Association Between Preterm-Birth Phenotypes and Differential Morbidity, Growth, and Neurodevelopment at Age 2 Years: Results From the INTERBIO-21st Newborn Study.

Importance: The etiologic complexities of preterm birth remain inadequately understood, which may impede the development of better preventative and treatment measures. Objective: To examine the association between specific preterm-birth phenotypes and clinical, growth, and neurodevelopmental differences among preterm newborns compared with term newborns up to age 2 years. Design, Setting, and Participants: The INTERBIO-21st study included a cohort of preterm and term newborn singletons enrolled between March 2012 and June 2018 from maternity hospitals in 6 countries worldwide who were followed up from birth to age 2 years. All pregnancies were dated by ultrasonography. Data were analyzed from November 2019 to October 2020. Exposures/Interventions: Preterm-birth phenotypes. Main Outcomes and Measures: Infant size, health, nutrition, and World Health Organization motor development milestones assessed at ages 1 and 2 years; neurodevelopment evaluated at age 2 years using the INTERGROWTH-21st Neurodevelopment Assessment (INTER-NDA) tool. Results: A total of 6529 infants (3312 boys [50.7%]) were included in the analysis. Of those, 1381 were preterm births (mean [SD] gestational age at birth, 34.4 [0.1] weeks; 5148 were term births (mean [SD] gestational age at birth, 39.4 [0] weeks). Among 1381 preterm newborns, 8 phenotypes were identified: no main maternal, fetal, or placental condition detected (485 infants [35.1%]); infections (289 infants [20.9%]); preeclampsia (162 infants [11.7%]); fetal distress (131 infants [9.5%]); intrauterine growth restriction (110 infants [8.0%]); severe maternal disease (85 infants [6.2%]); bleeding (71 infants [5.1%]); and congenital anomaly (48 infants [3.5%]). For all phenotypes, a previous preterm birth was a risk factor for recurrence. Each phenotype displayed differences in neonatal morbidity and infant outcomes. For example, infants with the no main condition detected phenotype had low neonatal morbidity but increased morbidity and hospitalization incidence at age 1 year (odds ratio [OR], 2.2; 95% CI, 1.8-2.7). Compared with term newborns, the highest risk of scoring lower than the 10th centile of INTER-NDA normative values was observed in the fine motor development domain among newborns with the fetal distress (OR, 10.6; 95% CI, 5.1-22.2) phenotype. Conclusions and Relevance: Results of this study suggest that phenotypic classification may provide a better understanding of the etiologic factors and mechanisms associated with preterm birth than continuing to consider it an exclusively time-based entity

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

Association of maternal prenatal copper concentration with gestational duration and preterm birth: a multicountry meta-analysis

Background Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). Objectives This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. Methods Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. Results The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. Conclusions Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB

Maternal colonization with Streptococcus agalactiae and associated stillbirth and neonatal disease in coastal Kenya.

Streptococcus agalactiae (group B streptococcus, GBS) causes neonatal disease and stillbirth, but its burden in sub-Saharan Africa is uncertain. We assessed maternal recto-vaginal GBS colonization (7,967 women), stillbirth and neonatal disease. Whole-genome sequencing was used to determine serotypes, sequence types and phylogeny. We found low maternal GBS colonization prevalence (934/7,967, 12%), but comparatively high incidence of GBS-associated stillbirth and early onset neonatal disease (EOD) in hospital (0.91 (0.25-2.3)/1,000 births and 0.76 (0.25-1.77)/1,000 live births, respectively). However, using a population denominator, EOD incidence was considerably reduced (0.13 (0.07-0.21)/1,000 live births). Treated cases of EOD had very high case fatality (17/36, 47%), especially within 24 h of birth, making under-ascertainment of community-born cases highly likely, both here and in similar facility-based studies. Maternal GBS colonization was less common in women with low socio-economic status, HIV infection and undernutrition, but when GBS-colonized, they were more probably colonized by the most virulent clone, CC17. CC17 accounted for 267/915 (29%) of maternal colonizing (265/267 (99%) serotype III; 2/267 (0.7%) serotype IV) and 51/73 (70%) of neonatal disease cases (all serotype III). Trivalent (Ia/II/III) and pentavalent (Ia/Ib/II/III/V) vaccines would cover 71/73 (97%) and 72/73 (99%) of disease-causing serotypes, respectively. Serotype IV should be considered for inclusion, with evidence of capsular switching in CC17 strains

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 (INTERBIO21st 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

Fetal cranial growth trajectories are associated with growth and neurodevelopment at 2 years of age: INTERBIO-21st Fetal Study.

Many observational studies and some randomized trials demonstrate how fetal growth can be influenced by environmental insults (for example, maternal infections)1 and preventive interventions (for example, multiple-micronutrient supplementation)2 that can have a long-lasting effect on health, growth, neurodevelopment and even educational attainment and income in adulthood3. In a cohort of pregnant women (n = 3,598), followed-up between 2012 and 2019 at six sites worldwide4, we studied the associations between ultrasound-derived fetal cranial growth trajectories, measured longitudinally from <14 weeks' gestation, against international standards5,6, and growth and neurodevelopment up to 2 years of age7,8. We identified five trajectories associated with specific neurodevelopmental, behavioral, visual and growth outcomes, independent of fetal abdominal growth, postnatal morbidity and anthropometric measures at birth and age 2. The trajectories, which changed within a 20-25-week gestational age window, were associated with brain development at 2 years of age according to a mirror (positive/negative) pattern, mostly focused on maturation of cognitive, language and visual skills. Further research should explore the potential for preventive interventions in pregnancy to improve infant neurodevelopmental outcomes before the critical window of opportunity that precedes the divergence of growth at 20-25 weeks' gestation

Fetal cranial growth trajectories are associated with growth and neurodevelopment at 2 years of age: INTERBIO-21st Fetal Study

Many observational studies and some randomized trials demonstrate how fetal growth can be influenced by environmental insults (for example, maternal infections)1 and preventive interventions (for example, multiple-micronutrient supplementation)2 that can have a long-lasting effect on health, growth, neurodevelopment and even educational attainment and income in adulthood3. In a cohort of pregnant women (n = 3,598), followed-up between 2012 and 2019 at six sites worldwide4, we studied the associations between ultrasound-derived fetal cranial growth trajectories, measured longitudinally from <14 weeks’ gestation, against international standards5,6, and growth and neurodevelopment up to 2 years of age7,8. We identified five trajectories associated with specific neurodevelopmental, behavioral, visual and growth outcomes, independent of fetal abdominal growth, postnatal morbidity and anthropometric measures at birth and age 2. The trajectories, which changed within a 20–25-week gestational age window, were associated with brain development at 2 years of age according to a mirror (positive/negative) pattern, mostly focused on maturation of cognitive, language and visual skills. Further research should explore the potential for preventive interventions in pregnancy to improve infant neurodevelopmental outcomes before the critical window of opportunity that precedes the divergence of growth at 20–25 weeks’ gestation