Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

Area of Science:

• Genetics
• Neuroscience
• Molecular Biology

Background:

• Stroke is a leading cause of death globally, particularly in individuals over 60.
• Both genetic and environmental factors contribute to stroke's complex pathogenesis.
• Previous genome-wide association studies (GWAS) identified stroke-related genetic loci, but their functional mechanisms remain largely unknown.

Purpose of the Study:

• To explore the molecular function of single-nucleotide polymorphisms (SNPs) associated with stroke.
• To identify specific genes and SNPs linked to various stroke subtypes (ischemic, large artery, cardioembolic, small vessel).
• To investigate the role of environmental factors, specifically methylation, in stroke susceptibility.

Main Methods:

• Integration of 8 GWAS datasets with brain expression quantitative trait loci (eQTL) data.
• Identification of SNPs and their associated genes affecting gene expression.
• Utilizing methylation quantitative trait loci (MQTL) to identify methylation susceptibility loci.

Main Results:

• Thirty-eight SNPs associated with stroke were identified, influencing the expression of 14 genes.
• Specific gene associations were found for different stroke types: 10 for ischemic, 1 for large artery, 6 for cardioembolic, and 8 for small vessel stroke.
• Thirty-one of the 38 identified SNPs were linked to methylation changes, significantly altering gene expression levels.

Conclusions:

• The study elucidates the genetic pathogenesis of stroke from the level of genetic loci to gene expression and ultimately to phenotypic outcomes.
• Identified SNPs and genes provide potential molecular targets for understanding and potentially treating stroke.
• The findings highlight the interplay between genetic predisposition and environmental factors like methylation in stroke development.