TY - JOUR
T1 - Maternity Log study
T2 - A longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy
AU - Sugawara, Junichi
AU - Ochi, Daisuke
AU - Yamashita, Riu
AU - Yamauchi, Takafumi
AU - Saigusa, Daisuke
AU - Wagata, Maiko
AU - Obara, Taku
AU - Ishikuro, Mami
AU - Tsunemoto, Yoshiki
AU - Harada, Yuki
AU - Shibata, Tomoko
AU - Mimori, Takahiro
AU - Kawashima, Junko
AU - Katsuoka, Fumiki
AU - Igarashi-Takai, Takako
AU - Ogishima, Soichi
AU - Metoki, Hirohito
AU - Hashizume, Hiroaki
AU - Fuse, Nobuo
AU - Minegishi, Naoko
AU - Koshiba, Seizo
AU - Tanabe, Osamu
AU - Kuriyama, Shinichi
AU - Kinoshita, Kengo
AU - Kure, Shigeo
AU - Yaegashi, Nobuo
AU - Yamamoto, Masayuki
AU - Hiyama, Satoshi
AU - Nagasaki, Masao
N1 - Funding Information:
Funding The present study was supported by NTT DoCoMo, Inc, with a collaborative research agreement between NTT DoCoMo and ToMMo. This work was supported in part by the Tohoku Medical Megabank Project from the Japan Agency for Medical Research and Development and the Ministry of Education, Culture, Sports, Science and Technology. Competing interests This study was funded by NTT DoCoMo, Inc. DO, TY and SH are employees of NTT DoCoMo, Inc.
Publisher Copyright:
© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Purpose A 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. Participants Pregnant 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 date Study 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 plans Lifelog 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.
AB - Purpose A 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. Participants Pregnant 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 date Study 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 plans Lifelog 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.
KW - complicated pregnancy
KW - lifelog
KW - multi-omics analysis
KW - prediction
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UR - http://www.scopus.com/inward/citedby.url?scp=85061338921&partnerID=8YFLogxK
U2 - 10.1136/bmjopen-2018-025939
DO - 10.1136/bmjopen-2018-025939
M3 - Article
C2 - 30782942
AN - SCOPUS:85061338921
SN - 2044-6055
VL - 9
JO - BMJ Open
JF - BMJ Open
IS - 2
M1 - e025939
ER -
