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Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries.
Espinosa, Camilo A; Khan, Waqasuddin; Khanam, Rasheda; Das, Sayan; Khalid, Javairia; Pervin, Jesmin; Kasaro, Margaret P; Contrepois, Kévin; Chang, Alan L; Phongpreecha, Thanaphong; Michael, Basil; Ellenberger, Mathew; Mehmood, Usma; Hotwani, Aneeta; Nizar, Ambreen; Kabir, Furqan; Wong, Ronald J; Becker, Martin; Berson, Eloise; Culos, Anthony; De Francesco, Davide; Mataraso, Samson; Ravindra, Neal; Thuraiappah, Melan; Xenochristou, Maria; Stelzer, Ina A; Maric, Ivana; Dutta, Arup; Raqib, Rubhana; Ahmed, Salahuddin; Rahman, Sayedur; Hasan, A S M Tarik; Ali, Said M; Juma, Mohamed H; Rahman, Monjur; Aktar, Shaki; Deb, Saikat; Price, Joan T; Wise, Paul H; Winn, Virginia D; Druzin, Maurice L; Gibbs, Ronald S; Darmstadt, Gary L; Murray, Jeffrey C; Stringer, Jeffrey S A; Gaudilliere, Brice; Snyder, Michael P; Angst, Martin S; Rahman, Anisur; Baqui, Abdullah H.
Afiliação
  • Espinosa CA; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Khan W; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Khanam R; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Das S; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
  • Khalid J; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Pervin J; Centre for Public Health Kinetics, New Delhi, Delhi, India.
  • Kasaro MP; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
  • Contrepois K; Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh.
  • Chang AL; University of North Carolina Global Projects Zambia, Lusaka, Zambia.
  • Phongpreecha T; Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
  • Michael B; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Ellenberger M; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Mehmood U; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Hotwani A; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Nizar A; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Kabir F; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Wong RJ; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
  • Becker M; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Berson E; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
  • Culos A; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
  • De Francesco D; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
  • Mataraso S; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
  • Ravindra N; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
  • Thuraiappah M; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Xenochristou M; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Stelzer IA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Maric I; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Dutta A; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Raqib R; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Ahmed S; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
  • Rahman S; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Hasan ASMT; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Ali SM; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Juma MH; Department of Computer Science, Columbia University, New York, NY, USA.
  • Rahman M; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Aktar S; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Deb S; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Price JT; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Wise PH; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Winn VD; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Druzin ML; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Gibbs RS; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Darmstadt GL; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Murray JC; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Stringer JSA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Gaudilliere B; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Snyder MP; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Angst MS; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Rahman A; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
  • Baqui AH; Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Sci Adv ; 9(21): eade7692, 2023 05 24.
Article em En | MEDLINE | ID: mdl-37224249
ABSTRACT
Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate proteomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nascimento Prematuro Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans / Newborn / Pregnancy Idioma: En Revista: Sci Adv Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nascimento Prematuro Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans / Newborn / Pregnancy Idioma: En Revista: Sci Adv Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos