The role of the digenic model in rare disorders has been relatively under explored, mostly due to both the difficulties of statistically supporting these associations to disease and the limitations of generating experimental models. We have developed an approach based on the analysis of genomic data from hundreds of thousands of individuals available from large biomedical projects to detect or validate pathogenic digenic interactions.

We analyzed genotyping data for 70 autoinflammatory disorder genes in UK Biobank for 467,000 European ancestry individuals based on PCA analyses. We compared the expected and observed frequencies of co-carriers for all possible pairs of variants from different genes.

The analysis revealed candidate digenic interactions among AID genes, evidenced by deviations from neutrality of the genotypes distribution. One of the interactions, validated in an independent patient cohort, may provide insight into the incomplete penetrance of Familial Mediterranean Fever (FMF) where heterozygous individuals carrying pathogenic variants in the MEFV gene may or may not develop the disease. Specifically, we suggest that a genetic variant in a functionally related gene acts as a modifier, influencing disease expression by modifying the action of the primary pathogenic variant in MEFV.

Our approach can identify digenic and modifier interactions in rare diseases. We have identified a candidate modifier gene that may explain incomplete penetrance in FMF.

Co-authors: Diego Garrido-Martin, Llorenc Villalonga-Gonyalons, Alex Velaza-Gil, Nerea Moreno-Ruiz, Roderic Guigo, Hafid Laayouni, Juan Ignacio Arostegui, Ferran Casals