A Mechanistic Map of the Phenotypic Complexity in Recessive Dystrophic Epidermolysis Bullosa Provides Basis for Therapeutic Target Discovery and Drug Repurposing.
6 affiliations
- 1Departamento de Bioingeniería, Universidad Carlos III de Madrid, ROR Code 03ths8210, Avenida de la Universidad, 30 (Edificio Sabatini), 28911 Leganés, Spain.
- 2Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), 28029 Madrid, Spain.
- 3Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD, UAM), 28040 Madrid, Spain.
- 4Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain.
- 5Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, 41092 Seville, Spain.
- 6Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, 41013 Seville, Spain.
Abstract
Recessive dystrophic epidermolysis bullosa (RDEB) is a genodermatosis caused by loss-of-function mutations in the COL7A1 gene, producing a complex and heterogeneous phenotype. Clinical manifestations include skin fragility, local and systemic inflammation, impaired wound healing, dysbiosis, pain, and pruritus, increasing the risk of skin cancer. This work aimed to develop an actionable model of RDEB's molecular mechanisms to identify and prioritize therapeutic targets for drug repurposing. Transcriptomic data of skin biopsies from pediatric RDEB patients and unaffected individuals were used to build the mechanistic map of the disease. This model, combined with machine learning, made it possible to infer actionable targets from the map circuits and identify candidate drugs capable of reversing the transcriptomic alterations. The resulting map is defined by 13 altered signaling circuits and 10 effector proteins which were linked to disease hallmarks including inflammation, fibrosis, and tumor progression. Analysis of the map identified 66 actionable targets with 74 drug candidates. Among them, overrepresentation analysis showed enrichment of phosphodiesterases and antineoplastic and immunomodulating agents. Finally, 16 drugs were prioritized for their potential to revert circuit alterations without potentiating unintended effects, with bendroflumethiazide and ibutilide showing the highest impact. This mechanistic model delivers the first functional disease map of RDEB and reveals promising therapeutic candidates targeted by approved drugs.
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BibTeX
@article{herraizgil2026mechanistic,
title = {{A Mechanistic Map of the Phenotypic Complexity in Recessive Dystrophic Epidermolysis Bullosa Provides Basis for Therapeutic Target Discovery and Drug Repurposing.}},
author = {Sara Herráiz-Gil and Miriam Payá-Milans and María Del Carmen de Arriba and Lucía Martínez-Santamaría and Carlos Loucera and Nuria Illera and Marcela Del Río and Joaquín Dopazo and Carlos León and María José Escámez},
journal = {International journal of molecular sciences},
year = {2026},
month = sep,
doi = {10.3390/ijms27198436},
url = {https://europepmc.org/article/MED/42883687},
note = {CC BY},
}
RIS
TY - JOUR
TI - A Mechanistic Map of the Phenotypic Complexity in Recessive Dystrophic Epidermolysis Bullosa Provides Basis for Therapeutic Target Discovery and Drug Repurposing.
AU - Sara Herráiz-Gil
AU - Miriam Payá-Milans
AU - María Del Carmen de Arriba
AU - Lucía Martínez-Santamaría
AU - Carlos Loucera
AU - Nuria Illera
AU - Marcela Del Río
AU - Joaquín Dopazo
AU - Carlos León
AU - María José Escámez
PY - 2026
DA - 2026/09/22
JO - International journal of molecular sciences
DO - 10.3390/ijms27198436
UR - https://europepmc.org/article/MED/42883687
AB - Recessive dystrophic epidermolysis bullosa (RDEB) is a genodermatosis caused by loss-of-function mutations in the COL7A1 gene, producing a complex and heterogeneous phenotype. Clinical manifestations include skin fragility, local and systemic inflammation, impaired wound healing, dysbiosis, pain, and pruritus, increasing the risk of skin cancer. This work aimed to develop an actionable model of RDEB's molecular mechanisms to identify and prioritize therapeutic targets for drug repurposing. Transcriptomic data of skin biopsies from pediatric RDEB patients and unaffected individuals were used to build the mechanistic map of the disease. This model, combined with machine learning, made it possible to infer actionable targets from the map circuits and identify candidate drugs capable of reversing the transcriptomic alterations. The resulting map is defined by 13 altered signaling circuits and 10 effector proteins which were linked to disease hallmarks including inflammation, fibrosis, and tumor progression. Analysis of the map identified 66 actionable targets with 74 drug candidates. Among them, overrepresentation analysis showed enrichment of phosphodiesterases and antineoplastic and immunomodulating agents. Finally, 16 drugs were prioritized for their potential to revert circuit alterations without potentiating unintended effects, with bendroflumethiazide and ibutilide showing the highest impact. This mechanistic model delivers the first functional disease map of RDEB and reveals promising therapeutic candidates targeted by approved drugs.
SN - 1422-0067
ER -