Efficient candidate drug target discovery through proteogenomics in a Scottish cohort

Area of Science:

• Genetics
• Proteomics
• Biomedical Research

Background:

• Understanding genomic influences on protein levels is crucial for identifying disease causal relationships and drug targets.
• Previous genome-wide association studies (GWAS) have largely focused on genetic variants, with limited exploration of proteomic variability.

Purpose of the Study:

• To investigate the genomic basis of human plasma proteomic variability by analyzing a large set of proteins.
• To identify novel protein quantitative trait loci (pQTL) and assess their potential causal roles in complex human diseases.

Main Methods:

• Utilized aptamer-based SomaLogic technology to measure 6432 plasma proteins in a Scottish population (Viking Genes study).
• Performed genome-wide association studies (GWAS) to identify significant cis- and trans-pQTL.
• Employed bidirectional Mendelian randomization and colocalization analyses to infer causal relationships between pQTL and complex traits.

Main Results:

• Identified 505 significant independent pQTL for 455 proteins, with 382 cis-pQTL and 123 trans-pQTL.
• Discovered 31 cis-pQTL for proteins not previously studied in large-scale GWAS.
• Found 43 colocalizing associations, suggesting plausible causal roles for proteins in various traits.
• Uncovered novel causal links between leukocyte receptor tyrosine kinase (LTK) and type-2 diabetes, and beta-1,3-glucuronyltransferase (B3GAT1) and prostate cancer.

Conclusions:

• The study highlights the value of large-scale proteomic GWAS in uncovering genetic determinants of protein levels.
• Identified novel protein-disease associations that can guide the development of new therapeutic strategies.
• Supports the expansion of GWAS to include a broader range of proteins to enhance understanding of disease biology.