Maternal diabetes and obesity are established risk factors for adverse offspring health. Emerging evidence suggests that these fetal programming effects vary by sex, yet it remains unclear whether these factors independently or interactively influence early brain development. This prospective study included 1,965 infants from six international cohorts. Infant MRI was used to derive subcortical volumes (thalamus, amygdala, hippocampus, pallidum, putamen, caudate). ComBat harmonization was applied. Multiple linear regression tested main and interaction effects of maternal obesity, maternal diabetes, and sex, controlling for covariates with false discovery rate (FDR) corrections. Of the sample, 46

Magnetic resonance imaging (MRI) is critical for neurodevelopmental research, however access to high-field (HF) systems in low- and middle-income countries is severely hindered by their cost. Ultra-low-field (ULF) systems mitigate such issues of access inequality, however their diminished signal-to-noise ratio limits their applicability for research and clinical use. Deep-learning approaches can enhance the quality of scans acquired at lower field strengths at no additional cost. For example, Convolutional neural networks (CNNs) fused with transformer modules have demonstrated a remarkable ability to capture both local information and long-range context. Unfortunately, the quadratic complexity of transformers leads to an undesirable trade-off between long-range sensitivity and local precision. We propose a hybrid CNN and state-space model (SSM) architecture featuring a novel 3D to 1D serialisation (GAMBAS), which learns long-range context without sacrificing spatial precision. We exhibit improved performance compared to other state-of-the-art medical image-to-image translation models.

The scarcity of epidemiological data on anaemia in low- and middle-income countries, coupled with contrasting approaches to the assessment of iron status with inflammation, represent critical research gaps. This study characterised the prevalence and profile of iron deficiency anaemia, including adjustment for inflammation, in mothers and infants from South Africa. Mother-child dyads (n = 394) were recruited (2021-2022) for the Khula birth cohort in Cape Town. Haematological metrics, iron metrics, and inflammatory biomarkers were obtained from mothers antenatally and 3-6 months postnatally, and infants 3-18 months postnatally. The extent to which inflammation impacted iron deficiency was assessed using two methods; Method A: higher serum ferritin thresholds for classifying iron status in participants with inflammation (World Health Organisation), Method B: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anaemia (BRINDA) regression which corrects serum ferritin based on inflammatory biomarker concentrations. Prevalence of maternal anaemia was 34.74% (107/308) in pregnancy and 22.50% (54/240) in mothers at 3-6 months after childbirth. Of their infants, 46.82% (125/267) and 48.10% (136/283) were anaemic by 6-12 months and 12-18 months, respectively. Using Method A, the prevalence of maternal iron deficiency (regardless of anaemia), increased from 18.35% (20/109) to 55.04% (60/109) in pregnancy, and from 11.97% (28/234) to 46.58% (109/234) postnatally. Similarly, using Method B, maternal iron deficiency prevalence increased to 38.53% (42/109) in pregnancy, and 25.21% (59/234) postnatally. In infants at 12-18 months, the prevalence of iron deficiency increased from 19.79% (19/96) to 31.25% (30/96) and 32.29% (31/96) using Methods A and B, respectively. Approximately half of anaemia cases in mothers antenatally (50%; 20/40) and postnatally (45.10%; 23/51), and infants at 12-18 months (55.56%; 10/18), were attributable to iron deficiency. This is one of the first studies reporting the extent to which iron deficiency anaemia may be underestimated if inflammation is unaccounted for in South African mothers and infants.

In the next two decades, Africa is projected to have one of the highest number of people with Alzheimer's disease and related dementias (ADRD) (Figure 1). Neuroimaging tools, particularly magnetic resonance imaging (MRI) and positron emission tomography (PET), are established diagnostic tools for characterizing ADRD. However, the use of these tools is unevenly distributed globally and acutely lacking in Africa, particularly in Sub-Saharan Africa. Because ADRD prevalence and risk factors vary across populations and geospatial lines, there is a growing need to develop neuroimaging capacity for dementia research in diverse populations to expand our understanding of its characteristics. Here, we highlight gaps in dementia imaging research globally, identify associated barriers to their use in Africa, and provide a perspective on opportunities to enable dementia neuroimaging research across Africa. We reviewed published data from literature and clinical trial databases for ongoing or past ADRD studies around the world with PET or MRI. We then estimated the number of sites, participants, and capacity (participants/site). We also used published data to estimate Africa's imaging infrastructure and personnel needs and costs. A total of 49 countries (∼25% of all countries in the world) account for the global ADRD neuroimaging research (Figure 2). On a regional level, Africa has the least number of ADRD study sites and participants who have/will have PET or MRI (Figure 2). In Africa, only 4 countries have conducted ADRD research using MRI and none have published research or reported ongoing clinical trials using PET. The challenges with acquiring and operating neuroimaging infrastructure including high costs of scanner and radiotracer production as well as shortage of skilled personnel are fundamental barriers to dementia imaging research in Africa. At minimum, $29,321,441,393 is required to equip Africa with the neuroimaging infrastructure and personnel to bridge the gap (Figure 3). Thus, we propose, 1) increased imaging infrastructure investment, especially in low-cost technologies, 2) optimization of existing clinical imaging systems for advanced imaging, 3) collaborative training of local personnel through upskilling programs and 4) establishment of regional and global partnerships. Together these actions can transform dementia imaging capacity in Africa.

This article examines how exposure to violence in childhood is linked to impaired cognitive functioning and academic performance. Children who reside in low- and middle-income countries (LMICs) are more likely to be exposed to violence yet their representation in published studies is often limited. Here, we conducted a systematic review to examine the evidence regarding the association between childhood violence exposure and cognitive outcomes assessed up to age 11 in children from LMICs. EMBASE, Medline, and PsychInfo were systematically searched to identify cross-sectional, case-control, or cohort studies published from inception to May 2023. All studies were assessed for risk of bias. We identified 17 studies that met our inclusion criteria, encompassing 27,643 children from 20 LMICs. Children were exposed to maltreatment, intimate partner violence, and war. Cognitive outcomes assessed included cognitive development (n = 9), executive functioning (n = 6), general intelligence (n = 2), language (n = 2), and memory (n = 1). A majority (71%) of the studies found a relationship between violence exposure and poor cognitive outcomes in childhood. Our findings suggest associations between different forms of violence and poor cognitive outcomes in children in LMICs. An increased investment in prevention is needed to tackle this human rights violation, and early interventions are important to ensure that LMIC children achieve their full potential. This is crucial in LMICs in which the burden of violence is high.

Abstract Background This study aimed to determine whether associations of antenatal maternal anaemia with smaller corpus callosum, caudate nucleus, and putamen volumes previously described in children at age 2–3 years persisted to age 6–7 years in the Drakenstein Child Health Study (DCHS). Methods This neuroimaging sub-study was nested within the DCHS, a South African population-based birth cohort. Pregnant women were enrolled (2012–2015) and mother–child dyads were followed prospectively. A sub-group of children had magnetic resonance imaging at 6–7 years of age (2018–2022). Mothers had haemoglobin measurements during pregnancy and a proportion of children were tested postnatally. Maternal anaemia (haemoglobin < 11 g/dL) and child anaemia were classified using WHO and local guidelines. Linear modeling was used to investigate associations between antenatal maternal anaemia status, maternal haemoglobin concentrations, and regional child brain volumes. Models included potential confounders and were conducted with and without child anaemia to assess the relative roles of antenatal versus postnatal anaemia. Results Overall, 157 children (Mean [SD] age of 75.54 [4.77] months; 84 [53.50%] male) were born to mothers with antenatal haemoglobin data. The prevalence of maternal anaemia during pregnancy was 31.85% (50/157). In adjusted models, maternal anaemia status was associated with smaller volumes of the total corpus callosum (adjusted percentage difference, − 6.77%; p = 0.003), left caudate nucleus (adjusted percentage difference, − 5.98%, p = 0.005), and right caudate nucleus (adjusted percentage difference, − 6.12%; p = 0.003). Continuous maternal haemoglobin was positively associated with total corpus callosum (β = 0.239 [CI 0.10 to 0.38]; p < 0.001) and caudate nucleus (β = 0.165 [CI 0.02 to 0.31]; p = 0.027) volumes. In a sub-group (n = 89) with child haemoglobin data (Mean [SD] age of 76.06 [4.84]), the prevalence of antenatal maternal anaemia and postnatal child anaemia was 38.20% (34/89) and 47.19% (42/89), respectively. There was no association between maternal and child anaemia (χ 2 = 0.799; p = 0.372), and child anaemia did not contribute to regional brain volume differences associated with maternal anaemia. Conclusions Associations between maternal anaemia and regional child brain volumes previously reported at 2–3 years of age were consistent and persisted to 6–7 years of age. Findings support the importance of optimising antenatal maternal health and reinforce these brain regions as a future research focus.

Objectives: The scarcity of epidemiological data on anaemia in low- and middle-income countries, coupled with poor characterisation of overlapping risk factors in high-risk settings and contrasting approaches to the assessment of iron status with inflammation, represent critical gaps to address. This study aimed to characterise the prevalence and profile of iron deficiency anaemia, including adjustment for inflammation, in pregnant and postpartum women, as well as infants from South Africa. Methods: Mother-child dyads (n=394) were recruited (2021-2022) for the Khula birth cohort study in Cape Town, South Africa. Haematological metrics (haemoglobin, mean corpuscular volume [MCV]), iron metrics (serum ferritin and soluble transferrin receptor [sTfR]), and inflammatory biomarkers (highly sensitive C-Reactive Protein [hsCRP]; Alpha-1 Acid Glycoprotein [AGP]) were obtained from mothers antenatally and postnatally, as well as from infants 3-18 months after birth. World Health Organisation (WHO) guidelines were used to classify anaemia and iron deficiency. The extent to which inflammation impacted iron deficiency was assessed using two methods: Method A: higher serum ferritin thresholds for classifying iron status in participants with inflammation (WHO), Method B: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anaemia (BRINDA) regression which corrects serum ferritin levels based on inflammatory biomarker concentrations. Results: Prevalence of anaemia was 34.74% (107/308) in pregnancy and 22.50% (54/240) in mothers at 3-6 months postpartum. Of their infants, 46.82% (125/267) and 48.10% (136/283) were anaemic at least once by 6-12 months and 12-18 months, respectively. When accounting for inflammation using Method A, the prevalence of maternal iron deficiency (regardless of anaemia), increased from 18.35% (20/109) to 55.04% (60/109) in pregnancy, and from 11.97% (28/234) to 46.58% (109/234) postnatally. Similarly, using Method B, the estimated prevalence of maternal iron deficiency increased to 38.53% (42/109) in pregnancy, and 25.21% (59/234) postnatally. In infants at 12-18 months, the prevalence of iron deficiency increased from 19.79% (19/96) to 31.25% (30/96) and 32.29% (31/96) using Methods A and B, respectively. Approximately half of anaemia cases in mothers antenatally (50%; 20/40) and postnatally (45.10%; 23/51), and infants at 12-18 months (55.56%; 10/18), were attributable to iron deficiency. However, there was little overlap in the estimated prevalence of microcytic anaemia (based on MCV) and iron deficiency anaemia (based on adjusted serum ferritin) in pregnant and postpartum mothers, as well as infants at 3-6 and 6-12 months. At these timepoints, microcytic anaemia underestimated the likely proportion of anaemia cases attributable to iron deficiency. Conclusion: This is one of the first studies to report the true prevalence of iron deficiency anaemia in South African mothers and infants, and the extent to which it may be underestimated if inflammation is not accounted for. Additionally, the results indicate that, while microcytic anaemia classification may be a valid proxy for iron deficiency anaemia in infants over 1 year of age, it seems less useful for pregnant and postpartum mothers and younger infants within the context of inflammation. Overall, the findings contribute to a global effort to understand the complex aetiology of iron deficiency anaemia, informing guidelines for optimised detection, prevention, and intervention in high-risk communities. Keywords: anaemia, iron deficiency, iron deficiency anaemia, inflammation, antenatal maternal health, child health, haemoglobin; mean corpuscular volume, serum ferritin, soluble transferrin receptor, highly sensitive C-Reactive Protein, Alpha-1 Acid Glycoprotein ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The Khula birth cohort was supported by the Wellcome Leap 1kD programme (The First 1000 Days; 222076/Z/20/Z). J.E. Ringshaw is supported by a Wellcome Trust International Training Fellowship (224287/Z/21/Z). The anaemia analyses were funded by the Bill and Melinda Gates Foundation (INV-023509) for K.A. Donald. S.C.R. Williams is supported by the Bill and Melinda Gates Foundation (INV-047888) and the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre (BRC). D.J. Stein is supported by the South African Medical research Council (SA-MRC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Human Research Ethics Committee of the University of Cape Town gave ethical approval for this work (reference 666/2021). All mothers provided written informed consent for cohort participation at Khula enrolment, and for their children to participate in study-specific procedures across timepoints. Given the longitudinal nature of the cohort, study consent was obtained from mothers on an annual basis. While specified, approved authors had access to identifiable participant information during data collection, only non-identifiable data was captured and analysed. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The de-identified data that support the findings of this study are available upon reasonable request from the corresponding author as per Khula cohort guidelines.

Owing to the high cost of modern magnetic resonance imaging (MRI) systems, their use in clinical care and neurodevelopmental research is limited to hospitals and universities in high income countries. Ultra-low-field systems with significantly lower scanning costs present a promising avenue towards global MRI accessibility; however, their reduced SNR compared to 1.5 or 3 T systems limits their applicability for research and clinical use. In this paper, we describe a deep learning-based super-resolution approach to generate high-resolution isotropic T2-weighted scans from low-resolution paediatric input scans. We train a 'multi-orientation U-Net', which uses multiple low-resolution anisotropic images acquired in orthogonal orientations to construct a super-resolved output. Our approach exhibits improved quality of outputs compared to current state-of-the-art methods for super-resolution of ultra-low-field scans in paediatric populations. Crucially for paediatric development, our approach improves reconstruction of deep brain structures with the greatest improvement in volume estimates of the caudate, where our model improves upon the state-of-the-art in: linear correlation (r = 0.94 vs. 0.84 using existing methods), exact agreement (Lin's concordance correlation = 0.94 vs. 0.80) and mean error (0.05 cm3 vs. 0.36 cm3). Our research serves as proof-of-principle of the viability of training deep-learning based super-resolution models for use in neurodevelopmental research and presents the first model trained exclusively on paired ultra-low-field and high-field data from infants.

Objective: Evidence suggests that prenatal environmental phenol exposures negatively impact child neurodevelopment, however there is little research on the effects of mixtures of multiple phenol exposures. We analyzed associations between prenatal exposure to phenol mixtures and cognitive neurodevelopment at two years of age among 545 mother-child pairs from the South African Drakenstein Child Health Study. Material and methods: We measured maternal urine environmental phenol concentrations once during the second trimester of pregnancy. We used the Bayley Scales of Infant and Toddler Development III to assess cognitive development at two years of age. We used linear regression models adjusted for maternal HIV status, maternal age, ethnicity, prenatal tobacco exposure, child sex, and socioeconomic status (SES) to examine individual associations. We compared four mixture methods: self- organizing maps (SOM), Bayesian kernel machine regression (BKMR), quantile-based G-computation (qgcomp) and weighted quantile sum (WQS) regression to explore joint effects of the exposure mixture. We assessed effect modification by SES, sex, prenatal tobacco exposure, and ethnicity. Results: Across all methods, we found no association between individual phenol exposures or the joint exposure mixture with the cognitive score. Prenatal tobacco exposure modified the association between pentachlorophenol (PCP) and cognitive neurodevelopment (interaction p-value = 0.012), with higher PCP concentrations associated with lower cognitive scores among non-smokers (beta =- 2.17; 95% CI:-3.83,-0.51). Sex modified the association between bisphenol A (BPA) and cognitive neurodevelopment (interaction p-value = 0.021), with males having a significant adverse association (beta =-1.39; 95% CI:-2.54,-0.23). SES modified the association between bisphenol S (BPS) and cognitive neurodevelopment (interaction p-value = 0.003), with individuals of moderate-high SES having a significant adverse association (beta =-1.84; 95% CI:-3.26, 0.06) Conclusion: While we found no main effects of prenatal phenol exposure on cognitive neurodevelopment, the associations with PCP, BPA, and BPS were more pronounced among certain subgroups.

Normative brain growth charts in early life hold great promise for furthering basic and clinical science. We leverage the rapid, substantial development of visual cortex function that is indexed by visual-evoked potentials (VEP) in electroencephalography to create longitudinal normative growth curves of task-related brain function with 1374 observations contributed by 802 infants (57 to 579 days old) from South Africa, Brazil, and the United States. Site-specific models were cross-validated and showed excellent fits to other sites' samples, demonstrating functional growth curves generalize across contexts robustly. Deviations from the normative growth models associated with early environmental and behavioral measures such as prenatal exposures and postnatal cognition. These findings demonstrate the utility of using functional growth charts to understand and potentially act on individual neurodevelopmental trajectories. VEP brain function growth charts represent a new direction for EEG research to serve public health and early identification efforts to support healthy brain development globally. ### Competing Interest Statement The authors have declared no competing interest.

The combined impact of prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) on white-matter integrity in pre-adolescence is poorly understood. We aimed to explore white-matter integrity in children aged 8- to 12-years with PAE and/or PTE versus those without (controls, CON). Here, 410 children (CON: n = 84; PAE: n = 94; PTE: n = 67; PAE + PTE: n = 165) underwent diffusion tensor MRI as part of the Safe Passage Study, a cohort based in Cape Town, South Africa. Linear regression modeling was used to investigate the main and interaction effects of PAE and PTE. There were disordinal PAE × PTE interactions on right-cerebral-peduncle mean, axial, and radial diffusivity: Individuals with PAE and PTE had higher mean and axial diffusivity than those with either exposure on its own, but similar to those with neither. In children with PAE, there were associations with altered axial diffusivity among those exposed during the first trimester and mean, axial, and radial diffusivity in those exposed during the second trimester in commissural, association, and projection tracts. Further, there were PTE associations with fractional anisotropy and radial diffusivity in projection tracts among those exposed mainly during the second trimester. These results support previous research in children with PAE and add to the PTE literature, highlighting potentially lasting impact on axonal and myelin microstructural development, which are important for motor, sensory, cognitive, and behavioral functions. Our results suggest sensitivity to the timing of exposure of PAE and PTE, particularly during the first and second trimesters of pregnancy.

Early exposure to violence can elicit a toxic-stress response in children. However, not all exposures to violence exert the same negative impact. This study aimed to develop a bifactor model of childhood adversity by integrating two established measures, the Child Exposure to Community Violence questionnaire and the Pediatric Emotional Distress Scale. The Adversity Exposure-Response Model was created using caregiver-proxy report data from children aged 3.5 and 4.5 years ( N = 801) in a South African birth cohort from two high-risk, low-income communities. A bifactor model best fit the data, with the newly formed composite serving as a statistically significant predictor of exposure to traumatic events (β = .34, p < .001). As predicted, this bifactor model provided a holistic approach to childhood adversity, challenging the assumption that all adverse events result in uniformly negative outcomes. It offers a comprehensive screening tool to identify at-risk children early, facilitating targeted interventions in high-risk settings.

Fetal, infant, and toddler (FIT) neuroimaging researchers study early brain development to gain insights into neurodevelopmental processes and identify early markers of neurobiological vulnerabilities to target for intervention. However, the field has historically excluded people from global majority countries and from marginalized communities in FIT neuroimaging research. Inclusive and representative samples are essential for generalizing findings across neuroimaging modalities, such as magnetic resonance imaging, magnetoencephalography, electroencephalography, functional near-infrared spectroscopy, and cranial ultrasonography. These FIT neuroimaging techniques pose unique and overlapping challenges to equitable representation in research through sampling bias, technical constraints, limited accessibility, and insufficient resources. The present article adds to the conversation around the need to improve inclusivity by highlighting modality-specific historical and current obstacles and ongoing initiatives. We conclude by discussing tangible solutions that transcend individual modalities, ultimately providing recommendations to promote equitable FIT neuroscience.

ABSTRACT Maternal capacity to adhere to recommended infant and young child feeding (IYCF) practices may be influenced by psychosocial factors. However, research examining associations between psychosocial factors and IYCF practices, and in particular complementary feeding indicators, is limited. As part of the Khula birth cohort study, we aimed to investigate associations between maternal depression, exposure to intimate partner violence (IPV), social support and stimulating home environments with IYCF practices among mother‐child dyads in Malawi ( n = 153) and South Africa ( n = 255). When children were 10–16 months of age, mothers completed a series of psychosocial and child diet questionnaires. Regression modelling assessed associations between maternal psychosocial measures and IYCF indicators, adjusting for maternal age, education, marital status and household socioeconomic status. IYCF practices were suboptimal in both settings, with 50%–54% meeting the minimum dietary diversity (MDD), 67%–73% the minimum meal frequency (MMF) and 39%–45% the minimum acceptable diet (MAD) indicators. In South Africa, mothers exposed to IPV in the previous 12 months were less likely to meet the MDD and MAD recommendations (MDD: OR 0.38, 95% CI: 0.19, 0.75; p = 0.006; MAD: OR 0.41, 95% CI: 0.20, 0.85; p = 0.02). There was a significant positive association between stimulation (i.e., more books/toys/play activities) and dietary diversity scores in South Africa. In adjusted analyses, maternal depression and social support were not significantly associated with IYCF indicators in either setting. IYCF programmes may benefit from supporting maternal psychosocial wellbeing and integrating nurturing care to improve children's dietary intakes, growth and development.

Prenatal alcohol exposure (PAE) is associated with various neurological, behavioral and cognitive deficits, including reading and language. Previous studies have demonstrated altered white matter in children and adolescents with PAE and associations with reading and language performance in children aged 3 years and older. However, little research has focused on the toddler years, despite this being a critical period for behavioral and neural development. We aimed to determine associations between structural brain connectivity and early language skills in toddlers, in the context of PAE. Eighty-eight toddlers (2-3 yr, 56 males), 23 of whom had PAE, underwent a diffusion MRI scan in Cape Town, South Africa, with language skills assessed using the Expressive and Receptive Communication subtests from the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III). Diffusion scans were preprocessed to create a structural network of regions associated with language skills using graph theory analysis. Linear regression models were used to examine moderation effects of PAE on structural network properties and language skills. Toddlers with PAE had higher structural connectivity in language networks than unexposed children. PAE moderated the relationship between structural network properties and Expressive Communication scores. None of the effects survived correction for multiple comparisons. Our findings show weak moderation effects of PAE on structural language network properties and language skills. Our study sheds light on the structural connectivity correlates of early language skills in an understudied population during a critical neurodevelopmental period, laying the foundation for future research.

Microstates, brief instances of distinct spatial topographies measured with electroencephalography (EEG), offer a novel approach to studying whole-brain network dynamics at a sub-second scale. While emerging literature is leveraging microstate dynamics in adults and children to understand mature largescale network function, the developmental trajectories of these networks during their rapid construction in infancy remain poorly understood. Magnetic resonance approaches have revealed much about largescale networks in sleep, but very little is known about functional network dynamics in awake, behaving infants. Using longitudinal resting-state EEG from 854 infants across 2 diverse cohorts, we identified conserved emergence of various network configurations (classes A-G) during the first 2 years of life via data-driven clustering analyses. Significant longitudinal changes included more frequent and rapid transitions between microstate classes, particularly in early infancy. Sensory microstates showed consistent development across cohorts, while higher-order cognitive microstates demonstrated context-specific trends. These findings reveal novel insights into the functional development and organization of largescale brain networks during this period of substantial development.

Characterizing the dynamics of microbial community succession in the infant gut microbiome is crucial for understanding child health and development, but no normative model currently exists. Here, we estimate child age using gut microbial taxonomic relative abundances from metagenomes, with high temporal resolution (±3 months) for the first 1.5 years of life. Using 3154 samples from 1827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.56 months. We identified key taxonomic predictors of age, including declines in Bifidobacterium spp. and increases in Faecalibacterium prausnitzii and Lachnospiraceae. Microbial succession patterns are conserved across infants from diverse human populations, suggesting universal developmental trajectories. Functional analysis confirmed trends in key microbial genes involved in feeding transitions and dietary exposures. This model provides a normative benchmark of “microbiome age” for assessing early gut maturation that may be used alongside other measures of child development. Here, the authors perform a global analysis of over 3000 infant gut samples revealing a universal pattern of microbial changes over the first 1.5 years, with declines in Bifidobacterium and increases in Faecalibacterium, providing a standard for early gut development.

Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 16 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 12,877; Npooled neuroimaging = 10,899; Npooled combined = 6074). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.

High-field magnetic resonance imaging to explore brain structure and function remains limited to high-resource settings. Novel, low-field (<0.1 T) imaging offers a more cost-effective/accessible alternative. However, the validity of low-field data at spatial resolutions relevant to research and clinic (vertex-level) remains unclear. Hence, we examine paired high-field (reference) and low-field (single/multi-orientation scans processed through established/novel pipelines) data (12 children [10-12 yrs] in a low- and middle-income country [LMIC]). We assess high-field/low-field correspondence between vertex-level measures of cortical volume, surface area, and cortical thickness; and compare analytic strategies. High/low-field images show weak-to-moderate global correspondence (cortical volume, surface area: Pearson's r ≤ 0.6, cortical thickness r ≤ 0.3), and weak-to-very strong local correspondence (r ≤ 0.99). Greatest correspondence is achieved with multi-orientation images and a pipeline adjusted for low-resolution images (recon-all-clinical); or image enhancement (SynthSR) plus standard processing (FastSurfer); but agreement varies across brain based on input, analytic strategy, and neuroanatomical feature. We provide an application to interactively explore our results. Thus, low-field imaging can provide reliable, high-resolution estimates of cortical volume and surface area, but not cortical thickness; and analytic approaches should be selected based on multiple considerations. Once validated, this research may help deploy low-field imaging to aid research/evidence-based clinical work in high- and low-resource settings, including LMIC.