Genetics in Medicine Open (Jan 2023)
GenIDA, a participatory patient registry for genetic forms of intellectual disability provides detailed caregiver-reported information on 237 individuals with Koolen-de Vries syndrome
Abstract
Purpose: GenIDA is an international patient registry for individuals diagnosed with intellectual disability, autism spectrum disorder, and/or epilepsy, which is based on an online questionnaire that is completed by parent caregivers. In this study, the GenIDA data on Koolen-de Vries syndrome (KdVS) was analyzed illustrating the value of GenIDA and patient/caregiver participation in rare genetic neurodevelopmental disorders (NDDs). Methods: Recruitment was done on the GenIDA website from November 2016 to February 2022. Clinical information on individuals with KdVS was extracted for in-depth analysis and for comparison with the GenIDA data of individuals diagnosed with other NDDs. Results: A total of 1417 patients/caregivers across 35 genetic conditions answered to the GenIDA questionnaire, including caregivers of 237 individuals with KdVS. GenIDA findings on KdVS were consistent with the existing literature, and there were no significant differences between individuals with a 17q21.31 microdeletion and those with a pathogenic variant in the KANSL1 gene. GenIDA provided detailed clinical information including features that are over-represented in KdVS compared with other NDDs (eg, laryngomalacia). Modeling of the natural history showed a positive development of speech and language over time and relatively good reading ability in KdVS. Valproate and oxcarbazepine were reported as effective antiepileptic drugs, and responses to open-ended questions indicated that childhood recurrent pneumonia and asthma are clinically relevant comorbidities that were not described in KdVS before. Conclusion: GenIDA is a powerful registry to collect and harness valuable data on rare NDDs. The study shows that caregiver-driven data collection is effective in terms of global recruitment and centralization of clinical data.