Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases - Brasil, Sandra; Neves, Cátia José; Rijoff, Tatiana; Falcão, Marta; Valadão, Gonçalo; Videira, Paula A.; dos Reis Ferreira, Vanessa (Frontiers in Molecular Biosciences, 2021)
More than 7000 rare diseases (RDs) exist worldwide affecting approximately 350 million people, from which only 5% have a treatment. The development of novel genome sequencing techniques has accelerated discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g. cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it mayalsobecome an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this “big data” age, the amount of information generated, collected and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field for RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.