So that's what I did. I wrote a script to loop through all HbA1c loci, and for each locus I recorded all the other phenotypes that colocalize with HbA1c.
1300 unique traits
999 unique gene symbols.
What did I find?
1300 unique traits
999 unique gene symbols.
What did I find?
Comments
Clustering all the phenotypes based on the associated loci reveals two distinct sets of phenotypes
The 1st includes traits like:
Type 2 diabetes, drugs for t2d, glucose.
L2G links 201 unique genes.
These are enriched for islet biology:
https://maayanlab.cloud/Enrichr/enrich?dataset=e01e2d356ca9628c5c2bfc09c976cc12
The 421 L2G associated genes are enriched in red blood cell markers and phenotype
https://maayanlab.cloud/Enrichr/enrich?dataset=081e051436abe115b04c716c75362e96
I guess HbA1c really is the perfect blend of a metabolite QTL and a protein QTL!
There are 10s of thousands of gwas.
I hope @opentargets and similar tools will make it easier for everyone to consider the full complement of phenotypes caused by the genetic variant of interest.
In my experience this makes it far easier to infer the likely causal gene.