Danish premature birth rates during the COVID-19 lockdown Hedermann, Gitte; Hedley, Paula Louise; Bækvad-Hansen, Marie ...
Archives of disease in childhood. Fetal and neonatal edition,
01/2021, Letnik:
106, Številka:
1
Journal Article
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To explore the impact of COVID-19 lockdown on premature birth rates in Denmark, a nationwide register-based prevalence proportion study was conducted on all 31 180 live singleton infants born in ...Denmark between 12 March and 14 April during 2015-2020.The distribution of gestational ages (GAs) was significantly different (p=0.004) during the lockdown period compared with the previous 5 years and was driven by a significantly lower rate of extremely premature children during the lockdown compared with the corresponding mean rate for the same dates in the previous years (OR 0.09, 95% CI 0.01 to 0.40, p<0.001). No significant difference between the lockdown and previous years was found for other GA categories.The reasons for this decrease are unclear. However, the lockdown has provided a unique opportunity to examine possible factors related to prematurity. Identification of possible causal mechanisms might stimulate changes in clinical practice.
This study aimed to evaluate the amniotic fluid protein profiles and the intensity of intraamniotic inflammatory response to Ureaplasma spp. and other bacteria, using the multiplex xMAP technology.
A ...retrospective cohort study was undertaken in the Department of Obstetrics and Gynecology, University Hospital Hradec Kralove, Czech Republic. A total of 145 pregnant women with preterm prelabor rupture of membranes between gestational age 24+0 and 36+6 weeks were included in the study. Amniocenteses were performed. The presence of Ureaplasma spp. and other bacteria was evaluated using 16S rRNA gene sequencing. The levels of specific proteins were determined using multiplex xMAP technology.
The presence of Ureaplasma spp. and other bacteria in the amniotic fluid was associated with increased levels of interleukin (IL)-6, IL-8, IL-10, brain-derived neurotropic factor, granulocyte macrophage colony stimulating factor, monocyte chemotactic protein-1, macrophage inflammatory protein-1, and matrix metalloproteinasis-9. Ureaplasma spp. were also associated with increased levels of neurotropin-3 and triggering receptor expressed on myeloid cells-1.
The presence of Ureaplasma spp. in the amniotic fluid is associated with a slightly different protein profile of inflammatory response, but the intensity of inflammatory response to Ureaplasma spp. is comparable with the inflammatory response to other bacteria.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Elevated latent prenatal steroidogenic activity has been found in the amniotic fluid of autistic boys, based on measuring prenatal androgens and other steroid hormones. To date, it is unclear if ...other prenatal steroids also contribute to autism likelihood. Prenatal oestrogens need to be investigated, as they play a key role in synaptogenesis and corticogenesis during prenatal development, in both males and females. Here we test whether levels of prenatal oestriol, oestradiol, oestrone and oestrone sulphate in amniotic fluid are associated with autism, in the same Danish Historic Birth Cohort, in which prenatal androgens were measured, using univariate logistic regression (n = 98 cases, n = 177 controls). We also make a like-to-like comparison between the prenatal oestrogens and androgens. Oestradiol, oestrone, oestriol and progesterone each related to autism in univariate analyses after correction with false discovery rate. A comparison of standardised odds ratios showed that oestradiol, oestrone and progesterone had the largest effects on autism likelihood. These results for the first time show that prenatal oestrogens contribute to autism likelihood, extending the finding of elevated prenatal steroidogenic activity in autism. This likely affects sexual differentiation, brain development and function.
IMPORTANCE: Diagnoses and treatment of mental disorders are hampered by the current lack of objective markers needed to provide a more precise diagnosis and treatment strategy. OBJECTIVE: To develop ...deep learning models to predict mental disorder diagnosis and severity spanning multiple diagnoses using nationwide register data, family and patient-specific diagnostic history, birth-related measurement, and genetics. DESIGN, SETTING, AND PARTICIPANTS: This study was conducted from May 1, 1981, to December 31, 2016. For the analysis, which used a Danish population-based case-cohort sample of individuals born between 1981 and 2005, genotype data and matched longitudinal health register data were taken from the longitudinal Danish population-based Integrative Psychiatric Research Consortium 2012 case-cohort study. Included were individuals with mental disorders (attention-deficit/hyperactivity disorder ADHD), autism spectrum disorder (ASD), major depressive disorder (MDD), bipolar disorder (BD), schizophrenia spectrum disorders (SCZ), and population controls. Data were analyzed from February 1, 2021, to January 24, 2022. EXPOSURE: At least 1 hospital contact with diagnosis of ADHD, ASD, MDD, BD, or SCZ. MAIN OUTCOMES AND MEASURES: The predictability of (1) mental disorder diagnosis and (2) severity trajectories (measured by future outpatient hospital contacts, admissions, and suicide attempts) were investigated using both a cross-diagnostic and single-disorder setup. Predictive power was measured by AUC, accuracy, and Matthews correlation coefficient (MCC), including an estimate of feature importance. RESULTS: A total of 63 535 individuals (mean SD age, 23 7 years; 34 944 male 55%; 28 591 female 45%) were included in the model. Based on data prior to diagnosis, the specific diagnosis was predicted in a multidiagnostic prediction model including the background population with an overall area under the curve (AUC) of 0.81 and MCC of 0.28, whereas the single-disorder models gave AUCs/MCCs of 0.84/0.54 for SCZ, 0.79/0.41 for BD, 0.77/0.39 for ASD, 0.74/0.38, for ADHD, and 0.74/0.38 for MDD. The most important data sets for multidiagnostic prediction were previous mental disorders and age (11%-23% reduction in prediction accuracy when removed) followed by family diagnoses, birth-related measurements, and genetic data (3%-5% reduction in prediction accuracy when removed). Furthermore, when predicting subsequent disease trajectories of the disorder, the most severe cases were the most easily predictable, with an AUC of 0.72. CONCLUSIONS AND RELEVANCE: Results of this diagnostic study suggest the possibility of combining genetics and registry data to predict both mental disorder diagnosis and disorder progression in a clinically relevant, cross-diagnostic setting prior to clinical assessment.
There is mounting evidence that seemingly diverse psychiatric disorders share genetic etiology, but the biological substrates mediating this overlap are not well characterized. Here we leverage the ...unique Integrative Psychiatric Research Consortium (iPSYCH) study, a nationally representative cohort ascertained through clinical psychiatric diagnoses indicated in Danish national health registers. We confirm previous reports of individual and cross-disorder single-nucleotide polymorphism heritability for major psychiatric disorders and perform a cross-disorder genome-wide association study. We identify four novel genome-wide significant loci encompassing variants predicted to regulate genes expressed in radial glia and interneurons in the developing neocortex during mid-gestation. This epoch is supported by partitioning cross-disorder single-nucleotide polymorphism heritability, which is enriched at regulatory chromatin active during fetal neurodevelopment. These findings suggest that dysregulation of genes that direct neurodevelopment by common genetic variants may result in general liability for many later psychiatric outcomes.
The exome sequences of approximately 8,000 children with autism spectrum disorder (ASD) and/or attention deficit hyperactivity disorder (ADHD) and 5,000 controls were analyzed, finding that ...individuals with ASD and individuals with ADHD had a similar burden of rare protein-truncating variants in evolutionarily constrained genes, both significantly higher than controls. This motivated a combined analysis across ASD and ADHD, identifying microtubule-associated protein 1A (MAP1A) as a new exome-wide significant gene conferring risk for childhood psychiatric disorders.
An important motivation for the construction of biobanks is to discover biomarkers that identify diseases at early, potentially curable stages. This will require biobanks from large numbers of ...individuals, preferably sampled repeatedly, where the samples are collected and stored under conditions that preserve potential biomarkers. Dried blood samples are attractive for biobanking because of the ease and low cost of collection and storage. Here we have investigated their suitability for protein measurements. Ninety-two proteins with relevance for oncology were analyzed using multiplex proximity extension assays (PEA) in dried blood spots collected on paper and stored for up to 30 years at either +4 °C or −24 °C.
Our main findings were that (1) the act of drying only slightly influenced detection of blood proteins (average correlation of 0.970), and in a reproducible manner (correlation of 0.999), (2) detection of some proteins was not significantly affected by storage over the full range of three decades (34 and 76% of the analyzed proteins at +4 °C and −24 °C, respectively), whereas levels of others decreased slowly during storage with half-lives in the range of 10 to 50 years, and (3) detectability of proteins was less affected in dried samples stored at −24 °C compared with at +4 °C, as the median protein abundance had decreased to 80 and 93% of starting levels after 10 years of storage at +4 °C or −24 °C, respectively. The results of our study are encouraging as they suggest an inexpensive means to collect large numbers of blood samples, even by the donors themselves, and to transport, and store biobanked samples as spots of whole blood dried on paper. Combined with emerging means to measure hundreds or thousands of protein, such biobanks could prove of great medical value by greatly enhancing discovery as well as routine analysis of blood biomarkers.
Epidemiological studies have provided evidence of an association between vitamin D insufficiency and depression and other mood disorders, and a role for vitamin D in various brain functions has been ...suggested. We hypothesized that low vitamin D status during pregnancy might increase the risk of postpartum depression (PPD). The objective of the study was thus to determine whether low vitamin D status during pregnancy was associated with postpartum depression. In a case-control study nested in the Danish National Birth Cohort, we measured late pregnancy serum concentrations of 25OHD3 in 605 women with PPD and 875 controls. Odds ratios OR) for PPD were calculated for six levels of 25OHD3. Overall, we found no association between vitamin D concentrations and risk of PPD (p = 0.08). Compared with women with vitamin D concentrations between 50 and 79 nmol/L, the adjusted odds ratios for PPD were 1.35 (95% CI: 0.64; 2.85), 0.83 (CI: 0.50; 1.39) and 1.13 (CI: 0.84; 1.51) among women with vitamin D concentrations < 15 nmol/L, 15-24 nmol/L and 25-49 nmol/L, respectively, and 1.53 (CI: 1.04; 2.26) and 1.89 (CI: 1.06; 3.37) among women with vitamin D concentrations of 80-99 nmol/L and ≥ 100 nmol/L, respectively. In an additional analysis among women with sufficient vitamin D (≥ 50 nmol/L), we observed a significant positive association between vitamin D concentrations and PPD. Our results did not support an association between low maternal vitamin D concentrations during pregnancy and risk of PPD. Instead, an increased risk of PPD was found among women with the highest vitamin D concentrations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In Denmark, a nationwide COVID-19 lockdown was implemented on March 12, 2020 and eased on April 14, 2020. The COVID-19 lockdown featured reduced prevalence of extremely preterm or extremely low ...birthweight births. This study aims to explore the impact of this COVID-19 lockdown on term birthweights in Denmark. We conducted a nationwide register-based cohort study on 27,870 live singleton infants, born at term (weeks 37-41), between March 12 and April 14, 2015-2020, using data from the Danish Neonatal Screening Biobank. Primary outcomes, corrected for confounders, were birthweight, small-for-gestational-age (SGA), and large-for-gestational-age (LGA), comparing the COVID-19 lockdown to the previous five years. Data were analysed using linear regression to assess associations with birthweight. Multinomial logistic regression was used to assess associations with relative-size-for-gestational-age (xGA) categories. Adjusted mean birthweight was significantly increased by 16.9 g (95% CI = 4.1-31.3) during the lockdown period. A dip in mean birthweight was found in gestational weeks 37 and 38 balanced by an increase in weeks 40 and 41. The 2020 lockdown period was associated with an increased LGA prevalence (aOR 1.13, 95% CI = 1.05-1.21). No significant changes in proportions of xGA groups were found between 2015 and 2019. The nationwide COVID-19 lockdown resulted in a small but significant increase in birthweight and proportion of LGA infants, driven by an increase in birthweight in gestational weeks 40 and 41.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The predictive performance of polygenic scores (PGS) is largely dependent on the number of samples available to train the PGS. Increasing the sample size for a specific phenotype is expensive and ...takes time, but this sample size can be effectively increased by using genetically correlated phenotypes. We propose a framework to generate multi-PGS from thousands of publicly available genome-wide association studies (GWAS) with no need to individually select the most relevant ones. In this study, the multi-PGS framework increases prediction accuracy over single PGS for all included psychiatric disorders and other available outcomes, with prediction R
increases of up to 9-fold for attention-deficit/hyperactivity disorder compared to a single PGS. We also generate multi-PGS for phenotypes without an existing GWAS and for case-case predictions. We benchmark the multi-PGS framework against other methods and highlight its potential application to new emerging biobanks.
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