The availability of biological resources that can aid in the interpretation of GWAS results, such as Hi-C and ChIA-PET, have dramatically increased recently and several studies have identified novel candidates from GWAS risk loci by integrating their results for example with chromatin interactions51,54–57. These technologies have the potential to identify distal interactions of promoters and enhancers. Especially for risk loci for which it has been difficult to identify target genes due to the presence of gene desserts, distal interactions might point to causal gene. Indeed, we identified additional putative causal genes by performing chromatin interaction mapping on outcomes from three GWAS studies (BMI, CD, and SCZ) and the additionally identified genes based on chromatin interaction information were mostly located outside of the risk loci, and were shown to have shared function with known candidates. Although chromatin interactions are highly tissue/cell type specific, as well as time dependent, and currently available data is still limited in those aspects, FUMA provides an option to upload custom interaction matrices. Additionally, FUMA is built in such a way that newly published data including 3D
