Network identification of hormonal regulation

PLoS One. 2014 May 22;9(5):e96284. doi: 10.1371/journal.pone.0096284. eCollection 2014.

Abstract

Relations among hormone serum concentrations are complex and depend on various factors, including gender, age, body mass index, diurnal rhythms and secretion stochastics. Therefore, endocrine deviations from healthy homeostasis are not easily detected or understood. A generic method is presented for detecting regulatory relations between hormones. This is demonstrated with a cohort of obese women, who underwent blood sampling at 10 minute intervals for 24-hours. The cohort was treated with bromocriptine in an attempt to clarify how hormone relations change by treatment. The detected regulatory relations are summarized in a network graph and treatment-induced changes in the relations are determined. The proposed method identifies many relations, including well-known ones. Ultimately, the method provides ways to improve the description and understanding of normal hormonal relations and deviations caused by disease or treatment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cohort Studies
  • Computer Simulation
  • Female
  • Hormones / blood*
  • Hormones / metabolism
  • Humans
  • Models, Biological
  • Obesity / blood*
  • Obesity / metabolism
  • Perimenopause / blood
  • Perimenopause / metabolism
  • Periodicity

Substances

  • Hormones

Grants and funding

TNO Quality of Life supported this research from the systems biology program (www.tno.nl) and The Netherlands Metabolomics Center, which is part of the Netherlands Genomics Initiative of the Netherlands Organization for Scientific Research (http://www.metabolomicscentre.nl/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.