# Gene Co-Expression Analysis Reveals Functional Differences Between Early- and Late-Onset Alzheimer’s Disease

## TL;DR

This study finds that early- and late-onset Alzheimer’s disease have distinct molecular patterns, which may affect how the disease progresses.

## Contribution

The study introduces a novel approach using gene co-expression networks to uncover functional differences between early- and late-onset Alzheimer’s disease.

## Key findings

- Early- and late-onset Alzheimer’s disease show distinct gene co-expression network structures.
- Network modularity analysis reveals unique biological features associated with each disease subtype.
- Age at onset influences molecular pathways linked to cognitive decline in Alzheimer’s disease.

## Abstract

The rising prevalence of Alzheimer’s disease (AD), particularly among older adults, has driven increased research into its underlying mechanisms and risk factors. Aging, genetic susceptibility, and cardiovascular health are recognized contributors to AD, but how the age of onset affects disease progression remains underexplored. This study investigates the role of early- versus late-onset Alzheimer’s disease (EOAD and LOAD, respectively) in shaping the trajectory of cognitive decline. Leveraging data from the Religious Orders Study and Memory and Aging Project (ROSMAP), two cohorts were established: individuals with early-onset AD and those with late-onset AD. Comprehensive analyses, including differential gene expression profiling, pathway enrichment, and gene co-expression network construction, were conducted to identify distinct molecular signatures associated with each cohort. Network modularity learning algorithms were used to discern the inner structure of co-expression networks and their related functional features. Computed network descriptors provided deeper insights into the influence of age at onset on the biological progression of AD.