Project: Identification of markers for personal phenotyping in Acne Inversa
| Acronym | BATMAN (Reference Number: ERAPERMED2018-137) |
| Duration | 01/03/2019 - 28/02/2022 |
| Project Topic | Acne Inversa (AI) is a chronic inflammatory disease involving hair follicles that imposes a major physical and psychological burden on patients and significant costs for health systems. Genetic variants affecting different pathways result in an extremely wide spectrum of AI phenotypes. Therefore, deciphering AI pathogenesis and tracking gene variants is essential in order to design personalized treatments. The proposal aims to bring together medical, genetic, experimental and lifestyle data to build a truly personalized model of each patient and to tailor specific treatments based on their personal characteristics. Research on animal or cellular models will be harnessed to validate hypotheses on genetic variants. This will generate useful information with immediate translational impact on patient stratification and therapeutic options, and also provide a wide-scale overview of previously identified and novel risk markers. DNA will be obtained from familial AI cases from 5 different locations in Europe. Data will be compiled from whole exome sequencing, targeted re-sequencing and transcriptomic signatures of lesions and novel mouse models. Genomic information will be merged with clinical evaluations and lifestyle data by advanced machine-learning and data mining algorithms. By the end of the project, our consortium intends to: identify genetic variants associated with AI susceptibility, severity and treatment; design in vivo and in vitro models for investigations on the main biological pathways affected by AI and testing the impact of genetic variants on immune and cutaneous cell biology; develop a smartphone application to remotely monitor the physical and psychological wellbeing of patients and advise them on physical activity and dietary and smoking habits and combine data from the smartphone application with clinical and genetic data; propose novel stratification methods that clinicians can use to assess severity, choose the therapy and follow the outcome. |
| Network | ERA PerMed |
| Call | 1st Joint Transnational Call for Proposals (2018) |
Project partner
| Number | Name | Role | Country |
|---|---|---|---|
| 1 | IRCCS Burlo Garofolo | Coordinator | Italy |
| 2 | Uniklinik Köln | Partner | Germany |
| 3 | Medical University Innsbruck | Partner | Austria |
| 4 | Université Paris Est-Créteil / INSERM U955- Mondor Institute For Biomedical Research (IMRB) | Partner | France |
| 5 | Centre National de la Recherche Scientifique | Partner | France |
| 6 | Jozef Stefan Institute | Partner | Slovenia |
| 7 | Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico | Partner | Italy |