Metabolomic study of plasma of patients with abdominal aortic aneurysm

Unveiling the metabolic landscape of pulmonary hypertension: insights from metabolomics

Pulmonary hypertension (PH) is regarded as cardiovascular disease with an extremely poor prognosis, primarily due to irreversible vascular remodeling. Despite decades of research progress, the absence of definitive curative therapies remains a critical challenge, leading to high mortality rates. Recent studies have shown that serious metabolic disorders generally exist in PH animal models and patients of PH, which may be the cause or results of the disease. It is imperative for future research to identify critical biomarkers of metabolic dysfunction in PH pathophysiology and to uncover metabolic targets that could enhance diagnostic and therapeutic strategies. Metabolomics offers a powerful tool for the comprehensive qualitative and quantitative analysis of metabolites within specific organisms or cells. On the basis of the findings of the metabolomics research on PH, this review summarizes the latest research progress on metabolic pathways involved in processes such as amino acid metabolism, carbohydrate metabolism, lipid metabolism, and nucleotide metabolism in the context of PH.

Multi-omics in thoracic aortic aneurysm: the complex road to the simplification

BACKGROUND

Thoracic aortic aneurysm (TAA) is a serious condition that affects the aorta, characterized by the dilation of its first segment. The causes of TAA (e.g., age, hypertension, genetic syndromes) are heterogeneous and contribute to the weakening of the aortic wall. This complexity makes treating this life-threatening aortopathy challenging, as there are currently no etiological therapy available, and pharmacological strategies, aimed at avoiding surgical aortic replacement, are merely palliative. Recent studies on novel therapies for TAA have focused on identifying biological targets and etiological mechanisms of the disease by using advanced -omics techniques, including epigenomics, transcriptomics, proteomics, and metabolomics approaches.

METHODS

This review presents the latest findings from -omics approaches and underscores the importance of integrating multi-omics data to gain more comprehensive understanding of TAA.

RESULTS

Literature suggests that the alterations in TAA mediators frequently involve members of pro-fibrotic process (i.e., TGF-β signaling pathways) or proteins associated with cell/extracellular structures (e.g., aggrecans). Further analyses often reported the importance in TAA of processes as inflammation (PCR, CD3, leukotriene compounds), oxidative stress (chromatin OXPHOS, fatty acids), mitochondrial respiration and glycolysis/gluconeogenesis (e.g., PPARs and HIF1a). Of note, more recent metabolomics studies added novel molecular markers to the list of TAA-specific detrimental mediators (proteoglycans).

CONCLUSION

It is increasingly clear that integrating data from different -omics branches, along with clinical data, is essential as well as complicated both to reveal hidden relevant information and to address complex diseases such as TAA. Importantly, recent progresses in metabolomics highlighted novel potential and unprecedented marks in TAA diagnosis and therapy.

Gut Microbiota and Metabolite Changes in Patients With Ulcerative Colitis and Clostridioides difficile Infection

Background

Patients with ulcerative colitis (UC) are at an increased risk of developing Clostridioides difficile infection (CDI), which in turn leads to poor outcomes. The gut microbial structure and metabolites in patients with UC and CDI have been scarcely studied. We hypothesized that CDI changes the gut microbiota and metabolites of patients with UC.

Materials and Methods

This study included 89 patients: 30 healthy controls (HC group), 29 with UC alone (UCN group), and 30 with UC and CDI (UCP group). None of the participants has been exposed to antibiotic treatments during the 3 months before stool collection. Stool samples were analyzed using 16S rRNA gene sequencing of the V3–V4 region and gas chromatography tandem time-of-flight mass spectrometry.

Results

The UCN group displayed lower diversity and richness in gut microbiota and a higher relative abundance of the phylum Proteobacteria than the HC group. There were no significant differences between the UCN and UCP groups in the α-diversity indices. The UCP group contained a higher relative abundance of the genera Clostridium sensu stricto, Clostridium XI, Aggregatibacter, and Haemophilus, and a lower relative abundance of genera Clostridium XIVb and Citrobacter than the UCN group. In the UCP group, the increased metabolites included putrescine, maltose, 4-hydroxybenzoic acid, 4-hydroxybutyrate, and aminomalonic acid. Spearman’s correlation analysis revealed that these increased metabolites negatively correlated with Clostridium XlVb and positively correlated with the four enriched genera. However, the correlations between hemoglobin and metabolites were contrary to the correlations between erythrocyte sedimentation rate and high-sensitivity C-reactive protein and metabolites.

Conclusion

Our study identified 11 differential genera and 16 perturbed metabolites in patients with UC and CDI compared to those with UC alone. These findings may guide the design of research on potential mechanisms and specific treatments for CDI in patients with UC.

The Echocardiographic Parameters of Systolic Function Are Associated with Specific Metabolomic Fingerprints in Obstructive and Non-Obstructive Hypertrophic Cardiomyopathy

The purpose of this study was to assess whether metabolomics, associated with echocardiography, was able to highlight pathophysiological differences between obstructive (OHCM) or non-obstructive (NOHCM) hypertrophic cardiomyopathy. Thirty-one HCM patients underwent standard and advanced echocardiography; a plasma sample was collected for metabolomic analysis. Results. Patients with OHCM compared with subjects with NOHCM had higher values of 2DLVEF (66.5 ± 3.3% vs. 60.6 ± 1.8%, p < 0.01), S wave (7.6 ± 1.1 vs. 6.3 ± 0.7 cm/s, p < 0.01) and 3D global longitudinal strain (17.2 ± 4.2%, vs. 13.4 ± 1.3%, p < 0.05). A 2-group PLS-Discriminant Analysis was performed to verify whether the two HCM groups differed also based on the metabolic fingerprint. A clear clustering was shown (ANOVA p = 0.014). The most discriminating metabolites resulted as follows: in the NOHCM Group, there were higher levels of threitol, aminomalonic acid, and sucrose, while the OHCM Group presented higher levels of amino acids, in particular those branched chains, of intermediates of glycolysis (lactate) and the Krebs cycle (fumarate, succinate, citrate), of fatty acids (arachidonic acid, palmitoleic acid), of ketone bodies (2-OH-butyrate). Our data point out a different systolic function related to a specific metabolic activity in the two HCM phenotypic forms, with specific metabolites associated with better contractility in OHCM.

Metabolomic Profile of Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is characterized by structural deterioration of the aortic wall, leading to aortic dilation and rupture. The aim was to compare 183 low molecular weight metabolites in AAA patients and aorta-healthy controls and to explore if low molecular weight metabolites are linked to AAA growth. Blood samples were collected from male AAA patients with fast (mean 3.3 mm/year; range 1.3-9.4 mm/year; n = 39) and slow growth (0.2 mm/year; range -2.6-1.1 mm/year; n = 40), and from controls with non-aneurysmal aortas (n = 79). Targeted analysis of 183 metabolites in plasma was performed with AbsoluteIDQ p180 kit. The samples were measured on a QTRAP 4500 coupled to an Agilent 1260 series HPLC. The levels of only four amino acids (histidine, asparagine, leucine, isoleucine) and four phosphatidylcholines (PC.ae.C34.3, PC.aa.C34.2, PC.ae.C38.0, lysoPC.a.C18.2) were found to be significantly lower (p < 0.05) after adjustment for confounders among the AAA patients compared with the controls. There were no differences in the metabolites distinguishing the AAA patients with slow or fast growth from the controls, or distinguishing the patients with slow growth from those with fast growth. The current study describes novel significant alterations in amino acids and phosphatidylcholines metabolism associated with AAA occurrence, but no associations were found with AAA growth rate.

Metabolomic Profiling for Diagnosis and Prognostication in Surgery: A Scoping Review

OBJECTIVE

This review assimilates and critically evaluates available literature regarding the use of metabolomic profiling in surgical decision-making.

BACKGROUND

Metabolomic profiling is performed by nuclear magnetic resonance spectroscopy or mass spectrometry of biofluids and tissues to quantify biomarkers (ie, sugars, amino acids, and lipids), producing diagnostic and prognostic information that has been applied among patients with cardiovascular disease, inflammatory bowel disease, cancer, and solid organ transplants.

METHODS

PubMed was searched from 1995 to 2019 to identify studies investigating metabolomic profiling of surgical patients. Articles were included and assimilated into relevant categories per PRISMA-ScR guidelines. Results were summarized with descriptive analytical methods.

RESULTS

Forty-seven studies were included, most of which were retrospective studies with small sample sizes using various combinations of analytic techniques and types of biofluids and tissues. Results suggest that metabolomic profiling has the potential to effectively screen for surgical diseases, suggest diagnoses, and predict outcomes such as postoperative complications and disease recurrence. Major barriers to clinical adoption include a lack of high-level evidence from prospective studies, heterogeneity in study design regarding tissue and biofluid procurement and analytical methods, and the absence of large, multicenter metabolome databases to facilitate systematic investigation of the efficacy, reproducibility, and generalizability of metabolomic profiling diagnoses and prognoses.

CONCLUSIONS

Metabolomic profiling research would benefit from standardization of study design and analytic approaches. As technologies improve and knowledge garnered from research accumulates, metabolomic profiling has the potential to provide personalized diagnostic and prognostic information to support surgical decision-making from preoperative to postdischarge phases of care.

Plasma Metabolomics Analysis Identifies Abnormal Energy, Lipid, and Amino Acid Metabolism in Abdominal Aortic Aneurysms

Background

Abdominal aortic aneurysm (AAA) is a complicated aortic dilatation disease. Metabolomics is an emerging system biology method. This aim of this study was to identify abnormal metabolites and metabolic pathways associated with AAA and to discover potential biomarkers that could affect the size of AAAs.

Material/Methods

An untargeted metabolomic method was used to analyze the plasma metabolic profiles of 39 patients with AAAs and 30 controls. Multivariate analysis methods were used to perform differential metabolite screening and metabolic pathway analysis. Cluster analysis and univariate analysis were performed to identify potential metabolites that could affect the size of an AAA.

Results

Forty-five different metabolites were identified with an orthogonal projection to latent squares-discriminant analysis model and the differences between them in the patients with AAAs and the control group were compared. A variable importance in the projection score >1 and P<0.05 were considered statistically significant. In patients with AAAs, the pathways involving metabolism of alanine, aspartate, glutamate, D-glutamine, D-glutamic acid, arginine, and proline; tricarboxylic acid cycling; and biosynthesis of arginine are abnormal. The progression of an AAA may be related to 13 metabolites: citric acid, 2-oxoglutarate, succinic acid, coenzyme Q1, pyruvic acid, sphingosine-1-phosphate, platelet-activating factor, LysoPC (16: 00), lysophosphatidylcholine (18: 2(9Z,12Z)/0: 0), arginine, D-aspartic acid, and L- and D-glutamine.

Conclusions

An untargeted metabolomic analysis using ultraperformance liquid chromatography-tandem mass spectrometry identified metabolites that indicate disordered metabolism of energy, lipids, and amino acids in AAAs.

Functional role of endothelial CXCL16/CXCR6-platelet-leucocyte axis in angiotensin II-associated metabolic disorders

Aims

Angiotensin-II (Ang-II) is the main effector peptide of the renin-angiotensin system (RAS) and promotes leucocyte adhesion to the stimulated endothelium. Because RAS activation and Ang-II signalling are implicated in metabolic syndrome (MS) and abdominal aortic aneurysm (AAA), we investigated the effect of Ang-II on CXCL16 arterial expression, the underlying mechanisms, and the functional role of the CXCL16/CXCR6 axis in these cardiometabolic disorders.

Methods and results

Results from in vitro chamber assays revealed that CXCL16 neutralization significantly inhibited mononuclear leucocyte adhesion to arterial but not to venous endothelial cells. Flow cytometry and immunofluorescence studies confirmed that Ang-II induced enhanced endothelial CXCL16 expression, which was dependent on Nox5 up-regulation and subsequent RhoA/p38-MAPK/NFκB activation. Flow cytometry analysis further showed that MS patients had higher levels of platelet activation and a higher percentage of circulating CXCR6-expressing platelets, CXCR6-expressing-platelet-bound neutrophils, monocytes, and CD8+ lymphocytes than age-matched controls, leading to enhanced CXCR6/CXCL16-dependent adhesion to the dysfunctional (Ang-II- and TNFα-stimulated) arterial endothelium. Ang-II-challenged apolipoprotein E-deficient (apoE-/-) mice had a higher incidence of AAA, macrophage, CD3+, and CXCR6+ cell infiltration and neovascularization than unchallenged animals, which was accompanied by greater CCL2, CXCL16, and VEGF mRNA expression within the lesion together with elevated levels of circulating soluble CXCL16. Significant reductions in these parameters were found in animals co-treated with the AT1 receptor antagonist losartan or in apoE-/- mice lacking functional CXCR6 receptor (CXCR6GFP/GFP).

Conclusion

CXCR6 expression on platelet-bound monocytes and CD8+ lymphocytes may constitute a new membrane-associated biomarker for adverse cardiovascular events. Moreover, pharmacological modulation of this axis may positively affect cardiovascular outcome in metabolic disorders linked to Ang-II.

Evaluating the performance of sample preparation methods for ultra-performance liquid chromatography/mass spectrometry based serum metabonomics

RATIONALE

Metabonomics investigating perturbation to endogenous metabolism in response to external stimuli is emerging as a powerful tool for clinical diagnosis as well as in many other areas. The ability to retrieve reliable and reproducible information from complex biological fluids such as serum is crucial for its further applications.

METHODS

In this study, the performance of the commonly used sample preparation methods for ultra-performance liquid chromatography/mass spectrometry (UPLC/MS)-based metabonomics was investigated. Specifically, we compared the extraction efficiencies, the method reproducibility, and the ability to identify potential biomarkers using solvent-based protein precipitation and solid-phase extraction (SPE) for serum metabonomic studies. Differences between extraction methods were explored using principal component analysis (PCA) and orthogonal partial least squares-discrimination analysis (OPLS-DA).

RESULTS

Among the sample preparation methods tested, solvent-based protein precipitation using methanol has demonstrated the best analytical precision and extraction efficiency. Furthermore, this study revealed, for the first time, gender-specific differences in levels of two lysophosphatidylcholines (lysoPC 18:0 and lysoPC 18:1) in rat serum samples.

CONCLUSIONS

The performance of sample preparation methods for UPLC/MS-based serum metabonomics was evaluated systematically. Results showed sample preparation by solvent precipitation using methanol provided the best analytical precision and extraction efficiency for UPLC/MS-based serum metabonomics.

Obesity leads to distinct metabolomic signatures in follicular fluid of women undergoing in vitro fertilization

Although obesity negatively influences the metabolic homeostasis of cells within a broad range of tissues, its impact on oocyte metabolism is not fully understood. Prior evidence suggests that obesity increases expression of oocyte genes associated with inflammation, oxidative stress, and lipid metabolism; however, the metabolic impact of these genetic differences is not known. To address this gap, we conducted an exploratory assessment of the follicular fluid (FF) metabolome in eight overweight/obese (OW) and nine normal-weight (NW) women undergoing in vitro fertilization. FF and serum were collected and analyzed by untargeted metabolomics using gas chromatography-quadrupole time-of-flight mass spectrometry and charged-surface hybrid column-electrospray ionization quadrupole time-of-flight tandem mass spectrometry. Untargeted metabolomics identified obesity-associated changes in FF metabolites related to oxidative stress/antioxidant capacity, xenometabolism/amino acid biosynthesis, and lipid metabolism. Discriminant FF metabolites included elevated uric acid, isothreonic acid, one unknown primary metabolite, and six unknown complex lipids in OW compared with NW women. Conversely, 2-ketoglucose dimethylacetal, aminomalonate, two unknown primary metabolites, and two unknown complex lipids were decreased in FF of OW relative to NW women. Indole-3-propionic acid (IPA), a bacteria-derived metabolite, was also decreased in both FF and serum of OW women ( P < 0.05). The significant correlation between antioxidant IPA in serum and FF ( R = 0.95, P < 0.0001) suggests a potential serum biomarker of FF antioxidant status or reflection of the gut metabolism interaction with the follicle. These results suggest that obesity has important consequences for the follicular environment during the preconception period, a window of time that may be important for lifestyle interventions to ameliorate obesity-associated risk factors.

Application of Metabolic Profiling to Abdominal Aortic Aneurysm Research

Abdominal aortic aneurysm (AAA) is a complex disease posing diagnostic and therapeutic challenges. Metabonomics may aid in the diagnosis of AAA, determination of individualized risk, discovery of therapeutic targets, and improve understanding of pathogenesis. A systematic review of the diversity and outcomes of existing AAA metabonomic research has been performed. Original research studies applying metabonomics to human aneurysmal disease are included. Seven relevant articles were identified: four studies were based on plasma/serum metabolite profiling, and three studies examined aneurysmal tissue. Aminomalonic acid, guanidinosuccinic acid, and glycerol emerge as potential plasma biomarkers of large aneurysm. Lipid profiling improves predictive models of aneurysm presence. Patterns of metabolite variation associated with AAA relate to carbohydrate and lipid metabolism. Perioperative perturbations in metabolites suggest differential systemic inflammatory responses to surgery, generating hypotheses for adjunctive perioperative therapy. Significant limitations include small study sizes, lack of correction for multiple testing false discovery rates, and single time-point sampling. Metabolic profiling carries the potential to identify biomarkers of AAA and elucidate pathways underlying aneurysmal disease. Statistically and methodologically robust studies are required for validation, addressing the hiatus in understanding mechanisms of aneurysm growth and developing effective treatment strategies.

Metabolomic profiling of ascending thoracic aortic aneurysms and dissections - Implications for pathophysiology and biomarker discovery

Objective

Our basic understanding of ascending thoracic aortic aneurysm (ATAA) pathogenesis is still very limited, hampering early diagnosis, risk prediction, and development of treatment options. “Omics”-technologies, ideal to reveal tissue alterations from the normal physiological state due to disease have hardly been applied in the field. Using a metabolomic approach, with this study the authors seek to define tissue differences between controls and various forms of ATAAs.

Methods

Using a targeted FIA-MS/MS metabolomics approach, we analysed and compared the metabolic profiles of ascending thoracic aortic wall tissue of age-matched controls (n = 8), bicuspid aortic valve-associated aneurysms (BAV-A; n = 9), tricuspid aortic valve-associated aneurysms (TAV-A; n = 14), and tricuspid aortic valve-associated aortic dissections (TAV-Diss; n = 6).

Results

With sphingomyelin (SM) (OH) C22:2, SM C18:1, SM C22:1, and SM C24:1 only 4 out of 92 detectable metabolites differed significantly between controls and BAV-A samples. Between controls and TAV-Diss samples only phosphatidylcholine (PC) ae C32:1 differed. Importantly, our analyses revealed a general increase in the amount of total sphingomyelin levels in BAV-A and TAV-Diss samples compared to controls.

Conclusions

Significantly increased levels of sphingomyelins in BAV-A and TAV-Diss samples compared to controls may argue for a repression of sphingomyelinase activity and the sphingomyelinase-ceramide pathway, which may result in an inhibition of tissue regeneration; a potential basis for disease initiation and progression.

New Biochemical Insights into the Mechanisms of Pulmonary Arterial Hypertension in Humans

Diagnosis of pulmonary arterial hypertension (PAH) is difficult due to the lack of specific clinical symptoms and biomarkers, especially at early stages. We compared plasma metabolic fingerprints of PAH patients (n = 20) with matched healthy volunteers (n = 20) using, for the first time, untargeted multiplatform metabolomics approach consisting of high-performance liquid and gas chromatography coupled with mass spectrometry. Multivariate statistical analyses were performed to select metabolites that contribute most to groups’ classification (21 from liquid in both ionization modes and 9 from gas chromatography-mass spectrometry). We found metabolites related to energy imbalance, such as glycolysis-derived metabolites, as well as metabolites involved in fatty acid, lipid and amino acid metabolism. We observed statistically significant changes in threitol and aminomalonic acid in PAH patients, which could provide new biochemical insights into the pathogenesis of the disease. The results were externally validated on independent case and control cohorts, confirming up to 16 metabolites as statistically significant in the validation study. Multiplatform metabolomics, followed by multivariate chemometric data analysis has a huge potential for explaining pathogenesis of PAH and for searching potential and new more specific and less invasive markers of the disease.

New insight on obesity and adipose-derived stem cells using comprehensive metabolomics

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.

Molecular phenotyping of a UK population: defining the human serum metabolome

Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).

Metabolomics for laboratory diagnostics

Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice.

Identification of biomarkers in the hair of dogs: new diagnostic possibilities in the study and control of visceral leishmaniasis

Visceral leishmaniasis (VL) is a zoonosis whose etiologic agent in the Americas is Leishmania infantum, and dogs are the main host. Research and innovation in diagnostic techniques are essential to improve the surveillance and control of VL in endemic areas. The present study investigates the profile of the volatile organic compounds (VOCs) emitted by healthy dogs and by dogs infected by L. infantum to detect variations in the VOCs that may be used as biomarkers in the diagnosis of VL. In total, 36 dogs were selected from an endemic area and divided into three groups: G1, not infected with L. infantum; G2, infected without clinical signs of VL; and G3, infected with clinical signs of VL. To analyze the profiles of the VOCs emitted by dogs from the three groups, solid-phase microextraction (SPME) combined with gas chromatography-mass spectrometry (GC-MS) was used. Variations were observed between the profiles of the VOCs emitted in the three groups studied, and they also differentiated infected animals with or without clinical signs. Six VOCs were identified as potential biomarkers of infection, with significant variations between healthy dogs (G1) and infected dogs (G2 + G3). The detection of variations between groups G2 and G3 suggested that the profiles of some VOCs may be related to the type of immune response and the parasite load of the infected dogs. This study demonstrated the possibility of analysis of VOCs as biomarkers of VL in diagnostic, clinical, and epidemiological work.

New Insights Into Aortic Diseases: A Report From the Third International Meeting on Aortic Diseases (IMAD3)

The current state of research and treatment on aortic diseases was discussed in the "3rd International Meeting on Aortic Diseases" (IMAD3) held on October 4-6, 2012, in Liège, Belgium. The 3-day meeting covered a wide range of topics related to thoracic aortic aneurysms and dissections, abdominal aortic aneurysms, and valvular diseases. It brought together clinicians and basic scientists and provided an excellent opportunity to discuss future collaborative research projects for genetic, genomics, and biomarker studies, as well as clinical trials. Although great progress has been made in the past few years, there are still a large number of unsolved questions about aortic diseases. Obtaining answers to the key questions will require innovative, interdisciplinary approaches that integrate information from epidemiological, genetic, molecular biology, and bioengineering studies on humans and animal models. It is more evident than ever that multicenter collaborations are needed to accomplish these goals.

Discovery of safety biomarkers for realgar in rat urine using UFLC-IT-TOF/MS and 1H NMR based metabolomics

As an arsenical, realgar (As4S4) is known as a poison and paradoxically as a therapeutic agent. However, a complete understanding of the precise biochemical alterations accompanying the toxicity and therapy effects of realgar is lacking. Using a combined ultrafast liquid chromatography (UFLC) coupled with ion trap time-of-flight mass spectrometry (IT-TOF/MS) and (1)H NMR spectroscopy based metabolomics approach, we were able to delineate significantly altered metabolites in the urine samples of realgar-treated rats. The platform stability of the liquid chromatography LC/MS and NMR techniques was systematically investigated, and the data processing method was carefully optimized. Our results indicate significant perturbations in amino acid metabolism, citric acid cycle, choline metabolism, and porphyrin metabolism. Thirty-six metabolites were proposed as potential safety biomarkers related to disturbances caused by realgar, and glycine and serine are expected to serve as the central contacts in the metabolic pathways related to realgar-induced disturbance. The LC/MS and NMR based metabolomics approach established provided a systematic and holistic view of the biochemical effects of realgar on rats, and might be employed to investigate other drugs or xenobiotics in the future.