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ObjectiveTo determine if preterm birth is associated with adaptation of the hypothalamic–pituitary–adrenal (HPA) axis and whether HPA axis programming relates to the degree of prematurity (defined as extremely preterm birth at DesignThis study reports findings from a prospective birth cohort. Saliva cortisol concentrations were measured prevaccination and postvaccination, and in the morning and evening, at 4 months chronological age.SettingInfants born at a single Scottish hospital.Participants45 term-born, 42 very preterm and 16 extremely preterm infants.OutcomesCortisol stress response to vaccination (postvaccination minus prevaccination cortisol concentrations), diurnal slope (log-transformed morning minus log-transformed evening cortisol values) and mean log-transformed daily cortisol.ResultsCompared with infants born at term, infants born extremely preterm had a blunted cortisol response to vaccination (5.8 nmol/L vs 13.1 nmol/L, difference in means: −7.3 nmol/L, 95% CI −14.0 to −0.6) and a flattened diurnal slope (difference in geometric means: −72.9%, 95% CI −87.1 to −42.8). In contrast, the cortisol response to vaccination (difference in means −2.7 nmol/L, 95% CI −7.4 to 2.0) and diurnal slope at 4 months (difference in geometric means: −33.6%, 95% CI −62.0 to 16.0) did not differ significantly in infants born very preterm compared with infants born at term.ConclusionsInfants born extremely preterm have blunted cortisol reactivity and a flattened diurnal slope. These patterns of HPA axis regulation are commonly seen after childhood adversity and could contribute to later metabolic and neurodevelopmental phenotypes observed in this population.

Background Preterm birth can lead to impaired language development. This study aimed to predict language outcomes at 2 years corrected gestational age (CGA) for children born preterm. Methods We analysed data from 89 preterm neonates (median GA 29 weeks) who underwent diffusion MRI (dMRI) at term-equivalent age and language assessment at 2 years CGA using the Bayley-III. Feature selection and a random forests classifier were used to differentiate typical versus delayed (Bayley-III language composite score Results The model achieved balanced accuracy: 91%, sensitivity: 86%, and specificity: 96%. The probability of language delay at 2 years CGA is increased with: increasing values of peak width of skeletonized fractional anisotropy (PSFA), radial diffusivity (PSRD), and axial diffusivity (PSAD) derived from dMRI; among twins; and after an incomplete course of, or no exposure to, antenatal corticosteroids. Female sex and breastfeeding during the neonatal period reduced the risk of language delay. Conclusions The combination of perinatal clinical information and MRI features leads to accurate prediction of preterm infants who are likely to develop language deficits in early childhood. This model could potentially enable stratification of preterm children at risk of language dysfunction who may benefit from targeted early interventions. Impact A combination of clinical perinatal factors and neonatal DTI measures of white matter microstructure leads to accurate prediction of language outcome at 2 years corrected gestational age following preterm birth. A model that comprises clinical and MRI features that has potential to be scalable across centres. It offers a basis for enhancing the power and generalizability of diagnostic and prognostic studies of neurodevelopmental disorders associated with language impairment. Early identification of infants who are at risk of language delay, facilitating targeted early interventions and support services, which could improve the quality of life for children born preterm.

Background Preterm birth is associated with dysconnectivity of structural brain networks, impaired cognition and psychiatric disease. Systemic inflammation contributes to cerebral dysconnectivity, but the immune mediators driving this association are poorly understood. We analysed information from placenta, umbilical cord and neonatal blood, and brain MRI to determine which immune mediators link perinatal systemic inflammation with dysconnectivity of structural brain networks. Methods Participants were 102 preterm infants (mean gestational age 29+1 weeks, range 23+3-32+0). Placental histopathology identified reaction patterns indicative of histologic chorioamnionitis (HCA), and a customized immunoassay of 24 inflammation-associated proteins selected to reflect the neonatal innate and adaptive immune response was performed from umbilical cord (n = 55) and postnatal day 5 blood samples (n = 71). Brain MRI scans were acquired at term-equivalent age (41+0 weeks [range 38+0-44+4 weeks]) and alterations in white matter connectivity were inferred from mean diffusivity and neurite density index across the white matter skeleton. Results HCA was associated with elevated concentrations of C5a, C9, CRP, IL-1β, IL-6, IL-8 and MCP-1 in cord blood, and IL-8 concentration predicted HCA with an area under the receiver operator curve of 0.917 (95% CI 0.841 – 0.993, p Conclusions These findings suggest that IL-8 dysregulation has a role in linking perinatal systemic inflammation and atypical white matter development in preterm infants.

BackgroundHypothalamic-pituitary-adrenal (HPA) axis adaptation is a potential mechanism linking early life exposures with later adverse health. This study tested the hypothesis that preterm birth is associated with adaptation of diurnal cortisol regulation across infancy.MethodsA secondary analysis was conducted of saliva cortisol measured morning, midday and evening, monthly, across infancy, as part of a birth cohort conducted in Linköping, Sweden. Diurnal cortisol regulation of infants born extremely preterm (n=24), very preterm (n=27) and at term (n=130) were compared across infancy through random coefficients regression models.ResultsCompared with infants born at term, infants born extremely preterm (−17.2%, 95% CI: −30.7 to −1.2), but not very preterm (1.7%, 95% CI: −14.1 to 20.4), had a flattened diurnal slope across infancy.ConclusionsExtremely preterm birth is associated with a flattened diurnal slope in infancy. This pattern of cortisol regulation could contribute to adverse metabolic and neurodevelopmental phenotypes observed in this population.

Preterm birth is closely associated with diffuse white matter dysmaturation inferred from diffusion MRI and neurocognitive impairment in childhood. Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are distinct dMRI modalities, yet metrics derived from these two methods share variance across tracts. This raises the hypothesis that dimensionality reduction approaches may provide efficient whole-brain estimates of white matter microstructure that capture (dys)maturational processes. To investigate the optimal model for accurate classification of generalised white matter dysmaturation in preterm infants we assessed variation in DTI and NODDI metrics across 16 major white matter tracts using principal component analysis and structural equation modelling, in 79 term and 141 preterm infants at term equivalent age. We used logistic regression models to evaluate performances of single-metric and multimodality general factor frameworks for efficient classification of preterm infants based on variation in white matter microstructure. Single-metric general factors from DTI and NODDI capture substantial shared variance (41.8-72.5%) across 16 white matter tracts, and two multimodality factors captured 93.9% of variance shared between DTI and NODDI metrics themselves. General factors associate with preterm birth and a single model that includes all seven DTI and NODDI metrics provides the most accurate prediction of microstructural variations associated with preterm birth. This suggests that despite global covariance of dMRI metrics in neonates, each metric represents information about specific (and additive) aspects of the underlying microstructure that differ in preterm compared to term subjects.HighlightsWe measured variation of 7 DTI and NODDI metrics across 16 major tractsGeneral factors for DTI and NODDI capture substantial shared variance across tractsGeneral factors also capture substantial shared variance between DTI and NODDISingle-metric and multimodality factors associate with gestational age at birthThe best preterm prediction model contains all 7 single-metric g-factors

The mechanisms linking maternal stress in pregnancy with infant neurodevelopment in a sexually dimorphic manner are poorly understood. We tested the hypothesis that maternal hypothalamic-pituitary-adrenal axis activity, measured by hair cortisol concentration (HCC), is associated with microstructure, structural connectivity, and volume of the infant amygdala. In 78 mother-infant dyads, maternal hair was sampled postnatally, and infants underwent magnetic resonance imaging at term-equivalent age. We found a relationship between maternal HCC and amygdala development that differed according to infant sex. Higher HCC was associated with higher left amygdala fractional anisotropy (β = 0.677, p=0.010), lower left amygdala orientation dispersion index (β = −0.597, p=0.034), and higher fractional anisotropy in connections between the right amygdala and putamen (β = 0.475, p=0.007) in girls compared to boys. Furthermore, altered amygdala microstructure was only observed in boys, with connectivity changes restricted to girls. Maternal cortisol during pregnancy is related to newborn amygdala architecture and connectivity in a sexually dimorphic manner. Given the fundamental role of the amygdala in the emergence of emotion regulation, these findings offer new insights into mechanisms linking maternal health with neuropsychiatric outcomes of children., eLife digest Stress during pregnancy, for example because of mental or physical disorders, can have long-term effects on child development. Epidemiological studies have shown that individuals exposed to stress in the womb are at higher risk of developmental and mood conditions, such as ADHD and depression. This effect is different between the sexes, and the biological mechanisms that underpin these observations are poorly understood. One possibility is that a baby’s developing amygdala, the part of the brain that processes emotions, is affected by a signal known as cortisol. This hormone is best known for its role in coordinating the stress response, but it also directs the growth of a fetus. Tracking fetal amygdala changes as well as cortisol levels in the pregnant individual could explain how stress during pregnancy affects development. To investigate, Stoye et al. recruited nearly 80 volunteers and their newborn children. MRI scans were used to examine the structure of the amygdala, and how it is connected to other parts of the brain. In parallel, the amount of cortisol was measured in hair samples collected from the volunteers around the time of birth, which reflects stress levels during the final three months of pregnancy. Linking the brain imaging results to the volunteers’ cortisol levels showed that being exposed to higher cortisol levels in the womb affected babies in different ways based on their sex: boys showed alterations in the fine structure of their amygdala, while girls displayed changes in the way that brain region connected to other neural networks. The work by Stoye et al. potentially reveals a biological mechanism by which early exposure to stress could affect brain development differently between the sexes, potentially informing real-world interventions.

The human adult structural connectome has a rich topology composed of nodal hierarchies containing highly diverse connectivity patterns, aligned to the diverse range of functional specialisations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of neu-rocognitive impairment and atypical brain development, on hierarchical complexity. We report that the neonatal and adult structural connectomes are both composed of distinct hierarchical tiers. Consistency of ROIs is found at both ends of this hierarchy during early life and in adulthood, but significant differences are evident in intermediate tiers. The neonatal connectome is hierarchically complex in term born neonates, but hierarchically complexity is altered in association with preterm birth. This is mainly due to diversity of connectivity patterns in Tier 3, which is comprised of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (comprising hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid hierarchical structure in hub regions allowing for the development of greater and more diverse functional specialisation in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.

Highlights • Multiple MRI features are integrated in a single model to study brain maturation in newborns. • Morphometric similarity networks (MSNs) provide a whole-brain description of the structural properties of neonatal brain. • The information encoded in MSNs is predictive of chronological brain age in the perinatal period. • MSNs provide a novel data-driven method for investigating neuroanatomic variation associated with preterm birth., Graphical abstract, Multi-contrast MRI captures information about brain macro- and micro-structure which can be combined in an integrated model to obtain a detailed “fingerprint” of the anatomical properties of an individual’s brain. Inter-regional similarities between features derived from structural and diffusion MRI, including regional volumes, diffusion tensor metrics, neurite orientation dispersion and density imaging measures, can be modelled as morphometric similarity networks (MSNs). Here, individual MSNs were derived from 105 neonates (59 preterm and 46 term) who were scanned between 38 and 45 weeks postmenstrual age (PMA). Inter-regional similarities were used as predictors in a regression model of age at the time of scanning and in a classification model to discriminate between preterm and term infant brains. When tested on unseen data, the regression model predicted PMA at scan with a mean absolute error of 0.70 ± 0.56 weeks, and the classification model achieved 92% accuracy. We conclude that MSNs predict chronological brain age accurately; and they provide a data-driven approach to identify networks that characterise typical maturation and those that contribute most to neuroanatomic variation associated with preterm birth.

Adult hair glucocorticoid concentrations reflect months of hypothalamic-pituitary-adrenal axis activity. However, little is known about the determinants of neonatal hair glucocorticoids. We tested associations between perinatal exposures and neonatal hair glucocorticoids. Cortisol and cortisone were measured by LC-MS/MS in paired maternal and infant hair samples collected within 10 days of birth (n = 49 term, n = 47 preterm), with neonatal samples collected at 6-weeks in n = 54 preterm infants. We demonstrate cortisol accumulation in hair increases with fetal maturity, with hair cortisol being higher in term than preterm born infants after delivery (median 401 vs 106 pg/mg; p, Highlights • Neonatal hair cortisol is higher after term compared to preterm birth. • Neonatal hair cortisol reflects fetal growth, maternal cortisol and birth exposures. • Hair sampled at 6 weeks reflects postnatal exposures in preterm infants.

Preterm infants are at increased risk of alterations in brain structure and connectivity, and subsequent neurocognitive impairment. Breast milk may be more advantageous than formula feed for promoting brain development in infants born at term, but uncertainties remain about its effect on preterm brain development and the optimal nutritional regimen for preterm infants. We test the hypothesis that breast milk exposure is associated with improved markers of brain development and connectivity in preterm infants at term equivalent age. We collected information about neonatal breast milk exposure and brain MRI at term equivalent age from 47 preterm infants (mean postmenstrual age [PMA] 29.43 weeks, range 23.28-33.0). Network-Based Statistics (NBS), Tract-based Spatial Statistics (TBSS) and volumetric analysis were used to investigate the effect of breast milk exposure on white matter water diffusion parameters, tissue volumes, and the structural connectome. Twenty-seven infants received exclusive breast milk feeds for ≥75% of days of in-patient care and this was associated with higher connectivity in the fractional anisotropy (FA)-weighted connectome compared with the group who had 75% of days receiving exclusive breast milk feeds (NBS, p = 0.04). Within the TBSS white matter skeleton, the group that received ≥75% exclusive breast milk days exhibited higher FA within the corpus callosum, cingulum cingulate gyri, centrum semiovale, corticospinal tracts, arcuate fasciculi and posterior limbs of the internal capsule compared with the low exposure group after adjustment for PMA at birth, PMA at image acquisition, bronchopulmonary dysplasia, and chorioamnionitis (p 0.05). The effect on structural connectivity and tract water diffusion parameters was greater with ≥90% exposure, suggesting a dose effect. There were no significant groupwise differences in brain volumes. Breast milk feeding in the weeks after preterm birth is associated with improved structural connectivity of developing networks and greater FA in major white matter fasciculi.