Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis

NAD+ Metabolism Reprogramming Mediates Irradiation-Induced Immunosuppressive Polarization of Macrophages

PURPOSE

Radiation therapy stands as an important complementary treatment for head and neck squamous cell carcinoma (HNSCC), yet it does not invariably result in complete tumor regression. The infiltration of immunosuppressive macrophages is believed to mediate the radiation therapy resistance, whose mechanism remains largely unexplored. This study aimed to elucidate the role of immunosuppressive macrophages during radiation therapy and the associated underlying mechanisms.

METHODS AND MATERIALS

Male C3H mice bearing syngeneic SCC-VII tumor received irradiation (2 × 8 Gy). The impact of irradiation on tumor-infiltrating macrophages was assessed. Bone marrow-derived macrophages were evaluated in differentiation, proliferation, migration, and inflammatory cytokines after treatment of irradiated tumor culture medium and irradiated tumor-derived extracellular vesicles (irTEVs). A comprehensive metabolomics profiling of the irTEVs was conducted using liquid chromatography-mass spectrometry, whereas key metabolites were investigated for their role in the mechanism of immunosuppression of macrophages in vitro and in vivo.

RESULTS

Radiation therapy on SCC-VII syngeneic graft tumors increased polarization of both M1 and M2 macrophages in the tumor microenvironment and drove infiltrated macrophages toward an immunosuppressive phenotype. Irradiation-induced polarization and immunosuppression of macrophages were dependent on irTEVs which delivered an increased amount of niacinamide (NAM) to macrophages. NAM directly bound to the nuclear factor kappa-B transcriptional activity regulator USP7, through which NAM reduced translocation of nuclear factor kappa-B into the nucleus, thereby decreasing the release of cytokines interleukin 6 and interleukin 8. Increased enzyme activity of NAM phosphoribosyl transferase which is the rate-limiting enzyme of NAD+ metabolism, contributed to the irradiation-induced accumulation levels of NAM in irradiated HNSCC and irTEVs. Inhibition of NAM phosphoribosyl transferase decreased NAM levels in irTEVs and increased radiation therapy sensitivity by alleviating the immunosuppressive function of macrophages.

CONCLUSIONS

Radiation therapy could induce NAD+ metabolic reprogramming of HNSCC cells, which regulate macrophages toward an immunosuppressive phenotype. Pharmacologic targeting of NAD+ metabolism might be a promising strategy for radiation therapy sensitization of HNSCC.

CE-MS-Based Clinical Metabolomics of Human Plasma

Capillary electrophoresis coupled to mass spectrometry (CE-MS) has emerged as a powerful analytical technique with significant implications for clinical research and diagnostics. The integration of information from CE and MS strengthens confidence in the identification of compounds present in clinical samples. The ability of CE to separate molecules based on their electrophoretic mobility coupled to MS enables the accurate identification and quantification of analytes, even in complex biological matrices such as human plasma.Here, we present a detailed protocol for an untargeted metabolomics study using CE-MS and its application in a study on human plasma from patients suffering Long COVID syndrome. The protocol ranges from sample preparation to biological interpretation, detailing a workflow enabling the analysis of cationic and anionic compounds, metabolite identification, and data processing.

Lithocholic acid phenocopies anti-ageing effects of calorie restriction

Calorie restriction (CR) is a dietary intervention used to promote health and longevity1,2. CR causes various metabolic changes in both the production and the circulation of metabolites1; however, it remains unclear which altered metabolites account for the physiological benefits of CR. Here we use metabolomics to analyse metabolites that exhibit changes in abundance during CR and perform subsequent functional validation. We show that lithocholic acid (LCA) is one of the metabolites that alone can recapitulate the effects of CR in mice. These effects include activation of AMP-activated protein kinase (AMPK), enhancement of muscle regeneration and rejuvenation of grip strength and running capacity. LCA also activates AMPK and induces life-extending and health-extending effects in Caenorhabditis elegans and Drosophila melanogaster. As C. elegans and D. melanogaster are not able to synthesize LCA, these results indicate that these animals are able to transmit the signalling effects of LCA once administered. Knockout of AMPK abrogates LCA-induced phenotypes in all the three animal models. Together, we identify that administration of the CR-mediated upregulated metabolite LCA alone can confer anti-ageing benefits to metazoans in an AMPK-dependent manner.

Intrinsic Factors Behind the Long-COVID: V. Immunometabolic Disorders

The complex link between COVID-19 and immunometabolic diseases demonstrates the important interaction between metabolic dysfunction and immunological response during viral infections. Severe COVID-19, defined by a hyperinflammatory state, is greatly impacted by underlying chronic illnesses aggravating the cytokine storm caused by increased levels of Pro-inflammatory cytokines. Metabolic reprogramming, including increased glycolysis and altered mitochondrial function, promotes viral replication and stimulates inflammatory cytokine production, contributing to illness severity. Mitochondrial metabolism abnormalities, strongly linked to various systemic illnesses, worsen metabolic dysfunction during and after the pandemic, increasing cardiovascular consequences. Long COVID-19, defined by chronic inflammation and immune dysregulation, poses continuous problems, highlighting the need for comprehensive therapy solutions that address both immunological and metabolic aspects. Understanding these relationships shows promise for effectively managing COVID-19 and its long-term repercussions, which is the focus of this review paper.

Combinatorial lipidomics and proteomics underscore erythrocyte lipid membrane aberrations in the development of adverse cardio-cerebrovascular complications in maintenance hemodialysis patients

Patients on maintenance hemodialysis exhibit a notably higher risk of cardio-cerebrovascular complications that constitute the major cause of death. Preceding studies have reported conflicting associations between traditional lipid measures and clinical outcome in dialysis patients. In this prospective longitudinal study, we utilized quantitative lipidomics to elucidate, at molecular resolution, changes in lipidome profiles of erythrocyte and plasma samples collected from maintenance hemodialysis patients followed up for 86 months (≈7 years). Primary outcome was defined as cardiovascular-related deaths or new-onset cardio-cerebrovascular events. Cox regression model uncovered plasma/erythrocyte lipids associated with incident cardio-cerebrovascular events in the erythrocyte cohort (n = 117 patients, 37 events) and plasma cohort (n = 45 patients, 11 events), respectively. Both the erythrocyte lipid panel [PA 40:5, PI 34:2, PC 42:6, AUC = 0.83] and plasma lipid panel [PC O-34:1, GM3 18:1; O2/25:0, TG 44:1(16:1_28:0), AUC = 0.94] significantly improved the prediction of cardio-cerebrovascular-related outcome compared to the base model comprising age, sex and dialysis vintage alone. Our findings underscore the pathophysiological significance of anionic phospholipid accretion in erythrocytes in the development of cardio-cerebrovascular complications in dialysis patients. In particular, distorted membrane lipid asymmetry leads to compromised membrane deformability, aberrant cell-cell interactions and altered glutathione metabolism in the erythrocytes of high-risk individuals even at relatively early stage of hemodialysis. Our findings thus underscore the importance of maintaining the RBC pool to lower the risk of cardio-cerebrovascular complications in dialysis patients.

Predicting Disease-Metabolite Associations Based on the Metapath Aggregation of Tripartite Heterogeneous Networks

The exploration of the interactions between diseases and metabolites holds significant implications for the diagnosis and treatment of diseases. However, traditional experimental methods are time-consuming and costly, and current computational methods often overlook the influence of other biological entities on both. In light of these limitations, we proposed a novel deep learning model based on metapath aggregation of tripartite heterogeneous networks (MAHN) to explore disease-related metabolites. Specifically, we introduced microbes to construct a tripartite heterogeneous network and employed graph convolutional network and enhanced GraphSAGE to learn node features with metapath length 3. Additionally, we utilized node-level and semantic-level attention mechanisms, a more granular approach, to aggregate node features with metapath length 2. Finally, the reconstructed association probability is obtained by fusing features from different metapaths into the bilinear decoder. The experiments demonstrate that the proposed MAHN model achieved superior performance in five-fold cross-validation with Acc (91.85%), Pre (90.48%), Recall (93.53%), F1 (91.94%), AUC (97.39%), and AUPR (97.47%), outperforming four state-of-the-art algorithms. Case studies on two complex diseases, irritable bowel syndrome and obesity, further validate the predictive results, and the MAHN model is a trustworthy prediction tool for discovering potential metabolites. Moreover, deep learning models integrating multi-omics data represent the future mainstream direction for predicting disease-related biological entities.

Exosomes and SARS-CoV-2 infection

Exosomes, which are small extracellular vesicles, are of particular interest in studies on SARS-CoV-2 infection because of their crucial role in intercellular communication. These vesicles are released by several cell types and are rich in "cargo" such as proteins, lipids, and nucleic acids, which are vital for regulating immune response and viral pathogenesis. Exosomes have been reported to be involved in viral transmission, immune escape mechanisms, and illness development in SARS-CoV-2 infection. This review examines the current research on the contribution of exosomes to the interplay between the virus and host cells, highlighting their potential as diagnostic biomarkers and therapeutic targets in combating COVID-19.

Lopes T, de Oliveira JM, Raimundo JRS, Furtado DZS, Fonseca FLA, Oliveira RV, Cardoso DR, Carrilho E, Assunção NA. Multiplatform Metabolomics: Enhancing the Severity Risk Prognosis of SARS-CoV-2 Infection

Concerns about the SARS-CoV-2 outbreak (COVID-19) continue to persist even years later, with the emergence of new variants and the risk of disease severity. Common clinical symptoms, like cough, fever, and respiratory symptoms, characterize the noncritical patients, classifying them from mild to moderate. In a more severe and complex scenario, the virus infection can affect vital organs, resulting, for instance, in pneumonia and impaired kidney and heart function. However, it is well-known that subclinical symptoms at a metabolic level can be observed previously but require a proper diagnosis because viral replication on the host leaves a track with a different profile depending on the severity of the illness. Metabolomic profiles of mild, moderate, and severe COVID-19 patients were obtained by multiple platforms (LC-HRMS and MALDI-MS), increasing the chance to elucidate a prognosis for severity risk. A strong link was discovered between phenylalanine metabolism and increased COVID-19 severity symptoms, a pathway linked to cardiac and neurological consequences. Glycerophospholipids and sphingolipid metabolisms were also dysregulated linearly with the increasing symptom severity, which can be related to virus proliferation, immune system avoidance, and apoptosis escaping. Our data, endorsed by other literature, strengthens the notion that these pathways might play a vital role in a patient's prognosis.

Proteomics of circulating extracellular vesicles reveals diverse clinical presentations of COVID-19 but fails to identify viral peptides

Extracellular vesicles (EVs) released by virus-infected cells have the potential to encapsulate viral peptides, a characteristic that could facilitate vaccine development. Furthermore, plasma-derived EVs may elucidate pathological changes occurring in distal tissues during viral infections. We hypothesized that molecular characterization of EVs isolated from COVID-19 patients would reveal peptides suitable for vaccine development. Blood samples were collected from three cohorts: severe COVID-19 patients (G1), mild/asymptomatic cases (G2), and SARS-CoV-2-negative healthcare workers (G3). Samples were obtained at two time points: during the initial phase of the pandemic in early 2020 (m0) and eight months later (m8). Clinical data analysis revealed elevated inflammatory markers in G1. Notably, non-vaccinated individuals in G1 exhibited increased levels of neutralizing antibodies at m8, suggesting prolonged exposure to viral antigens. Proteomic profiling of EVs was performed using three distinct methods: immunocapture (targeting CD9), ganglioside-capture (utilizing Siglec-1) and size-exclusion chromatography (SEC). Contrary to our hypothesis, this analysis failed to identify viral peptides. These findings were subsequently validated through Western blot analysis targeting the RBD of the SARS-CoV-2 Spike protein's and comparative studies using samples from experimentally infected Syrian hamsters. Furthermore, analysis of the EV cargo revealed a diverse molecular profile, including components involved in the regulation of viral replication, systemic inflammation, antigen presentation, and stress responses. These findings underscore the potential significance of EVs in the pathogenesis and progression of COVID-19.

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanisms-are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.

Circulating Proteins Associated with Anti-IL6 Receptor Therapeutic Resistance in the Sera of Patients with Severe COVID-19

Circulating proteomes provide a snapshot of the physiological state of a human organism responding to pathogenic challenges and drug interventions. The outcomes of patients with COVID-19 and acute respiratory distress syndrome triggered by the SARS-CoV2 virus remain uncertain. Tocilizumab is an anti-interleukin-6 treatment that exerts encouraging clinical activity by controlling the cytokine storm and improving respiratory distress in patients with COVID-19. We investigate the biological determinants of therapeutic outcomes after tocilizumab treatment. Overall, 28 patients hospitalized due to severe COVID-19 who were treated with tocilizumab intravenously were included in this study. Sera were collected before and after tocilizumab, and the patient's outcome was evaluated until day 30 post-tocilizumab infusion for favorable therapeutic response to tocilizumab and mortality. Hyperreaction monitoring measurements by liquid chromatography-mass spectrometry-based proteomic analysis with data-independent acquisition quantified 510 proteins and 7019 peptides in the serum of patients. Alterations in the serum proteome reflect COVID-19 outcomes in patients treated with tocilizumab. Our results suggested that circulating proteins associated with the most significant prognostic impact belonged to the complement system, platelet degranulation, acute-phase proteins, and the Fc-epsilon receptor signaling pathway. Among these, upregulation of the complement system by activation of the classical pathway was associated with poor response to tocilizumab, and upregulation of Fc-epsilon receptor signaling was associated with lower mortality.

Pangolin scales as adaptations for innate immunity against pathogens

BACKGROUND

Pangolins are the only mammals that have overlapping scales covering most of their bodies, and they play a crucial role in the ecosystem, biological research, and human health and disease. Previous studies indicated pangolin scale might provide an important mechanical defense to themselves. The origin and exact functions of this unique trait remain a mystery. Using a multi-omics analysis approach, we report a novel functional explanation for how mammalian scales can provide host-pathogen defense.

RESULTS

Our data suggest that pangolin scales have a sophisticated structure that could potentially trap pathogens. We identified numerous proteins and metabolites exhibiting antimicrobial activity, which could suggest a role for scales in pathogen defense. Notably, we found evidence suggesting the presence of exosomes derived from diverse cellular origins, including mesenchymal stem cells, immune cells, and keratinocytes. This observation suggests a complex interplay where various cell types may contribute to the release of exosomes and antimicrobial compounds at the interface between scales and viable tissue. These findings indicate that pangolin scales may serve as a multifaceted defense system, potentially contributing to innate immunity. Comparisons with human nail and hair revealed pangolin-specific proteins that were enriched in functions relating to sensing, immune responses, neutrophil degranulation, and stress responses. We demonstrated the antimicrobial activity of key pangolin scale components on pathogenic bacteria by antimicrobial assays.

CONCLUSIONS

This study identifies a potential role of pangolin scales and implicates scales, as possible determinants of pathogen defense due to their structure and contents. We indicate for the first time the presence of exosomes in pangolin scales and propose the new functions of scales and their mechanisms. This new mechanism could have implications for multiple fields, including providing interesting new research directions and important insights that can be useful for synthesizing and implementing new biomimetic antimicrobial approaches.

Serum lipidome reveals lipid metabolic dysregulation in severe fever with thrombocytopenia syndrome

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is a rapidly progressing infectious disease with a high fatality rate caused by a novel bunyavirus (SFTSV). The role of lipids in viral infections is well-documented; however, the specific alterations in lipid metabolism during SFTSV infection remain elusive. This study aims to elucidate the lipid metabolic dysregulations in the early stages of SFTS patients.

METHODS

This study prospectively collected peripheral blood sera from 11 critical SFTS patients, 37 mild SFTS patients, and 23 healthy controls during the early stages of infection for lipidomics analysis. A systematic bioinformatics analysis was conducted from three aspects integrating lipid differential expressions, lipid differential correlations, and lipid-clinical indices correlations to reveal the serum lipid metabolic dysregulation in SFTSV-infected individuals.

RESULTS

Our findings reveal significant lipid metabolic dysregulation in SFTS patients. Specifically, compared to healthy controls, SFTS patients exhibited three distinct modes of lipid differential expression: increased levels of lipids including phosphatidylserine (PS), hexosylceramide (HexCer), and triglycerides (TG); decreased levels of lipids including lysophosphatidylcholine (LPC), acylcarnitine (AcCa), and cholesterol esters (ChE); and lipids showing "dual changes" including phosphatidylcholine (PC) and phosphatidylethanolamine (PE). Finally, based on lipid metabolic pathways and literature analysis, we systematically elucidated the potential mechanisms underlying lipid metabolic dysregulation in the early stage of SFTSV infection.

CONCLUSIONS

Our study presents the first global serum lipidome profile and reveals the lipid metabolic dysregulation patterns in the early stage of SFTSV infection. These findings provide a new basis for the diagnosis, treatment, and further investigation of the disease.

Metabolomic profiling of COVID-19 using serum and urine samples in intensive care and medical ward cohorts

The COVID-19 pandemic remains a significant global health threat, with uncertainties persisting regarding the factors determining whether individuals experience mild symptoms, severe conditions, or succumb to the disease. This study presents an NMR metabolomics-based approach, analysing 80 serum and urine samples from COVID-19 patients (34 intensive care patients and 46 hospitalized patients) and 32 from healthy controls. Our research identifies discriminant metabolites and clinical variables relevant to COVID-19 diagnosis and severity. These discriminant metabolites play a role in specific pathways, mainly "Phenylalanine, tyrosine and tryptophan biosynthesis", "Phenylalanine metabolism", "Glycerolipid metabolism" and "Arginine and proline metabolism". We propose a three-metabolite diagnostic panel-comprising isoleucine, TMAO, and glucose-that effectively discriminates COVID-19 patients from healthy individuals, achieving high efficiency. Furthermore, we found an optimal biomarker panel capable of efficiently classify disease severity considering both clinical characteristics (obesity/overweight, dyslipidemia, and lymphocyte count) together with metabolites content (ethanol, TMAO, tyrosine and betaine).

COVID-19 detection from exhaled breath

The SARS-CoV-2 coronavirus emerged in 2019 causing a COVID-19 pandemic that resulted in 7 million deaths out of 770 million reported cases over the next 4 years. The global health emergency called for unprecedented efforts to monitor and reduce the rate of infection, pushing the study of new diagnostic methods. In this paper, we introduce a cheap, fast, and non-invasive COVID-19 detection system, which exploits only exhaled breath. Specifically, provided an air sample, the mass spectra in the 10-351 mass-to-charge range are measured using an original micro and nano-sampling device coupled with a high-precision spectrometer; then, the raw spectra are processed by custom software algorithms; the clean and augmented data are eventually classified using state-of-the-art machine-learning algorithms. An uncontrolled clinical trial was conducted between 2021 and 2022 on 302 subjects who were concerned about being infected, either due to exhibiting symptoms or having recently recovered from illness. Despite the simplicity of use, our system showed a performance comparable to the traditional polymerase-chain-reaction and antigen testing in identifying cases of COVID-19 (that is, 95% accuracy, 94% recall, 96% specificity, and 92% [Formula: see text]-score). In light of these outcomes, we think that the proposed system holds the potential for substantial contributions to routine screenings and expedited responses during future epidemics, as it yields results comparable to state-of-the-art methods, providing them in a more rapid and less invasive manner.

Nobiletin promotes lipolysis of white adipose tissue in a circadian clock-dependent manner

Nobiletin has been reported to protect against obesity-related metabolic disorders by enhancing the circadian rhythm; however its effects on lipid metabolism in adipose tissue are unclear. In this study, mice were fed with high-fat diet (HFD) for four weeks firstly and gavaged with 50 or 200 mg/kg bodyweight/day nobiletin at Zeitgeber time (ZT) 4 for another four weeks while still receiving HFD. At the end of the 8-week experimental period, the mice were sacrificed at ZT4 or ZT8 on the same day. Mature 3T3-L1 adipocytes were treated with nobiletin in the presence or absence of siBmal1, siRora, siRorc, SR8278 or SR9009. Nobiletin reduced the weight of white adipose tissue (WAT) and the size of adipocytes in WAT. At ZT4, nobiletin decreased the TG, TC and LDL-c levels and increased serum FFA level and glucose tolerance. Nobiletin triggered the lipolysis of mesenteric and epididymal WAT at both ZT4 and ZT16. Nobiletin increased the level of RORγ at ZT16, that of BMAL1 and PPARγ at ZT4, and that of ATGL at both ZT4 and ZT16. Nobiletin increased lipolysis and ATGL levels in 3T3-L1 adipocytes in Bmal1- or Rora/c- dependent manner. Dual luciferase assay indicated that nobiletin enhanced the transcriptional activation of RORα/γ on Atgl promoter and decreased the repression of RORα/γ on PPARγ-binding PPRE. Promoter deletion analysis indicated that nobiletin inhibited the suppression of PPARγ-mediated Atgl transcription by RORα/γ. Taken together, nobiletin elevated lipolysis in WAT by increasing ATGL levels through activating the transcriptional activity of RORα/γ and decreasing the repression of RORα/γ on PPARγ-binding PPRE.

Withdrawn: Combinatorial lipidomics and proteomics underscore erythrocyte lipid membrane aberrations in the development of adverse cardio-cerebrovascular complications in maintenance hemodialysis patients

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). The authors reached out to the Publisher to alert the Publisher to incorrect text published in the article. After investigating the situation, the journal came to the conclusion that the wrong version of the file was sent by the authors to the production team during the proof stage and the misplaced text was not noticed by the authors when they approved the final version. After consulting with the Editor-in-Chief of the journal, the decision was made to withdraw the current version of the article.

Lipid droplets sequester palmitic acid to disrupt endothelial ciliation and exacerbate atherosclerosis in male mice

Disruption of ciliary homeostasis in vascular endothelial cells has been implicated in the development of atherosclerosis. However, the molecular basis for the regulation of endothelial cilia during atherosclerosis remains poorly understood. Herein, we provide evidence in male mice that the accumulation of lipid droplets in vascular endothelial cells induces ciliary loss and contributes to atherosclerosis. Triglyceride accumulation in vascular endothelial cells differentially affects the abundance of free fatty acid species in the cytosol, leading to stimulated lipid droplet formation and suppressed protein S-palmitoylation. Reduced S-palmitoylation of ciliary proteins, including ADP ribosylation factor like GTPase 13B, results in the loss of cilia. Restoring palmitic acid availability, either through pharmacological inhibition of stearoyl-CoA desaturase 1 or a palmitic acid-enriched diet, significantly restores endothelial cilia and mitigates the progression of atherosclerosis. These findings thus uncover a previously unrecognized role of lipid droplets in regulating ciliary homeostasis and provide a feasible intervention strategy for preventing and treating atherosclerosis.

A comprehensive IDA and SWATH-DIA Lipidomics and Metabolomics dataset: SARS-CoV-2 case control study

A significant hurdle in untargeted lipid/metabolomics research lies in the absence of reliable, cross-validated spectral libraries, leading to a considerable portion of LC-MS features being labeled as unknowns. Despite continuous advancement in annotation tools and libraries, it is important to safeguard, publish and share acquired data through public repositories. Embracing this trend of data sharing not only promotes efficient resource utilization but also paves the way for future repurposing and in-depth analysis; ultimately advancing our comprehension of Covid-19 and other diseases. In this work, we generated an extensive MS-dataset of 39 Covid-19 infected patients versus age- and gender-matched 39 healthy controls. We implemented state of the art acquisition techniques including IDA and SWATH-DIA to ensure a thorough insight in the lipidome and metabolome, ensuring a repurposable dataset.

Exploring metabolic anomalies in COVID-19 and post-COVID-19: a machine learning approach with explainable artificial intelligence

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection's long-term consequences. This study employs a novel approach utilizing machine learning (ML) and explainable artificial intelligence (XAI) to analyze metabolic alterations in COVID-19 and Post-COVID-19 patients. Samples were taken from a cohort of 142 COVID-19, 48 Post-COVID-19, and 38 control patients, comprising 111 identified metabolites. Traditional analysis methods, like PCA and PLS-DA, were compared with ML techniques, particularly eXtreme Gradient Boosting (XGBoost) enhanced by SHAP (SHapley Additive exPlanations) values for explainability. XGBoost, combined with SHAP, outperformed traditional methods, demonstrating superior predictive performance and providing new insights into the metabolic basis of the disease's progression and aftermath. The analysis revealed metabolomic subgroups within the COVID-19 and Post-COVID-19 conditions, suggesting heterogeneous metabolic responses to the infection and its long-term impacts. Key metabolic signatures in Post-COVID-19 include taurine, glutamine, alpha-Ketoglutaric acid, and LysoPC a C16:0. This study highlights the potential of integrating ML and XAI for a fine-grained description in metabolomics research, offering a more detailed understanding of metabolic anomalies in COVID-19 and Post-COVID-19 conditions.

Lipidomics and metabolomics investigation into the effect of DAG dietary intervention on hyperuricemia in athletes

The occurrence of hyperuricemia (HUA; elevated serum uric acid) in athletes is relatively high despite that exercise can potentially reduce the risk of developing this condition. Although recent studies have shown the beneficial properties of DAG in improving overall metabolic profiles, a comprehensive understanding of the effect of DAG in modulating HUA in athletes is still lacking. In this study, we leveraged combinatorial lipidomics and metabolomics to investigate the effect of replacing TAG with DAG in the diet of athletes with HUA. A total of 1,074 lipids and metabolites from 94 classes were quantitated in serum from 33 athletes, who were categorized into responders and non-responders based on whether serum uric acid levels returned to healthy levels after the DAG diet intervention. Lipidomics and metabolomics analyses revealed lower levels of xanthine and uric acid in responders, accompanied by elevated plasmalogen phosphatidylcholines and diminished acylcarnitine levels. Our results highlighted the mechanisms behind how the DAG diet circumvented the risk and effects associated with high uric acid via lowered triglycerides at baseline influencing the absorption of DAG resulting in a decline in ROS and uric acid production, increased phospholipid levels associated with reduced p-Cresol metabolism potentially impacting on intestinal excretion of uric acid as well as improved ammonia recycling contributing to decreased serum uric acid levels in responders. These observed alterations might be suggestive that successful implementation of the DAG diet can potentially minimize the likelihood of a potentially vicious cycle occurring in high uric acid, elevated ROS, and impaired mitochondrial metabolism environment.

CYP7B1 deficiency impairs myeloid cell activation in autoimmune disease of the central nervous system

Dysregulation of cholesterol metabolism underlies neurodegenerative disease and is increasingly implicated in neuroinflammatory diseases, such as multiple sclerosis (MS). Cytochrome P450 family 7 subfamily B member 1 (CYP7B1) is a key enzyme in alternative cholesterol metabolism. A recessive mutation in the gene CYP7B1 is known to cause a neurodegenerative disease, hereditary spastic paraplegia type 5 and oxysterol accumulation. However, the role of CYP7B1 in neuroinflammation has been little revealed. In this study, we induced experimental autoimmune encephalomyelitis (EAE), as a murine model of MS, using CYP7B1 homozygous knockout (KO) mice. We found that CYP7B1 deficiency can significantly attenuate EAE severity. CYP7B1 deficiency is sufficient to reduce leukocyte infiltration into the central nervous system, suppress proliferation of pathogenic CD4+ T cells, and decrease myeloid cell activation during EAE. Additionally, live-animal imaging targeting translocator protein expression, an outer mitochondrial membrane protein biomarker of neuroinflammation, showed that CYP7B1 deficiency results in suppressed neuroinflammation. Using human monocyte-derived microglia-like cellular disease model and primary microglia of CYP7B1 KO mice, we also found that activation of microglia of CYP7B1 deficiency was impaired. These cumulative results suggest that CYP7B1 can regulate neuroinflammation, thus providing potential new targets for therapeutic intervention.

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.

Lipidomic and metabolomic changes in community-acquired and COVID-19 pneumonia

This prospective observational study compared the 1H NMR blood lipidomes and metabolomes of 71 patients with community-acquired pneumonia (CAP), 75 patients with COVID-19 pneumonia, and 75 healthy controls (matched by age and sex) to identify potential biomarkers and pathways associated with respiratory infections. Both pneumonia groups had comparable severity indices, including mortality, invasive mechanical ventilation, and intensive care unit admission rates. Patients with COVID-19 pneumonia exhibited more pronounced hypolipidemia, with significantly lower levels of total cholesterol and LDL-c compared to patients with CAP. Atherogenic lipoprotein subclasses (VLDL-cholesterol, IDL-cholesterol, IDL-triglyceride, and LDL-triglyceride/LDL-cholesterol) were significantly increased in severe cases of both pneumonia types, while lower HDL-c and small, dense HDL particles were associated with more severe illness. Both infected groups showed decreased esterified cholesterol and increased triglycerides, along with reduced phosphatidylcholine, lysophosphatidylcholine, PUFA, omega-3 fatty acids, and DHA. Additionally, infected patients had elevated levels of glucose, lactate, 3-hydroxybutyrate, and acetone, which are linked to inflammation, hypoxemia, and sepsis. Increased levels of branched-chain amino acids, alanine, glycine, and creatine, which are involved in energy metabolism and protein catabolism, were also observed. Neurotransmitter synthesis metabolites like histidine and glutamate were higher in infected patients, especially those with COVID-19. Notably, severe infections showed a significant decrease in glutamine, essential for lymphocyte and macrophage energy. The severity of COVID-19 pneumonia was also associated with elevated glycoprotein levels (glycoprotein A, glycoprotein B, and glycoprotein F), indicating an inflammatory state. These findings suggest that metabolomic and lipidomic changes in pneumonia are connected to bioenergetic pathways regulating the immune response.

Post-Acute Sequelae and Mitochondrial Aberration in SARS-CoV-2 Infection

This review investigates links between post-acute sequelae of SARS-CoV-2 infection (PASC), post-infection viral persistence, mitochondrial involvement and aberrant innate immune response and cellular metabolism during SARS-CoV-2 infection. Advancement of proteomic and metabolomic studies now allows deeper investigation of alterations to cellular metabolism, autophagic processes and mitochondrial dysfunction caused by SARS-CoV-2 infection, while computational biology and machine learning have advanced methodologies of predicting virus-host gene and protein interactions. Particular focus is given to the interaction between viral genes and proteins with mitochondrial function and that of the innate immune system. Finally, the authors hypothesise that viral persistence may be a function of mitochondrial involvement in the sequestration of viral genetic material. While further work is necessary to understand the mechanisms definitively, a number of studies now point to the resolution of questions regarding the pathogenesis of PASC.

β-Caryophyllene Confers Cardioprotection by Scavenging Radicals and Blocking Ferroptosis

Ferroptosis is a form of regulated cell death triggered by iron-dependent lipid peroxidation and has been associated with heart diseases. However, there are currently no approved drugs that specifically inhibit ferroptosis in clinical practice, which largely limits the translational potential of this novel target. Here, we demonstrated that β-caryophyllene (BCP; 150 μM), a natural dietary cannabinoid, protects cardiomyocytes against ferroptotic cell death induced by cysteine deprivation or glutathione peroxidase 4 (GPX4) inactivation. Moreover, BCP preserved the mitochondrial morphology and function during ferroptosis induction. Unexpectedly, BCP supported ferroptosis resistance independent of canonical antiferroptotic pathways. Our results further suggested that BCP may terminate radical chain reactions through interactions with molecular oxygen, which also explains why its oxidation derivative failed to suppress ferroptosis. Finally, oral BCP administration (50 mg/kg, daily) significantly alleviated doxorubicin (15 mg/kg, single i.p. injection)-induced cardiac ferroptosis and cardiomyopathy in mice. In conclusion, our data revealed the role of BCP as a natural antiferroptotic compound and suggest pharmacological modification based on BCP as a promising therapeutic strategy for treating ferroptosis-associated heart disorders.

Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40). Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients. We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

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.

Network-based integrative multi-omics approach reveals biosignatures specific to COVID-19 disease phases

Background

COVID-19 disease is characterized by a spectrum of disease phases (mild, moderate, and severe). Each disease phase is marked by changes in omics profiles with corresponding changes in the expression of features (biosignatures). However, integrative analysis of multiple omics data from different experiments across studies to investigate biosignatures at various disease phases is limited. Exploring an integrative multi-omics profile analysis through a network approach could be used to determine biosignatures associated with specific disease phases and enable the examination of the relationships between the biosignatures.

Aim

To identify and characterize biosignatures underlying various COVID-19 disease phases in an integrative multi-omics data analysis.

Method

We leveraged a multi-omics network-based approach to integrate transcriptomics, metabolomics, proteomics, and lipidomics data. The World Health Organization Ordinal Scale WHO Ordinal Scale was used as a disease severity reference to harmonize COVID-19 patient metadata across two studies with independent data. A unified COVID-19 knowledge graph was constructed by assembling a disease-specific interactome from the literature and databases. Disease-state specific omics-graphs were constructed by integrating multi-omics data with the unified COVID-19 knowledge graph. We expanded on the network layers of multiXrank, a random walk with restart on multilayer network algorithm, to explore disease state omics-specific graphs and perform enrichment analysis.

Results

Network analysis revealed the biosignatures involved in inducing chemokines and inflammatory responses as hubs in the severe and moderate disease phases. We observed distinct biosignatures between severe and moderate disease phases as compared to mild-moderate and mild-severe disease phases. Mild COVID-19 cases were characterized by a unique biosignature comprising C-C Motif Chemokine Ligand 4 (CCL4), and Interferon Regulatory Factor 1 (IRF1). Hepatocyte Growth Factor (HGF), Matrix Metallopeptidase 12 (MMP12), Interleukin 10 (IL10), Nuclear Factor Kappa B Subunit 1 (NFKB1), and suberoylcarnitine form hubs in the omics network that characterizes the moderate disease state. The severe cases were marked by biosignatures such as Signal Transducer and Activator of Transcription 1 (STAT1), Superoxide Dismutase 2 (SOD2), HGF, taurine, lysophosphatidylcholine, diacylglycerol, triglycerides, and sphingomyelin that characterize the disease state.

Conclusion

This study identified both biosignatures of different omics types enriched in disease-related pathways and their associated interactions (such as protein-protein, protein-transcript, protein-metabolite, transcript-metabolite, and lipid-lipid interactions) that are unique to mild, moderate, and severe COVID-19 disease states. These biosignatures include molecular features that underlie the observed clinical heterogeneity of COVID-19 and emphasize the need for disease-phase-specific treatment strategies. The approach implemented here can be used to find associations between transcripts, proteins, lipids, and metabolites in other diseases.

Proteome analysis develops novel plasma proteins classifier in predicting the mortality of COVID-19

COVID-19 has been a global concern for 3 years, however, consecutive plasma protein changes in the disease course are currently unclear. Setting the mortality within 28 days of admission as the main clinical outcome, plasma samples were collected from patients in discovery and independent validation groups at different time points during the disease course. The whole patients were divided into death and survival groups according to their clinical outcomes. Proteomics and pathway/network analyses were used to find the differentially expressed proteins and pathways. Then, we used machine learning to develop a protein classifier which can predict the clinical outcomes of the patients with COVID-19 and help identify the high-risk patients. Finally, a classifier including C-reactive protein, extracellular matrix protein 1, insulin-like growth factor-binding protein complex acid labile subunit, E3 ubiquitin-protein ligase HECW1 and phosphatidylcholine-sterol acyltransferase was determined. The prediction value of the model was verified with an independent patient cohort. This novel model can realize early prediction of 28-day mortality of patients with COVID-19, with the area under curve 0.88 in discovery group and 0.80 in validation group, superior to 4C mortality and E-CURB65 scores. In total, this work revealed a potential protein classifier which can assist in predicting the outcomes of COVID-19 patients and providing new diagnostic directions.

Linoelaidic acid gavage has more severe consequences on triglycerides accumulation, inflammation and intestinal microbiota in mice than elaidic acid

This work aims to study the effects of oral gavage (0.2 mg/g body weight) of elaidic acid (C18:1-9 t, EA) and linoelaidic acid (C18:2-9 t,12 t, LEA) on lipid metabolism, inflammation and gut homeostasis of mice. Results showed that both EA and LEA gavage significantly increased LDL-c, TC and oxidative stress levels in the liver and serum and may stimulate liver inflammation via NF-κB and MAPK signaling pathway. Compared with EA, LEA gavage significantly promoted TAG accumulation and inflammatory signaling. Serum lipidomics revealed that LEA intake significantly increased the concentration of ∼50 TAGs, while EA gavage primarily caused significant decreases in several SMs. 16S rRNA demonstrated that LEA ingestion markedly changed fecal microbiota by enriching Lactobacillus (phylum Firmicutes), however, EA treatment did not affect it. Overall, LEA gavage has more severe consequences on TAG accumulation, inflammation and microbial structure than EA, highlighting that the number of trans double bonds affects these processes.

Designing optimal experiments in metabolomics

BACKGROUND

Metabolomics data is often complex due to the high number of metabolites, chemical diversity, and dependence on sample preparation. This makes it challenging to detect significant differences between factor levels and to obtain accurate and reliable data. To address these challenges, the use of Design of Experiments (DoE) techniques in the setup of metabolomic experiments is crucial. DoE techniques can be used to optimize the experimental design space, ensuring that the maximum amount of information is obtained from a limited sample space.

AIM OF REVIEW

This review aims at providing a baseline workflow for applying DoE when generating metabolomics data.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review provides insights into the theory of DoE. The review showcases the theory being put into practice by highlighting different examples DoE being applied in metabolomics throughout the literature, considering both targeted and untargeted metabolomic studies in which the data was acquired using both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry techniques. In addition, the review presents DoE concepts not currently being applied in metabolomics, highlighting these as potential future prospects.

A ternary correlation multi-symptom network strategy based on in vivo chemical profile identification and metabolomics to explore the molecular basis of Ephedra herb against viral pneumonia

Ephedra herb (EH), an important medicine prescribed in herbal formulas by Traditional Chinese Medicine practitioners, has been widely used in the treatment of viral pneumonia in China. However, the molecular basis of EH in viral pneumonia remains unclear. In this study, a ternary correlation multi-symptom network strategy was established based on in vivo chemical profile identification and metabolomics to explore the molecular basis of EH against viral pneumonia. Results showed that 143 compounds of EH and 70 prototype components were identified in vivo. EH could reduce alveolar-capillary barrier disruption in rats with viral pneumonia and significantly downregulate the expression of inflammatory factors and bronchoalveolar lavage fluid. Plasma metabolomics revealed that EH may be involved in the regulation of arachidonic acid, tryptophan, tyrosine, nicotinate, and nicotinamide metabolism. The multi-symptom network showed that 12 compounds have an integral function in the treatment of viral pneumonia by intervening in many pathways related to viruses, immunity and inflammation, and lung injury. Further verification demonstrated that sinapic acid and frambinone can regulate the expression of related genes. It has been shown to be a promising representative of the pharmacological constituents of ephedra.

Identification of Key Factors in Cartilage Tissue During the Progression of Osteoarthritis Using a Non-targeted Metabolomics Strategy

This research was to reveal the key factors in the progression of osteoarthritis (OA) using non-targeted metabolomics and to find targeted therapies for patients with OA. Twenty-two patients with knee OA scheduled for total knee arthroplasty were divided into two groups: Kellgren-Lawrence (KL) grade 3 (n = 16) and grade 4 (n = 6), according to plain X-rays of the knee. After the operation, the cartilages of femur samples were analyzed using non-targeted metabolomics. When compared with grade 3 patients, the levels of choline, 2-propylpiperidine, rhamnose, and monomethyl glutaric acid were higher; while 1-methylhistamine, sphingomyelin (SM) (d18:1/14:0), zeranol, 3- (4-hydroxyphenyl)-1-propanol, 5-aminopentanamide, dihydrouracil, 2-hydroxypyridine, and 3-amino-2-piperidone were lower in grade 4 patients. Furthermore, some metabolic pathways were found to be significantly different in two groups such as the pantothenate and coenzyme A (CoA) biosynthesis pathway, the glycerophospholipid metabolism pathway, histidine metabolism pathway, lysine degradation pathway, glycine, serine and threonine metabolism pathway, fructose and mannose metabolism pathway, the pyrimidine metabolism pathway, and beta-alanine metabolism pathway. This work used non-targeted metabolomics and screened out differential metabolites and metabolic pathways, providing a reliable theoretical basis for further study of specific markers and their specific pathways in the progression of OA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00123-z.

Lipid and Transcriptional Regulation in a Parkinson's Disease Mouse Model by Intranasal Vesicular and Hexosomal Plasmalogen-Based Nanomedicines

Plasmalogens (vinyl-ether phospholipids) are an emergent class of lipid drugs against various diseases involving neuro-inflammation, oxidative stress, mitochondrial dysfunction, and altered lipid metabolism. They can activate neurotrophic and neuroprotective signaling pathways but low bioavailabilities limit their efficiency in curing neurodegeneration. Here, liquid crystalline lipid nanoparticles (LNPs) are created for the protection and non-invasive intranasal delivery of purified scallop-derived plasmalogens. The in vivo results with a transgenic mouse Parkinson's disease (PD) model (characterized by motor impairments and α-synuclein deposition) demonstrate the crucial importance of LNP composition, which determines the self-assembled nanostructure type. Vesicle and hexosome nanostructures (characterized by small-angle X-ray scattering) display different efficacy of the nanomedicine-mediated recovery of motor function, lipid balance, and transcriptional regulation (e.g., reduced neuro-inflammation and PD pathogenic gene expression). Intranasal vesicular and hexosomal plasmalogen-based LNP treatment leads to improvement of the behavioral PD symptoms and downregulation of the Il6, Il33, and Tnfa genes. Moreover, RNA-sequencing and lipidomic analyses establish a dramatic effect of hexosomal nanomedicines on PD amelioration, lipid metabolism, and the type and number of responsive transcripts that may be implicated in neuroregeneration.

Increased expression of CD38 on endothelial cells in SARS-CoV-2 infection in cynomolgus macaques

SARS-CoV-2 infection causes activation of endothelial cells (ECs), leading to dysmorphology and dysfunction. To study the pathogenesis of endotheliopathy, the activation of ECs in lungs of cynomolgus macaques after SARS-CoV-2 infection and changes in nicotinamide adenine dinucleotide (NAD) metabolism in ECs were investigated, with a focus on the CD38 molecule, which degrades NAD in inflammatory responses after SARS-CoV-2 infection. Activation of ECs was seen from day 3 after SARS-CoV-2 infection in macaques, with increases of intravascular fibrin and NAD metabolism-associated enzymes including CD38. In vitro, upregulation of CD38 mRNA in human ECs was detected after interleukin 6 (IL-6) trans-signaling induction, which was increased in the infection. In the presence of IL-6 trans-signaling stimulation, however, CD38 mRNA silencing induced significant IL-6 mRNA upregulation in ECs and promoted EC apoptosis after stimulation. These results suggest that upregulation of CD38 in patients with COVID-19 has a protective role against IL-6 trans-signaling stimulation induced by SARS-CoV-2 infection.

SCARLET (Supplemental Citicoline Administration to Reduce Lung injury Efficacy Trial): study protocol for a single-site, double-blinded, placebo-controlled, and randomized Phase 1/2 trial of i.v. citicoline (CDP-choline) in hospitalized SARS CoV-2-infected patients with hypoxemic acute respiratory failure

BACKGROUND

The SARS CoV-2 pandemic has resulted in more than 1.1 million deaths in the USA alone. Therapeutic options for critically ill patients with COVID-19 are limited. Prior studies showed that post-infection treatment of influenza A virus-infected mice with the liponucleotide CDP-choline, which is an essential precursor for de novo phosphatidylcholine synthesis, improved gas exchange and reduced pulmonary inflammation without altering viral replication. In unpublished studies, we found that treatment of SARS CoV-2-infected K18-hACE2-transgenic mice with CDP-choline prevented development of hypoxemia. We hypothesize that administration of citicoline (the pharmaceutical form of CDP-choline) will be safe in hospitalized SARS CoV-2-infected patients with hypoxemic acute respiratory failure (HARF) and that we will obtain preliminary evidence of clinical benefit to support a larger Phase 3 trial using one or more citicoline doses.

METHODS

We will conduct a single-site, double-blinded, placebo-controlled, and randomized Phase 1/2 dose-ranging and safety study of Somazina® citicoline solution for injection in consented adults of any sex, gender, age, or ethnicity hospitalized for SARS CoV-2-associated HARF. The trial is named "SCARLET" (Supplemental Citicoline Administration to Reduce Lung injury Efficacy Trial). We hypothesize that SCARLET will show that i.v. citicoline is safe at one or more of three doses (0.5, 2.5, or 5 mg/kg, every 12 h for 5 days) in hospitalized SARS CoV-2-infected patients with HARF (20 per dose) and provide preliminary evidence that i.v. citicoline improves pulmonary outcomes in this population. The primary efficacy outcome will be the SpO2:FiO2 ratio on study day 3. Exploratory outcomes include Sequential Organ Failure Assessment (SOFA) scores, dead space ventilation index, and lung compliance. Citicoline effects on a panel of COVID-relevant lung and blood biomarkers will also be determined.

DISCUSSION

Citicoline has many characteristics that would be advantageous to any candidate COVID-19 therapeutic, including safety, low-cost, favorable chemical characteristics, and potentially pathogen-agnostic efficacy. Successful demonstration that citicoline is beneficial in severely ill patients with SARS CoV-2-induced HARF could transform management of severely ill COVID patients.

TRIAL REGISTRATION

The trial was registered at www.

CLINICALTRIALS

gov on 5/31/2023 (NCT05881135).

TRIAL STATUS

Currently enrolling.

Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019

Objective

To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on the progression and severity prediction of COVID-19.

Methods

This case-control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 patients aged ≥18 years old and diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids were detected. The discrimination ability was calculated with the area under the curve (AUC). A random forest (RF) model was conducted to determine the significance of different lipids.

Results

Totally, 44 COVID-19 patients were enrolled with 16 mild and 28 severe patients. The top 5 super classes were triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) and free fatty acids (FFA, 3.6%) among the 778 detected lipids from the serum of COVID-19 patients. Certain lipids, especially lysophosphatidylcholines (LPCs), turned to have significant correlations with certain immune/cytokine indexes. Reduced level of LPC 20:0 was observed in severe patients particularly in acute stage. The AUC of LPC 20:0 reached 0.940 in discriminating mild and severe patients and 0.807 in discriminating acute and recovery stages in the severe patients. The results of RF models also suggested the significance of LPCs in predicting the severity and progression of COVID-19.

Conclusion

Lipids probably have the potential to differentiate and forecast the severity, progression, and clinical outcomes of COVID-19 patients, with implications for immune/inflammatory responses. LPC 20:0 might be a potential target in predicting the progression and outcome and the treatment of COVID-19.

Oral tongue squamous cell carcinoma diagnosis from tissue metabolic profiling

OBJECTIVE

Disease metabolomes have been studied for identifying diagnostic and predictive biomarkers of pathology. Oral tongue squamous cell carcinoma (OTSCC) is one of the most prevalent subtypes of head and neck squamous cell carcinoma, yet the profile and diagnostic value of its tissue metabolite are unclear.

SUBJECTS AND METHODS

Tumor tissue samples and matched normal mucosal tissue samples were collected from 40 OTSCC patients. Untargeted metabolic analysis by liquid chromatography-mass spectrometry/mass spectrometry, in positive and negative ion modes, was used to identify dysregulated metabolites in OTSCC. Further, utilizing LASSO regression and receiver operating characteristic analyses, biomarker metabolites were selected and validated, and a diagnostic model was established.

RESULTS

One hundred and ninety metabolites were detected. The OTSCC had a total of 89 dysregulated metabolites, of which 73 were elevated. A diagnostic panel of nine metabolites was subsequently created that could accurately identify OTSCC with 100% sensitivity of 100%, 100% specificity and an AUC of 1.00.

CONCLUSIONS

This study identified distinct metabolic characteristics of OTSCC and established a diagnostic model. Our research also contributes to the investigation of the pathogenesis of OTSCC.

ALISTER - Application for lipid stability evaluation and research

BACKGROUND AND AIMS

In lipidomic and metabolomic studies, pre-analytical pitfalls enhance the risk of misusing resources such as time and money, as samples that are analyzed may not yield accurate or reliable data due to poor sample handling. Guidance and pre-analytic know-how are necessary for translation of omics technologies into routine clinical testing. The present work aims to enable decision making regarding sample stability in every phase of lipidomics- and metabolomics-centered studies.

MATERIALS AND METHODS

Data of multiple pre-analytic studies were aggregated into a database. Flexible approaches for evaluating these data were implemented in an RShiny-based web-application, tailored towards broad applicability in clinical and bioanalytic research.

RESULTS

Our "Application for lipid stability evaluation & research" - ALISTER facilitates decision making on blood sample stability during lipidomic and metabolomic studies, such as biomarker research, analysis of biobank samples and clinical testing. The interactive tool gives sampling recommendations when planning sample collection or aids in the assessment of sample quality of experiments retrospectively.

CONCLUSION

ALISTER is available for use under https://itmp.shinyapps.io/alister/. The application enables and simplifies data-driven decision making concerning pre-analytic blood sample handling and fits the needs of clinical investigations from multiple perspectives.

BDE-99 stimulates generation of aberrant brown/beige adipocytes

Adipose tissue compromises one of the principal depots where brominated flame retardants (BFR) accumulate in vivo, yet whether BFR disturb thermogenic brown/beige adipocytes is still not referred to date. Herein, effects of BDE-99, a major congener of polybrominated diphenyl ethers (PBDEs) detected in humans, on brown/beige adipocytes were explored for the first time, aiming to provide new knowledge evaluating the obesogenic and metabolic disrupting effects of BFR. Our results firstly demonstrated that exposure to BDE-99 during the lineage commitment period significantly promoted C3H10T1/2 MSCs differentiating into brown/beige adipocytes, evidenced by the increase of brown/beige adipocyte marker UCP1, Cidea as well as mitochondrial membrane potential and basal respiration rate, which was similar to pharmacological PPARγ agonist rosiglitazone. Unexpectedly, the mitochondrial maximal respiration rate of BDE-99 stimulated brown/beige adipocytes was not synchronously enhanced and resulted in a significant reduction of mitochondrial spare respiration capacity (SRC) compared to control or rosiglitazone stimulated adipocytes, indicating a deficient energy-dissipating capacity of BDE-99 stimulated thermogenic adipocytes. Consistently with compromised mitochondrial SRC, lipidomic analysis further revealed that the lipids profile of mitochondria derived from BDE-99 stimulated brown/beige adipocytes were quite different from control or rosiglitazone stimulated cells. In detail, BDE-99 group contains more free fatty acid (FFA) and lyso-PE in mitochondria. In addition to energy metabolism, our results also demonstrated that BDE-99 stimulated brown/beige adipocytes were deficient in endocrine, which secreted more adverse adipokine named resistin, coinciding with comparable beneficial adipokine adiponectin compared with that of rosiglitazone. Taken together, our results showed for the first time that BDE-99 stimulated brown/beige adipocytes were aberrant in energy metabolism and endocrine, which strongly suggests that BDE-99 accumulated in human adipose tissue could interfere with brown/beige adipocytes to contribute to the occurrence of obesity and relevant metabolic disorders.

Challenges in the Metabolomics-Based Biomarker Validation Pipeline

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.

Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957-0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610-0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901-0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Predictive Value of Lysophosphatidylcholine for Determining the Disease Severity and Prognosis of Elderly Patients with Community-Acquired Pneumonia

Purpose

To investigate the clinical value of serum lysophosphatidylcholine (LPC) as a predictive biomarker for determining disease severity and mortality risk in hospitalized elderly patients with community-acquired pneumonia (CAP).

Methods

This prospective, single-center study enrolled 208 elderly patients, including 67 patients with severe CAP (SCAP) and 141 with non-SCAP between November 1st, 2020, and November 30th, 2021 at the Qingdao Municipal Hospital, Shandong Province, China. The demographic and clinical parameters were recorded for all the included patients. Serum LPC levels were measured on day 1 and 6 after admission using ELISA. Propensity score matching (PSM) was used to balance the baseline variables between SCAP and non-SCAP patient groups. Receiver operative characteristic (ROC) curve analysis was used to compare the predictive performances of LPC and other clinical parameters in discriminating between SCAP and non-SCAP patients and determining the 30-day mortality risk of the hospitalized CAP patients. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with SCAP. Cox proportional hazard regression analysis was used to determine if serum LPC was an independent risk factor for the 30-day mortality of CAP patients.

Results

The serum LPC levels at admission were significantly higher in the non-SCAP patients than in the SCAP patients (P = 0.011). Serum LPC level <24.36 ng/mL, and PSI score were independent risk factors for the 30-day mortality in the elderly patients with CAP. The risk of 30-day mortality in the elderly CAP patients with low serum LPC levels (< 24.36ng/mL) was >5-fold higher than in the patients with high serum LPC levels (≥ 24.36ng/mL).

Conclusion

Low serum LPC levels were associated with significantly higher disease severity and 30-day mortality in the elderly patients with CAP. Therefore, serum LPC is a promising predictive biomarker for the early identification of elderly CAP patients with poor prognosis.

Extracellular Vesicles: The Invisible Heroes and Villains of COVID-19 Central Neuropathology

Acknowledging the neurological symptoms of COVID-19 and the long-lasting neurological damage even after the epidemic ends are common, necessitating ongoing vigilance. Initial investigations suggest that extracellular vesicles (EVs), which assist in the evasion of the host's immune response and achieve immune evasion in SARS-CoV-2 systemic spreading, contribute to the virus's attack on the central nervous system (CNS). The pro-inflammatory, pro-coagulant, and immunomodulatory properties of EVs contents may directly drive neuroinflammation and cerebral thrombosis in COVID-19. Additionally, EVs have attracted attention as potential candidates for targeted therapy in COVID-19 due to their innate homing properties, low immunogenicity, and ability to cross the blood-brain barrier (BBB) freely. Mesenchymal stromal/stem cell (MSCs) secreted EVs are widely applied and evaluated in patients with COVID-19 for their therapeutic effect, considering the limited antiviral treatment. This review summarizes the involvement of EVs in COVID-19 neuropathology as carriers of SARS-CoV-2 or other pathogenic contents, as predictors of COVID-19 neuropathology by transporting brain-derived substances, and as therapeutic agents by delivering biotherapeutic substances or drugs. Understanding the diverse roles of EVs in the neuropathological aspects of COVID-19 provides a comprehensive framework for developing, treating, and preventing central neuropathology and the severe consequences associated with the disease.

Emerging roles and therapeutic potentials of sphingolipids in pathophysiology: emphasis on fatty acyl heterogeneity

Sphingolipids not only exert structural roles in cellular membranes, but also act as signaling molecules in various physiological and pathological processes. A myriad of studies have shown that abnormal levels of sphingolipids and their metabolic enzymes are associated with a variety of human diseases. Moreover, blood sphingolipids can also be used as biomarkers for disease diagnosis. This review summarizes the biosynthesis, metabolism, and pathological roles of sphingolipids, with emphasis on the biosynthesis of ceramide, the precursor for the biosynthesis of complex sphingolipids with different fatty acyl chains. The possibility of using sphingolipids for disease prediction, diagnosis, and treatment is also discussed. Targeting endogenous ceramides and complex sphingolipids along with their specific fatty acyl chain to promote future drug development will also be discussed.

Elevated expression of HIGD1A drives hepatocellular carcinoma progression by regulating polyamine metabolism through c-Myc-ODC1 nexus

BACKGROUND

Hypoxia contributes to cancer progression through various molecular mechanisms and hepatocellular carcinoma (HCC) is one of the most hypoxic malignancies. Hypoxia-inducible gene domain protein-1a (HIGD1A) is typically induced via epigenetic regulation and promotes tumor cell survival during hypoxia. However, the role of HIGD1A in HCC remains unknown.

METHODS

HIGD1A expression was determined in 24 pairs of human HCC samples and para-tumorous tissues. Loss-of-function experiments were conducted both in vivo and in vitro to explore the role of HIGD1A in HCC proliferation and metastasis.

RESULTS

Increased HIGD1A expression was found in HCC tissues and cell lines, which was induced by hypoxia or low-glucose condition. Moreover, HIGD1A knockdown in HCC cells arrested the cell cycle at the G2/M phase and promoted hypoxia-induced cell apoptosis, resulting in great inhibition of cell proliferation, migration, and invasion, as well as tumor xenograft formation. Interestingly, these anti-tumor effects were not observed in normal hepatocyte cell line L02. Further, HIGD1A knockdown suppressed the expression of ornithine decarboxylase 1 (ODC1), a rate-limiting enzyme of polyamine metabolism under c-Myc regulation. HIGD1A was found to bind with the c-Myc promoter region, and its knockdown decreased the levels of polyamine metabolites. Consistently, the inhibitory effect on HCC phenotype by HIGD1A silencing could be reversed by overexpression of c-Myc or supplementation of polyamines.

CONCLUSIONS

Our results demonstrated that HIGD1A activated c-Myc-ODC1 nexus to regulate polyamine synthesis and to promote HCC survival and malignant phenotype, implying that HIGD1A might represent a novel therapeutic target for HCC.

High-fat and high-sucrose diet impairs female reproduction by altering ovarian transcriptomic and metabolic signatures

BACKGROUND

Excessive energy intake in modern society has led to an epidemic surge in metabolic diseases, such as obesity and type 2 diabetes, posing profound threats to women's reproductive health. However, the precise impact and underlying pathogenesis of energy excess on female reproduction remain unclear.

METHODS

We established an obese and hyperglycemic female mouse model induced by a high-fat and high-sucrose (HFHS) diet, then reproductive phenotypes of these mice were evaluated by examing sexual hormones, estrous cycles, and ovarian morphologies. Transcriptomic and precise metabolomic analyses of the ovaries were performed to compare the molecular and metabolic changes in HFHS mice. Finally, orthogonal partial least squares discriminant analysis was performed to compare the similarities of traits between HFHS mice and women with polycystic ovary syndrome (PCOS).

RESULTS

The HFHS mice displayed marked reproductive dysfunctions, including elevated serum testosterone and luteinizing hormone levels, irregular estrous cycles, and impaired folliculogenesis, mimicking the clinical manifestations of women with PCOS. Precise metabolomic overview suggested that HFHS diet disrupted amino acid metabolism in the ovaries of female mice. Additionally, transcriptional profiling revealed pronounced disturbances in ovarian steroid hormone biosynthesis and glucolipid metabolism in HFHS mice. Further multi-omics analyses unveiled prominent aberration in ovarian arginine biosynthesis pathway. Notably, comparisons between HFHS mice and a cohort of PCOS patients identified analogous reproductive and metabolic signatures.

CONCLUSIONS

Our results provide direct in vivo evidence for the detrimental effects of overnutrition on female reproduction and offer insights into the metabolic underpinnings of PCOS.

Low-input lipidomics reveals lipid metabolism remodelling during early mammalian embryo development

Lipids are indispensable for energy storage, membrane structure and cell signalling. However, dynamic changes in various categories of endogenous lipids in mammalian early embryonic development have not been systematically characterized. Here we comprehensively investigated the dynamic lipid landscape during mouse and human early embryo development. Lipid signatures of different developmental stages are distinct, particularly for the phospholipid classes. We highlight that the high degree of phospholipid unsaturation is a conserved feature as embryos develop to the blastocyst stage. Moreover, we show that lipid desaturases such as SCD1 are required for in vitro blastocyst development and blastocyst implantation. One of the mechanisms is through the regulation of unsaturated fatty-acid-mediated fluidity of the plasma membrane and apical proteins and the establishment of apical-basal polarity during development of the eight-cell embryo to the blastocyst. Overall, our study provides an invaluable resource about the remodelling of the endogenous lipidome in mammalian preimplantation embryo development and mechanistic insights into the regulation of embryogenesis and implantation by lipid unsaturation.

Comparing plasma and skin imprint metabolic profiles in COVID-19 diagnosis and severity assessment

As SARS-CoV-2 continues to produce new variants, the demand for diagnostics and a better understanding of COVID-19 remain key topics in healthcare. Skin manifestations have been widely reported in cases of COVID-19, but the mechanisms and markers of these symptoms are poorly described. In this cross-sectional study, 101 patients (64 COVID-19 positive patients and 37 controls) were enrolled between April and June 2020, during the first wave of COVID-19, in São Paulo, Brazil. Enrolled patients had skin imprints sampled non-invasively using silica plates; plasma samples were also collected. Samples were used for untargeted lipidomics/metabolomics through high-resolution mass spectrometry. We identified 558 molecular ions, with lipids comprising most of them. We found 245 plasma ions that were significant for COVID-19 diagnosis, compared to 61 from the skin imprints. Plasma samples outperformed skin imprints in distinguishing patients with COVID-19 from controls, with F1-scores of 91.9% and 84.3%, respectively. Skin imprints were excellent for assessing disease severity, exhibiting an F1-score of 93.5% when discriminating between patient hospitalization and home care statuses. Specifically, oleamide and linoleamide were the most discriminative biomarkers for identifying hospitalized patients through skin imprinting, and palmitic amides and N-acylethanolamine 18:0 were also identified as significant biomarkers. These observations underscore the importance of primary fatty acid amides and N-acylethanolamines in immunomodulatory processes and metabolic disorders. These findings confirm the potential utility of skin imprinting as a valuable non-invasive sampling method for COVID-19 screening; a method that may also be applied in the evaluation of other medical conditions. KEY MESSAGES: Skin imprints complement plasma in disease metabolomics. The annotated markers have a role in immunomodulation and metabolic diseases. Skin imprints outperformed plasma samples at assessing disease severity. Skin imprints have potential as non-invasive sampling strategy for COVID-19.