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Robinson JF, Das S, Khan W, Khanam R, Price JT, Rahman A, Ahmed S, Ali SM, Deb S, Deveale B, Dutta A, Gormley M, Hall SC, Hasan ASMT, Hotwani A, Juma MH, Kasaro MP, Khalid J, Kshetrapal P, McMaster MT, Mehmood U, Nisar I, Pervin J, Rahman S, Raqib R, San A, Sarker P, Tuomivaara ST, Zhang G, Zhou Y, Aktar S, Baqui AH, Jehan F, Sazawal S, Stringer JSA, Fisher SJ. High rates of placental inflammation among samples collected by the Multi-Omics for Mothers and Infants consortium. Am J Obstet Gynecol 2024:S0002-9378(24)00560-X. [PMID: 38697337 DOI: 10.1016/j.ajog.2024.04.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 04/18/2024] [Accepted: 04/24/2024] [Indexed: 05/04/2024]
Abstract
BACKGROUND The Multi-Omics for Mothers and Infants consortium aims to improve birth outcomes. Preterm birth is a major obstetrical complication globally and causes significant infant and childhood morbidity and mortality. OBJECTIVE We analyzed placental samples (basal plate, placenta or chorionic villi, and the chorionic plate) collected by the 5 Multi-Omics for Mothers and Infants sites, namely The Alliance for Maternal and Newborn Health Improvement Bangladesh, The Alliance for Maternal and Newborn Health Improvement Pakistan, The Alliance for Maternal and Newborn Health Improvement Tanzania, The Global Alliance to Prevent Prematurity and Stillbirth Bangladesh, and The Global Alliance to Prevent Prematurity and Stillbirth Zambia. The goal was to analyze the morphology and gene expression of samples collected from preterm and uncomplicated term births. STUDY DESIGN The teams provided biopsies from 166 singleton preterm (<37 weeks' gestation) and 175 term (≥37 weeks' gestation) deliveries. The samples were fixed in formalin and paraffin embedded. Tissue sections from these samples were stained with hematoxylin and eosin and subjected to morphologic analyses. Other placental biopsies (n=35 preterm, 21 term) were flash frozen, which enabled RNA purification for bulk transcriptomics. RESULTS The morphologic analyses revealed a surprisingly high rate of inflammation that involved the basal plate, placenta or chorionic villi, and the chorionic plate. The rate of inflammation in chorionic villus samples, likely attributable to chronic villitis, ranged from 25% (Pakistan site) to 60% (Zambia site) of cases. Leukocyte infiltration in this location vs in the basal plate or chorionic plate correlated with preterm birth. Our transcriptomic analyses identified 267 genes that were differentially expressed between placentas from preterm vs those from term births (123 upregulated, 144 downregulated). Mapping the differentially expressed genes onto single-cell RNA sequencing data from human placentas suggested that all the component cell types, either singly or in subsets, contributed to the observed dysregulation. Consistent with the histopathologic findings, gene ontology analyses highlighted the presence of leukocyte infiltration or activation and inflammatory responses in both the fetal and maternal compartments. CONCLUSION The relationship between placental inflammation and preterm birth is appreciated in developed countries. In this study, we showed that this link also exists in developing geographies. In addition, among the participating sites, we found geographic- and population-based differences in placental inflammation and preterm birth, suggesting the importance of local factors.
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Affiliation(s)
- Joshua F Robinson
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA
| | - Sayan Das
- Public Health Laboratory Ivo de Carneri, Wawi, Chake, Pemba, Zanzibar, Tanzania
| | - Waqasuddin Khan
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan
| | - Rasheda Khanam
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Joan T Price
- UNC Global Projects - Zambia, Lusaka, Zambia; Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Anisur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | | | - Said Mohammed Ali
- Public Health Laboratory Ivo de Carneri, Wawi, Chake, Pemba, Zanzibar, Tanzania
| | - Saikat Deb
- Public Health Laboratory Ivo de Carneri, Wawi, Chake, Pemba, Zanzibar, Tanzania; Center for Public Health Kinetics, Vinoba Puri, Lajpatnagar II, New Delhi, India
| | - Brian Deveale
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA; Department of Urology, University of California, San Francisco, San Francisco, CA
| | - Arup Dutta
- Center for Public Health Kinetics, Vinoba Puri, Lajpatnagar II, New Delhi, India
| | - Matthew Gormley
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA; Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, San Francisco, CA
| | - Steven C Hall
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA; Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, San Francisco, CA
| | - A S M Tarik Hasan
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Aneeta Hotwani
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan
| | - Mohamed Hamid Juma
- Public Health Laboratory Ivo de Carneri, Wawi, Chake, Pemba, Zanzibar, Tanzania
| | - Margaret P Kasaro
- UNC Global Projects - Zambia, Lusaka, Zambia; Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC; Department of Gynaecology and Obstetrics, University of Zambia School of Medicine, Lusaka, Zambia
| | - Javairia Khalid
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan
| | - Pallavi Kshetrapal
- Maternal and Child Health, Translational Health Science and Technology Institute, Faridabad, India
| | - Michael T McMaster
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA; Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA
| | - Usma Mehmood
- Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan
| | - Imran Nisar
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan
| | - Jesmin Pervin
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Sayedur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh; Projahnmo Research Foundation, Dhaka, Bangladesh
| | - Rubhana Raqib
- International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Ali San
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA
| | - Protim Sarker
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Sami T Tuomivaara
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA; Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, San Francisco, CA
| | - Ge Zhang
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH; Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati Children's Hospital Medical Center and Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
| | - Yan Zhou
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA
| | - Shaki Aktar
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Abdullah H Baqui
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Fyezah Jehan
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan; Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi, Pakistan
| | - Sunil Sazawal
- Center for Public Health Kinetics, Vinoba Puri, Lajpatnagar II, New Delhi, India
| | - Jeffrey S A Stringer
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Susan J Fisher
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA; Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, San Francisco, CA.
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2
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Ross RK, Zivich PN, Stringer JSA, Cole SR. M-estimation for common epidemiological measures: introduction and applied examples. Int J Epidemiol 2024; 53:dyae030. [PMID: 38423105 PMCID: PMC10904145 DOI: 10.1093/ije/dyae030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 02/13/2024] [Indexed: 03/02/2024] Open
Abstract
M-estimation is a statistical procedure that is particularly advantageous for some comon epidemiological analyses, including approaches to estimate an adjusted marginal risk contrast (i.e. inverse probability weighting and g-computation) and data fusion. In such settings, maximum likelihood variance estimates are not consistent. Thus, epidemiologists often resort to bootstrap to estimate the variance. In contrast, M-estimation allows for consistent variance estimates in these settings without requiring the computational complexity of the bootstrap. In this paper, we introduce M-estimation and provide four illustrative examples of implementation along with software code in multiple languages. M-estimation is a flexible and computationally efficient estimation procedure that is a powerful addition to the epidemiologist's toolbox.
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Affiliation(s)
- Rachael K Ross
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Paul N Zivich
- Institute for Global Health and Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jeffrey S A Stringer
- Department of Obstetrics and Gynecology, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Stephen R Cole
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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3
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Espinosa C, Ali SM, Khan W, Khanam R, Pervin J, Price JT, Rahman S, Hasan T, Ahmed S, Raqib R, Rahman M, Aktar S, Nisar MI, Khalid J, Dhingra U, Dutta A, Deb S, Stringer JS, Wong RJ, Shaw GM, Stevenson DK, Darmstadt GL, Gaudilliere B, Baqui AH, Jehan F, Rahman A, Sazawal S, Vwalika B, Aghaeepour N, Angst MS. Comparative predictive power of serum vs plasma proteomic signatures in feto-maternal medicine. AJOG GLOBAL REPORTS 2023; 3:100244. [PMID: 37456144 PMCID: PMC10339042 DOI: 10.1016/j.xagr.2023.100244] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Blood proteins are frequently measured in serum or plasma, because they provide a wealth of information. Differences in the ex vivo processing of serum and plasma raise concerns that proteomic health and disease signatures derived from serum or plasma differ in content and quality. However, little is known about their respective power to predict feto-maternal health outcomes. Predictive power is a sentinel characteristic to determine the clinical use of biosignatures. OBJECTIVE This study aimed to compare the power of serum and plasma proteomic signatures to predict a physiological pregnancy outcome. STUDY DESIGN Paired serum and plasma samples from 73 women were obtained from biorepositories of a multinational prospective cohort study on pregnancy outcomes. Gestational age at the time of sampling was the predicted outcome, because the proteomic signatures have been validated for such a prediction. Multivariate and cross-validated models were independently derived for serum and plasma proteins. RESULTS A total of 1116 proteins were measured in 88 paired samples from 73 women with a highly multiplexed platform using proximity extension technology (Olink Proteomics Inc, Watertown, MA). The plasma proteomic signature showed a higher predictive power (R=0.64; confidence interval, 0.42-0.79; P=3.5×10-6) than the serum signature (R=0.45; confidence interval, 0.18-0.66; P=2.2×10-3). The serum signature was validated in plasma with a similar predictive power (R=0.58; confidence interval, 0.34-0.75; P=4.8×10-5), whereas the plasma signature was validated in serum with reduced predictive power (R=0.53; confidence interval, 0.27-0.72; P=2.6×10-4). Signature proteins largely overlapped in the serum and plasma, but the strength of association with gestational age was weaker for serum proteins. CONCLUSION Findings suggest that serum proteomics are less informative than plasma proteomics. They are compatible with the view that the partial ex-vivo degradation and modification of serum proteins during sample processing are an underlying reason. The rationale for collecting and analyzing serum and plasma samples should be carefully considered when deriving proteomic biosignatures to ascertain that specimens of the highest scientific and clinical yield are processed. Findings suggest that plasma is the preferred matrix.
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Affiliation(s)
- Camilo Espinosa
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA (Mr Espinosa and Drs Gaudilliere, Aghaeepour and Angst)
| | - Said Mohammed Ali
- Public Health Laboratory Ivo de Carneri, Zanzibar, Pemba, Tanzania (Messrs Ali, Dutta, and Deb)
| | - Waqasuddin Khan
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, Aga Khan University, Karachi, Pakistan (Drs Khan and Nisar, Ms Khalid, and Dr Jehan)
| | - Rasheda Khanam
- Newborn Health, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (Drs Khanam and Baqui)
| | - Jesmin Pervin
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh (Mr Pervin, Mr M. Rahman, and Drs Aktar and A. Rahman)
| | - Joan T. Price
- Department of Obstetrics and Gynecology, The University of North Carolina at Chapel Hill, Chapel Hill, NC (Drs Price and Stringer)
| | - Sayedur Rahman
- Projahnmo Research Foundation, Dhaka, Bangladesh (Dr Rahman, Mr Hasan, and Dr Ahmed)
| | - Tarik Hasan
- Projahnmo Research Foundation, Dhaka, Bangladesh (Dr Rahman, Mr Hasan, and Dr Ahmed)
| | - Salahuddin Ahmed
- Projahnmo Research Foundation, Dhaka, Bangladesh (Dr Rahman, Mr Hasan, and Dr Ahmed)
| | - Rubhana Raqib
- Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh (Dr Raqib)
| | - Monjur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh (Mr Pervin, Mr M. Rahman, and Drs Aktar and A. Rahman)
| | - Shaki Aktar
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh (Mr Pervin, Mr M. Rahman, and Drs Aktar and A. Rahman)
| | - Muhammad I. Nisar
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, Aga Khan University, Karachi, Pakistan (Drs Khan and Nisar, Ms Khalid, and Dr Jehan)
| | - Javairia Khalid
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, Aga Khan University, Karachi, Pakistan (Drs Khan and Nisar, Ms Khalid, and Dr Jehan)
| | - Usha Dhingra
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD (Ms Dhingra and Dr Sazawal)
| | - Arup Dutta
- Public Health Laboratory Ivo de Carneri, Zanzibar, Pemba, Tanzania (Messrs Ali, Dutta, and Deb)
- Center for Public Health Kinetics, New Delhi, India (Ms Dhingra, Messrs Dutta and Drs Deb, and Sazawal)
| | - Saikat Deb
- Public Health Laboratory Ivo de Carneri, Zanzibar, Pemba, Tanzania (Messrs Ali, Dutta, and Deb)
- Center for Public Health Kinetics, New Delhi, India (Ms Dhingra, Messrs Dutta and Drs Deb, and Sazawal)
| | - Jeffrey S.A. Stringer
- Department of Obstetrics and Gynecology, The University of North Carolina at Chapel Hill, Chapel Hill, NC (Drs Price and Stringer)
| | - Ronald J. Wong
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
| | - Gary M. Shaw
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
| | - David K. Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
| | - Gary L. Darmstadt
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA (Mr Espinosa and Drs Gaudilliere, Aghaeepour and Angst)
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
| | - Abdullah H. Baqui
- Newborn Health, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (Drs Khanam and Baqui)
| | - Fyezah Jehan
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, Aga Khan University, Karachi, Pakistan (Drs Khan and Nisar, Ms Khalid, and Dr Jehan)
| | - Anisur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh (Mr Pervin, Mr M. Rahman, and Drs Aktar and A. Rahman)
| | - Sunil Sazawal
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD (Ms Dhingra and Dr Sazawal)
- Center for Public Health Kinetics, New Delhi, India (Ms Dhingra, Messrs Dutta and Drs Deb, and Sazawal)
| | - Bellington Vwalika
- Department of Obstetrics and Gynecology, UNC School of Medicine, University of Zambia, Lusaka, Zambia (Dr Vwalika)
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA (Mr Espinosa and Drs Gaudilliere, Aghaeepour and Angst)
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
- Department of Biomedical Informatics, Stanford University School of Medicine, Stanford, CA (Dr Aghaeepour)
| | - Martin S. Angst
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA (Drs Wong, Shaw, Stevenson, Darmstadt, Gaudilliere and Aghaeepour)
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4
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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. SCIENCE ADVANCES 2023; 9:eade7692. [PMID: 37224249 PMCID: PMC10208584 DOI: 10.1126/sciadv.ade7692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [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.
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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 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
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5
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Appiagyei A, Vwalika B, Spelke MB, Conner MG, Mabula-Bwalya CM, Kasaro MP, Honart AW, Kumwenda A, Stringer EM, Stringer JSA, Price JT. Maternal mid-upper arm circumference to predict small for gestational age: Findings in a Zambian cohort. Int J Gynaecol Obstet 2023; 161:462-469. [PMID: 36263879 PMCID: PMC10115906 DOI: 10.1002/ijgo.14517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 10/11/2022] [Accepted: 10/14/2022] [Indexed: 01/16/2023]
Abstract
OBJECTIVE To compare the performance of mid upper arm circumference (MUAC) and body mass index (BMI) for prediction of small for gestational age (SGA) in Zambia. METHODS This is a secondary analysis of an ongoing clinical cohort that included women with a single gestation and MUAC measured before 24 weeks of pregnancy. We assessed relationships between maternal MUAC and birth weight centile using regression. The performance of MUAC and BMI to predict SGA was compared using receiver operating characteristic curves and the effect of maternal HIV was investigated in sub-group analyses. RESULTS Of 1117 participants, 847 (75%) were HIV-negative (HIV-) and 270 (24%) were HIV-positive (HIV+). Seventy-four (7%) delivered severe SGA infants (<3rd centile), of whom 56 (76%) were HIV- and 18 (24%) were HIV+ (odds ratio [OR] 1.01, 95% confidence interval [CI] 0.58-1.75). MUAC was associated with higher birth weight centile (+1.2 centile points, 95% CI 0.7-1.6; P < 0.001); this relationship was stronger among HIV+ women (+1.7 centile points, 95% CI 0.8-2.6; P < 0.001) than HIV- women (+0.9 centile points, 95% CI 0.4-1.4; P = 0.001). The discriminatory power was similar, albeit poor (area under the curve [AUC] < 0.7), between MUAC and BMI for the prediction of SGA. In stratified analysis, MUAC and BMI showed excellent discrimination predicting severe SGA among HIV+ (AUC 0.83 and 0.81, respectively) but not among HIV- women (AUC 0.64 and 0.63, respectively). CONCLUSION Maternal HIV infection increased the discrimination of both early pregnancy MUAC and BMI for prediction of severe SGA in Zambia. CLINICAL TRIAL NUMBER ClinicalTrials.gov (NCT02738892).
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Affiliation(s)
- Ashley Appiagyei
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Bellington Vwalika
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - M Bridget Spelke
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Madelyn G Conner
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | | | | | - Anne West Honart
- Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Andrew Kumwenda
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Elizabeth M Stringer
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Jeffrey S A Stringer
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Joan T Price
- Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
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6
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Hawken S, Ducharme R, Murphy MSQ, Olibris B, Bota AB, Wilson LA, Cheng W, Little J, Potter BK, Denize KM, Lamoureux M, Henderson M, Rittenhouse KJ, Price JT, Mwape H, Vwalika B, Musonda P, Pervin J, Chowdhury AKA, Rahman A, Chakraborty P, Stringer JSA, Wilson K. Development and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers. PLoS One 2023; 18:e0281074. [PMID: 36877673 PMCID: PMC9987787 DOI: 10.1371/journal.pone.0281074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 01/14/2023] [Indexed: 03/07/2023] Open
Abstract
BACKGROUND Accurate estimates of gestational age (GA) at birth are important for preterm birth surveillance but can be challenging to obtain in low income countries. Our objective was to develop machine learning models to accurately estimate GA shortly after birth using clinical and metabolomic data. METHODS We derived three GA estimation models using ELASTIC NET multivariable linear regression using metabolomic markers from heel-prick blood samples and clinical data from a retrospective cohort of newborns from Ontario, Canada. We conducted internal model validation in an independent cohort of Ontario newborns, and external validation in heel prick and cord blood sample data collected from newborns from prospective birth cohorts in Lusaka, Zambia and Matlab, Bangladesh. Model performance was measured by comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound. RESULTS Samples were collected from 311 newborns from Zambia and 1176 from Bangladesh. The best-performing model accurately estimated GA within about 6 days of ultrasound estimates in both cohorts when applied to heel prick data (MAE 0.79 weeks (95% CI 0.69, 0.90) for Zambia; 0.81 weeks (0.75, 0.86) for Bangladesh), and within about 7 days when applied to cord blood data (1.02 weeks (0.90, 1.15) for Zambia; 0.95 weeks (0.90, 0.99) for Bangladesh). CONCLUSIONS Algorithms developed in Canada provided accurate estimates of GA when applied to external cohorts from Zambia and Bangladesh. Model performance was superior in heel prick data as compared to cord blood data.
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Affiliation(s)
- Steven Hawken
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- * E-mail:
| | - Robin Ducharme
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Malia S. Q. Murphy
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Brieanne Olibris
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - A. Brianne Bota
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Lindsay A. Wilson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Wei Cheng
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Julian Little
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Beth K. Potter
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Kathryn M. Denize
- Newborn Screening Ontario, Children’s Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Monica Lamoureux
- Newborn Screening Ontario, Children’s Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Matthew Henderson
- Newborn Screening Ontario, Children’s Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Katelyn J. Rittenhouse
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Joan T. Price
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - Bellington Vwalika
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Patrick Musonda
- Department of Medical Statistics, University of Zambia College of Public Health, Lusaka, Zambia
| | - Jesmin Pervin
- International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | | | - Anisur Rahman
- International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Pranesh Chakraborty
- Newborn Screening Ontario, Children’s Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Jeffrey S. A. Stringer
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kumanan Wilson
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
- Faculty of Medicine, Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
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7
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HIV-associated vaginal microbiome and inflammation predict spontaneous preterm birth in Zambia. Sci Rep 2022; 12:8573. [PMID: 35595739 PMCID: PMC9123167 DOI: 10.1038/s41598-022-12424-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/26/2022] [Indexed: 11/27/2022] Open
Abstract
A Lactobacillus-deficient, anaerobe-rich vaginal microbiome has been associated with local inflammation and spontaneous preterm birth (sPTB), but few studies have assessed this association in the setting of HIV. We performed metagenomic sequencing and inflammatory marker assays on vaginal swabs collected in pregnancy. We grouped samples into 7 metagenomic clusters (mgClust) using the non-redundant VIRGO catalogue, and derived inflammatory scores by factor analysis. Of 221 participants, median Shannon diversity index (SDI) was highest in HIV+ with detectable viral load (1.31, IQR: 0.85–1.66; p < 0.001) and HIV+ with undetectable virus (1.17, IQR: 0.51–1.66; p = 0.01) compared to HIV− (0.74, IQR: 0.35–1.26). Inflammatory scores positively correlated with SDI (+ 0.66, 95%CI 0.28, 1.03; p = 0.001), highest among anaerobe-rich mgClust2–mgClust6. HIV was associated with predominance of anaerobe-rich mgClust5 (17% vs. 6%; p = 0.02) and mgClust6 (27% vs. 11%; p = 0.002). Relative abundance of a novel Gardnerella metagenomic subspecies > 50% predicted sPTB (RR 2.6; 95%CI: 1.1, 6.4) and was higher in HIV+ (23% vs. 10%; p = 0.001). A novel Gardnerella metagenomic subspecies more abundant in women with HIV predicted sPTB. The risk of sPTB among women with HIV may be mediated by the vaginal microbiome and inflammation, suggesting potential targets for prevention.
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8
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Price JT, Sebastião YV, Vwalika B, Cole SR, Mbewe FM, Phiri WM, Freeman BL, Kasaro MP, Peterson M, Rouse DJ, Stringer EM, Stringer JSA. Risk of Adverse Birth Outcomes in Two Cohorts of Pregnant Women With HIV in Zambia. Epidemiology 2022; 33:422-430. [PMID: 35067569 PMCID: PMC9516482 DOI: 10.1097/ede.0000000000001465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND A trial of progesterone to prevent preterm birth among HIV-infected Zambian women [Improving Pregnancy Outcomes with Progesterone (IPOP)] found no treatment effect, but the risk of the primary outcome was among the lowest ever documented in women with HIV. In this secondary analysis, we compare the risks of preterm birth (<37 weeks), stillbirth, and a composite primary outcome comprising the two in IPOP versus an observational pregnancy cohort [Zambian Preterm Birth Prevention Study (ZAPPS)] in Zambia, to evaluate reasons for the low risk in IPOP. METHODS Both studies enrolled women before 24 gestational weeks, during August 2015-September 2017 (ZAPPS) and February 2018-January 2020 (IPOP). We used linear probability and log-binomial regression to estimate risk differences and risk ratios (RR), before and after restriction and standardization with inverse probability weights. RESULTS The unadjusted risk of composite outcome was 18% in ZAPPS (N = 1450) and 9% in IPOP (N = 791) (RR = 2.0; 95% CI = 1.6, 2.6). After restricting and standardizing the ZAPPS cohort to the distribution of IPOP baseline characteristics, the risk remained higher in ZAPPS (RR = 1.6; 95% CI = 1.0, 2.4). The lower risk of preterm/stillbirth in IPOP was only partially explained by measured risk factors. CONCLUSIONS Possible benefits in IPOP of additional monetary reimbursement, more frequent visits, and group-based care warrant further investigation.
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Affiliation(s)
- Joan T Price
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
- University of North Carolina Global Projects Zambia, Lusaka, Zambia
| | - Yuri V Sebastião
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bellington Vwalika
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Stephen R Cole
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Felistas M Mbewe
- University of North Carolina Global Projects Zambia, Lusaka, Zambia
| | | | - Bethany L Freeman
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Margaret P Kasaro
- Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
- University of North Carolina Global Projects Zambia, Lusaka, Zambia
| | - Marc Peterson
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dwight J Rouse
- Department of Obstetrics and Gynecology, Brown University, Providence, RI, USA
| | - Elizabeth M Stringer
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jeffrey S A Stringer
- From the Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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9
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Webster CM, Kasaro MP, Price JT, Stringer EM, Wiesen CA, Vwalika B, Stringer JSA. Seroreduction of syphilis nontreponemal titers during pregnancy for women with and without HIV coinfection. Int J Gynaecol Obstet 2022; 159:427-434. [PMID: 35122676 DOI: 10.1002/ijgo.14131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/31/2021] [Accepted: 02/03/2022] [Indexed: 11/10/2022]
Abstract
OBJECTIVE To evaluate the effect of HIV coinfection on nontreponemal titers during pregnancy in women with syphilis. METHODS This is a secondary analysis of pregnant women with syphilis in the prospective, observational Zambian Preterm Birth Prevention Study (ZAPPS). Treponemal (TPPA) and nontreponemal (RPR) testing were performed on serum biospecimens, resulting in 47 participants with serologically-confirmed syphilis (27 HIV-positive, 20 HIV-negative). The primary outcome, achievement of RPR titer seroreduction during pregnancy, was analyzed by logistic regression. Secondary outcomes included overall titer reduction, seroreduction rate, serologic cure, and adverse pregnancy outcomes. RESULTS Seroreduction of RPR titer occurred in 78% (21/27) of women with HIV versus 45% (9/20) of women without (aOR 4.66; 95%CI 1.14-19.08). Overall RPR titer reduction, rates of seroreduction per week, and the proportion achieving serologic cure each trended higher among women with HIV compared to those without HIV. There was a trend toward decreased stillbirth incidence in participants achieving seroreduction (OR 0.15, 95%CI 0.01-1.58). CONCLUSION HIV coinfection in this cohort of Zambian women with syphilis was associated with greater odds of RPR titer seroreduction during pregnancy. Pregnant women with syphilis and HIV may not be at increased risk for delayed syphilis treatment response compared to women without HIV.
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Affiliation(s)
- Carolyn M Webster
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Margaret P Kasaro
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,UNC Global Projects, Zambia.,Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Joan T Price
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,UNC Global Projects, Zambia
| | - Elizabeth M Stringer
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher A Wiesen
- The Odum Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bellington Vwalika
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Jeffrey S A Stringer
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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10
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Mabula‐Bwalya CM, Smithmyer ME, Mwape H, Chipili G, Conner M, Vwalika B, De Paris K, Stringer JS, Price JT. Association of mid-trimester maternal angiogenic biomarkers with small-for-gestational-age infants in an urban Zambian cohort: a nested case-control study. Int J Gynaecol Obstet 2021; 157:604-612. [PMID: 34358336 PMCID: PMC8818065 DOI: 10.1002/ijgo.13860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/20/2021] [Accepted: 08/05/2021] [Indexed: 11/07/2022]
Abstract
Objective To investigate whether angiogenic biomarker concentrations differ between women who deliver small‐for‐gestational‐age (SGA) infants (<10th centile birth weight for gestational age) compared with controls, because identifying SGA risk early could improve outcomes. Methods This case‐control study compared serum concentrations of angiogenic biomarkers before 24 weeks of pregnancy from 62 women who delivered SGA infants (cases) and 62 control women from an urban Zambian cohort. Odds of delivering an SGA infant were calculated using conditional logistic regression. Results Placental growth factor (PlGF), soluble fms‐like tyrosine kinase (sFLT‐1) and soluble endoglin (sEng) in controls were 37.74 pg/mL (interquartile range [IQR] 23.12–63.15), 2525.18 pg/mL (IQR 1502.21–4265.54) and 2408.18 pg/mL (IQR 1854.87–3017.94), respectively. SGA cases had higher PlGF (40.50 pg/mL, IQR 22.81–67.94) and sFLT‐1 (2613.06 pg/mL, IQR 1720.58–3722.50), and lower sEng (2038.06 pg/mL, IQR 1445.25–3372.26). Participants with sEng concentration below and concomitant sFLT‐1 concentration above their respective thresholds (n = 40) had five‐fold higher odds of SGA (adjusted odds ratio 4.77, 95% confidence interval 1.61–14.1; P = 0.005). Conclusion Biomarker concentrations were similar between cases and controls. Participants with concomitant low sEng and high sFLT‐1 had the highest odds of SGA, suggesting that a combination of biomarkers may better for predicting SGA than single biomarkers. Prediction of SGA risk using the interaction of multiple angiogenic biomarkers may perform better than using a single angiogenic biomarker concentration before 24 weeks gestation.
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Affiliation(s)
| | | | - Humphrey Mwape
- University of North Carolina Global Projects ZambiaLusakaZambia
| | - Gabriel Chipili
- University of North Carolina Global Projects ZambiaLusakaZambia
| | - Madelyn Conner
- University of North Carolina at Chapel HillChapel HillNCUSA
| | | | | | | | - Joan T. Price
- University of North Carolina at Chapel HillChapel HillNCUSA
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11
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Bone JN, Pickerill K, Woo Kinshella ML, Vidler M, Craik R, Poston L, Stones W, Sevene E, Temmerman M, Koech Etyang A, Roca A, Russell D, Tribe RM, von Dadelszen P, Magee LA. Pregnancy cohorts and biobanking in sub-Saharan Africa: a systematic review. BMJ Glob Health 2021; 5:bmjgh-2020-003716. [PMID: 33243854 PMCID: PMC7692823 DOI: 10.1136/bmjgh-2020-003716] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 09/22/2020] [Accepted: 09/23/2020] [Indexed: 12/17/2022] Open
Abstract
Background Technological advances and high throughput biological assays can facilitate discovery science in biobanks from population cohorts, including pregnant women. Biological pathways associated with health outcomes differ depending on geography, and high-income country data may not generalise to low-resource settings. We conducted a systematic review to identify prospective pregnancy cohorts in sub-Saharan Africa (SSA) that include biobanked samples with potential to enhance discovery science opportunity. Methods Inclusion criteria were prospective data collection during pregnancy, with associated biobanking in SSA. Data sources included: scientific databases (with comprehensive search terms), grey literature, hand searching applicable reference lists and expert input. Results were screened in a three-stage process based on title, abstract and full text by two independent reviewers. The review is registered on PROSPERO (CRD42019147483). Results Fourteen SSA studies met the inclusion criteria from database searches (n=8), reference list searches (n=2) and expert input (n=4). Three studies have ongoing data collection. The most represented countries were South Africa and Mozambique (Southern Africa) (n=3), Benin (Western Africa) (n=4) and Tanzania (Eastern Africa) (n=4); including an estimated 31 763 women. Samples commonly collected were blood, cord blood and placenta. Seven studies collected neonatal samples. Common clinical outcomes included maternal and perinatal mortality, malaria and preterm birth. Conclusions Increasingly numerous pregnancy cohorts in SSA that include biobanking are generating a uniquely valuable resource for collaborative discovery science, and improved understanding of the high regional risks of maternal, fetal and neonatal morbidity and mortality. Future studies should align protocols and consider their added value and distinct contributions.
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Affiliation(s)
- Jeffrey N Bone
- Department of Obstetrics and Gynaecology, The University of British Columbia, Faculty of Medicine, Vancouver, British Columbia, Canada
| | - Kelly Pickerill
- Department of Obstetrics and Gynaecology, The University of British Columbia, Faculty of Medicine, Vancouver, British Columbia, Canada
| | - Mai-Lei Woo Kinshella
- Department of Obstetrics and Gynaecology, The University of British Columbia, Faculty of Medicine, Vancouver, British Columbia, Canada
| | - Marianne Vidler
- Department of Obstetrics and Gynaecology, The University of British Columbia, Faculty of Medicine, Vancouver, British Columbia, Canada
| | - Rachel Craik
- Department of Women and Children's Health, King's College London, School of Life Course Sciences, Faculty of Life Sciences and Medicine, London, UK
| | - Lucilla Poston
- Department of Women and Children's Health, King's College London, School of Life Course Sciences, Faculty of Life Sciences and Medicine, London, UK
| | - William Stones
- Centre for Reproductive Health, University of Malawi College of Medicine, Blantyre, Malawi
| | - Esperanca Sevene
- Centro de Investigação em Saúde de Manhiça, Manhiça, Maputo, Mozambique.,Department of Physiologic Sciences, Faculty of Medicine, Universidade Eduardo Mondlane, Maputo, Mozambique
| | - Marleen Temmerman
- Department of Obstetrics and Gynaecology, Centre of Excellence in Women and Child Health, Aga Khan University, Nairobi, Kenya
| | - Angela Koech Etyang
- Department of Obstetrics and Gynaecology, Centre of Excellence in Women and Child Health, Aga Khan University, Nairobi, Kenya
| | - Anna Roca
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, The Gambia
| | | | - Rachel M Tribe
- Department of Women and Children's Health, King's College London, School of Life Course Sciences, Faculty of Life Sciences and Medicine, London, UK
| | - Peter von Dadelszen
- Department of Women and Children's Health, King's College London, School of Life Course Sciences, Faculty of Life Sciences and Medicine, London, UK
| | - Laura A Magee
- Department of Women and Children's Health, King's College London, School of Life Course Sciences, Faculty of Life Sciences and Medicine, London, UK
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12
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Price JT, Vwalika B, Edwards JK, Cole SR, Kasaro MP, Rittenhouse KJ, Kumwenda A, Lubeya MK, Stringer JSA. Maternal HIV Infection and Spontaneous Versus Provider-Initiated Preterm Birth in an Urban Zambian Cohort. J Acquir Immune Defic Syndr 2021; 87:860-868. [PMID: 33587508 PMCID: PMC8131221 DOI: 10.1097/qai.0000000000002654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 01/11/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVE We investigated the effect of maternal HIV and its treatment on spontaneous and provider-initiated preterm birth (PTB) in an urban African cohort. METHODS The Zambian Preterm Birth Prevention Study enrolled pregnant women at their first antenatal visit in Lusaka. Participants underwent ultrasound, laboratory testing, and clinical phenotyping of delivery outcomes. Key exposures were maternal HIV serostatus and timing of antiretroviral therapy initiation. We defined the primary outcome, PTB, as delivery between 16 and 37 weeks' gestational age, and differentiated spontaneous from provider-initiated parturition. RESULTS Of 1450 pregnant women enrolled, 350 (24%) had HIV. About 1216 (84%) were retained at delivery, 3 of whom delivered <16 weeks. Of 181 (15%) preterm deliveries, 120 (66%) were spontaneous, 56 (31%) were provider-initiated, and 5 (3%) were unclassified. In standardized analyses using inverse probability weighting, maternal HIV increased the risk of spontaneous PTB [RR 1.68; 95% confidence interval (CI): 1.12 to 2.52], but this effect was mitigated on overall PTB [risk ratio (RR) 1.31; 95% CI: 0.92 to 1.86] owing to a protective effect against provider-initiated PTB. HIV reduced the risk of preeclampsia (RR 0.32; 95% CI: 0.11 to 0.91), which strongly predicted provider-initiated PTB (RR 17.92; 95% CI: 8.13 to 39.53). The timing of antiretroviral therapy start did not affect the relationship between HIV and PTB. CONCLUSION The risk of HIV on spontaneous PTB seems to be opposed by a protective effect of HIV on provider-initiated PTB. These findings support an inflammatory mechanism underlying HIV-related PTB and suggest that published estimates of PTB risk overall underestimate the risk of spontaneous PTB.
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Affiliation(s)
- Joan T Price
- Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Obstetrics and Gynecology, University of Zambia School of Medicine, Lusaka, Zambia
- University of North Carolina Global Projects Zambia, Lusaka, Zambia ; and
| | - Bellington Vwalika
- Department of Obstetrics and Gynecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Jessie K Edwards
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Stephen R Cole
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Margaret P Kasaro
- Department of Obstetrics and Gynecology, University of Zambia School of Medicine, Lusaka, Zambia
- University of North Carolina Global Projects Zambia, Lusaka, Zambia ; and
| | - Katelyn J Rittenhouse
- Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Andrew Kumwenda
- Department of Obstetrics and Gynecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Mwansa K Lubeya
- Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC
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Rittenhouse KJ, Mwape H, Nelson JA, Mwale J, Chipili G, Price JT, Hudgens M, Stringer EM, De Paris K, Vwalika B, Stringer JS. Maternal HIV, antiretroviral timing, and spontaneous preterm birth in an urban Zambian cohort: the role of local and systemic inflammation. AIDS 2021; 35:555-565. [PMID: 33394679 PMCID: PMC7944942 DOI: 10.1097/qad.0000000000002808] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To assess plasma and vaginal inflammation in three antenatal groups (HIV-uninfected women, HIV-infected women entering care on preconceptional ART, and HIV-infected women not on preconceptional ART) and whether these measures are associated with spontaneous preterm birth (sPTB). DESIGN Case--control study nested within a pregnancy cohort in Lusaka, Zambia. METHODS We analyzed 11 pro-inflammatory and two anti-inflammatory markers in 207 women with paired plasma and vaginal specimens collected between 16 and 20 gestational weeks. Among 51 HIV-infected women, we repeated the assays in 24-34-week samples. We used confirmatory factor analysis to create inflammation scores and compared them among the three groups. RESULTS At baseline, HIV-infected women not on ART had higher vaginal pro-inflammatory scores than HIV-uninfected women [mean 0.37 (95% CI -0.06 to 0.80) vs. -0.02 (-0.32 to 0.27), P = 0.02]. In repeat testing, women not on preconceptional ART had an increase in vaginal inflammation between the baseline and 24-34-week visits compared with those continuing preconceptional ART [mean 0.62 (95% CI -0.80 to 4.20) vs. -0.07 (-2.78 to 2.11), P = 0.04]. In multivariate analyses, baseline vaginal inflammation predicted sPTB (aOR 1.5; 95% CI 1.0-2.3; P = 0.02). Plasma inflammation did not differ by HIV or ART exposure and was not associated with sPTB. CONCLUSION Women not receiving ART at entry into pregnancy care had more vaginal inflammation than women entering on treatment. They also experienced an increase in vaginal inflammation between the two sampling timepoints, possibly as a consequence of ART initiation. Vaginal (but not systemic) inflammation was associated with sPTB and offers a potential mechanistic insight into this important adverse birth outcome.
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Affiliation(s)
- Katelyn J. Rittenhouse
- University of North Carolina at Chapel Hill, Chapel Hill, USA
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
| | - Humphrey Mwape
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
| | | | - John Mwale
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
| | - Gabriel Chipili
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
| | - Joan T. Price
- University of North Carolina at Chapel Hill, Chapel Hill, USA
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
| | - Michael Hudgens
- University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Elizabeth M. Stringer
- University of North Carolina at Chapel Hill, Chapel Hill, USA
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
| | | | | | - Jeffrey S.A. Stringer
- University of North Carolina at Chapel Hill, Chapel Hill, USA
- University of North Carolina Global Projects-Zambia, Lusaka, Zambia
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Price JT, Winston J, Vwalika B, Cole SR, Stoner MCD, Lubeya MK, Kumwenda A, Stringer JSA. Quantifying bias between reported last menstrual period and ultrasonography estimates of gestational age in Lusaka, Zambia. Int J Gynaecol Obstet 2019; 144:9-15. [PMID: 30267538 PMCID: PMC6283668 DOI: 10.1002/ijgo.12686] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 07/21/2018] [Accepted: 09/27/2018] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To quantify differences in assessing preterm delivery when calculating gestational age from last menstrual period (LMP) versus ultrasonography biometry. METHODS The Zambian Preterm Birth Prevention Study is an ongoing prospective cohort study that commenced enrolment in August 2015 at Women and Newborn Hospital of University Teaching Hospital in Lusaka, Zambia. Women at less than 20 weeks of pregnancy who were enrolled between August 17, 2015, and August 31, 2017, and underwent ultrasonography examination were included in the present analysis. The primary outcome was the difference between ultrasonography- and LMP-based estimated gestational age. Associations between baseline predictors and outcomes were assessed using simple regression. The proportion of preterm deliveries using LMP- and ultrasonography-derived gestational dating was calculated using Kaplan-Meier analysis. RESULTS The analysis included 942 women. The discrepancy between estimating gestational age using ultrasonography and LMP increased with greater gestational age at presentation and among patients with no history of preterm delivery. In a Kaplan-Meier analysis of 692 deliveries, 140 (20.2%, 95% confidence interval [CI] 17.7-23.0) and 79 (11.4%, 95% CI 9.6-13.6) deliveries were classified as preterm by LMP and ultrasonography estimates, respectively. CONCLUSION Taking ultrasonography as a standard, a bias was observed in LMP-based gestational age estimates, which increased with advancing gestation at presentation. This resulted in misclassification of term deliveries as preterm.
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Affiliation(s)
- Joan T. Price
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Women and Newborn Hospital, University Teaching Hospital, Lusaka, Zambia
| | - Jennifer Winston
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bellington Vwalika
- Women and Newborn Hospital, University Teaching Hospital, Lusaka, Zambia
- Department of Obstetrics and Gynecology, University of Zambia School of Medicine, Lusaka, Zambia
| | - Stephen R. Cole
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marie C. D. Stoner
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mwansa K. Lubeya
- Women and Newborn Hospital, University Teaching Hospital, Lusaka, Zambia
| | - Andrew Kumwenda
- Women and Newborn Hospital, University Teaching Hospital, Lusaka, Zambia
| | - Jeffrey S. A. Stringer
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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