The rationale for this project is to identify protein quantitative trait loci (pQTLs), which are robust connections between a gene variant and the levels of a protein, across the life course. We will conduct genome-wide association studies (GWAS’s) of protein levels at three separate timepoints and compare pQTLs at these different timepoints. Associations with independent lead variants within 300 kb window of the gene boundaries of the protein-coding gene are defined as cis-signals, and otherwise in trans. In this project, we will estimate the proportion of pQTLs that are in cis versus in trans at each of the three timepoints. We will investigate how much of the longitudinal correlation in inflammation levels is explained by genotype. We will also evaluate the relationship of pQTL with other down-stream phenotypes, including traits and diseases, and quantify the contribution made by pQTL to genetic variance in several common complex diseases that have previously been the subject of genome-wide association studies (GWAS).
This project will use the ALSPAC proteomic data, which consists of 92 proteins measured by Olink, measured in approximately 3000 mothers, 3000 children at age 9 and another 3000 children at age 24. We will also perform the analyses on the inflammatory biomarkers Glyoprotein Acetyls (GlycA) and C-reactive protein (CRP), as well as IL-6 measured in the 9-year-olds via clinical chemistry, since IL-6 is the only protein measured by Olink that has been measured previously in ALSPAC to be used as a validation.