**Abstract**

Implementations of high-field nuclear magnetic resonance (NMR) facilities into metabolomics studies are unfortunately restricted by their large dimensions, high costings, and specialist technical staff requirements. Therefore, here the application and practical advantages offered by low-field (60 MHz), compact NMR spectrometers for probing the metabolic profiles of human saliva was explored, as was their value in salivary metabolomics studies. Saliva samples were collected from cigarette smoking (n = 11) and non-smoking (n = 31) human participants. <sup>1</sup> H NMR spectra were acquired on both low-field (60 MHz) and medium-field (400 MHz) spectrometers. Metabolomics analyses were employed to evaluate the consistencies of salivary metabolite levels determined, and their abilities to distinguish between smokers and non-smokers. Low-field <sup>1</sup> H NMR analysis detected up to 15, albeit permitted the reliable quantification of 5, potentially key diagnostic biomolecules simultaneously (LLOQ values 250–400 μmol/L), although these were limited to those with the most prominent resonances. Such low-field profiles were also found to be suitable for salivary metabolomics investigations, which confirmed the successful discrimination between smoking and non-smoking participant sample donors. Differences observed between these groups were largely ascribable to upregulated salivary levels of methanol, and its metabolite formate, in the smoking group, but higher smoking-mediated concentrations of acetate, propionate and glycine may arise from a diminished salivary flow-rate in these participants. In conclusion, determination of salivary biomolecules using low-field, benchtop <sup>1</sup> H NMR analysis techniques were found to be valuable for bioanalytical and metabolomics investigations. Future perspectives for the applications of this non-stationary NMR technique, for example for the on-site 'point-of-care' testing of saliva samples for diagnostic oral disease screening purposes at dental surgeries and community pharmacies, are considered.

**Keywords:** compact low-field NMR analysis, NMR spectroscopy, NMR-linked metabolomics, bioanalytical chemistry, saliva, salivary biomarkers, oral diseases, tobacco smoking, salivary biomarkers for smoking, methanol

### **1. Introduction**

'State-of-the-art' developments of novel devices and facilities for the metabolic screening of biofluids through 'omics'strategies provide an encouraging and thoroughly emerging outlook for future healthcare management prospects, including those focused on the diagnosis of diseases and/or their prognostic stratification [1]. Indeed, high-field (HF) nuclear magnetic resonance (NMR) facilities are routinely used for metabolomics investigations in order to rapidly recognize unusual metabolic patterns in patients suffering from a wide range of diseases. However, deployments in healthcare settings have been prohibitively impacted by the large sizes and costs of the instrumentation required for these purposes [2].

Imbalances in the human metabolome have long been associated with healthmediated disturbances, with ancient societies employing very crude methods to assess biofluids [3], including the smell and taste of urine samples to detect urinary ketone bodies and glucose, respectively, in cases of diabetes, for example. However, more recently there have been many notable developments in this research area, and these have given rise to the development of multicomponent metabolic profile analysis by many researchers since the early 1970s [4–7]. Whilst tandem liquid-chromatographicand gas-chromatographic-mass spectrometric methods (LC-MS and GC-MS, respectively) can be employed for the reliable and sensitive determination of low concentrations of metabolites in biofluids, these approaches suffer from issues associated with matrix effects, and both are destructive techniques, which usually require a substantial knowledge of sample composition, and the likely identities of key biomarker analytes, prior to analysis [8]. Conversely, high-resolution NMR-based metabolomics analysis offers a highly selective means of simultaneously identifying a wide range of biomolecules present in complex biofluids at a minimal detectable concentration of ≤5 μM, providing an untargeted methodology ideal for the analysis of a very large number of biomolecules simultaneously [9] (up to 120 or so and *ca.* 80 in human urine and saliva, respectively at operating frequencies of ≥600 MHz). Therefore, the multicomponent <sup>1</sup> H NMR analysis of biofluids such as blood plasma, urine and saliva, and tissue biopsies, offers a high level of potential regarding the investigation of metabolic processes, and when coupled with conventional and/or newlydeveloped multivariate (MV) data analysis techniques, serves as an extremely powerful means of probing the biochemical basis of human disease aetiology [1–5]. Indeed, this form of combined multianalyte-MV analysis is generally classified as metabolomics, and has been extensively applied in a very wide range of biomedical and clinical investigations, including the identification of diagnostic or prognostic biomarkers for a very wide range of diseases.

Although previous applications of low-field (LF) rather than HF NMR spectroscopy to the multicomponent analysis of intact or near-intact biofluids, or other biological media, have been severely limited, our laboratory has paved the way forward for the performance of such studies. Indeed, one of our recent investigations explored the ability of a LF (60 MHz) NMR spectrometer to provide valuable urinary

#### *Metabolomics Distinction of Cigarette Smokers from Non-Smokers Using Non-Stationary… DOI: http://dx.doi.org/10.5772/intechopen.101414*

metabolite data for the monitoring of type 2 diabetes (T2D) in humans [10]. Indeed, this application displayed a high level of chemopathological classification success, although this is perhaps not completely unexpected, since uncontrolled or poorly controlled T2D samples all contain quite high levels of glucose (both <sup>1</sup> H NMRdistinguishable α- and β-anomers), along with the ketone bodies acetoacetate, acetone and 3-D-hydroxybutyrate, whereas little or none of these biomolecules are normally detectable in healthy control samples. However, one of the major advantages of the <sup>1</sup> H NMR technique is that it can simultaneously detect and monitor abnormal levels of a range of further metabolites involved in human disease pathology and associated comorbidities, for example excessive urinary creatinine concentrations arising from kidney dysfunction and damage in T2D, together with hypoglycaemic drugs such as metformin [11].

Saliva serves as a multifunctional biofluid which plays important roles in facilitating the chewing, swallowing and tasting of foods, and also the regulation of oral flora; hence, it is of much importance for the maintenance of overall health in humans. Indeed, human saliva comprises an agglomerate hypertonic 'solution' which contains oral mucosal exudates, salivary acini and gingival crevicular fluid (GCF) [12]. Since this biofluid is readily accessible, it offers much potential as a medium for the identification and monitoring of established or potential biomarkers for human diseases, particularly oral health conditions, but not exclusively so. Indeed, it's collection can be self-performed by participants with minimal training and without clinical supervision. Therefore, here we have employed optimized LF NMR-based metabolic profiling strategies for the global analysis of human saliva in order to assess the viabilities of these compact instruments for biomedical applications in metabolic profiling, metabolomics, oral health assessments, and potentially future screenings of the efficacies of oral healthcare products. Coupling of this LF salivary analysis technique to MV analysis strategies may indeed serve to facilitate the development of favourable outcome strategies for such investigations, and therefore here we also demonstrate, for the first time, the applications of LF NMR-based metabolomics protocols to the distinction of saliva samples collected from non-smoking and tobacco cigarettesmoking subjects. The future clinical monitoring applications of this novel technique are discussed.
