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Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset.
Stelzer, Ina A; Ghaemi, Mohammad S; Han, Xiaoyuan; Ando, Kazuo; Hédou, Julien J; Feyaerts, Dorien; Peterson, Laura S; Rumer, Kristen K; Tsai, Eileen S; Ganio, Edward A; Gaudillière, Dyani K; Tsai, Amy S; Choisy, Benjamin; Gaigne, Lea P; Verdonk, Franck; Jacobsen, Danielle; Gavasso, Sonia; Traber, Gavin M; Ellenberger, Mathew; Stanley, Natalie; Becker, Martin; Culos, Anthony; Fallahzadeh, Ramin; Wong, Ronald J; Darmstadt, Gary L; Druzin, Maurice L; Winn, Virginia D; Gibbs, Ronald S; Ling, Xuefeng B; Sylvester, Karl; Carvalho, Brendan; Snyder, Michael P; Shaw, Gary M; Stevenson, David K; Contrepois, Kévin; Angst, Martin S; Aghaeepour, Nima; Gaudillière, Brice.
Afiliación
  • Stelzer IA; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Ghaemi MS; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Han X; Digital Technologies Research Centre, National Research Council Canada, Toronto, ON M5T 3J1, Canada.
  • Ando K; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Hédou JJ; Department of Biomedical Sciences, University of the Pacific, Arthur A. Dugoni School of Dentistry, San Francisco, CA 94103, USA.
  • Feyaerts D; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Peterson LS; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Rumer KK; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Tsai ES; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Ganio EA; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Gaudillière DK; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Tsai AS; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Choisy B; Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Gaigne LP; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Verdonk F; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Jacobsen D; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Gavasso S; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Traber GM; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Ellenberger M; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Stanley N; Department of Neurology, NeuroSys-Med, Haukeland University Hospital, 5021 Bergen, Norway.
  • Becker M; Department of Genetics, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Culos A; Department of Genetics, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Fallahzadeh R; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Wong RJ; Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Darmstadt GL; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Druzin ML; Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Winn VD; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Gibbs RS; Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Ling XB; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Sylvester K; Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Carvalho B; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Snyder MP; Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Shaw GM; Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Stevenson DK; Department of Obstetrics and Gynecology, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Contrepois K; Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Angst MS; Department of Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Aghaeepour N; Department of Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
  • Gaudillière B; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
Sci Transl Med ; 13(592)2021 05 05.
Article en En | MEDLINE | ID: mdl-33952678
ABSTRACT
Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10-40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10-7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inicio del Trabajo de Parto / Proteoma / Metaboloma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inicio del Trabajo de Parto / Proteoma / Metaboloma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy Idioma: En Año: 2021 Tipo del documento: Article