Heart diseases are one of the leading causes of death in Western Countries and tend to become chronic, lowering the quality of life of the patients and ending up in a massive cost for the Health Systems and the society. Thus, there is a growing interest in finding new technologies that would allow the physician to effectively treat and prevent cardiac illnesses. Metabolomics is one of the new “omics” sciences enabling creation of a photograph of the metabolic state of an individual exposed to different environmental factors and pathologies. This review analyzed the most recent literature about this technology and its application in cardiology in order to understand the metabolic shifts that occur even before the manifestation of these pathologies to find possible early predictive biomarkers. In this way, it could be possible to find better treatments, ameliorate the patient’s quality of life, and lower the death rate. This technology seems to be so promising that several industries are trying to set up kits to immediately assess the metabolites variations in order to provide a faster diagnosis and the best treatment specific for that patient, offering a further step toward the path of the development of a tailored medicine.
Cardiac pathologies are a critical health issue affecting millions of people worldwide with a constant mortality rate in particular in the elderly, a difficult prognosis, and a worsening in quality life of affected people. In fact, they tend to become chronic and lead to several complications that may affect other vital organs such as brain, lungs, and kidneys. Indeed cardiovascular diseases (CVDs) are globally the number one cause of death: more people die every year from CVDs than from any other cause (17.5 million deaths, an estimation of 31% of all deaths worldwide). People with cardiovascular pathologies or who are at high cardiovascular risk need early detection since the 80% of premature heart diseases are preventable [
Among the complications of these pathologies there are pulmonary edema or respiratory tract infections, kidney insufficiency, and stroke. In children, cardiovascular diseases or congenital heart malformations can lead to pulmonary hypertension and neurodevelopmental problems due to the lack of oxygen supply [
The pathophysiology of heart pathologies is complex. Indeed, recent findings pointed out a possible pivotal role of mitochondrial dysfunction and the subsequent altered energy metabolism in cardiac diseases, in particular in case of heart failure [
In general, patient management could be quite challenging and demanding; thus there is a need for the clinician to have the best tools that can improve and facilitate the diagnosis and the prognosis for these diseases.
During the last decade, animal and human studies have applied metabolomics to cardiovascular research, using both targeted and untargeted approaches; as such, metabolic fingerprints have been identified for several cardiovascular risk factors and diseases [
Indeed, by entering the keywords “metabolomics” and “cardiology” on PubMed, this will show 161 papers, 156 written from 2011 to 2016 (Figure
PubMed results concerning the studies of metabolomics and cardiology from 2011 to 2016.
In fact metabolomics is a new technique that allows investigators to study the metabolic network involved in heart diseases so as to better understand their pathophysiological mechanism. Griffin et al. highlighted how the classical metabolomics technique could be applied in cardiology; indeed high resolution Magnetic Resonance Imaging (MRI) and mass spectrometry (MS) are extremely useful for gaining information about cardiac disease processes since they are both highly discriminant for a range of pathological processes starting from cardiac ischemia (angina and myocardial infarction) to heart failure [
In Table
Recent relevant works concerning metabolomics in cardiology are shown chronologically with the main metabolites shifts.
Authors | Patients | Methods | Sample | Metabolites results |
---|---|---|---|---|
Feng et al. 2016 [ |
59 CHD patients and 43 healthy controls |
Untargeted metabolomics method |
Plasma, urine |
|
Ahmad et al. 2016 [ |
41 patients with end-stage heart failure | Tandem flow injection |
Plasma |
|
Oni-Orisan et al. 2016 [ |
123 patients with coronary artery disease (CAD) versus 39 controls | Mass spectrometry | Plasma |
|
Deidda et al. 2015 [ |
24 heart failure patients versus 9 controls |
1H-NMR |
Plasma |
|
Zordoky et al. 2015 [ |
44 HF patients versus 20 controls | LC/MS 1H-NMR |
Serum |
|
Cheng et al. 2015 [ |
401 HF patients versus 114 controls | Mass spectrometry |
Plasma |
|
Würtz et al. 2015 [ |
1373 cardiovascular events | Quantitative nuclear magnetic resonance | Serum |
|
Zhong et al. 2014 [ |
157 hypertension patients versus 99 controls | 1H-NMR | Serum |
|
Vaarhorst et al. 2014 [ |
79 cases of coronary heart disease | 1H-NMR | Plasma and serum |
|
Shi et al. 2014 [ |
45 cases of coronary heart disease versus 15 controls | 1H-NMR | Plasma |
|
Rizza et al. 2014 [ |
17 major cardiovascular events (MACE) patients versus 50 controls | Mass spectrometry | Serum |
|
Kalim et al. |
100 individuals dead of a cardiovascular cause versus 100 controls |
Liquid chromatography/mass spectrometry | Plasma |
|
Tenori et al. 2013 [ |
185 heart failure patients versus 111 controls | 1H-NMR | Serum, urine |
|
Desmoulin et al. 2013 [ |
126 acute heart failure (AHF) patients | 1H-NMR | Plasma |
|
Samara et al. 2013 [ |
25 acute decompensated heart failure (ADHF) patients versus 16 controls |
Selected ion flow tube mass spectrometry | Breath |
|
Magnusson et al. 2013 [ |
253 cardiovascular disease patients (CVD) versus 253 controls | Liquid chromatography/mass spectrometry | Plasma |
|
Bodi et al. 2012 [ |
20 angioplasty induced myocardial ischemia versus 9 controls | 1H-NMR | Serum |
|
Kang et al. 2011 [ |
15 heart failure patients versus 20 controls | 1H-NMR | Urine |
|
In 2011 Kang et al. investigated metabolomics urinary profiles of elderly patients with ischemic heart failure, using 1H-nuclear magnetic resonance (1H-NMR) [
Among others, the study performed by Desmoulin et al. in 2013 underlines the predictive power of metabolomics [
Another interesting study performed by Deidda et al. in 2015 questioned whether there could be any changes in patients metabolome according to the worsening of their conditions [
In line with presented data, a latest review published in the Journal of the American College of Cardiology stated that metabolomics is transforming the ability to predict, identify, and better understand several cardiac diseases, by allowing monitoring of the effectiveness of therapeutic interventions, thus leading to advancing the objective of personalizing the practice of medicine [
The perinatal programming of adult diseases (DOHaD theory) states that every adverse event that may occur during pregnancy “shapes” the health status of the fetus and its development and could affects its life course [
In fact Bassareo et al. investigated the cardiac outcome of young adults born with extremely low birth weight (ELBW) [
Possible long-term consequences in adulthood to subjects born with extremely low birth weight: suggestion for diagnosis and care.
Possible consequences in adulthood | Risks | Suggestion for diagnosis and care |
---|---|---|
Increase in the QT interval of ECG in some subjects | Risk of arrhythmia and sudden death | ECG monitoring |
Reduced vascular elasticity | Risk of hypertension | Blood pressure monitoring |
High ADMA levels | Risk of acute cardiovascular problems | ECG and blood pressure monitoring |
Increase in microalbuminuria and urinary NGAL, reduction of kidney volume | Risk of chronic kidney insufficiency | Urine stick monitoring, albuminuria, creatinine, and cystatin C in the blood, kidney ultrasound |
It is therefore a big challenge, on the opposite side of the life span, to try to predict the cardiac outcome of the neonate during pregnancy. Metabolomics seems to have made it possible even though to our knowledge there is only one study of metabolomics in pregnancy performed by Bahado-Singh et al. [
Moving from neonates to infants and young adults (since CVDs have a long latent period), metabolomics could be a useful tool to investigate the actual role of genetic predisposition. It could help understand whether a particular gene mutation is protective or harmful and in which metabolism it is involved or if there are any sex differences. A very interesting study concerning this topic was performed by Klein et al. in 2014 [
Metabolomics allows not only measuring changes in metabolites concentrations, but also discriminating those of human origin from those of microbial origins; in fact several authors consider this technology as the Rosetta Stone of microbiomics [
The first one: bacterial infection activates the immune system causing an excessive inflammatory response that may turn out to be dangerous, independently of the site of invasion. The subsequent proatherogenic response could be mediated by Toll-like receptor 4 expressed in macrophages.
The second: the TMAO production could initiate the activation of platelets and foam cells.
The third: the production of noxious molecules such as the previously mentioned TMAO is related to the diet and gut microbiota metabolites.
With metabolomics it is possible to demonstrate that apparently healthy young adults who were born with birth weight < 1000 g present a specific profile compared to apparently healthy young adults who were born at term. That is perinatal programming.
Differences in the two groups were related to the alterations in the arginine and proline metabolism, in the purine and pyrimidine metabolism in the histidine, in beta-alanine metabolism, and in the urea cycle [
The most investigated cardiac pathologies are heart failure, coronary heart disease, and myocardial infarction.
Several studies displayed an alteration of metabolites concerning lipid metabolism, highlighting the energy imbalance as a peculiar feature of such pathologies.
On the other hand, some authors showed different metabolites that indicate an interaction between diet and microbiota.
These findings open up unusual scenarios to the cardiologist and although it is normal to feel some sort of incredulity, they could pave the way to new possibilities of early diagnosis and individualized treatment. Congenital malformations, gut colonization by microbiota, individual genetic arrangement, and its interplay with both behavioral and risk factors, such as drugs assumption, can influence the occurrence of heart diseases. Metabolomics, for its peculiarities, seems to be the most promising technology to investigate the individual predisposition or the eventual long-term prognosis of these pathologies.
The authors declare that there are no conflicts of interest regarding the publication of this paper.