Metabolomic Fingerprinting in Various Body Fluids of a Diet-Controlled Clinical Smoking Cessation Study Using a Validated GC-TOF-MS Metabolomics Platform

A comprehensive non-targeted approach for the analysis of biomarkers in exhaled breath across different nicotine product categories

In the context of the evolving landscape of nicotine consumption, the assessment of biomarkers plays a crucial role in understanding the health impact of different product categories. Exhaled breath (EB) emerges as a promising, non-invasive matrix for biomarker analysis, complementary to conventional urine and plasma data. This study explores distinctive EB biomarker profiles among users of combustible cigarettes (CC), heated tobacco products (HTP), electronic cigarettes (EC), smokeless/oral tobacco (OT), and oral/dermal nicotine products (NRT). We have successfully developed and validated a non-targeted GC-TOF-MS method for the analysis of EB samples across the aforementioned product categories. A total of 66 compounds were identified, with significantly elevated levels in at least one study group. The study found that CC users had higher levels of established VOCs associated with smoking, which supports the proof-of-concept of the method. Breathomic analysis identified increased levels of p-cymene and α-pinene in EC users, while HTP users showed potential biomarker candidates like γ-butyrolactone. This study underscores the utility of EB biomarkers for a comprehensive evaluation of diverse nicotine products. The unique advantages offered by EB analysis position it as a valuable tool for understanding the relationship between exposure and health outcomes.

Ion mobility spectrometry and ion mobility-mass spectrometry in clinical chemistry

Advancements in clinical chemistry have major implications in terms of public health, prompting many clinicians to seek out chemical information to aid in diagnoses and treatments. While mass spectrometry (MS) and hyphenated-MS techniques such as LC-MS or tandem MS/MS have long been the analytical methods of choice for many clinical applications, these methods routinely demonstrate difficulty in differentiating between isomeric forms in complex matrices. Consequently, ion mobility spectrometry (IM), which differentiates molecules on the basis of size, shape, and charge, has demonstrated unique advantages in the broad application of stand-alone IM and hyphenated IM instruments towards clinical challenges. Here, we highlight representative IM applications and approaches and describe contemporary commercial offerings of IM technology and how these can be, or are currently being, applied to the field of clinical chemistry.

Role of untargeted omics biomarkers of exposure and effect for tobacco research

Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.

Lipidomic analysis reveals the effect of passive smoking on facial skin surface lipid in females

BACKGROUND

Smoking has toxic effects on the skin and can damage it. However, few studies have focused on the lipid profile changes of facial skin surface lipids (SSL) by passive smoking.

METHOD

A cross-sectional analytical study was conducted on middle-aged females volunteered from Henan, China to participate in the study. A total of 20 passive smoking females and 20 non-passive smoking females were recruited for this study. The components of skin surface lipids were measured by ultra-performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-QTOF-MS). Multivariate data analysis and enrichment analysis were used to investigate the differences in facial SSL between passive and non-passive smoking females.

RESULT

There were 1247 lipid entities identified in facial SSL between passive and non-passive smoking females. Significant differences in composition of facial SSL were observed between the two groups. After multivariate data analysis suggested, 28 significantly different lipids were identified and classified into four classes in SSL of the female cheeks. As well as 32 significantly different lipids were obtained in SSL of the female foreheads, which included three classes of lipids. Subsequent analysis revealed that the content of fatty acids (FA) in passive smoking females was significantly reduced and the content of glycerolipids (GL) and sphingolipids (SP) increased, compared with the control group.

CONCLUSION

These results indicated that an increase in GLs and SPs of facial lipids and a decrease in FAs in passive smoking females. These changes in lipids might be associated with oxidative stress and interference with signaling pathways by substances in smoke. And passive smoking affected facial SSL and changed the content and metabolism of skin lipids.

Urine metabolomics analysis of sleep quality in deep-underground miners: A pilot study

Background

In previous questionnaire surveys of miners, sleep disorders were found among underground workers. The influence of the special deep-underground environment and its potential mechanism are still unclear. Therefore, this study intends to utilize LC-MS metabolomics to study the potential differences between different environments and different sleep qualities.

Methods

Twenty-seven miners working at 645-1,500 m deep wells were investigated in this study, and 12 local ground volunteers were recruited as the control group. The Pittsburgh Sleep Quality Index (PSQI) was used to examine and evaluate the sleep status of the subjects in the past month, and valuable basic information about the participants was collected. PSQI scores were obtained according to specific calculation rules, and the corresponding sleep grouping and subsequent analysis were carried out. Through liquid chromatography-mass spectrometry (LC-MS) non-targeted metabolomics analysis, differences in metabolism were found by bioinformatics analysis in different environments.

Results

Between the deep-underground and ground (DUvsG) group, 316 differential metabolites were identified and 125 differential metabolites were identified in the good sleep quality vs. poor sleep quality (GSQvsPSQ) group. The metabolic pathways of Phenylalanine, tyrosine and tryptophan biosynthesis (p = 0.0102) and D-Glutamine and D-glutamate metabolism (p = 0.0241) were significantly enriched in DUvsG. For GSQvsPSQ group, Butanoate metabolism was statistically significant (p = 0.0276). L-Phenylalanine, L-Tyrosine and L-Glutamine were highly expressed in the deep-underground group. Acetoacetic acid was poorly expressed, and 2-hydroxyglutaric acid was highly expressed in good sleep quality.

Conclusions

The influence of the underground environment on the human body is more likely to induce specific amino acid metabolism processes, and regulate the sleep-wake state by promoting the production of excitatory neurotransmitters. The difference in sleep quality may be related to the enhancement of glycolytic metabolism, the increase in excitatory neurotransmitters and the activation of proinflammation. L-phenylalanine, L-tyrosine and L-glutamine, Acetoacetic acid and 2-hydroxyglutaric acid may be potential biomarkers correspondingly.

Physiology, pathology and the biomolecular corona: the confounding factors in nanomedicine design

The biomolecular corona that forms on nanomedicines in different physiological and pathological environments confers a new biological identity. How the recipient biological system's state can potentially affect nanomedicine corona formation, and how this can be modulated, remains obscure. With this perspective, this review summarizes the current knowledge about the content of biological fluids in various compartments and how they can be affected by pathological states, thus impacting biomolecular corona formation. The content of representative biological fluids is explored, and the urgency of integrating corona formation, as an essential component of nanomedicine designs for effective cargo delivery, is highlighted.

Development of a method for dansylation of metabolites using organic solvent-compatible buffer systems for amine/phenol submetabolome analysis

Metabolomics, which serves as a readout of biological processes and diseases monitoring, is an informative research area for disease biomarker discovery and systems biology studies. In particular, reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) has become a powerful and popular tool for metabolomics analysis, enabling the detection of most metabolites. Very polar and ionic metabolites, however, are less easily detected because of their poor retention in RP columns. Dansylation of metabolites simplifies the sub-metabolome analysis by reducing its complexity and increasing both hydrophobicity and ionization ability. However, the various metabolite concentrations in clinical samples have a wide dynamic range with highly individual variation in total metabolite amount, such as in saliva. The bicarbonate buffer typically used in dansylation labeling reactions induces solvent stratification, resulting in poor reproducibility, selective sample loss and an increase in false-determined metabolite peaks. In this study, we optimized the dansylation protocol for samples with wide concentration range of metabolites, utilizing diisopropylethylamine (DIPEA) or tri-ethylamine (TEA) in place of bicarbonate buffer, and presented the results of a systemic investigation of the influences of individual processes involved on the overall performance of the protocol. In addition to achieving high reproducibility, substitution of DIPEA or TEA buffer resulted in similar labeling efficiency of most metabolites and more efficient labeling of some metabolites with a higher pK_a. With this improvement, compounds that are only present in samples in trace amounts can be detected, and more comprehensive metabolomics profiles can be acquired for biomarker discovery or pathway analysis, making it possible to analyze clinical samples with limited amounts of metabolites.

Metabolomic Analysis Identified Reduced Levels of Xenobiotics, Oxidative Stress, and Improved Vitamin Metabolism in Smokers Switched to Vuse Electronic Nicotine Delivery System

Introduction

Switching to noncombustible tobacco products presents an opportunity for cigarette smokers to potentially reduce the health risks associated with smoking. Electronic Nicotine Delivery Systems (ENDS) are one such product because the vapor produced from ENDS contains far fewer toxicants than cigarette smoke. To investigate the biochemical effects of switching from smoking to an ENDS, we assessed global metabolomic profiles of smokers in a 7-day confinement clinical study.

Methods

In the first 2 days of this clinical study, the subjects used their usual brand of cigarettes and then switched to exclusive ENDS ad libitum use for 5 days. Urine and plasma samples were collected at baseline and 5 days after switching. The samples were analyzed using a mass spectrometry-based metabolomic platform.

Results

Random forest analyses of urine and plasma metabolomic data revealed excellent predictive accuracy (>97%) of a 30-metabolite signature that can differentiate smokers from 5-day ENDS switchers. In these signatures, most biomarkers are nicotine-derived metabolites or xenobiotics. They were significantly reduced in urine and plasma, suggesting a decreased xenobiotic load on subjects. Our results also show significantly decreased levels of plasma glutathione metabolites after switching, which suggests reduced levels of oxidative stress. In addition, increased urinary and plasma levels of vitamins and antioxidants were identified, suggesting enhanced bioavailability due to discontinuation of cigarette smoking and switching to Vuse ENDS use.

Conclusions

Our results suggest reduced toxicant exposure, reduced oxidative stress, and potential beneficial changes in vitamin metabolism within 5 days in smokers switching to Vuse ENDS.

Implications

Switching from smoking to exclusive ENDS use in clinical confinement settings results in significant reduction of nicotine metabolites and other cigarette-related xenobiotics in urine and plasma of subjects. Significantly decreased oxidative stress-related metabolites and increased urinary and plasma levels of vitamin metabolites and antioxidants in 5-day short-term ENDS switchers suggest less toxic physiological environment for consumers of ENDS products and potential health benefits if such changes persist.

Identification of biomarkers specific to five different nicotine product user groups: Study protocol of a controlled clinical trial

Background

Assessing biomarker profiles in various body fluids is of large value to discern between the sole use of nicotine products. In particular, the assessment of the product compliance is required for long-term clinical studies. The objective of this study was the identification of biomarkers and biomarker patterns in body fluids, to distinguish between combustibles, heated tobacco products, electronic cigarettes, oral tobacco and oral/dermal nicotine products used for nicotine replacement therapy (NRT), as well as a control group of non-users.

Methods

A controlled, single-center study was conducted with 60 healthy subjects, divided into 6 groups (5 nicotine product user groups and one non-user group) based on their sole use of the products of choice. The subjects were confined for 76 h, during which, free and uncontrolled use of the products was provided. Sample collections were performed according to the study time schedule provided in Table 2. The primary outcome will be validated through analysis of the collected biospecimens (urine, blood, saliva, exhaled breath and exhaled breath condensate) by means of untargeted omics approaches (i.e. exposomics, breathomics and adductomics). Secondary outcome will include established biomarker quantification methods to allow for the identification of typical biomarker patterns. Statistical analysis tools will be used to specifically discriminate different product use categories.

Results/Conclusions

The clinical trial was successfully completed in May 2020, resulting in sample management and preparations for the quantitative and qualitative analyses. This work will serve as a solid basis to discern between biomarker profiles of different nicotine product user groups. The knowledge collected during this research will be required to develop prototype diagnostic tools that can reliably assess the differences and evaluate possible health risks of various nicotine products.

Chemoradiation therapy changes oral microbiome and metabolomic profiles in patients with oral cavity cancer and oropharyngeal cancer

BACKGROUND

Patients with oral cavity cancer (OCC) and oropharyngeal cancer (OPC) are often seen with locoregionally advanced disease requiring complex multimodality treatments. These treatments may have detrimental effects on the oral microbiome, which is critical to maintaining physiological balance and health.

METHODS

The effects of different OCC and OPC treatment types on the oral microbiome and metabolomic profiles for 24-month post-treatment in patients with OCC and OPC were investigated using 16S rRNA gene amplicon next-generation sequencing and gas chromatography-mass spectrometry (GC-MS), respectively.

RESULTS

Chemoradiation resulted in oral dysbiosis with specific depletion of genera which regulate the enterosalivary nitrate-nitrite-nitric oxide pathway. These data also correlate with the oral metabolomic profiles with nitric oxide-related precursor, modulator, or catalyst significantly downregulated in saliva samples from patients' postchemoradiation.

CONCLUSIONS

Together, we have shown that oral dysbiosis due to the effects of chemoradiation could potentially have an impact on OCC and OPC patient's quality of life post-treatment.

Salivaomics as a Potential Tool for Predicting Alzheimer's Disease During the Early Stages of Neurodegeneration

BACKGROUND

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is poorly understood and the relationships between systemic abnormalities in metabolism and AD/AMCI pathogenesis are unclear.

OBJECTIVE

The aim of the study was to compare the metabolomic and proteomic signature of saliva from cognitively normal and patients diagnosed with MCI or AD, to identify specific cellular pathways altered with the progression of the disease.

METHODS

We analyzed 80 saliva samples from individuals with MCI or AD as well as age- and gender-matched healthy controls. Saliva proteomic and metabolomic analyses were conducted utilizing mass spectrometry methods and data combined using pathway analysis.

RESULTS

We found significant alterations in multiple cellular pathways, demonstrating that at the omics level, disease progression impacts numerous cellular processes. Multivariate statistics using SIMCA showed that partial least squares-data analysis could be used to provide separation of the three groups.

CONCLUSION

This study found significant changes in metabolites and proteins from multiple cellular pathways in saliva. These changes were associated with AD, demonstrating that this approach might prove useful to identify new biomarkers based upon integration of multi-omics parameters.

Short halt in vaping modifies cardiorespiratory parameters and urine metabolome: a randomized trial

Propylene glycol and glycerol are e-cigarette constituents that facilitate liquid vaporization and nicotine transport. As these small hydrophilic molecules quickly cross the lung epithelium, we hypothesized that short-term cessation of vaping in regular users would completely clear aerosol deposit from the lungs and reverse vaping-induced cardiorespiratory toxicity. We aimed to assess the acute effects of vaping and their reversibility on biological/clinical cardiorespiratory parameters [serum/urine pneumoproteins, hemodynamic parameters, lung-function test and diffusing capacities, transcutaneous gas tensions (primary outcome), and skin microcirculatory blood flow]. Regular e-cigarette users were enrolled in this randomized, investigator-blinded, three-period crossover study. The periods consisted of nicotine-vaping (nicotine-session), nicotine-free vaping (nicotine-free-session), and complete cessation of vaping (stop-session), all maintained for 5 days before the session began. Multiparametric metabolomic analyses were used to verify subjects' protocol compliance. Biological/clinical cardiorespiratory parameters were assessed at the beginning of each session (baseline) and after acute vaping exposure. Compared with the nicotine- and nicotine-free-sessions, a specific metabolomic signature characterized the stop-session. Baseline serum club cell protein-16 was higher during the stop-session than the other sessions (P < 0.01), and heart rate was higher in the nicotine-session (P < 0.001). Compared with acute sham-vaping in the stop-session, acute nicotine-vaping (nicotine-session) and acute nicotine-free vaping (nicotine-free-session) slightly decreased skin oxygen tension (P < 0.05). In regular e-cigarette-users, short-term vaping cessation seemed to shift baseline urine metabolome and increased serum club cell protein-16 concentration, suggesting a decrease in lung inflammation. Additionally, acute vaping with and without nicotine decreased slightly transcutaneous oxygen tension, likely as a result of lung gas exchanges disturbances.

Effects of cessation of cigarette smoking on eicosanoid biomarkers of inflammation and oxidative damage

The urinary metabolites “prostaglandin E₂ metabolite” (PGE-M) and (Z)-7-[1R,2R,3R,5S)-3,5-dihydroxy-2-[(E,3S)-3-hydroxyoct-1-enyl]cyclopentyl]hept-5-enoic acid (8-iso-PGF_2α) are biomarkers of inflammation and oxidative damage, respectively, and are elevated in cigarette smokers. Relatively little is known about the effects of smoking cessation on these biomarkers. To investigate this, current cigarette smokers interested in quitting were recruited and invited to participate in a smoking cessation study where varenicline (Chantix) and brief supportive behavioral counseling were offered at each visit after baseline. Subjects returned to the clinic during the 12 week treatment phase for 9 visits post cessation on days 3, 7, 14, 21, 28, 42, 56, 70 and 84. Urine samples were collected at each visit and analyzed by liquid chromatography-tandem mass spectrometry for PGE-M, 8-iso-PGF_2α, and cotinine. Cotinine values demonstrated that 15 of 38 subjects quit smoking for the entire 84 day period. Significant decreases in mean levels of PGE-M and 8-iso-PGF_2α per milligram creatinine were observed in these subjects, by 44% (p = 0.0014) and 27% (p<0.001), respectively. The results of this study demonstrate that cessation of smoking for 84 days results in modest but significant declines in urinary PGE-M and 8-iso-PGF_2α indicating reductions in systemic inflammation and oxidative damage. Given that levels were only modestly decreased, these markers are not specific to tobacco-smoke exposure. The modest declines in these biomarkers should be considered when planning studies with ex-smokers. There is a “hangover” from smoking that lasts at least 3 months.