In the United States at least 1 in 8 babies is born preterm (< 37 weeks), our ranking falling far behind those of other industrialized nations. In fact, prematurity rates here have risen over 36 percent in the last 25 years. About $51,600 is spent for every infant who is born prematurely, with annual medical costs associated with preterm birth exceeding $3 billion in the state of California alone. We also see disparities between racial and ethnic groups, with substantially elevated rates of preterm birth among African Americans. All things considered, it’s a seemingly intractable public health problem despite medical advances in obstetrics and newborn intensive care.
At Stanford we’re changing the way we think about preterm birth as traditional models in academia have failed to solve the problem. In 2011, with a generous $20 million grant from the March of Dimes, we launched the March of Dimes Prematurity Research Center at Stanford University. Over 130 scientists, doctors, researchers and staff are dedicated to reducing the rate of preterm birth and shrinking the disparity in prematurity among racial and ethnic groups. Our investigation requires the integration of researchers from multiple disciplines that together develop a new trandisciplinary language to facilitate understanding. Biologic, behavioral, social, physical and environmental disciplines converge to form new structures of scientific discovery.
Evidence suggests that gene-to-gene and gene-environment interactions are much more complex than we previously believed them to be. Where limits on resources and technology had once stalled progress, we are now studying large populations in a more comprehensive way using state-of-the-art approaches. The Center collects and analyzes unique, diverse data sets, including vital statistics and hospital discharge data from > 1 million preterm births (50,000 births for 20 years) in California and across the country. Working with our California Department of Public Health colleagues, Center investigators can access newborn bloodspots on every birth in California since 1983, and a mid-pregnancy blood specimen on >1,000,000 women.
The Center draws upon the patient base at Lucile Packard Children’s Hospital Stanford and partners with other Schools across Stanford University and elsewhere, combining the expertise of those in the fields of computer science, mathematics, engineering, biological and social science. With additional funding from the Children's Health Research Institute, we strive to improve outcomes for babies born in California. Our hope is that advancements will be extended nationally, and globally shortly thereafter.
Key Areas of Inquiry
- Bioinformatics Gene-Environment Discovery: Atul Butte’s laboratory is applying highly innovative bioinformatics methods to a variety of publically available genomic and environmental datasets, the goal being to elucidate the etiologies of preterm birth and improve diagnostics to detect early spontaneous preterm birth. They are also searching for variants that may disrupt gene regulation, predicting that a cluster of disruptive variants may predispose a woman to deliver preterm.
- Infection/Inflammation Discovery: David Relman’s laboratory aims to establish a benchmark description of the microbiome during pregnancy (normal and abnormal pregnancies, and with a focus on early spontaneous birth). Conducting the largest study of its kind to date, Relman and colleagues are characterizing changes in the microbiome using sampling data from multiple body sites of women during pre-pregnancy, pregnancy and post pregnancy. The group is also performing a longitudinal and comprehensive investigation of immune profiles during pregnancy of women with a history of preterm labor and birth, comparing those to the profiles of women with a history of term labor and birth.
- The Transcriptome: Stephen Quake’s laboratory, building upon the work conducted by the Butte and Relman groups, aims to characterize the transcriptome (reflects genes actively expressed) of the various phenotypes of preterm birth by collecting plasma samples from pregnant women and extracting cell-free RNA. The RNA is converted to cDNA and sequenced. It’s later analyzed using robust computational approaches in order to assess the variations in the transcriptome that exist with respect to early spontaneous preterm birth and other pregnancy complications.