Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

Children with hemodynamically significant congenital heart disease can be identified through population-based registers.

BACKGROUND: Epidemiological research is facilitated in Sweden by a history of national health care registers, making large unselected national cohort studies possible. However, for complex clinical populations, such as children with congenital heart disease (CHD), register-based studies are challenged by registration limitations. For example, the diagnostic code system International Classification of Diseases, 10th version (ICD-10) does not indicate the clinical significance of abnormalities, therefore may be of limited use if used as the sole parameter in epidemiological research. Palivizumab is indicated as a prophylactic treatment against respiratory syncytial virus infections in children with hemodynamically significant CHD. AIM: The aim of the study reported here was to develop and validate an algorithm to identify children with hemodynamically significant CHD according to recommendations for palivizumab prophylaxis in register-based research. METHODS: By using a strategy of combining criteria for age at diagnosis, diagnostic codes, surgical procedure codes, and dispensing records, we created an algorithm to define the specific cases with hemodynamically significant CHD in which palivizumab could be advocated according to recommendations. RESULTS: The algorithm identified 928 children with hemodynamically significant CHD in the Swedish birth cohort born July 1, 2005 to December 31, 2010. A sensitivity (95% confidence interval) of 80% (70-88) for the algorithm was found by analyzing 121 children identified through local hospital data who were treated with palivizumab within a defined region and study period. The positive predictive value was estimated by medical record review in a random sample of 34 cases identified by the algorithm. In 79% (62-91) of these cases, the children were regarded as having hemodynamically significant CHD according to the recommendations for treatment with palivizumab. CONCLUSION: It was possible to identify a subgroup of children with hemodynamically significant CHD using an epidemiological approach and an algorithm with high validity. Our results will enable well-powered national cohort studies of individuals with complex clinical conditions such as hemodynamically significant CHD.