A lipidomic view of SARS-CoV-2

Mass spectrometric approaches in discovering lipid biomarkers for COVID-19 by lipidomics: Future challenges and perspectives

Coronavirus disease 2019 (COVID-19) has emerged as a global health threat and has rapidly spread worldwide. Significant changes in the lipid profile before and after COVID-19 confirmed the significance of lipid metabolism in regulating the response to viral infection. Therefore, understanding the role of lipid metabolism may facilitate the development of new therapeutics for COVID-19. Owing to their high sensitivity and accuracy, mass spectrometry (MS)-based methods are widely used for rapidly identifying and quantifying of thousands of lipid species present in a small amount of sample. To enhance the capabilities of MS for the qualitative and quantitative analysis of lipids, different platforms have been combined to cover a wide range of lipidomes with high sensitivity, specificity, and accuracy. Currently, MS-based technologies are being established as efficient methods for discovering potential diagnostic biomarkers for COVID-19 and related diseases. As the lipidome of the host cell is drastically affected by the viral replication process, investigating lipid profile alterations in patients with COVID-19 and targeting lipid metabolism pathways are considered to be crucial steps in host-directed drug targeting to develop better therapeutic strategies. This review summarizes various MS-based strategies that have been developed for lipidomic analyzes and biomarker discoveries to combat COVID-19 by integrating various other potential approaches using different human samples. Furthermore, this review discusses the challenges in using MS technologies and future perspectives in terms of drug discovery and diagnosis of COVID-19.

Early Metabolomic and Immunologic Biomarkers as Prognostic Indicators for COVID-19

This prospective study in Hong Kong aimed at identifying prognostic metabolomic and immunologic biomarkers for Coronavirus Disease 2019 (COVID-19). We examined 327 patients, mean age 55 (19-89) years, in whom 33.6% were infected with Omicron and 66.4% were infected with earlier variants. The effect size of disease severity on metabolome outweighed others including age, gender, peak C-reactive protein (CRP), vitamin D and peak viral levels. Sixty-five metabolites demonstrated strong associations and the majority (54, 83.1%) were downregulated in severe disease (z score: -3.30 to -8.61). Ten cytokines/chemokines demonstrated strong associations (p < 0.001), and all were upregulated in severe disease. Multiple pairs of metabolomic/immunologic biomarkers showed significant correlations. Fourteen metabolites had the area under the receiver operating characteristic curve (AUC) > 0.8, suggesting a high predictive value. Three metabolites carried high sensitivity for severe disease: triglycerides in medium high-density lipoprotein (MHDL) (sensitivity: 0.94), free cholesterol-to-total lipids ratio in very small very-low-density lipoprotein (VLDL) (0.93), cholesteryl esters-to-total lipids ratio in chylomicrons and extremely large VLDL (0.92);whereas metabolites with the highest specificity were creatinine (specificity: 0.94), phospholipids in large VLDL (0.94) and triglycerides-to-total lipids ratio in large VLDL (0.93). Five cytokines/chemokines, namely, interleukin (IL)-6, IL-18, IL-10, macrophage inflammatory protein (MIP)-1b and tumour necrosis factor (TNF)-a, had AUC > 0.8. In conclusion, we demonstrated a tight interaction and prognostic potential of metabolomic and immunologic biomarkers enabling an outcome-based patient stratification.

Lipidomics signature in post-COVID patient sera and its influence on the prolonged inflammatory response

BACKGROUND

The ongoing issues with post-COVID conditions (PCC), where symptoms persist long after the initial infection, highlight the need for research into blood lipid changes in these patients. While most studies focus on the acute phase of COVID-19, there's a significant lack of information on the lipidomic changes that occur in the later stages of the disease. Addressing this knowledge gap is critical for understanding the long-term effects of COVID-19 and could be key to developing personalized treatments for those suffering from PCC.

METHODS

We employed untargeted lipidomics to analyze plasma samples from 147 PCC patients, assessing nearly 400 polar lipids. Data mining (DM) and machine learning (ML) tools were utilized to decode the results and ascertain significant lipidomic patterns.

RESULTS

The study uncovered substantial changes in various lipid subclasses, presenting a detailed profile of the polar lipid fraction in PCC patients. These alterations correlated with ongoing inflammation and immune response. Notably, there were elevated levels of lysophosphatidylglycerols (LPGs) and phosphatidylethanolamines (PEs), and reduced levels of lysophosphatidylcholines (LPCs), suggesting these as potential lipid biomarkers for PCC. The lipidomic signatures indicated specific anionic lipid changes, implicating antimicrobial peptides (AMPs) in inflammation. Associations between particular medications and symptoms were also suggested. Classification models, such as multinomial regression (MR) and random forest (RF), successfully differentiated between symptomatic and asymptomatic PCC groups using lipidomic profiles.

CONCLUSIONS

The study's groundbreaking discovery of specific lipidomic disruptions in PCC patients marks a significant stride in the quest to comprehend and combat this condition. The identified lipid biomarkers not only pave the way for novel diagnostic tools but also hold the promise to tailor individualized therapeutic strategies, potentially revolutionizing the clinical approach to managing PCC and improving patient care.

Precision nutrition to reset virus-induced human metabolic reprogramming and dysregulation (HMRD) in long-COVID

SARS-CoV-2, the etiological agent of COVID-19, is devoid of any metabolic capacity; therefore, it is critical for the viral pathogen to hijack host cellular metabolic machinery for its replication and propagation. This single-stranded RNA virus with a 29.9 kb genome encodes 14 open reading frames (ORFs) and initiates a plethora of virus-host protein-protein interactions in the human body. These extensive viral protein interactions with host-specific cellular targets could trigger severe human metabolic reprogramming/dysregulation (HMRD), a rewiring of sugar-, amino acid-, lipid-, and nucleotide-metabolism(s), as well as altered or impaired bioenergetics, immune dysfunction, and redox imbalance in the body. In the infectious process, the viral pathogen hijacks two major human receptors, angiotensin-converting enzyme (ACE)-2 and/or neuropilin (NRP)-1, for initial adhesion to cell surface; then utilizes two major host proteases, TMPRSS2 and/or furin, to gain cellular entry; and finally employs an endosomal enzyme, cathepsin L (CTSL) for fusogenic release of its viral genome. The virus-induced HMRD results in 5 possible infectious outcomes: asymptomatic, mild, moderate, severe to fatal episodes; while the symptomatic acute COVID-19 condition could manifest into 3 clinical phases: (i) hypoxia and hypoxemia (Warburg effect), (ii) hyperferritinemia ('cytokine storm'), and (iii) thrombocytosis (coagulopathy). The mean incubation period for COVID-19 onset was estimated to be 5.1 days, and most cases develop symptoms after 14 days. The mean viral clearance times were 24, 30, and 39 days for acute, severe, and ICU-admitted COVID-19 patients, respectively. However, about 25-70% of virus-free COVID-19 survivors continue to sustain virus-induced HMRD and exhibit a wide range of symptoms that are persistent, exacerbated, or new 'onset' clinical incidents, collectively termed as post-acute sequelae of COVID-19 (PASC) or long COVID. PASC patients experience several debilitating clinical condition(s) with >200 different and overlapping symptoms that may last for weeks to months. Chronic PASC is a cumulative outcome of at least 10 different HMRD-related pathophysiological mechanisms involving both virus-derived virulence factors and a multitude of innate host responses. Based on HMRD and virus-free clinical impairments of different human organs/systems, PASC patients can be categorized into 4 different clusters or sub-phenotypes: sub-phenotype-1 (33.8%) with cardiac and renal manifestations; sub-phenotype-2 (32.8%) with respiratory, sleep and anxiety disorders; sub-phenotype-3 (23.4%) with skeleto-muscular and nervous disorders; and sub-phenotype-4 (10.1%) with digestive and pulmonary dysfunctions. This narrative review elucidates the effects of viral hijack on host cellular machinery during SARS-CoV-2 infection, ensuing detrimental effect(s) of virus-induced HMRD on human metabolism, consequential symptomatic clinical implications, and damage to multiple organ systems; as well as chronic pathophysiological sequelae in virus-free PASC patients. We have also provided a few evidence-based, human randomized controlled trial (RCT)-tested, precision nutrients to reset HMRD for health recovery of PASC patients.

Superoxide dismutase alterations in COVID-19: implications for disease severity and mortality prediction in the context of omicron variant infection

Background

In the few reports to date, the changes in superoxide dismutase (SOD), a key factor in cellular protection against superoxide, in COVID-19 have been very inconsistent and contradictory. There is also a lack of data on COVID-19 induced by Omicron variant. Further investigation is warranted to figure out SOD alterations in COVID-19, particularly within the context of ongoing Omicron variant infection, which may provide clues to its role within COVID-19 pathogenesis and open up new avenues for COVID-19 treatment.

Methods

SOD activity in 109 COVID-19 patients (including 46 severe cases and 63 mild to moderate cases) and 30 matched healthy controls were quantified. Demographic data, blood cell counts, biochemical indicators, coagulation indicators, and inflammatory markers were also recorded.

Results

SOD, an important key node, experienced a significant decrease in COVID-19, with the severe patients exhibiting lower activity compared to the mild to moderate patients and control healthy. Notably, severe patients who deceased had the lowest SOD activity. Correlation analysis revealed significant correlations between SOD and inflammatory markers, organ injury markers, coagulation dysfunction indicators, nutritional markers, and lymphocytes counts. The ROC curve also showed good performance for the differentiation of severe cases and the prediction of death.

Conclusion

SOD activity was significantly decreased in COVID-19 infected with Omicron variant and significantly correlated with systemic changes, and could be used as a biomarker to assess disease severity and predict mortality in COVID-19 clinical pathway management. Additionally, this finding will contribute to exploring new potential direction for the treatment of severe COVID-19 patients.

Unraveling lipid and inflammation interplay in cancer, aging and infection for novel theranostic approaches

The synergistic relationships between Cancer, Aging, and Infection, here referred to as the CAIn Triangle, are significant determinants in numerous health maladies and mortality rates. The CAIn-related pathologies exhibit close correlations with each other and share two common underlying factors: persistent inflammation and anomalous lipid concentration profiles in the membranes of affected cells. This study provides a comprehensive evaluation of the most pertinent interconnections within the CAIn Triangle, in addition to examining the relationship between chronic inflammation and specific lipidic compositions in cellular membranes. To tackle the CAIn-associated diseases, a suite of complementary strategies aimed at diagnosis, prevention, and treatment is proffered. Our holistic approach is expected to augment the understanding of the fundamental mechanisms underlying these diseases and highlight the potential of shared features to facilitate the development of novel theranostic strategies.

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.

COVID-19 metabolism: Mechanisms and therapeutic targets

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS‐CoV‐2‐induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID‐19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS‐CoV‐2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID‐19 metabolism. SARS‐CoV‐2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS‐CoV‐2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID‐19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS‐CoV‐2‐induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID‐19 pandemic.

Untargeted lipidomics reveals specific lipid profiles in COVID-19 patients with different severity from Campania region (Italy)

COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease's severity and patient's outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639-0.904) and outcome (AUC= 0.789, CI: 0.658-0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.

Enzymes in the time of COVID-19: An overview about the effects in the human body, enzyme market, and perspectives for new drugs

The rising pandemic caused by a coronavirus, resulted in a scientific quest to discover some effective treatments against its etiologic agent, the severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2). This research represented a significant scientific landmark and resulted in many medical advances. However, efforts to understand the viral mechanism of action and how the human body machinery is subverted during the infection are still ongoing. Herein, we contributed to this field with this compilation of the roles of both viral and human enzymes in the context of SARS‐CoV‐2 infection. In this sense, this overview reports that proteases are vital for the infection to take place: from SARS‐CoV‐2 perspective, the main protease (M^pro) and papain‐like protease (PL^pro) are highlighted; from the human body, angiotensin‐converting enzyme‐2, transmembrane serine protease‐2, and cathepsins (CatB/L) are pointed out. In addition, the influence of the virus on other enzymes is reported as the JAK/STAT pathway and the levels of lipase, enzymes from the cholesterol metabolism pathway, amylase, aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, and glyceraldehyde 3‐phosphate dehydrogenase are also be disturbed in SARS‐CoV‐2 infection. Finally, this paper discusses the importance of detailed enzymatic studies for future treatments against SARS‐CoV‐2, and how some issues related to the syndrome treatment can create opportunities in the biotechnological market of enzymes and the development of new drugs.