# Image based Spatial Transcriptomics to Identify Beta Cell Phenotypes in Type 1 Diabetes

> **NIH NIH R03** · PURDUE UNIVERSITY · 2024 · $150,627

## Abstract

Diabetes mellitus (DM) is a global health challenge that affects nearly 463 million people
worldwide. Type 1 diabetes (T1D) accounts for 5-10% of all diabetes cases and is increasing at
a rate of 2-6% annually. Recent research has challenged the dogma that all β cells are
eventually destroyed in type 1 diabetes (T1D). Emerging data suggest that some cells in long-
duration disease may be protected from autoimmunity owing to the acquisition of a ‘de-
differentiated' phenotype that makes them less visible to the immune system. However, a
consensus definition and the precise phenotype of a de-differentiated cell has yet to be
established. Moreover, the heterogeneity of such a phenotype between single cells within and
between islets and persons with T1D is not clear.
Using single molecule Fluorescence In-situ Hybridization, our preliminary data has revealed
significant heterogeneity of the spatial transcriptome in cells. This project will utilize the newly
emerging tools such as computer vision and artificial intelligence, to deepen the exploration of
the FISH images of human pancreatic tissues. We will develop computational tools and
bioinformatics strategies to understand the spatial distribution of the transcriptome in T1D β cell
phenotypes.
(1) Develop computational tools to process, analyze, and quantify multiplexed transcriptomic
images and proteomic images of pancreatic tissue from human organ donors.
(2) Identify representative features of RNA expression in β cell phenotypes in long-duration T1D
and during T1D evolution with bioinformatics strategies.
Clarifying the molecular phenotype of persistent cells in long-duration disease could have
important implications for T1D therapeutics, and it has the potential to inform the development
of disease modifying interventions aimed at improving the function of these cells.

## Key facts

- **NIH application ID:** 11057346
- **Project number:** 7R03DK135457-02
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** Jing Liu
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $150,627
- **Award type:** 7
- **Project period:** 2024-03-16 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11057346

## Citation

> US National Institutes of Health, RePORTER application 11057346, Image based Spatial Transcriptomics to Identify Beta Cell Phenotypes in Type 1 Diabetes (7R03DK135457-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11057346. Licensed CC0.

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