Cardiometabolic diseases, including cardiovascular disorders and type 2 diabetes mellitus, are the leading cause of morbidity and mortality worldwide, placing a significant burden on healthcare systems. Although advances in imaging and risk stratification have improved disease management, conventional diagnostic and prognostic tools often lack the requisite sensitivity and specificity for early and precise risk stratification. This limitation stems from their poor ability to capture the full molecular complexity of these conditions, underscoring an urgent need for innovative biomarkers to bridge these gaps. MicroRNAs, small non-coding RNAs that regulate gene expression post-transcriptionally, have emerged as promising candidates. Their characteristics offer several advantages over traditional methods, including exceptional stability in biological fluids, strong tissue and disease specificity, and the ability to reflect dynamic pathological changes. These unique features enable miRNAs to detect subtle molecular alterations that may precede clinical symptoms, thereby overcoming key limitations of current diagnostic approaches. Altered circulating miRNA profiles have been linked to pathological processes such as endothelial dysfunction, inflammation, oxidative stress, and maladaptive cardiac remodeling. This review provides a comprehensive overview of the current evidence supporting the diagnostic and prognostic role of circulating miRNAs in cardiometabolic disease. We highlight their potential as early detection biomarkers, tools for patient stratification, and indicators of therapeutic response. Furthermore, we discuss key limitations to clinical translation, including methodological variability, challenges in sample handling, differences in normalization strategies, and platform-dependent quantification inconsistencies. Overcoming these obstacles and achieving robust large-scale clinical validation will be essential to fully harness the potential of miRNAs as next-generation molecular signatures in precision medicine.

Despite enormous insights into the molecular mechanisms of acute myeloid leukemia (AML) pathophysiology, this disease is still fatal in the majority of patients, highlighting the urgent need for novel biomarkers useful in AML prognosis and therapy. The advent of modern sequencing technologies has allowed the identification of genetic mutations in genes encoding for specific enzymes involved in the epigenetic regulation of gene expression. The authors review recent data demonstrating the involvement of mutations in genes encoding for epigenetic players and their complex combination with somatic genetic mutations in the pathogenesis of AML. They also discuss the prognostic and therapeutic implications of these findings. Current clinical and preclinical studies are underscoring the importance of targeting epigenetic modifiers as new biomarkers for a better prognostic risk stratification and therapeutic evaluation of intermediate-risk patients. Combining data from traditional and modern methodologies will allow a definition of the complex networks of epigenetic changes and molecular interactions between candidate epitargets and key regulators of hematopoiesis. It will thus be possible to achieve an overview of potential aberrant mechanisms driving leukemogenesis in different classes of AML patients. Such an improved approach could pave the way towards 'personalized' therapies.

Background: Osteoarthritis (OA) is a multifactorial, hypertrophic, and degenerative condition involving the whole joint and affecting a high percentage of middle-aged people. It is due to a combination of factors, although the pivotal mechanisms underlying the disease are still obscure. Moreover, current treatments are still poorly effective, and patients experience a painful and degenerative disease course.Methods: We used an integrative approach that led us to extract aconsensussignature from a meta-analysis of three different OA cohorts. We performed a network-based drug prioritization to detect the most relevant drugs targeting these genes and validated in vitro the most promising candidates. We also proposed a risk score based on a minimal set of genes to predict the OA clinical stage from RNA-Seq data.Results: We derived aconsensussignature of 44 genes that we validated on an independent dataset. Using network analysis, we identified Resveratrol, Tenoxicam, Benzbromarone, Pirinixic Acid, and Mesalazine as putative drugs of interest for therapeutics in OA for anti-inflammatory properties. We also derived a list of seven gene-targets validated with functional RT-qPCR assays, confirming the in silico predictions. Finally, we identified a predictive subset of genes composed ofDNER, TNFSF11, THBS3, LOXL3, TSPAN2, DYSF, ASPNandHTRA1to compute the patient’s risk score. We validated this risk score on an independent dataset with a high AUC (0.875) and compared it with the same approach computed using the entireconsensussignature (AUC 0.922).Conclusions: Theconsensussignature highlights crucial mechanisms for disease progression. Moreover, these genes were associated with several candidate drugs that could represent potential innovative therapeutics. Furthermore, the patient’s risk scores can be used in clinical settings.

Acute leukemia is the most common pediatric cancer. In most cases, this disease results from the malignant transformation of either the B-cell (B-ALL) or, less frequently, T-cell progenitors (T-ALL). Recently, a marked overexpression of KCTD15, a member of the emerging class of the potassium (K) channel tetramerization domain-containing proteins (KCTDs) has been detected in both patients and continuous cell lines as in vitro model systems. Because there is growing evidence of the key, yet diversified, roles played by KCTDs in cancers, we here report an exhaustive analysis of their expression profiles in both B-ALL and T-ALL patients. Although for most KCTDs, no significant alterations were found in these pathological states, for some members of the family, significant up- and down-regulations were detected in comparison with the values found in healthy subjects in the transcriptome analysis. Among these, particularly relevant is the upregulation of the closely related KCTD1 and KCTD15 in T-ALL patients. Interestingly, KCTD1 is barely expressed in both unaffected controls and B-ALL patients. Therefore, not only does this analysis represent the first study in which the dysregulation of all KCTDs is simultaneously evaluated in specific pathological contexts, but it also provides a promising T-ALL biomarker that could be suitable for clinical applications.

Coronary artery disease (CAD) is a long-term inflammatory process, with atherosclerosis as its underlying pathophysiological mechanism. Endothelial dysfunction is the first step towards atherosclerosis, where damaged endothelial cells release large amounts of pro-inflammatory cytokines and mediators, thus promoting vascular inflammation and disease progression. However, the correlation between serum cytokines and CAD severity remains to be defined. Serum samples from patients performing cardiac computed tomography for suspected CAD (n = 75) were analyzed with a multiplex bead-based immunoassay panel for simultaneous assessment of the concentration of 11 cytokines using flow cytometric technology. The analysis showed statistically significant increases in sRAGE, CCL2_MCP1, FLT1, and IL6 levels in CAD patients compared with healthy subjects and a gradual increase trend towards a more severe form of the disease for most cytokines (e.g., sCD40L, FLT1, sRAGE, CCL2-MCP1, TNFα). Lastly, we explored the performance of cytokines in predicting the diagnosis of CAD and found that an increase in IL6 levels will increase the odds of being non-obstructive CAD-positive. In contrast, an increase in CCL2-MCP1 or FLT1 levels will increase the probability of being obstructive CAD-positive. These results suggest that the combination of serum cytokines may contribute to the not-invasive stratification risk for patients with suspected CAD.

Cardiometabolic and cardiovascular diseases (CVDs) remain the leading cause of death worldwide, with well-established risk factors such as smoking, obesity, and diabetes contributing to plaque formation and chronic inflammation. However, emerging evidence suggests that the immune system plays a more significant role in the development and progression of CVD than previously thought. Specifically, the finely tuned regulation of lymphocyte subsets governs post-injury inflammation and tissue damage resolution and orchestrates the functions and activation of endothelial cells, cardiomyocytes, and fibroblasts in CVD-associated lesions (e.g., atherosclerotic plaques). A deeper understanding of the immune system’s involvement in CVD development and progression will provide new insights into disease biology and uncover novel therapeutic targets aimed at re-establishing immune homeostasis. In this review, we summarize the current state of knowledge on the distribution and involvement of lymphocyte subsets in CVD, including atherosclerosis, diabetes, hypertension, myocardial infarction, and stroke.