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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.

Highlights • 60 studies of association between DNAm and human brain MRI were identified. • Differential DNAm is associated with brain structure and function throughout life. • There is modest consistency between DNAm and image endophenotypes. • Approaches for reducing heterogeneity in DNAm-MRI analyses are proposed., MRI has enhanced our capacity to understand variations in brain structure and function conferred by the genome. We identified 60 studies that report associations between DNA methylation (DNAm) and human brain structure/function. Forty-three studies measured candidate loci DNAm; seventeen measured epigenome-wide DNAm. MRI features included region-of-interest and whole-brain structural, diffusion and functional imaging features. The studies report DNAm-MRI associations for: neurodevelopment and neurodevelopmental disorders; major depression and suicidality; alcohol use disorder; schizophrenia and psychosis; ageing, stroke, ataxia and neurodegeneration; post-traumatic stress disorder; and socio-emotional processing. Consistency between MRI features and differential DNAm is modest. Sources of bias: variable inclusion of comparator groups; different surrogate tissues used; variation in DNAm measurement methods; lack of control for genotype and cell-type composition; and variations in image processing. Knowledge of MRI features associated with differential DNAm may improve understanding of the role of DNAm in brain health and disease, but caution is required because conventions for linking DNAm and MRI data are not established, and clinical and methodological heterogeneity in existing literature is substantial.

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

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.

Introduction Preterm birth (PTB) is closely associated with atypical cerebral cortical development and cognitive impairment. Early exposure to extrauterine life often results in atypical environmental and biological experiences that co-occur, including early life stress (ELS) and systemic inflammation. Understanding how these experiences interact to shape cortical development is an essential prerequisite to developing therapeutic interventions that will work in the complex postnatal environment of the preterm infant. Here, we studied the effects of a murine model of infection and ELS on the neonatal cortex transcriptome. Methods We used a mouse model of infection (1 ​mg/kg LPS at postnatal day (P)3) +/− ELS (modified maternal separation; MMS on days P4–P6) at timepoints with neurodevelopmental relevance to PTB. We used 4 groups: control, LPS, MMS and LPS ​+ ​MMS. Cortices were dissected at P6 for 3′RNA sequencing. Results LPS exposure resulted in reduced weight gain and increased expression of inflammation-associated genes in the brain. More genes were differentially expressed following LPS (15) and MMS (29) than with LPS ​+ ​MMS (8). There was significant overlap between the LPS and MMS datasets, particularly amongst upregulated genes, and when comparing LPS and MMS datasets with LPS ​+ ​MMS. Gene Ontology terms related to the extracellular matrix and cytokine response were enriched following MMS, but not following LPS or LPS ​+ ​MMS. 26 Reactome pathways were enriched in the LPS group, none of which were enriched in the LPS ​+ ​MMS group. Finally, a rank-rank hypergeometric overlap test showed similarities, particularly in upregulated genes, in the LPS and MMS conditions, indicating shared mechanisms. Conclusion LPS and MMS interact to modify the cortical transcriptome in the neonatal period. This has important implications for understanding the neural basis of atypical cortical development associated with early exposure to extrauterine life., Highlights • LPS exposure is associated with reduced weight gain in the neonatal period. • There is an overlap in the transcriptomic response to LPS and early life stress (ELS). • LPS and ELS modulate the response to each other in the developing male cerebral cortex.

Preterm birth is associated with altered connectivity of neural circuits. We developed a tract segmentation method that provides measures of tract shape and integrity (probabilistic neighborhood tractography, PNT) from diffusion MRI (dMRI) data to test the hypotheses: 1) preterm birth is associated with alterations in tract topology (R), and tract-averaged mean diffusivity (〈D〉) and fractional anisotropy (FA); 2) neural systems are separable based on tract-averaged dMRI parameters; and 3) PNT can detect neuroprotective treatment effects. dMRI data were collected from 87 preterm infants (mean gestational age 29+1 weeks, range 23+2 –34+6) at term equivalent age and 24 controls (mean gestational age 39+6 weeks). PNT was used to segment eight major fasciculi, characterize topology, and extract tract-averaged 〈D〉 and FA. Tract topology was altered by preterm birth in all tracts except the splenium (p, Highlights • Probabilistic neighborhood tractography models tract shape from neonatal dMRI. • The shape of major fasciculi is altered in association with preterm birth. • Developing neural systems are separable based on dMRI parameters. • Tract-averaged dMRI parameters are sensitive to neuroprotective treatment effects.

The prevalence of preterm birth is increasing globally and it is a leading cause of neurodevelopmental impairment in childhood. Preterm brain injury consists predominantly of: white matter disease, which may be diffuse or cystic and is usually accompanied by grey matter alterations; and haemorrhagic lesions (germinal matrix haemorrhage–intraventricular haemorrhage). The evidence base for neuroprotective strategies has grown in recent years. Antenatal interventions include the use of corticosteroids and magnesium sulphate, and organisation of maternity services so that early postnatal transfer is avoided. Postnatal interventions associated with improved neurological outcome include delayed clamping of the umbilical cord, respiratory management strategies that reduce the incidence of pneumothorax and bronchopulmonary dysplasia, avoidance of hypotension and hypocarbia, feeding practices that promote human milk intake, caffeine therapy, avoidance of early relatively high dose postnatal dexamethasone, and minimising the incidence of postnatal sepsis. In this review, we describe the predominant forms of preterm brain injury in the current era and consider the evidence base for clinical practices designed to reduce brain injury and adverse outcome after preterm birth.

Introduction Defining connectivity in the human brain signifies a major neuroscientific goal. Advanced imaging techniques have enabled the non-invasive tracing of brain networks to define the human connectome on a millimetre-scale. During early development, the brain undergoes significant changes that are likely represented in the developing connectome, and preterm birth represents a significant environmental risk factor that impacts negatively on early cerebral development. Using tractography to comprehensively map the connections of the thalamocortical unit, we aim to demonstrate that premature extrauterine life due to preterm delivery results in significantly decreased thalamocortical connectivity in the developing human neonate. Methods T1- and T2-weighted magnetic resonance images and 32-direction diffusion tensor images were acquired from 18 healthy term-born neonates (median gestational age: 41+3) and 47 preterm infants (median gestational age: 28+3) scanned at term-equivalent age. Using a novel processing pipeline for tracing connections in the neonatal brain we map and compare the thalamocortical macro-connectome between groups. Results We demonstrate that connections between the thalamus and the frontal cortices, supplementary motor areas, occipital lobe and temporal gyri are significantly diminished in preterm infants (FDR-corrected, p Conclusions This supports the hypothesis that the thalamocortical system is vulnerable following preterm birth and the tractographic framework presented represents a method for analysing system connectivity that can be readily applied to other populations and neural systems.

Medical imaging has shown that, during early development, the brain undergoes more changes in size, shape and appearance than at any other time in life. A better understanding of brain development requires a spatio-temporal atlas that characterizes the dynamic changes during this period. In this paper we present an approach for constructing a 4D atlas of the developing brain, between 28 and 44 weeks post-menstrual age at time of scan, using T1 and T2 weighted MR images from 204 premature neonates. The method used for the creation of the average 4D atlas utilizes non-rigid registration between all pairs of images to eliminate bias in the atlas toward any of the original images. In addition, kernel regression is used to produce age-dependent anatomical templates. A novelty in our approach is the use of a time-varying kernel width, to overcome the variations in the distribution of subjects at different ages. This leads to an atlas that retains a consistent level of detail at every time-point. Comparisons between the resulting atlas and atlases constructed using affine and non-rigid registration are presented. The resulting 4D atlas has greater anatomic definition than currently available 4D atlases created using various affine and non-rigid registration approaches, an important factor in improving registrations between the atlas and individual subjects. Also, the resulting 4D atlas can serve as a good representative of the population of interest as it reflects both global and local changes. The atlas is publicly available at www.brain-development.org .

Diffuse white matter injury is common in preterm infants and is a candidate substrate for later cognitive impairment. This injury pattern is associated with morphological changes in deep grey nuclei, the localization of which is uncertain. We test the hypotheses that diffuse white matter injury is associated with discrete focal tissue loss, and that this image phenotype is associated with impairment at 2years. We acquired magnetic resonance images from 80 preterm infants at term equivalent (mean gestational age 29(+6)weeks) and 20 control infants (mean GA 39(+2)weeks). Diffuse white matter injury was defined by abnormal apparent diffusion coefficient values in one or more white matter region (frontal, central or posterior white matter at the level of the centrum semiovale), and morphological difference between groups was calculated from 3D images using deformation based morphometry. Neurodevelopmental assessments were obtained from preterm infants at a mean chronological age of 27.5months, and from controls at a mean age of 31.1months. We identified a common image phenotype in 66 of 80 preterm infants at term equivalent comprising: diffuse white matter injury; and tissue volume reduction in the dorsomedial nucleus of the thalamus, the globus pallidus, periventricular white matter, the corona radiata and within the central region of the centrum semiovale (t=4.42 p

Three-dimensional atlases and databases of the brain at different ages facilitate the description of neuroanatomy and the monitoring of cerebral growth and development. Brain segmentation is challenging in young children due to structural differences compared to adults. We have developed a method, based on established algorithms, for automatic segmentation of young children's brains into 83 regions of interest (ROIs), and applied this to an exemplar group of 33 2-year-old subjects who had been born prematurely. The algorithm uses prior information from 30 normal adult brain magnetic resonance (MR) images, which had been manually segmented to create 30 atlases, each labeling 83 anatomical structures. Each of these adult atlases was registered to each 2-year-old target MR image using non-rigid registration based on free-form deformations. Label propagation from each adult atlas yielded a segmentation of each 2-year-old brain into 83 ROIs. The final segmentation was obtained by combination of the 30 propagated adult atlases using decision fusion, improving accuracy over individual propagations. We validated this algorithm by comparing the automatic approach with three representative manually segmented volumetric regions (the subcortical caudate nucleus, the neocortical pre-central gyrus and the archicortical hippocampus) using similarity indices (SI), a measure of spatial overlap (intersection over average). SI results for automatic versus manual segmentations for these three structures were 0.90+/-0.01, 0.90+/-0.01 and 0.88+/-0.03 respectively. This registration approach allows the rapid construction of automatically labelled age-specific brain atlases for children at the age of 2 years.

Preterm delivery accounts for 5% of all deliveries and its consequences contribute to significant individual, medical, and social problems. The neuroanatomical substrates of these disorders are not known, but are essential for understanding mechanisms of causation, and developing strategies for intervention. In the recent years, multivariate pattern recognition methods that analyse all voxels simultaneously have been proposed to characterise the neuroanatomical differences between a reference group of magnetic resonance (MR) images and the population under investigation. Most of these techniques have overcome the difficulty of dealing with the inherent high dimensionality of 3D MR brain image data by using pre-processed segmented images or a small number of specific features. However, an intuitive way of mapping the classification results back into the original image domain for further interpretation remains challenging. In this paper, we propose the idea of using Principal Components Analysis (PCA) plus the maximum uncertainty Linear Discriminant Analysis (MLDA) approach to classify and analyse MR brain images that have been aligned with either affine or non-rigid registration techniques. This approach avoids the computation costs intrinsic to commonly used covariance-based optimisation processes for solving small sample size problems, resulting in a simple and efficient implementation for the maximisation and interpretation of the Fisher's classification results. In order to demonstrate the effectiveness of the approach, we have used a neonatal MR brain data set that contains images of 93 preterm infants at term equivalent age and 20 term controls. Our results indicate that the two-stage linear framework makes clear the statistical differences between the control and preterm samples, showing a classification accuracy of 95.0% and 97.8% for the controls and preterms samples, respectively, using the leave-one-out method. Moreover, it provides a simple and intuitive method of visually analysing the differences between preterm infants at term equivalent age and the control group, such as differences in cerebrospinal fluid spaces, structure of the corpus callosum, and subtle differences in myelination.

Preterm birth is a leading risk factor for neurodevelopmental and cognitive impairment in childhood and adolescence. The most common known cerebral abnormality among preterm infants at term equivalent age is a diffuse white matter abnormality seen on magnetic resonance (MR) images. It occurs with a similar prevalence to subsequent impairment, but its effect on developing neural systems is unknown. MR images were obtained at term equivalent age from 62 infants born at 24–33 completed weeks gestation and 12 term born controls. Tissue damage was quantified using diffusion-weighted imaging, and deformation-based morphometry was used to make a non-subjective survey of the whole brain to identify significant cerebral morphological alterations associated with preterm birth and with diffuse white matter injury. Preterm infants at term equivalent age had reduced thalamic and lentiform volumes without evidence of acute injury in these regions (t = 5.81, P < 0.05), and these alterations were more marked with increasing prematurity (t = 7.13, P < 0.05 for infants born at less than 28 weeks) and in infants with diffuse white matter injury (t = 6.43, P < 0.05). The identification of deep grey matter growth failure in association with diffuse white matter injury suggests that white matter injury is not an isolated phenomenon, but rather, it is associated with the maldevelopment of remote structures. This could be mediated by a disturbance to corticothalamic connectivity during a critical period in cerebral development. Deformation-based morphometry is a powerful tool for modelling the developing brain in health and disease, and can be used to test putative aetiological factors for injury.

Preterm birth is associated with a high prevalence of neuropsychiatric impairment in childhood and adolescence, but the neural correlates underlying these disorders are not fully understood. Quantitative magnetic resonance imaging techniques have been used to investigate subtle differences in cerebral growth and development among children and adolescents born preterm or with very low birth weight. Diffusion tensor imaging and computer-assisted morphometric techniques (including voxel-based morphometry and deformation-based morphometry) have identified abnormalities in tissue microstructure and cerebral morphology among survivors of preterm birth at different ages, and some of these alterations have specific functional correlates. This chapter reviews the literature reporting differential brain development following preterm birth, with emphasis on the morphological changes that correlate with neuropsychiatric impairment.

Background We have previously identified an association between lipids and features of diffusion tensor imaging in preterm infants, highlighting the KEGG peroxisome proliferator-activated receptor pathway (PPAR) as the most highly ranked in association with a white matter phenotype. Here we applied a penalised linear regression model—the graph-guided group lasso (GGGL)—to select single nucleotide polymorphisms within functionally related genes associated with the imaging trait. The GGGL model utilises network-based prior knowledge to improve the selection of variables of interest. Methods Images acquired with a 3T MR scanner were collected along with saliva for 72 preterm infants (mean gestational age 28 weeks [+4 days], mean postmenstrual age at scan 40 weeks [+3 days]). Salivary DNA was extracted and genotyped with HumanOmniExpress-12 arrays (Illumina, San Diego, CA, USA). Fractional anisotropy maps were constructed from diffusion tensor imaging, and tract-based spatial statistics were used to obtain a group white matter skeleton varying with degree of prematurity, adjusting for age at scan. GGGL was applied to the genes in the PPAR pathway. Findings The GGGL method selected five of the 69 genes in the PPAR pathway, and these were functionally related in terms of Gene Ontology Biological Process and linearly correlated with white matter fractional anisotropy ( AQP7, ME1, PLIN1, SLC27A1 , and ACAA1 ). Analysis of transcriptional regulation with the PASTAA algorithm indicated that ACAA1, AQP7, ME1 , and SLC27A1 were jointly regulated by the EGR4 transcription factor (adjusted p=7·7×10 −4 ). Interpretation Our GGGL analysis of genes in the PPAR pathway identified five highly ranked genes involved in neuronal growth, myelinogenesis, and nervous system response to inflammation, and jointly transcriptionally regulated. Since preterm infants are at increased risk of mental illness and cardiovascular morbidity in later life, this work uses an integrative data-driven strategy to propose a unifying mechanism for these systemic effects, suggesting a promising avenue for intervention. Funding Medical Research Council, National Institute for Health Research Biomedical Research Centre.