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Eur J Epidemiol. 2019 Mar;34(3):279-300. doi: 10.1007/s10654-019-00502-9. Epub 2019 Mar 18.

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects.

Author information

1
Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia. c.middeldorp@uq.edu.au.
2
Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia. c.middeldorp@uq.edu.au.
3
Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT, Amsterdam, The Netherlands. c.middeldorp@uq.edu.au.
4
The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3015 CE, Rotterdam, The Netherlands.
5
Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, 3015 CE, Rotterdam, The Netherlands.
6
Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, 3015 CE, Rotterdam, The Netherlands.
7
Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
8
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, OX3 7LE, UK.
9
Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Oxford, OX3 7LE, UK.

Abstract

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

KEYWORDS:

Childhood traits and disorders; Consortium; Genetics; Longitudinal

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