# Computational Analysis of CD8 T Cells Using Single Cell Sequencing

> **NIH NIH R15** · UNIVERSITY OF CALIFORNIA, MERCED · 2020 · $110,583

## Abstract

PROJECT SUMMARY
Autoimmunity is a complex disorder affecting over 20 million Americans. Unveiling the multi-step process
leading to autoimmunity and ultimately the ability to effectively treat disease requires an in-depth
understanding of the self-reactive lymphocytes and the mechanisms by which they evade tolerance and
promote destruction of self-tissue. Although there has been a large accumulation of quantitative data on the
dynamics of CD8 T cell responses following infection, much less is known about how naive CD8 T cells
differentiate into various effector pathways, nor about global CD8 T cell gene expression changes during
autoimmune disease. Our proposal seeks to combine experimental, computational and mathematical
approaches to understand the initiation and development of autoimmune disease by analysis of CD8 T cells.
Using well-characterized, tractable experimental models of autoimmune disease, we will test, refine and
validate previously published CD4 T cell differentiation mathematical models to develop a model of CD8 T cell
differentiation and dysregulation during the autoimmune disease process. Aim 1 will quantitatively define the
gene expression kinetics in spontaneous autoimmune models with multiple disease manifestations. In Aim 2
we will expand this evaluation to several autoimmune models with some overlapping and distinct autoimmune
disease outcomes to systematically define the genes and pathways that underlie immune abnormalities critical
to the development of individual diseases and those that underlie multiple diseases. We will further compare
these data to published patient data to focus on clinically relevant genes. In Aim 3 we will combine the results
of Aim 1 and 2 to mathematically model CD8 T cell gene expression kinetics, and validate this model using
mouse in vivo disease studies. This mathematical model will enable us to predict the gene signatures driving
CD8 T cell fate choices and triggering autoimmunity.

## Key facts

- **NIH application ID:** 9981905
- **Project number:** 3R15HL146779-01S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, MERCED
- **Principal Investigator:** Katrina K Hoyer
- **Activity code:** R15 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $110,583
- **Award type:** 3
- **Project period:** 2020-03-09 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9981905

## Citation

> US National Institutes of Health, RePORTER application 9981905, Computational Analysis of CD8 T Cells Using Single Cell Sequencing (3R15HL146779-01S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9981905. Licensed CC0.

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