Direct Implementation of Intestinal Permeability Test in NMR Metabolomics for Simultaneous Biomarker Discovery-A Feasibility Study in a Preterm Piglet Model

Intestinal metabolomics in premature infants with late-onset sepsis

We aimed to investigate the characteristics of intestinal metabolomics and non-invasive biomarkers for early diagnosis of late-onset sepsis (LOS) by analyzing gut metabolites in preterm infants with LOS. We collected stool samples from septic and healthy preterm infants for analysis by liquid chromatography-mass spectrometry. 123 different metabolites were identified and 13 pathways were mainly involved. Glycine, serine, and threonine metabolism; glyoxylate and dicarboxylic acid metabolism; glutathione metabolism; primary bile acid biosynthesis; steroid synthesis; pentose and glucuronic acid interconversion may be involved in the pathogenesis of LOS in preterm infants. The significant changes of N-Methyldopamine, cellulose, glycine, gamma-Glutamyltryptophan, N-Ribosylnicotinamide and 1alpha, 25-dihydroxycholecalciferol showed specific diagnostic values and as non-invasive biomarkers for LOS.

Targeted and untargeted urinary metabolic profiling of bladder cancer

Bladder cancer (BC) is frequent cancer affecting the urinary tract and is one of the most prevalent malignancies worldwide. No biomarkers that can be used for effective monitoring of therapeutic interventions for this cancer have been identified to date. This study investigated polar metabolite profiles in urine samples from 100 BC patients and 100 normal controls (NCs) using nuclear magnetic resonance (NMR) and two methods of high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS). Five urine metabolites were identified and quantified using NMR spectroscopy to be potential indicators of bladder cancer. Twenty-five LDI-MS-detected compounds, predominantly peptides and lipids, distinguished urine samples from BC and NCs individuals. Level changes of three characteristic urine metabolites enabled BC tumor grades to be distinguished, and ten metabolites were reported to correlate with tumor stages. Receiver-Operating Characteristics analysis showed high predictive power for all three types of metabolomics data, with the area under the curve (AUC) values greater than 0.87. These findings suggest that metabolite markers identified in this study may be useful for the non-invasive detection and monitoring of bladder cancer stages and grades.

NMR-Based Metabolomics to Decipher the Molecular Mechanisms in the Action of Gut-Modulating Foods

Metabolomics deals with uncovering and characterizing metabolites present in a biological system, and is a leading omics discipline as it provides the nearest link to the biological phenotype. Within food and nutrition, metabolomics applied to fecal samples and bio-fluids has become an important tool to obtain insight into how food and food components may exert gut-modulating effects. This review aims to highlight how nuclear magnetic resonance (NMR)-based metabolomics in food and nutrition science may help us get beyond where we are today in understanding foods’ inherent, or added, biofunctionalities in relation to gut health.

Plasma Metabolic and Lipidomic Fingerprinting of Individuals with Increased Intestinal Permeability

The dual-sugar intestinal permeability test is a commonly used test to assess changes in gut barrier function. However, it does not identify functional changes and the exact mechanism of damage caused by the increased intestinal permeability. This study aims to explore the application of untargeted metabolomics and lipidomics to identify markers of increased intestinal permeability. Fifty fasting male participants (18–50 years) attended a single visit to conduct the following procedures: assessment of anthropometric measures, assessment of gastrointestinal symptoms, intestinal permeability test, and assessment of blood samples 90 min post-administration of the intestinal permeability test. Rhamnose and lactulose were analysed using gas chromatography-mass spectrometry (GC-MS). Untargeted polar metabolites and lipidomics were assessed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF MS). There was an elevated lactulose/rhamnose ratio in 27 subjects, indicating increased permeability compared to the remaining 23 control subjects. There were no significant differences between groups in characteristics such as age, body mass index (BMI), weight, height, and waist conference. Fourteen metabolites from the targeted metabolomics data were identified as statistically significant in the plasma samples from intestinal permeability subjects. The untargeted metabolomics and lipidomics analyses yielded fifteen and fifty-one statistically significant features, respectively. Individuals with slightly elevated intestinal permeability had altered energy, nucleotide, and amino acid metabolism, in addition to increased glutamine levels. Whether these biomarkers may be used to predict the early onset of leaky gut warrants further investigation.

Personalized Metabolic Profile by Synergic Use of NMR and HRMS

A new strategy that takes advantage of the synergism between NMR and UHPLC–HRMS yields accurate concentrations of a high number of compounds in biofluids to delineate a personalized metabolic profile (SYNHMET). Metabolite identification and quantification by this method result in a higher accuracy compared to the use of the two techniques separately, even in urine, one of the most challenging biofluids to characterize due to its complexity and variability. We quantified a total of 165 metabolites in the urine of healthy subjects, patients with chronic cystitis, and patients with bladder cancer, with a minimum number of missing values. This result was achieved without the use of analytical standards and calibration curves. A patient’s personalized profile can be mapped out from the final dataset’s concentrations by comparing them with known normal ranges. This detailed picture has potential applications in clinical practice to monitor a patient’s health status and disease progression.

Biomarkers for diagnosis and prediction of therapy responses in allergic diseases and asthma

Modern health care requires a proactive and individualized response to diseases, combining precision diagnosis and personalized treatment. Accordingly, the approach to patients with allergic diseases encompasses novel developments in the area of personalized medicine, disease phenotyping and endotyping, and the development and application of reliable biomarkers. A detailed clinical history and physical examination followed by the detection of IgE immunoreactivity against specific allergens still represents the state of the art. However, nowadays, further emphasis focuses on the optimization of diagnostic and therapeutic standards and a large number of studies have been investigating the biomarkers of allergic diseases, including asthma, atopic dermatitis, allergic rhinitis, food allergy, urticaria and anaphylaxis. Various biomarkers have been developed by omics technologies, some of which lead to a better classification of distinct phenotypes or endotypes. The introduction of biologicals to clinical practice increases the need for biomarkers for patient selection, prediction of outcomes and monitoring, to allow for an adequate choice of the duration of these costly and long‐lasting therapies. Escalating healthcare costs together with questions about the efficacy of the current management of allergic diseases require further development of a biomarker‐driven approach. Here, we review biomarkers in diagnosis and treatment of asthma, atopic dermatitis, allergic rhinitis, viral infections, chronic rhinosinusitis, food allergy, drug hypersensitivity and allergen immunotherapy with a special emphasis on specific IgE, the microbiome and the epithelial barrier. In addition, EAACI guidelines on biologicals are discussed within the perspective of biomarkers.