at hospital admission. We found a strong effect of SARS-CoV-2 infection on the plasma metabolome in mild cases. Our results revealed that plasma lipids and alterations in their saturation level are important biomarkers for the detection of the infection. We also identified deoxy-fructosyl-amino acids as new putative plasma biomarkers for SARS-CoV-2 infection and COVID-19 severity. Finally, our results highlight a key role for plasma levels of tryptophan and kynurenine in the symptoms of COVID-19 patients.

Conclusion

Our results showed that plasma metabolome profiling is an efficient tool for the diagnosis and prognosis of SARS-CoV-2 infection.

Fatty acids homeostasis during fasting predicts protection from chemotherapy toxicity

Fasting exerts beneficial effects in mice and humans, including protection from chemotherapy toxicity. To explore the involved mechanisms, we collect blood from humans and mice before and after 36 or 24 hours of fasting, respectively, and measure lipid composition of erythrocyte membranes, circulating micro RNAs (miRNAs), and RNA expression at peripheral blood mononuclear cells (PBMCs). Fasting coordinately affects the proportion of polyunsaturated versus saturated and monounsaturated fatty acids at the erythrocyte membrane; and reduces the expression of insulin signaling-related genes in PBMCs. When fasted for 24 hours before and 24 hours after administration of oxaliplatin or doxorubicin, mice show a strong protection from toxicity in several tissues. Erythrocyte membrane lipids and PBMC gene expression define two separate groups of individuals that accurately predict a differential protection from chemotherapy toxicity, with important clinical implications. Our results reveal a mechanism of fasting associated with lipid homeostasis, and provide biomarkers of fasting to predict fasting-mediated protection from chemotherapy toxicity.

Fasting has been reported to protect from chemotherapy-associated toxicity. Here, the authors show that fatty acid profiles in erythrocyte membranes and gene expression from peripheral blood mononuclear cells are associated to the fasting-mediated benefits during cancer treatment in mice and patients.

Circulating pyruvate is a potent prognostic marker for critical COVID-19 outcomes

Background

Coronavirus-19 (COVID-19) disease is driven by an unchecked immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus which alters host mitochondrial-associated mechanisms. Compromised mitochondrial health results in abnormal reprogramming of glucose metabolism, which can disrupt extracellular signalling. We hypothesized that examining mitochondrial energy-related signalling metabolites implicated in host immune response to SARS-CoV-2 infection would provide potential biomarkers for predicting the risk of severe COVID-19 illness.

Methods

We used a semi-targeted serum metabolomics approach in 273 patients with different severity grades of COVID-19 recruited at the acute phase of the infection to determine the relative abundance of tricarboxylic acid (Krebs) cycle-related metabolites with known extracellular signaling properties (pyruvate, lactate, succinate and α-ketoglutarate). Abundance levels of energy-related metabolites were evaluated in a validation cohort (n=398) using quantitative fluorimetric assays.

Results

Increased levels of four energy-related metabolites (pyruvate, lactate, a-ketoglutarate and succinate) were found in critically ill COVID-19 patients using semi-targeted and targeted approaches (p<0.05). The combined strategy proposed herein enabled us to establish that circulating pyruvate levels (p<0.001) together with body mass index (p=0.025), C-reactive protein (p=0.039), D-Dimer (p<0.001) and creatinine (p=0.043) levels, are independent predictors of critical COVID-19. Furthermore, classification and regression tree (CART) analysis provided a cut-off value of pyruvate in serum (24.54 µM; p<0.001) as an early criterion to accurately classify patients with critical outcomes.

Conclusion

Our findings support the link between COVID-19 pathogenesis and immunometabolic dysregulation, and show that fluorometric quantification of circulating pyruvate is a cost-effective clinical decision support tool to improve patient stratification and prognosis prediction.

Antioxidant Effects of Dietary Supplements on Adult COVID-19 Patients: Why Do We Not Also Use Them in Children?

Respiratory tract infections (RTIs) are very common in children, especially in the first five years of life, and several viruses, such as the influenza virus, Respiratory Syncytial Virus, and Rhinovirus, are triggers for symptoms that usually affect the upper airways. It has been known that during respiratory viral infections, a condition of oxidative stress (OS) occurs, and many studies have suggested the potential use of antioxidants as complementary components in prophylaxis and/or therapy of respiratory viral infections. Preliminary data have demonstrated that antioxidants may also interfere with the new coronavirus 2’s entry and replication in human cells, and that they have a role in the downregulation of several pathogenetic mechanisms involved in disease severity. Starting from preclinical data, the aim of this narrative review is to evaluate the current evidence about the main antioxidants that are potentially useful for preventing and treating Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in adults and to speculate on their possible use in children by exploring the most relevant issues affecting their use in clinical practice, as well as the associated evidence gaps and research limitations.

Association between antidepressant use and ED or hospital visits in outpatients with SARS-CoV-2

Antidepressants have previously been associated with better outcomes in patients hospitalized with COVID-19, but their effect on clinical deterioration among ambulatory patients has not been fully explored. The objective of this study was to assess whether antidepressant exposure was associated with reduced emergency department (ED) or hospital visits among ambulatory patients with SARS-CoV-2 infection. This retrospective cohort study included adult patients (N = 25 034) with a positive SARS-CoV-2 test performed in a non-hospital setting. Logistic regression analyses tested associations between home use of antidepressant medications and a composite outcome of ED visitation or hospital admission within 30 days. Secondary exposures included individual antidepressants and antidepressants with functional inhibition of acid sphingomyelinase (FIASMA) activity. Patients with antidepressant exposure were less likely to experience the primary composite outcome compared to patients without antidepressant exposure (adjusted odds ratio [aOR] 0.89, 95% CI 0.79-0.99, p = 0.04). This association was only observed with daily doses of at least 20 mg fluoxetine-equivalent (aOR 0.87, 95% CI 0.77-0.99, p = 0.04), but not with daily doses lower than 20 mg fluoxetine-equivalent (aOR 0.94, 95% CI 0.80-1.11, p = 0.48). In exploratory secondary analyses, the outcome incidence was also reduced with exposure to selective serotonin reuptake inhibitors (aOR 0.87, 95% CI 0.75-0.99, p = 0.04), bupropion (aOR 0.70, 95% CI 0.55-0.90, p = 0.005), and FIASMA antidepressant drugs (aOR 0.87, 95% CI 0.77-0.99, p = 0.03). Antidepressant exposure was associated with a reduced incidence of emergency department visitation or hospital admission among SARS-CoV-2 positive patients, in a dose-dependent manner. These data support the FIASMA model of antidepressants' effects against COVID-19.

The tryptophan catabolite or kynurenine pathway in COVID-19 and critical COVID-19: a systematic review and meta-analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) is accompanied by activated immune-inflammatory pathways and oxidative stress, which both induce indoleamine-2,3-dioxygenase (IDO), a key enzyme of the tryptophan (TRP) catabolite (TRYCAT) pathway. The aim of this study was to systematically review and meta-analyze the status of the TRYCAT pathway, including the levels of TRP and kynurenine (KYN) and the activity of IDO, as measured by the ratio of KYN/TRP.

METHODS

This systematic review searched PubMed, Google Scholar, and Web of Sciences and included 14 articles that compared TRP and tryptophan catabolites (TRYCATs) in COVID-19 patients versus non-COVID-19 controls, as well as severe/critical versus mild/moderate COVID-19. The analysis was done on a total of 1269 people, including 794 COVID-19 patients and 475 controls.

RESULTS

The results show a significant (p < 0.0001) increase in the KYN/TRP ratio (standardized mean difference, SMD = 1.099, 95% confidence interval, CI: 0.714; 1.484) and KYN (SMD = 1.123, 95% CI: 0.730; 1.516) and significantly lower TRP (SMD = - 1.002, 95%CI: - 1.738; - 0.266) in COVID-19 versus controls. The KYN/TRP ratio (SMD = 0.945, 95%CI: 0.629; 1.262) and KYN (SMD = 0.806, 95%CI: 0.462; 1.149) were also significantly (p < 0.0001) higher and TRP lower (SMD = - 0.909, 95% CI: - 1.569; - 0.249) in severe/critical versus mild/moderate COVID-19. No significant difference was detected in kynurenic acid (KA) and the KA/KYN ratio between COVID-19 patients and controls.

CONCLUSIONS

Our results indicate increased activity of the IDO enzyme in COVID-19 and severe/critical patients. The TRYCAT pathway is implicated in the pathophysiology and progression of COVID-19 and may signal a worsening outcome of the disease.

Metabolic Reprogramming in SARS-CoV-2 Infection Impacts the Outcome of COVID-19 Patients

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection triggers inflammatory clinical stages that affect the outcome of patients with coronavirus disease 2019 (COVID-19). Disease severity may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. The aim of this study was to characterize the profile of amino acids and acylcarnitines in COVID-19 patients. A multicenter, cross-sectional study was carried out. A total of 453 individuals were classified by disease severity. Levels of 11 amino acids, 31 acylcarnitines, and succinylacetone in serum samples were analyzed by electrospray ionization-triple quadrupole tandem mass spectrometry. Different clusters were observed in partial least squares discriminant analysis, with phenylalanine, alanine, citrulline, proline, and succinylacetone providing the major contribution to the variability in each cluster (variable importance in the projection >1.5). In logistic models adjusted by age, sex, type 2 diabetes mellitus, hypertension, and nutritional status, phenylalanine was associated with critical outcomes (odds ratio=5.3 (95% CI 3.16-9.2) in the severe vs. critical model, with an area under the curve of 0.84 (95% CI 0.77-0.90). In conclusion the metabolic imbalance in COVID-19 patients might affect disease progression. This work shows an association of phenylalanine with critical outcomes in COVID-19 patients, highlighting phenylalanine as a potential metabolic biomarker of disease severity.

Characterization of serotonin as a candidate biomarker of severity and prognosis of COVID-19 using LC/MS analysis

The coronavirus disease 2019 (COVID-19) pandemic has been associated with high mortality worldwide. Owing to its complicated pathophysiology, diagnostic and prognostic biomarkers for effective patient management remain scarce. We analyzed kynurenine, tryptophan, and serotonin levels in the serum of patients with COVID-19 via liquid chromatography/mass spectrometry analysis. Serum serotonin levels were decreased in patients with more severe COVID-19, along with increased kynurenine and decreased tryptophan concentrations. Patients with moderate disease who subsequently worsened showed significantly lower serotonin concentrations compared with those who did not experience severe disease. Serum serotonin levels may represent a valuable biomarker for COVID-19 severity and prognosis.

Skeletal Muscle and COVID-19: The Potential Involvement of Bioactive Sphingolipids

SARS-CoV-2 virus infection is the cause of the coronavirus disease 2019 (COVID-19), which is still spreading over the world. The manifestation of this disease can range from mild to severe and can be limited in time (weeks) or persist for months in about 30–50% of patients. COVID-19 is considered a multiple organ dysfunction syndrome and the musculoskeletal system manifestations are beginning to be considered of absolute importance in both COVID-19 patients and in patients recovering from the SARS-CoV-2 infection. Musculoskeletal manifestations of COVID-19 and other coronavirus infections include loss of muscle mass, muscle weakness, fatigue or myalgia, and muscle injury. The molecular mechanisms by which SARS-CoV-2 can cause damage to skeletal muscle (SkM) cells are not yet well understood. Sphingolipids (SLs) represent an important class of eukaryotic lipids with structural functions as well as bioactive molecules able to modulate crucial processes, including inflammation and viral infection. In the last two decades, several reports have highlighted the role of SLs in modulating SkM cell differentiation, regeneration, aging, response to insulin, and contraction. This review summarizes the consequences of SARS-CoV-2 infection on SkM and the potential involvement of SLs in the tissue responses to virus infection. In particular, we highlight the role of sphingosine 1-phosphate signaling in order to aid the prediction of novel targets for preventing and/or treating acute and long-term musculoskeletal manifestations of virus infection in COVID-19.

COVID-19 Outcomes: Does the Use of Psychotropic Drugs Make a Difference? Accumulating Evidence of a Beneficial Effect of Antidepressants-A Scoping Review

PURPOSE/BACKGROUND

Studies for repurposed drugs in severe acute respiratory syndrome coronavirus type 2-infected and coronavirus disease 2019 (COVID-19) patients are ongoing. According to preclinical research, antidepressants (ADs) might be useful in the treatment of COVID-19.

METHODS/PROCEDURES

We conducted a scoping review including clinical studies on AD effects on SARS-CoV-2 infection and COVID-19.

FINDING/RESULTS

As of January 2, 2022, we found 14 clinical studies, which could be included into this review. Among them, there were 2 randomized, placebo-controlled studies and 2 prospective parallel-group studies about the efficacy/effectiveness and tolerability of fluvoxamine. The remaining studies were mainly retrospective studies considering COVID-19 hospital populations predominantly exposed to fluoxetine (N = 3), other selective serotonin reuptake inhibitors (SSRI), selective norepinephrine reuptake inhibitors (SNRI), and trazodone. The vast majority were hospital studies and assessed COVID-19 severity (morbidity) and mortality as primary endpoints. The only outpatient study (fluvoxamine) investigated the COVID-19-related hospitalization rate, and 1 psychiatric hospital study (SSRI, SNRI, trazodone) focused on the SARS-CoV-2 infection rate.

IMPLICATIONS/CONCLUSIONS

At present, the best evidence of an "anti-COVID-19" potential of ADs exists for fluvoxamine and, to a lesser extent, for fluoxetine. Preliminary evidence had found that patients exposed to SSRI or SNRI substance classes might have a reduced mortality risk and that trazodone might reduce SARS-CoV-2 infection rates. Three studies found no relevant influence of ADs on COVID-19 morbidity and mortality, and 1 study described increased mortality. The latter study, however, did not differentiate between psychotropic medication and ADs. Tricyclics and monoamine oxidase inhibitors are still absolute "dark zones" in COVID-19 research. Further controlled studies testing the effectiveness/efficacy and tolerability/safety (as well as the treatment timing and duration) of different AD substance classes in COVID-19 and post/long-COVID patients of various populations are warranted.

Metabolomics and integrated network analysis reveal roles of endocannabinoids and large neutral amino acid balance in the ayahuasca experience

There has been a renewed interest in the potential use of psychedelics for the treatment of psychiatric conditions. Nevertheless, little is known about the mechanism of action and molecular pathways influenced by ayahuasca use in humans. Therefore, for the first time, our study aims to investigate the human metabolomics signature after consumption of a psychedelic, ayahuasca, and its connection with both the psychedelic-induced subjective effects and the plasma concentrations of ayahuasca alkaloids. Plasma samples of 23 individuals were collected both before and after ayahuasca consumption. Samples were analysed through targeted metabolomics and further integrated with subjective ratings of the ayahuasca experience (i.e., using the 5-Dimension Altered States of Consciousness Rating Scale [ASC]), and plasma ayahuasca-alkaloids using integrated network analysis. Metabolic pathways enrichment analysis using diffusion algorithms for specific KEGG modules was performed on the metabolic output. Compared to baseline, the consumption of ayahuasca increased N-acyl-ethanolamine endocannabinoids, decreased 2-acyl-glycerol endocannabinoids, and altered several large-neutral amino acids (LNAAs). Integrated network results indicated that most of the LNAAs were inversely associated with 9 out of the 11 subscales of the ASC, except for tryptophan which was positively associated. Several endocannabinoids and hexosylceramides were directly associated with the ayahuasca alkaloids. Enrichment analysis confirmed dysregulation in several pathways involved in neurotransmission such as serotonin and dopamine synthesis. In conclusion, a crosstalk between the circulating LNAAs and the subjective effects is suggested, which is independent of the alkaloid concentrations and provides insights into the specific metabolic fingerprint and mechanism of action underlying ayahuasca experiences.

Association between benzodiazepine receptor agonist use and mortality in patients hospitalised for COVID-19: a multicentre observational study

AIMS

To examine the association between benzodiazepine receptor agonist (BZRA) use and mortality in patients hospitalised for coronavirus disease 2019 (COVID-19).

METHODS

A multicentre observational study was performed at Greater Paris University hospitals. The sample involved 14 381 patients hospitalised for COVID-19. A total of 686 (4.8%) inpatients received a BZRA at hospital admission at a mean daily diazepam-equivalent dose of 19.7 mg (standard deviation (s.d.) = 25.4). The study baseline was the date of admission, and the primary endpoint was death. We compared this endpoint between patients who received BZRAs and those who did not in time-to-event analyses adjusted for sociodemographic characteristics, medical comorbidities and other medications. The primary analysis was a Cox regression model with inverse probability weighting (IPW).

RESULTS

Over a mean follow-up of 14.5 days (s.d. = 18.1), the primary endpoint occurred in 186 patients (27.1%) who received BZRAs and in 1134 patients (8.3%) who did not. There was a significant association between BZRA use and increased mortality both in the crude analysis (hazard ratio (HR) = 3.20; 95% confidence interval (CI) = 2.74-3.74; p < 0.01) and in the IPW analysis (HR = 1.61; 95% CI = 1.31-1.98, p < 0.01), with a significant dose-dependent relationship (HR = 1.55; 95% CI = 1.08-2.22; p = 0.02). This association remained significant in sensitivity analyses. Exploratory analyses indicate that most BZRAs may be associated with an increased mortality among patients hospitalised for COVID-19, except for diazepam, which may be associated with a reduced mortality compared with any other BZRA treatment.

CONCLUSIONS

BZRA use may be associated with an increased mortality among patients hospitalised for COVID-19, suggesting the potential benefit of decreasing dose or tapering off gradually these medications when possible.