# Spatiotemporal Atlas of Cellular Networks and Ultrastructural States Mediating the Progression and Resolution of Pulmonary Fibrosis

> **NIH NIH F32** · STANFORD UNIVERSITY · 2023 · $69,500

## Abstract

PROJECT SUMMARY
Pulmonary fibrosis (PF) represents a global clinical burden that affects over 5,000,000 people and can occur as
a result of chemical injury, chronic conditions such as systemic sclerosis, or respiratory infections such as
influenza and COVID-19. Commonly, PF has no clinically determinable cause and is diagnosed as idiopathic
PF, which presents a median survival time of only 2-4 years after diagnosis. Given the often unclear
pathogenesis of PF, there exists a strong clinical need to elucidate the biological mechanisms that contribute to
its onset and progression. Nevertheless, the factors that drive spatial heterogeneity and temporal progression in
fibrotic architecture are not well understood. Furthermore, the post-fibrotic resolution of aberrant PF matrix
remains an elusive goal, for which no single-cell characterizations have been performed to date. Thus, this
project aims to establish a spatiotemporal atlas of PF progression that links multi-omics with spatially
defined tissue neighborhoods and temporally defined architectural states of fibrosis and post-fibrotic
resolution.
Mesenchymal cell populations play a critical role in the fibrosis of all major organs, with a number of macrophage
and fibroblast subtypes often implicated as mediators of fibrotic ECM deposition. Based on prior studies, I
hypothesize that transcriptionally defined macrophage and fibroblast subtypes act as both spatial and temporal
nodes of fibrosis and post-fibrotic resolution. To investigate this hypothesis, this project will establish a novel
computational atlas of transcriptional/epigenetic cell subtypes, interaction networks, and ultrastructural states
that mediate the pathological progression of PF and post-fibrotic repair in mice. Specific Aim 1 will investigate
the roles of transcriptionally defined cell subpopulations in the temporal progression and resolution of fibrotic
pulmonary architecture, using high-throughput multi-omics (transcriptomic, epigenomic, and ultrastructural) and
computational modeling of biological variations over time. Specific Aim 2 will define the spatial tissue
neighborhoods of cell- and matrix- mediated interactions in pulmonary fibrosis, by integrating Visium spatial
transcriptomics, imputed spatial epigenomics in BABEL, and ultrastructural quantification on consecutive
histological slices. Specific Aim 3 will develop a machine learning algorithm for prognosis of clinical outcomes in
human pulmonary fibrosis, by unifying histopathological architecture, protein and cell spatial networks, and
clinical metadata. Ultimately, this project will establish a multi-omic, cross-species, and computationally rigorous
atlas of PF progression and repair that identifies biologically conserved mechanistic pathways and clinically
relevant targets for prognosis and therapeutic development.

## Key facts

- **NIH application ID:** 10600647
- **Project number:** 1F32HL167318-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Jason Liwei Guo
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $69,500
- **Award type:** 1
- **Project period:** 2023-07-18 → 2026-07-17

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10600647

## Citation

> US National Institutes of Health, RePORTER application 10600647, Spatiotemporal Atlas of Cellular Networks and Ultrastructural States Mediating the Progression and Resolution of Pulmonary Fibrosis (1F32HL167318-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10600647. Licensed CC0.

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