Benchtop NMR metabolomics: an exploration of biofluids and diseases

Megram, OJ, 2025. Benchtop NMR metabolomics: an exploration of biofluids and diseases. PhD, Nottingham Trent University.

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Abstract

With ageing populations and increasing healthcare demands, there has been a growing need for cost-efficient diagnostic tools that enable early disease detection and intervention. Metabolomics has demonstrated significant potential in identifying disease-associated biomarkers, providing a valuable approach for early diagnosis and monitoring. Nuclear magnetic resonance (NMR) spectroscopy has been widely used in metabolomics; however, high-field (HF) NMR spectrometers are expensive, requiring specialised infrastructure, limiting accessibility. Recent advances in benchtop NMR (bNMR) spectroscopy have offered a more affordable technique, though its diagnostic utility across a broader range of diseases remains underexplored.

This research investigated bNMR’s potential for disease detection through metabolomic profiling across multiple biofluids and pathological conditions. Using optimised pulse sequences and minimal sample preparation, bNMR’s ability to differentiate between health states was evaluated. The study examined its performance in distinguishing metabolic signatures in diabetes, asthma and epilepsy using urine, blood plasma, and cerebrospinal fluid (CSF), respectively.

The findings demonstrated that bNMR successfully differentiated diabetic patients from healthy controls in urine-based analysis. However, it could not distinguish pre-diabetic individuals, a distinction HF-NMR achieved, suggesting a limitation in bNMR’s sensitivity. Similarly, in blood plasma, bNMR identified metabolic differences between individuals with well-managed asthma, though differentiation between a more severe asthma type and controls remained challenging. In CSF, bNMR could not effectively distinguish between idiopathic epilepsy and control samples, highlighting potential limitations in detecting subtle metabolic changes in this biofluid. Metabolites were detected using bNMR, with only minor differences compared to HF-NMR. These findings suggested that bNMR could help guide targeted disease analysis.

This research highlighted bNMR’s potential as a cost-effective tool while emphasising the need for further refinement in sensitivity and validation across diverse disease cohorts. While applications of bNMR are promising, future research should explore its applicability in detecting comorbid populations and assess its clinical viability for early disease detection.

Item Type:	Thesis
Creators:	Megram, O.J.
Contributors:	Name Role NTU ID ORCID Hunter, E. Thesis supervisor CHP3BUDENE UNSPECIFIED Hunt, J. Thesis supervisor CST3HUNTJA https://orcid.org/0000-0002-5168-4778
Date:	July 2025
Rights:	The copyright and intellectual property of this work is held by the author. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any re-use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed to the author.
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Borcherds
Date Added:	09 Apr 2026 15:25
Last Modified:	09 Apr 2026 15:25
URI:	https://irep.ntu.ac.uk/id/eprint/55527

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