Biomarkers

Area of Science:

• Neurogenetics
• Cognitive Neuroscience
• Alzheimer's Disease Research

Background:

• Memory performance is a key indicator for Alzheimer's disease (AD).
• The genetic underpinnings connecting brain structure/function and memory are not well understood.
• Neuroimaging studies have explored memory correlates, but genetic relationships require further investigation.

Purpose of the Study:

• To investigate the genetic covariance between brain imaging-derived phenotypes (IDPs) and memory performance/decline.
• To identify specific neuroimaging features with significant genetic overlap with memory.
• To explore potential genetic links between AD-vulnerable brain regions and memory.

Main Methods:

• Utilized GeNetic cOVariance Analyzer (GNOVA) to analyze genome-wide association study (GWAS) summary statistics.
• Integrated data from large-scale GWAS on 3,143 imaging-derived phenotypes (IDPs) from UK Biobank and memory performance/decline from four aging cohorts (ACT, ADNI, NACC, ROSMAP).
• Stratified analyses by imaging modality (dMRI, T1-weighted MRI, rs-fMRI) to identify top IDPs genetically correlated with memory.

Main Results:

• Significant genetic covariance found between memory and various brain regions, including the uncinate fasciculus, cingulate gyrus, and posterior collateral sulcus.
• Resting-state functional MRI (rs-fMRI) components showed overlap with the Default Mode Network and Visual Network.
• Top associations were concentrated in the medial temporal lobe and adjacent structures, mirroring AD vulnerability patterns.

Conclusions:

• Genetic covariance analyses reveal broad associations between multimodal brain imaging and memory.
• Identified brain regions and networks, beyond the hippocampus, genetically linked to memory performance.
• Findings suggest potential new neural correlates for AD biomarker development, particularly within default mode network-associated regions.