Cell-type-specific analysis in Alzheimer’s disease Public
Li, Can (Spring 2020)
Published
Abstract
Background:
Alzheimer’s disease (AD) is one of the chronic neurodegenerative diseases which starts slowly but worsens over time. It has been found that distinct cell types in the brain play different roles in AD etiology and progression.
Methods and Materials:
We estimated cell-type-specific proportions in the brain applying reference-free DNA methylation mixture deconvolution (R/CRAN package RefFreeEWAS) and the newly developed TOAST (Tools for the Analysis of Heterogeneous Tissues, an R/Bioconductor package) statistical method. We detected cell-type specific differential signals between patients with Alzheimer’s and normal controls. Differential methylation calling without consideration of cell mixtures was conducted to compare the results using Bioconductor package Minfi. We conducted the downstream analysis, including pathway/GO analysis and motif analysis using EnrichR
Results:
We assumed there are four brain cell types which are neuron, astrocyte, oligo, microglia during our analysis. We mainly focus on cell type 3 since both Reference-free DNA methylation mixture deconvolution and TOAST statistical method express the lowest average proportion on cell type 3. The average proportion of cell type 3 is 0.0809 (SD=0.0049) for AD patients and 0.0803 (SD=0.0042) for control groups resulted from the Reference-free DNA methylation mixture deconvolution. And the average proportion of cell type 3 generated from the TOAST statistical method is 0.0882 (SD=0.0043) for AD patients and 0.0803 (SD=0.0035) for control groups. The proportions of cell type 1 and 2 are highly negatively correlated to each other with correlation coefficients -0.94 indicating the possible cell type 1 and 2 might be neuron and oligo which are anti-correlated conducted from a recently published paper. The number of DMCs of cell type 3 identified by TOAST is less than that of RefFreeEWAS although it has the least proportions. The biological process regulation of adiponectin secretion has the highest combined score and the neurotransmitter receptor complex is the top cellular component GO term shown in the GO analysis.
Conclusion:
The study reveals that differential analysis could provide insights for diagnostic biomarkers and therapeutic targets and both RefFreeEWAS and TOAST approaches should be encouraged in the practice that future studies could address cell-type-specific idea in AD area.
Table of Contents
Introduction 1
Methods 4
Description of subject and data 4
Proportions Estimation 5
Cell-type specific DM (csDM) test using TOAST 7
Pathway and Gene Ontologies Analysis 9
Results 10
Data Description 10
Estimated cell Proportions 10
DMCs of four unknown cell types in brain, and joint signal analysis 15
Comparison with existing results 16
Pathway Analysis and GO Ontologies Analysis 18
Discussion 20
Conclusion 21
Reference 22
Appendix 24
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