Differential co-expression analysis reveals early stage transcriptomic decoupling in alzheimer's disease

Area of Science:

• Genomics
• Systems Biology
• Neuroscience

Background:

• Alzheimer's disease (AD) is a leading cause of death with no cure.
• Current biomarker discovery for AD yields limited insights into underlying transcriptomic changes.
• Understanding gene co-expression patterns across AD progression is crucial.

Purpose of the Study:

• To explore gene co-expression patterns in cognitively normal (CN), early mild cognitive impairment (EMCI), late MCI, and AD stages.
• To identify stage-specific transcriptomic decoupling during AD progression.
• To discover potential system-level biomarkers for early AD screening.

Main Methods:

• Modified joint graphical lasso (JGL) to model similarities and differences in co-expression networks across consecutive disease stages.
• Network comparison analysis to identify stage-specific transcriptomic decoupling.
• Focused analysis on AD-enriched pathways.

Main Results:

• Identified gene co-expression network changes across AD progression, with significant alterations observed in the AD stage.
• Observed 66 gene pairs with continuously decreasing or increasing co-expression from CN to AD.
• Discovered eight gene modules with altered co-expression patterns, with five showing significant changes from CN to EMCI.

Conclusions:

• A modified JGL model effectively estimated co-expression networks across multiple AD stages, accounting for stage similarity.
• Five gene clusters exhibited significant co-expression pattern changes from CN to EMCI.
• These findings highlight potential system-level biomarkers for early AD screening.