Annalaura Mastrangelo
@cnic.es
Immunobiology Lab
Spanish National Center for Cardiovascular Research (CNIC)
RESEARCH INTERESTS
Metabolomics, gut microbiota, biochemistry, analytical chemistry, biostatitistics, obesity, cardiovascul disease, lipidomics, diabetes, insulin resistance
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Laura Díaz-Marugan, Mattia Gallizioli, Leonardo Márquez-Kisinousky, Silvia Arboleya, Annalaura Mastrangelo, Francisca Ruiz-Jaén, Jordi Pedragosa, Climent Casals, Francisco Javier Morales, Sara Ramos-Romero,et al.
Ovid Technologies (Wolters Kluwer Health)
BACKGROUND: Respiratory and urinary tract infections are frequent complications in patients with severe stroke. Stroke-associated infection is mainly due to opportunistic commensal bacteria of the microbiota that may translocate from the gut. We investigated the mechanisms underlying gut dysbiosis and poststroke infection. METHODS: Using a model of transient cerebral ischemia in mice, we explored the relationship between immunometabolic dysregulation, gut barrier dysfunction, gut microbial alterations, and bacterial colonization of organs, and we explored the effect of several drug treatments. RESULTS: Stroke-induced lymphocytopenia and widespread colonization of lung and other organs by opportunistic commensal bacteria. This effect correlated with reduced gut epithelial barrier resistance, and a proinflammatory sway in the gut illustrated by complement and nuclear factor-κB activation, reduced number of gut regulatory T cells, and a shift of gut lymphocytes to γδT cells and T helper 1/T helper 17 phenotypes. Stroke increased conjugated bile acids in the liver but decreased bile acids and short-chain fatty acids in the gut. Gut fermenting anaerobic bacteria decreased while opportunistic facultative anaerobes, notably Enterobacteriaceae, suffered an expansion. Anti-inflammatory treatment with a nuclear factor-κB inhibitor fully abrogated the Enterobacteriaceae overgrowth in the gut microbiota induced by stroke, whereas inhibitors of the neural or humoral arms of the stress response were ineffective at the doses used in this study. Conversely, the anti-inflammatory treatment did not prevent poststroke lung colonization by Enterobacteriaceae. CONCLUSIONS: Stroke perturbs homeostatic neuro-immuno-metabolic networks facilitating a bloom of opportunistic commensals in the gut microbiota. However, this bacterial expansion in the gut does not mediate poststroke infection.
Stefanie K. Wculek, Ignacio Heras-Murillo, Annalaura Mastrangelo, Diego Mañanes, Miguel Galán, Verónica Miguel, Andrea Curtabbi, Coral Barbas, Navdeep S. Chandel, José Antonio Enríquez,et al.
Elsevier BV
Rafael Barrero-Rodríguez, Jose Manuel Rodriguez, Rocío Tarifa, Jesús Vázquez, Annalaura Mastrangelo, and Alessia Ferrarini
Frontiers Media SA
Untargeted metabolomics aims at measuring the entire set of metabolites in a wide range of biological samples. However, due to the high chemical diversity of metabolites that range from small to large and more complex molecules (i.e., amino acids/carbohydrates vs. phospholipids/gangliosides), the identification and characterization of the metabolome remain a major bottleneck. The first step of this process consists of searching the experimental monoisotopic mass against databases, thus resulting in a highly redundant/complex list of candidates. Despite the progress in this area, researchers are still forced to manually explore the resulting table in order to prioritize the most likely identifications for further biological interpretation or confirmation with standards. Here, we present TurboPutative (https://proteomics.cnic.es/TurboPutative/), a flexible and user-friendly web-based platform composed of four modules (Tagger, REname, RowMerger, and TPMetrics) that streamlines data handling, classification, and interpretability of untargeted LC-MS-based metabolomics data. Tagger classifies the different compounds and provides preliminary insights into the biological system studied. REname improves putative annotation handling and visualization, allowing the recognition of isomers and equivalent compounds and redundant data removal. RowMerger reduces the dataset size, facilitating the manual comparison among annotations. Finally, TPMetrics combines different datasets with feature intensity and relevant information for the researcher and calculates a score based on adduct probability and feature correlations, facilitating further identification, assessment, and interpretation of the results. The TurboPutative web application allows researchers in the metabolomics field that are dealing with massive datasets containing multiple putative annotations to reduce the number of these entries by 80%–90%, thus facilitating the extrapolation of biological knowledge and improving metabolite prioritization for subsequent pathway analysis. TurboPutative comprises a rapid, automated, and customizable workflow that can also be included in programmed bioinformatics pipelines through its RESTful API services. Users can explore the performance of each module through demo datasets supplied on the website. The platform will help the metabolomics community to speed up the arduous task of manual data curation that is required in the first steps of metabolite identification, improving the generation of biological knowledge.
Ana Devesa, Manuel Lobo-González, Juan Martínez-Milla, Belén Oliva, Inés García-Lunar, Annalaura Mastrangelo, Samuel España, Javier Sanz, José M Mendiguren, Hector Bueno,et al.
Oxford University Press (OUP)
Abstract Aims Experimental studies suggest that increased bone marrow (BM) activity is involved in the association between cardiovascular risk factors and inflammation in atherosclerosis. However, human data to support this association are sparse. The purpose was to study the association between cardiovascular risk factors, BM activation, and subclinical atherosclerosis. Methods and results Whole body vascular 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) was performed in 745 apparently healthy individuals [median age 50.5 (46.8–53.6) years, 83.8% men] from the Progression of Early Subclinical Atherosclerosis (PESA) study. Bone marrow activation (defined as BM 18F-FDG uptake above the median maximal standardized uptake value) was assessed in the lumbar vertebrae (L3–L4). Systemic inflammation was indexed from circulating biomarkers. Early atherosclerosis was evaluated by arterial metabolic activity by 18F-FDG uptake in five vascular territories. Late atherosclerosis was evaluated by fully formed plaques on MRI. Subjects with BM activation were more frequently men (87.6 vs. 80.0%, P = 0.005) and more frequently had metabolic syndrome (MetS) (22.2 vs. 6.7%, P < 0.001). Bone marrow activation was significantly associated with all MetS components. Bone marrow activation was also associated with increased haematopoiesis—characterized by significantly elevated leucocyte (mainly neutrophil and monocytes) and erythrocyte counts—and with markers of systemic inflammation including high-sensitivity C-reactive protein, ferritin, fibrinogen, P-selectin, and vascular cell adhesion molecule-1. The associations between BM activation and MetS (and its components) and increased erythropoiesis were maintained in the subgroup of participants with no systemic inflammation. Bone marrow activation was significantly associated with high arterial metabolic activity (18F-FDG uptake). The co-occurrence of BM activation and arterial 18F-FDG uptake was associated with more advanced atherosclerosis (i.e. plaque presence and burden). Conclusion In apparently healthy individuals, BM 18F-FDG uptake is associated with MetS and its components, even in the absence of systemic inflammation, and with elevated counts of circulating leucocytes. Bone marrow activation is associated with early atherosclerosis, characterized by high arterial metabolic activity. Bone marrow activation appears to be an early phenomenon in atherosclerosis development. [Progression of Early Subclinical Atherosclerosis (PESA); NCT01410318].
Stefanie K. Wculek, Gillian Dunphy, Ignacio Heras-Murillo, Annalaura Mastrangelo, and David Sancho
Springer Science and Business Media LLC
AbstractCellular metabolism orchestrates the intricate use of tissue fuels for catabolism and anabolism to generate cellular energy and structural components. The emerging field of immunometabolism highlights the importance of cellular metabolism for the maintenance and activities of immune cells. Macrophages are embryo- or adult bone marrow-derived leukocytes that are key for healthy tissue homeostasis but can also contribute to pathologies such as metabolic syndrome, atherosclerosis, fibrosis or cancer. Macrophage metabolism has largely been studied in vitro. However, different organs contain diverse macrophage populations that specialize in distinct and often tissue-specific functions. This context specificity creates diverging metabolic challenges for tissue macrophage populations to fulfill their homeostatic roles in their particular microenvironment and conditions their response in pathological conditions. Here, we outline current knowledge on the metabolic requirements and adaptations of macrophages located in tissues during homeostasis and selected diseases.
María Martínez-López, Salvador Iborra, Ruth Conde-Garrosa, Annalaura Mastrangelo, Camille Danne, Elizabeth R. Mann, Delyth M. Reid, Valérie Gaboriau-Routhiau, Maria Chaparro, María P. Lorenzo,et al.
Elsevier BV
&NA; Production of interleukin‐17 (IL‐17) and IL‐22 by T helper 17 (Th17) cells and group 3 innate lymphoid cells (ILC3s) in response to the gut microbiota ensures maintenance of intestinal barrier function. Here, we examined the mechanisms whereby the immune system detects microbiota in the steady state. A Syk‐kinase‐coupled signaling pathway in dendritic cells (DCs) was critical for commensal‐dependent production of IL‐17 and IL‐22 by CD4+ T cells. The Syk‐coupled C‐type lectin receptor Mincle detected mucosal‐resident commensals in the Peyer's patches (PPs), triggered IL‐6 and IL‐23p19 expression, and thereby regulated function of intestinal Th17‐ and IL‐17‐secreting ILCs. Mice deficient in Mincle or with selective depletion of Syk in CD11c+ cells had impaired production of intestinal RegIII&ggr; and IgA and increased systemic translocation of gut microbiota. Consequently, Mincle deficiency led to liver inflammation and deregulated lipid metabolism. Thus, sensing of commensals by Mincle and Syk signaling in CD11c+ cells reinforces intestinal immune barrier and promotes host‐microbiota mutualism, preventing systemic inflammation. Graphical Abstract Figure. No caption available. HighlightsMincle detects mucosal commensals and triggers IL‐6 and IL‐23p19 in PPsLysoDC and CD11b+ DC from PPs prime a microbiota‐ and Mincle‐Syk‐dependent IL‐17Gut Th17 and ILCs producing IL‐17 and IL‐22 require Mincle and Syk in CD11c+ cellsMincle promotes the gut barrier, limiting microbial translocation and liver inflammation &NA; Martínez‐López et al. explore host signaling pathways linking recognition of commensal microbes and Th17 differentiation. They find that the Mincle‐Syk axis in Peyer's patch DCs detects mucosal‐resident bacteria, inducing IL‐6 and IL‐23p19 and stimulating IL‐17 and IL‐22 production by intestinal T cells and ILCs, which control the intestinal immune barrier function.
Annalaura Mastrangelo, Gabriel Á. Martos-Moreno, Francisco J. Rupérez, Julie A. Chowen, Coral Barbas, and Jesús Argente
Elsevier BV
OBJECTIVE
Mutations in the pregnancy-associated plasma protein A2 (PAPP-A2) gene have recently been shown to cause postnatal growth failure in two prepubertal patients from a non-consanguineous Spanish family due to the resulting decrease in IGF1 bioavailability. Although a specific pharmacological treatment of this entity is yet to be established, both children received progressive subcutaneous doses (40 to 120 μg/kg) of rhIGF1 twice daily for 2 years. The improvements in growth, hyperinsulinemia and bone mineral density have been previously reported. The objective of this study was to analyze the changes in metabolism associated with these responses to rhIGF1 treatment.
DESIGN
Herein we present a detailed characterization of the acute and long-term changes in the metabolic profiles of these two siblings with PAPP-A2 deficiency after the initial injections of rhIGF1 and after two years of treatment.
RESULTS
By using a GC-MS-based untargeted metabolomics approach, metabolic fingerprinting yielded the identification of 70 serum metabolites including amino acids (46%), organic acids (21%) carbohydrates (16%), fatty acids (14%), and purine bases (3%). Free fatty acids (FFAs) and amino acids showed the largest changes in the compared metabolic profiles, suggesting that rhIGF1 treatment has the greatest effects on lipid and protein metabolic pathways in the PAPP-A2 deficient subjects.
CONCLUSIONS
The administration of rhIGF1 resulted in changes related to crucial metabolic pathways, including lipid and protein metabolism, and this could be associated with the previously reported treatment-induced improvement in the mild basal hyperinsulinemia.
Paulina Samczuk, Magdalena Luba, Joanna Godzien, Annalaura Mastrangelo, Hady Razak Hady, Jacek Dadan, Coral Barbas, Maria Gorska, Adam Kretowski, and Michal Ciborowski
Elsevier BV
Graphical abstract Figure. No caption available. HighlightsChanges in metabolism after bariatric surgeries (LSG, LRYGB) were evaluated.Metabolic fingerprinting of serum samples with LC–MS and GC–MS was performed.LSG and RYGB evoked partially different changes in serum metabolome.Modulations of gut microbiota related metabolites were observed.Gear mechanism showing molecular changes evoked by bariatric procedures was proposed. ABSTRACT Mechanisms responsible for metabolic gains after bariatric surgery are not entirely clear. The purpose of this study was evaluation of metabolic changes after laparoscopic Roux‐en‐Y gastric bypass or laparoscopic sleeve gastrectomy in semi‐annual follow up. The study participants were selected from obese patients with T2DM who underwent one of the mentioned bariatric procedures. Serum metabolic fingerprinting by use of liquid and gas chromatography with mass spectrometry detection was performed on samples obtained from studied patients before, one, and six months post‐surgery. Performed analyses resulted in 49 significant and identified metabolites. Comparison of the two described procedures has allowed to detect metabolites linked with numerous pathways, processes and diseases. Based on the metabolites detected and pathways affected, we propose a “gear mechanism” showing molecular changes evoked by both bariatric procedures. Critical evaluation of clinical data and obtained metabolomics results enables us to conclude that both procedures are very similar in terms of general clinical outcome, but they strongly differ from each other in molecular mechanisms leading to the final effect. For the first time general metabolic effect of bariatric procedures is described. New hypotheses concerning molecular mechanisms induced by bariatric surgeries and new gut microbiota modulations are presented.
G Á Martos-Moreno, A Mastrangelo, V Barrios, A García, J A Chowen, F J Rupérez, C Barbas, and J Argente
Springer Science and Business Media LLC
Background/Objectives:Insulin resistance (IR) is the cornerstone of the obesity-associated metabolic derangements observed in obese children. Targeted metabolomics was employed to explore the pathophysiological relevance of hyperinsulinemia in childhood obesity in order to identify biomarkers of IR with potential clinical application.Subjects/Methods:One hundred prepubertal obese children (50 girls/50 boys, 50% IR and 50% non-IR in each group), underwent an oral glucose tolerance test for usual carbohydrate and lipid metabolism determinations. Fasting serum leptin, total and high molecular weight-adiponectin and high-sensitivity C-reactive protein (CRP) levels were measured and the metabolites showing significant differences between IR and non-IR groups in a previous metabolomics study were quantified. Enrichment of metabolic pathways (quantitative enrichment analysis) and the correlations between lipid and carbohydrate metabolism parameters, adipokines and serum metabolites were investigated, with their discriminatory capacity being evaluated by receiver operating characteristic (ROC) analysis.Results:Twenty-three metabolite sets were enriched in the serum metabolome of IR obese children (P<0.05, false discovery rate (FDR)<5%). The urea cycle, alanine metabolism and glucose-alanine cycle were the most significantly enriched pathways (PFDR<0.00005). The high correlation between metabolites related to fatty acid oxidation and amino acids (mainly branched chain and aromatic amino acids) pointed to the possible contribution of mitochondrial dysfunction in IR. The degree of body mass index-standard deviation score (BMI-SDS) excess did not correlate with any of the metabolomic components studied. In the ROC analysis, the combination of leptin and alanine showed a high IR discrimination value in the whole cohort (area under curve, AUCALL=0.87), as well as in boys (AUCM=0.84) and girls (AUCF=0.91) when considered separately. However, the specific metabolite/adipokine combinations with highest sensitivity were different between the sexes.Conclusions:Combined sets of metabolic, adipokine and metabolomic parameters can identify pathophysiological relevant IR in a single fasting sample, suggesting a potential application of metabolomic analysis in clinical practice to better identify children at risk without using invasive protocols.
Alessia Ferrarini, Laura Righetti, Ma Paz Martínez, Mariano Fernández-López, Annalaura Mastrangelo, Juan P. Horcajada, Antoni Betbesé, Andrés Esteban, Jordi Ordóñez, Joaquín Gea,et al.
Wiley
Acute respiratory distress syndrome (ARDS) is a serious complication of influenza A (H1N1) virus infection. Its pathogenesis is unknown and biomarkers are lacking. Untargeted metabolomics allows the analysis of the whole metabolome in a biological compartment, identifying patterns associated with specific conditions. We hypothesized that LC‐MS could help identify discriminant metabolites able to define the metabolic alterations occurring in patients with influenza A (H1N1) virus infection that developed ARDS. Serum samples from patients diagnosed with 2009 influenza A (H1N1) virus infection with (n = 25) or without (n = 32) ARDS were obtained on the day of hospital admission and analyzed by LC‐MS/MS. Metabolite identification was determined by MS/MS analysis and analysis of standards. The specificity of the patterns identified was confirmed in patients without 2009 influenza A(H1N1) virus pneumonia (15 without and 17 with ARDS). Twenty‐three candidate biomarkers were found to be significantly different between the two groups, including lysophospholipids and sphingolipids related to inflammation; bile acids, tryptophan metabolites, and thyroxine, related to the metabolism of the gut microflora. Confirmation results demonstrated the specificity of major alterations occurring in ARDS patients with influenza A (H1N1) virus infection.
Annalaura Mastrangelo and Coral Barbas
Springer International Publishing
Chronic diseases, also known as noncommunicable diseases (NCDs), are complex disorders that last for long periods of time and progress slowly. They currently account for the major cause of death worldwide with an alarming increase in rate both in developed and developing countries. In this chapter, the principal metabolomic-based investigations on chronic diseases (cardiovascular diseases, diabetes, and respiratory chronic diseases) and their major risk factors (particularly overweight/obesity) are described by focusing both on metabolites and metabolic pathways. Additional information on the contribution of metabolomics strategies in the ambit of the biomarker discovery for NCDs is also provided by exploring the major prospective studies of the last years (i.e., Framingham Heart Study, EPIC, MONICA, KORA, FINRIK, ECLIPSE). The metabolic signature of diseases, which arises from the metabolomic-based investigation, is therefore depicted in the chapter by pointing out the potential of metabolomics to explain the pathophysiological mechanisms underlying a disease, as well as to propose new therapeutic targets for alternative treatments.
A Mastrangelo, G Á Martos-Moreno, A García, V Barrios, F J Rupérez, J A Chowen, C Barbas, and J Argente
Springer Science and Business Media LLC
Background:Insulin resistance (IR) is usually the first metabolic alteration diagnosed in obese children and the key risk factor for development of comorbidities. The factors determining whether or not IR develops as a result of excess body mass index (BMI) are still not completely understood.Objectives:This study aimed to elucidate the mechanisms underpinning the predisposition toward hyperinsulinemia-related complications in obese children by using a metabolomic strategy that allows a profound interpretation of metabolic profiles potentially affected by IR.Methods:Serum from 60 prepubertal obese children (30 girls/30 boys, 50% IR and 50% non-IR in each group, but with similar BMIs) were analyzed by using liquid chromatography–mass spectrometry, gas chromatography–mass spectrometry and capillary electrophoresis–mass spectrometry following an untargeted metabolomics approach. Validation was then performed on a group of 100 additional children with the same characteristics.Results:When obese children with and without IR were compared, 47 metabolites out of 818 compounds (P<0.05) obtained after data pre-processing were found to be significantly different. Bile acids exhibit the greatest changes (that is, approximately a 90% increase in IR). The majority of metabolites differing between groups were lysophospholipids (15) and amino acids (17), indicating inflammation and central carbon metabolism as the most altered processes in impaired insulin signaling. Multivariate analysis (OPLS-DA models) showed subtle differences between groups that were magnified when females were analyzed alone.Conclusions:Inflammation and central carbon metabolism, together with the contribution of the gut microbiota, are the most altered processes in obese children with impaired insulin signaling in a sex-specific fashion despite their prepubertal status.
Annalaura Mastrangelo, María I. Panadero, Laura M. Pérez, Beatriz G. Gálvez, Antonia García, Coral Barbas, and Francisco J. Rupérez
Portland Press Ltd.
Obesity affects the functional capability of adipose-derived stem cells (ASCs) and their effective use in regenerative medicine through mechanisms that are still poorly understood. In the present study we used a multiplatform [LC/MS, GC/MS and capillary electrophoresis/MS (CE/MS)], metabolomics, untargeted approach to investigate the metabolic alteration underlying the inequalities observed in obesity-derived ASCs. The metabolic fingerprint (metabolites within the cells) and footprint (metabolites secreted in the culture medium), from obesity- and non-obesity-derived ASCs of humans or mice, were characterized to provide valuable information. Metabolites associated with glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway and the polyol pathway were increased in the footprint of obesity-derived human ASCs, indicating alterations in carbohydrate metabolism, whereas, from the murine model, deep differences in lipid and amino acid catabolism were highlighted. Therefore, new insights on the ASCs’ metabolome were provided that enhance our understanding of the processes underlying ASCs’ stemness capacity and its relationship with obesity, in different cell models.
Laura M. Pérez, Aurora Bernal, Beatriz de Lucas, Nuria San Martin, Annalaura Mastrangelo, Antonia García, Coral Barbas, and Beatriz G. Gálvez
Public Library of Science (PLoS)
Adipose stem cells (ASCs) are an appealing source of cells for therapeutic intervention; however, the environment from which ASCs are isolated may impact their usefulness. Using a range of functional assays, we have evaluated whether ASCs isolated from an obese environment are comparable to cells from non-obese adipose tissue. Results showed that ASCs isolated from obese tissue have a reduced proliferative ability and a loss of viability together with changes in telomerase activity and DNA telomere length, suggesting a decreased self-renewal capacity. Metabolic analysis demonstrated that mitochondrial content and function was impaired in obese-derived ASCs resulting in changes in favored oxidative substrates. These findings highlight the impact of obesity on adult stem properties. Hence, caution should be exercised when considering the source of ASCs for cellular therapies since their therapeutic potential may be impaired.
Annalaura Mastrangelo, Alessia Ferrarini, Fernanda Rey-Stolle, Antonia García, and Coral Barbas
Elsevier BV
This tutorial provides a comprehensive description of the GC-MS-based untargeted metabolomics workflow including: ethical approval requirement, sample collection and storage, equipment maintenance and setup, sample treatment, monitoring of analytical variability, data pre-processing including deconvolution by free software such as AMDIS, data processing, statistical analysis and validation, detection of outliers and biological interpretation of the results. For each stage tricks will be suggested, pitfalls will be highlighted and advice will be provided on how to get the best from this methodology and technique. In addition, a step-by-step procedure and an example of our in-house library have been included in the supplementary material to lead the user through the concepts described herein. As a case study, an interesting example from one of our experiments at CEMBIO Research Centre is described, presenting an example of the use of this ready-to use protocol for identification of a metabolite that was not previously included in Fiehn commercial target library.
Alicia Navarrete, Emily G. Armitage, Monica Musteanu, Antonia García, Annalaura Mastrangelo, Renata Bujak, Pedro P. López-Casas, Manuel Hidalgo, and Coral Barbas
Wiley
In a personalized treatment designed for a patient with pancreatic cancer resistant to other treatments, the success of Mitomycin C (MMC) has been highlighted. This was revealed in a murine xenograft tumor model encompassing pancreatic adenocarcinoma cells extracted from the patient. The patient was found to exhibit a biallelic inactivation of the PALB2 gene, involved in DNA repair in addition to another mutation in the TSC2 gene that induces susceptibility of the tumor to therapeutic targets of the PI3K‐mTOR pathway. The aim of the study was to apply metabolomics to elucidate the modes of action of each therapy, suggesting why MMC was so successful in this patient and why it could be a more popular choice in future pancreatic cancer treatment. The effectiveness of MMC compared to rapamycin (RM), another relevant therapeutic agent has been evaluated through liquid‐ and gas‐chromatography mass spectrometry‐based metabolomic analyses of the xenograft tumors. The relative concentrations of many metabolites in the xenograft tumors were found to be increased by MMC relative to other treatments (RM and a combination of both), including a number that are involved in central carbon metabolism (CCM). Metabolic fingerprinting revealed statistically significantly altered pathways including, but not restricted to, the pentose phosphate pathway, glycolysis, TCA cycle, purine metabolism, fatty acid biosynthesis, in addition to many significant lipid and amino acid alterations. Given the genetic background of the patient, it was expected that the combined therapy would be most effective; however, the most effective was MMC alone. It is proposed that the effectiveness of MMC is owed to its direct effect on CCM, a vital region of tumor metabolism.
Annalaura Mastrangelo, Emily Armitage, Antonia García, and Coral Barbas
Bentham Science Publishers Ltd.
Studying the effects of drugs on the metabolome constitutes a huge part of the metabolomics discipline. Whether the approach is associated with drug discovery (altered pathways due to the disease that provide future targets and information into the mechanism of action or resistance, etc.) or pharmacometabolomics (studying the outcome of treatment), there have been many aspiring published articles in this area. With specific experimental design, including fingerprinting analysis with different analytical platforms in a non-targeted way, the approach is advancing towards the discovery of markers for the implication of personalised medicine, while also providing information that could help to improve the efficacy and reduce the side effects associated with a treatment. In this review, the evolution of pharmacometabolomics from other areas of drug efficacy metabolomics studies is explored.