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Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy

Authors :
Naoko Minegishi
Satoshi Hiyama
Soichi Ogishima
Mami Ishikuro
Tomoko Shibata
Daisuke Saigusa
Masao Nagasaki
Hirohito Metoki
Hiroaki Hashizume
Masayuki Yamamoto
Takahiro Mimori
Taku Obara
Nobuo Fuse
Riu Yamashita
yuki harada
Nobuo Yaegashi
Junko Kawashima
Kengo Kinoshita
Shinichi Kuriyama
Junichi Sugawara
Seizo Koshiba
Osamu Tanabe
Tsunemoto Yoshiki
Daisuke Ochi
Takako Igarashi-Takai
Shigeo Kure
Maiko Wagata
Fumiki Katsuoka
Takafumi Yamauchi
Source :
BMJ Open
Publication Year :
2019
Publisher :
BMJ Publishing Group, 2019.

Abstract

PurposeA prospective cohort study for pregnant women, the Maternity Log study, was designed to construct a time-course high-resolution reference catalogue of bioinformatic data in pregnancy and explore the associations between genomic and environmental factors and the onset of pregnancy complications, such as hypertensive disorders of pregnancy, gestational diabetes mellitus and preterm labour, using continuous lifestyle monitoring combined with multiomics data on the genome, transcriptome, proteome, metabolome and microbiome.ParticipantsPregnant women were recruited at the timing of first routine antenatal visits at Tohoku University Hospital, Sendai, Japan, between September 2015 and November 2016. Of the eligible women who were invited, 65.4% agreed to participate, and a total of 302 women were enrolled. The inclusion criteria were age ≥20 years and the ability to access the internet using a smartphone in the Japanese language.Findings to dateStudy participants uploaded daily general health information including quality of sleep, condition of bowel movements and the presence of nausea, pain and uterine contractions. Participants also collected physiological data, such as body weight, blood pressure, heart rate and body temperature, using multiple home healthcare devices. The mean upload rate for each lifelog item was ranging from 67.4% (fetal movement) to 85.3% (physical activity), and the total number of data points was over 6 million. Biospecimens, including maternal plasma, serum, urine, saliva, dental plaque and cord blood, were collected for multiomics analysis.Future plansLifelog and multiomics data will be used to construct a time-course high-resolution reference catalogue of pregnancy. The reference catalogue will allow us to discover relationships among multidimensional phenotypes and novel risk markers in pregnancy for the future personalised early prediction of pregnancy complications.

Details

Language :
English
ISSN :
20446055
Volume :
9
Issue :
2
Database :
OpenAIRE
Journal :
BMJ Open
Accession number :
edsair.doi.dedup.....6f14fba9b9ad2767c72dfcf234794647