# Core B: Human and Clinical Phenotyping Core

> **NIH NIH P01** · NORTHWESTERN UNIVERSITY · 2024 · $503,232

## Abstract

PROJECT SUMMARY CORE B
Core B has the overarching goal of supporting the Scientific Projects by providing reliable and readily available
clinical data from patients and will support the Project Investigators by collecting, processing, and analyzing a
rich multi-omics dataset from patients undergoing lung transplantation. Investigators in the Core will collect
detailed clinical data from lung transplant recipients and manually adjudicate clinical episodes and the diagnosis
of PGD and CLAD. Core B investigators will identify clinical and research procedures that will generate biologic
material and enroll patients in observational studies. Core B will work synergistically with the Core C investigators
to process the samples to generate single cell suspensions that will be analyzed using flow cytometry and single
cell RNA-sequencing/CITE seq, paired fixed tissue for spatial transcriptomics, and other assays. Core B will
apply robust machine learning approaches to organize clinical data and use this framework as a scaffold to
overlay longitudinally collected genomic and proteomic data collected over the clinical course of transplantation.
The resulting models of clinical PGD and CLAD will be used to identify biomarkers and generate hypotheses
about biologic pathways that will be causally tested in the Projects, credentialling the pathways as therapeutic
targets. Hence, Core B will directly support the Projects through the following aims. Aim 1. To enroll lung
transplant recipients for prospective tissue collection and data integration throughout longitudinal care.
We have developed integrated clinical and research teams to enable patient enrollment and collection of events
over the clinical course of patients. The clinical data extracted from the electronic health record will complement
the molecular phenotyping data and enable the Scientific Projects to test the hypotheses outlined. This integrated
model will facilitate the identification of biomarkers and clinical predictors of transitions in clinical state after
transplantation. Aim 2. To process, immunophenotype, and cryopreserve biological material from the lung
and esophagus collected as part of clinical care or research. We will leverage our experience with sample
collection, processing, flow cytometry, single cell RNA-sequencing, metabolomic and spatial transcriptomic
profiling to develop a robust multi-omics dataset of patients undergoing lung transplantation. Aim 3. To perform
next-generation sequencing assays, including single-cell RNA-seq, CITE-seq, and single cell TCR and
BCR clonotyping as well as spatial transcriptomics on selected samples. A major challenge in data science
has been the integration of large-scale datasets coming from multiple groups. Through collaborations with the
Chan Zuckerberg Human Cell Atlas Consortium, we have contributed to approaches based on transfer learning
that allow integration of single cell transcriptomic data rapidly and at scale. We will apply these ap...

## Key facts

- **NIH application ID:** 10933921
- **Project number:** 1P01HL169188-01A1
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Benjamin David Singer
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $503,232
- **Award type:** 1
- **Project period:** 2024-09-17 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10933921

## Citation

> US National Institutes of Health, RePORTER application 10933921, Core B: Human and Clinical Phenotyping Core (1P01HL169188-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10933921. Licensed CC0.

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