Metabolomic Signature of Early Vascular Aging (EVA) in Hypertension

Plasma Metabolome Predicts Aortic Stiffness and Future Risk of Coronary Artery Disease and Mortality After 23 Years of Follow-Up in the General Population

BACKGROUND

Increased aortic stiffness (arteriosclerosis) is associated with early vascular aging independent of age and sex. The underlying mechanisms of early vascular aging remain largely unexplored in the general population. We aimed to investigate the plasma metabolomic profile in aortic stiffness (vascular aging) and associated risk of incident cardiovascular disease and mortality.

METHODS AND RESULTS

We included 6865 individuals from 2 Swedish population-based cohorts. Untargeted plasma metabolomics was performed by liquid-chromatography mass spectrometry. Aortic stiffness was assessed directly by carotid-femoral pulse wave velocity (PWV) and indirectly by augmentation index (AIx@75). A least absolute shrinkage and selection operator (LASSO) regression model was created on plasma metabolites in order to predict aortic stiffness. Associations between metabolite-predicted aortic stiffness and risk of new-onset cardiovascular disease, cardiovascular mortality, and all-cause mortality were calculated. Metabolite-predicted aortic stiffness (PWV and AIx@75) was positively associated particularly with acylcarnitines, dimethylguanidino valeric acid, glutamate, and cystine. The plasma metabolome predicted aortic stiffness (PWV and AIx@75) with good accuracy (R2=0.27 and R2=0.39, respectively). Metabolite-predicted aortic stiffness (PWV and AIx@75) was significantly correlated with age, sex, systolic blood pressure, body mass index, and low-density lipoprotein. After 23 years of follow-up, metabolite-predicted aortic stiffness (PWV and AIx@75) was significantly associated with increased risk of new-onset coronary artery disease, cardiovascular mortality, and all-cause mortality.

CONCLUSIONS

Aortic stiffness is associated particularly with altered metabolism of acylcarnitines, cystine, and dimethylguanidino valeric acid. These metabolic disturbances predict increased risk of new-onset coronary artery disease, cardiovascular mortality, and all-cause mortality after more than 23 years of follow-up in the general population.

How do metabolic processes age: Evidence from human metabolomic studies

Metabolomics, the global profiling of small molecules in the body, has emerged as a promising analytical approach for assessing molecular changes associated with ageing at the population level. Understanding root metabolic ageing pathways may have important implications for managing age-related disease risk. In this short review, relevant studies published in the last few years that have made valuable contributions to this field will be discussed. These include large-scale studies investigating metabolic changes with age, metabolomic clocks, and metabolic pathways associated with ageing phenotypes. Recent significant advances include the use of longitudinal study designs, populations spanning the whole life course, standardised analytical platforms of enhanced metabolome coverage and development of multivariate analyses. While many challenges remain, recent studies have demonstrated the considerable promise of this field.

Effects of RIPC on the Metabolomical Profile during Lower Limb Digital Subtraction Angiography: A Randomized Controlled Trial

Remote ischemic preconditioning (RIPC) has demonstrated protective effects in patients with lower extremity arterial disease (LEAD) undergoing digital subtraction angiography (DSA) and/or percutaneous transluminal angioplasty (PTA). This study aimed to investigate the impact of RIPC on the metabolomical profile of LEAD patients undergoing these procedures and to elucidate its potential underlying mechanisms. A total of 100 LEAD patients were enrolled and randomly assigned to either the RIPC group (n = 46) or the sham group (n = 54). Blood samples were drawn before and 24 h after intervention. Targeted metabolomics analysis was performed using the AbsoluteIDQ p180 Kit, and changes in metabolite concentrations were compared between the groups. The RIPC group demonstrated significantly different dynamics in nine metabolites compared to the sham group, which generally showed a decrease in metabolite concentrations. The impacted metabolites included glutamate, taurine, the arginine-dimethyl-amide-to-arginine ratio, lysoPC a C24:0, lysoPC a C28:0, lysoPC a C26:1, PC aa C38:1, PC ae C30:2, and PC ae C44:3. RIPC exhibited a 'stabilization' effect, maintaining metabolite levels amidst ischemia-reperfusion injuries, suggesting its role in enhancing metabolic control. This may improve outcomes for LEAD patients. However, additional studies are needed to definitively establish causal relationships among these metabolic changes.

Replacement of dietary saturated with unsaturated fatty acids is associated with beneficial effects on lipidome metabolites: a secondary analysis of a randomized trial

BACKGROUND

The effects of replacing dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) and/or polyunsaturated fatty acids (PUFAs) on the plasma lipidome in relation to the cardiometabolic disease (CMD) risk are poorly understood.

OBJECTIVES

We aimed to assess the impact of substituting dietary SFAs with unsaturated fatty acids (UFAs) on the plasma lipidome and examine the relationship between lipid metabolites modulated by diet and CMD risk.

METHODS

Plasma fatty acid (FA) concentrations among 16 lipid classes (within-class FAs) were measured in a subgroup from the Dietary Intervention and VAScular function (DIVAS) parallel randomized controlled trial (n = 113/195), which consisted of three 16-wk diets enriched in SFAs (target SFA:MUFA:n-6PUFA ratio = 17:11:4% total energy [TE]), MUFAs (9:19:4% TE), or a MUFA/PUFA mixture (9:13:10% TE). Similar lipidomics analyses were conducted in the European investigation into Cancer and Nutrition (EPIC)-Potsdam prospective cohort study (specific case/cohorts: n = 775/1886 for type 2 diabetes [T2D], n = 551/1671 for cardiovascular disease [CVD]). Multiple linear regression and multivariable Cox models identified within-class FAs sensitive to replacement of dietary SFA with UFA in DIVAS and their association with CMD risk in EPIC-Potsdam. Elastic-net regression models identified within-class FAs associated with changes in CMD risk markers post-DIVAS interventions.

RESULTS

DIVAS high-UFA interventions reduced plasma within-class FAs associated with a higher CVD risk in EPIC-Potsdam, especially SFA-containing glycerolipids and sphingolipids (e.g., diacylglycerol (20:0) z-score = -1.08; SE = 0.17; P value < 10^-8), whereas they increased those inversely associated with CVD risk. The results on T2D were less clear. Specific sphingolipids and phospholipids were associated with changes in markers of endothelial function and ambulatory blood pressure, whereas higher low-density lipoprotein cholesterol concentrations were characterized by higher plasma glycerolipids containing lauric and stearic acids.

CONCLUSIONS

These results suggest a mediating role of plasma lipid metabolites in the association between dietary fat and CMD risk. Future research combining interventional and observational findings will further our understanding of the role of dietary fat in CMD etiology. This trial was registered in ClinicalTrials.gov as NCT01478958.

Markers of arterial stiffness and urinary metabolomics in young adults with early cardiovascular risk: the African-PREDICT study

INTRODUCTION

Increased exposure to risk factors in the young and healthy contributes to arterial changes, which may be accompanied by an altered metabolism.

OBJECTIVES

To increase our understanding of early metabolic alterations and how they associate with markers of arterial stiffness, we profiled urinary metabolites in young adults with cardiovascular disease (CVD) risk factor(s) and in a control group without CVD risk factors.

METHODS

We included healthy black and white women and men (N = 1202), aged 20-30 years with a detailed CVD risk factor profile, reflecting obesity, physical inactivity, smoking, excessive alcohol intake, masked hypertension, hyperglycemia, dyslipidemia and low socio-economic status, forming the CVD risk group (N = 1036) and the control group (N = 166). Markers of arterial stiffness, central systolic blood pressure (BP) and pulse wave velocity were measured. A targeted metabolomics approach was followed by measuring amino acids and acylcarnitines using a liquid chromatography-tandem mass spectrometry method.

RESULTS

In the CVD risk group, central systolic BP (adjusted for age, sex, ethnicity) was negatively associated with histidine, arginine, asparagine, serine, glutamine, dimethylglycine, threonine, GABA, proline, methionine, pyroglutamic acid, aspartic acid, glutamic acid, branched chain amino acids (BCAAs) and butyrylcarnitine (all P ≤ 0.048). In the same group, pulse wave velocity (adjusted for age, sex, ethnicity, mean arterial pressure) was negatively associated with histidine, lysine, threonine, 2-aminoadipic acid, BCAAs and aromatic amino acids (AAAs) (all P ≤ 0.044). In the control group, central systolic BP was negatively associated with pyroglutamic acid, glutamic acid and dodecanoylcarnitine (all P ≤ 0.033).

CONCLUSION

In a group with increased CVD risk, markers of arterial stiffness were negatively associated with metabolites related to AAA and BCAA as well as energy metabolism and oxidative stress. Our findings may suggest that metabolic adaptations may be at play in response to increased CVD risk to maintain cardiovascular integrity.

Phospholipid remodeling and its derivatives are associated with COVID-19 severity

BACKGROUND

Timely medical intervention in severe cases of coronavirus disease 2019 (COVID-19) and better understanding of the disease's pathogenesis are essential for reducing mortality, but early classification of severe cases and its progression is challenging.

OBJECTIVE

We investigated the levels of circulating phospholipid metabolites and their relationship with COVID-19 severity, as well as the potential role of phospholipids in disease progression.

METHODS

We performed nontargeted lipidomic analysis of plasma samples (n = 150) collected from COVID-19 patients (n = 46) with 3 levels of disease severity, healthy individuals, and subjects with metabolic disease.

RESULTS

Phospholipid metabolism was significantly altered in COVID-19 patients. Results of a panel of phosphatidylcholine (PC) and lysophosphatidylcholine (LPC) and of phosphatidylethanolamine and lysophosphatidylethanolamine (LPE) ratios were significantly correlated with COVID-19 severity, in which 16 phospholipid ratios were shown to distinguish between patients with severe disease, mild disease, and healthy controls, 9 of which were at variance with those in subjects with metabolic disease. In particular, relatively lower ratios of circulating (PC16:1/22:6)/LPC 16:1 and (PE18:1/22:6)/LPE 18:1 were the most indicative of severe COVID-19. The elevation of levels of LPC 16:1 and LPE 18:1 contributed to the changes of related lipid ratios. An exploratory functional study of LPC 16:1 and LPE 18:1 demonstrated their ability in causing membrane perturbation, increased intracellular calcium, cytokines, and apoptosis in cellular models.

CONCLUSION

Significant Lands cycle remodeling is present in patients with severe COVID-19, suggesting a potential utility of selective phospholipids with functional consequences in evaluating COVID-19's severity and pathogenesis.

Lysophospholipids and branched chain amino acids are associated with aging: a metabolomics-based study of Chinese adults

BACKGROUND

Aging is an inevitable process associated with impairments in multiple organ systems, which increases the risk of comorbidity and disability, and reduces the health-span. Metabolomics is a powerful tool in aging research, which can reflect the characteristics of aging at the level of terminal metabolism, and may contribute to the exploration of aging mechanisms and the formulation of anti-aging strategies.

METHODS

To identify possible biomarkers and pathways associated with aging using untargeted metabolomics methods, we performed liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics profiling on serum samples from 32 older adults and 32 sex-matched young controls.

RESULTS

Metabolite profiling could distinguish the two groups. Among the 349 metabolites identified, 80-including lysophospholipids whose levels gradually decline-are possible candidate aging biomarkers. Valine, leucine and isoleucine degradation and biosynthesis were important pathways in aging, with reduced levels of L-isoleucine (r = - 0.30, p = 0.017) and L-leucine (r = - 0.32, p = 0.010) observed in older adults.

CONCLUSIONS

We preliminarily revealed the metabolite changes associated with aging in Chinese adults. Decreases in mitochondrial membrane-related lysophospholipids and dysfunction of branched-chain amino acid metabolism were determined to be the characteristics and promising research targets for aging.

Vascular lipidomics analysis reveales increased levels of phosphocholine and lysophosphocholine in atherosclerotic mice

OBJECTIVE

Atherosclerosis (AS) is the major cause of cardiovascular disease, and dyslipidemia is a principal determinant of the initiation and progression of AS. Numerous works have analyzed the lipid signature of blood, but scarce information on the lipidome of vascular tissue is available. This study investigated the lipid profile in the aorta of ApoE^-/- mice.

METHOD

ApoE^-/- mice were randomly divided into two groups: (1) the normal diet (ND) group and (2) the high-fat diet (HFD) group. After feeding for 8 weeks, the plasma low-density lipoprotein (LDL), total cholesterol (TC), and triglyceride (TGs) levels were measured. UHPLC-Q Exactive plus MS was used to assess the lipid profile using both positive and negative ionization modes.

RESULTS

LDL and TC levels were significantly increased in HFD mice, and lipid deposition, plaque area and collagen fiber levels were increased in HFD group. In addition, a total of 131 differential lipids were characterized, including 57 lipids with levels that were increased in the HFD group and 74 with levels that were decreased. Further analysis revealed that the levels of several differentially expressed phosphocholines (PCs) and lysophosphocholines (LPCs) were significantly increased. These PCs included PC (38:3), PC (36:4), PC (36:3), PC (36:2), PC (36:1), PC (34:1e), PC (34:1), PC (32:1), PC (18:0/18:1), and PC (38:5), and the LPCs included LPC (18:1), LPC (18:0) and LPC (16:0).

CONCLUSION

Our findings indicate the presence of a comprehensive lipid profile in the vascular tissue of atherosclerotic mice, particularly involving PC and LPC, which exhibited significantly increased levels in AS.

Multiomics technologies: role in disease biomarker discoveries and therapeutics

 

Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.

SUMMARY POINTS

Serum metabolomic profiles associated with subclinical and clinical cardiovascular phenotypes in people with type 2 diabetes

BACKGROUND

Atherosclerotic cardiovascular diseases (CVD) is the leading cause of death in diabetes, but the full range of biomarkers reflecting atherosclerotic burden and CVD risk in people with diabetes is unknown. Metabolomics may help identify novel biomarkers potentially involved in development of atherosclerosis. We investigated the serum metabolomic profile of subclinical atherosclerosis, measured using ankle brachial index (ABI), in people with type 2 diabetes, compared with the profile for symptomatic CVD in the same population.

METHODS

The Edinburgh Type 2 Diabetes Study is a cohort of 1,066 individuals with type 2 diabetes. ABI was measured at baseline, years 4 and 10, with cardiovascular events assessed at baseline and during 10 years of follow-up. A panel of 228 metabolites was measured at baseline using nuclear magnetic resonance spectrometry, and their association with both ABI and prevalent CVD was explored using univariate regression models and least absolute shrinkage and selection operator (LASSO). Metabolites associated with baseline ABI were further explored for association with follow-up ABI and incident CVD.

RESULTS

Mean (standard deviation, SD) ABI at baseline was 0.97 (0.18, N = 1025), and prevalence of CVD was 35.0%. During 10-year follow-up, mean (SD) change in ABI was + 0.006 (0.178, n = 436), and 257 CVD events occurred. Lactate, glycerol, creatinine and glycoprotein acetyls levels were associated with baseline ABI in both univariate regression [βs (95% confidence interval, CI) ranged from - 0.025 (- 0.036, - 0.015) to - 0.023 (- 0.034, - 0.013), all p < 0.0002] and LASSO analysis. The associations remained nominally significant after adjustment for major vascular risk factors. In prospective analyses, lactate was nominally associated with ABI measured at years 4 and 10 after adjustment for baseline ABI. The four ABI-associated metabolites were all positively associated with prevalent CVD [odds ratios (ORs) ranged from 1.29 (1.13, 1.47) to 1.49 (1.29, 1.74), all p < 0.0002], and they were also positively associated with incident CVD [ORs (95% CI) ranged from 1.19 (1.02, 1.39) to 1.35 (1.17, 1.56), all p < 0.05].

CONCLUSIONS

Serum metabolites relating to glycolysis, fluid balance and inflammation were independently associated with both a marker of subclinical atherosclerosis and with symptomatic CVD in people with type 2 diabetes. Additional investigation is warranted to determine their roles as possible etiological and/or predictive biomarkers for atherosclerotic CVD.

Metabolomics of Arterial Stiffness

Arterial stiffness (AS) is one of the earliest detectable signs of structural and functional alterations of the vessel wall and an independent predictor of cardiovascular events and death. The emerging field of metabolomics can be utilized to detect a wide spectrum of intermediates and products of metabolism in body fluids that can be involved in the pathogenesis of AS. Research over the past decade has reinforced this idea by linking AS to circulating acylcarnitines, glycerophospholipids, sphingolipids, and amino acids, among other metabolite species. Some of these metabolites influence AS through traditional cardiovascular risk factors (e.g., high blood pressure, high blood cholesterol, diabetes, smoking), while others seem to act independently through both known and unknown pathophysiological mechanisms. We propose the term 'arteriometabolomics' to indicate the research that applies metabolomics methods to study AS. The 'arteriometabolomics' approach has the potential to allow more personalized cardiovascular risk stratification, disease monitoring, and treatment selection. One of its major goals is to uncover the causal metabolic pathways of AS. Such pathways could represent valuable treatment targets in vascular ageing.

Inflammation as A Precursor of Atherothrombosis, Diabetes and Early Vascular Aging

Vascular disease was for a long time considered a disease of the old age, but it is becoming increasingly clear that a cumulus of factors can cause early vascular aging (EVA). Inflammation plays a key role in vascular stiffening and also in other pathologies that induce vascular damage. There is a known and confirmed connection between inflammation and atherosclerosis. However, it has taken a long time to prove the beneficial effects of anti-inflammatory drugs on cardiovascular events. Diabetes can be both a product of inflammation and a cofactor implicated in the progression of vascular disease. When diabetes and inflammation are accompanied by obesity, this ominous trifecta leads to an increased incidence of atherothrombotic events. Research into earlier stages of vascular disease, and documentation of vulnerability to premature vascular disease, might be the key to success in preventing clinical events. Modulation of inflammation, combined with strict control of classical cardiovascular risk factors, seems to be the winning recipe. Identification of population subsets with a successful vascular aging (supernormal vascular aging-SUPERNOVA) pattern could also bring forth novel therapeutic interventions.

Metabolic Profiling and Metabolites Fingerprints in Human Hypertension: Discovery and Potential

Early detection of pathogenesis through biomarkers holds the key to controlling hypertension and preventing cardiovascular complications. Metabolomics profiling acts as a potent and high throughput tool offering new insights on disease pathogenesis and potential in the early diagnosis of clinical hypertension with a tremendous translational promise. This review summarizes the latest progress of metabolomics and metabolites fingerprints and mainly discusses the current trends in the application in clinical hypertension. We also discussed the associated mechanisms and pathways involved in hypertension's pathogenesis and explored related research challenges and future perspectives. The information will improve our understanding of the development of hypertension and inspire the clinical application of metabolomics in hypertension and its associated cardiovascular complications.

OMICS approaches in cardiovascular diseases: a mini review

Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.