Multi-omics profiling reveals two distinct trajectories in the progression from mild cognitive impairment to Alzheimer's disease

Abstract

Background

Alzheimer's disease (AD) exhibits significant clinical and pathological heterogeneity, particularly during the mild cognitive impairment (MCI) transitional stage. Current understanding of the molecular drivers underlying distinct MCI progression trajectories remains incomplete, hindering the development of personalized interventions.

Objective

This study aims to integrate transcriptomic, epigenomic, and metabolomic data to identify distinct trajectories in the progression from MCI to AD, and to explore the underlying disease heterogeneity.

Methods

We integrated transcriptomic, epigenomic, and metabolomic data from MCI patients to model the progression to AD and stratified them into subtypes. We then examined molecular differences between MCI and AD within each subtype, identifying key immune microenvironments and regulatory pathways via immune cell infiltration analysis, WGCNA, and GO/KEGG analyses. Finally, we applied Cox regression to identify prognostic biomarkers and built a random forest prognostic model.

Results

Our analysis identified two distinct MCI-to-AD progression subtypes. Subtype 1 was marked by metabolic dysregulation and slower cognitive decline, while Subtype 2 was driven by chronic immune activation and exhibited faster cognitive decline. The trajectory subtypes captured molecular perturbations that were missed by traditional unclustered methods. Prognostic models based on these molecular signatures predicted disease progression over 1–5 years, with AUROC values ranging from 0.851 to 0.893 for Subtype 1 and from 0.878 to 0.927 for Subtype 2.

Conclusions

Our findings highlight the importance of multi-omics trajectory stratification in understanding the heterogeneity of AD progression. The identification of two distinct progression trajectories provides insights into the underlying mechanisms of AD.