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[This corrects the article DOI: 10.1371/journal.pmed.1004036.].
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BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. METHODS AND FINDINGS: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. CONCLUSIONS: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.
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Sobrepeso , Nacimiento Prematuro , Niño , Embarazo , Femenino , Humanos , Recién Nacido , Lactante , Preescolar , Adolescente , Sobrepeso/epidemiología , Sobrepeso/complicaciones , Edad Gestacional , Factores de Riesgo , Nacimiento Prematuro/epidemiología , Estudios de Cohortes , Peso al Nacer , Índice de Masa CorporalRESUMEN
International sharing of cohort data for research is important and challenging. We explored the feasibility of multi-cohort federated analyses by examining associations between three pregnancy exposures (maternal education, exposure to green vegetation and gestational diabetes) with offspring BMI from infancy to 17 years. We used data from 18 cohorts (n=206,180 mother-child pairs) from the EU Child Cohort Network and derived BMI at ages 0-1, 2-3, 4-7, 8-13 and 14-17 years. Associations were estimated using linear regression via one-stage IPD meta-analysis using DataSHIELD. Associations between lower maternal education and higher child BMI emerged from age 4 and increased with age (difference in BMI z-score comparing low with high education age 2-3 years = 0.03 [95% CI 0.00, 0.05], 4-7 years = 0.16 [95% CI 0.14, 0.17], 8-13 years = 0.24 [95% CI 0.22, 0.26]). Gestational diabetes was positively associated with BMI from 8 years (BMI z-score difference = 0.18 [CI 0.12, 0.25]) but not at younger ages; however associations attenuated towards the null when restricted to cohorts which measured GDM via universal screening. Exposure to green vegetation was weakly associated with higher BMI up to age one but not at older ages. Opportunities of cross-cohort federated analyses are discussed.
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BACKGROUND: Studies examining associations of early-life cat and dog ownership with childhood asthma have reported inconsistent results. Several factors could explain these inconsistencies, including type of pet, timing, and degree of exposure. OBJECTIVE: Our aim was to study associations of early-life cat and dog ownership with asthma in school-aged children, including the role of type (cat vs dog), timing (never, prenatal, or early childhood), and degree of ownership (number of pets owned), and the role of allergic sensitization. METHODS: We used harmonized data from 77,434 mother-child dyads from 9 birth cohorts in the European Union Child Cohort Network when the child was 5 to 11 years old. Associations were examined through the DataSHIELD platform by using adjusted logistic regression models, which were fitted separately for each cohort and combined by using random effects meta-analysis. RESULTS: The prevalence of early-life cat and dog ownership ranged from 12% to 45% and 7% to 47%, respectively, and the prevalence of asthma ranged from 2% to 20%. There was no overall association between either cat or dog ownership and asthma (odds ratio [OR] = 0.97 [95% CI = 0.87-1.09] and 0.92 [95% CI = 0.85-1.01], respectively). Timing and degree of ownership did not strongly influence associations. Cat and dog ownership were also not associated with cat- and dog-specific allergic sensitization (OR = 0.92 [95% CI = 0.75-1.13] and 0.93 [95% CI = 0.57-1.54], respectively). However, cat- and dog-specific allergic sensitization was strongly associated with school-age asthma (OR = 6.69 [95% CI = 4.91-9.10] and 5.98 [95% CI = 3.14-11.36], respectively). There was also some indication of an interaction between ownership and sensitization, suggesting that ownership may exacerbate the risks associated with pet-specific sensitization but offer some protection against asthma in the absence of sensitization. CONCLUSION: Our findings do not support early-life cat and dog ownership in themselves increasing the risk of school-age asthma, but they do suggest that ownership may potentially exacerbate the risks associated with cat- and dog-specific allergic sensitization.
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Alérgenos , Asma , Animales , Asma/epidemiología , Gatos , Niño , Preescolar , Estudios de Cohortes , Perros , Exposición a Riesgos Ambientales , Humanos , Oportunidad Relativa , PropiedadRESUMEN
The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.
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Bases de Datos Factuales/normas , Difusión de la Información , Niño , Preescolar , Estudios de Cohortes , Europa (Continente) , Humanos , Salud PúblicaRESUMEN
MOTIVATION: The volume and complexity of biological data increases rapidly. Many clinical professionals and biomedical researchers without a bioinformatics background are generating big '-omics' data, but do not always have the tools to manage, process or publicly share these data. RESULTS: Here we present MOLGENIS Research, an open-source web-application to collect, manage, analyze, visualize and share large and complex biomedical datasets, without the need for advanced bioinformatics skills. AVAILABILITY AND IMPLEMENTATION: MOLGENIS Research is freely available (open source software). It can be installed from source code (see http://github.com/molgenis), downloaded as a precompiled WAR file (for your own server), setup inside a Docker container (see http://molgenis.github.io), or requested as a Software-as-a-Service subscription. For a public demo instance and complete installation instructions see http://molgenis.org/research.
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Biología Computacional , Programas Informáticos , Algoritmos , Genoma , GenómicaRESUMEN
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.
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Exposición a Riesgos Ambientales , Enfermedades no Transmisibles , Adolescente , Niño , Preescolar , Estudios de Cohortes , Bases de Datos Factuales , Salud Ambiental , Unión Europea , Femenino , Humanos , Lactante , Masculino , Padres , Embarazo , Factores de Riesgo , Factores SocioeconómicosRESUMEN
The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our "modern" postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered. LongITools, as one of the 9 projects included in the European Human Exposome Network, will tackle this environmental health equation linking multidimensional environmental exposures to the occurrence of cardiovascular and metabolic noncommunicable diseases.
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Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward.