Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.

Background: Non-severe paediatric burns can result in poor long-term health outcomes. This occurs even in cases with good acute burn-related outcomes, including minimal scarring. The mechanisms that underpin the transition from non-severe burn to sustained negative long-term health impacts are currently unknown. However, sustained metabolic and immune changes have been observed in paediatric burn studies, suggesting these changes may be important. The plasma lipidome consists of a rich pool of bioactive metabolites that play critical roles in systemic processes including molecular signalling and inflammation. We hypothesised that changes in the plasma lipidome may reflect underlying changes in health status and be linked to long-term health after burn trauma. Methods: This study analysed the lipidome in children who had previously experienced a non-severe burn, compared to non-injured controls. Thirty-three participants were recruited between the ages of 5 and 8 years who had experienced a non-severe burn between the ages of 1 and 3 years. Plasma samples were also collected from a non-injured, healthy, age and gender matched control group (n = 21). Plasma lipids were measured using reversed-phase liquid chromatographymass spectrometery (LC-MS). Results: In total 838 reproducible lipid species from 19 sub-classes passed quality control procedures and progressed to statistical analysis. Analysis of individual lipid metabolites showed significantly higher concentrations of lysophosphatidylethanolamines and phosphatidylethanolamines, and significantly lower concentrations in myristic, palmitic and palmitoleic acids in the plasma of those who had experienced burn injury compared to controls. Conclusion: Long-term changes in the lipid profile may give insight into the mechanisms underlying poor long-term health subsequent to non-severe burn injury. Further work to investigate the relationship between long-term pathology and lipidomic changes may lead to a better understanding of the causes of secondary morbidity post-burn and to clinical intervention to reduce the long-term health burden of burn trauma.

Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic comorbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on the impact of nonsevere injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of a nonsevere burn injury, longitudinal plasma was collected from adults (n = 35) who presented at hospital with a nonsevere burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from nonburn control participants (n = 14). Samples underwent multiplatform metabolic phenotyping using ¹H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoprotein signatures and 852 lipid species from across 20 subclasses. Multivariate data modeling (orthogonal projections to latent structures-discriminate analysis; OPLS-DA) revealed alterations in lipoprotein and lipid metabolism when comparing the baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value < 1.0e^-4), low density lipoprotein-2 subfractions (variable importance in projection score; VIP > 6.83e^-1) and monoacyglyceride (20:4) (p-value < 1.0e^-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP > 7.75e^-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols, and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of a nonsevere burn injury. The phenotype is indicative of an acute inflammatory profile that continues to be sustained postinjury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have an elevated incidence postburn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalize intervention strategies, and improve acute care, reducing the risk of chronic comorbidity.

Robust tissue pre-treatment and lipid extraction workflows are crucial to metabolic phenotyping studies and accurate interpretation of lipid profiles. Numerous methods for lipid extraction from tissues have been developed, and the choice of technique influences analysis. This study provides a comprehensive evaluation of six liquid-liquid extraction methods (three biphasic and three monophasic) used for lipidomic tissue analysis by liquid chromatography-mass spectrometry. Extraction methods were assessed for their suitability for comprehensive lipid profiling across diverse tissue types: adipose, liver, and heart. These techniques were compared using lyophilised and fresh frozen samples. The study revealed significant differences in the coverage and reliability of lipid species extracted using each technique, dependent on the tissue type. The optimal extraction method for adipose tissue was butanol:methanol (BUME) (3:1) which achieved the highest lipid coverage, yield and reproducibility (886 lipids with a coefficient of variation (CV) < 30 %); methyl tert-butyl ether (MTBE) with ammonium acetate was most effective for liver tissue (707 lipids CV < 30 %) and BUME (1:1) for heart tissue (311 lipids CV < 30 %). These findings showed that the most effective lipid extraction methods are highly tissue-specific, underscoring the critical need for bespoke protocols tailored to each tissue type. The optimised tissue-specific methods were validated using an intervention study in C57BL/6 mice to investigate diet-induced metabolic changes. The results demonstrated distinct discriminating lipid profiles unique to each tissue type, with 374 lipid species from 13 subclasses significantly different between high-fat diet (HFD) and normal diet (ND) in adipose tissue, while 485 lipid species from 17 subclasses were significantly different between HFD and ND in liver tissue. This study presents a new approach to studying lipid profiles derived from diverse tissues that substantially improve comprehensive lipid species' detection sensitivity and reliability. Our systematic evaluation provides evidence that tailored tissue-specific extraction protocols are highly valuable in comprehensive lipidomics studies, offering robust tools for reliably identifying lipid changes and facilitates a deeper understanding of tissue-specific metabolic processes in diverse research and clinical applications.