|
1
|
Espinosa CA, Khan W, Khanam R, Das S, Khalid J, Pervin J, Kasaro MP, Contrepois K, Chang AL, Phongpreecha T, Michael B, Ellenberger M, Mehmood U, Hotwani A, Nizar A, Kabir F, Wong RJ, Becker M, Berson E, Culos A, De Francesco D, Mataraso S, Ravindra N, Thuraiappah M, Xenochristou M, Stelzer IA, Marić I, Dutta A, Raqib R, Ahmed S, Rahman S, Hasan ASMT, Ali SM, Juma MH, Rahman M, Aktar S, Deb S, Price JT, Wise PH, Winn VD, Druzin ML, Gibbs RS, Darmstadt GL, Murray JC, Stringer JSA, Gaudilliere B, Snyder MP, Angst MS, Rahman A, Baqui AH, Jehan F, Nisar MI, Vwalika B, Sazawal S, Shaw GM, Stevenson DK, Aghaeepour N. Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries. Sci Adv 2023; 9:eade7692. [PMID: 37224249 DOI: 10.1126/sciadv.ade7692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 04/20/2023] [Indexed: 05/26/2023]
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.
Collapse
Affiliation(s)
- Camilo A Espinosa
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Waqasuddin Khan
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Rasheda Khanam
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sayan Das
- Centre for Public Health Kinetics, New Delhi, Delhi, India
| | - Javairia Khalid
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Jesmin Pervin
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Margaret P Kasaro
- University of North Carolina Global Projects Zambia, Lusaka, Zambia
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Alan L Chang
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Thanaphong Phongpreecha
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Basil Michael
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Mathew Ellenberger
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Usma Mehmood
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Aneeta Hotwani
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Ambreen Nizar
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Furqan Kabir
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Ronald J Wong
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin Becker
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Eloise Berson
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Columbia University, New York, NY, USA
| | - Davide De Francesco
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Samson Mataraso
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Neal Ravindra
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Melan Thuraiappah
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Maria Xenochristou
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Ina A Stelzer
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ivana Marić
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Arup Dutta
- Centre for Public Health Kinetics, New Delhi, Delhi, India
| | - Rubhana Raqib
- International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | | | | | | | - Said M Ali
- Public Health Laboratory-Ivo de Carneri, Pemba, Zanzibar, Tanzania
| | - Mohamed H Juma
- Public Health Laboratory-Ivo de Carneri, Pemba, Zanzibar, Tanzania
| | - Monjur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Shaki Aktar
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Saikat Deb
- Centre for Public Health Kinetics, New Delhi, Delhi, India
- Public Health Laboratory-Ivo de Carneri, Pemba, Zanzibar, Tanzania
| | - Joan T Price
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Paul H Wise
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Maurice L Druzin
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Ronald S Gibbs
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Gary L Darmstadt
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jeffrey C Murray
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Jeffrey S A Stringer
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Anisur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Abdullah H Baqui
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Fyezah Jehan
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Muhammad Imran Nisar
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan
| | - Bellington Vwalika
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Sunil Sazawal
- Centre for Public Health Kinetics, New Delhi, Delhi, India
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Gary M Shaw
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - David K Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| |
Collapse
|
|
2
|
Juliana NCA, Deb S, Juma MH, Poort L, Budding AE, Mbarouk A, Ali SM, Ouburg S, Morré SA, Sazawal S, Ambrosino E. The Vaginal Microbiota Composition and Genital Infections during and after Pregnancy among Women in Pemba Island, Tanzania. Microorganisms 2022; 10:microorganisms10030509. [PMID: 35336085 PMCID: PMC8951098 DOI: 10.3390/microorganisms10030509] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 02/03/2022] [Accepted: 02/21/2022] [Indexed: 01/25/2023] Open
Abstract
We investigated the vaginal microbiota (VMB) composition, prevalence of genital pathogens and their association among pregnant and post-delivery women in Pemba Island, Tanzania. Vaginal swabs were collected from 90 women, at two time points during pregnancy (<20 weeks of gestational age [GA] and ≥20 weeks GA) and once after delivery, when possible. IS-pro assay was used for VMB characterization. Chlamydia trachomatis (CT), Neisseria gonorrhea (NG), Trichomonas vaginalis (TV), Mycoplasma genitalium (MG) and human papillomavirus (HPV) were detected by qPCRs. VMB were mostly Lactobacillus dominant during pregnancy and non-Lactobacillus dominant post-delivery. A significant decrease in VMB richness was observed during pregnancy among paired and unpaired samples. Shannon diversity was significantly lower during pregnancy than post-delivery among unpaired samples. Klebsiella species and Streptococcus anginosus were the most commonly identified pathobionts at all timepoints. A high abundance of pathobionts was mostly seen in women with non-Lactobacillus dominant VMB. At ≥20 weeks GA timepoint during pregnancy, 63.0% of the women carrying one or more genital pathogen (either HPV, CT, TV, or MG) had L. iners dominant VMB. NG was not detected pre-delivery. This study contributes evidence on VMB composition, its changes during pregnancy and post-delivery, and their association with pathobionts and genital pathogens.
Collapse
Affiliation(s)
- Naomi C. A. Juliana
- Institute for Public Health Genomics (IPHG), Department of Genetics and Cell Biology, Research School GROW (School for Oncology & Reproduction), Faculty of Health, Medicine & Life Sciences, University of Maastricht, 6200 Maastricht, The Netherlands; (N.C.A.J.); (S.A.M.)
| | - Saikat Deb
- Public Health Laboratory—Ivo de Carneri, Chake Chake 74201, Pemba Island, Tanzania; (S.D.); (M.H.J.); (A.M.); (S.M.A.)
- Centre for Public Health Kinetics, New Delhi 110024, India;
| | - Mohamed H. Juma
- Public Health Laboratory—Ivo de Carneri, Chake Chake 74201, Pemba Island, Tanzania; (S.D.); (M.H.J.); (A.M.); (S.M.A.)
| | - Linda Poort
- inBiome, 1098 Amsterdam, The Netherlands; (L.P.); (A.E.B.)
| | | | - Abdalla Mbarouk
- Public Health Laboratory—Ivo de Carneri, Chake Chake 74201, Pemba Island, Tanzania; (S.D.); (M.H.J.); (A.M.); (S.M.A.)
| | - Said M. Ali
- Public Health Laboratory—Ivo de Carneri, Chake Chake 74201, Pemba Island, Tanzania; (S.D.); (M.H.J.); (A.M.); (S.M.A.)
| | - Sander Ouburg
- Laboratory of Immunogenetics, Department of Medical Microbiology and Infection Control, Amsterdam UMC, Location AMC, 1105 Amsterdam, The Netherlands;
| | - Servaas A. Morré
- Institute for Public Health Genomics (IPHG), Department of Genetics and Cell Biology, Research School GROW (School for Oncology & Reproduction), Faculty of Health, Medicine & Life Sciences, University of Maastricht, 6200 Maastricht, The Netherlands; (N.C.A.J.); (S.A.M.)
| | - Sunil Sazawal
- Centre for Public Health Kinetics, New Delhi 110024, India;
| | - Elena Ambrosino
- Institute for Public Health Genomics (IPHG), Department of Genetics and Cell Biology, Research School GROW (School for Oncology & Reproduction), Faculty of Health, Medicine & Life Sciences, University of Maastricht, 6200 Maastricht, The Netherlands; (N.C.A.J.); (S.A.M.)
- Correspondence: ; Tel.: +31-04-3388-4081
| |
Collapse
|