Increased Brain Age Gap Estimate (BrainAGE) in Young Adults After Premature Birth

Complications of Preterm Birth-The Importance of Care for the Outcome: A Narrative Review

Preterm-born children are susceptible to problems of adaptation in the early neonatal period, as well as the emergence of consequences due to the immaturity of the respiratory, cardiovascular, and especially cerebrovascular systems. The authors searched PubMed, Scopus, the Cochrane Library, and Web of Science for articles that were available in their entirety and published in English between 1990 and 2024 in peer-reviewed journals using keywords relevant to the manuscript topic. Analyzing the requested studies and manuscripts, adequate articles describing the stated problem were used. The last trimester of pregnancy is the most important period in brain development. Brain growth is at its most intense, and nerve cells are created, multiply, and migrate, creating numerous connections between them and receptors. During this period, the baby is protected from the influence of external environmental factors. When a baby is born, it leaves its protected environment and very often requires intensive treatment to survive. In these circumstances, the immature nervous system, which is in a sensitive stage of development, is overloaded with numerous external stimuli, continuous light, noise, inappropriate positioning, and repeated painful reactions due to necessary diagnostic and therapeutic procedures and the unavoidable absence of the mother and the family, which cause stress that threatens proper programmed development. Minimally invasive therapeutic procedures and the presence of parents during hospitalization play a significant role in reducing the consequences for a premature child.

Cortical growth from infancy to adolescence in preterm and term-born children

Early life experiences can exert a significant influence on cortical and cognitive development. Very preterm birth exposes infants to several adverse environmental factors during hospital admission, which affect cortical architecture. However, the subsequent consequence of very preterm birth on cortical growth from infancy to adolescence has never been defined; despite knowledge of critical periods during childhood for establishment of cortical networks. Our aims were to: chart typical longitudinal cortical development and sex differences in cortical development from birth to adolescence in healthy term-born children; estimate differences in cortical development between children born at term and very preterm; and estimate differences in cortical development between children with normal and impaired cognition in adolescence. This longitudinal cohort study included children born at term (≥37 weeks' gestation) and very preterm (<30 weeks' gestation) with MRI scans at ages 0, 7 and 13 years (n = 66 term-born participants comprising 34 with one scan, 18 with two scans and 14 with three scans; n = 201 very preterm participants comprising 56 with one scan, 88 with two scans and 57 with three scans). Cognitive assessments were performed at age 13 years. Cortical surface reconstruction and parcellation were performed with state-of-the-art, equivalent MRI analysis pipelines for all time points, resulting in longitudinal cortical volume, surface area and thickness measurements for 62 cortical regions. Developmental trajectories for each region were modelled in term-born children, contrasted between children born at term and very preterm, and contrasted between all children with normal and impaired cognition. In typically developing term-born children, we documented anticipated patterns of rapidly increasing cortical volume, area and thickness in early childhood, followed by more subtle changes in later childhood, with smaller cortical size in females than males. In contrast, children born very preterm exhibited increasingly reduced cortical volumes, relative to term-born children, particularly during ages 0-7 years in temporal cortical regions. This reduction in cortical volume in children born very preterm was largely driven by increasingly reduced cortical thickness rather than area. This resulted in amplified cortical volume and thickness reductions by age 13 years in individuals born very preterm. Alterations in cortical thickness development were found in children with impaired language and memory. This study shows that the neurobiological impact of very preterm birth on cortical growth is amplified from infancy to adolescence. These data further inform the long-lasting impact on cortical development from very preterm birth, providing broader insights into neurodevelopmental consequences of early life experiences.

BrainAGE, brain health, and mental disorders: A systematic review

The imaging-based method of brainAGE aims to characterize an individual's vulnerability to age-related brain changes. The present study systematically reviewed brainAGE findings in neuropsychiatric conditions and discussed the potential of brainAGE as a marker for biological age. A systematic PubMed search (from inception to March 6th, 2023) identified 273 articles. The 30 included studies compared brainAGE between neuropsychiatric and healthy groups (n≥50). We presented results qualitatively and adapted a bias risk assessment questionnaire. The imaging modalities, design, and input features varied considerably between studies. While the studies found higher brainAGE in neuropsychiatric conditions (11 mild cognitive impairment/ dementia, 11 schizophrenia spectrum/ other psychotic and bipolar disorder, six depression/ anxiety, two multiple groups), the associations with clinical characteristics were mixed. While brainAGE is sensitive to group differences, limitations include the lack of diverse training samples, multi-modal studies, and external validation. Only a few studies obtained longitudinal data, and all have used algorithms built solely to predict chronological age. These limitations impede the validity of brainAGE as a biological age marker.

A randomized-controlled trial of parent-administered interventions to improve short-term motor outcomes in hospitalized very low birthweight infants

BACKGROUND

Premature infants are at increased risk for cerebral palsy (CP). Early interventions with a motor focus and administered by parents may improve motor outcomes.

AIMS

Secondary study evaluating the short-term motor outcomes and risk for CP in very low birthweight (VLBW) infants randomized to multimodal interventions with a motor focus provided by parents versus usual care.

STUDY DESIGN

Randomized controlled trial (intervention vs. usual care (control group)).

SUBJECTS

Infants (<32 weeks' gestational age (GA) and/or <1500 grams birthweight) born between March 2019 and October 2020.

OUTCOME MEASURES

Short-term motor outcomes and risk for CP was evaluated using the Hammersmith Infant Neurological Evaluation (HINE, primary motor outcome), the General Movement Assessment (GMA) and the Test of Infant Motor Performance (TIMP) at 3 months' postmenstrual age (PMA).

RESULTS

70 participants were enrolled (GA 28.3±2.7 weeks, birthweight 1139.2±376.6 grams, 64.3% male). The in-person follow-up rate was 73%, lower than expected, in part due to COVID-19 restrictions, resulting in 25 infants (intervention) and 26 infants (control) with outcome data available for analysis. There was not a significant difference in the HINE, GMA or TIMP at 3 months' PMA between groups.

CONCLUSION

Multimodal interventions with a motor focus and provided by parents need further investigation to determine if they can improve short-term motor outcomes in VLBW infants. These interventions are evidence-based and the evaluation of broader implementation into routine care is also needed.

Lower cortical thickness and increased brain aging in adults with cocaine use disorder

Background

Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear.

Methods

Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses.

Results

We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration.

Conclusion

Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.

Altered gray-to-white matter tissue contrast in preterm-born adults

AIMS

To investigate cortical organization in brain magnetic resonance imaging (MRI) of preterm-born adults using percent contrast of gray-to-white matter signal intensities (GWPC), which is an in vivo proxy measure for cortical microstructure.

METHODS

Using structural MRI, we analyzed GWPC at different percentile fractions across the cortex (0%, 10%, 20%, 30%, 40%, 50%, and 60%) in a large and prospectively collected cohort of 86 very preterm-born (<32 weeks of gestation and/or birth weight <1500 g, VP/VLBW) adults and 103 full-term controls at 26 years of age. Cognitive performance was assessed by full-scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale.

RESULTS

GWPC was significantly decreased in VP/VLBW adults in frontal, parietal, and temporal associative cortices, predominantly in the right hemisphere. Differences were pronounced at 20%, 30%, and 40%, hence, in middle cortical layers. GWPC was significantly increased in right paracentral lobule in VP/VLBW adults. GWPC in frontal and temporal cortices was positively correlated with birth weight, and negatively with duration of ventilation (p < 0.05). Furthermore, GWPC in right paracentral lobule was negatively correlated with IQ (p < 0.05).

CONCLUSIONS

Widespread aberrant gray-to-white matter contrast suggests lastingly altered cortical microstructure after preterm birth, mainly in middle cortical layers, with differential effects on associative and primary cortices.

Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction Models

Brain age is an estimate of chronological age obtained from T1-weighted magnetic resonance images (T1w MRI) and represents a simple diagnostic biomarker of brain ageing and associated diseases. While the current best accuracy of brain age predictions on T1w MRIs of healthy subjects ranges from two to three years, comparing results from different studies is challenging due to differences in the datasets, T1w preprocessing pipelines, and performance metrics used. This paper investigates the impact of T1w image preprocessing on the performance of four deep learning brain age models presented in recent literature. Four preprocessing pipelines were evaluated, differing in terms of registration, grayscale correction, and software implementation. The results showed that the choice of software or preprocessing steps can significantly affect the prediction error, with a maximum increase of 0.7 years in mean absolute error (MAE) for the same model and dataset. While grayscale correction had no significant impact on MAE, the affine registration, compared to the rigid registration of T1w images to brain atlas was shown to statistically significantly improve MAE. Models trained on 3D images with isotropic 1 mm3 resolution exhibited less sensitivity to the T1w preprocessing variations compared to 2D models or those trained on downsampled 3D images. Some proved invariant to the preprocessing pipeline, however only after offset correction. Our findings generally indicate that extensive T1w preprocessing enhances the MAE, especially when applied to a new dataset. This runs counter to prevailing research literature which suggests that models trained on minimally preprocessed T1w scans are better poised for age predictions on MRIs from unseen scanners. Regardless of model or T1w preprocessing used, we show that to enable generalization of model's performance on a new dataset with either the same or different T1w preprocessing than the one applied in model training, some form of offset correction should be applied.

Long-lasting effects of very preterm birth on brain structure in adulthood: A systematic review and meta-analysis

Early life experiences, such as very preterm (VP) birth, can affect brain and cognitive development. Several prior studies investigated brain structure in adults born VP; synthesising these studies may help to provide a clearer understanding of long-term effects of VP birth on the brain. We systematically searched Medline and Embase for articles that investigated brain structure using MRI in adulthood in individuals born VP (<32 weeks' gestation) or with very low birth weight (VLBW; <1500 g), and controls born at term or with normal birth weight. In total, 77 studies met the review inclusion criteria, of which 28 studies were eligible for meta-analyses, including data from up to 797 VP/VLBW participants and 518 controls, aged 18-33 years. VP/VLBW adults exhibited volumetric, morphologic and microstructural alterations in subcortical and temporal cortical regions compared with controls, with pooled standardised mean differences up to - 1.0 (95% confidence interval: -1.2, -0.8). This study suggests there is a persisting neurological impact of VP birth, which may provide developmental neurobiological insights for adult cognition in high-risk populations.

Association of Maternal Depression During Pregnancy and Recent Stress With Brain Age Among Adult Offspring

IMPORTANCE

Maternal mental health problems during pregnancy are associated with altered neurodevelopment in offspring, but the long-term relationship between these prenatal risk factors and offspring brain structure in adulthood remains incompletely understood due to a paucity of longitudinal studies.

OBJECTIVE

To evaluate the association between exposure to maternal depression in utero and offspring brain age in the third decade of life, and to evaluate recent stressful life events as potential moderators of this association.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study examined the 30-year follow-up of a Czech prenatal birth cohort with a within-participant design neuroimaging component in young adulthood conducted from 1991 to 2022. Participants from the European Longitudinal Study of Pregnancy and Childhood prenatal birth cohort were recruited for 2 magnetic resonance imaging (MRI) follow-ups, one between ages 23 and 24 years (early 20s) and another between ages 28 and 30 years (late 20s).

EXPOSURES

Maternal depression during pregnancy; stressful life events in the past year experienced by the young adult offspring.

MAIN OUTCOMES AND MEASURES

Gap between estimated neuroanatomical vs chronological age at MRI scan (brain age gap estimation [BrainAGE]) calculated once in participants' early 20s and once in their late 20s, and pace of aging calculated as the differences between BrainAGE at the 2 MRI sessions in young adulthood.

RESULTS

A total of 260 individuals participated in the second neuroimaging follow-up (mean [SD] age, 29.5 [0.6] years; 135 [52%] male); MRI data for both time points and a history of maternal depression were available for 110 participants (mean [SD] age, 29.3 [0.6] years; 56 [51%] male). BrainAGE in participants' early 20s was correlated with BrainAGE in their late 20s (r = 0.7, P < .001), and a previously observed association between maternal depression during pregnancy and BrainAGE in their early 20s persisted in their late 20s (adjusted R2 = 0.04; P = .04). However, no association emerged between maternal depression during pregnancy and the pace of aging between the 2 MRI sessions. The stability of the associations between maternal depression during pregnancy and BrainAGE was also supported by the lack of interactions with recent stress. In contrast, more recent stress was associated with greater pace of aging between the 2 MRI sessions, independent of maternal depression (adjusted R2 = 0.09; P = .01).

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that maternal depression and recent stress may have independent associations with brain age and the pace of aging, respectively, in young adulthood. Prevention and treatment of depression in pregnant mothers may have long-term implications for offspring brain development.

Aberrant allometric scaling of cortical folding in preterm-born adults

A universal allometric scaling law has been proposed to describe cortical folding of the mammalian brain as a function of the product of cortical surface area and the square root of cortical thickness across different mammalian species, including humans. Since these cortical properties are vulnerable to developmental disturbances caused by preterm birth in humans and since these alterations are related to cognitive impairments, we tested (i) whether cortical folding in preterm-born adults follows this cortical scaling law and (ii) the functional relevance of potential scaling aberrances. We analysed the cortical scaling relationship in a large and prospectively collected cohort of 91 very premature-born adults (<32 weeks of gestation and/or birthweight <1500 g, very preterm and/or very low birth weight) and 105 full-term controls at 26 years of age based on the total surface area, exposed surface area and average cortical thickness measured with structural magnetic resonance imaging and surface-based morphometry. We found that the slope of the log-transformed cortical scaling relationship was significantly altered in adults (very preterm and/or very low birth weight: 1.24, full-term: 1.14, P = 0.018). More specifically, the slope was significantly altered in male adults (very preterm and/or very low birth weight: 1.24, full-term: 1.00, P = 0.031), while there was no significant difference in the slope of female adults (very preterm and/or very low birth weight: 1.27, full-term: 1.12, P = 0.225). Furthermore, offset was significantly lower compared with full-term controls in both male (very preterm and/or very low birth weight: -0.546, full-term: -0.538, P = 0.001) and female adults (very preterm and/or very low birth weight: -0.545, full-term: -0.538, P = 0.023), indicating a systematic shift of the regression line after preterm birth. Gestational age had a significant effect on the slope in very preterm and/or very low birth weight adults and more specifically in male very preterm and/or very low birth weight adults, indicating that the difference in slope is specifically related to preterm birth. The shape or tension term of the scaling law had no significant effect on cognitive performance, while the size of the cortex did. Results demonstrate altered scaling of cortical surface and cortical thickness in very premature-born adults. Data suggest altered mechanical forces acting on the cortex after preterm birth.

An individual-level weighted artificial neural network method to improve the systematic bias in BrainAGE analysis

BrainAGE is a commonly used machine learning technique to measure the accelerated/delayed development pattern of human brain structure/function with neuropsychiatric disorders. However, recent studies have shown a systematic bias ("regression toward mean" effect) in the BrainAGE method, which indicates that the prediction error is not uniformly distributed across Chronological Ages: for the older individuals, the Brain Ages would be under-estimated but would be over-estimated for the younger individuals. In the present study, we propose an individual-level weighted artificial neural network method and apply it to simulation datasets (containing 5000 simulated subjects) and a real dataset (containing 135 subjects). Results show that compared with traditional machine learning methods, the individual-level weighted strategy can significantly reduce the "regression toward mean" effect, while the prediction performance can achieve the comparable level with traditional machine learning methods. Further analysis indicates that the sigmoid active function for artificial neural network shows better performance than the relu active function. The present study provides a novel strategy to reduce the "regression toward mean" effect of BrainAGE analysis, which is helpful to improve accuracy in exploring the atypical brain structure/function development pattern of neuropsychiatric disorders.

Neuroimaging-Based Brain Age Estimation: A Promising Personalized Biomarker in Neuropsychiatry

It is now possible to estimate an individual's brain age via brain scans and machine-learning models. This validated technique has opened up new avenues for addressing clinical questions in neurology, and, in this review, we summarize the many clinical applications of brain-age estimation in neuropsychiatry and general populations. We first provide an introduction to typical neuroimaging modalities, feature extraction methods, and machine-learning models that have been used to develop a brain-age estimation framework. We then focus on the significant findings of the brain-age estimation technique in the field of neuropsychiatry as well as the usefulness of the technique for addressing clinical questions in neuropsychiatry. These applications may contribute to more timely and targeted neuropsychiatric therapies. Last, we discuss the practical problems and challenges described in the literature and suggest some future research directions.

Of differing methods, disputed estimates and discordant interpretations: the meta-analytical multiverse of brain volume and IQ associations

Brain size and IQ are positively correlated. However, multiple meta-analyses have led to considerable differences in summary effect estimations, thus failing to provide a plausible effect estimate. Here we aim at resolving this issue by providing the largest meta-analysis and systematic review so far of the brain volume and IQ association (86 studies; 454 effect sizes from k = 194 independent samples; N = 26 000+) in three cognitive ability domains (full-scale, verbal, performance IQ). By means of competing meta-analytical approaches as well as combinatorial and specification curve analyses, we show that most reasonable estimates for the brain size and IQ link yield r-values in the mid-0.20s, with the most extreme specifications yielding rs of 0.10 and 0.37. Summary effects appeared to be somewhat inflated due to selective reporting, and cross-temporally decreasing effect sizes indicated a confounding decline effect, with three quarters of the summary effect estimations according to any reasonable specification not exceeding r = 0.26, thus contrasting effect sizes were observed in some prior related, but individual, meta-analytical specifications. Brain size and IQ associations yielded r = 0.24, with the strongest effects observed for more g-loaded tests and in healthy samples that generalize across participant sex and age bands.

Preterm Delivery: Microbial Dysbiosis, Gut Inflammation and Hyperpermeability

Preterm birth is one of the main health problems encountered in the neonatal period, especially because it is also the first cause of death in the critical 1st month of life and the second in children under 5 years of age. Not only preterm birth entails short term health risks due to low weight and underdeveloped organs, but also increases the risk of suffering from non-transmissible diseases in the long term. To date, it is known that medical conditions and lifestyle factors could increase the risk of preterm birth, but the molecular mechanisms that control this process remain unclear. Luteolysis, increased inflammation or oxidative stress have been described as possible triggers for preterm birth and, in some cases, the cause of dysbiosis in preterm neonates. Several murine models have been developed to shed light into the mechanistic of preterm birth but, for the most part, are inflammation-based labor induction models and the offspring health readouts are mainly limited to survival and weight. Using a set of SWISS-CD1 mice born prematurely we analyzed inflammation and gut permeability parameters compared with term pups at weaning age. Overall, preterm mice presented higher systemic inflammation and gastrointestinal tract permeability. In this perspective article, we discuss the recent discoveries on preterm birth and the necessity of non-inflammatory murine models to really understand these phenotypes and be able to design strategies to prevent the sequels of this traumatic event in neonates.

A feasibility randomized controlled trial of a NICU rehabilitation program for very low birth weight infants

Motor disability is common in children born preterm. Interventions focusing on environmental enrichment and emotional connection can positively impact outcomes. The NICU-based rehabilitation (NeoRehab) program consists of evidence-based interventions provided by a parent in addition to usual care. The program combines positive sensory experiences (vocal soothing, scent exchange, comforting touch, skin-to-skin care) as well as motor training (massage and physical therapy) in a gestational age (GA) appropriate fashion. To investigate the acceptability, feasibility and fidelity of the NeoRehab program in very low birthweight (VLBW) infants. All interventions were provided by parents in addition to usual care. Infants (≤ 32 weeks' GA and/or ≤ 1500 g birthweight) were enrolled in a randomized controlled trial comparing NeoRehab to usual care (03/2019-10/2020). The a priori dosing goal was for interventions to be performed 5 days/week. The primary outcomes were the acceptability, feasibility and fidelity of the NeoRehab program. 36 participants were randomized to the intervention group and 34 allocated to usual care. The recruitment rate was 71% and retention rate 98%. None of the interventions met the 5 days per week pre-established goal. 97% of participants documented performing a combination of interventions at least 3 times per week. The NeoRehab program was well received and acceptable to parents of VLBW infants. Programs that place a high demand on parents (5 days per week) are not feasible and goals of intervention at least 3 times per week appear to be feasible in the context of the United States. Parent-provided motor interventions were most challenging to parents and alternative strategies should be considered in future studies. Further studies are needed to evaluate the relationship between intervention dosing on long term motor outcomes.

Linking Brain Age Gap to Mental and Physical Health in the Berlin Aging Study II

From a biological perspective, humans differ in the speed they age, and this may manifest in both mental and physical health disparities. The discrepancy between an individual's biological and chronological age of the brain ("brain age gap") can be assessed by applying machine learning techniques to Magnetic Resonance Imaging (MRI) data. Here, we examined the links between brain age gap and a broad range of cognitive, affective, socioeconomic, lifestyle, and physical health variables in up to 335 adults of the Berlin Aging Study II. Brain age gap was assessed using a validated prediction model that we previously trained on MRI scans of 32,634 UK Biobank individuals. Our statistical analyses revealed overall stronger evidence for a link between higher brain age gap and less favorable health characteristics than expected under the null hypothesis of no effect, with 80% of the tested associations showing hypothesis-consistent effect directions and 23% reaching nominal significance. The most compelling support was observed for a cluster covering both cognitive performance variables (episodic memory, working memory, fluid intelligence, digit symbol substitution test) and socioeconomic variables (years of education and household income). Furthermore, we observed higher brain age gap to be associated with heavy episodic drinking, higher blood pressure, and higher blood glucose. In sum, our results point toward multifaceted links between brain age gap and human health. Understanding differences in biological brain aging may therefore have broad implications for future informed interventions to preserve mental and physical health in old age.

Alzheimer resemblance atrophy index, BrainAGE, and normal pressure hydrocephalus score in the prediction of subtle cognitive decline: added value compared to existing MR imaging markers

OBJECTIVES

Established visual brain MRI markers for dementia include hippocampal atrophy (mesio-temporal atrophy MTA), white matter lesions (Fazekas score), and number of cerebral microbleeds (CMBs). We assessed whether novel quantitative, artificial intelligence (AI)-based volumetric scores provide additional value in predicting subsequent cognitive decline in elderly controls.

METHODS

A prospective study including 80 individuals (46 females, mean age 73.4 ± 3.5 years). 3T MR imaging was performed at baseline. Extensive neuropsychological assessment was performed at baseline and at 4.5-year follow-up. AI-based volumetric scores were derived from 3DT1: Alzheimer Disease Resemblance Atrophy Index (AD-RAI), Brain Age Gap Estimate (BrainAGE), and normal pressure hydrocephalus (NPH) index. Analyses included regression models between cognitive scores and imaging markers.

RESULTS

AD-RAI score at baseline was associated with Corsi (visuospatial memory) decline (10.6% of cognitive variability in multiple regression models). After inclusion of MTA, CMB, and Fazekas scores simultaneously, the AD-RAI score remained as the sole valid predictor of the cognitive outcome explaining 16.7% of its variability. Its percentage reached 21.4% when amyloid positivity was considered an additional explanatory factor. BrainAGE score was associated with Trail Making B (executive functions) decrease (8.5% of cognitive variability). Among the conventional MRI markers, only the Fazekas score at baseline was positively related to the cognitive outcome (8.7% of cognitive variability). The addition of the BrainAGE score as an independent variable significantly increased the percentage of cognitive variability explained by the regression model (from 8.7 to 14%). The addition of amyloid positivity led to a further increase in this percentage reaching 21.8%.

CONCLUSIONS

The AI-based AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs.

KEY POINTS

• AD-RAI score at baseline was associated with Corsi score (visuospatial memory) decline. • BrainAGE score was associated with Trail Making B (executive functions) decrease. • AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs.

Investigating brain structural maturation in children and adolescents born very preterm using the brain age framework

Very preterm (VP) birth is associated with an increased risk for later neurodevelopmental and behavioural challenges. Although the neurobiological underpinnings of such challenges continue to be explored, previous studies have reported brain volume and morphology alterations in children and adolescents born VP compared with full-term (FT)-born controls. How these alterations relate to the trajectory of brain maturation, with potential implications for later brain ageing, remains unclear. In this longitudinal study, we investigate the relationship between VP birth and brain development during childhood and adolescence. We construct a normative 'brain age' model to predict age over childhood and adolescence based on measures of brain cortical and subcortical volumes and cortical morphology from structural MRI of a dataset of typically developing children aged 3-21 years (n = 768). Using this model, we examined deviations from normative brain development in a separate dataset of children and adolescents born VP (<30 weeks' gestation) at two timepoints (ages 7 and 13 years) compared with FT-born controls (120 VP and 29 FT children at age 7 years; 140 VP and 47 FT children at age 13 years). Brain age delta (brain-predicted age minus chronological age) was, on average, higher in the VP group at both timepoints compared with controls, however this difference had a small to medium effect size and was not statistically significant. Variance in brain age delta was higher in the VP group compared with controls; this difference was significant at the 13-year timepoint. Within the VP group, there was little evidence of associations between brain age delta and perinatal risk factors or cognitive and motor outcomes. Under the brain age framework, our results may suggest that children and adolescents born VP have similar brain structural developmental trajectories to term-born peers between 7 and 13 years of age.