Acute maternal infection and risk of pre-eclampsia: a population-based case-control study.

BACKGROUND: Infection in pregnancy may be involved in the aetiology of pre-eclampsia. However, a clear association between acute maternal infection and pre-eclampsia has not been established. We assessed whether acute urinary tract infection, respiratory tract infection, and antibiotic drug prescriptions in pregnancy (a likely proxy for maternal infection) are associated with an increased risk of pre-eclampsia. METHODS AND FINDINGS: We used a matched nested case-control design and data from the UK General Practice Research Database to examine the association between maternal infection and pre-eclampsia. Primiparous women aged at least 13 years and registered with a participating practice between January 1987 and October 2007 were eligible for inclusion. We selected all cases of pre-eclampsia and a random sample of primiparous women without pre-eclampsia (controls). Cases (n=1533) were individually matched with up to ten controls (n=14236) on practice and year of delivery. We calculated odds ratios and 95% confidence intervals for pre-eclampsia comparing women exposed and unexposed to infection using multivariable conditional logistic regression. After adjusting for maternal age, pre-gestational hypertension, diabetes, renal disease and multifetal gestation, the odds of pre-eclampsia were increased in women prescribed antibiotic drugs (adjusted odds ratio 1.28;1.14-1.44) and in women with urinary tract infection (adjusted odds ratio 1.22;1.03-1.45). We found no association with maternal respiratory tract infection (adjusted odds ratio 0.91;0.72-1.16). Further adjustment for maternal smoking and pre-pregnancy body mass index made no difference to our findings. CONCLUSIONS: Women who acquire a urinary infection during pregnancy, but not those who have a respiratory infection, are at an increased risk of pre-eclampsia. Maternal antibiotic prescriptions are also associated with an increased risk. Further research is required to elucidate the underlying mechanism of this association and to determine whether, among women who acquire infections in pregnancy, prompt treatment or prophylaxis against infection might reduce the risk of pre-eclampsia

Long-term psychological effects of COVID-19-related quarantine: an observational study of three cohorts in Norway and Iceland

Background: Longitudinal assessments of psychological effects related to length and recency of quarantine experience in general populations are of importance. We aim to investigate if recency and duration of quarantine exposures during the COVID-19 pandemic were associated with mental health, across subgroups. Methods: We included three prospective cohorts from Iceland and Norway with data on quarantine and symptoms of depression and anxiety from March 2020 to March 2022. We calculated prevalence ratios (PR) of probable depression and anxiety in relation to quarantine exposure, and performed longitudinal analyses in a subpopulation with repeated assessments to test the potential change in mental health burden due to quarantine over time while controlling for current quarantine status and other covariates. Results: In total, 105,344 and 94,435 individuals were included in the analysis of probable depression and anxiety, respectively, with 18.2% and 40.0% reporting quarantine exposure before the most recent assessment of corresponding mental health symptoms. Overall, quarantine exposure was associated with probable depression (PR 1.19 [95% CI: 0.99–1.42]) and anxiety (PR 1.21 [1.08–1.36]). Compared to individuals without quarantine, being exposed to quarantine for 0–2, 2–4, or > 4 weeks was associated with incrementally higher prevalence of probable depression (PR 1.15 [0.93–1.43]; 1.34 [1.06–1.68]; 1.72 [1.35–2.18], respectively) and probable anxiety (PR 1.12 [1.01–1.23]; 1.28 [1.14–1.45]; 1.76 [1.56–1.98]) in a step-wise manner; those who were quarantined within the last 2 weeks, last 2–4 weeks, or earlier showed a higher prevalence of probable depression in a dose–response manner (PR 1.62 [1.32–1.99], 1.32 [1.07–1.63], and 1.23 [1.06–1.43], respectively). The prevalence of probable anxiety did not appear to differ by the recency of quarantine. The longitudinal analyses (mean follow-up: 20.5 months) confirmed significantly higher prevalence of probable depression but only among those who were quarantined for > 4 weeks (PR 1.61 [1.30–2.00]), and of probable anxiety among those quarantined 2–4 weeks (PR 1.29 [1.14–1.45]) and > 4 weeks (PR 1.56 [1.34–1.82]). Conclusions: This study underscores the importance of monitoring mental well-being of populations recently quarantined, particularly those quarantined for prolonged periods. Greater emphasis should be placed on the detrimental psychological effects in the risk-cost–benefit analysis of quarantine as a mitigation strategy in future pandemics

Acute COVID-19 severity and mental health morbidity trajectories in patient populations of six nations:An observational study

BACKGROUND: Long-term mental and physical health consequences of COVID-19 (long COVID) are a persistent public health concern. Little is still known about the long-term mental health of non-hospitalised patients with COVID-19 with varying illness severities. Our aim was to assess the prevalence of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis.METHODS: This observational follow-up study included seven prospectively planned cohorts across six countries (Denmark, Estonia, Iceland, Norway, Sweden, and the UK). Participants were recruited from March 27, 2020, to Aug 13, 2021. Individuals aged 18 years or older were eligible to participate. In a cross-sectional analysis, we contrasted symptom prevalence of depression, anxiety, COVID-19-related distress, and poor sleep quality (screened with validated mental health instruments) among individuals with and without a diagnosis of COVID-19 at entry, 0-16 months from diagnosis. In a cohort analysis, we further used repeated measures to estimate the change in mental health symptoms before and after COVID-19 diagnosis.FINDINGS: The analytical cohort consisted of 247 249 individuals, 9979 (4·0%) of whom were diagnosed with COVID-19 during the study period. Mean follow-up was 5·65 months (SD 4·26). Participants diagnosed with COVID-19 presented overall with a higher prevalence of symptoms of depression (prevalence ratio [PR] 1·18 [95% CI 1·03-1·36]) and poorer sleep quality (1·13 [1·03-1·24]) but not symptoms of anxiety (0·97 [0·91-1·03]) or COVID-19-related distress (1·05 [0·93-1·20]) compared with individuals without a COVID-19 diagnosis. Although the prevalence of depression and COVID-19-related distress attenuated with time, individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risk of depression (PR 0·83 [95% CI 0·75-0·91]) and anxiety (0·77 [0·63-0·94]) than those not diagnosed with COVID-19, whereas patients who were bedridden for more than 7 days were persistently at higher risk of symptoms of depression (PR 1·61 [95% CI 1·27-2·05]) and anxiety (1·43 [1·26-1·63]) than those not diagnosed throughout the study period.INTERPRETATION: Severe acute COVID-19 illness-indicated by extended time bedridden-is associated with long-term mental morbidity among recovering individuals in the general population. These findings call for increased vigilance of adverse mental health development among patients with a severe acute disease phase of COVID-19.FUNDING: Nordforsk, Horizon2020, Wellcome Trust, and Estonian Research Council

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Mental distress among Norwegian adults during the Covid-19 pandemic: predictors of initial response and subsequent trajectories

SummaryBackgroundUnderstanding factors associated with mental distress during a pandemic is imperative for planning interventions to reduce the negative mental health impact of future crises. Our aim was to identify factors associated with change in levels of mental distress in the Norwegian adult population at the onset of the Covid-19 pandemic, relative to pre-pandemic levels, and with longitudinal changes in mental distress until vaccination against Covid-19 became widespread in Norway (the first 1.5 years of the pandemic).MethodsThe Norwegian Mother, Father and Child Cohort Study (MoBa) is a prospective longitudinal study with baseline recruitment from 1999-2009. Baseline characteristics and eight waves of data collection during the pandemic (between March 2020 and September 2021) were used for this analysis. Mental distress was measured with the 5-item version of Hopkins Symptoms Checklist (HSCL-5). A piecewise latent growth model was fitted to identify initial change in mental distress (March-early April 2020, adjusting for pre-pandemic mental distress measured during prior years of data collection) and longitudinal changes across the pandemic in three distinct periods.FindingsOur sample consisted of 105 972 adult participants (59.6% females). Mental distress levels peaked at the beginning of the pandemic. Several factors were associated with initial increases in distress: chronic medical conditions, living alone, history of psychiatric disorders, relatively lower educational background, female sex, younger age, and obesity. Several of these factors were also associated with long-term change. Being quarantined or having to isolate was associated with the likelihood of increasing distress during the pandemic. We observed a reduction in distress associated with Covid-19 vaccination status, while being infected with SARS-CoV-2 was associated with increasing distress late in the pandemic.InterpretationPre-pandemic vulnerability factors – like having a chronic disease – as well as Covid-19-related factors – like being quarantined or infected by SARS-CoV-2 – were associated with increased mental distress during the pandemic. This knowledge is important for planning of interventions to support vulnerable individuals during pandemics and other health crises.FundingThe Norwegian Ministry of Health, and Care Services and the Ministry of Education and Research. NordForsk, The Research Council of Norway, The South-Eastern Norway Regional Health Authority.</jats:sec