An analysis of urine and serum amino acids in critically ill patients upon admission by means of targeted LC-MS/MS: a preliminary study

Mendelian randomization analysis identifies causal associations between serum lipidomic profile, amino acid biomarkers and sepsis

Background

Sepsis is a life-threatening condition marked by a severe systemic response to infection, leading to widespread inflammation, cellular signaling disruption, and metabolic dysregulation. The role of lipid and amino acid metabolism in sepsis is not fully understood, but aberrations in this pathway could contribute to the disease's pathophysiology.

Methods

To explore the potential of lipid and amino acid compounds as biomarkers for the diagnosis and prognosis of sepsis, a two-sample Mendelian Randomization (MR) study was conducted, examining the relationship between sepsis and 249 serum lipid and amino acid-related markers. Key enzymes involved in synthesis of phosphatidylcholine, including choline/ethanolamine phosphotransferase 1 (CEPT1), choline phosphotransferase 1 (CPT1), and ethanolamine phosphotransferase 1 (EPT1), were also targeted for drug-target Mendelian randomization.

Results

The study found that phosphatidylcholines (OR IVW: 0.88, 95%CI: 0.80-0.96, p = 0.005) and phospholipids in medium HDL (OR IVW: 0.86, 95%CI: 0.77-0.96, p = 0.007) potentially exhibit a protective effect against sepsis nominally. However, the potential drug target of CEPT1, CPT1, and EPT1 was found to be unrelated to septic outcomes.

Conclusion

Our findings suggest that increasing levels of phosphatidylcholines and medium HDL phospholipids may reduce the incidence of sepsis. This highlights the potential of lipid-based biomarkers in the diagnosis and management of sepsis, opening avenues for new therapeutic strategies.

Patient Stratification in Sepsis: Using Metabolomics to Detect Clinical Phenotypes, Sub-Phenotypes and Therapeutic Response

Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of sepsis, outside of antibiotics and supportive measures. Some of the difficulty in identifying novel therapies is the heterogeneity of the condition. Metabolic phenotyping has great potential for gaining understanding of this heterogeneity and how the metabolic fingerprints of patients with sepsis differ based on survival, organ dysfunction, disease severity, type of infection, treatment or causative organism. Moreover, metabolomics offers potential for patient stratification as metabolic profiles obtained from analytical platforms can reflect human individuality and phenotypic variation. This article reviews the most relevant metabolomic studies in sepsis and aims to provide an overview of the metabolic derangements in sepsis and how metabolic phenotyping has been used to identify sub-groups of patients with this condition. Finally, we consider the new avenues that metabolomics could open, exploring novel phenotypes and untangling the heterogeneity of sepsis, by looking at advances made in the field with other -omics technologies.

Longitudinal associations of pre-pregnancy BMI and gestational weight gain with maternal urinary metabolites: an NYU CHES study

Background/Objectives:

Excessive gestational weight gain (GWG) and pre-pregnancy obesity affect a significant portion of the US pregnant population and are linked with negative maternal and child health outcomes. The objective of this study was to explore associations of pre-pregnancy body mass index (pBMI) and GWG with longitudinally measured maternal urinary metabolites throughout pregnancy.

Subjects/Methods:

Among 652 participants in the New York University Children’s Health and Environment Study, a longitudinal pregnancy cohort, targeted metabolomics were measured in serially collected urine samples throughout pregnancy. Metabolites were measured at median 10 (T1), 21 (T2), and 29 (T3) weeks gestation using the Biocrates AbsoluteIDQ® p180 Urine Extension kit. Acylcarnitine, amino acid, biogenic amine, phosphatidylcholine, lysophosphatidylcholine, sphingolipid, and sugar levels were quantified. Pregnant people 18 years or older, without type 1 or 2 diabetes and with singleton live births and valid pBMI and metabolomics data were included. GWG and pBMI were calculated using weight and height data obtained from electronic health records. Linear mixed effects models with interactions with time were fit to determine the gestational age-specific associations of categorical pBMI and continuous interval-specific GWG with urinary metabolites. All analyses were corrected for false discovery rate.

Results:

Participants with obesity had lower long-chain acylcarnitine levels throughout pregnancy and lower phosphatidylcholine and glucogenic amino acids and higher phenylethylamine concentrations in T2 and T3 compared with participants with normal/underweight pBMI. GWG was associated with taurine in T2 and T3 and C5 acylcarnitine species, C5:1, C5-DC, and C5-M-DC, in T2.

Conclusions:

pBMI and GWG were associated with the metabolic environment of pregnant individuals, particularly in relation to mid-pregnancy. These results highlight the importance of both preconception and prenatal maternal health.