Complex diseases are driven by multiple genetic loci interacting with each other and with environmental factors. Rather than utilizing the conventional statistical genetics approach to complex traits in which associations are quantitated for each potential locus and interaction terms determined, we believe that precision medicine mandates a more rigorous quantitative approach that incorporates a causal systems and network analysis, denoted network medicine.
More at: Loscalzo Lab
Dr. Gupta is the recipient of the Sperling Family Fellowship 2019.
Atherosclerosis is the common cause of coronary artery disease, stroke and peripheral vascular disease. These three diseases combined cause over half the deaths and disabilities throughout the world. Coronary artery disease accounts for over 366,000 deaths annually in the United States and is the leading cause of death among both men and women. Stroke and peripheral vascular disease are related vascular conditions with rising rates despite effective therapies to lower cholesterol.
Dr. Gupta’s work is focused on identifying and characterizing Circulating Endothelial Progenitor Cells (CEPCs) which are thought to provide protection and repair the damage to the blood vessels caused by atherosclerosis. The goal of this research is to create a “blood biopsy” for vascular disease which allows to measure blood levels of CEPCs for prevention, diagnosis and treatment of vascular disease.
Genetic diseases affect millions of patients worldwide, and are often life-threatening or chronically debilitating. Early molecular diagnosis and individualized management that targets the underlying pathophysiology can improve the quality of life for many of these patients and reduce medical costs: i.e., Precision Medicine. However, only about half of the clinically described genetic diseases have a clearly identified genetic cause.
We use genome sequencing, functional genomics and disease modeling for the following clinical research projects.
Our efforts contribute to scaling precision medicine to meet the needs of patients. In addition, genes responsible for large effects in genetic disorders may contribute moderate effects to more common forms of the same or related disease phenotypes.
The Maron Cardiovascular and Pulmonary Hypertension Research Laboratory uses systems biology and network medicine to characterize the molecular mechanisms and pathophysiology of cardiopulmonary diseases. Pulmonary vascular disease is a complex and heterogenous collection of disorders that require nuanced approaches to understand and characterize. In this field, there is an emerging need, for example, to couple pathobiology with clinical phenotype on a individual patient level. Developing this strategy, in turn, marks the early phases of precision medicine for patients with pulmonary arterial hypertension, right heart failure, exercise intolerance, and other conditions defined by dysfunction of the lung-pulmonary vascular-right ventricular circuit.
The immune system, and its regulation is the center to a wide range of diseases including autoimmune diseases, cancer, infectious, and even metabolic diseases. Dysregulation of CD4+ T cells leads to greater risk of rheumatoid arthritis, type I diabetes, and tuberculosis. Each of these diseases affect different populations worldwide – but confer disability, morbidity, and mortality even with state of the art treatment.
More at: Immunogenomics at HMS/
We are interested in understanding cardiovascular disease and its risk factors. To make progress in the field we are working to enhance our ability to predict an individual’s risk for cardiovascular disease; studying the complex interactions between an individual’s disease and response to various treatment options and identifying patients most likely to benefit from novel therapies.
We have established several collaborations to develop innovative approaches:
The TARGET Trial is an NIH/NIAMS funded trial that aims to determine which treatments for rheumatoid arthritis reduced cardiovascular risk. Patients with rheumatoid arthritis suffer a 50% increase in cardiovascular risk but there is little known about which treatments are best to reduce this risk. This trial uses FDG PET/CT scanning to assess cardiovascular risk and is collecting a large group of biomarkers to help subset patients into various risk groups. As well, two different randomized treatment arms will facilitate detailed analyses of which patients respond best to different treatments for rheumatoid arthritis.
Rare and undiagnosed diseases of plausible genetic etiology represent the forefront and essence of precision medicine. The constantly arising challenge in the genetic analysis of these cases is whether these rare diseases are caused by individual mutations of very large effects mappable within the paradigm of Mendelian genetics. The additional complexity is due to occasional presence of family members with a much milder form of the same condition, and it is unclear whether the presentation in family members is related to the extreme phenotype of the patient. Currently, we lack a quantitative framework to address this issue.
We analyze unique cases of rare genetic diseases with the overlapping goals to diagnose patients without definitive medical diagnosis, provide clinical recommendations and discover functional roles of poorly characterized human genes.
We are developing a statistical genetics modeling framework to analyze the genetic architecture of extreme phenotypes using large-scale population genetic simulations and clinical sequencing data from patients with unusual presentation.
We are applying our statistical framework as a pilot study to clinical whole exome sequencing data from individuals with extreme levels of risk factors for cardiovascular disease.