Using Big Data to Predict and Prevent Preterm Birth

Photo for BlogWorldwide, preterm birth is the leading cause of death for all children under age 5, taking the lives of more than 1.1 million children every year. Now, new research utilizing the emerging field of systems biology aims to harness big data in an effort to reduce the global burden of preterm birth.

Seattle is well known as a technology hub, and big data has become an area of great focus and opportunity. Advances in technology now allow for analysis of data sets that would have been much more difficult to accomplish just 10 years ago.

The Global Alliance to Prevent Prematurity and Stillbirth (GAPPS), an initiative of Seattle Children’s, is announcing three new projects that will use big data to help discover the root causes of preterm birth and identify potential targets for interventions to improve pregnancy health. In this case, big data is defined as large and complex data sets generated from biological components like molecules and cells, which require computational and mathematical modeling to interpret.

“We’re excited to bring researchers skilled in big data generation and analysis to the field of preterm birth,” said Dr. Craig Rubens, executive director of GAPPS. “Using systems biology approaches to research a global health crisis like preterm birth opens many new doors for discovering what causes babies to be born too soon and developing new prevention techniques.”

The projects, each two years in length, are funded through the Preventing Preterm Birth initiative, a Grand Challenge in Global Health administered by GAPPS. Each research project uses one or more systems biology approaches in a pilot study to analyze data and biological specimens donated and collected throughout the course of pregnancy.

Systems biology, also known as “-omics” biology, includes cutting-edge fields such as transcriptomics (the study of RNA molecules in cells), proteomics (the large scale study of proteins), metabolomics (the study of cellular metabolites), lipidomics (the study of cellular fats and naturally occurring molecules) and the microbiome (a collection of microorganisms living within the human body). Essentially it focuses on studying the interactions between components of biological systems and how these interactions cause the system to behave. In recent years, systems biology has been widely adapted to study different diseases, but up until now, it was poorly utilized in researching pregnancy complications such as preterm birth.

New projects funded to help predict and prevent preterm birth

  • Gregory Buck, PhD, and Jennifer Fettweis, PhD, and their team at Virginia Commonwealth University will perform proteomic and metabolomic analysis on biospecimens from pregnant women. They will research changes in the microbiome throughout pregnancy and determine how they contribute to preterm birth. This will help them identify predictive biomarkers that will allow development of early interventions to prevent preterm birth and other adverse pregnancy outcomes.
  • Elaine Holmes, PhD, and her team at Imperial College London will research the microbiome and metabolome of pregnant women who deliver either at term or preterm, and evaluate connections between biological processes of pregnancy by analyzing data to predict women at risk for preterm birth.
  • Robert C. Murphy, PhD, and his team at University of Colorado Denver will investigate lipid and hormone biochemistry of pregnant women who deliver either at term or preterm. They will use mass spectrometry – a way of measuring the characteristics of individual molecules by turning them into ions – to analyze a broad spectrum of lipids in biospecimens from pregnant women to identify biomarkers and determine pregnant women at risk for preterm birth.

Preterm birth is a very broad term that is used to describe any number of ways that a baby is born too soon. The projects aim to discover the specific ways that preterm birth occurs, which will allow for better identification of women at risk, as well as development of specific prevention interventions that target each cause of preterm birth.

“Just as we don’t say someone has cancer, we say they have brain cancer, lung cancer, breast cancer, etc., because the type of cancer determines how we best address it,” Rubens said. “We want to be able to know specifically the different kinds of preterm birth so that each specific kind can be targeted and prevented.”