Vascular calcification (VC) is highly prevalent in patients with advanced age, or those with chronic kidney disease and diabetes, accounting for substantial global cardiovascular burden. The pathophysiology of VC involves active mineral deposition by transdifferentiated vascular smooth muscle cells exhibiting osteoblast-like behavior, building upon cores with or without apoptotic bodies. Oxidative stress drives the progression of the cellular phenotypic switch and calcium deposition in the vascular wall. In this review, we discuss potential compounds that shield these cells from the detrimental influences of reactive oxygen species as promising treatment options for VC. A comprehensive summary of the current literature regarding antioxidants for VC is important, as no effective therapy is currently available for this disease. We systematically searched through the existing literature to identify original articles investigating traditional antioxidants and novel compounds with antioxidant properties with regard to their effectiveness against VC in experimental or clinical settings. We uncovered 36 compounds with antioxidant properties against VC pathology, involving mechanisms such as suppression of NADPH oxidase, BMP-2, and Wnt/β-catenin; anti-inflammation; and activation of Nrf2 pathways. Only two compounds have been tested clinically. These findings suggest that a considerable opportunity exists to harness these antioxidants for therapeutic use for VC. In order to achieve this goal, more translational studies are needed.

Vascular calcification (VC) describes the pathophysiological phenotype of calcium apatite deposition within the vascular wall, leading to vascular stiffening and the loss of compliance. VC is never benign; the presence and severity of VC correlate closely with the risk of myocardial events and cardiovascular mortality in multiple at-risk populations such as patients with diabetes and chronic kidney disease. Mitochondrial dysfunction involving each of vascular wall constituents (endothelia and vascular smooth muscle cells (VSMCs)) aggravates various vascular pathologies, including atherosclerosis and VC. However, few studies address the pathogenic role of mitochondrial dysfunction during the course of VC, and mitochondrial reactive oxygen species (ROS) seem to lie in the pathophysiologic epicenter. Superoxide dismutase 2 (SOD2), through its preferential localization to the mitochondria, stands at the forefront against mitochondrial ROS in VSMCs and thus potentially modifies the probability of VC initiation or progression. In this review, we will provide a literature-based summary regarding the relationship between SOD2 and VC in the context of VSMCs. Apart from the conventional wisdom of attenuating mitochondrial ROS, SOD2 has been found to affect mitophagy and the formation of the autophagosome, suppress JAK/STAT as well as PI3K/Akt signaling, and retard vascular senescence, all of which underlie the beneficial influences on VC exerted by SOD2. More importantly, we outline the therapeutic potential of a novel SOD2-targeted strategy for the treatment of VC, including an ever-expanding list of pharmaceuticals and natural compounds. It is expected that VSMC SOD2 will become an important druggable target for treating VC in the future.

Aims Vascular calcification (VC) increases the future risk of cardiovascular events in uremic patients, but effective therapies are still unavailable. Accurate identification of those at risk of developing VC using pathogenesis-based biomarkers is of particular interest and may facilitate individualized risk stratification. We aimed to uncover miRNA-target protein-based biomarker panels for evaluating uremic VC probability and severity. Methods and Results We created a 3-tiered in vitro VC model and an in vivo uremic rat model receiving high phosphate diet to mimic uremic VC. RNAs from the 3-tiered in vitro and in vivo uremic VC models underwent miRNA and mRNA microarray, with results screened for differentially expressed miRNAs and their target genes as biomarkers. Findings were validated in original models and additionally in an ex vivo VC model and human cells, followed by functional assays of identified miRNAs and target proteins, and tests of sera from end-stage renal disease (ESRD) and non-dialysis dependent chronic kidney disease (CKD) patients without and with VC. Totally 122 down-regulated and 119 up-regulated miRNAs during calcification progression were identified initially; further list-narrowing based on miRNA-mRNA pairing, anti-correlation, and functional enrichment left 16 and 14 differentially expressed miRNAs and mRNAs. Levels of 4 miRNAs (miR-10b-5p, miR-195, miR-125b-2-3p, and miR-378a-3p) were shown to decrease throughout all models tested, while 1 mRNA (SULF1, a potential target of miR-378a-3p) exhibited the opposite trend concurrently. Among 96 ESRD (70.8% with VC) and 59 CKD patients (61% with VC), serum miR-125b2-3p and miR-378a-3p decreased with greater VC severity, while serum SULF1 levels increased. Adding serum miR-125b-2-3p, miR-378a-3p, and SULF1 into regression models for VC substantially improved performance compared to using clinical variables alone. Conclusion Using a translational approach, we discovered a novel panel of biomarkers for gauging the probability/severity of uremic VC based on miRNAs/target proteins, which improved the diagnostic accuracy. Translational perspective Through miRNA and transcriptomic profiling with serial result validation in different models, we discover that miR-378a-3p and its target gene, SULF1, are an important pair of circulating biomarkers for the diagnosis and severity classification of uremic VC among patients with non-dialysis CKD and ESRD. This approach improves the predictive performance compared to that based on traditional clinical features alone. These findings suggest that a combined miRNA/target protein panel may represent a potentially useful approach for detecting uremic VC.

Vascular calcification (VC) is a critical contributor to the rising cardiovascular risk among at-risk populations such as those with diabetes or renal failure. The pathogenesis of VC involves an uprising of oxidative stress, for which antioxidants can be theoretically effective. However, astaxanthin, a potent antioxidant, has not been tested before for the purpose of managing VC. To answer this question, we tested the efficacy of astaxanthin against VC using the high phosphate (HP)-induced vascular smooth muscle cell (VSMC) calcification model. RNAs from treated groups underwent Affymetrix microarray screening, with intra-group consistency and inter-group differential expressions identified. Candidate hub genes were selected, followed by validation in experimental models and functional characterization. We showed that HP induced progressive calcification among treated VSMCs, while astaxanthin dose-responsively and time-dependently ameliorated calcification severities. Transcriptomic profiling revealed that 3491 genes exhibited significant early changes during VC progression, among which 26 potential hub genes were selected based on closeness ranking and biologic plausibility. SOD2 was validated in the VSMC model, shown to drive the deactivation of cellular senescence and enhance antioxidative defenses. Astaxanthin did not alter intracellular reactive oxygen species (ROS) levels without HP, but significantly lowered ROS production in HP-treated VSMCs. SOD2 knockdown prominently abolished the anti-calcification effect of astaxanthin on HP-treated VSMCs, lending support to our findings. In conclusion, we demonstrated for the first time that astaxanthin could be a potential candidate treatment for VC, through inducing the up-regulation of SOD2 early during calcification progression and potentially suppressing vascular senescence.

Background. Vascular calcification (VC) constitutes subclinical vascular burden and increases cardiovascular mortality. Effective therapeutics for VC remains to be procured. We aimed to use a deep learning-based strategy to screen and uncover plant compounds that potentially can be repurposed for managing VC. Methods. We integrated drugome, interactome, and diseasome information from Comparative Toxicogenomic Database (CTD), DrugBank, PubChem, Gene Ontology (GO), and BioGrid to analyze drug-disease associations. A deep representation learning was done using a high-level description of the local network architecture and features of the entities, followed by learning the global embeddings of nodes derived from a heterogeneous network using the graph neural network architecture and a random forest classifier established for prediction. Predicted results were tested in an in vitro VC model for validity based on the probability scores. Results. We collected 6,790 compounds with available Simplified Molecular-Input Line-Entry System (SMILES) data, 11,958 GO terms, 7,238 diseases, and 25,482 proteins, followed by local embedding vectors using an end-to-end transformer network and a node2vec algorithm and global embedding vectors learned from heterogeneous network via the graph neural network. Our algorithm conferred a good distinction between potential compounds, presenting as higher prediction scores for the compound categories with a higher potential but lower scores for other categories. Probability score-dependent selection revealed that antioxidants such as sulforaphane and daidzein were potentially effective compounds against VC, while catechin had low probability. All three compounds were validated in vitro. Conclusions. Our findings exemplify the utility of deep learning in identifying promising VC-treating plant compounds. Our model can be a quick and comprehensive computational screening tool to assist in the early drug discovery process.