An overview of lipidomics utilizing cadaver derived biological samples

A study protocol to characterise pathophysiological and molecular markers of rheumatic heart disease and degenerative aortic stenosis using multiparametric cardiovascular imaging and multiomics techniques

INTRODUCTION

Rheumatic heart disease (RHD), degenerative aortic stenosis (AS), and congenital valve diseases are prevalent in sub-Saharan Africa. Many knowledge gaps remain in understanding disease mechanisms, stratifying phenotypes, and prognostication. Therefore, we aimed to characterise patients through clinical profiling, imaging, histology, and molecular biomarkers to improve our understanding of the pathophysiology, diagnosis, and prognosis of RHD and AS.

METHODS

In this cross-sectional, case-controlled study, we plan to recruit RHD and AS patients and compare them to matched controls. Living participants will undergo clinical assessment, echocardiography, CMR and blood sampling for circulatory biomarker analyses. Tissue samples will be obtained from patients undergoing valve replacement, while healthy tissues will be obtained from cadavers. Immunohistology, proteomics, metabolomics, and transcriptome analyses will be used to analyse circulatory- and tissue-specific biomarkers. Univariate and multivariate statistical analyses will be used for hypothesis testing and identification of important biomarkers. In summary, this study aims to delineate the pathophysiology of RHD and degenerative AS using multiparametric CMR imaging. In addition to discover novel biomarkers and explore the pathomechanisms associated with RHD and AS through high-throughput profiling of the tissue and blood proteome and metabolome and provide a proof of concept of the suitability of using cadaveric tissues as controls for cardiovascular disease studies.

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

PMI estimation through metabolomics and potassium analysis on animal vitreous humour

INTRODUCTION

The estimation of post-mortem interval (PMI) remains a major challenge in forensic science. Most of the proposed approaches lack the reliability required to meet the rigorous forensic standards.

OBJECTIVES

We applied ¹H NMR metabolomics to estimate PMI on ovine vitreous humour comparing the results with the actual scientific gold standard, namely vitreous potassium concentrations.

METHODS

Vitreous humour samples were collected in a time frame ranging from 6 to 86 h after death. Experiments were performed by using ¹H NMR metabolomics and ion capillary analysis. Data were submitted to multivariate statistical data analysis.

RESULTS

A multivariate calibration model was built to estimate PMI based on 47 vitreous humour samples. The model was validated with an independent test set of 24 samples, obtaining a prediction error on the entire range of 6.9 h for PMI < 24 h, 7.4 h for PMI between 24 and 48 h, and 10.3 h for PMI > 48 h. Time-related modifications of the ¹H NMR vitreous metabolomic profile could predict PMI better than potassium up to 48 h after death, whilst a combination of the two is better than the single approach for higher PMI estimation.

CONCLUSION

The present study, although in a proof-of-concept animal model, shows that vitreous metabolomics can be a powerful tool to predict PMI providing a more accurate estimation compared to the widely studied approach based on vitreous potassium concentrations.

Infant urinary metabolomic profile in a fatal acute methadone intoxication

A case report suspicious for a Sudden Infant Death Syndrome is here described. Pathological findings were consistent with an acute respiratory failure while toxicological analysis revealed an elevated blood methadone concentration. Death was then ascribed to an acute methadone intoxication. In addition to the routinary approach, the urinary sample collected at autopsy was investigated with a ¹H NMR metabolomic approach and the identified metabolomic profile was challenged with the urinary metabolomic profiles previously obtained from 10 newborns who experienced perinatal asphyxia and 16 healthy control newborns. Intriguingly, the urinary profile of the methadone intoxicated infant was very similar to those belonging to the perinatal asphyxia newborns, especially to those belonging to the newborns characterised by the worst outcome. The results offer several hints on a shared metabolic derangement between different mechanisms of asphyxia/hypoxia. To the best of the authors’ knowledge, this is the first report of the use of a metabolomic approach in a pathological case, in which metabolomics offers useful additional information regarding the mechanism and the cause of death.

Analyses of Pseudoexfoliation aqueous humor lipidome

Pseudoexfoliation syndrome (PEX) is a systemic disorder that manifests as fluffy, proteinaceous fibrillar material throughout the body. In the eye such deposits result in glaucoma (PEXG), due to impeding aqueous...