Dimensions of Early-Life Adversity Are Differentially Associated With Patterns of Delayed and Accelerated Brain Maturation

Biological Psychiatry, Год журнала: 2024, Номер 97(1), С. 64 - 72

Опубликована: Июль 29, 2024

BackgroundDifferent types of early-life adversity have been associated with children's brain structure and function. However, understanding the disparate influence distinct exposures on developing remains a major challenge.MethodsThis study investigates neural correlates 10 robust dimensions identified through exploratory factor analysis in large community sample youth from Adolescent Brain Cognitive Development (ABCD) Study. age models were trained, validated, tested separately T1-weighted (T1; N = 9524), diffusion tensor (DTI; 8834), resting-state functional (rs-fMRI; 8233) magnetic resonance imaging (MRI) data two time points (mean 10.7 years, SD 1.2, range 8.9-13.8 years).ResultsBayesian multilevel modelling supported associations between different younger- older-looking brains. Dimensions generally related to emotional neglect, such as lack primary secondary caregiver support, supervision, lower gaps (BAGs), i.e., younger-looking In contrast, psychopathology, trauma exposure, family aggression, substance use separation biological parent, socio-economic disadvantage neighbourhood safety higher BAGs, brains.ConclusionsThe findings suggest that are differentially neurodevelopmental patterns, indicative dimension-specific delayed accelerated maturation.

Язык: Английский

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Puberty differentially predicts brain maturation in male and female youth: A longitudinal ABCD Study

Developmental Cognitive Neuroscience, Год журнала: 2023, Номер 61, С. 101261 - 101261

Опубликована: Июнь 1, 2023

Research has demonstrated associations between pubertal development and brain maturation. However, existing studies have been limited by small samples, cross-sectional designs, inconclusive findings regarding directionality of effects sex differences. We examined the longitudinal temporal coupling puberty status assessed using Pubertal Development Scale (PDS) magnetic resonance imaging (MRI)-based grey white matter structure. Our sample consisted 8896 children adolescents at baseline (mean age = 9.9) 6099 follow-up 11.9) from Adolescent Brain Cognitive (ABCD) Study cohort. Applying multigroup Bivariate Latent Change Score (BLCS) models, we found that PDS predicted rate change in cortical thickness among females surface area for both males females. also a correlation co-occurring changes over time males. Diffusion tensor (DTI) analyses revealed correlated fractional anisotropy (FA) females, but no significant mean diffusivity (MD). results suggest predicts maturation, strength differ sex. Further research spanning entire duration is needed to understand extent contribution on youth brain.

Язык: Английский

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Differences in educational opportunity predict white matter development

Developmental Cognitive Neuroscience, Год журнала: 2024, Номер 67, С. 101386 - 101386

Опубликована: Апрель 22, 2024

Coarse measures of socioeconomic status, such as parental income or education, have been linked to differences in white matter development. However, these do not provide insight into specific aspects an individual's environment and how they relate brain On the other hand, educational intervention studies shown that changes context can drive measurable their matter. These studies, however, rarely consider factors results. In present study, we examined unique relationship between opportunity development, when controlling known factors. To explore this question, leveraged rich demographic neuroimaging data available ABCD well data-crosswalk Stanford Education Data Archive (SEDA). We find is related accelerated even accounting for factors, most pronounced tracts associated with academic skills. results suggest school a child attends has development years come.

Язык: Английский

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The role of brain structure in the association between pubertal timing and depression risk in an early adolescent sample (the ABCD Study®): A registered report

Developmental Cognitive Neuroscience, Год журнала: 2023, Номер 60, С. 101223 - 101223

Опубликована: Фев. 25, 2023

Earlier pubertal timing is associated with higher rates of depressive disorders in adolescence. Neuroimaging studies report brain structural associations both and depression. However, whether structure mediates the relationship between depression remains unclear. The current registered examined (indexed via perceived development), (cortical subcortical metrics, white matter microstructure) symptoms a large sample (N = ∼5000) adolescents (aged 9–13 years) from Adolescent Brain Cognitive Development (ABCD) Study. We used three waves follow-up data when youth were aged 10–11 years, 11–12 12–13 respectively. generalised linear-mixed models (H1) equation modelling (H2 & H3) to test our hypotheses. hypothesised that earlier at Year 1 would be increased 3 (H1), this mediated by global (H2a-b) regional (H3a-g) measures 2. Global included reduced cortical volume, thickness, surface area sulcal depth. Regional thickness volume temporal fronto-parietal areas, ventral diencephalon, depth pars orbitalis, fractional anisotropy cortico-striatal tract corpus callosum. These regions interest informed pilot analyses using baseline ABCD 9–10 years. was two years later. magnitude effect stronger female association remained significant controlling for parental depression, family income, BMI females but not male youth. Our did however mediate later symptoms. present results demonstrate youth, particularly females, who begin puberty ahead their peers are an risk adolescent-onset Future work should explore additional biological socio-environmental factors may affect so we can identify targets intervention help these at-risk

Язык: Английский

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Deviations from normative brain white and gray matter structure are associated with psychopathology in youth

Developmental Cognitive Neuroscience, Год журнала: 2022, Номер 58, С. 101173 - 101173

Опубликована: Ноя. 1, 2022

Combining imaging modalities and metrics that are sensitive to various aspects of brain structure maturation may help identify individuals show deviations in relation same-aged peers, thus benefit early-risk-assessment for mental disorders. We used one timepoint multimodal imaging, cognitive, questionnaire data from 1280 eight- twenty-one-year-olds the Philadelphia Neurodevelopmental Cohort. estimated age-related gray white matter properties individual deviation scores using normative modeling. Next, we tested associations between scores, with psychopathology domain cognition. More negative DTI-based fractional anisotropy (FA) first principal eigenvalue diffusion tensor (L1) were associated higher on psychosis positive prodromal symptoms general psychopathology. A more cortical thickness (CT) was a score. Negative global FA, surface area, L1 CT also poorer cognitive performance. No robust found based DTI. The low correlations different magnetic resonance imaging-based suggest psychopathological burden adolescence can be mapped onto partly distinct neurobiological features.

Язык: Английский

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Brain Age Gap in Early Illness Schizophrenia and the Clinical High-Risk Syndrome: Associations With Experiential Negative Symptoms and Conversion to Psychosis

Schizophrenia Bulletin, Год журнала: 2024, Номер 50(5), С. 1159 - 1170

Опубликована: Май 30, 2024

Abstract Background and Hypothesis Brain development/aging is not uniform across individuals, spawning efforts to characterize brain age from a biological perspective model the effects of disease maladaptive life processes on brain. The gap represents discrepancy between estimated chronological (in this case, based structural magnetic resonance imaging, MRI). Structural MRI studies report an increased (biological > age) in schizophrenia, with greater related negative symptom severity. Less known regarding nature early schizophrenia (ESZ), if psychosis conversion biomarker clinical high-risk (CHR-P) how altered development and/or aging map onto specific facets. Study Design Using MRI, we compared among CHR-P (n = 51), ESZ 78), unaffected comparison participants (UCP; n 90), examined associations (CHR-P converters 10; non-converters; 23) positive symptoms. Results showed relative UCP (Ps < .010). individuals who converted (P .043) non-converters. A larger was associated experiential .008), but expressive Conclusions Consistent pathophysiological models positing abnormal maturation, results suggest present psychosis. An may be especially relevant motivational functional deficits schizophrenia.

Язык: Английский

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Assessing neurocognitive maturation in early adolescence based on baby and adult functional brain landscapes

Developmental Cognitive Neuroscience, Год журнала: 2025, Номер 73, С. 101543 - 101543

Опубликована: Март 6, 2025

Adolescence is a period of growth in cognitive performance and functioning. Recently, data-driven measures brain-age gap, which can index decline older populations, have been utilized adolescent data with mixed findings. Instead using approach, here we assess the maturation status brain functional landscape early adolescence by directly comparing an individual's resting-state connectivity (rsFC) to canonical early-life adulthood communities. Specifically, hypothesized that degree youth's connectome better captured adult networks compared infant/toddler predictive their development. To test this hypothesis across individuals longitudinally, Adolescent Brain Cognitive Development (ABCD) Study at baseline (9-10 years; n = 6469) 2-year-follow-up (Y2: 11-12 5060). Adjusted for demographic factors, our anchored rsFC score (AFC) was associated task both within participants. AFC related age aging youth, change statistically mediated age-related performance. In conclusion, showed model-fitting-free rest baby landscapes predicts development youth.

Язык: Английский

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Dimensions of early life adversity are differentially associated with patterns of delayed and accelerated brain maturation

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 23, 2024

Different types of early-life adversity have been associated with childrens brain structure and function. However, understanding the disparate influence distinct exposures on developing remains a major challenge. This study investigates neural correlates 10 robust dimensions identified through exploratory factor analysis in large community sample youth from Adolescent Brain Cognitive Development (ABCD) Study. age models were trained, validated, tested separately T1-weighted (T1; N = 9524), diffusion tensor (DTI; 8834), resting-state functional (rs-fMRI; 8233) magnetic resonance imaging (MRI) data two time points (mean 10.7 years, SD 1.2, range 8.9-13.8 years). Bayesian multilevel modelling supported associations between different younger- older-looking brains. Dimensions generally related to emotional neglect, such as lack primary secondary caregiver support, supervision, lower gaps (BAGs), i.e., younger-looking In contrast, psychopathology, trauma exposure, family aggression, substance use separation biological parent, socio-economic disadvantage neighbourhood safety higher BAGs, The findings suggest that are differentially neurodevelopmental patterns, indicative dimension-specific delayed accelerated maturation.

Язык: Английский

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Menarche, pubertal timing and the brain: female-specific patterns of brain maturation beyond age-related development

Biology of Sex Differences, Год журнала: 2024, Номер 15(1)

Опубликована: Март 26, 2024

Abstract Background Puberty depicts a period of profound and multifactorial changes ranging from social to biological factors. While brain development in youths has been studied mostly an age perspective, recent evidence suggests that pubertal measures may be more sensitive study adolescent neurodevelopment, however, studies on timing relation are still scarce. Methods We investigated if pre- vs. post-menarche status can classified using machine learning cortical subcortical structural magnetic resonance imaging (MRI) data strictly age-matched females the Adolescent Brain Cognitive Development (ABCD) cohort. For comparison identified menarche-related patterns age-related we trained prediction model Philadelphia Neurodevelopmental Cohort applied it same ABCD data, yielding differences between predicted chronological referred as gaps. tested sensitivity both these frameworks maturation, specifically at menarche puberty status. Results The achieved moderate but statistically significant accuracy classification task, for each subject class probability 0 (pre-) 1 (post- menarche). Comparison predictions revealed shared distinct neurodevelopment captured by approaches. Continuous probabilities were positively associated with gaps, only probabilities—not gaps—were menarche. Conclusions This demonstrates use classify MRI while accounting neurodevelopment. Given its towards timing, our work developed toward objective brain-based marker development.

Язык: Английский

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A review of artificial intelligence-based brain age estimation and its applications for related diseases

Briefings in Functional Genomics, Год журнала: 2024, Номер unknown

Опубликована: Окт. 22, 2024

Abstract The study of brain age has emerged over the past decade, aiming to estimate a person’s based on imaging scans. Ideally, predicted should match chronological in healthy individuals. However, structure and function change presence brain-related diseases. Consequently, also changes affected individuals, making gap (BAG)—the difference between age—a potential biomarker for health, early screening, identifying age-related cognitive decline disorders. With recent successes artificial intelligence healthcare, it is essential track latest advancements highlight promising directions. This review paper presents machine learning techniques used estimation (BAE) studies. Typically, BAE models involve developing regression model capture variations from scans individuals automatically predict new subjects. process involves estimating BAG as measure health. While we discuss clinical applications methods, studies biological that can be integrated into research. Finally, point out current limitations BAE’s

Язык: Английский

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