tralfamadorian97
Established Member (Voting Rights)
I’m interested in linking the DecodeME summary statistics to summary statistics from GWAS of objectively measured molecular traits. To explore this, I ran a colocalization screen of DecodeME against proteomic GWAS from the UK Biobank Pharma Proteomics Project (PPP). PPP used the Olink assay to measure plasma levels of more than 5K proteins in about 50K UK biobank participants. In simple terms, I searched for places on the genome at which the DecodeME signal matched the signal of a genetic study of the level of a protein in the blood.
The results are described here.
Here is a table of all locus/protein pairs with greater than 80% probability of colocalization.
Here are some Manhattan plots
To summarize, I did not find colocalization at genome-wide-significant DecodeME loci. However, there was some colocalization with protein levels at sub-genome-wide significant loci. The colocalization was with trans-pQTL. This means the site of the colocalization is far from the gene encoding the protein in question. Trans pQTL are generally more difficult to interpret than cis-pQTL.
These findings may not be particularly informative on their own. Perhaps combined with other results they will prove a useful puzzle piece.
The results are described here.
Here is a table of all locus/protein pairs with greater than 80% probability of colocalization.
Here are some Manhattan plots
To summarize, I did not find colocalization at genome-wide-significant DecodeME loci. However, there was some colocalization with protein levels at sub-genome-wide significant loci. The colocalization was with trans-pQTL. This means the site of the colocalization is far from the gene encoding the protein in question. Trans pQTL are generally more difficult to interpret than cis-pQTL.
These findings may not be particularly informative on their own. Perhaps combined with other results they will prove a useful puzzle piece.
