Investigating the immunogenetic mechanisms of Alzheimer's disease
- PI
- Yokoyama, Jennifer
- DAR ID
- 11731
- Initial Approval Date
- September 5, 2025
- Current DAR Status
- Expired
- PI Institution
- University of California, San Francisco
- PI Institution Country
- United States
- PI Institution Type
- Non-Profit
Requested Datasets (2)
Research Use Statement
Objectives: The primary aim of this study is to compare how the abundance and expression of immune cells, in the brains of Alzheimer's disease (AD) patients and healthy individuals change stratified on genotype at immune-related genes using the SEA-AD dataset. Secondly, in both SEA-AD and ADSP datasets, we aim to associate SNPs in immune-related genes with clinical and pathological measures.
Study Design: This study will combine the publicly available single-cell sequencing data and WGS data from the SEA-AD dataset, comprising samples from both AD patients and healthy individuals. We will also assess WGS and cognitive data from the ADSP study. We will stratify patients by diagnosis (AD, control). Immune-associated genotypes will be extracted from whole genome sequencing data; gene expression will be quantified from bulk and single-cell transcriptomic data available in the SEA-AD cohort.
Analysis Plan: Using the immune cell data from the SEA-AD datasets, we will identify and characterize different immune cell populations present in the brain samples. Gene expression profiles of immune cells will be analyzed to identify differentially expressed genes (DEGs) between genotypes. This analysis will be conducted using methods such as DESeq2 or edgeR, with adjustments for multiple testing. DEGs will be functionally annotated and subjected to pathway and functional enrichment analysis to elucidate biological processes and pathways associated with immune cell function. We will compare the abundance of immune cell types between individuals with different genotypes using statistical tests such as t-tests or Wilcoxon rank-sum tests and adjust for cofactors through the use of generalized linear models. To assess associations between genetic variants and cognitive outcomes, we will leverage data from ADSP and SEA-AD cohorts, employing linear-mixed effects regression models that control for demographic (race, sex, age, education) and clinical (APOE status) characteristics.
Study Design: This study will combine the publicly available single-cell sequencing data and WGS data from the SEA-AD dataset, comprising samples from both AD patients and healthy individuals. We will also assess WGS and cognitive data from the ADSP study. We will stratify patients by diagnosis (AD, control). Immune-associated genotypes will be extracted from whole genome sequencing data; gene expression will be quantified from bulk and single-cell transcriptomic data available in the SEA-AD cohort.
Analysis Plan: Using the immune cell data from the SEA-AD datasets, we will identify and characterize different immune cell populations present in the brain samples. Gene expression profiles of immune cells will be analyzed to identify differentially expressed genes (DEGs) between genotypes. This analysis will be conducted using methods such as DESeq2 or edgeR, with adjustments for multiple testing. DEGs will be functionally annotated and subjected to pathway and functional enrichment analysis to elucidate biological processes and pathways associated with immune cell function. We will compare the abundance of immune cell types between individuals with different genotypes using statistical tests such as t-tests or Wilcoxon rank-sum tests and adjust for cofactors through the use of generalized linear models. To assess associations between genetic variants and cognitive outcomes, we will leverage data from ADSP and SEA-AD cohorts, employing linear-mixed effects regression models that control for demographic (race, sex, age, education) and clinical (APOE status) characteristics.
Non-Technical Summary
This study aims to understand how immune cells in the brain differ between Alzheimer's disease (AD) patients and healthy individuals, focusing on genetic differences in immune-related genes. Additionally, we will analyze single-cell sequencing and whole genome sequencing (WGS) data to compare immune cell abundance, gene expression, and genetic variation. We will also investigate how specific genetic variations (SNPs) in immune-related genes are linked to clinical and pathological features of AD.
Reported Publications
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
No publications have been reported for this DAR.