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While a number of methods are available for analyzing lipids, unbiased untargeted lipidomics with high coverage remains a challenge. In this work, we report a study of isotope-standard-assisted liquid chromatography mass spectrometry lipidomics of serum for biomarker discovery. We focus on Parkinson's disease (PD), a neurodegenerative disorder that often progresses to dementia. Currently, the diagnosis of PD is purely clinical and there is limited ability to predict which PD patients will transition to dementia, hampering early interventions. We studied serum samples from healthy controls and PD patients with no clinical signs of dementia. A follow-up 3 years later revealed that a subset of PD patients had transitioned to dementia. Using the baseline samples, we constructed two biomarker panels to differentiate (1) PD patients from healthy controls and (2) PD patients that remained cognitively stable from PD patients with incipient dementia (diagnosed 3 years after sample collection). The proposed biomarker panels displayed excellent performance and may be useful for detecting prodromal PD dementia, allowing early interventions and prevention efforts. The biochemistry of significantly changed lipids is also discussed within the current knowledge of neurological pathologies. Our results are promising and future work using a larger cohort of samples is warranted.

Cystic fibrosis is a genetic pathology characterized by abnormal accumulation of mucus in the respiratory, gastrointestinal, and reproductive tracts, caused by mutations in the CFTR gene. Although the classical presentation of the condition is well known, there is still a need for a better characterization of metabolic alterations related to cystic fibrosis and different genotypic mutations. We employed untargeted, comprehensive lipidomics of blood serum samples to investigate alterations in the lipid metabolism related to the pathology, mutation classes, and lung function decline. Six unique biomarker candidates were able to independently differentiate diseased individuals from healthy controls with excellent performance. Cystic fibrosis patients showed dyslipidemia for most lipid subclasses, with significantly elevated odd-chain and polyunsaturated fatty acyl lipids. Phosphatidic acids and diacylglycerols were particularly affected by different genotypic mutation classes. We selected a biomarker panel composed of four lipids, including two ceramides, one sphingomyelin, and one fatty acid, which correctly classified all validation samples from classes III and IV. A biomarker panel of five oxidized lipids was further selected to differentiate patients with reduced lung function, measured as predicted FEV1%. Our results indicate that cystic fibrosis is deeply related to lipid metabolism and provide new clues for the investigation of the disease mechanisms and therapeutic targets.

Respiratory syncytial virus (RSV) is a significant cause of mortality and morbidity in infants, the elderly, immunocompromised individuals, and patients with congenital heart diseases. Despite extensive efforts, a vaccine against RSV is still not available. We have previously reported the development of a subunit vaccine (ΔF/TriAdj) composed of a truncated version of the fusion protein (ΔF) and a polymer-based combination adjuvant (TriAdj). We compared inflammatory responses of ΔF/TriAdj-vaccinated and unvaccinated mice following intranasal challenge with RSV. Rapid and early inflammatory responses were observed in lung samples from both groups but modulated in the vaccinated group 7 days after the viral challenge. The underlying mechanism of action of ΔF/TriAdj was further studied through LC-MS-based metabolomic profiling by using 12C- or 13C-dansyl labeling for the amine/phenol submetabolome. RSV infection predominantly affected the amino acid biosynthesis pathways and urea cycle, whereas ΔF/TriAdj modulated the concentrations of almost all of the altered metabolites. Tryptophan metabolites were significantly affected, including indole, l-kynurenine, xanthurenic acid, serotonin, 5-hydroxyindoleacetic acid, and 6-hydroxymelatonin. The results from the present study provide further mechanistic insights into the mode of action of this RSV vaccine candidate and have important implications in the design of metabolic therapeutic interventions.

Dexamethasone is a synthetic glucocorticoid medication vastly used to treat abnormal immune responses and inflammation. Although the medication is well-established in the medical community, the prolonged treatment with high dosages of dexamethasone may lead to severe adverse effects through mechanisms that are not yet well-known. Lipids are a large class of hydrophobic molecules involved in energy storage, signaling, modulation of gene expression, and membranes. Hence, untargeted lipidomics may help unravel the biochemical alterations following prolonged treatment with high dosages of dexamethasone. We performed comprehensive lipidomic analyses of brain, heart, kidney, liver, and muscle samples obtained from rats that were treated with intramuscular injections of dexamethasone for 14 weeks compared to healthy controls. The employed methodology and statistical analysis showed that phosphatidic acids, glycerophospholipids, plasmalogens, and fatty acids are deeply affected by prolonged use of the medication. Brain tissue was only mildly affected, but skeletal muscle showed a strong accumulation of lipids that may be correlated with alterations in the energy metabolism, myopathy, and oxidative processes. This work provides new insights into the mechanisms of action and adverse effects for one of the most commonly prescribed class of drugs in the world.

Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory infections in young children. Although the disease may be severe in immunocompromised, young, and elderly people, there is currently no approved vaccine. We previously reported the development and immunological assessment of a novel intranasal vaccine formulation consisting of a truncated version of the RSV fusion protein (ΔF) combined with a three-component adjuvant (TriAdj). Now, we aim to investigate the mechanism of action of the ΔF/TriAdj formulation by searching for metabolic alterations caused by intranasal immunization and the RSV challenge. We carried out untargeted lipidomics and submetabolome profiling (carboxylic acids and amine/phenol-containing metabolites) of lung tissue from ΔF/TriAdj-immunized and nonimmunized, RSV-challenged mice. We observed significant changes of lipids involved in the lung surfactant layer for the nonimmunized animals compared to healthy controls but not for the immunized mice. Metabolic pathways involving the synthesis and regulation of amino acids and unsaturated fatty acids were also modulated by immunization and the RSV challenge. This study illustrates that lipidomic and metabolomic profiling could provide a more comprehensive understanding of the immunological and metabolic alterations caused by RSV and the modulation effected by the ΔF/TriAdj formulation.

Lipidomics focuses on the comprehensive analysis of lipids and their interactions with other molecules. Many biological samples are available in small volumes or limited amounts and display very complex lipid compositions; thus, highly sensitive lipidomic analysis methods are often needed. NanoLC-MS offers extremely high sensitivity, although it is known to be technically more challenging than the conventional LC-MS approach, requiring greater care and maintenance. This work describes the development and optimization of a nanoLC-MS method for routine analysis of the lipidome of small volumes of biological samples. We focused on achieving robust conditions for high sensitivity analysis of complex samples. The nanoLC method, mass spectrometry conditions and sample preparation by liquid-liquid extraction of lipids were fully optimized using serum samples and deuterated lipid standards, including an evaluation of contamination sources. The performance of the method was assessed through the analysis of human and pig sera, as well as cerebrospinal fluid samples from pigs. This method allowed the detection of 9900 to 12,200 features by employing only 1.0–2.5 μL of serum samples and identification of 5842 lipids from 36 subclasses within a 50-min gradient. The method can be easily adapted to other types of biological samples where only limited volumes are available.

Cancer is responsible for millions of deaths worldwide, but most base diseases may be cured if detected early. Screening tests may be used to identify early-stage malignant neoplasms. However, the major screening tool for prostate cancer, the prostate-specific antigen test, has unsuitable sensitivity. Since cancer cells may affect the pattern of consumption and excretion of nucleosides, such biomolecules are putative biomarkers that can be used for diagnosis and treatment evaluation. Using a previously validated method for the analysis of nucleosides in blood serum by capillary electrophoresis with UV-vis spectroscopy detection, we investigated 60 samples from healthy individuals and 42 samples from prostate cancer patients. The concentrations of nucleosides in both groups were compared and a multivariate partial least squares-discriminant analysis classification model was optimized for prediction of prostate cancer. The validation of the model with an independent sample set resulted in the correct classification of 82.4% of the samples, with sensitivity of 90.5% and specificity of 76.7%. A significant downregulation of 5-methyluridine and inosine was observed, which can be indicative of the carcinogenic process. Therefore, such analytes are potential candidates for prostate cancer screening. Graphical Abstract Separation of the studied nucleosides and the internal standard 8-Bromoguanosine by CE-UV (a); classification of the external validation samples (30 from healthy volunteers and 21 from prostate cancer patients) by the developed Partial Least Square - Discriminant Analysis (PLS-DA) model with accuracy of 82.4% (b); Receiver Operating Characteristics (ROC) curve (c); and Variable Importance in the Projection (VIP) values for the studied nucleosides (d). A significant down-regulation of 5- methyluridine (5mU) and inosine (I) was observed, which can be indicative of the presence of prostate tumors.

Metabolomics is one of the most recent trends in the "omics" era that investigates the end products of an organism activity, that is, all metabolites in a biological system, which are small molecules (less than 1000 Da) from different chemical classes. Metabolomics represents a tool to assess the biochemical activity of a living system through the analysis of substrates and products processed during the metabolism. The analysis of the metabolic profile (nontargeted analysis, i.e. a comparison between samples profiles of individuals) and of specific metabolites (targeted analysis, which quantifies a selected group of metabolites) in biological samples provides an insight into the metabolic state and the biochemical processes of the organism and, therefore, may indicate the onset and the stage of different diseases. An early and accurate diagnosis is essential for successful treatment and probable cure of most illnesses; hence, the investigation of metabolites as disease biomarkers has increased considerably in recent years. This review aims to present the most relevant works that address the nontargeted and targeted analysis of metabolites in different diseases for the past 10 years, including kidney and neurological disorders, cardiovascular diseases, diabetes, and cancer, using CE and LC coupled with the accurate detection of mass spectroscopy.

Malignant tumors are the cause of millions of deaths all over the world every year, but the detection of the disease in the first stages may save lives. Tumor biomarkers allow earlier and less invasive diagnosis, hence they are vital in the cancer treatment. Nucleosides have been investigated as a potential group of tumor biomarkers present in biological fluids. In this work, a method for the analysis of nucleosides in blood serum samples by capillary electrophoresis with UV detection (CE-UV) was developed and validated according to the current legislation in Brazil. Separation of ten nucleosides plus the internal standard was achieved in ca. 25 min. The method may contribute for earlier and more accurate diagnosis of cancer cases. Tumores malignos são a causa de milhões de falecimentos no mundo todos os anos, porém a detecção da doença em seu estágio inicial pode salvar vidas. Biomarcadores tumorais permitem diagnósticos mais precoces e menos invasivos, portanto são vitais no tratamento do câncer. Os nucleosídeos têm sido pesquisados como um grupo potencial de biomarcadores tumorais presentes em fluidos biológicos. Neste trabalho, um método para a análise de nucleosídeos por eletroforese capilar com detecção UV (CE-UV) em amostras de soro sanguíneo foi desenvolvido e validado de acordo com a legislação vigente no Brasil. A separação de dez nucleosídeos mais o padrão interno foi atingida em ca. 25 min. O método pode contribuir para o diagnóstico precoce e preciso de casos de câncer.