Deep clinical and biological phenotyping of the preterm birth and small for gestational age syndromes: The INTERBIO-21 st Newborn Case-Control Study protocol

Etiologically Based Functional Taxonomy of the Preterm Birth Syndrome

Preterm birth (PTB) is a complex syndrome traditionally defined by a single parameter, namely, gestational age at birth (ie, ˂37 weeks). This approach has limitations for clinical usefulness and may explain the lack of progress in identifying cause-specific effective interventions. The authors offer a framework for a functional taxonomy of PTB based on (1) conceptual principles established a priori; (2) known etiologic factors; (3) specific, prospectively identified obstetric and neonatal clinical phenotypes; and (4) postnatal follow-up of growth and development up to 2 years of age. This taxonomy includes maternal, placental, and fetal conditions routinely recorded in data collection systems.

Association between maternal haemoglobin concentrations and maternal and neonatal outcomes: the prospective, observational, multinational, INTERBIO-21st fetal study

BACKGROUND

Anaemia in pregnancy is a global health problem with associated maternal and neonatal morbidity and mortality. We aimed to investigate the association between maternal haemoglobin concentrations during pregnancy and the risk of adverse maternal and neonatal outcomes.

METHODS

In this prospective, observational, multinational, INTERBIO-21st fetal study conducted at maternity units in Brazil, Kenya, Pakistan, South Africa, and the UK, we enrolled pregnant women (aged ≥18 years, BMI <35 kg/m2, natural conception, and singleton pregnancy) who initiated antenatal care before 14 weeks' gestation. At each 5±1 weekly visit until delivery, information was collected about the pregnancy, as well as the results of blood tests taken as part of routine antenatal care, including haemoglobin values. The outcome measures were maternal (gestational diabetes, pregnancy-induced hypertension, and preterm premature rupture of membranes) and neonatal outcomes (small for gestational age, preterm birth, and acute respiratory distress syndrome).

FINDINGS

Between Feb 8, 2012, and Nov 30, 2019, 2069 women (mean age 30·7 years [SD 5·0]) had at least one routinely haemoglobin concentration measured at 14-40 weeks' gestation, contributing 4690 haemoglobin measurements for the analysis. Compared with a haemoglobin cutoff of 110 g/L, the risk was increased more than two-fold for pregnancy-induced hypertension at haemoglobin concentrations of 170 g/L (risk ratio [RR] 2·29 [95% CI 1·19-4·39]) and higher, for preterm birth at haemoglobin concentrations of 70 g/L (RR 2·04 [95% CI 1·20-3·48]) and 165 g/L (RR 2·06 [95% CI 1·41-3·02]), and for acute respiratory distress syndrome at haemoglobin concentrations of 165 g/L (RR 2·84 [95% CI 1·51-5·35]). Trimester-specific results are also presented.

INTERPRETATION

Our data suggests that the current WHO haemoglobin cutoffs are associated with reduced risk of adverse maternal and neonatal outcomes. The current haemoglobin concentration cutoffs during pregnancy should not only consider thresholds for low haemoglobin concentrations that are associated with adverse outcomes but also define a threshold for high haemoglobin concentrations given the U-shaped relationship between haemoglobin concentration and adverse neonatal and maternal outcomes.

FUNDING

Bill & Melinda Gates Foundation.

Association between fetal abdominal growth trajectories, maternal metabolite signatures early in pregnancy, and childhood growth and adiposity: prospective observational multinational INTERBIO-21st fetal study

BACKGROUND

Obesity predominantly affects populations in high-income countries and those countries facing epidemiological transition. The risk of childhood obesity is increased among infants who had overweight or obesity at birth, but in low-resource settings one in five infants are born small for gestational age. We aimed to study the relationships between: (1) maternal metabolite signatures; (2) fetal abdominal growth; and (3) postnatal growth, adiposity, and neurodevelopment.

METHODS

In the prospective, multinational, observational INTERBIO-21st fetal study, conducted in maternity units in Pelotas (Brazil), Nairobi (Kenya), Karachi (Pakistan), Soweto (South Africa), Mae Sot (Thailand), and Oxford (UK), we enrolled women (≥18 years, with a BMI of less than 35 kg/m², natural conception, and a singleton pregnancy) who initiated antenatal care before 14 weeks' gestation. Ultrasound scans were performed every 5±1 weeks until delivery to measure fetal growth and feto-placental blood flow, and we used finite mixture models to derive growth trajectories of abdominal circumference. The infants' health, growth, and development were monitored from birth to age 2 years. Early pregnancy maternal blood and umbilical cord venous blood samples were collected for untargeted metabolomic analysis.

FINDINGS

From Feb 8, 2012, to Nov 30, 2019, we enrolled 3598 pregnant women and followed up their infants to 2 years of age. We identified four ultrasound-derived trajectories of fetal abdominal circumference growth that accelerated or decelerated within a crucial 20-25 week gestational age window: faltering growth, early accelerating growth, late accelerating growth, and median growth tracking. These distinct phenotypes had matching feto-placental blood flow patterns throughout pregnancy, and different growth, adiposity, vision, and neurodevelopment outcomes in early childhood. There were 709 maternal metabolites with positive effect for the faltering growth phenotype and 54 for the early accelerating growth phenotype; 31 maternal metabolites had a negative effect for the faltering growth phenotype and 76 for the early accelerating growth phenotype. Metabolites associated with the faltering growth phenotype had statistically significant odds ratios close to 1·5 (ie, suggesting upregulation of metabolic pathways of impaired fetal growth). The metabolites had a reciprocal relationship with the early accelerating growth phenotype, with statistically significant odds ratios close to 0.6 (ie, suggesting downregulation of fetal growth acceleration). The maternal metabolite signatures included 5-hydroxy-eicosatetraenoic acid, and 11 phosphatidylcholines linked to oxylipin or saturated fatty acid sidechains. The fungicide, chlorothalonil, was highly abundant in the early accelerating growth phenotype group.

INTERPRETATION

Early pregnancy lipid biology associated with fetal abdominal growth trajectories is an indicator of patterns of growth, adiposity, vision, and neurodevelopment up to the age of 2 years. Our findings could contribute to the earlier identification of infants at risk of obesity.

FUNDING

Bill & Melinda Gates Foundation.

Clinical phenotypes for risk stratification in small-for-gestational-age fetuses

OBJECTIVE

To evaluate whether clinical phenotypes of small-for-gestational-age (SGA) fetuses can be identified and used for adverse perinatal outcome risk stratification to facilitate clinical decision-making.

METHODS

This was a multicenter observational cohort study conducted in two tertiary care university hospitals. SGA fetuses were classified according to maternal, fetal and placental conditions using a two-step cluster algorithm, in which fetuses with more than one condition were assigned to the cluster associated with the highest mortality risk. Delivery and perinatal outcomes were compared using chi-square test among SGA clusters, and the associations between outcomes and each cluster were evaluated by calculating odds ratios (OR), adjusted for gestational age.

RESULTS

The study included 17 631 consecutive singleton pregnancies, of which 1274 (7.2%) were defined as SGA at birth according to INTERGROWTH-21^st standards. Nine SGA clinical phenotypes were identified using a predefined conceptual framework. All delivery and perinatal outcomes analyzed were significantly different among the nine phenotypes. The whole SGA cohort had a three-times higher risk of perinatal mortality compared with non-SGA fetuses (1.4% vs 0.4%; P < 0.001). SGA clinical phenotypes exhibited three patterns of perinatal mortality risk: the highest risk was associated with congenital anomaly (8.3%; OR, 17.17 (95% CI, 2.17-136.12)) and second- or third-trimester hemorrhage (8.3%; OR, 9.94 (95% CI, 1.23-80.02)) clusters; medium risk was associated with gestational diabetes (3.8%; OR, 9.59 (95% CI, 1.27-72.57)), preterm birth (3.2%; OR, 4.65 (95% CI, 0.62-35.01)) and intrauterine growth restriction (3.1%; OR, 5.93 (95% CI, 3.21-10.95)) clusters; and the lowest risk was associated with the remaining clusters. Perinatal mortality rate did not differ between SGA fetuses without other clinical conditions (54.1% of SGA fetuses) and appropriate-for-gestational-age fetuses (0.1% vs 0.4%; OR, 0.41 (95% CI, 0.06-2.94); P = 0.27). SGA combined with other obstetric pathologies increased significantly the risk of perinatal mortality, as demonstrated by the increased odds of perinatal death in SGA cases with gestational diabetes compared to non-SGA cases with the same condition (OR, 24.40 (95% CI, 1.31-453.91)).

CONCLUSIONS

We identified nine SGA clinical phenotypes associated with different patterns of risk for adverse perinatal outcome. Our findings suggest that considering clinical characteristics in addition to ultrasound findings could improve risk stratification and decision-making for management of SGA fetuses. Future clinical trials investigating management of fetuses with SGA should take into account clinical information in addition to Doppler parameters and estimated fetal weight. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Association of maternal prenatal selenium concentration and preterm birth: a multicountry meta-analysis

BACKGROUND

Selenium (Se), an essential trace mineral, has been implicated in preterm birth (PTB). We aimed to determine the association of maternal Se concentrations during pregnancy with PTB risk and gestational duration in a large number of samples collected from diverse populations.

METHODS

Gestational duration data and maternal plasma or serum samples of 9946 singleton live births were obtained from 17 geographically diverse study cohorts. Maternal Se concentrations were determined by inductively coupled plasma mass spectrometry analysis. The associations between maternal Se with PTB and gestational duration were analysed using logistic and linear regressions. The results were then combined using fixed-effect and random-effect meta-analysis.

FINDINGS

In all study samples, the Se concentrations followed a normal distribution with a mean of 93.8 ng/mL (SD: 28.5 ng/mL) but varied substantially across different sites. The fixed-effect meta-analysis across the 17 cohorts showed that Se was significantly associated with PTB and gestational duration with effect size estimates of an OR=0.95 (95% CI: 0.9 to 1.00) for PTB and 0.66 days (95% CI: 0.38 to 0.94) longer gestation per 15 ng/mL increase in Se concentration. However, there was a substantial heterogeneity among study cohorts and the random-effect meta-analysis did not achieve statistical significance. The largest effect sizes were observed in UK (Liverpool) cohort, and most significant associations were observed in samples from Malawi.

INTERPRETATION

While our study observed statistically significant associations between maternal Se concentration and PTB at some sites, this did not generalise across the entire cohort. Whether population-specific factors explain the heterogeneity of our findings warrants further investigation. Further evidence is needed to understand the biologic pathways, clinical efficacy and safety, before changes to antenatal nutritional recommendations for Se supplementation are considered.

Pregnancy cohorts and biobanking in sub-Saharan Africa: a systematic review

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.

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study

Background

Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal gestational age are often inaccurate. For example, between 20 and 30 weeks of gestation, the width of the 95% prediction interval around the actual gestational age is estimated to be 18–36 days, even when the best ultrasound estimates are used. The aims of this study are to improve estimates of fetal gestational age and provide personalised predictions of future growth.

Methods

Using ultrasound-derived, fetal biometric data, we developed a machine learning approach to accurately estimate gestational age. The accuracy of the method is determined by reference to exactly known facts pertaining to each fetus—specifically, intervals between ultrasound visits—rather than the date of the mother's last menstrual period. The data stem from a sample of healthy, well-nourished participants in a large, multicentre, population-based study, the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st). The generalisability of the algorithm is shown with data from a different and more heterogeneous population (INTERBIO-21st Fetal Study).

Findings

In the context of two large datasets, we estimated gestational age between 20 and 30 weeks of gestation with 95% confidence to within 3 days, using measurements made in a 10-week window spanning the second and third trimesters. Fetal gestational age can thus be estimated in the 20–30 weeks gestational age window with a prediction interval 3–5 times better than with any previous algorithm. This will enable improved management of individual pregnancies. 6-week forecasts of the growth trajectory for a given fetus are accurate to within 7 days. This will help identify at-risk fetuses more accurately than currently possible. At population level, the higher accuracy is expected to improve fetal growth charts and population health assessments.

Interpretation

Machine learning can circumvent long-standing limitations in determining fetal gestational age and future growth trajectory, without recourse to often inaccurately known information, such as the date of the mother's last menstrual period. Using this algorithm in clinical practice could facilitate the management of individual pregnancies and improve population-level health. Upon publication of this study, the algorithm for gestational age estimates will be provided for research purposes free of charge via a web portal.

Funding

Bill & Melinda Gates Foundation, Office of Science (US Department of Energy), US National Science Foundation, and National Institute for Health Research Oxford Biomedical Research Centre.

PRECISE pregnancy cohort: challenges and strategies in setting up a biorepository in sub-Saharan Africa

BACKGROUND AND OBJECTIVE

PRECISE is a population-based, prospective pregnancy cohort study designed for deep phenotyping of pregnancies in women with placenta-related disorders, and in healthy controls. The PRECISE Network is recruiting ~ 10,000 pregnant women in three countries (The Gambia, Kenya, and Mozambique) representing sub-Saharan Africa. The principal aim is to improve our understanding of pre-eclampsia, fetal growth restriction and stillbirth. This involves the creation of a highly curated biorepository for state of the art discovery science and a rich database of antenatal variables and maternal and neonatal outcomes. Our overarching aim is to provide large sample numbers with adequate power to address key scientific questions. Here we describe our experience of establishing a biorepository in the PRECISE Network and review the issues and challenges surrounding set-up, management and scientific use.

METHODS

The feasibility of collecting and processing each sample type was assessed in each setting and plans made for establishing the necessary infrastructure. Quality control (QC) protocols were established to ensure that biological samples are 'fit-for-purpose'. The management structures required for standardised sample collection and processing were developed. This included the need for transport of samples between participating countries and to external academic/commercial institutions.

RESULTS

Numerous practical challenges were encountered in setting up the infrastructure including facilities, staffing, training, cultural barriers, procurement, shipping and sample storage. Whilst delaying the project, these were overcome by establishing good communication with the sites, training workshops and constant engagement with the necessary commercial suppliers. A Project Executive Committee and Biology Working Group together defined the biospecimens required to answer the research questions paying particular attention to harmonisation of protocols with other cohorts so as to enable cross-biorepository collaboration. Governance structures implemented include a Data and Sample Committee to ensure biospecimens and data will be used according to consent, and prioritisation by scientific excellence. A coordinated sample and data transfer agreement will prevent delay in sample sharing.

DISCUSSION

With adequate training and infrastructure, it is possible to establish high quality sample collections to facilitate research programmes such as the PRECISE Network in sub-Saharan Africa. These preparations are pre-requisites for effective execution of a biomarker-based approach to better understand the complexities of placental disease in these settings, and others.

Congenital microcephaly unrelated to flavivirus exposure in coastal Kenya

Background: Zika virus (ZIKV) was first discovered in East Africa in 1947.  ZIKV has caused microcephaly in the Americas, but it is not known whether ZIKV is a cause of microcephaly in East Africa. Methods: We used surveillance data from 11,061 live births at Kilifi County Hospital in coastal Kenya between January 2012 and October 2016 to identify microcephaly cases and conducted a nested case-control study to determine risk factors for microcephaly. Gestational age at birth was estimated based on antenatal ultrasound scanning ('Scanned cohort') or last menstrual period ('LMP cohort', including births ≥37 weeks' gestation only). Controls were newborns with head circumference Z scores between >-2 and ≤2 SD that were compared to microcephaly cases in relation to ZIKV exposure and other maternal and newborn factors. Results: Of the 11,061 newborns, 214 (1.9%, 95%CI 1.69, 2.21) had microcephaly. Microcephaly prevalence was 1.0% (95%CI 0.64, 1.70, n=1529) and 2.1% (95%CI 1.81, 2.38, n=9532) in the scanned and LMP cohorts, respectively. After excluding babies <2500 g (n=1199) in the LMP cohort the prevalence was 1.1% (95%CI 0.93, 1.39). Microcephaly showed an association with being born small for gestational age (p<0.001) but not with ZIKV neutralising antibodies (p=0.6) or anti-ZIKV NS1 IgM response (p=0.9). No samples had a ZIKV neutralising antibody titre that was at least fourfold higher than the corresponding dengue virus (DENV) titre. No ZIKV or other flavivirus RNA was detected in cord blood from cases or controls. Conclusions: Microcephaly was prevalent in coastal Kenya, but does not appear to be related to ZIKV exposure; the ZIKV response observed in our study population was largely due to cross-reactive responses to DENV or other related flaviviruses. Further research into potential causes and the clinical consequences of microcephaly in this population is urgently needed.