Investigating metabolomic biomarkers of hypoxic ischaemic encephalopathy

Background An early objective biomarker to predict the severity of hypoxic-ischaemic encephalopathy (HIE) and identify infants suitable for intervention remains elusive. This thesis aims to progress metabolomic markers of HIE through a pipeline of biomarker discovery and validation by employing a novel untargeted mass spectrometry metabolomic method. Methodology Term infants with perinatal asphyxia were recruited, all having umbilical cord blood (UCB) drawn and biobanked within three hours of birth. HIE was defined by Sarnat score at 24hours and continuous multichannel-EEG. Infant neurodevelopment was assessed at 36-42 months using the Bayley Scales of Infant and Toddler Development Ed. III (BSID-III). Untargeted metabolomic analysis of UCB was performed using direct injection FT-ICR mass spectrometry (DI FT-ICR MS). Putative metabolite annotations and lipid classes were assigned and pathway analysis was performed. Results Untargeted metabolomic analysis: Thirty enrolled infants were diagnosed with HIE, including 17 mild, 8 moderate, and 5 severe cases. Pathway analysis revealed that ΔHIE was associated with a 50% and 75% perturbation of tryptophan and pyrimidine metabolism respectively, alongside alterations in amino acid pathways. Significant metabolite alterations were detected from six putatively identified lipid classes including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids and prenol lipids. Outcome prediction: Metabolite model scores significantly correlated with outcome R=0.429 (model A) and R=0.549 (model B) respectively. Model B demonstrates the potential to predict both severe outcome (AUROC of 0.915) and intact survival (AUROC of 0.800). The effect of haemolysis: On average 5% of polar and 1.5% of non-polar features were altered between paired haemolysed and clean samples. However unsupervised multivariate analysis concluded that the preanalytical variability introduced by haemolysis was negligible compared with the inherent biological inter-individual variability. Conclusion This research has employed untargeted metabolomics to identify potential early cord blood biomarkers of HIE and has performed the technical validation of previously proposed markers.

Enhancing non-refractory aerosol apportionment from an urban industrial site through receptor modelling of complete high time-resolution aerosol mass spectra

Receptor modelling was performed on quadrupole unit mass resolution aerosol mass spectrometer (Q-AMS) sub-micron particulate matter (PM) chemical speciation measurements from Windsor, Ontario, an industrial city situated across the Detroit River from Detroit, Michigan. Aerosol and trace gas measurements were collected on board Environment Canada’s CRUISER mobile laboratory. Positive matrix factorization (PMF) was performed on the AMS full particle-phase mass spectrum (PMFFull MS) encompassing both organic and inorganic components. This approach was compared to the more common method of analysing only the organic mass spectra (PMFOrg MS). PMF of the full mass spectrum revealed that variability in the non-refractory sub-micron aerosol concentration and composition was best explained by six factors: an amine-containing factor (Amine); an ammonium sulphate and oxygenated organic aerosol containing factor (Sulphate-OA); an ammonium nitrate and oxygenated organic aerosol containing factor (Nitrate-OA); an ammonium chloride containing factor (Chloride); a hydrocarbon like organic aerosol (HOA) factor; and a moderately oxygenated organic aerosol factor (OOA). PMF of the organic mass spectrum revealed three factors of similar composition to some of those revealed through PMFFull MS: Amine, HOA and OOA. Including both the inorganic and organic mass proved to be a beneficial approach to analysing the unit mass resolution AMS data for several reasons. First, it provided a method for potentially calculating more accurate sub-micron PM mass concentrations, particularly when unusual factors are present, in this case, an Amine factor. As this method does not rely on a priori knowledge of chemical species, it circumvents the need for any adjustments to the traditional AMS species fragmentation patterns to account for atypical species, and can thus lead to more complete factor profiles. It is expected that this method would be even more useful for HR-ToF-AMS data, due to the ability to better understand the chemical nature of atypical factors from high resolution mass spectra. Second, utilizing PMF to extract factors containing inorganic species allowed for the determination of extent of neutralization, which could have implications for aerosol parameterization. Third, subtler differences in organic aerosol components were resolved through the incorporation of inorganic mass into the PMF matrix. The additional temporal features provided by the inorganic aerosol components allowed for the resolution of more types of oxygenated organic aerosol than could be reliably re-solved from PMF of organics alone. Comparison of findings from the PMFFull MS and PMFOrg MS methods showed that for the Windsor airshed, the PMFFull MS method enabled additional conclusions to be drawn in terms of aerosol sources and chemical processes. While performing PMFOrg MS can provide important distinctions between types of organic aerosol, it is shown that including inorganic species in the PMF analysis can permit further apportionment of organics for unit mass resolution AMS mass spectra.