Hexosylceramides and Glycerophosphatidylcholine GPC(36:1) Increase in Multi-Organ Dysfunction Syndrome Patients with Pediatric Intensive Care Unit Admission over 8-Day Hospitalization

Leimanis-Laurens, Mara L.; Wolfrum, Emily; Ferguson, Karen; Grunwell, Jocelyn R.; Sanfilippo, Dominic; Prokop, Jeremy W.; Lydic, Todd A.; Rajasekaran, Surender

doi:10.3390/jpm11050339

Cited by 2 publications

(1 citation statement)

References 56 publications

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“…It has also been demonstrated that ceramides could predict death in patients with stable coronary artery disease and acute coronary syndromes, where it was postulated that the ceramides are associated with lipoprotein aggregation and uptake, superoxide anion production, apoptosis, and inflammation [80]. More specifically, hexosylceramides have been found in higher concentrations in patients with multiorgan dysfunction syndrome than sedated controls in an intensive care unit [81] and have also been linked to viral load in hepatitis C infection [82].…”

Section: Mortality Prediction In Sars-cov-2 Positive Patientsmentioning

confidence: 99%

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

Lodge

Lawler

Gray

et al. 2023

IJMS

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

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Section: Mortality Prediction In Sars-cov-2 Positive Patientsmentioning

confidence: 99%

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

Lodge

Lawler

Gray

et al. 2023

IJMS

View full text Add to dashboard Cite

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Introduction to Personalized Medicine in Pediatrics

Bupp¹,

English²,

Rajasekaran³

et al. 2022

Pediatr Ann

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Exciting new developments in biomedical and computational sciences provide an extraordinary and unparalleled opportunity to compile, connect, and analyze multiple types of “big data,” driving the development of personalized medicine. These insights must begin in early life (ie, pregnancy, neonatal, and infancy) and focus on early prevention, diagnosis, and intervention—areas of medicine where pediatricians are poised to lead the way to a personalized medicine future. The rapid growth of genomics (including pharmacogenomics), transcriptomics, and related “omics” has revolutionized the diagnosis of rare monogenic disorders. It is now clarifying the pathogenesis of complex conditions ranging from autism spectrum disorder to asthma. Collaborations between clinicians and basic scientists integrating multiomics approaches in evaluating children with severe illness are transforming the fields of perinatal, neonatal, and pediatric critical care medicine. Improvements in rapid diagnostic and prognostic information suggest that pediatric personalized medicine is under way and has an exciting future. [ Pediatr Ann . 2022;51(10):e381–e386.]

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Hexosylceramides and Glycerophosphatidylcholine GPC(36:1) Increase in Multi-Organ Dysfunction Syndrome Patients with Pediatric Intensive Care Unit Admission over 8-Day Hospitalization

Cited by 2 publications

References 56 publications

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

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

Introduction to Personalized Medicine in Pediatrics

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