White matter microstructure shows sex differences in late childhood: Evidence from 6797 children

Sex-differences in brain multimodal estimates of white matter microstructure during early adolescence: Sex-specific associations with biological factors

Adolescence is marked by significant maturation of brain white matter microstructure, with evidence for sex-specific maturational trajectory. Most studies have examined conventional diffusion tensor imaging (DTI) metrics, which lack specificity to the underlying tissue modifications. In this study, we characterized sex-differences in white matter microstructure cross-sectionally using DTI, advanced diffusion spectrum imaging (DSI) and diffusion kurtosis imaging (DKI), as well as the white matter tract integrity-Watson (WMTI-W) biophysical model. We also aimed to explore the effect of age and biological systems undergoing sex-specific changes during adolescence, namely pubertal hormones, hypothalamic-pituitary-adrenal (HPA)-axis function, and glutathione-redox cycle homeostasis. The results indicate widespread sex-differences in all the white matter derived metrics, suggesting more advanced maturation in females compared to males as well as distinct tissue modifications underlying white matter maturation between males and females during this narrow developmental period. Additionally, the three biological factors explored appeared to be associated with indices of white matter maturation in females specifically, emphasizing this period as critical in female white matter development and sensitivity to environmental factors.

White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life

Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.

Multivariate links between the developmental timing of adversity exposure and white matter tract connectivity in adulthood

BACKGROUND

Early-life adversity is pervasive worldwide and represents a potent risk factor for increased mental health burden across the lifespan. However, there is substantial individual heterogeneity in associations between adversity exposure, neurobiological changes, and mental health problems. Accounting for key features of adversity such as the developmental timing of exposure may clarify associations between adversity, neurodevelopment, and mental health.

METHODS

The present study leverages sparse canonical correlation analysis to characterize modes of covariation between adversity exposure across development and the connectivity of white matter tracts throughout the brain in a sample of 107 adults.

RESULTS

We found that adversity exposure during preschool-age and middle childhood (ages 4-5 and 8 in particular) were consistently linked across diffusion metrics with alterations in white matter tract connectivity. Whereas tracts supporting sensorimotor functions displayed higher connectivity with higher preschool-age and middle childhood adversity exposure, tracts supporting cortico-cortical communication displayed lower connectivity. Further, latent patterns of tract connectivity linked with adversity experienced across preschool-age and middle childhood (ages 3-8) were associated with post-traumatic stress symptoms in adulthood.

CONCLUSIONS

Our findings underscore that adversity exposure may differentially affect white matter in a function- and developmental-timing specific manner and suggest that adversity experienced between ages 3-8 may shape the development of white matter tracts across the brain in ways that are relevant for mental health in adulthood.

Sleep duration and efficiency moderate the effects of prenatal and childhood ambient pollutant exposure on global white matter microstructural integrity in adolescence

Background

Air pollution is a ubiquitous neurotoxicant associated with alterations in structural connectivity. Good habitual sleep may be an important protective lifestyle factor due to its involvement in the brain waste clearance and its bidirectional relationship with immune function. Wearable multisensory devices may provide more objective measures of sleep quantity and quality. We investigated whether sleep duration and efficiency moderated the relationship between prenatal and childhood pollutant exposure and whole-brain white matter microstructural integrity at ages 10-13 years.

Methods

We used multi-shell diffusion-weighted imaging data collected on 3T MRI scanners and objective sleep data collected with Fitbit Charge 2 from the 2-year follow-up visit for 2178 subjects in the Adolescent Brain Cognitive Development Study®. White matter tracts were identified using a probabilistic atlas. Restriction spectrum imaging was performed to extract restricted normalized isotropic (RNI) and directional (RND) signal fraction parameters for all white matter tracts, then averaged to calculate global measures. Sleep duration was calculated by summing the time spent in each sleep stage; sleep efficiency was calculated by dividing sleep duration by time spent in bed. Using an ensemble-based modeling approach, air pollution concentrations of PM2.5, NO2, and O3 were assigned to each child's residential addresses during the prenatal period (9-month average before birthdate) as well as at ages 9-10 years. Multi-pollutant linear mixed effects models assessed the associations between global RNI and RND and sleep-by-pollutant interactions, adjusting for appropriate covariates.

Results

Sleep duration interacted with childhood NO2 exposure and sleep efficiency interacted with prenatal O3 exposure to affect RND at ages 10-13 years. Longer sleep duration and higher sleep efficiency in the context of higher pollutant exposure was associated with lower RND compared to those with similar pollutant exposure but shorter sleep duration and lower sleep efficiency.

Conclusions

Low-level air pollution poses a risk to brain health in youth, and healthy sleep duration and efficiency may increase resilience to its harmful effects on white matter microstructural integrity. Future studies should evaluate the generalizability of these results in more diverse cohorts as well as utilize longitudinal data to understand how sleep may impact brain health trajectories in the context of pollution over time.

More similarity than difference: comparison of within- and between-sex variance in early adolescent brain structure

Background

Adolescent neuroimaging studies of sex differences in the human brain predominantly examine mean differences between males and females. This focus on between-groups differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain.

Methods

We aimed to characterize the variance in brain macro- and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11 year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N=7,723). Specifically, for global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within- and between-sex variance, overlap between male and female distributions, inhomogeneity of variance via the Fligner-Killeen test, and an analysis of similarities (ANOSIM). For completeness, we examined these sex differences using both uncorrected (raw) brain estimates and residualized brain estimates after using mixed-effects modeling to account for age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable.

Results

The overlap between male and female distributions was universally greater than the difference (overlap coefficient range: 0.585 - 0.985) and the ratio of within-sex and between-sex differences was similar (ANOSIM R range: -0.001 - 0.117). All cortical and subcortical volumes showed significant inhomogeneity of variance, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Inhomogeneity of variance was reduced after accounting for other sources of variance. Overlap coefficients were larger and ANOSIM R values were smaller for residualized outcomes, indicating greater within- and smaller between-sex differences once accounting for other covariates.

Conclusions

Reported sex differences in early adolescent human brain structure may be driven by disparities in variance, rather than binary, sex-based phenotypes. Contrary to the popular view of the brain as sexually dimorphic, we found more similarity than difference between sexes in all global and regional measurements of brain structure examined. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure.

Sex-related variability of white matter tracts in the whole HCP cohort

Behavioral differences between men and women have been studied extensively, as have differences in brain anatomy. However, most studies have focused on differences in gray matter, while white matter has been much less studied. We conducted a comprehensive study of 77 deep white matter tracts to analyze their volumetric and microstructural variability between men and women in the full Human Connectome Project (HCP) cohort of 1065 healthy individuals aged 22-35 years. We found a significant difference in total brain volume between men and women (+ 12.6% in men), consistent with the literature. 16 tracts showed significant volumetric differences between men and women, one of which stood out due to a larger effect size: the corpus callosum genu, which was larger in women (+ 7.3% in women, p = 5.76 × 10-19). In addition, we found several differences in microstructural parameters between men and women, both using standard Diffusion Tensor Imaging (DTI) parameters and more complex microstructural parameters from the Neurite Orientation Dispersion and Density Imaging (NODDI) model, with the tracts showing the greatest differences belonging to motor (cortico-spinal tracts, cortico-cerebellar tracts) or limbic (cingulum, fornix, thalamo-temporal radiations) systems. These microstructural differences may be related to known behavioral differences between the sexes in timed motor performance, aggressiveness/impulsivity, and social cognition.

Exposure to multiple ambient air pollutants changes white matter microstructure during early adolescence with sex-specific differences

BACKGROUND

Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex.

METHODS

We investigate sex-stratified effects of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at ages 9-10 years on longitudinal patterns of white matter microstructure over a 2-year period. Diffusion-weighted imaging was collected on 3T MRI scanners for 8182 participants (1-2 scans per subject; 45% with two scans) from the Adolescent Brain Cognitive Development (ABCD) Study®. Restriction spectrum imaging was performed to quantify intracellular isotropic (RNI) and directional (RND) diffusion. Ensemble-based air pollution concentrations were assigned to each child's primary residential address. Multi-pollutant, sex-stratified linear mixed-effect models assessed associations between pollutants and RNI/RND with age over time, adjusting for sociodemographic factors.

RESULTS

Here we show higher PM2.5 exposure is associated with higher RND at age 9 in both sexes, with no significant effects of PM2.5 on RNI/RND change over time. Higher NO2 exposure is associated with higher RNI at age 9 in both sexes, as well as attenuating RNI over time in females. Higher O3 exposure is associated with differences in RND and RNI at age 9, as well as changes in RND and RNI over time in both sexes.

CONCLUSIONS

Criteria air pollutants influence patterns of white matter maturation between 9-13 years old, with some sex-specific differences in the magnitude and anatomical locations of affected tracts. This occurs at concentrations that are below current U.S. standards, suggesting exposure to low-level pollution during adolescence may have long-term consequences.

Sex and mental health are related to subcortical brain microstructure

Some mental health problems such as depression and anxiety are more common in females, while others such as autism and attention deficit/hyperactivity (AD/H) are more common in males. However, the neurobiological origins of these sex differences are poorly understood. Animal studies have shown substantial sex differences in neuronal and glial cell structure, while human brain imaging studies have shown only small differences, which largely reflect overall body and brain size. Advanced diffusion MRI techniques can be used to examine intracellular, extracellular, and free water signal contributions and provide unique insights into microscopic cellular structure. However, the extent to which sex differences exist in these metrics of subcortical gray matter structures implicated in psychiatric disorders is not known. Here, we show large sex-related differences in microstructure in subcortical regions, including the hippocampus, thalamus, and nucleus accumbens in a large sample of young adults. Unlike conventional T1-weighted structural imaging, large sex differences remained after adjustment for age and brain volume. Further, diffusion metrics in the thalamus and amygdala were associated with depression, anxiety, AD/H, and antisocial personality problems. Diffusion MRI may provide mechanistic insights into the origin of sex differences in behavior and mental health over the life course and help to bridge the gap between findings from experimental, epidemiological, and clinical mental health research.

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

Sex Differences in White Matter Diffusivity in Children with Developmental Dyslexia

Despite the high prevalence of developmental dyslexia in the U.S. population, research remains limited and possibly biased due to the overrepresentation of males in most dyslexic samples. Studying biological sex differences in the context of developmental dyslexia can help provide a more complete understanding of the neurological markers that underly this disorder. The current study aimed to explore sex differences in white matter diffusivity in typical and dyslexic samples in third and fourth graders. Participants were asked to complete behavioral/cognitive assessments at baseline followed by MRI scanning and diffusion-weighted imaging sequences. A series of ANOVAs were conducted for comparing group membership (developmental dyslexia or typically developing), gender status (F/M), and white matter diffusivity in the tracts of interest. The Results indicated significant differences in fractional anisotropy in the left hemisphere components of the inferior and superior (parietal and temporal) longitudinal fasciculi. While males with dyslexia had lower fractional anisotropy in these tracts compared to control males, no such differences were found in females. The results of the current study may suggest that females may use a more bilateral/alternative reading network.

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

Sex, gender diversity, and brain structure in early adolescence

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Diffusion MRI harmonization via personalized template mapping

One fundamental challenge in diffusion magnetic resonance imaging (dMRI) harmonization is to disentangle the contributions of scanner-related effects from the variable brain anatomy for the observed imaging signals. Conventional harmonization methods rely on establishing an atlas space to resolve anatomical variability and generate a unified inter-site mapping function. However, this approach is limited in accounting for the misalignment of neuroanatomy that still widely persists even after registration, especially in regions close to cortical boundaries. To overcome this challenge, we propose a personalized framework in this paper to more effectively address the confounding from the misalignment of neuroanatomy in dMRI harmonization. Instead of using a common template representing site-effects for all subjects, the main novelty of our method is the adaptive computation of personalized templates for both source and target scanning sites to estimate the inter-site mapping function. We integrate our method with the rotation invariant spherical harmonics (RISH) features to achieve the harmonization of dMRI signals between sites. In our experiments, the proposed approach is applied to harmonize the dMRI data acquired from two scanning platforms: Siemens Prisma and GE MR750 from the Adolescent Brain Cognitive Development dataset and compared with a state-of-the-art method based on RISH features. Our results indicate that the proposed harmonization framework achieves superior performance not only in reducing inter-site variations due to scanner differences but also in preserving sex-related biological variability in original cohorts. Moreover, we assess the impact of harmonization on the estimation of fiber orientation distributions and show the robustness of the personalized harmonization procedure in preserving the fiber orientation of original dMRI signals.

Quantitative diffusion imaging and genotype-by-sex interactions in a rat model of Alexander disease

PURPOSE

The clinical diagnosis and classification of Alexander disease (AxD) relies in part on qualitative neuroimaging biomarkers; however, these biomarkers fail to distinguish and discriminate different subtypes of AxD, especially in the presence of overlap in clinical symptoms. To address this gap in knowledge, we applied neurite orientation dispersion and density imaging (NODDI) to an innovative CRISPR-Cas9 rat genetic model of AxD to gain quantitative insights into the neural substrates and brain microstructural changes seen in AxD and to potentially identify novel quantitative NODDI biomarkers of AxD.

METHODS

Multi-shell DWI of age- and sex-matched AxD and wild-type Sprague Dawley rats (n = 6 per sex per genotype) was performed and DTI and NODDI measures calculated. A 3 × 2 × 2 analysis of variance model was used to determine the effect of genotype, biological sex, and laterality on quantitative measures of DTI and NODDI across regions of interest implicated in AxD.

RESULTS

There is a significant effect of genotype in the amygdala, hippocampus, neocortex, and thalamus in measures of both DTI and NODDI brain microstructure. A genotype by biological sex interaction was identified in DTI and NODDI measures in the corpus callosum, hippocampus, and neocortex.

CONCLUSION

We present the first application of NODDI to the study of AxD using a rat genetic model of AxD. Our analysis identifies alterations in NODDI and DTI measures to large white matter tracts and subcortical gray nuclei. We further identified genotype by sex interactions, suggesting a possible role for biological sex in the neuropathogenesis of AxD.

Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI

Age-related white matter (WM) microstructure maturation and decline occur throughout the human lifespan, complementing the process of gray matter development and degeneration. Here, we create normative lifespan reference curves for global and regional WM microstructure by harmonizing diffusion MRI (dMRI)-derived data from ten public datasets (N = 40,898 subjects; age: 3-95 years; 47.6% male). We tested three harmonization methods on regional diffusion tensor imaging (DTI) based fractional anisotropy (FA), a metric of WM microstructure, extracted using the ENIGMA-DTI pipeline. ComBat-GAM harmonization provided multi-study trajectories most consistent with known WM maturation peaks. Lifespan FA reference curves were validated with test-retest data and used to assess the effect of the ApoE4 risk factor for dementia in WM across the lifespan. We found significant associations between ApoE4 and FA in WM regions associated with neurodegenerative disease even in healthy individuals across the lifespan, with regional age-by-genotype interactions. Our lifespan reference curves and tools to harmonize new dMRI data to the curves are publicly available as eHarmonize (https://github.com/ahzhu/eharmonize).

Sex-specific effects in how childhood exposures to multiple ambient air pollutants affect white matter microstructure development across early adolescence

Ambient air pollution is ubiquitous, yet questions remain as to how it might impact the developing brain. Large changes occur in the brain's white matter (WM) microstructure across adolescence, with noticeable differences in WM integrity in male and female youth. Here we report sex-stratified effects of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) on longitudinal patterns of WM microstructure from 9-13 years-old in 8,182 (49% female) participants using restriction spectrum imaging. After adjusting for key sociodemographic factors, multi-pollutant, sex-stratified models showed that one-year annual exposure to PM2.5 and NO2 was associated with higher, while O3 was associated with lower, intracellular diffusion at age 9. All three pollutants also affected trajectories of WM maturation from 9-13 years-old, with some sex-specific differences in the number and anatomical locations of tracts showing altered trajectories of intracellular diffusion. Concentrations were well-below current U.S. standards, suggesting exposure to these criteria pollutants during adolescence may have long-term consequences on brain development.

Associations between psychological resilience and metrics of white matter microstructure in pediatric concussion

This study investigated associations between psychological resilience and characteristics of white matter microstructure in pediatric concussion. This is a case control study and a planned substudy of a larger randomized controlled trial. Children with an acute concussion or orthopedic injury were recruited from the emergency department. Participants completed both the Connor-Davidson Resilience Scale 10 and an MRI at 72 h and 4-weeks post-injury. The association between resiliency and fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) at both timepoints were examined. We examined whether these associations were moderated by group. The association between resiliency captured at 72 h and diffusion tensor imaging metrics at 4 weeks was also investigated. Clusters were extracted using a significance threshold of threshold-free cluster enhancement corrected p < .05. A total of 66 children with concussion (median (IQR) age = 12.88 (IQR: 11.80-14.36); 47% female) and 29 children with orthopedic-injury (median (IQR) age = 12.49 (IQR: 11.18-14.01); 41% female) were included. A negative correlation was identified in the concussion group between 72 h resilience and 72 h FA. Meanwhile, positive correlations were identified in the concussion group with concussion between 72 h resilience and both 72 h MD and 72 h RD. These findings suggest that 72 h resilience is associated with white matter microstructure of the forceps minor, superior longitudinal fasciculus, and anterior thalamic radiation at 72 h post-concussion. Resilience seems to be associated with neural integrity only in the acute phase of concussion and thus may be considered when researching concussion recovery.

Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition

Importance

Both neighborhood and household socioeconomic disadvantage relate to negative health outcomes and altered brain structure in children. It is unclear whether such findings extend to white matter development, and via what mechanisms socioeconomic status (SES) influences the brain.

Objective

To test independent associations between neighborhood and household SES indicators and white matter microstructure in children, and examine whether body mass index and cognitive function (a proxy of environmental cognitive/sensory stimulation) may plausibly mediate these associations.

Design

This cross-sectional study used baseline data from the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing 10-year cohort study tracking child health.

Setting

School-based recruitment at 21 U.S. sites.

Participants

Children aged 9 to 11 years and their parents/caregivers completed baseline assessments between October 1 st , 2016 and October 31 st , 2018. Data analysis was conducted from July to December 2022.

Exposures

Neighborhood disadvantage was derived from area deprivation indices at primary residence. Household SES indicators were total income and the highest parental education attainment.

Main Outcomes and Measures

Thirty-one major white matter tracts were segmented from diffusion-weighted images. The Restriction Spectrum Imaging (RSI) model was implemented to measure restricted normalized directional (RND; reflecting oriented myelin organization) and isotropic (RNI; reflecting glial/neuronal cell bodies) diffusion in each tract. Obesity-related measures were body mass index (BMI), BMI z -scores, and waist circumference, and cognitive performance was assessed using the NIH Toolbox Cognition Battery. Linear mixed-effects models tested the associations between SES indicators and scanner-harmonized RSI metrics. Structural equation models examined indirect effects of obesity and cognitive performance in the significant associations between SES and white mater microstructure summary principal components. Analyses were adjusted for age, sex, pubertal development stage, intracranial volume, and head motion.

Results

The analytical sample included 8842 children (4299 [48.6%] girls; mean age [SD], 9.9 [0.7] years). Greater neighborhood disadvantage and lower parental education were independently associated with lower RSI-RND in forceps major and corticospinal/pyramidal tracts, and had overlapping associations in the superior longitudinal fasciculus. Lower cognition scores and greater obesity-related measures partially accounted for these SES associations with RSI-RND. Lower household income was related to higher RSI-RNI in almost every tract, and greater neighborhood disadvantage had similar effects in primarily frontolimbic tracts. Lower parental education was uniquely linked to higher RSI-RNI in forceps major. Greater obesity-related measures partially accounted for these SES associations with RSI-RNI. Findings were robust in sensitivity analyses and mostly corroborated using traditional diffusion tensor imaging (DTI).

Conclusions and Relevance

These cross-sectional results demonstrate that both neighborhood and household contexts are relevant to white matter development in children, and suggest cognitive performance and obesity as possible pathways of influence. Interventions targeting obesity reduction and improving cognition from multiple socioeconomic angles may ameliorate brain health in low-SES children.

Key Points

Question: Are neighborhood and household socioeconomic levels associated with children’s brain white matter microstructure, and if so, do obesity and cognitive performance (reflecting environmental stimulation) mediate the associations?Findings: In a cohort of 8842 children, higher neighborhood disadvantage, lower household income, and lower parental education had independent and overlapping associations with lower restricted directional diffusion and greater restricted isotropic diffusion in white matter. Greater body mass index and poorer cognitive performance partially mediated these associations.Meaning: Both neighborhood and household poverty may contribute to altered white matter development in children. These effects may be partially explained by obesity incidence and poorer cognitive performance.