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| Funder | NATIONAL HEART, LUNG, AND BLOOD INSTITUTE |
|---|---|
| Recipient Organization | University of California, San Diego |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2029 |
| Duration | 1,825 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10975746 |
PROJECT SUMMARY The tremendous diversity across human lung diseases presents significant clinical challenges, but also offers remarkable opportunities for capturing high-resolution disease mechanisms to more effectively treat these conditions. Adhering to the mission of LungMAP phase II, our Research Center has generated, curated,
and made publicly available a rich array of high-quality single nucleus RNAseq and single nucleus ATACseq datasets, focusing on normal developing lung and pediatric lung diseases. In LungMAP phase III, with the extension into adult lung diseases, we will leverage our expertise on lung biology and single cell technologies
to embark on direct cross-disease comparisons, a recognized bottleneck in the next-stage disease mechanism discoveries. We have assembled an interdisciplinary team with strong expertise in lung biology, pulmonology, surgery, pathology, single cell technology and computational biology, with a track record of working together
within and beyond the LungMAP consortium. Guided by the scientific premise that different lung diseases can be distinguished by a finite set of signatures, we will test the hypothesis that these diseases differ in cell type/cell state composition, transcriptomic and epigenomic profiles, signaling and extracellular matrix
dynamics, among other dimensions. Capturing cutting-edge technologies, we present robust preliminary data demonstrating the feasibility of using single nucleus Multiome (RNAseq and ATACseq from the same nucleus) and spatial transcriptomic MERFISH (Multiplexed Error-Robust Fluorescence in situ Hybridization)
technologies on tissues procured using an ultra-low ischemia time protocol. Critical to achieving precise cross- disease comparisons, we show preliminary data demonstrating effective addition of multiplexing to these technologies, which eliminated batch effect which was the major roadblock in previous comparison efforts. We
expect that the datasets that we will generate and make publicly available in LungMAP phase III will facilitate paradigm-shifting studies by the collective lung research community.
University of California, San Diego
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