Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases

Sandra Brasil, Cátia José Neves, Tatiana Rijoff, Marta Falcão, Gonçalo Valadão, Paula A. Videira, Vanessa dos Reis Ferreira

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)
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More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the 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 may also become 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 of 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.

Original languageEnglish
Article number648012
JournalFrontiers in Molecular Biosciences
Publication statusPublished - 5 May 2021


  • artificial intelligence
  • epigenetics
  • epigenomic
  • machine learning
  • personalized medicine
  • rare diseases (RD)


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