Bio-ontologies are widely used to annotate and characterize biological objects or situations, enabling the use of shared or similar features in classification tasks. It may appear beneficial to make two or more bio-ontologies cooperate for building more complete descriptions, and therefore more accurate classifications of biological objects. This hypothesis is evaluated here for the classification of an heterogeneous set of 374 Genetic Intellectual Disabilities (GIDs), using a diseasome approach. These GIDs are annotated with classes of the Human Phenotype Ontol-ogy (HPO) and their causal genes with the three aspects of the Gene Ontology (GO). We test two semantic similarity measures, and different combinations of ontologies, to connect semantically similar diseases. We then evaluate how well these ontologies, and their combinations, are exploited by the similarity measures to classify GIDs in accordance with an expert classification. Results show that combining the three aspects of GO achieves very good overall performance, and that, for each GID class, a particular combination of 2 or 3 GO aspects and occasionally HPO yields the best performance. These results illustrate how bio-ontologies can cooperate in a classification by refining the characterization of biological objects.