Brain White Matter Microstructure Research Articles

White matter microstructural differences in children and genetic risk for multiple sclerosis: A population-based study

Background: MS patients show abnormalities in white matter (WM) on brain imaging, with heterogeneity in the location of WM lesions. The “pothole” method can be applied to diffusion-weighted images to identify spatially distinct clusters of divergent brain WM microstructure. Objective: To investigate the association between genetic risk for MS and spatially independent clusters of decreased or increased fractional anisotropy (FA) in the brain. In addition, we studied sex- and age-related differences. Methods: 3 Tesla diffusion tensor imaging (DTI) data were collected in 8- to 12-year-old children from a population-based study. Global and tract-based potholes (lower FA clusters) and molehills (higher FA clusters) were quantified in 3047 participants with usable DTI data. A polygenic risk score (PRS) for MS was calculated in genotyped individuals (n = 1087) and linear regression analyses assessed the relationship between the PRS and the number of potholes and molehills, correcting for multiple testing using the False Discovery Rate. Results: The number of molehills increased with age, potholes decreased with age, and fewer potholes were observed in girls during typical development. The MS-PRS was positively associated with the number of molehills (β = 0.9, SE = 0.29, p = 0.002). Molehills were found more often in the corpus callosum (β = 0.3, SE = 0.09, p = 0.0003). Conclusion: Genetic risk for MS is associated with spatially distinct clusters of increased FA during childhood brain development.

Brain Structure and Physical Activity Levels in Middle-Aged and Elderly Individuals: A Bidirectional Longitudinal Population-Based Study

Background: To prevent and reduce age-related brain changes, it is crucial to identify modifiable factors that might contribute to preserving brain health during aging. Therefore, we aimed to investigate the bidirectional associations of physical activity with brain structure in middle-aged and elderly individuals. Methods: Overall, 4,365 participants (64.01±10.82 years; 56% females) from the Rotterdam Study had physical activity and brain structure assessed on at least one of two timepoints (‘baseline’: 2006-2012 or ‘follow-up’: 2012-2017, median duration between visits: 5 years). Physical activity was assessed through the LASA Physical Activity Questionnaire. T1-weighted MRI and diffusion tensor imaging were used to quantify brain volumes and white matter microstructure, respectively. Cross-lagged panel models were performed to estimate bidirectional associations, and linear mixed-effects models to investigate the consistency of findings. False discovery rate (FDR) was used to correct for multiple testing. Findings: Larger total brain volume (β = 0.067, 95%CI 0.035;0.099, pFDR=0.001), gray matter volume (β= 0.063, 0.031;0.096, pFDR=0.002), and white matter volume (β= 0.051, 0.020;0.083, pFDR=0.013) were associated with an increase in sport participation over time. Lower global mean diffusivity was associated with an increase in walking levels over time (β= -0.074, -0.111;-0.037, pFDR=0.001). No associations were found between physical activity and changes in brain metrics over time. Interpretation: Physical activity was not associated with a healthier brain structure over time in elderly individuals. In contrast, brain structure was associated with individuals remaining physically active over time. Funding: Erasmus MC University Medical Center Rotterdam, and Netherlands Organization for the Health Research and Development. Declaration of Interests: We declare no competing interests. Ethics Approval Statement: The Rotterdam Study has been approved by the Medical Ethics Committee of Erasmus MC (registration number MEC 02.1015) and by the Dutch Ministry of Health, Welfare and Sport (Population Screening Act WBO, license number 1071272-159521-PG). The Rotterdam Study Personal Registration Data collection is filed with the Erasmus MC Data Protection Officer under registration number EMC1712001. Trial Registration: The Rotterdam Study has been registered at the Netherlands National Trial Register (NTR; www.trialregister.nl) and the WHO International Clinical Trials Registry Platform (ICTRP; www.who.int/ictrp/network/primary/en/) under shared catalogue number NTR6831.

White Matter Microstructural Differences in Youth With Classical Congenital Adrenal Hyperplasia.

Gray matter morphology in the prefrontal cortex and subcortical regions, including the hippocampus and amygdala, are affected in youth with classical congenital adrenal hyperplasia (CAH). It remains unclear if white matter connecting these aforementioned brain regions is compromised in youth with CAH. To examine brain white matter microstructure in youth with CAH compared to controls. A cross-sectional sample of 23 youths with CAH due to 21-hydroxylase deficiency (12.9 ± 3.5 year; 61% female) and 33 healthy controls (13.1 ± 2.8 year; 61% female) with 3T multishell diffusion-weighted magnetic resonance brain scans. Complementary modeling approaches, including diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), to examine in vivo white matter microstructure in six white matter tracts that innervate the prefrontal and subcortical regions. DTI showed CAH youth had lower fractional anisotropy in both the fornix and stria terminalis and higher mean diffusivity in the fornix compared to controls. NODDI modeling revealed that CAH youth have a significantly higher orientation dispersion index in the stria terminalis compared to controls. White matter microstructural integrity was associated with smaller hippocampal and amygdala volumes in CAH youth. These patterns of microstructure reflect less restricted water diffusion likely due to less coherency in oriented microstructure. These results suggest that white matter microstructural integrity in the fornix and stria terminalis is compromised and may be an additional related brain phenotype alongside affected hippocampus and amygdala neurocircuitry in individuals with CAH.

Difference in distribution functions: A new diffusion weighted imaging metric for estimating white matter integrity

Diffusion weighted imaging (DWI) is a widely recognized neuroimaging technique to evaluate the microstructure of brain white matter. The objective of this study is to establish an improved automated DWI marker for estimating white matter integrity and investigating ageing related cognitive decline. The concept of Wasserstein distance was introduced to help establish a new measure: difference in distribution functions (DDF), which captures the difference of reshaping one's mean diffusivity (MD) distribution to a reference MD distribution. This new DWI measure was developed using a population-based cohort (n=19,369) from the UK Biobank. Validation was conducted using the data drawn from two independent cohorts: the Sydney Memory and Ageing Study, a community-dwelling sample (n=402), and the Renji Cerebral Small Vessel Disease Cohort Study (RCCS), which consisted of cerebral small vessel disease (CSVD) patients (n=171) and cognitively normal controls (NC) (n=43). DDF was associated with age across all three samples and better explained the variance of changes than other established DWI measures, such as fractional anisotropy, mean diffusivity and peak width of skeletonized mean diffusivity (PSMD). Significant correlations between DDF and cognition were found in the UK Biobank cohort and the MAS cohort. Binary logistic analysis and receiver operator characteristic curve analysis of RCCS demonstrated that DDF had higher sensitivity in distinguishing CSVD patients from NC than the other DWI measures. To demonstrate the flexibility of DDF, we calculated regional DDF which also showed significant correlation with age and cognition. DDF can be used as a marker for monitoring the white matter microstructural changes and ageing related cognitive decline in the elderly.

Maternal polyunsaturated fatty acids during pregnancy and offspring brain development in childhood

Emerging evidence suggests an association of maternal PUFA concentrations during pregnancy with child cognitive and neuropsychiatric outcomes such as intelligence and autistic traits. However, little is known about prenatal maternal PUFAs in relation to child brain development, which may underlie these associations. We aimed to investigate the association of maternal PUFA status during pregnancy with child brain morphology, including volumetric and white matter microstructure measures. This study was embedded in a prospective population-based study. In total, 1553 mother-child dyads of Dutch origin were included. Maternal plasma glycerophospholipid PUFAs were assessed in midpregnancy. Child brain morphologic outcomes, including total gray and white matter volumes, as well as white matter microstructure quantified by global fractional anisotropy and mean diffusivity, were measured using MRI (including diffusion tensor imaging) at age 9-11 y. Maternal ω-3 (n-3) long-chain PUFA (LC-PUFA) concentrations during pregnancy had an inverted U-shaped relation with child total gray volume (linear term: β: 16.7; 95% CI: 2.0, 31.5; quadratic term: β: -1.1; 95% CI: -2.1, -0.07) and total white matter volume (linear term: β: 15.7; 95% CI: 3.6, 27.8; quadratic term: β: -1.0; 95% CI: -1.8, -0.16). Maternal gestational ω-6 LC-PUFA concentrations did not predict brain volumetric differences in children, albeit the linolenic acid concentration was inversely associated with child total white matter volume. Maternal PUFA status during pregnancy was not related to child white matter microstructure. Sufficient maternal ω-3 PUFAs during pregnancy may be related to more optimal child brain development in the long term. In particular, exposure to lower ω-3 PUFA concentrations in fetal life was associated with less brain volume in childhood. Maternal ω-6 LC-PUFAs were not related to child brain morphology.

Measuring compartmental [formula omitted]-orientational dependence in human brain white matter using a tiltable RF coil and diffusion-[formula omitted] correlation MRI

The anisotropy of brain white matter microstructure manifests itself in orientational-dependence of various MRI contrasts, and can result in significant quantification biases if ignored. Understanding the origins of this orientation-dependence could enhance the interpretation of MRI signal changes in development, ageing and disease and ultimately improve clinical diagnosis. Using a novel experimental setup, this work studies the contributions of the intra- and extra-axonal water to the orientation-dependence of one of the most clinically-studied parameters, apparent transverse relaxation T2. Specifically, a tiltable receive coil is interfaced with an ultra-strong gradient MRI scanner to acquire multidimensional MRI data with an unprecedented range of acquisition parameters. Using this setup, compartmental T2 can be disentangled based on differences in diffusional-anisotropy, and its orientation-dependence further elucidated by re-orienting the head with respect to the main magnetic field B→0. A dependence of (compartmental) T2 on the fibre orientation w.r.t. B→0 was observed, and further quantified using characteristic representations for susceptibility- and magic angle effects. Across white matter, anisotropy effects were dominated by the extra-axonal water signal, while the intra-axonal water signal decay varied less with fibre-orientation. Moreover, the results suggest that the stronger extra-axonal T2 orientation-dependence is dominated by magnetic susceptibility effects (presumably from the myelin sheath) while the weaker intra-axonal T2 orientation-dependence may be driven by a combination of microstructural effects. Even though the current design of the tiltable coil only offers a modest range of angles, the results demonstrate an overall effect of tilt and serve as a proof-of-concept motivating further hardware development to facilitate experiments that explore orientational anisotropy. These observations have the potential to lead to white matter microstructural models with increased compartmental sensitivity to disease, and can have direct consequences for longitudinal and group-wise T2- and diffusion-MRI data analysis, where the effect of head-orientation in the scanner is commonly ignored.

Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure

Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia.

Association between breastfeeding during infancy and white matter microstructure in early childhood

IntroductionAssociations between breastfeeding and brain development, in the context of child, perinatal, and sociodemographic variables, remain unclear. This study investigated whether exclusive breastfeeding for the first 6 months and total duration of breastfeeding were associated with brain white matter microstructure in young children. MethodsThis study included 85 typically developing children (42 males) born to 83 mothers that were predominantly white, highly educated, and in high income households. Children underwent their first diffusion tensor imaging scan between ages 2.34 and 6.97 years; some children returned multiple times, providing a total of 331 datasets. Feeding information was collected from mothers at 3, 6, and 12 months postpartum and at their child's scan to calculate breastfeeding status at 6 months (exclusive or not) as well as total duration of any breastfeeding. Linear regression was used to investigate associations between breastfeeding exclusivity/duration and fractional anisotropy (FA) for the whole brain and 10 individual white matter tracts. ResultsBreastfeeding exclusivity and duration were associated with global and regional white matter microstructure, even after controlling for perinatal and sociodemographic factors. Greater exclusivity was associated with higher FA in females and lower FA in males. ConclusionsThese findings suggest white matter differences associated with breastfeeding that differ by sex. These may stem from different trajectories in white matter development between males and females in early childhood and suggest possible long-term white matter differences associated with breastfeeding.

Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure.

Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia. A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient's symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data. Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual's symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = -5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05). Symptom network structure varies over the course of schizophrenia: symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia.

A randomized controlled trial investigating the impact of maternal dietary supplementation with pomegranate juice on brain injury in infants with IUGR

Animal studies have demonstrated the therapeutic potential of polyphenol-rich pomegranate juice. We recently reported altered white matter microstructure and functional connectivity in the infant brain following in utero pomegranate juice exposure in pregnancies with intrauterine growth restriction (IUGR). This double-blind exploratory randomized controlled trial further investigates the impact of maternal pomegranate juice intake on brain structure and injury in a second cohort of IUGR pregnancies diagnosed at 24–34 weeks’ gestation. Ninety-nine mothers and their eligible fetuses (n = 103) were recruited from Brigham and Women’s Hospital and randomly assigned to 8 oz pomegranate (n = 56) or placebo (n = 47) juice to be consumed daily from enrollment to delivery. A subset of participants underwent fetal echocardiogram after 2 weeks on juice with no evidence of ductal constriction. 57 infants (n = 26 pomegranate, n = 31 placebo) underwent term-equivalent MRI for assessment of brain injury, volumes and white matter diffusion. No significant group differences were found in brain volumes or white matter microstructure; however, infants whose mothers consumed pomegranate juice demonstrated lower risk for brain injury, including any white or cortical grey matter injury compared to placebo. These preliminary findings suggest pomegranate juice may be a safe in utero neuroprotectant in pregnancies with known IUGR warranting continued investigation.Clinical trial registration: NCT04394910, https://clinicaltrials.gov/ct2/show/NCT04394910, Registered May 20, 2020, initial participant enrollment January 16, 2016.

Evidence of Genetic Overlap Between Circadian Preference and Brain White Matter Microstructure.

Several neuroimaging studies have reported associations between brain white matter microstructure and chronotype. However, it is unclear whether those phenotypic relationships are causal or underlined by genetic factors. In the present study, we use genetic data to examine the genetic overlap and infer causal relationships between chronotype and diffusion tensor imaging (DTI) measures. We identify 29 significant pairwise genetic correlations, of which 13 also show evidence for a causal association. Genetic correlations were identified between chronotype and brain-wide mean, axial and radial diffusivities. When exploring individual tracts, 10 genetic correlations were observed with mean diffusivity, 10 with axial diffusivity, 4 with radial diffusivity and 2 with mode of anisotropy. We found evidence for a possible causal association of eveningness with white matter microstructure measures in individual tracts including the posterior limb and the retrolenticular part of the internal capsule; the genu and splenium of the corpus callosum and the posterior, superior and anterior regions of the corona radiata. Our findings contribute to the understanding of how genes influence circadian preference and brain white matter and provide a new avenue for investigating the role of chronotype in health and disease.

Interpolation and Averaging of Diffusion MRI Multi-Compartment Models.

Multi-compartment models (MCM) are increasingly used to characterize the brain white matter microstructure from diffusion-weighted imaging (DWI). Their use in clinical studies is however limited by the inability to resample an MCM image towards a common reference frame, or to construct atlases from such brain microstructure models. We propose to solve this problem by first identifying that these two tasks amount to the same problem. We propose to tackle it by viewing it as a simplification problem, solved thanks to spectral clustering and the definition of semi-metrics between several usual compartments encountered in the MCM literature. This generic framework is evaluated for two models: the multi-tensor model where individual fibers are modeled as individual tensors and the diffusion direction imaging (DDI) model that differentiates intra- and extra-axonal components of each fiber. Results on simulated data, simulated transformations and real data show the ability of our method to well interpolate MCM images of these types. We finally present as an application an MCM template of normal controls constructed using our approach.

Examining brain white matter after pediatric mild traumatic brain injury using neurite orientation dispersion and density imaging: An A-CAP study

BackgroundPediatric mild traumatic brain injury (mTBI) affects millions of children annually. Diffusion tensor imaging (DTI) is sensitive to axonal injuries and white matter microstructure and has been used to characterize the brain changes associated with mild traumatic brain injury (mTBI). Neurite orientation dispersion and density imaging (NODDI) is a diffusion model that can provide additional insight beyond traditional DTI metrics, but has not been examined in pediatric mTBI. The goal of this study was to employ DTI and NODDI to gain added insight into white matter alterations in children with mTBI compared to children with mild orthopedic injury (OI). MethodsChildren (mTBI n = 320, OI n = 176) aged 8–16.99 years (12.39 ± 2.32 years) were recruited from emergency departments at five hospitals across Canada and underwent 3 T MRI on average 11 days post-injury. DTI and NODDI metrics were calculated for seven major white matter tracts and compared between groups using univariate analysis of covariance controlling for age, sex, and scanner type. False discovery rate (FDR) was used to correct for multiple comparisons. ResultsUnivariate analysis revealed no significant group main effects or interactions in DTI or NODDI metrics. Fractional anisotropy and neurite density index in all tracts exhibited a significant positive association with age and mean diffusivity in all tracts exhibited a significant negative association with age in the whole sample. ConclusionsOverall, there were no significant differences between mTBI and OI groups in brain white matter microstructure from either DTI or NODDI in the seven tracts. This indicates that mTBI is associated with relatively minor white matter differences, if any, at the post-acute stage. Brain differences may evolve at later stages of injury, so longitudinal studies with long-term follow-up are needed.

Brain structural correlates of autistic traits across the diagnostic divide: A grey matter and white matter microstructure study

Autism Spectrum Disorders (ASD) are a set of neurodevelopmental conditions characterised by difficulties in social interaction and communication as well as stereotyped and restricted patterns of interest. Autistic traits exist in a continuum across the general population, whilst the extreme end of this distribution is diagnosed as clinical ASD. While many studies have investigated brain structure in autism using a case-control design, few have used a dimensional approach. To add to this growing body of literature, we investigated the structural brain correlates of autistic traits in a mixed sample of adult participants (25 ASD and 66 neurotypicals; age: 18–60 years). We examined the relationship between regional brain volumes (using voxel-based morphometry and surface-based morphometry) and white matter microstructure properties (using Diffusion Tensor Imaging) and autistic traits (using Autism Spectrum Quotient). Our findings show grey matter differences in regions including the orbitofrontal cortex and lingual gyrus, and suggestive evidence for white matter microstructure differences in tracts including the superior longitudinal fasciculus being related to higher autistic traits. These grey matter and white matter microstructure findings from our study are consistent with previous reports and support the brain structural differences in ASD. These findings provide further support for shared aetiology for autistic traits across the diagnostic divide.

Direct and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure With Executive Functioning and General and Specific Dimensions of Psychopathology in Children

BackgroundExecutive functions (EFs) are important partly because they are associated with risk for psychopathology and substance use problems. Because EFs have been linked to white matter microstructure, we tested the prediction that fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts are associated with EFs and dimensions of psychopathology in children younger than the age of widespread psychoactive substance use. MethodsParent symptom ratings, EF test scores, and diffusion tensor parameters from 8588 9- to 10-year-olds in the ABCD Study (Adolescent Brain Cognitive Development Study) were used. ResultsA latent factor derived from EF test scores was significantly associated with specific conduct problems and attention-deficit/hyperactivity disorder problems, with dimensions defined in a bifactor model. Furthermore, EFs were associated with FA and MD in 16 of 17 bilateral white matter tracts (range: β = .05; SE = .17; through β = −.31; SE = .06). Neither FA nor MD was directly associated with psychopathology, but there were significant indirect associations via EFs of both FA (range: β = .01; SE = .01; through β = −.09; SE = .02) and MD (range: β = .01; SE = .01; through β = .09; SE = .02) with both specific conduct problems and attention-deficit/hyperactivity disorder in all tracts except the forceps minor. ConclusionsEFs in children are inversely associated with diffusion tensor imaging measures in nearly all tracts throughout the brain. Furthermore, variance in diffusion tensor measures that is shared with EFs is indirectly shared with attention-deficit/hyperactivity disorder and conduct problems.

White Matter Microstructure Underlies the Effects of Sleep Quality and Life Stress on Depression Symptomatology in Older Adults

Sleep complaints are the most prevalent syndromes in older adults, particularly in women. Moreover, they are frequently accompanied with a high level of depression and stress. Although several diffusion tensor imaging (DTI) studies reported associations between sleep quality and brain white matter (WM) microstructure, it is still unclear whether gender impacts the effect of sleep quality on structural alterations, and whether these alterations mediate the effects of sleep quality on emotional regulation. We included 389 older participants (176 females, age = 65.5 ± 5.5 years) from the 1000BRAINS project. Neuropsychological examinations covered the assessments of sleep quality, depressive symptomatology, current stress level, visual working memory, and selective attention ability. Based on the DTI dataset, the diffusion parameter maps, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), were calculated and normalized to a population-specific FA template. According to the global Pittsburgh Sleep Quality Index (PSQI), 119 poor sleepers (PSQI: 10∼17) and 120 good sleepers (PSQI: 3∼6) were identified. We conducted a two by two (good sleepers/poor sleepers) × (males/females) analysis of variance by using tract-based spatial statistics (TBSS) and JHU-ICBM WM atlas-based comparisons. Moreover, we performed a voxel-wise correlation analysis of brain WM microstructure with the neuropsychological tests. Finally, we applied a mediation analysis to explore if the brain WM microstructure mediates the relationship between sleep quality and emotional regulation. No significant differences in brain WM microstructure were detected on the main effect of sleep quality. However, the MD, AD, and RD of pontine crossing tract and bilateral inferior cerebellar peduncle were significant lower in the males than females. Voxel-wise correlation analysis revealed that FA and RD values in the corpus callosum were positively related with depressive symptomatology and negatively related with current stress levels. Additionally, we found a significantly positive association between higher FA values in visual-related WM tracts and better outcomes in a visual pattern recognition test. Furthermore, a mediation analysis suggested that diffusion metrics within the corpus callosum partially mediated the associations between poor sleep quality/high stress and depressive symptomatology.

Concussion Disrupts Normal Brain White Matter Microstructural Symmetry.

Injuries and illnesses can alter the normal bilateral symmetry of the brain, and determining the extent of this disruption may be useful in characterizing the pathology. One way of quantifying brain symmetry is in terms of bilateral correlation of diffusion tensor metrics between homologous white matter tracts. With this approach, we hypothesized that the brains of patients with a concussion are more asymmetrical than those of healthy individuals without a history of a concussion. We scanned the brains of 35 normal individuals and 15 emergency department patients with a recent concussion. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were determined for regions of interest (ROI) defined by a standard white-matter atlas that included 21 bilateral ROIs. For each ROI pair, bilateral correlation coefficients were calculated and compared between the two subject groups. A symmetry index, defined as the ratio between the difference and the sum of bilateral measures, was also calculated for each ROI pair and compared between the groups. We found that in normal subjects, the extent of symmetry varied among regions and individuals, and at least subtle forms of structural lateralization were common across regions. In patients, higher asymmetry was found overall as well as in the corticospinal tract specifically. Results indicate that a concussion can manifest in brain asymmetry that deviates from a normal state. The clinical utility of characterizing post-concussion pathology as abnormal brain asymmetry merits further exploration.

Fluoride Exposure and neurodevelopmental outcomes among children in the United States: A pilot study

Background/Aim: Developmental neurotoxicity of fluoride has been demonstrated in animal studies. Additionally, fluoride exposure during prenatal development, infancy, middle-to-late childhood and adolescence has been associated with poorer neurodevelopmental outcomes among children in Mexico and/or Canada. However, potential impacts of chronic low-level fluoride exposure in early childhood on brain structure and neurodevelopment remain relatively unexamined. We conducted the first United States (US) study to examine associations of early childhood urinary fluoride levels with measures of attention and executive function, as well as changes in white matter (WM) microstructure in the brain.Methods: This community-based sample included 31 children ages 4-6-years recruited from New York City. Executive function was assessed with the Behavior Rating Inventory of Executive Function (BRIEF) and attention and behavior were assessed with the Child Behavior Checklist (CBCL). We assessed whole brain WM microstructure integrity using diffusion tensor imaging (DTI). We applied linear regression to examine associations of urine fluoride with measures of attention, behavior and executive functioning, as well as fractional anisotropy (FA), a common DTI measurement of WM integrity. Urine fluoride concentrations were adjusted for specific gravity to correct for dilution (UFSG). Regression models were adjusted for a priori covariates including age, sex and race. Results: The median (IQR) urine fluoride level was 0.72 (0.49) mg/L. Most children scored within the normal and non-clinical range on measures of attention, behavior and executive function. We did not observe significant associations between UFSG and any of the behavioral outcomes assessed; however, higher UFSG was significantly associated with decreased FA in the dorsolateral prefrontal cortex (p&lt;0.05 fdr adjusted for multiple comparisons, cluster size = 56 voxels).Conclusions: Early childhood fluoride exposure may contribute to subclinical changes in brain regions implicated in executive functioning. Future prospective studies are needed to examine behavioral consequences of these neurological changes.

Synchronous nonmonotonic changes in functional connectivity and white matter integrity in a rat model of sporadic Alzheimer's disease

Brain glucose hypometabolism has been singled out as an important contributor and possibly main trigger to Alzheimer's disease (AD). Intracerebroventricular injections of streptozotocin (icv-STZ) cause brain glucose hypometabolism without systemic diabetes. Here, a first-time longitudinal study of brain glucose metabolism, functional connectivity and white matter microstructure was performed in icv-STZ rats using PET and MRI. Histological markers of pathology were tested at an advanced stage of disease. STZ rats exhibited altered functional connectivity and intra-axonal damage and demyelination in brain regions typical of AD, in a temporal pattern of acute injury, transient recovery/compensation and chronic degeneration. In the context of sustained glucose hypometabolism, these nonmonotonic trends – also reported in behavioral studies of this animal model as well as in human AD – suggest a compensatory mechanism, possibly recruiting ketone bodies, that allows a partial and temporary repair of brain structure and function. The early acute phase could thus become a valuable therapeutic window to strengthen the recovery phase and prevent or delay chronic degeneration, to be considered both in preclinical and clinical studies of AD. In conclusion, this work reveals the consequences of brain insulin resistance on structure and function, highlights signature nonmonotonic trajectories in their evolution and proposes potent MRI-derived biomarkers translatable to human AD and diabetic populations.

Dietary patterns, cognitive function, and structural neuroimaging measures of brain aging.

To examine the cross-sectional associations between dietary patterns and cognitive and neuroimaging indices of brain health concurrently in the same sample of healthy older adults. Dietary patterns were derived from a 130-item food frequency questionnaire for 511 individuals in the Lothian Birth Cohort 1936 (mean age 79.3±0.6years). Composite scores for global cognitive function, visuospatial ability, processing speed, memory, and verbal ability were assessed. Brain volumes and white matter microstructure were assessed in participants (n=358) who also underwent structural magnetic resonance imaging. A Mediterranean-style dietary pattern and a processed dietary pattern were identified using principal component analysis of food frequency questionnaire items. In fully-adjusted linear regression models, adherence to the Mediterranean-style pattern was associated with better verbal ability (β=0.121, P=0.002). Associations with global cognitive function (β=0.094, P=0.043), visuospatial ability (β=0.113, P=0.019), and memory (β=0.105, P=0.029) did not survive correction for multiple comparisons. Associations between the processed pattern and lower cognitive scores were attenuated by around 50% following adjustment for prior (childhood) cognitive ability; only an association with verbal ability remained (β=-0.130, P=0.001). Neither dietary pattern was associated with brain volumes or white matter microstructure. Specific Mediterranean diet features-green leafy vegetables and a low intake of red meat-were associated with better cognitive functioning. These observational findings suggest that adherence to a Mediterranean-style diet is associated with better cognitive functioning, but not better brain structural integrity, in older adults.