The activities of INHERENT are divided into five working groups (WG)
1. Clinical WG
Lead: Baba Inusa and Obiageli Nnodu for SCD; Sara Trompeter and Bin Alwi Zilfalil for thalassemia. Coordinator: Natasha Archer
The Clinical WG is working on the definition of the main clinical questions to be studied by INHERENT. This includes a detailed specification of the core data parameters required for any member participation and the data parameters needed for each clinical question. The Clinical WG has developed a CRF that can be used to gather data across countries with different resource capabilities. In collaboration with the Data Management and Analysis WG, established clinical, laboratory and disease ontologies, such as HPO, LOINC and SCDO, will be used for the standardization of the data, thus allowing data interoperability.
2. Genotyping WG
Lead: Coralea Stephanou, Siana Nkya
3. Data Management and Analysis WG
Lead: Kyriaki Michailidou, Petros Kountouris
This WG is developing the protocols for data management, security, and analysis, including bioinformatics and biostatistical analysis. Moreover, the WG is developing the infrastructure for the collection, storage and sharing of the INHERENT data. The network will collaborate with existing regional patient registries, such as RADeep and SPARCO, to integrate the INHERENT CRF into their existing infrastructure, thus avoiding the recruitment of the same patients for different software platforms. In addition, a central REDCap application for direct submission of patient data is under development for members that do not participate in existing registries. This WG, in collaboration with the Ethics WG, will also assess available solutions for the pseudonymization of patient data.
After all appropriate quality control measures will be performed, we will use imputation to the most updated multi-ethnic reference panel. Depending on the endpoint of interest, we will use the most appropriate statistical analyses to evaluate the effect of each variant as a modifier of the disease, such as survival analyses, linear or logistic regression taking into consideration possible confounders. Since the ascertainment of mutation carriers is not at random, we will use statistical techniques to account for potential biases. Identified modifying variants will then be used in combination to create polygenic risk scores that could potentially lead to a better estimation of the risk of developing different complications.
4. Ethics WG
Lead: Fedele Bonifazi, Viviana Giannuzzi. Coordinator: Antonella Didio
5. Knowledge Translation WG
Lead: Kevin Kuo. Coordinator: Anneliesse Justiniano
- integrating findings from INHERENT within the larger body of knowledge on hemoglobinopathies using quantitative and/or qualitative approaches (e.g., consensus conference, expert panel, practice guidelines);
- identifying and tailoring the message to the appropriate audience (e.g., educational sessions with patients, practitioners, policymakers, tools creation, and media engagement); and
- facilitate interaction between INHERENT researchers and decision-makers at the local and global level to plan, produce, disseminate and apply findings from INHERENT in decision-making.