Dynamic modulations of urinary sphingolipid and glycerophospholipid levels in COVID-19 and correlations with COVID-19-associated kidney injuries

Diagnosis, Severity, and Prognosis from Potential Biomarkers of COVID-19 in Urine: A Review of Clinical and Omics Results

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has spurred an extraordinary scientific effort to better understand the disease's pathophysiology and develop diagnostic and prognostic tools to guide more precise and effective clinical management. Among the biological samples analyzed for biomarker identification, urine stands out due to its low risk of infection, non-invasive collection, and suitability for frequent, large-volume sampling. Integrating data from omics studies with standard biochemical analyses offers a deeper and more comprehensive understanding of COVID-19. This review aims to provide a detailed summary of studies published to date that have applied omics and clinical analyses on urine samples to identify potential biomarkers for COVID-19. In July 2024, an advanced search was conducted in Web of Science using the query: "covid* (Topic) AND urine (Topic) AND metabol* (Topic)". The search included results published up to 14 October 2024. The studies retrieved from this digital search were evaluated through a two-step screening process: first by reviewing titles and abstracts for eligibility, and then by retrieving and assessing the full texts of articles that met the specific criteria. The initial search retrieved 913 studies, of which 45 articles were ultimately included in this review. The most robust biomarkers identified include kynurenine, neopterin, total proteins, red blood cells, ACE2, citric acid, ketone bodies, hypoxanthine, amino acids, and glucose. The biological causes underlying these alterations reflect the multisystemic impact of COVID-19, highlighting key processes such as systemic inflammation, renal dysfunction, critical hypoxia, and metabolic stress.

Virus infection and sphingolipid metabolism

Cellular sphingolipids have vital roles in human virus replication and spread as they are exploited by viruses for cell entry, membrane fusion, genome replication, assembly, budding, and propagation. Intracellular sphingolipid biosynthesis triggers conformational changes in viral receptors and facilitates endosomal escape. However, our current understanding of how sphingolipids precisely regulate viral replication is limited, and further research is required to comprehensively understand the relationships between viral replication and endogenous sphingolipid species. Emerging evidence now suggests that targeting and manipulating sphingolipid metabolism enzymes in host cells is a promising strategy to effectively combat viral infections. Additionally, serum sphingolipid species and concentrations could function as potential serum biomarkers to help monitor viral infection status in different patients. In this work, we comprehensively review the literature to clarify how viruses exploit host sphingolipid metabolism to accommodate viral replication and disrupt host innate immune responses. We also provide valuable insights on the development and use of antiviral drugs in this area.

Comprehensive metabolic modulations of sphingolipids are promising severity indicators in COVID-19

The COVID-19 pandemic, caused by SARS-CoV-2, has had a significant worldwide impact, affecting millions of people. COVID-19 is characterized by a heterogenous clinical phenotype, potentially involving hyperinflammation and prolonged tissue damage, although the exact underlying mechanisms are yet to be fully understood. Sphingolipid metabolites, which govern cell survival and proliferation, have emerged as key players in inflammatory signaling and cytokine responses. Given the complex metabolic pathway of sphingolipids, this study aimed to understand their potential role in the pathogenesis of COVID-19. We conducted a comprehensive examination of sphingolipid modulations across groups classified based on disease severity, incorporating a time-course in serum and urine samples. Several sphingolipids, including sphingosine, lactosylceramide, and hexosylceramide, emerged as promising indicators of COVID-19 severity, as validated by correlation analyses conducted on both serum and urine samples. Other sphingolipids, such as sphingosine 1-phosphate, ceramides, and deoxy-dihydroceramides, decreased in both COVID-19 patients and individuals with non-COVID infectious diseases. This suggests that these sphingolipids are not specifically associated with COVID-19 but rather with pathological conditions caused by infectious diseases. Our analysis of urine samples revealed elevated levels of various sphingolipids, with changes dependent on disease severity, potentially highlighting the acute kidney injury associated with COVID-19. This study illuminates the intricate relationship between disturbed sphingolipid metabolism, COVID-19 severity, and clinical factors. These findings provide valuable insights into the broader landscape of inflammatory diseases.

Genetic and biochemical analysis of severe hypertriglyceridemia complicated with acute pancreatitis or with low post-heparin lipoprotein lipase mass

Severe hypertriglyceridemia is a pathological condition caused by genetic factors alone or in combination with environmental factors, sometimes leading to acute pancreatitis (AP). In this study, exome sequencing and biochemical analyses were performed in 4 patients with hypertriglyceridemia complicated by obesity or diabetes with a history of AP or decreased post-heparin LPL mass. In a patient with a history of AP, SNP rs199953320 resulting in LMF1 nonsense mutation and APOE rs7412 causing apolipoprotein E2 were both found in heterozygous form. Three patients were homozygous for APOA5 rs2075291, and one was heterozygous. ELISA and Western blot analysis of the serum revealed the existence of apolipoprotein A-V in the lipoprotein-free fraction regardless of the presence or absence of rs2075291; furthermore, the molecular weight of apolipoprotein A-V was different depending on the class of lipoprotein or lipoprotein-free fraction. Lipidomics analysis showed increased serum levels of sphingomyelin and many classes of glycerophospholipid; however, when individual patients were compared, the degree of increase in each class of phospholipid among cases did not coincide with the increases seen in total cholesterol and triglycerides. Moreover, phosphatidylcholine, lysophosphatidylinositol, and sphingomyelin levels tended to be higher in patients who experienced AP than those who did not, suggesting that these phospholipids may contribute to the onset of AP. In summary, this study revealed a new disease-causing gene mutation in LMF1, confirmed an association between overlapping of multiple gene mutations and severe hypertriglyceridemia, and suggested that some classes of phospholipid may be involved in the pathogenesis of AP.

Enrichment of Bioactive Lipids in Urinary Extracellular Vesicles and Evidence of Apoptosis in Kidneys of Hypertensive Diabetic Cathepsin B Knockout Mice after Streptozotocin Treatment

Cathepsin B (CtsB) is a ubiquitously expressed cysteine protease that plays important roles in health and disease. Urinary extracellular vesicles (uEVs) are released from cells associated with urinary organs. The antibiotic streptozotocin (STZ) is known to induce pancreatic islet beta cell destruction, diabetic nephropathy, and hypertension. We hypothesized that streptozotocin-induced diabetic kidney disease and hypertension result in the release of bioactive lipids from kidney cells that induce oxidative stress and renal cell death. Lipidomics was performed on uEVs isolated from CtsB knockout mice treated with or without STZ, and their kidneys were used to investigate changes in proteins associated with cell death. Lysophosphatidylethanolamine (LPE) (18:1), lysophosphatidylserine (LPS) (22:6), and lysophosphatidylglycerol (LPG) (22:5) were among the bioactive lipids enriched in uEVs from CtsB knockout mice treated with STZ compared to untreated CtsB mice (n = 3 uEV preparations per group). Anti-oxidant programming was activated in the kidneys of the CtsB knockout mice treated with STZ, as indicated by increased expression of glutathione peroxidase 4 (GPX4) and the cystine/glutamate antiporter SLC7A11 (XCT) (n = 4 mice per group), which was supported by a higher reactivity to 4-hydroxy-2-nonenal (4-HNE), a marker for oxidative stress (n = 3 mice per group). Apoptosis but not ferroptosis was the ongoing form of cell death in these kidneys as cleaved caspase-3 levels were significantly elevated in the STZ-treated CtsB knockout mice (n = 4 mice per group). There were no appreciable differences in the pro-ferroptosis enzyme acyl-CoA synthetase long-chain family member 4 (ACSL4) or the inflammatory marker CD93 in the kidneys (n = 3 mice per group), which further supports apoptosis as the prevalent mechanism of pathology. These data suggest that STZ treatment leads to oxidative stress, inducing apoptotic injury in the kidneys during the development of diabetic kidney disease and hypertension.

Alzheimer's disease manifests abnormal sphingolipid metabolism

Introduction

Alzheimer's disease (AD) is associated with disturbed metabolism, prompting investigations into specific metabolic pathways that may contribute to its pathogenesis and pathology. Sphingolipids have garnered attention due to their known physiological impact on various diseases.

Methods

We conducted comprehensive profiling of sphingolipids to understand their possible role in AD. Sphingolipid levels were measured in AD brains, Cerad score B brains, and controls, as well as in induced pluripotent stem (iPS) cells (AD, PS, and control), using liquid chromatography mass spectrometry.

Results

AD brains exhibited higher levels of sphingosine (Sph), total ceramide 1-phosphate (Cer1P), and total ceramide (Cer) compared to control and Cerad-B brains. Deoxy-ceramide (Deoxy-Cer) was elevated in Cerad-B and AD brains compared to controls, with increased sphingomyelin (SM) levels exclusively in Cerad-B brains. Analysis of cell lysates revealed elevated dihydroceramide (dhSph), total Cer1P, and total SM in AD and PS cells versus controls. Multivariate analysis highlighted the relevance of Sph, Cer, Cer1P, and SM in AD pathology. Machine learning identified Sph, Cer, and Cer1P as key contributors to AD.

Discussion

Our findings suggest the potential importance of Sph, Cer1P, Cer, and SM in the context of AD pathology. This underscores the significance of sphingolipid metabolism in understanding and potentially targeting mechanisms underlying AD.

Addressing the untargeted lipidomics challenge in urine samples: Comparative study of extraction methods by UHPLC-ESI-QTOF-MS

Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine's unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.

Development of an advanced liquid chromatography-tandem mass spectrometry measurement system for simultaneous sphingolipid analysis

Mass spectrometry-based lipidomics approaches offer valuable tools for the detection and quantification of various lipid species, including sphingolipids. The present study aimed to develop a new method to simultaneously detect various sphingolipid species that applies to diverse biological samples. We developed and validated a measurement system by employing a single-column liquid chromatography-mass spectrometry system utilizing a normal-phase separation mode with positive ionization. The measurement system provided precision with a coefficient of variant below 20% for sphingolipids in all types of samples, and we observed good linearity in diluted serum samples. This system can measure the following sphingolipids: sphingosine 1-phosphate (S1P), sphingosine (Sph), dihydroS1P (dhS1P), dihydroSph (dhSph), ceramide 1-phosphate (Cer1P), hexosylceramide (HexCer), lactosylceramide (LacCer), dh-ceramide, deoxy-ceramide, deoxy-dh-ceramide, and sphingomyelin (SM). By measuring these sphingolipids in cell lysates where S1P lyase expression level was modulated, we could observe significant and dynamic modulations of sphingolipids in a comprehensive manner. Our newly established and validated measurement system can simultaneously measure many kinds of sphingolipids in biological samples. It holds great promise as a valuable tool for laboratory testing applications to detect overall modulations of sphingolipids, which have been proposed to be involved in pathogenesis processes in a series of elegant basic research studies.

Alterations in urinary ceramides, sphingoid bases, and their phosphates among patients with kidney disease

Background

To avoid an invasive renal biopsy, noninvasive laboratory testing for the differential diagnosis of kidney diseases is a desirable goal. As sphingolipids are demonstrated to be involved in the pathogenesis of various kidney diseases, we investigated the possible usefulness of the simultaneous measurement of urinary sphingolipids for differentiating kidney diseases.

Materials and methods

Residual urine specimens were collected from patients who had been clinically diagnosed with chronic glomerulonephritis (CGN), diabetic mellitus (DM), systemic lupus erythematosus (SLE), and arterial hypertension (AH). The urinary sphingolipids-CERs C16:0, C18:0, C18:1, C20:0, C22:0, and C24:0; sphingosine [Sph]; dihydrosphingosine; sphingosine 1-phosphate [S1P]; and dihydroS1P [dhS1P]-were measured by liquid chromatography-tandem mass spectrometry. Based on the results, machine learning models were constructed to differentiate the various kidney diseases.

Results

The urinary S1P was higher in patients with DM than in other participants (P < 0.05), whereas dhS1P was lower in the CGN and AH groups compared with control participants (P < 0.05). Sph and dhSph were higher in patients with CGN, AH, and SLE than in those with control participants (P < 0.05). The urinary CERs were significantly higher in patients with CGN, AH, and SLE than in those with control participants (P < 0.05). As a results of constructing a machine learning model discriminating kidney diseases, the resulting diagnostic accuracy and precision were improved from 94.03% and 66.96% to 96.10% and 78.26% respectively, when the urinary CERs, Sph, dhSph, S1P, dhS1P, and their ratios were added to the models.

Conclusion

The urinary CERs, sphingoid bases, and their phosphates show alterations among kidney diseases, suggesting their potential involvement in the development of kidney injury.

Exploring salivary lipid profile changes in COVID-19 patients: Insights from mass spectrometry analysis

The most common COVID-19 testing relies on the use of nasopharyngeal swabs. However, this sampling step is very uncomfortable and is one of the biggest challenges regarding population testing. In the present study, the use of saliva as an alternative sample for COVID-19 diagnosis was investigated. Therefore, high-resolution mass spectrometry analysis and chemometric approaches were applied to salivary lipid extracts. Two data organizations were used: classical MS data and pseudo-MS image datasets. The latter transformed MS data into pseudo-images, simplifying data interpretation. Classification models achieved high accuracy, with pseudo-MS image data performing exceptionally well. PLS-DA with OPSDA successfully separated COVID-19 and healthy groups, serving as a potential diagnostic tool. The most important lipids for COVID-19 classification were elucidated and include sphingolipids, ceramides, phospholipids, and glycerolipids. These lipids play a crucial role in viral replication and the inflammatory response. While pseudo-MS image data excelled in classification, it lacked the ability to annotate important variables, which was performed using classical MS data. These findings have the potential to improve clinical diagnosis using rapid, non-invasive testing methods and accurate high-volume results.

Immunolocalization of Sphingolipid Catabolism Enzymes along the Nephron: Novel Early Urinary Biomarkers of Renal Damage

The objective of this study was to investigate whether the activity of enzymes involved in sphingolipid catabolism could be biomarkers to predict early renal damage in streptozotocin (STZ)-induced diabetic rats and Angiotensin II (Ang II)-induced hypertension rats. Diabetic and hypertensive rats had no changes in plasma creatinine concentration. However, transmission electron microscopy (TEM) analysis showed slight ultrastructural changes in the glomeruli and tubular epithelial cells from diabetic and hypertensive rats. Our results show that the acid sphingomyelinase (aSMase) and neutral sphingomyelinase (nSMase) activity increased in the urine of diabetic rats and decreased in hypertensive rats. Only neutral ceramidase (nCDase) activity increased in the urine of diabetic rats. Furthermore, the immunofluorescence demonstrated positive staining for the nSMase, nCDase, and sphingosine kinase (SphK1) in glomerular mesangial cells, proximal tubule, ascending thin limb of the loop of Henle, thick ascending limb of Henle's loop, and principal cells of the collecting duct in the kidney. In conclusion, our results suggest that aSMase and nCDase activity in urine could be a novel predictor of early slight ultrastructural changes in the nephron, aSMase and nCDase as glomerular injury biomarkers, and nSMase as a tubular injury biomarker in diabetic and hypertensive rats.

Deep phenotyping of the lipidomic response in COVID-19 and non-COVID-19 sepsis

BACKGROUND

Lipids may influence cellular penetrance by viral pathogens and the immune response that they evoke. We deeply phenotyped the lipidomic response to SARs-CoV-2 and compared that with infection with other pathogens in patients admitted with acute respiratory distress syndrome to an intensive care unit (ICU).

METHODS

Mass spectrometry was used to characterise lipids and relate them to proteins, peripheral cell immunotypes and disease severity.

RESULTS

Circulating phospholipases (sPLA2, cPLA2 (PLA2G4A) and PLA2G2D) were elevated on admission in all ICU groups. Cyclooxygenase, lipoxygenase and epoxygenase products of arachidonic acid (AA) were elevated in all ICU groups compared with controls. sPLA2 predicted severity in COVID-19 and correlated with TxA2, LTE4 and the isoprostane, iPF2α-III, while PLA2G2D correlated with LTE4. The elevation in PGD2, like PGI2 and 12-HETE, exhibited relative specificity for COVID-19 and correlated with sPLA2 and the interleukin-13 receptor to drive lymphopenia, a marker of disease severity. Pro-inflammatory eicosanoids remained correlated with severity in COVID-19 28 days after admission. Amongst non-COVID ICU patients, elevations in 5- and 15-HETE and 9- and 13-HODE reflected viral rather than bacterial disease. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflected disease severity in COVID-19. In healthy marines, these lipids rose with seroconversion. Eicosanoids linked variably to the peripheral cellular immune response. PGE2, TxA2 and LTE4 correlated with T cell activation, as did PGD2 with non-B non-T cell activation. In COVID-19, LPS stimulated peripheral blood mononuclear cell PGF2α correlated with memory T cells, dendritic and NK cells while LA and DiHOMEs correlated with exhausted T cells. Three high abundance lipids - ChoE 18:3, LPC-O-16:0 and PC-O-30:0 - were altered specifically in COVID. LPC-O-16:0 was strongly correlated with T helper follicular cell activation and all three negatively correlated with multi-omic inflammatory pathways and disease severity.

CONCLUSIONS

A broad based lipidomic storm is a predictor of poor prognosis in ARDS. Alterations in sPLA2, PGD2 and 12-HETE and the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients and correlate with the inflammatory response to link to disease severity.

Deep Phenotyping of the Lipidomic Response in COVID and non-COVID Sepsis

Lipids may influence cellular penetrance by pathogens and the immune response that they evoke. Here we find a broad based lipidomic storm driven predominantly by secretory (s) phospholipase A 2 (sPLA 2 ) dependent eicosanoid production occurs in patients with sepsis of viral and bacterial origin and relates to disease severity in COVID-19. Elevations in the cyclooxygenase (COX) products of arachidonic acid (AA), PGD 2 and PGI 2 , and the AA lipoxygenase (LOX) product, 12-HETE, and a reduction in the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients, correlate with the inflammatory response and link to disease severity. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflect disease severity in COVID-19. AA and LA metabolites and LPC-O-16:0 linked variably to the immune response. These studies yield prognostic biomarkers and therapeutic targets for patients with sepsis, including COVID-19. An interactive purpose built interactive network analysis tool was developed, allowing the community to interrogate connections across these multiomic data and generate novel hypotheses.

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.