Brain-Specific Gene Expression and Quantitative Traits Association Analysis for Mild Cognitive Impairment

Area of Science:

• Neuroscience
• Genetics
• Computational Biology

Background:

• Transcriptome-wide association studies (TWAS) have linked genes to qualitative traits.
• Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease (AD), necessitating early detection and intervention strategies.

Purpose of the Study:

• To perform TWAS on quantitative traits in brain subcortical structures of MCI patients.
• To identify novel genes associated with MCI progression and explore their potential as therapeutic targets.
• To investigate the predictive value of baseline brain structure volumes and genetic factors for MCI conversion risk.

Main Methods:

• TWAS was conducted on gene expression and quantitative traits in six brain subcortical structures from 286 MCI patients (ADNI cohort).
• Longitudinal correlations between gene expression and quantitative traits were analyzed.
• Single-Nucleotide Polymorphism (SNP) analysis, including cis-expression Quantitative Trait Loci (cis-eQTL) analysis, was performed.
• Machine learning models were used to predict MCI conversion risk based on brain volumes and cis-eQTL SNPs.

Main Results:

• Identified 9, 15, and 6 stably correlated genes in the limbic, basal ganglia, and cerebellum regions, respectively.
• Discovered 3, 8, and 6 novel genes in these regions not previously associated with AD or MCI.
• Limbic region volumes and cis-eQTL SNPs of correlated genes demonstrated effective predictive ability for MCI conversion.

Conclusions:

• Novel genes associated with quantitative traits in brain subcortical regions of MCI patients were identified.
• These genes represent potential therapeutic targets for early-stage Alzheimer's disease.
• Limbic structure volumes and specific genetic markers are valuable predictors of MCI progression.