2020

We often model the brain as a network where the nodes are different brain regions and links between nodes represent the wiring connecting brain regions. Hierarchical complexity is a property of networks that tells us how diverse the connections are between similar nodes. When we translate this property into the brain, we can study how different areas of the brain are interconnected. In this work we did exactly that, finding some interesting properties of the neonatal brain. The first thing we noticed is that the newborn brain resembles the adult brain in terms of how the areas are connected to each other, and the second is that prematurity affects this property in the most specialized areas of the brain. The most central areas (knows as hubs, because they are connected most other areas of the brain) have the same connections in term and preterm infants, but other more specialised areas have different connections in the preterm babies compared to the term born.

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.

What was found?

We found that at 7-9 months of age, babies born at term had a stronger preference for social information compared to babies who were born early. However, by the time these children reached 5 years of age, preferences for social information were similar between preterm and term born children. We also found that reduced preference for social content at 7-9 months was associated with earlier gestational age and with socioeconomic disadvantage.

What we did?

We used a special type of camera (an eye-tracker) to measure eye-movements while children viewed images and videos of people and other non-social content. We compared their preference for social compared to non-social pictures. We did this when children were 7-9 months old and then again when they were 5-years of age.

What are the implications?

These findings indicate that children who were born early “catch-up” with their term-born peers by school-age. They also tell us that we might be able to use information about a child’s socio-economic circumstances and / or their gestational age to identify babies that might benefit support with their social development in early life.

Background: The UK hosts some of the world’s longest-running longitudinal cohort studies, which make repeated observations of their participants and use these data to explore health outcomes. An alternative method for data collection is record linkage; the linking together of electronic health and administrative records. Applied nationally, this could provide unrivalled opportunities to follow a large number of people in perpetuity. However, public attitudes to the use of data in research are currently unclear. Here we report on an event where we collected attitudes towards recent opportunities and controversies within health data science. Methods: The event was attended by ~250 individuals (cohort members and their guests), who had been invited through the offices of their participating cohort studies. There were a series of presentations describing key research results and the audience participated in 15 multiple-choice questions using interactive voting pads. Results: Our participants showed a high level of trust in researchers (87% scoring them 4/5 or 5/5) and doctors (81%); but less trust in commercial companies (35%). They supported the idea of researchers using information from both neonatal blood spots (Guthrie spots) (97% yes) and from electronic health records (95% yes). Our respondents were willing to wear devices like a ‘Fit-bit’ (88% agreed) or take a brain scan that might predict later mental illness (73%). However, they were less willing to take a new drug for research purposes (45%). They were keen to encourage others to take part in research; whether that be offering the opportunity to pregnant mothers (97% agreed) or extending invitations to their own children and grandchildren (98%). Conclusions: Our participants were broadly supportive of research access to data, albeit less supportive when commercial interests were involved. Public engagement events that facilitate two-way interactions can influence and support future research and public engagement efforts.

Some babies who are born too soon can encounter problems with learning, thinking and behaviour as they grow up due to altered brain development. One of the key aims of the Theirworld Edinburgh Birth Cohort is to identify causes of alterations in brain development after preterm birth so that we can develop effective treatments to reduce the risk of long-term problems.

We know that infection or inflammation around the time of birth can increase the risk of developmental problems but because our immune system responses to infection are complex, the specific mediators driving this association are not well understood.

During her PhD, Gemma Sullivan investigated the role of specific immune mediators in brain development after preterm birth and identified a potential therapeutic target. By combining information from placenta, blood and brain MRI from 71 preterm infants, she found that a protein generated by the immune system in response to infection, known as interleukin-8 (IL-8), was associated with altered development of the major information highways of the brain.

These findings suggest that preterm babies may benefit from therapies to reduce inflammation and restore healthy brain development.

Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10^-4. PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life.

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.

Introduction: Preterm birth is closely associated with altered brain development and is a leading cause of neurodevelopmental, cognitive and behavioural impairments across the life course. We aimed to investigate neuroanatomic variation and adverse outcomes associated with preterm birth by studying a cohort of preterm infants and controls born at term using brain MRI linked to biosamples and clinical, environmental and neuropsychological data.

Methods and analysis: Theirworld Edinburgh Birth Cohort is a prospective longitudinal cohort study at the University of Edinburgh. We plan to recruit 300 infants born at <33 weeks of gestational age (GA) and 100 healthy control infants born after 37 weeks of GA. Multiple domains are assessed: maternal and infant clinical and demographic information; placental histology; immunoregulatory and trophic proteins in umbilical cord and neonatal blood; brain macrostructure and microstructure from structural and diffusion MRI (dMRI); DNA methylation; hypothalamic-pituitary-adrenal axis activity; social cognition, attention and processing speed from eye tracking during infancy and childhood; neurodevelopment; gut and respiratory microbiota; susceptibility to viral infections; and participant experience. Main analyses include creation of novel methods for extracting information from neonatal structural and dMRI, regression analyses of predictors of brain maldevelopment and neurocognitive outcome associated with preterm birth, and determination of the quantitative predictive performance of MRI and other early life factors for childhood outcome.

Ethics and dissemination: Ethical approval has been obtained from the National Research Ethics Service (NRES), South East Scotland Research Ethics Committee (NRES numbers 11/55/0061 and 13/SS/0143 (phase I) and 16/SS/0154 (phase II)), and NHS Lothian Research and Development (2016/0255). Results are disseminated through open access journals, scientific meetings, social media, newsletters anda study website (www.tebc.ed.ac.uk), and we engage with the University of Edinburgh public relations and media office to ensure maximum publicity and benefit.

Context: Across pregnancy, maternal serum cortisol levels increase up to 3-fold. It is not known whether maternal peripheral cortisol metabolism and clearance change across pregnancy or influence fetal cortisol exposure and development.

Objectives: The primary study objective was to compare maternal urinary glucocorticoid metabolites, as markers of cortisol metabolism and clearance, between the second and third trimester of pregnancy. Secondary objectives were to test associations of total maternal urinary glucocorticoid excretion, with maternal serum cortisol levels and offspring birth weight z score.

Design, participants, and setting: A total of 151 women with singleton pregnancies, recruited from prenatal clinic at the Pittsburgh site of the Measurement of Maternal Stress (MOMS) study, had 24-hour urine collections during both the second and third trimesters.

Results: Between the second and third trimester, total urinary glucocorticoid excretion increased (ratio of geometric means [RGM] 1.37, 95% CI 1.22-1.52, P < .001), and there was an increase in calculated 5β-reductase compared to 5α-reductase activity (RGM 3.41, 95% CI 3.04-3.83, P < .001). During the third trimester total urinary glucocorticoid excretion and serum cortisol were negatively correlated (r = -0.179, P = .029). Mean total urinary glucocorticoid excretion across both trimesters and offspring birth weight z score were positively associated (β = 0.314, P = .001).

Conclusions: The estimated activity of maternal enzymes responsible for cortisol metabolism change between the second and third trimester of pregnancy. Additionally, maternal peripheral metabolism and clearance of cortisol may serve as a novel mechanism affecting fetal cortisol exposure and growth.

All people are different, and so are our brain. Through magnetic resonance imaging (MRI) we can acquire different types of brain images describing several aspects of the new-born brains: from the macroscopic level (e.g., how big a brain is) to the microscopic level (e.g., how water molecules move in brain tissue). Putting together all the information that we acquire from MRI scans, we can obtain a “fingerprint” describing the unique properties of an individual’s brain. To do so, we used a model called Morphometric similarity networks (MSNs), that builds such a fingerprint by measuring how brain characteristics vary across different regions of the brain.

Using data from 105 neonates of the Theirworld Edinburgh Birth Cohort (59 preterm and 46 term), we applied this model to investigate how much of the variability that we observe between subjects can be explained by age differences, and to measure the effect of being born preterm.

What we found was that in the first weeks after birth most changes involved subcortical and fronto-temporal areas of the brain. When we compared preterm and term-born babies, the differences we observed were located mainly in frontal, parietal, temporal and insular regions. We show where these regions are in the figure above. In the future, we plan to link these findings to the behavioural data collected using eye-tracking, to see if the differences that we observe in brain development in early life are related to behavioural differences in childhood.

Preterm birth (PTB) is a leading cause of neurodevelopmental and neurocognitive impairment in childhood and is closely associated with psychiatric disease. The biological and environmental factors that confer risk and resilience for healthy brain development and long-term outcome after PTB are uncertain, which presents challenges for risk stratification and for the discovery and evaluation of neuroprotective strategies. Neonatal magnetic resonance imaging reveals a signature of PTB that includes dysconnectivity of neural networks and atypical development of cortical and deep grey matter structures. Here we provide a brief review of perinatal factors that are associated with the MRI signature of PTB. We consider maternal and foetal factors including chorioamnionitis, foetal growth restriction, socioeconomic deprivation and prenatal alcohol, drug and stress exposures; and neonatal factors including co-morbidities of PTB, nutrition, pain and medication during neonatal intensive care and variation conferred by the genome/epigenome. Association studies offer the first insights into pathways to adversity and resilience after PTB. Future challenges are to analyse quantitative brain MRI data with collateral biological and environmental data in study designs that support causal inference, and ultimately to use the output of such analyses to stratify infants for clinical trials of therapies designed to improve outcome.