Adam Haber

Adam Haber

Assistant Professor
Departments of Environmental Health and Biostatistics
Harvard T.H. Chan School of Public Health
Adam Haber

Adam is Assistant Professor of Computational Biology and Environmental Health at the Harvard T.H. Chan School of Public Health. His research uses computational approaches to understand the effect of environmental exposures on our lungs, with particular emphasis on asthma. Asthma affects an estimated 1 in 20 people worldwide, and in the US, it is also amongst the diseases with the largest disparity between rich and poor and between white and black folks. Research in Adam’s group therefore pursues two directions: 1. understanding its molecular mechanisms to work towards improved asthma diagnosis and treatment and 2. applying environmental epidemiology to understand its causes and mitigate the exposures that perpetuate disparities in disease burden.

At the molecular level, research in the Haber lab aims to understand how the lung senses and responds to inhaled allergens (aeroallergens) and toxins, which can cause or exacerbate asthma, by applying and developing novel computational methods to analyze ‘multi-omics’ data such as single-cell RNA-sequencing. This work has so far uncovered several new previously unknown subtypes of cells in the lining of the lungs, such as ‘tuft’ cells, which can sense aeroallergens and trigger cascades of inflammatory signaling molecules, or the pulmonary ionocyte, a new cell-type crucial for controlling the mucosal barrier that protects the lungs from the outside world.

At the population level, poor-quality housing has been identified as one of the most important sources of exposures to inhaled toxins and allergens. For this reason, rates of respiratory infections and asthma are markedly higher in poor neighborhoods and in communities of color. To map the role of specific housing units in these disparities, Adam’s research applies machine learning to city-wide, population-level observations of indoor environmental exposures in order to identify complexes which contribute disproportionately to disparities in exposures and disease burden.