# Identifying Multidimensional Omics Profiles Associated with Cardiovascular and Pulmonary Responses to Chronic and Acute Air Pollution Exposure (Project 2) for AIRHEALTH Study > **NIH NIH P01** · STANFORD UNIVERSITY · 2022 · $508,541 ## Abstract ABSTRACT: PROJECT 2 Lung and cardiac diseases are complex disorders with underlying chronic inflammation, which can be induced or worsened by exposure to air pollution. Thus, understanding the molecular mechanisms by which air pollution activates the immune system and inflammation is essential to developing therapies. The recently reported association of the pro-inflammatory cytokine, IL-1β, with air pollution-linked pulmonary and cardiovascular inflammation presents the hypothesis that IL-1β could be the common mediator of downstream inflammatory immune responses linked to air pollution. Project 1 directly tests the hypothesis that IL-1β or other pathways are induced by air pollution, and examines the effect of air pollution and IL-1β or other pathways on immune cell and lung cell function using blood samples from three well-characterized cohorts that had been exposed to air pollution. Project 3 tests the hypothesis that IL-1β or other pathways are involved in immune signaling in cardiovascular tissue by directly by studying engineered heart cells' function after exposure to plasma samples from the same three cohorts. In Project 2, we will synergize and harmonize our studies with Projects 1 and 3 by developing hypotheses using specific systems biology approaches to understand the molecular circuitry induced by IL-1β in response to chronic and acute air pollution. There will be no redundancy with Project 1 and 3 or core laboratory experiments because we plan to perform unique-omics level experiments on blood samples from the three cohorts. We hypothesize that IL-1β or other pathways induce a gene/protein/metabolite expression response that plays a role in the pathophysiology of air pollution-linked immune system activation. Our results in Project 2 could provide a comprehensive, global view of IL-1β−related and IL-1β non-related responses in blood, lung, and/or cardiac tissues with fine-scale characterization of time-dependent and cytokine- specific response patterns. To characterize this response, we will perform assays to identify abundances of transcripts, proteins, and metabolites in samples from the three cohorts exposed to air pollution. We plan to identify networks of molecules associated or not associated with IL-1β pathways, which are differentially expressed in chronic versus acute air pollution. Our aims are Aim 1. to determine whether IL1α, IL1β, and IL36γ and other markers are upregulated in individuals exposed to air pollution vs healthy control (e.g. cohort with no air pollution exposure time point) in blood, lung, and cardiac tissues; Aim 2. to determine whether ATPases, glucokinase, HSP70, and MAPkinases and other pathways are upregulated in air pollution exposure in blood sample; and Aim 3. to determine whether the metabolites associated with lipid metabolism and lipogenesis are upregulated in air pollution exposure. We expect that our data will generate hypotheses about pathological mechanisms that can be shared collaboratively... ## Key facts - **NIH application ID:** 10460331 - **Project number:** 5P01HL152953-02 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** MICHAEL P. SNYDER - **Activity code:** P01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $508,541 - **Award type:** 5 - **Project period:** 2021-08-01 → 2023-01-13 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10460331 ## Citation > US National Institutes of Health, RePORTER application 10460331, Identifying Multidimensional Omics Profiles Associated with Cardiovascular and Pulmonary Responses to Chronic and Acute Air Pollution Exposure (Project 2) for AIRHEALTH Study (5P01HL152953-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10460331. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*