Dr. Bradley A. Maron

Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

Dr. Bradley Maron is an Associate Professor of Medicine at Harvard Medical School, Associate Physician in the Division of Cardiovascular Medicine at Brigham and Women’s Hospital, and Co-director of the Pulmonary Vascular Disease Center at the Boston VA Healthcare System. His laboratory focus involves utilizing network medicine and systems biology to characterize the pathobiological mechanisms underpinning pulmonary vascular disease. Through these approaches, Dr. Maron identified a critical cysteinyl thiol redox switch in the CAS protein NEDD9 that regulates endothelial collagen synthesis and vascular fibrosis in pulmonary arterial hypertension. This has, in turn, emerged as a potentially modifiable treatment target using small molecule technology. His group recently developed a novel risk assessment code for patients with exercise intolerance, which was based on a network analysis of patient-level clinical data. In related work, he lead a national team of investigators focusing on the cardiopulmonary hemodynamic spectrum of risk, and findings from this effort directly contributed to re-establishing the appropriate pulmonary artery pressure range used to diagnose pulmonary hypertension. Dr. Maron has co-authored numerous scientific manuscripts and is the lead editor of a recently published textbook on pulmonary vascular disease. His work is funded by the National Institutes of Health, American Heart Association, Cardiovascular Medical Research and Education Foundation, Scleroderma Foundation, and the Klarman Family Foundation. He is also the recipient of the distinguished Eleanor and Miles Shore Scholar in Medicine, American Society of Clinical Investigator Young Physician-Scientist Award, and the Harvard Medical School Excellence in Teaching award.


Day 2: September 12, 2019 | Session 1 | 11:00 AM - 11:20 AM

Network Medicine, Risk Stratification, and Pulmonary Hypertension

Bradley A Maron, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.

Pulmonary hypertension (PH) is a highly morbid cardiovascular disease that leads to heart failure and early death but often presents with non-specific symptoms, particularly unexplained dyspnea (UD). Early diagnosis of PH is associated with improved mortality; however, optimal methods for prognosticating patients with UD at risk for PH are lacking. We used network medicine to develop a unique model that integrates exercise measurements previously unrecognized as useful for classifying UD patients (Circ Res 2018;122:864-876). Specifically, data from 738 patients referred for invasive cardiopulmonary exercise testing, which is the gold standard clinical tool for patients with UD were analyzed retrospectively. From an exercise correlation network of 39 variables and 98 edges (|r|>0.5, P<10-40), we identified an informative subnetwork of 10 nodes. K-mean clustering based on these ten clinical variables identified 4 novel patient groups characterized by unique exercise and clinical profiles. Compared to a probabilistic model, the network model was less redundant and more effective at delineating exercise subtypes. Cluster assignment from the network was predictive of future hospitalization and mortality. From these data, we developed a novel point-of-care risk calculator for UD patients based on Euclidian geometry rather than logistical regression, which was validated in a second (international) cohort. In conclusion, network medicine was used to decipher unexpected relationships between clinical variables and prognosticate patients at-risk for PH. Overall, this work demonstrates the utility of applying network medicine to develop patient-level risk assessment models that are applicable to complex phenotypes.