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

Junichi Sugawara, Daisuke Ochi, Riu Yamashita, Takafumi Yamauchi, Daisuke Saigusa, Maiko Wagata, Taku Obara, Mami Ishikuro, Yoshiki Tsunemoto, Yuki Harada, Tomoko Shibata, Takahiro Mimori, Junko Kawashima, Fumiki Katsuoka, Takako Igarashi-Takai, Soichi Ogishima, Hirohito Metoki, Hiroaki Hashizume, Nobuo Fuse, Naoko MinegishiSeizo Koshiba, Osamu Tanabe, Shinichi Kuriyama, Kengo Kinoshita, Shigeo Kure, Nobuo Yaegashi, Masayuki Yamamoto, Satoshi Hiyama, Masao Nagasaki

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.

Original languageEnglish
Article numbere025939
JournalBMJ Open
Issue number2
Publication statusPublished - 2019 Feb 1


  • complicated pregnancy
  • lifelog
  • multi-omics analysis
  • prediction


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