M Sean Esplin1, Tracy A Manuck2, Michael W Varner2, Bryce Christensen3, Joseph Biggio4, Radek Bukowski5, Samuel Parry6, Heping Zhang7, Hao Huang7, William Andrews4, George Saade5, Yoel Sadovsky8, Uma M Reddy9, John Ilekis9. 1. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Utah School of Medicine, and Department of Maternal-Fetal Medicine, Intermountain Healthcare, Salt Lake City, UT. Electronic address: sean.esplin@imail.org. 2. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Utah School of Medicine, and Department of Maternal-Fetal Medicine, Intermountain Healthcare, Salt Lake City, UT. 3. Golden Helix, Bozeman, MT. 4. Department of Obstetrics and Gynecology, University of Alabama at Birmingham School of Medicine, Birmingham, AL. 5. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX. 6. Department of Obstetrics and Gynecology, University of Pennsylvania School of Medicine, Philadelphia, PA. 7. Department of Biostatistics, Yale University School of Public Health, New Haven, CT. 8. Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA. 9. Pregnancy and Perinatology Branch, Center for Developmental Biology and Perinatal Medicine, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD.
Abstract
OBJECTIVE: We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. STUDY DESIGN: We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. RESULTS: One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. CONCLUSION: We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB.
OBJECTIVE: We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. STUDY DESIGN: We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. RESULTS: One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. CONCLUSION: We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB.
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