Dataset Information

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

ABSTRACT:

Importance

Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies.

Objective

To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB.

Design, setting, and participants

This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019.

Exposures

Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites.

Main outcomes and measures

The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation.

Results

Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways.

Conclusions and relevance

This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB.

SUBMITTER: Jehan F

PROVIDER: S-EPMC7749442 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Jehan Fyezah F Sazawal Sunil S Baqui Abdullah H AH Nisar Muhammad Imran MI Dhingra Usha U Khanam Rasheda R Ilyas Muhammad M Dutta Arup A Mitra Dipak K DK Mehmood Usma U Deb Saikat S Mahmud Arif A Hotwani Aneeta A Ali Said Mohammed SM Rahman Sayedur S Nizar Ambreen A Ame Shaali Makame SM Moin Mamun Ibne MI Muhammad Sajid S Chauhan Aishwarya A Begum Nazma N Khan Waqasuddin W Das Sayan S Ahmed Salahuddin S Hasan Tarik T Khalid Javairia J Rizvi Syed Jafar Raza SJR Juma Mohammed Hamad MH Chowdhury Nabidul Haque NH Kabir Furqan F Aftab Fahad F Quaiyum Abdul A Manu Alexander A Yoshida Sachiyo S Bahl Rajiv R Rahman Anisur A Pervin Jesmin J Winston Jennifer J Musonda Patrick P Stringer Jeffrey S A JSA Litch James A JA Ghaemi Mohammad Sajjad MS Moufarrej Mira N MN Contrepois Kévin K Chen Songjie S Stelzer Ina A IA Stanley Natalie N Chang Alan L AL Hammad Ghaith Bany GB Wong Ronald J RJ Liu Candace C Quaintance Cecele C CC Culos Anthony A Espinosa Camilo C Xenochristou Maria M Becker Martin M Fallahzadeh Ramin R Ganio Edward E Tsai Amy S AS Gaudilliere Dyani D Tsai Eileen S ES Han Xiaoyuan X Ando Kazuo K Tingle Martha M Maric Ivana I Wise Paul H PH Winn Virginia D VD Druzin Maurice L ML Gibbs Ronald S RS Darmstadt Gary L GL Murray Jeffrey C JC Shaw Gary M GM Stevenson David K DK Snyder Michael P MP Quake Stephen R SR Angst Martin S MS Gaudilliere Brice B Aghaeepour Nima N

JAMA network open 20201201 12

<h4>Importance</h4>Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies.<h4>Objective</h4>To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological me ...[more]

PMID: 33337494

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Project description:BackgroundPreterm birth continues to be a major public health problem contributing to 75% of the neonatal mortality worldwide. Low birth weight (LBW) is an important but imperfect surrogate for prematurity when accurate assessment of gestational age is not possible. While there is overlap between preterm birth and LBW newborns, those that are both premature and LBW are at the highest risk of adverse neonatal outcomes. Understanding the epidemiology of preterm birth and LBW is important for prevention and improved care for at risk newborns, but in many countries, data are sparse and incomplete.MethodsWe conducted data analyses using the Global Network's (GN) population-based registry of pregnant women and their babies in rural communities in six low- and middle-income countries (Democratic Republic of Congo, Kenya, Zambia, Guatemala, India and Pakistan). We analyzed data from January 2014 to December 2018. Trained study staff enrolled all pregnant women in the study catchment area as early as possible during pregnancy and conducted follow-up visits shortly after delivery and at 42 days after delivery. We analyzed the rates of preterm birth, LBW and the combination of preterm birth and LBW and studied risk factors associated with these outcomes across the GN sites.ResultsA total of 272,192 live births were included in the analysis. The overall preterm birth rate was 12.6% (ranging from 8.6% in Belagavi, India to 21.8% in the Pakistani site). The overall LBW rate was 13.6% (ranging from 2.7% in the Kenyan site to 21.4% in the Pakistani site). The overall rate of both preterm birth and LBW was 5.5% (ranging from 1.2% in the Kenyan site to 11.0% in the Pakistani site). Risk factors associated with preterm birth, LBW and the combination were similar across sites and included nulliparity [RR - 1.27 (95% CI 1.21-1.33)], maternal age under 20 [RR 1.41 (95% CI 1.32-1.49)] years, severe antenatal hemorrhage [RR 5.18 95% CI 4.44-6.04)], hypertensive disorders [RR 2.74 (95% CI - 1.21-1.33], and 1-3 antenatal visits versus four or more [RR 1.68 (95% CI 1.55-1.83)].ConclusionsPreterm birth, LBW and their combination continue to be common public health problems at some of the GN sites, particularly among young, nulliparous women who have received limited antenatal care services. Trial registration The identifier of the Maternal and Newborn Health Registry at ClinicalTrials.gov is NCT01073475.Trial registrationThe identifier of the Maternal and Newborn Health Registry at ClinicalTrials.gov is NCT01073475.

Project description:BackgroundReducing preterm birth and stillbirth and improving outcomes for babies born too soon is essential to reduce under-5 mortality globally. In the context of a rapidly evolving evidence base and problems with extrapolating efficacy data from high- to low-income settings, an assessment of the evidence for maternal and newborn interventions specific to low- and middle-income countries (LMICs) is required.MethodsA systematic review of the literature was done. We included all studies performed in LMICs since the Every Newborn Action Plan, between 2013 - 2018, which reported on interventions where the outcome assessed was reduction in preterm birth or stillbirth incidence and/or a reduction in preterm infant neonatal mortality. Evidence was categorised according to maternal or neonatal intervention groups and a narrative synthesis conducted.Results179 studies (147 primary evidence studies and 32 systematic reviews) were identified in 82 LMICs. 81 studies reported on maternal interventions and 98 reported on neonatal interventions. Interventions in pregnant mothers which resulted in significant reductions in preterm birth and stillbirth were (i) multiple micronutrient supplementation and (ii) enhanced quality of antenatal care. Routine antenatal ultrasound in LMICs increased identification of fetal antenatal conditions but did not reduce stillbirth or preterm birth due to the absence of services to manage these diagnoses. Interventions in pre-term neonates which improved their survival included (i) feeding support including probiotics and (ii) thermal regulation. Improved provision of neonatal resuscitation did not improve pre-term mortality rates, highlighting the importance of post-resuscitation care. Community mobilisation, for example through community education packages, was found to be an effective way of delivering interventions.ConclusionsEvidence supports the implementation of several low-cost interventions with the potential to deliver reductions in preterm birth and stillbirth and improve outcomes for preterm babies in LMICs. These, however, must be complemented by overall health systems strengthening to be effective. Quality improvement methodology and learning health systems approaches can provide important means of understanding and tackling implementation challenges within local contexts. Further pragmatic efficacy trials of interventions in LMICs are essential, particularly for interventions not previously tested in these contexts.

Project description:BackgroundBirth weight (BW) is a strong predictor of neonatal outcomes. The purpose of this study was to compare BWs between global regions (south Asia, sub-Saharan Africa, Central America) prospectively and to determine if trends exist in BW over time using the population-based maternal and newborn registry (MNHR) of the Global Network for Women'sand Children's Health Research (Global Network).MethodsThe MNHR is a prospective observational population-based registryof six research sites participating in the Global Network (2013-2018), within five low- and middle-income countries (Kenya, Zambia, India, Pakistan, and Guatemala) in threeglobal regions (sub-Saharan Af rica, south Asia, Central America). The birth weights were obtained for all infants born during the study period. This was done either by abstracting from the infants' health facility records or from direct measurement by the registry staff for infants born at home. After controlling for demographic characteristics, mixed-effect regression models were utilized to examine regional differences in birth weights over time.ResultsThe overall BW meanswere higher for the African sites (Zambia and Kenya), 3186 g (SD 463 g) in 2013 and 3149 g (SD 449 g) in 2018, ascompared to Asian sites (Belagavi and Nagpur, India and Pakistan), 2717 g (SD450 g) in 2013 and 2713 g (SD 452 g) in 2018. The Central American site (Guatemala) had a mean BW intermediate between the African and south Asian sites, 2928 g (SD 452) in 2013, and 2874 g (SD 448) in 2018. The low birth weight (LBW) incidence was highest in the south Asian sites (India and Pakistan) and lowest in the African sites (Kenya and Zambia). The size of regional differences varied somewhat over time with slight decreases in the gap in birth weights between the African and Asian sites and slight increases in the gap between the African and Central American sites.ConclusionsOverall, BWmeans by global region did not change significantly over the 5-year study period. From 2013 to 2018, infants enrolled at the African sites demonstrated the highest BW means overall across the entire study period, particularly as compared to Asian sites. The incidence of LBW was highest in the Asian sites (India and Pakistan) compared to the African and Central American sites. Trial registration The study is registered at clinicaltrials.gov. ClinicalTrial.gov Trial Registration: NCT01073475.

Project description:BackgroundThere is ample evidence of associations between short birth interval and adverse maternal and child health outcomes, including infant and maternal mortality. Short birth interval is more common among women in low- and middle-income countries. Identifying actionable aspects of short birth interval is necessary to address the problem. To our knowledge, this is the first systematic review to systematize evidence on risk factors for short birth interval in low- and middle-income countries.MethodsA systematic mixed studies review searched PubMed, Embase, LILACS, and Popline databases for empirical studies on the topic. We included documents in English, Spanish, French, Italian, and Portuguese, without date restriction. Two independent reviewers screened the articles and extracted the data. We used the Mixed Methods Appraisal Tool to conduct a quality appraisal of the included studies. To accommodate variable definition of factors and outcomes, we present only a narrative synthesis of the findings.ResultsForty-three of an initial 2802 documents met inclusion criteria, 30 of them observational studies and 14 published after 2010. Twenty-one studies came from Africa, 18 from Asia, and four from Latin America. Thirty-two reported quantitative studies (16 studies reported odds ratio or relative risk, 16 studies reported hazard ratio), 10 qualitative studies, and one a mixed-methods study. Studies most commonly explored education and age of the mother, previous pregnancy outcome, breastfeeding, contraception, socioeconomic level, parity, and sex of the preceding child. For most factors, studies reported both positive and negative associations with short birth interval. Shorter breastfeeding and female sex of the previous child were the only factors consistently associated with short birth interval. The quantitative and qualitative studies reported largely non-overlapping results.ConclusionsPromotion of breastfeeding could help to reduce short birth interval and has many other benefits. Addressing the preference for a male child is complex and a longer-term challenge. Future quantitative research could examine associations between birth interval and factors reported in qualitative studies, use longitudinal and experimental designs, ensure consistency in outcome and exposure definitions, and include Latin American countries.Trial registrationProspectively registered on PROSPERO (International Prospective Register for Systematic Reviews) under registration number CRD42018117654.

Dataset Information

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Conclusions and relevance

Publications

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Similar Datasets

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