A genetic disorder is a disease triggered by a change within the DNA, which may be caused by a mutation in a single gene (monogenic), by mutations in multiple genes (oligo or polygenic) or by damage to large portions of a chromosome. Although many disease-related genetic mutations databases exist, no effort is made to organize the data so that one can investigate oligo- and polygenic nature of diseases. Nevertheless, research has shown that many disorders considered monogenic may be better described by more complex inheritance mechanisms. Inheritance models with imperfect genotype-phenotype correlation, which are considered as reduced penetrance in monogenic disorders, may be better explained by a digenic disease (DD) model. This modelling problem pinpoints the need to develop new databases and services focused on complex inheritance models, starting from the poorly understood oligogenic diseases. This is an ambitious goal since it is not possible to retrieve records regarding oligogenic diseases from existing biomedical databases. Even the simplest information concerning the combinations of variants, responsible for the development of a disease, is often not available. This underlines the necessity to develop ex-novo an oligogenic-centered database, where the initial focus should be first in DD.

Here we present DIDA (DIgenic DAtabase): a manually curated database collecting DD instances, which provides a resource for any future analysis in di-and oligogenic diseases.

DIDA was created by collecting all the DD data published in literature until now. We mined manually the medical literature to ensure the high quality of this ex novo DD variant database. For every article describing patients affected by a disease explained with a DD inheritance model, we annotated causative mutation-pairs, enriching every instance with different features. These features include coordinates of the mutations, gene names, disease name, inheritance model, symptoms, digenic effect (influence on severity, age onset, or 'on/off' situation) and additional notes (e.g. comparison with other patients, replication of the study, etc.). In addition, annotations have been mapped onto domain ontologies (e.g. HPO) and three types of mutation-coordinates have been integrated (genomic, exomic, and proteomic). Finally, additional information about the mutations and involved genes were collected for later analysis from external databases like dbNSFP. These data provide insights into the biomolecular relationships between the gene-pairs associated with certain diseases and the loci of the genes within the genome, enhancing recent studies.

DIDA is a novel database of known variants-pairs involved in different DD: it represents a first systematic effort in collecting information related to DD in a single repository. As such, this database is the basis for understanding how the combined interplay and weight of variants leads to disease, which in turn may provide novel insights into diseases classically considered monogenic. DIDA will have a clear impact on the future of the research on DD (clinical diagnosis, benchmarking of bioinformatics tools, etc.), it is available to the research community and we are currently working on a user-friendly web-interface that will allow extracting tailored information.
Original languageEnglish
Title of host publicationAbstract book of the 15th Annual Meeting of the Belgian Society of Human Genetics
PublisherBelgian Society of Human Genetics
Number of pages126
Publication statusPublished - 6 Mar 2015
Event15th Annual Meeting of the Belgian Society of Human Genetics - Charleroi, Belgium
Duration: 6 Mar 20156 Mar 2015


Conference15th Annual Meeting of the Belgian Society of Human Genetics


  • digenic
  • database
  • bioinformatics
  • genomics


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