Properties of local interactions and their potential value in complementing genome-wide association studies

Area of Science:

• Genetics and Genomics
• Complex Trait Association Studies
• Bioinformatics

Background:

• Genome-wide association studies (GWAS) have limitations in capturing variants missed through local interactions between neighboring single nucleotide polymorphisms (SNPs).
• The role of these local SNP interactions in complex traits like blood pressure and metabolic disorders remains underexplored.

Purpose of the Study:

• To investigate the utility of analyzing local SNP interactions as a complement to traditional GWAS.
• To identify novel genetic associations for blood pressure and metabolic traits by exploring pairwise SNP interactions.

Main Methods:

• Utilized a novel high-throughput analysis tool for full pair-wise genome scans.
• Conducted conventional GWAS alongside local interaction analyses in the Northern Finland Birth Cohort 1966 (NFBC1966) and the Atherosclerosis Risk in Communities (ARIC) study.
• Analyzed interactions for systolic/diastolic blood pressure and six metabolic traits.

Main Results:

• Detected genome-wide significant interactions for systolic blood pressure (PLEKHA7 and GPR180) and triglycerides (11q23.3 region) in the ARIC cohort, with triglyceride findings replicated in NFBC1966.
• Identified two independent functional variants within the 11q23.3 region, potentially involved in gene regulation.
• Local interaction analysis identified 9 new GWAS loci (3 replicated) and captured 73 previously identified GWAS loci across eight traits and related traits.

Conclusions:

• Analyzing local SNP interactions is a valuable complement to GWAS, enhancing the discovery of genetic variants influencing complex traits.
• Adequate SNP coverage and low linkage disequilibrium between SNPs are crucial for detecting local interactions.
• This approach provides new biological insights into the genetic architecture of complex traits.