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Introduction Preterm birth (PTB) is strongly associated with encephalopathy of prematurity (EoP) and neurocognitive impairment. The biological axes linking PTB with atypical brain development are uncertain. We aim to elucidate the roles of neuroendocrine stress activation and immune dysregulation in linking PTB with EoP.Methods and analysis PRENCOG (PREterm birth as a determinant of Neurodevelopment and COGnition in children: mechanisms and causal evidence) is an exposure-based cohort study at the University of Edinburgh. Three hundred mother–infant dyads comprising 200 preterm births (gestational age, GA 37 weeks, non-exposed), will be recruited between January 2023 and December 2027. We will collect parental and infant medical, demographic, socioeconomic characteristics and biological data which include placental tissue, umbilical cord blood, maternal and infant hair, infant saliva, infant dried blood spots, faecal material, and structural and diffusion MRI. Infant biosamples will be collected between birth and 44 weeks GA.EoP will be characterised by MRI using morphometric similarity networks (MSNs), hierarchical complexity (HC) and magnetisation transfer saturation imaging (MTsat). We will conduct: first, multivariable regressions and statistical association assessments to test how PTB-associated risk factors (PTB-RFs) relate to MSNs, HC and or MTsat; second, structural equation modelling to investigate neuroendocrine stress activation and immune dysregulation as mediators of PTB-RFs on features of EoP. PTB-RF selection will be informed by the variables that predict real-world educational outcomes, ascertained by linking the UK National Neonatal Research Database with the National Pupil Database.Ethics and dissemination A favourable ethical opinion has been given by the South East Scotland Research Ethics Committee 02 (23/SS/0067) and NHS Lothian Research and Development (2023/0150). Results will be reported to the Medical Research Council, in scientific media, via stakeholder partners and on a website in accessible language (https://www.ed.ac.uk/centre-reproductive-health/prencog).

Background The world is facing an opioid epidemic. Children of women who use opioids in pregnancy are difficult to follow-up over long periods using traditional research methods due to the complexity of their lives. Resultingly, we have little robust evidence on their longer-term outcomes. Objective This study aimed to explore the impact of illicit and prescription opioid exposure in pregnancy on preschool health and developmental outcomes. Approach Data identified 6,408 children (born 2009-2019 in Scotland) exposed to opioids through illicit use and/or medication assisted treatment (MAT), alongside a matched control group (n.19,089). Regression models will examine associations between opioid exposure and key outcomes up to age 5, including the Ages and Stages Questionnaire, accidents and injuries, and chronic health conditions such as asthma, controlling for other risk factors (e.g. alcohol use in pregnancy, gestation). Results Early results indicated differences in neonatal outcomes, with poorer outcomes for the illicit opioid/MAT cohort in terms of being born early, having lower birthweight, length and head circumference, and being more likely to be removed from their mother prior hospital discharge. Modelling of preschool outcomes is underway and will be finished in June 2024. Conclusions Having proven that we can identify these children in administrative data, this paper will present cutting-edge data on the impact of exposure to illicit and prescription opioids on preschool outcomes. This will provide robust evidence on these impacts, and highlight where additional support might be required for these children from birth to starting school.

Introduction The aim of the STOPPIT-3 study is to determine the clinical and cost effectiveness of antenatal corticosteroids (ACS) prior to planned birth of twins in a multicentre placebo-controlled trial with internal pilot.Methods and analysis This study will comprise a multicentre, double-blinded, randomised, placebo-controlled trial in at least 50 UK obstetric units. The target population is 1552 women with a twin pregnancy and a planned birth between 35 and 38+6 weeks’ gestation recruited from antenatal clinics. Women will be randomised to Dexamethasone Phosphate (24 mg) or saline administered via two intramuscular injections 24 hours apart, 24–120 hours prior to scheduled birth.Outcomes The primary outcome is need for respiratory support within 72 hours of birth. Secondary and safety outcomes will be included. Cognitive and language development at age 2 years will be assessed in a subset of participants using the Parent report of Children’s Abilities-Revised questionnaire. We will also determine the cost effectiveness of the treatment with ACS compared with placebo.Ethics and dissemination STOPPIT-3 has been funded and approved by the National Institute of Healthcare Research. It has been approved by the West Midlands Research Ethics Committee (22/WM/0018). The results will be disseminated via publication in peer-reviewed journals and conference presentation and will also be communicated to the public via links with charity partners and social media.Trial sponsor The University of Edinburgh and Lothian Health Board ACCORD, The Queen’s Medical Research Institute, 47 Little France Crescent, Edinburgh, EH16 4TJ.Trial registration number ISRCTN59959611.

Objectives Children of women who use substances are difficult to research at a population-level using traditional research methods due to the complexity of their lives. Resultingly, we have little robust evidence on their outcomes. This study developed an administrative data cohort of children exposed to opioids and explored health outcomes. Methods Using data from birth records, antenatal records, prescription data, hospital/psychiatric hospital admissions, and drug and alcohol service data, we identified 6,408 children (born 2009-2019) in Scotland who were exposed to opioids through illicit use and/or medication assisted treatment (i.e. methadone/buprenorphine). A control group (n. 19,089) of children not exposed to opioids were matched on age of mother and Scottish Index of Multiple Deprivation. Data were described and linear and logistic regression models were used to examine the relationship between risk factors (such as drug and alcohol use in pregnancy, gestation at booking and at birth), and key early outcomes. Results Although the majority of women had their substance use recorded in antenatal records, 28.9\% did not, demonstrating the importance of using multiple administrative datasets to form the cohort. Children in the cohort were more likely to experience a range of adverse outcomes including being born early (17\% born prematurely, compared with 6.5\% in control group), having a below normal Apgar score (the scoring system used to assess newborns shortly after birth) (2.9\% in cohort vs. 1.5\% in controls), having significantly lower birthweight, length and head circumference, and more likely to be removed from their mother prior hospital discharge. Differences between the cohorts remained after controlling for other risk factors including alcohol use, and gestation. Conclusion This feasibility study brought together a cohort of children usually excluded from traditional forms of research. The research demonstrated early differences in outcomes between exposed children and others from similar socio-economic groups. The next stage of this research is exploring health and development outcomes in the preschool period.

Introduction Methodologically robust clinical trials are required to improve neonatal care and reduce unwanted variations in practice. Previous neonatal research prioritisation processes have identified important research themes rather than specific research questions amenable to clinical trials. Practice-changing trials require well-defined research questions, commonly organised using the Population, Intervention, Comparison, Outcome (PICO) structure. By narrowing the scope of research priorities to those which can be answered in clinical trials and by involving a wide range of different stakeholders, we aim to provide a robust and transparent process to identify and prioritise research questions answerable within the National Healthcare System to inform future practice-changing clinical trials.Methods and analysis A steering group comprising parents, doctors, nurses, allied health professionals, researchers and representatives from key organisations (Neonatal Society, British Association of Perinatal Medicine, Neonatal Nurses Association and Royal College of Paediatrics and Child Health) was identified to oversee this project. We will invite submissions of research questions formatted using the PICO structure from the following stakeholder groups using an online questionnaire: parents, patients, healthcare professionals and academic researchers. Unanswered, non-duplicate research questions will be entered into a three-round eDelphi survey of all stakeholder groups. Research questions will be ranked by mean aggregate scores.Ethics and dissemination The final list of prioritised research questions will be disseminated through traditional academic channels, directly to key stakeholder groups through representative organisations and on social media. The outcome of the project will be shared with key research organisations such as the National Institute for Health Research. Research ethics committee approval is not required.

BackgroundApgar scores measure newborn health and are strongly associated with infant outcomes, but their performance has largely been determined in primarily white populations. Given the majority of the global population is not white, we aim to assess whether the association between low Apgar score and mortality in infants varies across racial groups.Methods and findingsPopulation-based cohort study using 2016 to 2017 United States National Vital Statistics System data. The study included singleton infants born between 37+0 and 44+6 weeks to mothers over 15 years, without congenital abnormalities. We looked at 3 different mortality outcomes: (1) early neonatal mortality; (2) overall neonatal mortality; and (3) infant mortality. We used logistic regression to assess the association between Apgar score (categorized as low, intermediate, and normal) and each mortality outcome, and adjusted for gestational age, sex, maternal BMI, education, age, previous number of live births, and smoking status, and stratified these models by maternal race group (as self-reported on birth certificates). The cohort consisted of 6,809,653 infants (52.8% non-Hispanic white, 23.7% Hispanic, 13.8% non-Hispanic black, 6.6% non-Hispanic Asian, and 3.1% non-Hispanic other). A total of 6,728,829 (98.8%) infants had normal scores, 63,467 (0.9%) had intermediate scores, and 17,357 (0.3%) had low Apgar scores. Compared to infants with normal scores, low-scoring infants had increased odds of infant mortality. There was strong evidence that this association varied by race (p < 0.001) with adjusted odds ratios (AORs) of 54.4 (95% confidence interval [CI] 49.9 to 59.4) in non-Hispanic white, 70.02 (95% CI 60.8 to 80.7) in Hispanic, 23.3 (95% CI 20.3 to 26.8) in non-Hispanic black, 100.4 (95% CI 74.5 to 135.4) in non-Hispanic Asian, and 26.8 (95% CI 19.8 to 36.3) in non-Hispanic other infants. The main limitation was missing data for some variables, due to using routinely collected data.ConclusionsThe association between Apgar scores and mortality varies across racial groups. Low Apgar scores are associated with mortality across racial groups captured by United States (US) records, but are worse at discriminating infants at risk of mortality for black and non-Hispanic non-Asian infants than for white infants. Apgar scores are useful clinical indicators and epidemiological tools; caution is required regarding racial differences in their applicability.

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.

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.

IntroductionPreterm 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 analysisTheirworld Edinburgh Birth Cohort is a prospective longitudinal cohort study at the University of Edinburgh. We plan to recruit 300 infants born at

Large diffusion-weighted brain MRI (dMRI) studies in neonates are crucial for developmental neuroscience. Our aim was to investigate the utility of ComBat, an empirical Bayes tool for multisite harmonization, in removing site effects from white matter (WM) dMRI measures in healthy infants born at 37 gestational weeks+ 0 days-42 weeks+ 6 days from the Theirworld Edinburgh Birth Cohort (n = 86) and Developing Human Connectome Project (n = 287). Skeletonized fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AD, RD) maps were harmonized. Differences between voxel-wise metrics, skeleton means and histogram widths (5th-95th percentile) were assessed before and after harmonization, as well as variance associated with gestational age at birth and scan. Before harmonization, large cohort differences were observed. Harmonization removed all voxel-wise differences from MD maps and all metric means and histogram widths, however small voxel-wise differences (

Early neuroimaging may provide a surrogate marker for brain development and outcome after preterm birth. Tract-Based Spatial Statistics (TBSS) is an advanced Diffusion Tensor Image (DTI) analysis technique that is sensitive to the effects of prematurity and may provide a quantitative marker for neuroprotection following perinatal brain injury or preterm birth. Here, we test the sensitivity of TBSS to detect diffuse microstructural differences in the developing white matter of preterm infants at term-equivalent age by modelling a 'treatment' effect as a global increase in fractional anisotropy (FA). As proof of concept we compare these simulations to a real effect of increasing age at scan. 3-Tesla, 15-direction diffusion tensor imaging (DTI) was acquired from 90 preterm infants at term-equivalent age. Datasets were randomly assigned to 'treated' or 'untreated' groups of increasing size and voxel-wise increases in FA were used to simulate global treatment effects of increasing magnitude in all 'treated' maps. 'Treated' and 'untreated' FA maps were compared using TBSS. Predictions from simulated data were then compared to exemplar TBSS group comparisons based on increasing postmenstrual age at scan. TBSS proved sensitive to global differences in FA within a clinically relevant range, even in relatively small group sizes, and simulated data were shown to predict well a true biological effect of increasing age on white matter development. These data confirm that TBSS is a sensitive tool for detecting global group-wise differences in FA in this population.

Background: Magnesium sulphate given to women immediately prior to very preterm birth protects the perinatal brain, so fewer babies die or develop cerebral palsy. How magnesium sulphate exerts these beneficial effects remains uncertain. The aim of the MagNUM Study was to assess the effect of exposure to antenatal magnesium sulphate on MRI measures of brain white matter microstructure at term equivalent age. Methods: Nested cohort study within the randomised Magnesium sulphate at 30 to

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.

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.

Background: The UK hosts some of the world’s longest-running longitudinal cohort studies, who 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’ (78% 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.

Methadone is used for medication-assisted treatment of heroin addiction during pregnancy. The neurodevelopmental outcome of children with prenatal methadone exposure can be sub-optimal. We tested the hypothesis that brain development is altered among newborn infants whose mothers were prescribed methadone.20 methadone-exposed neonates born after 37weeks' postmenstrual age (PMA) and 20 non-exposed controls underwent diffusion MRI at mean PMA of 39+2 and 41+1weeks, respectively. An age-optimized Tract-based Spatial Statistics (TBSS) pipeline was used to perform voxel-wise statistical comparison of fractional anisotropy (FA) data between exposed and non-exposed neonates.Methadone-exposed neonates had decreased FA within the centrum semiovale, inferior longitudinal fasciculi (ILF) and the internal and external capsules after adjustment for GA at MRI (p

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. Keywords: Morphometric similarity networks, Preterm, Developing brain, Brain age, Multi-modal data, MRI

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