If that sounds interesting, let us know!

For more information DM or email me (aurina.arnatkeviciute@monash.edu) or
@jchrispang.bsky.social (james.pang1@monash.edu)

According to our analysis and null model (which is quite stringent, but allows to ask a reasonable question) -- only in special cases, e.g. bipolar disorder. Matches for other disorders are very limited if any.

6/6 But the correspondence for most other psychiatric disorders rarely exceeds null expectation suggesting that the genetic mechanisms driving the risk for psychiatric disorders may be distinct from the pathophysiological mechanisms targeted by drugs.

5/6 We show that incorporating information derived from functional bioinformatics data, such as the PPI network can reveal links between GWAS and drugs for some disorders (bipolar disorder and diabetes [used for comparison]).

4/6 We propose a robust and realistic null model for significance testing that expects the identified matches to be specific for the selected group of treatments. Meaning that treatments for a selected disorder are expected to exceed matches for other treatments.

3/6 Here we integrate different functional information from protein-protein interactions, expression quantitative trait loci (eQTL), and spatial gene expression to determine the correspondence between GWAS hits and the genes for current drug targets.

2/6 Psychiatric disorders (most having a developmental component) present a special case, where the genetic risk that creates a vulnerability to illness may be distinct and separated in time from the pathophysiological mechanisms that influence symptom onset and severity.

1/6 GWASs were expected to inform the development of pharmacological treatments, such that identifying genetic variation associated with the disorder would provide targets for drug action. However, the direct translational applications have not yet been developed.