Acute dissections and ruptures of aortic aneurysms comprise for 1-2% of all deaths in industrialized countries. Dilation of the aorta is caused by a multitude of mechanisms including inherited connective tissue disorders such as Marfan, Loeys-Dietz or Ehlers-Danlos syndrome. The majority of these diseases eventually lead to an acute aortic dissection, a life-threatening condition with a mortality rate of 1% per hour without surgical intervention.
Assessment of the activity of aortic aneurysms is almost exclusively based on repeated imaging but it is very difficult to predict which patients will ultimately develop an aortic dissection. So far, prophylactic surgery is the only way to save these patients. In the patient with acute chest pain, there can be a considerable overlap with symptoms of other life-threatening diseases such as an acute coronary syndrome or acute pulmonary embolism. In the patient with known aortic aneurysms it is difficult to predict if medical therapy is successful, if there is any reduction of the activity of the aneurysm that will make surgery unnecessary, despite an enlarged aorta.
Our work addresses a clinically relevant and pressing need to find a biomarker that (i) would enable us to identify the patient at risk for a dissection among patients with known aortic aneurysms (ii) facilitate diagnosis of aortic dissection in the patient with acute chest pain and (iii) helps us to individualize therapy.
In our current work, we use proteomics techniques in an advanced animal model of aortic aneurysms and dissections to gain insight into these mechanisms and validate the findings in a large population of patients with aortic diseases.