# Exploring Gene Expression Patterns in Alzheimer’s Disease Using a Human Microarray Data Meta-Analysis

## TL;DR

This study uses a meta-analysis of microarray data to identify gene expression changes in Alzheimer’s disease, revealing immune activation and reduced synaptic activity.

## Contribution

The study provides a comprehensive meta-analysis of gene expression in Alzheimer’s disease, identifying potential biomarkers for early diagnosis and treatment.

## Key findings

- Alzheimer’s disease shows increased activity in immune-related genes and decreased activity in synaptic communication genes.
- A total of 4218 differentially expressed genes were identified, with 1944 up-regulated and 2274 down-regulated.
- The findings suggest immune response and inflammation are prevalent in Alzheimer’s, while synaptic and neuronal signaling is impaired.

## Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder that progressively damages the brain; however, there is currently no cure or easy way to diagnose AD early. This study aims to discover specific differences in gene activity in the brain of AD and identify genes that can serve as risk factors for disease or biomarkers of diagnostic, prognostic, or pharmacological value. Through the re-analysis and meta-analysis of data from multiple existing studies, a combined list of genes that have a statistically significant change in expression was produced. The results showed that genes responsible for communication between brain cells are less active in the AD brain. In contrast, genes involved in the body’s immune defense and inflammation are more active. These findings are valuable as the tracking of these specific gene changes could provide insights into earlier Alzheimer’s diagnosis and improved patient treatment.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder worldwide, for which aging represents the main risk factor. As the global elderly population expands, the prevalence of Alzheimer’s disease escalates rapidly. Notably, as AD brain lesions may start 15–20 years before the appearance of the first symptoms, early diagnosis or prognosis of AD is of paramount importance for better patient treatment. Based on the absence of effective cure or early diagnosis of AD, this meta-analysis investigates the differentially expressed genes between Alzheimer’s and a healthy brain and identifies genes that can serve as risk factors for the disease or biomarkers of diagnostic, prognostic, or pharmacological value. Microarray datasets were collected from public repositories, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. Quality control and data normalization were performed. Differentially expressed gene (DEG) lists were created for each study and combined through a Mosteller–Bush meta-analysis, resulting in a final list of DEGs. This list was filtered using an adjusted p-value cut-off of 0.001, and the included statistically significant DEGs were subjected to enrichment analyses. A total of eight microarray studies were identified, producing a combined list of 4218 DEGs, of which 1944 were up-regulated and enriched for immune response processes, and 2274 were down-regulated and enriched for synapse-related pathways. This meta-analysis reveals a distinct transcriptomic profile in Alzheimer’s disease characterized by the prevalence of immune response and inflammation alongside the collapse of essential synaptic and neuronal signaling.