Urinary 1H-NMR Metabolic Signature in Subjects Undergoing Colonoscopy for Colon Cancer Diagnosis

NMR metabolomic and microarray-based transcriptomic data integration identifies unique molecular signatures of hypersensitivity pneumonitis

Hypersensitivity pneumonitis (HP) is an immune-mediated granulomatous interstitial lung disease (ILD) that results from repeated inhalation of certain antigens. Despite major advances in research, pathophysiology of the disease remains poorly understood. The present study combines metabolomic and transcriptomic data to determine alterations in HP subjects as compared with healthy controls. Metabolic signatures were identified in serum, exhaled breath condensate (EBC) and bronchoalveolar lavage fluid (BALF) of HP patients using proton nuclear magnetic resonance (NMR) metabolomics. The expression of three metabolites, i.e., lactate, pyruvate, and proline, was found to be significantly altered in all three biofluids. The potential of differential diagnosis based on these three metabolites was investigated by including a group of patients with sarcoidosis, which is another type of granulomatous ILD. In addition, differentially expressed transcriptomic fingerprints in blood samples were identified by analyzing a Gene Expression Omnibus (GEO) database. The transcriptomics analysis of these microarray-based data revealed 59 genes to be significantly dysregulated in patients with HP. Over representation analysis of the metabolites and genes of interest was performed using IMPaLA (Integrated Molecular Pathway Level Analysis) version 12. Integrated analysis of serum metabolite signatures and blood gene expression suggests dysregulation of PI3K-AKT signaling and TCA cycle pathways in these patients. This preliminary study is a step towards better understanding of the pathogenesis of HP by identification of differentially expressed metabolites and transcriptomic fingerprints. These molecular signatures may be explored as diagnostic markers for differentiating HP from other lung diseases.

First trimester metabolomics 1H-NMR study of the urinary profile predicts gestational diabetes mellitus development in obese women

OBJECTIVE

Obesity is one of the main risk factors for the development gestational diabetes mellitus (GDM). Thus, we aim to identify changes in the urinary metabolomics profile of obese women at first trimester of pregnancy in order to predict later GDM diagnosis.

RESEARCH DESIGN AND METHODS

In this nested case-control study, urine samples collected in the first trimester of pregnancy obtained from obese women who developed GDM (n = 29) and obese women who did not develop diabetes (n = 25 NO GDM) were analyzed with Nuclear Magnetic Resonance spectroscopy combined with Multivariate Statistical Analysis. GDM diagnosis was obtained with one-step oral glucose load.

RESULTS

OPLS-DA significantly separated the GDM women from NO GDM women. Specifically, GDM women were characterized by a higher level of tryptophan, trigonelline, hippurate, and threonine, and lower levels of 1-methylnicotinamide, 3-hydroxykynurenine, glycocholate, isoleucine, kynurenine, and valine compared to NO GDM women.

CONCLUSION

In a prevalently Caucasian population, the changes of some metabolites such as tryptophan, trigonelline, and branch-chained amino acids in the urinary profile of obese women in the first trimester are able to make unequivocal prediction of those which later test positive for GDM. This approach could be useful to diagnose much earlier obese women with GDM allowing lifestyle counselling and other interventions.

Early Urinary Metabolomics in Patent Ductus Arteriosus Anticipates the Fate: Preliminary Data

Introduction: In premature neonates, the persistence of hemodynamically significant ductus arteriosus (hsPDA) can be associated with short- and long-term consequences, impairing their outcome. The correct strategy of management for such condition is under debate, especially regarding contraindications and/or side effects. In recent years, metabolomics was applied to several perinatal, pediatric, and adult conditions to investigate potential biomarkers of disease, which have become useful for early diagnosis and/or therapeutic management. Aim of the Study: The main purpose of our exploratory study was to asses, through ¹H-NMR metabolomics analysis of urinary samples at birth, possible metabolic pathways differentiating, with a significant predictive power, those preterm neonates who will subsequently develop hsPDA and neonates of comparable gestational age (GA) who will undergo spontaneous ductal closure or the persistence of an irrelevant PDA (no-hsPDA). Moreover, we investigated potential prenatal or perinatal clinical factors potentially influencing the development of hsPDA. Materials and Methods: We enrolled n = 35 preterm neonates with GA between 24 and 32 weeks; urinary samples were collected within the first 12 h of life. Patients were closely monitored regarding intensive care, respiratory support, fluid balance and administered drugs; an echocardiogram was performed at 48-72 h. Results: Our results reported a significant correlation between lower GA at birth and the development of hsPDA. Moreover, neonates with GA ≤ 30w developing hsPDA were characterized by lower Apgar scores at 1' and 5', higher rates of perinatal asphyxia, higher need of delivery room resuscitation and subsequent surfactant administration. Interestingly, metabolomics analysis at birth detected a clear separation between the ¹H-NMR urinary spectra of subjects GA ≤ 30w not developing hsPDA (n = 19) and those of subjects born at GA ≤ 30w in which hsPDA was confirmed at 48-72 h of life (n = 5). Conclusions: This is the first study applying metabolomics to investigate the PDA condition. Although preliminary and conducted on a limited sample, our results reveal that metabolomics could be a promising tool in the early identification of hsPDA, potentially superior to the clinical or laboratory predictive tools explored to date and even to the clinical observations and correlations in our sample, through the detection of specific urinary metabolites.