# Airway trees in the Anthropocene: Defining resilient airway trees and identifying the candidate mechanisms and etiologic factors that increase susceptibility to tobacco smoke and air pollution > **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $667,649 ## Abstract 11 million lives and 350 million disability-adjusted life-years were lost to tobacco smoke and other noxious pollutants in 2017 (significant increases from 2007). The airway tree is the first line of defense against these ubiquitous noxious agents and, according to textbooks, has a fairly standard anatomy. During the first funding period, we confirmed our primary hypothesis and found that approximately 25% of the general population have airway branch variants that modify susceptibility to cigarette smoke (published in PNAS). Further epidemiologic investigation of airway tree structure on computed tomography (CT) in multiple cohorts demonstrated that variation in native airway tree caliber (“dysanapsis”) is common and predicts incident chronic obstructive pulmonary disease (COPD) better than smoking (published in JAMA) and extends to the terminal bronchioles. These new findings suggest that native airway tree caliber is fundamental to COPD risk and may modify susceptibility to inhale particulates including cigarette smoke. This renewal therefore proposes to 1) establish the early-life origins of airway tree caliber to identify possible modifiable factors, 2) investigate the pathophysiology of increased susceptibility to inhaled noxious agents in adults, and 3) define resilient vs susceptible airway tree structure using clinical outcomes We will use new and existing data, and proven expertise in cohort epidemiology, lung imaging, tobacco and air pollution assessment and gene expression to address the following aims: Aim 1 Using radiation-free innovative MR lung imaging, we will establish the early-life origin of airway tree caliber variation that is physiologically relevant among adolescents (n=100) in a well-characterized mulit-ethnic birth cohort. 1a Explore if smaller airway tree caliber is associated with prospectively ascertained and modifiable early-life factors. Aim 2 Investigate two candidate pathophysiologic mechanisms linking airway tree caliber to increased susceptibility to tobacco smoke and other noxious pollutants: 2a: Mechanism 1 (higher dose delivered): Determine if smaller airway tree caliber is associated with i) higher baseline and prospective accumulation of lung macrophage black carbon content (n=554), and ii) higher systemic biomarker levels of tobacco smoke exposure and inflammation (n=6,570). 2b: Mechanism 2 (impaired airway homeostasis): Determine if smaller airway tree caliber is associated with attenuated basal progenitor cell expression signature among never smokers (n=40) and an ‘exhausted’ basal cell gene expression response to smoking with higher expression of airway inflammation (n=207). Aim 3 Identify the threshold of airway tree caliber that defines resilient versus susceptible airway tree caliber using existing cardiac and full-lung CT measures and clinical outcomes with up to 21 years of follow-up (n=9,664). 3a: Test whether airway tree caliber modifies the risk of death associated with tobacco smoking.... ## Key facts - **NIH application ID:** 10889985 - **Project number:** 5R01HL130506-08 - **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES - **Principal Investigator:** Julie Beth Herbstman - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $667,649 - **Award type:** 5 - **Project period:** 2016-07-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10889985 ## Citation > US National Institutes of Health, RePORTER application 10889985, Airway trees in the Anthropocene: Defining resilient airway trees and identifying the candidate mechanisms and etiologic factors that increase susceptibility to tobacco smoke and air pollution (5R01HL130506-08). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10889985. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*