Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels

Identification of diagnostic biomarkers used in the diagnosis of cardiovascular diseases and diabetes mellitus: A systematic review of quantitative studies

AIMS

To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM), which could be used in low- and middle-income countries (LMICs) where there is a lack of diagnostic equipment, treatments and training.

MATERIALS AND METHODS

Papers were sourced from six databases: the British Nursing Index, Google Scholar, PubMed, Sage, Science Direct and Scopus. Articles published between January 2002 and January 2023 were systematically reviewed by three reviewers and appropriate search terms and inclusion/exclusion criteria were applied.

RESULTS

A total of 18 studies were yielded, as well as 234 diagnostic biomarkers (74 for CVD and 160 for DM). Primary biomarkers for the diagnosis of CVDs included growth differentiation factor 15 and neurogenic locus notch homologue protein 1 (Notch1). For the diagnosis of DM, alpha-2-macroglobulin, C-peptides, isoleucine, glucose, tyrosine, linoleic acid and valine were frequently reported across the included studies. Advanced analytical techniques, such as liquid chromatography mass spectrometry, enzyme-linked immunosorbent assays and vibrational spectroscopy, were also repeatedly reported in the included studies and were utilized in combination with traditional and alternative matrices such as fingernails, hair and saliva.

CONCLUSIONS

While advanced analytical techniques are expensive, laboratories in LMICs should carry out a cost-benefit analysis of their use. Alternatively, laboratories may want to explore emerging techniques such as infrared, Fourier transform-infrared and near-infrared spectroscopy, which allow sensitive noninvasive analysis.

High-Throughput Metabolomics Applications in Pathogenesis and Diagnosis of Valvular Heart Disease

High-throughput metabolomics techniques are a useful tool to understand many disease conditions including cardiovascular disease such as valvular heart disease(s) (VHD). VHD involves damage to heart valves, mostly presenting as stenosis, regurgitation or prolapse and can be classified into degenerative, rheumatic, congenital, or prosthetic valve disease. Gaps remain in our understanding of the pathogenesis of the common VHD. It is now fitting to place into perspective the contribution of metabolomics in the mechanism of development, diagnosis, and prognosis of VHD. A structured search for metabolomics studies centred on human VHD was undertaken. Biomarkers associated with the pathogenesis of bicuspid aortic valve disease, mitral valve disease, rheumatic heart disease, and degenerative aortic valve stenosis are reviewed and discussed. In addition, metabolic biomarkers reported to prognosticate patient outcomes of post-valve repair or replacement are highlighted. Finally, we also review the pitfalls and limitations to consider when designing metabolomics studies, especially from a clinician's viewpoint. In the future, reliable and simple metabolic biomarker(s) may supplement the existing diagnostic tools in the early diagnosis of VHD.

Andrographolide ameliorates aortic valve calcification by regulation of lipid biosynthesis and glycerolipid metabolism targeting MGLL expression in vitro and in vivo

Calcific aortic valve disease (CAVD) is caused by the initiation of the thickening and calcification of valve leaflets by valve interstitial cells (VICs). Cell metabolic changes during the CAVD process are a new field of basic research on this disease. The present study aimed to investigate whether andrographolide (AGP) could attenuate the calcification of aortic valves by regulating cell metabolism. Gas chromatography-mass spectroscopy (GC-MS) metabolome analysis was utilized to investigate the changes in the metabolites of VICs from healthy and CAVD samples. Cell growth and the osteogenic differentiation of human VICs (hVICs) were assessed using a CCK8 assay and Alizarin Red S staining, respectively. The expression of two calcification-related markers, RUNX2 and ALP, was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) and immunofluorescence staining. Molecular docking was used to detect the interaction between AGP and monoglyceride lipase (MGLL). The high-fat-fed ApoE-/- mice aortic valve calcification animal model was used to verify the effect of AGP on CAVD in vivo. Metabolome analysis showed that the metabolites of VICs from healthy and CAVD samples were highly enriched in the biosynthesis of unsaturated fatty acids and glycerolipid metabolism. The top six highlighted metabolites were selected to reveal a high regulation of lipids in VICs from CAVD. AGP significantly suppressed the calcific differentiation of VICs while it decreased the accumulation of the above six metabolites, 1-monopalmitic, palmitic acid, glycerol, l-asparagine, tetraethylene glycol, and stearic acid induced by osteogenic medium (OM) stimulation. These metabolites were highly correlated with the calcific marker ALP and showed a positive correlation with CAVD. In the comprehensive assessment, MGLL, associated with glycerol synthesis, was selected as the molecular target of AGP in inhibiting the calcific phenotype of transforming hVICs. The in vivo results revealed that AGP visibly ameliorated aortic valve calcification by reducing Von Kossa and ALP staining, which was positively correlated with MGLL expression. AGP ameliorated aortic valve calcification by regulating lipid biosynthesis and glycerolipid metabolism targeting MGLL expression in vitro and in vivo. It is a potent therapeutic supplement that prevents the occurrence of heart valve calcification disease by regulating cell metabolism.

Diabetes Mellitus and Its Implications in Aortic Stenosis Patients

Aortic stenosis (AS) and diabetes mellitus (DM) are both progressive diseases that if left untreated, result in significant morbidity and mortality. Several studies revealed that the prevalence of DM is substantially higher in patients with AS and, thus, the progression from mild to severe AS is greater in those patients with DM. DM and common comorbidities associated with both diseases, DM and AS, increase patient management complexity and make aortic valve replacement the only effective treatment. For that reason, a better understanding of the pathogenesis underlying both these diseases and the relationships between them is necessary to design more appropriate preventive and therapeutic approaches. In this review, we provided an overview of the main aspects of the relationship between AS and DM, including common comorbidities and risk factors. We also discuss the established treatments/therapies in patients with AS and DM.

Multi-Omics Approaches to Define Calcific Aortic Valve Disease Pathogenesis

Calcific aortic valve disease sits at the confluence of multiple world-wide epidemics of aging, obesity, diabetes, and renal dysfunction, and its prevalence is expected to nearly triple over the next 3 decades. This is of particularly dire clinical relevance, as calcific aortic valve disease can progress rapidly to aortic stenosis, heart failure, and eventually premature death. Unlike in atherosclerosis, and despite the heavy clinical toll, to date, no pharmacotherapy has proven effective to halt calcific aortic valve disease progression, with invasive and costly aortic valve replacement representing the only treatment option currently available. This substantial gap in care is largely because of our still-limited understanding of both normal aortic valve biology and the key regulatory mechanisms that drive disease initiation and progression. Drug discovery is further hampered by the inherent intricacy of the valvular microenvironment: a unique anatomic structure, a complex mixture of dynamic biomechanical forces, and diverse and multipotent cell populations collectively contributing to this currently intractable problem. One promising and rapidly evolving tactic is the application of multiomics approaches to fully define disease pathogenesis. Herein, we summarize the application of (epi)genomics, transcriptomics, proteomics, and metabolomics to the study of valvular heart disease. We also discuss recent forays toward the omics-based characterization of valvular (patho)biology at single-cell resolution; these efforts promise to shed new light on cellular heterogeneity in healthy and diseased valvular tissues and represent the potential to efficaciously target and treat key cell subpopulations. Last, we discuss systems biology- and network medicine-based strategies to extract meaning, mechanisms, and prioritized drug targets from multiomics datasets.