Alan M Ezrin1, Brian Brohman2, Jackie Willmot3, Sarah Baxter4, Keith Moore5, Mike Luther6, Michael R Fannon7, Baha Sibai8. 1. NX Prenatal Inc., Louisville, Kentucky. 2. NX Prenatal Inc., Maternal Fetal Medicine Program, Louisville, Kentucky. 3. Department of Prenatal Diagnostics, NX Prenatal Inc., Maternal Fetal Medicine Program, Louisville, Kentucky. 4. David H. Murdock Research Institute, Kannapolis, North Carolina. 5. Moore BioAnalysis, Blue Bell, Pennsylvania. 6. Department of Discovery and Development, AMRI, Burlington, Massachusetts. 7. BioIT Solutions Inc., Silver Spring, Maryland. 8. Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Texas Health Science Center at Houston (UTHealth) Medical School, Houston, Texas.
Abstract
OBJECTIVE: The purpose of this study was to determine whether the proteomic biosignature of circulating microparticles in maternal serum obtained in the second trimester could identify pregnancies that result in spontaneous preterm birth (SPTB). STUDY DESIGN: Microparticles were isolated from blinded biorepository-sourced serum samples from 48 pregnant women at 15 to 17 weeks of gestation. Microparticle proteins were extracted and analyzed using label-free liquid chromatography/mass spectrometry. Peptide features were analyzed to assess the association of specific protein patterns with subjects delivering at term (≥ 37 weeks gestation; n = 24) and those experiencing SPTB (≤ 34 weeks gestation; n = 24). RESULTS: We found 99 proteins that had statistically significant differences in signal intensity between term and SPTB women in both first (n = 26) and second (n = 22) singleton gestation pregnancy cohorts. Additional evaluation identified 18 biomarkers that met criteria for further priority evaluation (12 preterm, 6 term). Pathway analysis showed that differentiating SPTB biomarker proteins were predominantly associated with inflammation and cell injury, while differentiating term biomarkers were associated with cell growth and hematological parameters. CONCLUSION: This study shows for the first time that the proteomic content of serum microparticles isolated in the second trimester can identify with a high degree of accuracy pregnancies that result in SPTB. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
OBJECTIVE: The purpose of this study was to determine whether the proteomic biosignature of circulating microparticles in maternal serum obtained in the second trimester could identify pregnancies that result in spontaneous preterm birth (SPTB). STUDY DESIGN: Microparticles were isolated from blinded biorepository-sourced serum samples from 48 pregnant women at 15 to 17 weeks of gestation. Microparticle proteins were extracted and analyzed using label-free liquid chromatography/mass spectrometry. Peptide features were analyzed to assess the association of specific protein patterns with subjects delivering at term (≥ 37 weeks gestation; n = 24) and those experiencing SPTB (≤ 34 weeks gestation; n = 24). RESULTS: We found 99 proteins that had statistically significant differences in signal intensity between term and SPTB women in both first (n = 26) and second (n = 22) singleton gestation pregnancy cohorts. Additional evaluation identified 18 biomarkers that met criteria for further priority evaluation (12 preterm, 6 term). Pathway analysis showed that differentiating SPTB biomarker proteins were predominantly associated with inflammation and cell injury, while differentiating term biomarkers were associated with cell growth and hematological parameters. CONCLUSION: This study shows for the first time that the proteomic content of serum microparticles isolated in the second trimester can identify with a high degree of accuracy pregnancies that result in SPTB. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Authors: David E Cantonwine; Zhen Zhang; Kevin Rosenblatt; Kevin S Goudy; Robert C Doss; Alan M Ezrin; Gail Page; Brian Brohman; Thomas F McElrath Journal: Am J Obstet Gynecol Date: 2016-02-11 Impact factor: 8.661
Authors: Thomas F McElrath; David E Cantonwine; Kathryn J Gray; Hooman Mirzakhani; Robert C Doss; Najmuddin Khaja; Malik Khalid; Gail Page; Brian Brohman; Zhen Zhang; David Sarracino; Kevin P Rosenblatt Journal: Sci Rep Date: 2020-10-21 Impact factor: 4.379