# Clinical Phenotyping and Molecular Integration Core > **NIH NIH U19** · NORTHWESTERN UNIVERSITY · 2024 · $619,882 ## Abstract PROJECT SUMMARY Clinical Phenotyping and Molecular Integration Core (Core B) Our innovative application seeks to understand the how heterogeneity neutrophil populations in the lung impact pneumonia and asthma development and outcomes by intersecting large scale clinical data collected during the course of care for people with severe pneumonia with high-dimensional genomic, transcriptomic and functional data. The overall goal of the Clinical Phenotyping and Molecular Integration (CPMI) Core is to curate patient samples at participating sites and develop and implement strategies that support phenotypic and mechanistic characterization of patient participants by integrating information from electronic health record (EHR) data, multi- omics, spatial-transcriptomics and neutrophil functional studies. This core, which will sit at the heart of the Neu- Lung project, will have sites at both Northwestern University (NU) and National Jewish (NJH), which will be responsible for development of datasets for the pneumonia and asthma samples, respectively. While the NU core will focus on a set of previously collected samples and associated clinical data, the team at NJ will collect samples from asthma patients during the course of Neu-Lung. Both sites in the CPMI will then apply a similar analysis pipeline 1) clean and curate clinical samples and data, 2) integrate clinical and molecular profiling data for each patient and 3) apply effective machine learning strategies to develop models of neutrophil behavior in the context of their lung disease focus area. The design of this core is based on the premise that data captured during the course of clinical care that provides a thorough description of the patient and their environment are essential for understanding the results of functional and multi-omic analyses and identifying clinically and mechanistically relevant subpopulations of patients. Achieving the goals of this project will require tight integration of clinical and molecular profiling data and the development of novel machine learning strategies that can translate a complex set of multi-dimensional datasets into interpretable and actionable information to support clinical care and mechanistic studies. In particular, we will leverage tailor- made algorithms for an integrative analysis of multiple omics data sets with clinical that enable modeling of the underlying gene regulatory networks. Datasets and metadata will be archived in the appropriate NIAID and/or NCBI archives and computational tools will be made available for broader use through a GitHub repository. In addition, we will develop web-based tools that will allow Neu-Lung researchers to interact with the study data repository and both browse and analyze the collected data. Aim 1: Curate clinical samples and metadata from patients with severe pneumonia and lung transplant recipients. Aim 2: Collect and curate clinical samples from patients with asthma. Aim 3: Implement a data integration-analys... ## Key facts - **NIH application ID:** 10824510 - **Project number:** 1U19AI181102-01 - **Recipient organization:** NORTHWESTERN UNIVERSITY - **Principal Investigator:** Theresa L Walunas - **Activity code:** U19 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $619,882 - **Award type:** 1 - **Project period:** 2024-04-01 → 2029-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10824510 ## Citation > US National Institutes of Health, RePORTER application 10824510, Clinical Phenotyping and Molecular Integration Core (1U19AI181102-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10824510. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*