Cracking the genetic code of epidermolysis bullosa with bioinformatics

Abstract

Epidermolysis bullosa (EB) is a group of rare, inherited skin disorders characterized by skin fragility and blistering due to mutations in genes encoding structural proteins essential for skin integrity. Despite significant advances in understanding the clinical manifestations of EB, the identification of disease-causing mutations and the development of targeted therapies remain challenging due to the complexity of genetic variations. Bioinformatic approaches have emerged as powerful tools to better understand the genetic source and mechanism of EB. This paper explores the role of bioinformatics in analyzing genetic data from EB patients, focusing on the use of whole-genome sequencing and whole-exome sequencing, variant calling and annotation, transcriptomic analysis through RNA sequencing, and protein-structure modeling to identify novel mutations and their impact on skin function. In addition, the applications of bioinformatics, including personalized treatment strategies, early diagnosis, and development of gene editing therapies, are discussed. While challenges such as data complexity and limited databases remain, bioinformatics hold significant promise in advancing our understanding of EB and improving patient outcomes through more precise and tailored therapeutic interventions. Future integration of artificial intelligence, expanded genetic databases, and clinical decision support tools will further enhance the potential of bioinformatics in the management of rare skin disorders like EB.

Keywords

Epidermolysis bullosa / Bioinformatics / Genetic mutations / Personalized medicine / Protein-structure modeling

Acknowledgments

None.

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

Author contributions

Conceptualization: Dorra Guermazi, Elie Saliba

Writing - original draft: Dorra Guermazi

Writing - review & editing: All authors

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data

Not applicable.

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