Integrative Base Ontology for the Research Analysis of Alzheimer’s Disease-Related Mild Cognitive Impairment - Gomez-Valades, Alba; Martinez-Tomas, Rafael; Rincon, Mariano (Frontiers in Neuroinformatics, 2021)
The early detection of mild cognitive impairment (MCI) has become a priority in Alzheimer’s disease (AD) research since it is a transition phase between normal aging and dementia. However, information regarding MCI and AD is scattered in disparate formats and standards generated by different technologies, which makes it difficult to work with them manually. Ontologies have emerged as a solution to this problem because of their capability of homogenization and consensus in the representation and reuse of data. In this context, an ontology that integrates the four main domains of neurodegenerative diseases, diagnostic tests, cognitive functions and brain areas will become significantly useful in research. Here, we introduce the first approach to this ontology, the Neurocognitive Integrated Ontology (NIO), which integrates the knowledge regarding neuropsychological tests, AD, cognitive functions, and brain areas. This ontology enables interoperability and facilitates access to data by integrating dispersed knowledge across different disciplines, rendering it useful for other research groups. To ensure the stability and reusability of NIO, the ontology was developed following the ontology-building life cycle, integrating and expanding terms from four different reference ontologies. The usefulness of this ontology was validated through use-case scenarios.