Various disease states have been studied using cardiovascular (CV) imaging and metabolomics. However, limited data is available regarding the application of CV imaging and metabolomics in understanding CV aging. This review intended to demonstrate new biomarkers and mechanisms of CV aging using CV imaging and metabolomics.
A variety of metabolites with different chemical properties are measured to understand the overall biological status of an individual through metabolomic profiling, a systems biology tool. Targeted and untargeted are the two main approaches taken in analyzing metabolomics.
Unbiased detection of biomarkers by assessing all the measurable analytes in a sample can be achieved through an untargeted approach. All potentially important analytes are covered in this wide coverage.
The disadvantages include:
Relative quantitation of compounds
A complicated workflow for the analysis of large samples
Frequent inability to identify peaks of interest
Bias towards identifying compounds with high abundance
Predefined metabolites are measured in a targeted approach.
A relatively fast workout is associated with a targeted approach. Low abundance analytes can also be identified and quantified by the use of internal standards.
This technique may overlook clinically significant analytes.
The proportion of the people aged 65 years or more will increase to 20% by the year 2030. In older adults, the leading cause of death is cardiovascular disease (CVD). Therefore, the risk factors for CVD in older adults need to be understood better. Cardiovascular aging is one such factor that can cause CVD. With chronologic aging, structural and functional alterations of the cardiovascular system occur during cardiovascular aging.
Increase in collagen and loss of elastic fibers results in increased stiffness of arteries.
CV imaging to detect and manage cardiovascular aging:
Systemic inflammation response and myocardial injury can be determined accurately by absolute native T1 values obtained through fluorodeoxyglucose positron emission tomography or magnetic resonance.
The pathological consequences of cardiovascular aging can be understood optimally by combining metabolomics and non-invasive CV imaging. Large-scale studies are needed to identify new biomarkers for predicting or monitoring disease progression.