Analyses of 1236 genotyped primary ciliary dyskinesia individuals identify regional clusters of distinct DNA variants and significant genotype–phenotype correlations

Primary ciliary dyskinesia; DNA variants; GenotypeDiscinesia ciliar primaria; Variantes de ADN; GenotipoDiscinesia ciliar primària; Variants d'ADN; GenotipBackground Primary ciliary dyskinesia (PCD) represents a group of rare hereditary disorders characterised by deficient ciliary airway clearance that can be associated with laterality defects. We aimed to describe the underlying gene defects, geographical differences in genotypes and their relationship to diagnostic findings and clinical phenotypes. Methods Genetic variants and clinical findings (age, sex, body mass index, laterality defects, forced expiratory volume in 1 s (FEV1)) were collected from 19 countries using the European Reference Network's ERN-LUNG international PCD Registry. Genetic data were evaluated according to American College of Medical Genetics and Genomics guidelines. We assessed regional distribution of implicated genes and genetic variants as well as genotype correlations with laterality defects and FEV1. Results The study included 1236 individuals carrying 908 distinct pathogenic DNA variants in 46 PCD genes. We found considerable variation in the distribution of PCD genotypes across countries due to the presence of distinct founder variants. The prevalence of PCD genotypes associated with pathognomonic ultrastructural defects (mean 72%, range 47–100%) and laterality defects (mean 42%, range 28–69%) varied widely among countries. The prevalence of laterality defects was significantly lower in PCD individuals without pathognomonic ciliary ultrastructure defects (18%). The PCD cohort had a reduced median FEV1 z-score (−1.66). Median FEV1 z-scores were significantly lower in CCNO (−3.26), CCDC39 (−2.49) and CCDC40 (−2.96) variant groups, while the FEV1 z-score reductions were significantly milder in DNAH11 (−0.83) and ODAD1 (−0.85) variant groups compared to the whole PCD cohort. Conclusion This unprecedented multinational dataset of DNA variants and information on their distribution across countries facilitates interpretation of the genetic epidemiology of PCD and indicates that the genetic variant can predict diagnostic and phenotypic features such as the course of lung function.This work was supported by grants from the Deutsche Forschungsgemeinschaft (DFG OM6/7, OM6/8, OM6/10, OM6/14, CRU 326 (to H. Omran, J. Raidt); OL 450/1 (H. Olbrich); CRC 1449 (project 431232613; sub-project Z02 to M.A. Mall)), the Interdisziplinaeres Zentrum für Klinische Forschung Muenster (Om2/009/12, Om2/015/16 and Om2/010/20), Registry Warehouse (Horizon2020 GA 777295) and the German Federal Ministry of Education and Research (82DZL009B1 to M.A. Mall). J.F. Roehmel is a participant of the Case Analysis and Decision Support (CADS) programme funded by the Berlin Institute of Health. The authors thank the “Børnelungefonden” and “Rigshospitalet's research fund” (K.G. Nielsen). A. Shoemark is supported by Asthma and Lung UK. The National UK PCD service is supported by NHS England. Some study authors and data contributors participate in the BEAT-PCD clinical research collaboration supported by the European Respiratory Society. This study was supported and promoted as part of work package 3 during the 2020-2023 BEAT-PCD funding period. H.M. Mitchison is supported by the NIHR Biomedical Research Centre at Great Ormond Street Hospital. S. Rovira-Amigo was funded by a grant from Instituto de Salud Carlos III (ISCIII) through the project “PI20/01419” and co-funded by the EU and a grant of the Spanish Society of Paediatrics (Invest-AEP 2021). V. Martinu was supported by Ministry of Health of the Czech Republic, grant number NV19-07-00210 and supported by Motol University Hospital, Prague, Czech Republic, 00064203 (conceptual development of research). E. Ziętkiewicz was supported by the Polish National Science Centre, grant 2018/31/B/NZ2/03248

Integration of Patient-Reported Outcome Data Collected Via Web Applications and Mobile Apps Into a Nation-Wide COVID-19 Research Platform Using Fast Healthcare Interoperability Resources: Development Study

BackgroundThe Network University Medicine projects are an important part of the German COVID-19 research infrastructure. They comprise 2 subprojects: COVID-19 Data Exchange (CODEX) and Coordination on Mobile Pandemic Apps Best Practice and Solution Sharing (COMPASS). CODEX provides a centralized and secure data storage platform for research data, whereas in COMPASS, expert panels were gathered to develop a reference app framework for capturing patient-reported outcomes (PROs) that can be used by any researcher. ObjectiveOur study aims to integrate the data collected with the COMPASS reference app framework into the central CODEX platform, so that they can be used by secondary researchers. Although both projects used the Fast Healthcare Interoperability Resources (FHIR) standard, it was not used in a way that data could be shared directly. Given the short time frame and the parallel developments within the CODEX platform, a pragmatic and robust solution for an interface component was required. MethodsWe have developed a means to facilitate and promote the use of the German Corona Consensus (GECCO) data set, a core data set for COVID-19 research in Germany. In this way, we ensured semantic interoperability for the app-collected PRO data with the COMPASS app. We also developed an interface component to sustain syntactic interoperability. ResultsThe use of different FHIR types by the COMPASS reference app framework (the general-purpose FHIR Questionnaire) and the CODEX platform (eg, Patient, Condition, and Observation) was found to be the most significant obstacle. Therefore, we developed an interface component that realigns the Questionnaire items with the corresponding items in the GECCO data set and provides the correct resources for the CODEX platform. We extended the existing COMPASS questionnaire editor with an import function for GECCO items, which also tags them for the interface component. This ensures syntactic interoperability and eases the reuse of the GECCO data set for researchers. ConclusionsThis paper shows how PRO data, which are collected across various studies conducted by different researchers, can be captured in a research-compatible way. This means that the data can be shared with a central research infrastructure and be reused by other researchers to gain more insights about COVID-19 and its sequelae