Host-derived protein profiles of human neonatal meconium across gestational ages.

Journal: Nature communications
PMID:

Abstract

Meconium, a non-invasive biomaterial reflecting prenatal substance accumulation, could provide valuable insights into neonatal health. However, the comprehensive protein profile of meconium across gestational ages remains unclear. Here, we conducted an extensive proteomic analysis of first meconium from 259 newborns across varied gestational ages to delineate protein composition and elucidate its relevance to neonatal diseases. The first meconium samples were collected, with the majority obtained before feeding, and the mean time for the first meconium passage from the anus was 11.9 ± 9.47 h. Our analysis revealed 5370 host-derived meconium proteins, which varied depending on sex and gestational age. Specifically, meconium from preterm infants exhibited elevated concentrations of proteins associated with the extracellular matrix. Additionally, the protein profiles of meconium also exhibited unique variations depending on both specific diseases, including gastrointestinal diseases, congenital heart diseases, and maternal conditions. Furthermore, we developed a machine learning model to predict gestational ages using meconium proteins. Our model suggests that newborns with gastrointestinal diseases and congenital heart diseases may have immature gastrointestinal systems. These findings highlight the intricate relationship between clinical parameters and meconium protein composition, offering potential for a novel approach to assess neonatal gastrointestinal health.

Authors

  • Yoshihiko Shitara
    Department of Pediatrics, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Ryo Konno
    Department of Applied Genomics, Kazusa DNA Research Institute, Chiba, Japan.
  • Masahito Yoshihara
    Institute for Advanced Academic Research (IAAR), Chiba University, Chiba, Japan.
  • Kohei Kashima
    Department of Pediatrics, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Atsushi Ito
    Department of Thoracic and Cardiovascular Surgery Mie University School of Medicine, Tsu, Japan.
  • Takeo Mukai
    Department of Pediatrics, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Goh Kimoto
    Department of Pediatrics, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Satsuki Kakiuchi
    Department of Pediatrics, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Masaki Ishikawa
    Department of Applied Genomics, Kazusa DNA Research Institute, Chiba, Japan.
  • Tomo Kakihara
    Department of Pediatric Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Takeshi Nagamatsu
    Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8654, Japan.
  • Naoto Takahashi
    AI Laboratory, Sapporo City University, Sapporo, Japan.
  • Jun Fujishiro
    Department of Pediatric Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
  • Eiryo Kawakami
    Medical Sciences Innovation Hub Program, RIKEN, Yokohama, Kanagawa, Japan.
  • Osamu Ohara
    Department of Technology Development Kazusa DNA Research Institute Chiba Japan.
  • Yusuke Kawashima
    Department of Maxillofacial Radiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan.
  • Eiichiro Watanabe
    Department of Pediatric Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, Japan. eiichiro.watanabe.riken@gmail.com.