Aortic dilatation diseases comprise a spectrum of high‑mortality vascular disorders that include aortic dissection, aortic aneurysm and pseudoaneurysm. These conditions are principal causes of acute aortic syndromes. The clinical burden is substantial because dilation of the aortic wall can progress silently and then present catastrophically with dissection or rupture.
The reviewed article frames these disorders as complex, multifactorial diseases in which structural and cellular changes in the aortic wall underlie clinical events. The authors emphasize the urgent need for earlier detection, improved risk stratification and therapies targeted to underlying mechanisms to reduce mortality.
At the tissue and cellular level, disease progression in aortic dilatation involves several interacting processes. Key mechanistic contributors described are phenotypic switching of vascular smooth muscle cells (VSMCs) and VSMC death, which compromise aortic wall integrity. Concurrently, local vascular wall inflammation drives further tissue injury and remodeling. Degradation of the extracellular matrix (ECM)—with loss of structural proteins and disruption of matrix architecture—fosters dilation and increases susceptibility to dissection or rupture.
These mechanisms act in concert rather than in isolation; VSMC dysfunction, inflammatory cell infiltration and ECM breakdown create a feed‑forward cycle that promotes progressive dilatation and acute events.
Genetic predisposition is an important determinant of susceptibility to aortic dilatation diseases. Inherited factors interact with environmental and clinical risks to influence disease onset and progression. Among conventional, modifiable risk factors, hypertension and smoking are highlighted as major contributors. The review makes clear that both genetic and acquired risks should be considered in efforts to identify high‑risk individuals and to design personalized interventions.
Recent progress in basic research has been accelerated by technologies that offer higher resolution and system‑level views of disease biology. The review identifies multi‑omics approaches, single‑cell sequencing and molecular imaging as important drivers of new insights. These tools enable detailed mapping of cell states, molecular pathways and spatial organization within diseased aortic tissue, opening opportunities for identifying mechanistic biomarkers and potential therapeutic targets.
Such technologies also support discovery of candidate markers for early disease, provide means to study heterogeneity between patients, and facilitate mechanistic hypotheses that can be tested in experimental systems.
Translation of basic findings into clinical tools has focused on biomarker screening and methods for risk stratification. The review notes that multi‑modal molecular readouts and imaging markers are being evaluated as potential diagnostic and prognostic indicators. These translational efforts aim to enable earlier recognition of patients at imminent risk of dissection or rupture and to tailor surveillance and treatment intensity accordingly.
However, the authors emphasize that many candidate biomarkers remain at the discovery stage and require standardized validation before clinical use can be recommended.
Mechanism‑driven therapeutic strategies are a logical extension of improved biological understanding. The review discusses development of targeted interventions grounded in insights about VSMC behavior, inflammation and ECM remodeling. Despite this, the clinical evidence base for specific targeted drugs remains insufficient. The authors report that robust clinical trials demonstrating efficacy of mechanism‑based agents in aortic dilatation diseases are lacking or incomplete.
Consequently, while promising targets have emerged from preclinical and translational studies, translation into validated, widely adopted therapies has been limited.
The review identifies several major obstacles to successful clinical translation. First, there is a shortage of standardized, validated biomarkers suitable for routine clinical application. Second, clinical evidence supporting targeted pharmacologic interventions is inadequate. Third, notable differences between animal models and human disease present challenges: animal systems often fail to fully recapitulate human aortic biology and disease progression, limiting the predictive value of preclinical results.
These bottlenecks slow the path from mechanistic discovery to improved patient outcomes.
To overcome current limitations, the authors call for integrated strategies that combine multi‑omics, advanced imaging, bioengineering and artificial intelligence. Such integration could enable earlier identification of disease, more precise patient stratification and individualized intervention planning. The review suggests that coordinated application of these technologies may improve biomarker validation, enhance understanding of patient heterogeneity, and support design of personalized therapies.
The authors advocate continued investment in translational pipelines that bridge mechanistic discovery with standardized validation studies and well‑designed clinical trials.
Aortic dilatation diseases are lethal vascular disorders driven by VSMC dysfunction and death, vascular inflammation and ECM degradation, with genetic and acquired risk factors such as hypertension and smoking modifying risk. Advances in multi‑omics, single‑cell sequencing and molecular imaging have advanced mechanistic understanding and supported translational research into biomarkers, risk stratification and targeted intervention. Nevertheless, key gaps remain: lack of standardized biomarker validation, insufficient clinical evidence for targeted drugs, and important animal‑to‑human differences. The review recommends integrated, multidisciplinary efforts—combining omics, imaging, bioengineering and AI—to enable early detection, precision stratification and individualized treatment for patients with aortic dilatation diseases.