Volatile Organic Compounds in Patients With Acute Kidney Injury and Changes During Dialysis

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Evaluation of urinary volatile organic compounds as a novel metabolomic biomarker to assess chronic kidney disease progression

BACKGROUND

There is a need to develop accurate and reliable non-invasive methods to evaluate chronic kidney disease (CKD) status and assess disease progression. Given it is recognized that dysregulation in metabolic pathways occur from early CKD, there is a basis in utilizing metabolomic biomarkers to monitor CKD progression. Volatile Organic Compounds (VOCs), a form of metabolomic biomarker, are gaseous products of metabolic processes in organisms which are typically released with greater abundance in disease conditions when there is dysregulation in metabolism. How urinary VOCs reflect the abnormal metabolic profile of patients with CKD status is unknown. Our study aimed to explore this.

METHODS

Individuals aged 18-75 years undergoing kidney biopsy were included. Pre-biopsy urine samples were collected. All biopsy samples had an interstitial fibrosis and tubular atrophy (IFTA) grade scored by standardized assessment. Urine supernatant was extracted from residue and sampled for stir bar sorptive extraction followed by Gas chromatography-mass spectrometry (GC-MS) analysis. Post-processing of GC-MS data separated complex mixtures of VOCs based on their volatility and polarity. Mass-to-charge ratios and fragment patterns were measured for individual VOCs identification and quantification. Linear discriminant analysis (LDA) was performed to assess the ability of urinary VOCs in discriminating between IFTA 0 ('no or minimal IFTA' i.e. <10%, IFTA), IFTA 1 ('mild IFTA' i.e. 10-25% IFTA) and IFTA ≥ 2 ('moderate or severe IFTA' i.e. >25% IFTA). Linear regression analysis adjusting for age, sex, estimated glomerular filtration rate, diabetes mellitus (DM) status, and albuminuria was conducted to determine significantly regulated urinary VOCs amongst the groups.

RESULTS

64 study participants (22 individuals IFTA 0, 15 individuals IFTA 1, 27 individuals IFTA ≥ 2) were included. There were 34 VOCs identified from GC-MS which were statistically associated with correct classification between the IFTA groups, and LDA demonstrated individuals with IFTA 0, IFTA 1 and IFTA ≥ 2 could be significantly separated by their urinary VOCs profile (p < 0.001). Multivariate linear regression analysis reported 4 VOCs significantly upregulated in the IFTA 1 compared to the IFTA 0 group, and 2 VOCs significantly upregulated in the IFTA ≥ 2 compared to the IFTA 1 group (p < 0.05). Significantly upregulated urinary VOCs belonged to one of four functional groups - aldehydes, ketones, hydrocarbons, or alcohols.

CONCLUSIONS

We report novel links between urinary VOCs and tubulointerstitial histopathology. Our findings suggest the application of urinary VOCs as a metabolomic biomarker may have a useful clinical role to non-invasively assess CKD status during disease progression.

Breath VOC analysis and machine learning approaches for disease screening: a review

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

The research hotspots and trends of volatile organic compound emissions from anthropogenic and natural sources: A systematic quantitative review

Volatile organic compound (VOC) emissions have attracted wide attention due to their impacts on atmospheric quality and public health. However, most studies reviewed certain aspects of natural VOCs (NVOCs) or anthropogenic VOCs (AVOCs) rather than comprehensively quantifying the hotspots and evolution trends of AVOCs and NVOCs. We combined the bibliometric method with the evolution tree and Markov chain to identify research focus and uncover the trends in VOC emission sources. This study found that research mainly focused on VOC emission characteristics, effects on air quality and health, and VOC emissions under climate change. More studies concerned on AVOCs than on NVOCs, and AVOC emissions have shifted with a decreasing proportion of transport emissions and an increasing share of solvent utilization in countries with high emissions and publications (China and the USA). Research on AVOCs is imperative to develop efficient and economical abatement techniques specific to solvent sources or BTEX species to mitigate the detrimental effects. Research on NVOCs originating from human sources risen due to their application in medicine, while studies on sources sensitive to climate change grew slowly, including plants, biomass burning, microbes, soil and oceans. Research on the long-term responses of NVOCs derived from various sources to climate warming is warranted to explore the evolution of emissions and the feedback on global climate. It is worthwhile to establish an emission inventory with all kinds of sources, accurate estimation, high spatial and temporal resolution to capture the emission trends in the synergy of industrialization and climate change as well as to simulate the effects on air quality. We review VOC emissions from both anthropogenic and natural sources under climate change and their effects on atmospheric quality and health to point out the research directions for the comprehensive control of global VOCs and mitigation of O₃ pollution.

Patterns of volatile organic compounds in excrements of preterm neonates

BACKGROUND

As neonates are susceptible for many diseases, establishing noninvasive diagnostic methods is desirable. We hypothesized that volatile organic compounds (VOCs) could be successfully measured in diaper samples.

METHODS

We performed a feasibility study to investigate whether ambient air-independent headspace measurements of the VOC profiles of diapers from premature infants can be conducted using ion mobility spectrometer coupled with multi-capillary columns (B & S Analytik GmbH).

RESULTS

We analysed 39 diapers filled with stool (n = 10) or urine (n = 20) respectively, using empty diapers as a control (n = 9). A total of 158 different VOCs were identified, and we classified the content of the diapers (urine or stool) according to their VOC profiles with a significance level of p < 0.05.

CONCLUSIONS

We have developed a novel method to study headspace VOC profiles of biosamples using ion mobility spectrometry coupled with multi-capillary columns. Using this method, we have characterized the VOC profiles of stool and urine of preterm neonates. Future studies are warranted to characterize specific VOC profiles in infections and other diseases of the preterm neonate, thus establishing quick and noninvasive diagnostics in the routine care of the highly vulnerable preterm and term neonates.

Quantification of Volatile Aldehydes Deriving from In Vitro Lipid Peroxidation in the Breath of Ventilated Patients

Exhaled aliphatic aldehydes were proposed as non-invasive biomarkers to detect increased lipid peroxidation in various diseases. As a prelude to clinical application of the multicapillary column–ion mobility spectrometry for the evaluation of aldehyde exhalation, we, therefore: (1) identified the most abundant volatile aliphatic aldehydes originating from in vitro oxidation of various polyunsaturated fatty acids; (2) evaluated emittance of aldehydes from plastic parts of the breathing circuit; (3) conducted a pilot study for in vivo quantification of exhaled aldehydes in mechanically ventilated patients. Pentanal, hexanal, heptanal, and nonanal were quantifiable in the headspace of oxidizing polyunsaturated fatty acids, with pentanal and hexanal predominating. Plastic parts of the breathing circuit emitted hexanal, octanal, nonanal, and decanal, whereby nonanal and decanal were ubiquitous and pentanal or heptanal not being detected. Only pentanal was quantifiable in breath of mechanically ventilated surgical patients with a mean exhaled concentration of 13 ± 5 ppb. An explorative analysis suggested that pentanal exhalation is associated with mechanical power—a measure for the invasiveness of mechanical ventilation. In conclusion, exhaled pentanal is a promising non-invasive biomarker for lipid peroxidation inducing pathologies, and should be evaluated in future clinical studies, particularly for detection of lung injury.

Exhaled breath analysis in disease detection

Investigating the use of exhaled breath analysis to diagnose and monitor different diseases has attracted much interest in recent years. This review introduces conventionally used methods and some emerging technologies aimed at breath analysis and their relevance to lung disease, airway inflammation, gastrointestinal disorders, metabolic disorders and kidney diseases. One section correlates breath components and specific diseases, whereas the other discusses some unique ideas, strategies, and devices to analyze exhaled breath for the diagnosis of some common diseases. This review aims to briefly introduce the potential application of exhaled breath analysis for the diagnosis and screening of various diseases, thereby providing a new avenue for the detection of non-invasive diseases.