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Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach

Authors :
Jonathan Yinhao Huang
Shirong Cai
Zhongwei Huang
Mya Thway Tint
Wen Lun Yuan
Izzuddin M. Aris
Keith M. Godfrey
Neerja Karnani
Yung Seng Lee
Jerry Kok Yen Chan
Yap Seng Chong
Johan Gunnar Eriksson
Shiao-Yng Chan
Source :
Nature Communications, Vol 12, Iss 1, Pp 1-16 (2021)
Publication Year :
2021
Publisher :
Nature Portfolio, 2021.

Abstract

Huang and colleagues used machine-learning estimators to analyse a broad range of parameters in a prospective cohort consisting ART and spontaneously conceived children. Small differences in stature and growth could not be explained by parental or perinatal environment factors, nor differences in fetal DNA methylation. No strong differences in metabolic parameters were seen.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.0dcc6959279147e19b2fae8d5e9574cb
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-021-25899-4