Linkage between the Danish National Health Service Prescription Database, the Danish Fetal Medicine Database, and other Danish registries as a tool for the study of drug safety in pregnancy

A linked population-based database is being created in Denmark for research on drug safety during pregnancy. It combines information from the Danish National Health Service Prescription Database (with information on all prescriptions reimbursed in Denmark since 2004), the Danish Fetal Medicine Database, the Danish National Registry of Patients, and the Medical Birth Registry. The new linked database will provide validated information on malformations diagnosed both prenatally and postnatally. The cohort from 2008 to 2014 will comprise 589,000 pregnancies with information on 424,000 pregnancies resulting in live-born children, ∼420,000 pregnancies undergoing prenatal ultrasound scans, 65,000 miscarriages, and 92,000 terminations. It will be updated yearly with information on ∼80,000 pregnancies. The cohort will enable identification of drug exposures associated with severe malformations, not only based on malformations diagnosed after birth but also including those having led to termination of pregnancy or miscarriage. Such combined data will provide a unique source of information for research on the safety of medications used during pregnancy

First-trimester prediction of preterm prelabour rupture of membranes incorporating cervical length measurement

Objectives: To examine early pregnancy risk factors for preterm prelabour rupture of membranes (PPROM) and develop a predictive model. Study design: Retrospective analysis of a cohort of mixed-risk singleton pregnancies screened in the first and second trimesters in three Danish tertiary fetal medicine centres, including a cervical length measurement at 11–14 weeks, at 19–21 weeks and at 23–24 weeks of gestation. Univariable and multivariable logistic regression analyses were employed to identify predictive maternal characteristics, biochemical and sonographic factors. Receiver operating characteristic (ROC) curve analysis was used to determine predictors for the most accurate model. Results: Of 3477 screened women, 77 (2.2%) had PPROM. Maternal factors predictive of PPROM in univariable analysis were nulliparity (OR 2.0 (95% CI 1.2–3.3)), PAPP-A < 0.5 MoM (OR 2.6 (1.1–6.2)), previous preterm birth (OR 4.2 (1.9–8.9)), previous cervical conization (OR 3.6 (2.0–6.4)) and cervical length ≤ 25 mm on transvaginal imaging (first-trimester OR 15.9 (4.3–59.3)). These factors all remained statistically significant in a multivariable adjusted model with an AUC of 0.72 in the most discriminatory first-trimester model. The detection rate using this model would be approximately 30% at a false-positive rate of 10%. Potential predictors such as bleeding in early pregnancy and pre-existing diabetes mellitus affected very few cases and could not be formally assessed. Conclusions: Several maternal characteristics, placental biochemical and sonographic features are predictive of PPROM with moderate discrimination. Larger numbers are required to validate this algorithm and additional biomarkers, not currently used for first-trimester screening, may improve model performance

Nuchal translucency of 3.0-3.4 mm an indication for NIPT or microarray? Cohort analysis and literature review

Introduction: Currently fetal nuchal translucency (NT) ≥3.5 mm is an indication for invasive testing often followed by chromosomal microarray. The aim of this study was to assess the risks for chromosomal aberrations in fetuses with an NT 3.0-3.4 mm, to determine whether invasive prenatal testing would be relevant in these cases and to assess the residual risks in fetuses with normal non-invasive prenatal test (NIPT) results. Material and methods: A retrospective study and meta-analysis of literature cases with NT between 3.0 and 3.4 mm and 2 cohorts of pregnant women referred for invasive testing and chromosomal microarray was performed: Rotterdam region (with a risk >1:200 and NT between 3.0 and 3.4 mm) tested in the period July 2012 to June 2019 and Central Denmark region (with a risk >1:300 and NT between 3.0 and 3.4 mm) tested between September 2015 and December 2018. Results: A total of 522 fetuses were referred for invasive testing and chromosomal microarray. Meta-analysis indicated that in 1:7.4 (13.5% [95% CI 8.2%-21.5%]) fetuses a chromosomal aberration was diagnosed. Of these aberrant cases, 47/68 (69%) involved trisomy 21, 18, and 13 and would potentially be detected by all NIPT approaches. The residual risk for missing a (sub)microscopic chromosome aberration depends on the NIPT approach and is highest if NIPT was performed only for common trisomies–1:21 (4.8% [95% CI 3.2%-7.3%]). However, it may be substantially lowered if a genome-wide 10-Mb resolution NIPT test was offered (~1:464). Conclusions: Based on these data, we suggest that the NT cut-off for invasive testing could be 3.0 mm (instead of 3.5 mm) because of the high risk of 1:7.4 for a chromosomal aberration. If women were offered NIPT first, there would be a significant diagnostic delay because all abnormal NIPT results need to be confirmed by diagnostic testing. If the woman had already received a normal NIPT result, the residual risk of 1:21 to 1:464 for chromosome aberrations other than common trisomies, dependent on the NIPT approach, should be raised. If a pregnant woman declines invasive testing, but still wants a test with a broader coverage of clinically significant conditions then the genome-wide >10-Mb resolution NIPT test, which detects most aberrations, could be proposed

Nuchal translucency of 3.0-3.4 mm an indication for NIPT or microarray? Cohort analysis and literature review

Introduction: Currently fetal nuchal translucency (NT) ≥3.5 mm is an indication for invasive testing often followed by chromosomal microarray. The aim of this study was to assess the risks for chromosomal aberrations in fetuses with an NT 3.0-3.4 mm, to determine whether invasive prenatal testing would be relevant in these cases and to assess the residual risks in fetuses with normal non-invasive prenatal test (NIPT) results. Material and methods: A retrospective study and meta-analysis of literature cases with NT between 3.0 and 3.4 mm and 2 cohorts of pregnant women referred for invasive testing and chromosomal microarray was performed: Rotterdam region (with a risk >1:200 and NT between 3.0 and 3.4 mm) tested in the period July 2012 to June 2019 and Central Denmark region (with a risk >1:300 and NT between 3.0 and 3.4 mm) tested between September 2015 and December 2018. Results: A total of 522 fetuses were referred for invasive testing and chromosomal microarray. Meta-analysis indicated that in 1:7.4 (13.5% [95% CI 8.2%-21.5%]) fetuses a chromosomal aberration was diagnosed. Of these aberrant cases, 47/68 (69%) involved trisomy 21, 18, and 13 and would potentially be detected by all NIPT approaches. The residual risk for missing a (sub)microscopic chromosome aberration depends on the NIPT approach and is highest if NIPT was performed only for common trisomies–1:21 (4.8% [95% CI 3.2%-7.3%]). However, it may be substantially lowered if a genome-wide 10-Mb resolution NIPT test was offered (~1:464). Conclusions: Based on these data, we suggest that the NT cut-off for invasive testing could be 3.0 mm (instead of 3.5 mm) because of the high risk of 1:7.4 for a chromosomal aberration. If women were offered NIPT first, there would be a significant diagnostic delay because all abnormal NIPT results need to be confirmed by diagnostic testing. If the woman had already received a normal NIPT result, the residual risk of 1:21 to 1:464 for chromosome aberrations other than common trisomies, dependent on the NIPT approach, should be raised. If a pregnant woman declines invasive testing, but still wants a test with a broader coverage of clinically significant conditions then the genome-wide >10-Mb resolution NIPT test, which detects most aberrations, could be proposed

Current use of noninvasive prenatal testing in Europe, Australia and the USA : A graphical presentation

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Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD