Rohan completed his medical training from the University College of Medical Sciences (Univ. of Delhi), New Delhi. He worked with the departments of Cardiothoracic Surgery at Mount Sinai, NY and Stanford University for his advanced elective rotations. During his medical school years, he worked on designing and developing novel mechanical heart valves making use of computational fluid dynamics methods and additive manufacturing techniques. His work was funded by the Indian government dept. of biotechnology.
Honors & Awards
Vivien Thomas Early Career Investigator Award - Finalist, American Heart Association (November 2020)
MBBS, University College of Medical Sicences, (Medical Doctorate) (2019)
Rohan Arora. "United States Patent US20170202664A1 Suturing ring for prosthetic heart valves", Dec 11, 2018
Single-Cell Transcriptomic Profiling of Vascular Smooth Muscle Cell Phenotype Modulation in Marfan Syndrome Aortic Aneurysm.
Arteriosclerosis, thrombosis, and vascular biology
OBJECTIVE: To delineate temporal and spatial dynamics of vascular smooth muscle cell (SMC) transcriptomic changes during aortic aneurysm development in Marfan syndrome (MFS). Approach and Results: We performed single-cell RNA sequencing to study aortic root/ascending aneurysm tissue from Fbn1C1041G/+ (MFS) mice and healthy controls, identifying all aortic cell types. A distinct cluster of transcriptomically modulated SMCs (modSMCs) was identified in adult Fbn1C1041G/+ mouse aortic aneurysm tissue only. Comparison with atherosclerotic aortic data (ApoE-/- mice) revealed similar patterns of SMC modulation but identified an MFS-specific gene signature, including plasminogen activator inhibitor-1 (Serpine1) and Kruppel-like factor 4 (Klf4). We identified 481 differentially expressed genes between modSMC and SMC subsets; functional annotation highlighted extracellular matrix modulation, collagen synthesis, adhesion, and proliferation. Pseudotime trajectory analysis of Fbn1C1041G/+ SMC/modSMC transcriptomes identified genes activated differentially throughout the course of phenotype modulation. While modSMCs were not present in young Fbn1C1041G/+ mouse aortas despite small aortic aneurysm, multiple early modSMCs marker genes were enriched, suggesting activation of phenotype modulation. modSMCs were not found in nondilated adult Fbn1C1041G/+ descending thoracic aortas. Single-cell RNA sequencing from human MFS aortic root aneurysm tissue confirmed analogous SMC modulation in clinical disease. Enhanced expression of TGF (transforming growth factor)-beta-responsive genes correlated with SMC modulation in mouse and human data sets.CONCLUSIONS: Dynamic SMC phenotype modulation promotes extracellular matrix substrate modulation and aortic aneurysm progression in MFS. We characterize the disease-specific signature of modSMCs and provide temporal, transcriptomic context to the current understanding of the role TGF-beta plays in MFS aortopathy. Collectively, single-cell RNA sequencing implicates TGF-beta signaling and Klf4 overexpression as potential upstream drivers of SMC modulation.
View details for DOI 10.1161/ATVBAHA.120.314670
View details for PubMedID 32698686
- A Design-Based Model of the Aortic Valve for Fluid-Structure Interaction arXiv preprint. https://arxiv.org/abs/2010.02346. 2020
Use of patient-specific computational models for optimization of aortic insufficiency after implantation of left ventricular assist device.
The Journal of thoracic and cardiovascular surgery
Aortic incompetence (AI) is observed to be accelerated in the continuous-flow left ventricular assist device (LVAD) population and is related to increased mortality. Using computational fluid dynamics (CFD), we investigated the hemodynamic conditions related to the orientation of the LVAD outflow in these patients.We identified 10 patients with new aortic regurgitation, and 20 who did not, after LVAD implantation between 2009 and 2018. Three-dimensional models of patients' aortas were created from their computed tomography scans. The geometry of the LVAD outflow graft in relation to the aorta was quantified using azimuth angles (AA), polar angles (PAs), and distance from aortic root. The models were used to run CFD simulations, which calculated the pressures and wall shear stress (rWSS) exerted on the aortic root.The AA and PA were found to be similar. However, for combinations of high values of AA and low values of PA, there were no patients with AI. The distance from aortic root to the outflow graft was also smaller in patients who developed AI (3.39 ± 0.7 vs 4.07 ± 0.77 cm, P = .04). There was no significant difference in aortic root pressures in the 2 groups. The rWSS was greater in AI patients (4.60 ± 5.70 vs 2.37 ± 1.20 dyne/cm2, P < .001). Qualitatively, we observed a trend of greater perturbations, regions of high rWSS, and flow eddies in the AI group.Using CFD simulations, we demonstrated that patients who developed de novo AI have greater rWSS at the aortic root, and their outflow grafts were placed closer to the aortic roots than those patients without de novo AI.
View details for DOI 10.1016/j.jtcvs.2020.04.164
View details for PubMedID 32653292
- MDCT-based lung volumetry as a prognostic tool-miles to go before we sleep INDIAN JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY 2017; 33 (3): 195–96
EVALUATION OF PARAVALVULAR LEAKAGE IN NOVEL MECHANICAL HEART VALVE
AMER SOC MECHANICAL ENGINEERS. 2017
View details for Web of Science ID 000423244000054