Project description
Assessing the health of ART-conceived children
Since the 1970s, artificial reproductive technology (ART) has resulted in millions of births worldwide. With infertility affecting 1 in 6 couples, ART is now perceived as a routine effective treatment. In this context, the EU-funded ART-HEALTH project will study the possible adverse effects on offspring health. Specifically, it will integrate evidence from diverse sources and use diverse methods to support a valid approach to assess the health and development of ART-conceived children, focusing on cardiometabolic health. To achieve its goal, ART-HEALTH will create and study data sets consisting of spontaneously conceived and ART-conceived children, supplemented by detailed information on couples undergoing treatment in relation to a group where spontaneous conception was possible.
Objective
Infertility affects 1 in 6 couples. With increasing numbers of artificial reproductive technology (ART) conceptions, understanding the effects of ART on maternal and offspring health has been designated a major research priority. Research to date has been highlighted as having limited quality and lacking methodological transparency. In ART-HEALTH we use a robust, systematic approach of triangulating different sources of evidence to address this.
work-package (WP) 1 will generate three new datasets with complementary sources of bias.
1. Birth cohort collaboration of 360,000 spontaneously conceived (SC) and 10,000 ART offspring. This will provide rich data on large numbers with ART offspring recruited, assessed and followed in identical ways to SC offspring.
2. Large ART cohort (5000 couples) with detailed information on treatments linked to a SC group that will have identical data collected from pregnancy to mid-childhood.
3. Large population record linkage of 200,000 contemporary ART births, 10,000 of their SC siblings and 400,000 general population SC births.
WP2 will triangulate evidence to determine the effects of ART on perinatal and offspring cardiometabolic health. It will compare results from the 3 datasets and updated systematic reviews, using conventional multivariable regression and within sibship analyses.
WP3 will analyse the datasets using Mendelian randomization, and multivariable regression in a counterfactual framework to explore pregnancy metabolomic mediation.
We will systematically and transparently assess risk of bias with each analytical method in each dataset and use bounds of causality and Bayesian approaches to integrate data.
PhD students, funded from elsewhere, will explore effects on parental and offspring mental health and cognitive function. In the final year we will work with colleagues in Brazil, Pakistan, a- ART is increasing
- Concerns about effects
- Evidence base limited
- Our objectives
- Why these will make a difference
Fields of science
Programme(s)
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Funding Scheme
ERC-ADG - Advanced GrantHost institution
BS8 1QU Bristol
United Kingdom