Despite advances in diagnostic and therapeutic technologies for cardiovascular diseases (CVDs), it remains a leading cause of mortality and morbidity worldwide. This underscores the urgency for innovative approaches aiming at early and precise detection and treatment of CVDs to reduce the disease burden. Iron oxide nanoparticles (IONPs), with their unique magnetism and bioproperties, have shown great potential in this regard. In this review, we will begin with a brief overview of the synthesis and properties of IONPs. We will then focus on the latest applications of IONPs in CVDs, including diagnosis and treatment. The use of IONPs in the integration of diagnosis and treatment for CVDs is a promising field, and will be addressed in a separate section. The translational potential and challenges of IONPs will also be discussed. In conclusion, ongoing research and development of IONP-based strategies are highly likely to address current challenges effectively, and offer more personalized and efficient options for the diagnosis and treatment of CVDs.

Hypertension (HT) is the most common public-health challenge and shows a high incidence around the world. Cardiovascular diseases are the leading cause of mortality and morbidity among the elderly (age > 65 years) in the United States. Now, there is widespread acceptance of the causal link between HT and acute myocardial infarction (MI). This is the first data-mining study to identify co-expressed differentially expressed genes (co-DEGs) between HT and MI (relative to normal control) and to uncover potential biomarkers and therapeutic targets of HT-related MI. In this manuscript, HT-specific DEGs and MI-specific DEGs and differentially expressed microRNAs (DE-miRNAs) were identified in Gene Expression Omnibus (GEO) datasets GSE24752, GSE60993, GSE62646, and GSE24548 after data consolidation and batch correction. Subsequently, enrichment in Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways as well as protein–protein interaction networks were identified, and single-gene gene set enrichment analysis was performed to determine the affected biological categories and networks. Cross-matching of the results on co-DE-miRNAs and predicted miRNAs targeting the co-DEGs was conducted and discussed as well. We found that MYC and HIST1H2BO may be associated with HT, whereas FCGR1A, FYN, KLRD1, KLRB1, and FOLR3 may be implicated in MI. Moreover, co-DEGs FOLR3 and NFE2 with predicted miRNAs and DE-miRNAs, especially miR-7 and miR-548, may be significantly associated and show huge potential as a new set of novel biomarkers and important molecular targets in the course of HT-related MI.