Exhaled breath condensate to discriminate individuals with different smoking habits by GC-TOF/MS.

Smoking is a crucial factor in respiratory diseases and lung inflammation, which are the reasons for high mortality worldwide. Despite the negative impact that tobacco consumption causes on health, few metabolomics studies have compared the composition of biofluids from smoker and non-smoker individuals. Exhaled breath condensate (EBC) is one of the biofluids less employed for clinical studies despite its non-invasive sampling and the foreseeable relationship between its composition and respiratory diseases. EBC was used in this research as clinical sample to compare three groups of individuals: current smokers (CS), former smokers (FS) and never smokers (NS). Special attention was paid to the cumulative consumption expressed as smoked pack-year. The levels of 12 metabolites found statistically significant among the three groups of individuals were discussed to find an explanation to their altered levels. Significant compounds included monoacylglycerol derivatives, terpenes and other compounds, the presence of which could be associated to the influence of smoking on the qualitative and quantitative composition of the microbiome.

Identification of metabolomics panels for potential lung cancer screening by analysis of exhaled breath condensate.

Exhaled breath condensate (EBC) is one of the less employed biofluids when searching for clinical markers, despite its non-invasive sampling and the potential relationship between its composition and respiratory disease phenotypes such as lung cancer. The advanced stage at which lung cancer is usually detected is the main reason for the high mortality rate of this carcinogenic disease. In this preliminary research, EBC was used as clinical sample to develop a screening tool for lung cancer discrimination from two control groups (with and without risk factor). Three panels of metabolites were configured using the PanelomiX tool to minimize false negatives (specificity) and false positives (sensitivity). The combination of five metabolites led to three panels providing a sensitivity above 77.9%, specificity above 67.5% and the area under the curve (AUC) above 77.5% for the three panels. An additional study was developed as a first approach to study the statistical significance of metabolites at different stages of lung cancer.

Metabolomics analysis of exhaled breath condensate for discrimination between lung cancer patients and risk factor individuals.

The search for new clinical tests aimed at diagnosing chronic respiratory diseases is a current research line motivated by the lack of efficient screening tools and the severity of some of these pathologies. Alternative biological samples can open the door to new screening tools. A promising biofluid that is rarely used for diagnostic purposes is exhaled breath condensate (EBC), the composition of which has been inadequately studied. In this research, untargeted analysis of EBC using gas chromatography time-of-flight mass spectrometry has been applied to a cohort of patients with lung cancer (n = 48), risk factor individuals (active smokers and ex-smokers, n = 130) and control healthy individuals (non-smokers without respiratory diseases, n = 61). An identical protocol was applied to the two EBC fractions provided by the sampling device (upper and central airways and distal airway) from each individual, which allowed the compositional differences between the two EBC fractions to be detected. Tentative compounds that contribute to discrimination between the three groups were identified, and a relevant role for lipids such as monoacylglycerols and squalene was found. These results could support the ability of metabolomics to go inside the study of lung cancer.

Influence of the collection tube on metabolomic changes in serum and plasma.

Major threats in metabolomics clinical research are biases in sampling and preparation of biological samples. Bias in sample collection is a frequently forgotten aspect responsible for uncontrolled errors in metabolomics analysis. There is a great diversity of blood collection tubes for sampling serum or plasma, which are widely used in metabolomics analysis. Most of the existing studies dealing with the influence of blood collection on metabolomics analysis have been restricted to comparison between plasma and serum. However, polymeric gel tubes, which are frequently proposed to accelerate the separation of serum and plasma, have not been studied. In the present research, samples of serum or plasma collected in polymeric gel tubes were compared with those taken in conventional tubes from a metabolomics perspective using an untargeted GC-TOF/MS approach. The main differences between serum and plasma collected in conventional tubes affected to critical pathways such as the citric acid cycle, metabolism of amino acids, fructose and mannose metabolism and that of glycerolipids, and pentose and glucuronate interconversion. On the other hand, the polymeric gel only promoted differences at the metabolite level in serum since no critical differences were observed between plasma collected with EDTA tubes and polymeric gel tubes. Thus, the main changes were attributable to serum collected in gel and affected to the metabolism of amino acids such as alanine, proline and threonine, the glycerolipids metabolism, and two primary metabolites such as aconitic acid and lactic acid. Therefore, these metabolite changes should be taken into account in planning an experimental protocol for metabolomics analysis.

Development of a method for metabolomic analysis of human exhaled breath condensate by gas chromatography-mass spectrometry in high resolution mode.

Exhaled breath condensate (EBC) is a promising biofluid scarcely used in clinical analysis despite its non-invasive sampling. The main limitation in the analysis of EBC is the lack of standardized protocols to support validation studies. The aim of the present study was to develop an analytical method for analysis of human EBC by GC-TOF/MS in high resolution mode. Thus, sample preparation strategies as liquid-liquid extraction and solid-phase extraction were compared in terms of extraction coverage. Liquid-liquid extraction resulted to be the most suited sample preparation approach providing an average extraction efficiency of 77% for all compounds in a single extraction. Different normalization approaches were also compared to determine which strategy could be successfully used to obtain a normalized profile with the least variability among replicates of the same sample. Normalization to the total useful mass spectrometry signal (MSTUS) proved to be the most suited strategy for the analysis of EBC from healthy individuals (n = 50) reporting a within-day variability below 7% for the 51 identified compounds and a suited data distribution in terms of percentage of metabolites passing the Skewness and Kurtosis test for normality distribution. The composition of EBC was clearly dominated by the presence of fatty acids and derivatives such as methyl esters and amides, and volatile prenol lipids. Therefore, EBC offers the profile of both volatile and non-volatile components as compared to other similar biofluids such as exhaled breath vapor, which only provides the volatile profile. This human biofluid could be an alternative to others such as serum/plasma, urine or sputum to find potential markers with high value for subsequent development of screening models.

The role of ultrasound in analytical derivatizations.

Ultrasound is a type of energy that until recently was rarely used for analytical purposes. In recent years, work in chemical and industrial fields alerted analytical chemists to the great potential of ultrasonic energy to accelerate or improve different steps of the analytical process. One of these steps is derivatization: depolymerization, redox, hydrolysis, esterification, alkylation and complex formation are examples of derivatization reactions, all of which are significantly improved with the aid of ultrasound. This review discusses the valuable characteristics of ultrasound and its influence on a number of derivatization reactions is discussed in this review.