Clinical Medicine

Feto-Maternal Medical Science

Establishment of Personalized Perinatal Medicine by Integrative Analysis of Gene-Environment Interaction

Medical Sciences Course

  • Master / Doctoral Degree



Professor, MD, PhD

*Concurrent Position

Research Theme

  • Genome analysis for perinatal diseases (e.g. pregnancy induced hypertension)
  • Multi-omics analysis for pregnancy related disorders
  • Early prediction by Bioinformatics for Pregnancy related disorders
Research Keywords:

Pregnancy induced hypertension, Genome, Omics, Obstetrics and gynecology, Community medicine

Technical Keywords:

Genome analysis, GWAS, Omics analysis

Laboratory Introduction

1. ToMMo Birth and Three Generation Cohort Study
Though this cohort project, we have started multi-omics analysis to clarify pathophysiology of perinatal disorders. Particularly, genetic analysis with family tree genomic information would be powerful tools to elucidate undetermined mechanisms of maternal-fetal disorders.

2. Early Prediction by Bioinformatics for Pregnancy Related Disorders
In the MLOG (Maternity Life Log) project, participants will collect daily health parameters, such as body weight, duration of sleep, activity amount, blood pressure and body temperature using health care devices. With the multilayer integration of these life log information, lifestyle habits and omics analysis, we try to establish mobile healthcare programs for the prediction of pregnancy related disorders, including pregnancy induced hypertension, gestational diabetes and premature labor. MLOG project is the collaborative research with NTT DOCOMO with a widely accepted commercial service of mobile health service in Japan.

3. Establishment of Biomarkers for the diagnosis of feto-maternal disorders.
Using newly developed in silico technology, proteome analysis by the project team with Prof. Terasaki has been just started. This study would reveal new biomarkers for the early prediction of perinatal disease (e.g. preeclampsia). Development of clinical diagnostic systems for personalized prevention would be strongly expected.

Figure 1.

Figure 1.

Recent Publications

  • Saigusa D, et al. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery. PLoS One. 2016 Aug 31;11(8):e0160555.
  • Koshiba S, et al. The structural origin of metabolic quantitative diversity. Sci Rep. 2016 Aug 16;6:31463.
  • Kuriyama S, et al. The Tohoku Medical Megabank Project: Design and Mission. J Epidemiol. 2016 Sep 5;26(9):493-511.
  • Sugawara J, et al. Impact of the Great East Japan Earthquake on Regional Obstetrical Care in Miyagi Prefecture. Prehosp Disaster Med. 2016 Jun;31(3):255-8.
  • Nagasaki M, et al. Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals. Nat Commun. 2015 Aug 21;6:8018.