Maternal antibiotic use and vaginal infections in the third trimester of pregnancy and the risk of obesity in preschool children

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Determinants of SARS-CoV-2 Contagiousness in Household Contacts of Symptomatic Adult Index Cases

BACKGROUND: Identifying determinants of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission in settings of contagion is fundamental to inform containment strategies. We assessed SARS-CoV-2 cycle threshold value (Ct) from the first diagnostic nasal–pharyngeal swab of symptomatic index cases and which demographic or clinical characteristics among cases and contacts are associated with transmission risk within households. METHODS: This is a retrospective prevalence study on secondary SARS-CoV-2 cases (SC) among the household contacts of symptomatic adult index cases randomly sampled from all the SARS-CoV-2-positive diagnostic nasopharyngeal swabs analyzed at our regional referral hospital (Amedeo di Savoia Hospital, Turin, Italy) in March, 2020. Index cases underwent a telephone survey to collect their demographic and clinical data and all their household contacts. The Ct value of RdRp gene from the first diagnostic swab of index cases was recorded and index cases were grouped according to Ct tertiles (A < first tertile, first ≤ B ≤ second tertile, C ≥ second tertile). Post hoc analysis was performed in SC as well as contacts that did not undergo SARS-CoV-2 testing but developed compatible signs and symptoms. Non-parametric tests and generalized linear models were run. RESULTS: Index (n = 72) and contact (n = 164) median age was 54 (48–63) and 32 (20–56) years, respectively. A total of 60, 50, and 54 subjects were contacts of group A, B, and C index cases, respectively; 35.9% of contacts were SC. Twenty-four further subjects (14.6%) met the criteria for symptom-based likely positive SC. The secondary attack rate was 36.0% (28.6–43.4), assuming a mean incubation period of 5 days and a maximum infectious period of 20 days. SC prevalence differed between Ct groups (53.3% A, 32.0% B, 20.4% C; p < 0.001). No difference in SC was found according to sex, presence of signs/symptoms, and COVID-19 severity of index cases, or according to contacts’ sex and number per household. The age of both index cases [aOR 4.52 (1.2–17.0) for 60 vs. ≤45 years old] and contacts [aOR 3.66 (1.3–10.6) for 60 vs. ≤45years old] and the Ct of the index [aOR 0.17 (0.07–0.4) for Ct ≥ 31.8 vs. Ct < 24.4] independently associated with SC risk. Sensitivity analysis including symptoms-based likely positive SC supported all the previous results. CONCLUSION: In confined transmission settings such as households, PCR Ct values may inform on the contagiousness of infected subjects and age may modulate transmission/contagion risk

Green space exposure and blood DNA methylation at birth and in childhood – A multi-cohort study

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value &lt; 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.</p

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort

IntroductionProstate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research.MethodsThe TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study’s prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks.ResultsThe cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage.DiscussionThis study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa

The LifeCycle Project-EU Child Cohort Network : a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.Peer reviewe