Gene-based aggregate SNP associations between candidate AD genes and cognitive decline

Area of Science:

• Neurogenetics
• Cognitive Neuroscience
• Aging Research

Background:

• Numerous single nucleotide polymorphisms (SNPs) in specific genes have been linked to Alzheimer's disease (AD) risk.
• The association between these established AD-risk genes and longitudinal cognitive decline remains less understood.
• Investigating aggregate genetic variation within these regions offers a novel approach to understanding cognitive trajectories.

Purpose of the Study:

• To determine if established Alzheimer's disease (AD)-associated genes are linked to longitudinal cognitive decline.
• To examine aggregate genetic variation across known AD-risk gene regions.
• To identify specific gene regions and SNPs associated with cognitive decline in older adults.

Main Methods:

• Utilized two single-sex cohorts of community-dwelling older adults.
• Employed the Sequence Kernel Association Test (SKAT) to assess aggregate SNP associations within gene regions and cognitive decline.
• Conducted univariate analyses for significant gene regions to identify individual SNP associations.

Main Results:

• Aggregate-level associations between cognitive decline and gene regions BIN1, CD33, CELF1, CR1, HLA cluster, and MEF2C were found in the all-female cohort.
• Significant aggregate associations were observed for ABCA7, HLA cluster, MS4A6E, PICALM, PTK2B, SLC24A4, and SORL1 in the all-male cohort.
• Specific blocks of correlated SNPs in CD33 and CELF1 showed univariate associations with cognitive decline in the all-female cohort.

Conclusions:

• Aggregate genetic variation in several AD-associated gene regions is linked to longitudinal cognitive decline, with some sex-specific patterns.
• While many AD-associated SNPs were not individually linked to cognitive decline, the broader gene regions show significant associations.
• These findings highlight the complex genetic architecture influencing cognitive aging and AD risk.