Metabolites Secreted by Human Atherothrombotic Aneurysms Revealed through a Metabolomic Approach

Early hyperlipidemia triggers metabolomic reprogramming with increased SAH, increased acetyl-CoA-cholesterol synthesis, and decreased glycolysis

To identify metabolomic reprogramming in early hyperlipidemia, unbiased metabolome was screened in four tissues from ApoE-/- mice fed with high fat diet (HFD) for 3 weeks. 30, 122, 67, and 97 metabolites in the aorta, heart, liver, and plasma, respectively, were upregulated. 9 upregulated metabolites were uremic toxins, and 13 metabolites, including palmitate, promoted a trained immunity with increased syntheses of acetyl-CoA and cholesterol, increased S-adenosylhomocysteine (SAH) and hypomethylation and decreased glycolysis. The cross-omics analysis found upregulation of 11 metabolite synthetases in ApoE‾/‾ aorta, which promote ROS, cholesterol biosynthesis, and inflammation. Statistical correlation of 12 upregulated metabolites with 37 gene upregulations in ApoE‾/‾ aorta indicated 9 upregulated new metabolites to be proatherogenic. Antioxidant transcription factor NRF2-/- transcriptome analysis indicated that NRF2 suppresses trained immunity-metabolomic reprogramming. Our results have provided novel insights on metabolomic reprogramming in multiple tissues in early hyperlipidemia oriented toward three co-existed new types of trained immunity.

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.

Plasma Lipidomics Analysis Reveals the Potential Role of Lysophosphatidylcholines in Abdominal Aortic Aneurysm Progression and Formation

Abdominal aortic aneurysm (AAA) is hallmarked by irreversible dilation of the infrarenal aorta. Lipid deposition in the aortic wall and the potential importance of a lipid disorder in AAA etiology highlight the need to explore lipid variation during AAA development. This study aimed to systematically characterize the lipidomics associated with AAA size and progression. Plasma lipids from 106 subjects (36 non-AAA controls and 70 AAA patients) were comprehensively analyzed using untargeted lipidomics. An AAA animal model was established by embedding angiotensin-II pump in ApoE^-/- mice for four weeks and blood was collected at 0, 2 and 4 weeks for lipidomic analysis. Using a false-discovery rate (FDR) < 0.05, a group of lysophosphatidylcholines (lysoPCs) were specifically decreased in AAA patients and mice. LysoPCs were principally lower in the AAA patients with larger diameter (diameter > 50 mm) than those with a smaller size (30 mm < diameter < 50 mm), and levels of lysoPCs were also found to be decreased with modelling time and aneurysm formation in AAA mice. Correlation matrices between lipids and clinical characteristics identified that the positive correlation between lysoPCs and HDL-c was reduced and negative correlations between lysoPCs and CAD rate, lysoPCs and hsCRP were converted to positive correlations in AAA compared to control. Weakened positive correlations between plasma lysoPCs and circulating HDL-c in AAA suggested that HDL-lysoPCs may elicit instinctive physiological effects in AAA. This study provides evidence that reduced lysoPCs essentially underlie the pathogenesis of AAA and that lysoPCs are promising biomarkers for AAA development.

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.

Untargeted Metabolomics Provides Insight into the Mechanisms Underlying Resistant Hypertension

BACKGROUND

Resistant hypertension (RH) affects about 15-20% of treated hypertensive patients worldwide. RH increases the risk of cardiovascular events such as myocardial infarction and stroke by 50%. The pathological mechanisms underlying resistance to treatment are still poorly understood.

OBJECTIVE

The main goal of this pilot study was to determine and compare plasma metabolomic profiles in resistant and non-resistant hypertensive patients.

METHODS

We applied untargeted metabolomic profiling in plasma samples collected from 69 subjects with RH and 81 subjects with controlled hypertension. To confirm patients' compliance to antihypertensive treatment, levels of selected drugs and their metabolites were determined in plasma samples with the LC-ESI-TOF/MS technique.

RESULTS

The results showed no statistically significant differences in the administration of antihypertensive drug in the compared groups. We identified 19 up-regulated and 13 downregulated metabolites in the RH.

CONCLUSION

The metabolites altered in RH are linked to oxidative stress and inflammation, endothelium dysfunction, vasoconstriction and cell proliferation. Our results may generate new hypothesis about RH development and progression.

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.

Metabolomics through the lens of precision cardiovascular medicine

Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.

LC-MS-Based Metabolic Fingerprinting of Aqueous Humor

Aqueous humor (AH) is a transparent fluid which fills the anterior and posterior chambers of the eye. It supplies nutrients and removes metabolic waste from avascular tissues in the eye. Proper homeostasis of AH is required to maintain adequate intraocular pressure as well as optical and refractive properties of the eye. Application of metabolomics to study human AH may improve knowledge about the molecular mechanisms of eye diseases. Until now, global analysis of metabolites in AH has been mainly performed using NMR. Among the analytical platforms used in metabolomics, LC-MS allows for the highest metabolome coverage. The aim of this study was to develop a method for extraction and analysis of AH metabolites by LC-QTOF-MS. Different protocols for AH preparation were tested. The best results were obtained when one volume of AH was mixed with one volume of methanol : ethanol (1 : 1). In the final method, 2 µL of extracted sample was analyzed by LC-QTOF-MS. The method allowed for reproducible measurement of over 1000 metabolic features. Almost 250 metabolites were identified in AH and assigned to 47 metabolic pathways. This method is suitable to study the potential role of amino acids, lipids, oxidative stress, or microbial metabolites in development of ocular diseases.

Metabolomics - A wide-open door to personalized treatment in chronic heart failure?

Heart failure (HF) is a complex syndrome representing a final stage of various cardiovascular diseases. Despite significant improvement in the diagnosis and treatment (e.g. ACE-inhibitors, β-blockers, aldosterone antagonists, cardiac resynchronization therapy) of the disease, prognosis of optimally treated patients remains very serious and HF mortality is still unacceptably high. Therefore there is a strong need for further exploration of novel analytical methods, predictive and prognostic biomarkers and more personalized treatment. The metabolism of the failing heart being significantly impaired from its baseline state may be a future target not only for biomarker discovery but also for the pharmacologic intervention. However, an assessment of a particular, isolated metabolite or protein cannot be fully informative and makes a correct interpretation difficult. On the other hand, metabolites profile analysis may greatly assist investigator in an interpretation of the altered pathway dynamics, especially when combined with other lines of evidence (e.g. metabolites from the same pathway, transcriptomics, proteomics). Despite many prior studies on metabolism, the knowledge of peripheral and cardiac pathophysiological mechanisms responsible for the metabolic imbalance and progression of the disease is still insufficient. Metabolomics enabling comprehensive characterization of low molecular weight metabolites (e.g. lipids, sugars, organic acids, amino acids) that reflects the complete metabolic phenotype seems to be the key for further potential improvement in HF treatment (diet-based or biochemical-based). Will this -omics technique one day open a door to easy patients identification before they have a heart failure onset or its decompensation?

Proteomics and metabolomics for in situ monitoring of wound healing

Wound healing of soft tissue and bone defects is a complex process in which cellular differentiation and adaption are regulated by internal and external factors, among them are many different proteins. In contrast to insights into the significance of various single proteins based on model systems, the knowledge about the processes at the actual site of wound healing is still limited. This is caused by a general lack of methods that allow sampling of extracellular factors, metabolites, and proteins in situ. Sampling of wound fluids in combination with proteomics and metabolomics is one of the promising approaches to gain comprehensive and time resolved data on effector molecules. Here, we describe an approach to sample metabolites by microdialysis and to extract proteins simultaneously by adsorption. With this approach it is possible (i) to collect, enrich, and purify proteins for a comprehensive proteome analysis; (ii) to detect more than 600 proteins in different defects including more than 100 secreted proteins, of which many proteins have previously been demonstrated to have diagnostic or predictive power for the wound healing state; and (iii) to combine continuous sampling of cytokines and metabolites and discontinuous sampling of larger proteins to gain complementary information of the same defect.

Comparison of the serum lipidome in patients with abdominal aortic aneurysm and peripheral artery disease

BACKGROUND

Currently, the relationship between circulating lipids and abdominal aortic aneurysm (AAA) is unclear. We conducted a lipidomic analysis to identify serum lipids associated with AAA presence. Secondary analyses assessed the ability of models incorporating lipidomic features to improve stratification of patient groups with and without AAA beyond traditional risk factors.

METHODS AND RESULTS

Serum lipids were profiled via liquid chromatography tandem mass spectrometry analysis of serum from 161 patients with AAA and 168 controls with peripheral artery disease. Binary logistic regression was used to identify AAA-associated lipids. Classification models were created based on a combination of (1) traditional risk factors only or (2) lipidomic features and traditional risk factors. Model performance was assessed using receiver operator characteristic curves. Three diacylglycerols and 7 triacylglycerols were associated with AAA. Combining lipidomic features with traditional risk factors significantly improved stratification of AAA and peripheral artery disease groups when compared with traditional risk factors alone (mean area under the receiver operator characteristic curve [95% confidence interval], 0.760 [0.756-0.763] and 0.719 [0.716-0.723], respectively; P<0.05).

CONCLUSIONS

A group of linoleic acid containing triacylglycerols and diacylglycerols were significantly associated with AAA presence. Inclusion of lipidomic features in multivariate analyses significantly improved prediction of AAA presence when compared with traditional risk factors alone.

Glutamine supplementation alleviates vasculopathy and corrects metabolic profile in an in vivo model of endothelial cell dysfunction

Endothelial Cell Dysfunction (ECD) is a recognized harbinger of a host of chronic cardiovascular diseases. Using a mouse model of ECD triggered by treatment with L-Nω-methylarginine (L-NMMA), we previously demonstrated that renal microvasculature displays a perturbed protein profile, including diminished expression of two key enzymes of the Krebs cycle associated with a Warburg-type suppression of mitochondrial metabolism. We hypothesized that supplementation with L-glutamine (GLN), that can enter the Krebs cycle downstream this enzymatic bottleneck, would normalize vascular function and alleviate mitochondrial dysfunction. To test this hypothesis, mice with chronic L-NMMA-induced ECD were co-treated with GLN at different concentrations for 2 months. Results confirmed that L-NMMA led to a defect in acetylcholine-induced relaxation of aortic rings that was dose-dependently prevented by GLN. In caveolin-1 transgenic mice characterized by eNOS inactivation, L-NMMA further impaired vasorelaxation which was partially rescued by GLN co-treatment. Pro-inflammatory profile induced by L-NMMA was blunted in mice co-treated with GLN. Using an LC/MS platform for metabolite profiling, we sought to identify metabolic perturbations associated with ECD and offset by GLN supplementation. 3453 plasma molecules could be detected with 100% frequency in mice from at least one treatment group. Among these, 37 were found to be differentially expressed in a 4-way comparison of control vs. LNMMA both with and without GLN. One of such molecules, hippuric acid, an “uremic toxin” was found to be elevated in our non-uremic mice receiving L-NMMA, but normalized by treatment with GLN. Ex vivo analysis of hippuric acid effects on vasomotion demonstrated that it significantly reduced acetylcholine-induced vasorelaxation of vascular rings. In conclusion, functional and metabolic profiling of animals with early ECD revealed macrovasculopathy and that supplementation GLN is capable of improving vascular function. Metabolomic analyses reveal elevation of hippuric acid, which may further exacerbate vasculopathy even before the development of uremia.

Metabolites secreted by human atherothrombotic aneurysm

One of the possibilities to study abdominal aortic aneurysm (AAA) biomarkers is to use -aneurysm biopsies of dilated arteries or intraluminal thrombus (ILT) for explant cultures. Those metabolites secreted into the culture medium are concentrated in comparison to plasma and free from other interferences that can appear in it, allowing an easier harvesting. Liquid chromatography coupled to quadrupole time-of-flight mass spectrometry detector (LC-QTOF-MS) with an electrospray (ESI) interface has a broad applicability to detect metabolites of all classes with high sensitivity and mass accuracy. Therefore, an LC-QTOF-MS-based metabolomics approach was chosen to select and identify metabolites that could be useful as diagnostic/prognostic markers of AAA. This chapter describes the methodology for the differential analysis of AAA metabolites in secretomes. It gives experimental details on basic steps such as sample preparation, protein precipitation, and analysis of the samples by LC-MS. A description for quality control of the methodology, raw data processing, as well as selection and identification of differentiating -metabolites are also presented in this chapter.

Assessment of compatibility between extraction methods for NMR- and LC/MS-based metabolomics

Because of the wide range of chemically and structurally diverse metabolites, efforts to survey the complete metabolome rely on the implementation of multiplatform approaches based on nuclear magnetic resonance (NMR) and mass spectrometry (MS). Sample preparation disparities between NMR and MS, however, may limit the analysis of the same samples by both platforms. Specifically, deuterated solvents used in NMR strategies can complicate LC/MS analysis as a result of potential mass shifts, whereas acidic solutions typically used in LC/MS methods to enhance ionization of metabolites can severely affect reproducibility of NMR measurements. These intrinsically different sample preparation requirements result in the application of different procedures for metabolite extraction, which involve additional sample and unwanted variability. To address this issue, we investigated 12 extraction protocols in liver tissue involving different aqueous/organic solvents and temperatures that may satisfy the requirements for both NMR and LC/MS simultaneously. We found that deuterium exchange did not affect LC/MS results, enabling the measurement of metabolites by NMR and, subsequently, the direct analysis of the same samples by using LC/MS with no need for solvent exchange. Moreover, our results show that the choice of solvents rather than the temperature determined the extraction efficiencies of metabolites, a combination of methanol/chloroform/water and methanol/water being the extraction methods that best complement NMR and LC/MS analysis for metabolomic studies.

Metabolomics with LC-QTOF-MS permits the prediction of disease stage in aortic abdominal aneurysm based on plasma metabolic fingerprint

Abdominal aortic aneurysm (AAA) is a permanent and localized aortic dilation, defined as aortic diameter ≥3 cm. It is an asymptomatic but potentially fatal condition because progressive enlargement of the abdominal aorta is spontaneously evolving towards rupture.

Biomarkers may help to explain pathological processes of AAA expansion, and allow us to find novel therapeutic strategies or to determine the efficiency of current therapies. Metabolomics seems to be a good approach to find biomarkers of AAA. In this study, plasma samples of patients with large AAA, small AAA, and controls were fingerprinted with LC-QTOF-MS. Statistical analysis was used to compare metabolic fingerprints and select metabolites that showed a significant change. Results presented here reveal that LC-QTOF-MS based fingerprinting of plasma from AAA patients is a very good technique to distinguish small AAA, large AAA, and controls. With the use of validated PLS-DA models it was possible to classify patients according to the disease stage and predict properly the stage of additional AAA patients. Identified metabolites indicate a role for sphingolipids, lysophospholipids, cholesterol metabolites, and acylcarnitines in the development and progression of AAA. Moreover, guanidinosuccinic acid, which mimics nitric oxide in terms of its vasodilatory action, was found as a strong marker of large AAA.

Metabolomics of oxidative stress in recent studies of endogenous and exogenously administered intermediate metabolites

Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing “omics”-based, diagnostic tests to help influence therapies.