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

      research-article
      1 , 2 , , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 4 , 15 , 20 , 23 , 24 , 25 , 26 , 27 , 17 , 9 , 10 , 28 , 29 , 30 , 12 , 31 , 3 , 32 , 32 , 24 , 8 , 33 , 34 , 35 , 36 , 18 , 37 , 38 , 33 , 34 , 35 , 30 , 1 , 2 , LifeCycle Project Group
      European Journal of Epidemiology
      Springer Netherlands
      Consortium, Birth cohorts, Exposome, Life course, Non-communicable diseases

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          Abstract

          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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          The online version of this article (10.1007/s10654-020-00662-z) contains supplementary material, which is available to authorized users.

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          Most cited references55

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          The Danish National Birth Cohort--its background, structure and aim.

          It is well known that the time from conception to early childhood has importance for health conditions that reach into later stages of life. Recent research supports this view, and diseases such as cardiovascular morbidity, cancer, mental illnesses, asthma, and allergy may all have component causes that act early in life. Exposures in this period, which influence fetal growth, cell divisions, and organ functioning, may have long-lasting impact on health and disease susceptibility. To investigate these issues the Danish National Birth Cohort (Better health for mother and child) was established. A large cohort of pregnant women with long-term follow-up of the offspring was the obvious choice because many of the exposures of interest cannot be reconstructed with sufficient validity back in time. The study needs to be large, and it is aimed to recruit 100,000 women early in pregnancy, and to continue follow-up for decades. The Nordic countries are better suited for this kind of research than most other countries because of their population-based registers on diseases, demography and social conditions, linkable at the individual level by means of the unique ID-number given to all citizens. Exposure information is mainly collected by computer-assisted telephone interviews with the women twice during pregnancy and when their children are six and 18 months old. Participants are also asked to fill in a self-administered food frequency questionnaire in mid-pregnancy. Furthermore, a biological bank has been set up with blood taken from the mother twice during pregnancy and blood from the umbilical cord taken shortly after birth. Data collection started in 1996 and the project covered all regions in Denmark in 1999. By August 2000. a total of 60,000 pregnant women had been recruited to the study. It is expected that a large number of gene-environmental hypotheses need to be based on case-control analyses within a cohort like this.
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            Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

            Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n=321,223) and offspring birth weight (n=230,069 mothers), we identified 190 independent association signals (129 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic effects, and then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of those alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
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              Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta‐analysis of European, North American, and Australian cohorts

              To assess the separate and combined associations of maternal pre-pregnancy BMI and gestational weight gain with the risks of pregnancy complications and their population impact. Individual participant data meta-analysis of 39 cohorts. Europe, North America and Oceania. 265,270 births. Information on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used. Gestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large size for gestational age at birth. Higher maternal pre-pregnancy BMI and gestational weight gain were, across their full ranges, associated with higher risks of gestational hypertensive disorders, gestational diabetes and large size for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared to normal weight mothers with medium gestational weight gain, obese mothers with high gestational weight gain had the highest risk of any pregnancy complication (Odds Ratio 2.51 (95% Confidence Interval 2.31, 2.74)). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large size for gestational age infants was attributable to excessive gestational weight gain. Maternal pre-pregnancy BMI and gestational weight gain are, across their full ranges, associated with the risks of pregnancy complications. Obese mothers with high gestational weight gain are at the highest risk of pregnancy complications. Promoting a healthy pre-pregnancy BMI and gestational weight gain may reduce the burden of pregnancy complications and ultimately the risk of maternal and neonatal morbidity. Promoting a healthy body mass index and gestational weight gain might reduce the population burden of pregnancy complications.
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                Author and article information

                Contributors
                v.jaddoe@erasmusmc.nl
                Journal
                Eur J Epidemiol
                Eur. J. Epidemiol
                European Journal of Epidemiology
                Springer Netherlands (Dordrecht )
                0393-2990
                1573-7284
                23 July 2020
                23 July 2020
                2020
                : 35
                : 7
                : 709-724
                Affiliations
                [1 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Pediatrics, , Erasmus MC, University Medical Center Rotterdam, The Generation R Study Group, ; (Na 29-18), PO Box 2040, 3000 CA Rotterdam, The Netherlands
                [2 ]GRID grid.5645.2, ISNI 000000040459992X, Generation R Study Group, , Erasmus MC, University Medical Center Rotterdam, ; Rotterdam, The Netherlands
                [3 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Section of Epidemiology, Department of Public Health, , University of Copenhagen, ; Copenhagen, Denmark
                [4 ]Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
                [5 ]GRID grid.77048.3c, ISNI 0000 0001 2286 7412, ELFE Joint Unit, , French Institute for Demographic Studies (Ined), French Institute for Medical Research and Health (INSERM), French Blood Agency, ; Aubervilliers, France
                [6 ]GRID grid.42505.36, ISNI 0000 0001 2156 6853, Department of Preventive Medicine, Keck School of Medicine, , University of Southern California, ; Los Angeles, CA USA
                [7 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Epidemiology, , University of Groningen, University Medical Center Groningen, ; Groningen, The Netherlands
                [8 ]GRID grid.424223.1, Concentris Research Management GmbH, ; Fürstenfeldbruck, Germany
                [9 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, MRC Integrative Epidemiology Unit, , University of Bristol, ; Bristol, UK
                [10 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, Population Health Sciences, Bristol Medical School, , University of Bristol, ; Bristol, UK
                [11 ]GRID grid.7737.4, ISNI 0000 0004 0410 2071, Department of General Practice and Primary Health Care, , University of Helsinki and Helsinki University Hospital, ; Helsinki, Finland
                [12 ]GRID grid.428673.c, ISNI 0000 0004 0409 6302, Folkhälsan Research Center, ; Helsinki, Finland
                [13 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Obstetrics and Gynecology, Yong Loo Lin School of Medicine, , National University of Singapore and National University Health System, ; Singapore, Singapore
                [14 ]GRID grid.452264.3, ISNI 0000 0004 0530 269X, Singapore Institute for Clinical Sciences (SICS), Agency for Science and Technology (A*STAR), ; Singapore, Singapore
                [15 ]GRID grid.414659.b, ISNI 0000 0000 8828 1230, Telethon Kids Institute, ; Perth, WA Australia
                [16 ]GRID grid.1032.0, ISNI 0000 0004 0375 4078, School of Physiotherapy and Exercise Science, , Curtin University, ; Perth, WA Australia
                [17 ]Department of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital, LMU, Munich, Germany
                [18 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, University of Groningen, University Medical Center Groningen, Genomics Coordination Center, ; Groningen, The Netherlands
                [19 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, Institute of Developmental Sciences, Faculty of Medicine, , University of Southampton, ; Southampton, UK
                [20 ]GRID grid.430506.4, NIHR Southampton Biomedical Research Centre, , University of Southampton and University Hospital Southampton NHS Foundation Trust, ; Southampton, UK
                [21 ]GRID grid.418193.6, ISNI 0000 0001 1541 4204, Centre for Fertility and Health, The Norwegian Institute of Public Health, ; Oslo, Norway
                [22 ]GRID grid.418193.6, ISNI 0000 0001 1541 4204, Division of Health Data and Digitalization, , Norwegian Institute of Public Health, ; Oslo, Norway
                [23 ]MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
                [24 ]GRID grid.10858.34, ISNI 0000 0001 0941 4873, Center for Life-Course Health Research, Faculty of Medicine, , University of Oulu, ; Oulu, Finland
                [25 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, , School of Public Health, Imperial College London, ; London, UK
                [26 ]GRID grid.7728.a, ISNI 0000 0001 0724 6933, Department of Life Sciences, College of Health and Life Sciences, , Brunel University London, ; London, UK
                [27 ]GRID grid.412326.0, ISNI 0000 0004 4685 4917, Unit of Primary Health Care, , Oulu University Hospital, OYS, ; Oulu, Finland
                [28 ]NIHR Bristol Biomedical Research Centre, Bristol, UK
                [29 ]GRID grid.12380.38, ISNI 0000 0004 1754 9227, Department of Economics, , VU University Amsterdam, ; Amsterdam, The Netherlands
                [30 ]GRID grid.418449.4, ISNI 0000 0004 0379 5398, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, ; Bradford, UK
                [31 ]GRID grid.418193.6, ISNI 0000 0001 1541 4204, Department of Genetics and Bioinformatics, Division of Health Data and Digitalisation, , Norwegian Institute of Public Health, ; Oslo, Norway
                [32 ]GRID grid.7605.4, ISNI 0000 0001 2336 6580, Cancer Epidemiology Unit, Department of Medical Sciences, , University of Turin, ; Turin, Italy
                [33 ]GRID grid.434607.2, ISNI 0000 0004 1763 3517, ISGlobal, ; Barcelona, Spain
                [34 ]GRID grid.5612.0, ISNI 0000 0001 2172 2676, Universitat Pompeu Fabra (UPF), ; Barcelona, Spain
                [35 ]GRID grid.413448.e, ISNI 0000 0000 9314 1427, CIBER Epidemiología y Salud Pública (CIBERESP), ; Barcelona, Spain
                [36 ]GRID grid.411142.3, ISNI 0000 0004 1767 8811, IMIM (Hospital del Mar Medical Research Institute), ; Barcelona, Spain
                [37 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Genetics, , University of Groningen, University Medical Center Groningen, ; Groningen, The Netherlands
                [38 ]GRID grid.8127.c, ISNI 0000 0004 0576 3437, Department of Social Medicine, Faculty of Medicine, , University of Crete, ; Heraklion, Crete, Greece
                Author information
                http://orcid.org/0000-0003-2939-0041
                Article
                662
                10.1007/s10654-020-00662-z
                7387322
                32705500
                33afb1a4-1c39-4831-b5d0-c596924dea6d
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 May 2020
                : 4 July 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100010676, H2020 Societal Challenges;
                Award ID: 733206
                Award Recipient :
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                © Springer Nature B.V. 2020

                Public health
                consortium,birth cohorts,exposome,life course,non-communicable diseases
                Public health
                consortium, birth cohorts, exposome, life course, non-communicable diseases

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