Mapping the gene regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several outputs at most, biasing discovery and limiting the likelihood of true disease-modifying drug candidates. Here, we developed a machine learning approach to identify small molecules that broadly correct gene networks dysregulated in a human induced pluripotent stem cell (iPSC) disease model of a common form of heart disease involving the aortic valve. Gene network correction by the most efficacious therapeutic candidate, XCT790, generalized to patient-derived primary aortic valve cells and was sufficient to prevent and treat aortic valve disease in vivo in a mouse model. This strategy, made feasible by human iPSC technology, network analysis, and machine learning, may represent an effective path for drug discovery.
Background: Ascending thoracic aortic aneurysm (aTAA) is a heterogeneous group of disorders that involve impaired endothelial function. The nitric oxide (NO) synthase inhibitor asymmetric dimethylarginine (ADMA) serves as an endothelial dysfunction marker. Thus, we investigated ADMA levels in patients with aTAA. Methods: Eighty-six patients with aTAA and 18 healthy individuals were enrolled. All patients underwent echocardiography. Plasma ADMA levels were measured using high-performance liquid chromatography. Results: ADMA levels were higher in aTAA patients than in control patients (p = 0.034). According to the multivariable regression model, higher ADMA levels were associated with ascending aortic diameter (p = 0.017), smoking (p = 0.016), and log-transformed estimated glomerular filtration rate (eGFR, p = 0.005). Conclusion: This pilot study demonstrates an association of ADMA with ascending aortic dilatation; however, further studies are needed to investigate whether increased ADMA levels underlie aTAA development.
The quadricuspid aortic valve is a very uncommon malformation associated with aortic insufficiency, aortic stenosis, endocarditis, and ascending aortic dilatation. We report four cases of this aortic valve malformation. One patient with severe aortic regurgitation and moderate aortic dilatation required aortic valve replacement. Three patients had mild or moderate aortic insufficiency combined with moderate ascending aortic dilatation. These patients were referred to follow-up. The presented cases demonstrate that this aortic valve malformation may not be as rare as it appears and that attention must be paid to any quadricuspid findings during computed tomographic angiography and echocardiography.
According to different systematic reviews incidence of thoracic aortic aneurysms (TAA) in the general population is increasing in frequency ranging from 5 to 10.4 per 100000 patients. However, only few studies have illustrated the role of different risk factors in the onset and progression of ascending aortic dilatation. Currently, noninvasive imaging techniques are used to assess the progression rate of aortic and aortic valve disease. Transthoracic (TT) Echocardiographic examination routinely includes evaluation of the aorta It is the most available screening method for diagnosis of proximal aortic dilatation. Since the predominant area of dilation is the proximal aorta, TT-echo is often sufficient for screening. We retrospectively analyzed the ECHO database with 78499 echocardiographic records in the Almazov National Medical Research Centre to identify patients with aneurysm. Detailed information including demographic characteristics, ECHO results and comorbidities were extracted from outpatient clinic and from hospital charts related to hospitalizations occurring within a year before index echocardiography was performed. Comorbid diseases were similarly extracted from outpatient clinic and/or hospital admissions. The classifier showed an AUC-ROC for predicting of aneurism detection after a repeated ECHO at 82%.
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