Putamen Volume Research Articles

Deep Learning for Ultra High Resolution T2‐weighted 7 Tesla Ex vivo Magnetic Resonance Imaging Reveals Differential Subcortical Atrophy across Neurodegenerative Diseases

AbstractBackgroundEx vivo magnetic resonance imaging (MRI) of the brain provides remarkable advantages over in vivo MRI for linking neuroanatomy and morphometry to underlying pathology (Yushkevich et al. 2021, Ravikumar et al. 2021). Subcortical structures show atrophy in certain neurodegenerative diseases, especially Frontotemporal Lobar Degeneration with TDP‐43 (FTLD‐TDP) and four‐repeat (4R) tauopathies (i.e., Corticobasal Degeneration, Progressive Supranuclear Palsy) (Miletić et al. 2022), yet few methods exist to measure subcortical atrophy in ex vivo MRI. We present a framework to quantify subcortical morphometry using 7 Tesla ex vivo MRI and distinguish atrophy patterns across neurodegenerative spectrums.MethodA deep learning method, nnU‐Net (Isensee et al. 2021), was trained on manual segmentations from only 3 brain hemispheres to obtain automated segmentations of 4 subcortical structures (caudate, putamen, globus pallidus, thalamus) across 38 subjects spanning Alzheimer's Disease (AD), Lewy Body Disease (LBD), FTLD‐TDP, 4R tauopathies and miscellaneous tauopathies (Figure 1, Table 1). Subcortical volumes were extracted from automated segmentations. Cerebral cortical volume was computed via cortical segmentation method in Khandelwal et al. 2021. Regional volumes were evaluated via likelihood ratio tests (Figure 2), adjusted for covariates (age, sex and intracranial volume from in vivo MRI) and multiple tests. Separately, correlations were computed between subcortical volumes, cortical thicknesses at 18 landmark locations and neuropathological ratings (Khandelwal et al. 2021, Wisse et al. 2021, Figure 3).ResultThe pipeline validated regional volumetric relationships in neurodegeneration. Global cortex volume did not significantly differ among disease groups (Figure 2). Compared to AD, FTLD‐TDP had significantly lower putamen and thalamus volumes while 4R tauopathies had reduced putamen and caudate volumes (P’s<0.05, adjusted for covariates/multiple comparisons). Before multiple tests correction, there were decreased covariate‐adjusted volumes in globus pallidus and caudate in FTLD‐TDP and thalamus in 4R tauopathy relative to AD. Subcortical volumes correlated with each other (P’s<0.05) but not with cortical thickness, with trends in motor cortex (Figure 3). Subcortical volumes also trended with local tau pathology (Figure 4).ConclusionOur ex vivo neuroimaging framework differentiates subcortical atrophy patterns in FTLD‐TDP and 4R tauopathies compared to AD, highlighting utility in ex vivo imaging for diagnosing and investigating neurodegeneration.

Subcortical brain structure and APOE genotype: An analysis of 43,000 participants from the UK Biobank

AbstractBackgroundCarriers of the ε4 allele of the apolipoprotein (APOE) gene are at higher risk for developing Alzheimer’s disease (AD). In individuals with mild cognitive impairment or AD, the ε4 allele is associated with lower hippocampal and amygdala volumes. How ε4 affects brain structure in healthy individuals before AD symptom onset is less clear. APOE ε2 allele carriers may show slower rates of hippocampal volume loss, suggesting protection against AD. In this large‐scale analysis, we plot normative regional brain volume trajectories in adults (45‐82 years) and map regional subcortical volume differences between APOE genotypes.MethodWe used FreeSurfer 7.1 to segment average left and right accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus and lateral ventricle volumes from T1‐weighted brain MRI (N=43,000). Comparisons between APOE genotypes (ε2ε2, n=257; ε2ε3, n=5,479; ε3ε3, n=26,016; ε3ε4, n=10,263; ε4ε4, n=985) were made using linear mixed effect models, correcting for population structure, age, sex, and intracranial volume (ICV) as fixed effects, and site as a random effect. Results were adjusted for multiple comparisons (FDR q<0.05). Nomograms were derived by adjusting subcortical volumes for population structure, ICV, and site then fitting normative quantile regression models based on the standardized residuals for each region stratified by genotype.ResultNomograms showed similar age‐related trajectories for all APOE genotypes, with smaller gray matter volume and larger ventricle volumes with increasing age. Significantly smaller amygdala and hippocampal volumes were found in ε4ε4 compared to ε3ε4, ε3ε3, and ε2ε3 carriers, and smaller amygdala volumes in ε2ε2 versus ε3ε3 carriers. Smaller accumbens volumes were found in ε4ε4 carriers versus ε2ε3 and ε3ε3, and in ε3ε4 versus ε3ε3 and ε2ε3. Smaller thalamus volumes were found in ε3ε4 versus ε2ε3 and ε3ε3, ε4ε4 carriers had smaller volumes versus ε2ε3 and ε3ε3, and ε2ε2 carriers had smaller volumes versus ε2ε3 and ε3ε3.ConclusionIn this large sample of generally healthy individuals, APOE ε4 allele carriers exhibited lower subcortical volumes compared to those with more neutral AD genetic risk background (ε3ε3). Carriers of ε2ε2 had smaller thalamus and amygdala volumes compared to ε3ε3, suggesting differential effects of AD genetic risk across brain structures known to play a role in AD pathophysiology.

Multisite test-retest reliability and compatibility of brain metrics derived from FreeSurfer versions 7.1, 6.0, and 5.3.

Automatic neuroimaging processing tools provide convenient and systematic methods for extracting features from brain magnetic resonance imaging scans. One tool, FreeSurfer, provides an easy-to-use pipeline to extract cortical and subcortical morphometric measures. There have been over 25 stable releases of FreeSurfer, with different versions used across published works. The reliability and compatibility of regional morphometric metrics derived from the most recent version releases have yet to be empirically assessed. Here, we used test-retest data from three public data sets to determine within-version reliability and between-version compatibility across 42 regional outputs from FreeSurfer versions 7.1, 6.0, and 5.3. Cortical thickness from v7.1 was less compatible with that of older versions, particularly along the cingulate gyrus, where the lowest version compatibility was observed (intraclass correlation coefficient 0.37-0.61). Surface area of the temporal pole, frontal pole, and medial orbitofrontal cortex, also showed low to moderate version compatibility. We confirm low compatibility between v6.0 and v5.3 of pallidum and putamen volumes, while those from v7.1 were compatible with v6.0. Replication in an independent sample showed largely similar results for measures of surface area and subcortical volumes, but had lower overall regional thickness reliability and compatibility. Batch effect correction may adjust for some inter-version effects when most sites are run with one version, but results vary when more sites are run with different versions. Age associations in a quality controlled independent sample (N= 106) revealed version differences in results of downstream statistical analysis. We provide a reference to highlight the regional metrics that may yield recent version-related inconsistencies in published findings. An interactive viewer is provided at http://data.brainescience.org/Freesurfer_Reliability/.

Brain volume in Tanzanian children with sickle cell anaemia: Aneuroimaging study.

Brain injury is a common complication of sickle cell anaemia (SCA). White matter (WM) and cortical and subcortical grey matter (GM), structures may have reduced volume in patients with SCA. This study focuses on whether silent cerebral infarction (SCI), vasculopathy or anaemia affects WM and regional GM volumes in children living in Africa. Children with SCA (n=144; aged 5-20 years; 74 male) and sibling controls (n=53; aged 5-17 years; 29 male) underwent magnetic resonance imaging. Effects of SCI (n=37), vasculopathy (n=15), and haemoglobin were assessed. Compared with controls, after adjusting for age, sex and intracranial volume, patients with SCA had smaller volumes for WM and cortical, subcortical and total GM, as well as bilateral cerebellar cortex, globus pallidus, amygdala and right thalamus. Left globus pallidus volume was further reduced in patients with vasculopathy. Putamen and hippocampus volumes were larger in patients with SCA without SCI or vasculopathy than in controls. Significant positive effects of haemoglobin on regional GM volumes were confined to the controls. Patients with SCA generally have reduced GM volumes compared with controls, although some subcortical regions may be spared. SCI and vasculopathy may affect the trajectory of change in subcortical GM and WM volume. Brain volume in non-SCA children may be vulnerable to contemporaneous anaemia.

Putamen Atrophy Is a Possible Clinical Evaluation Index for Parkinson's Disease Using Human Brain Magnetic Resonance Imaging.

Parkinson's disease is characterized by motor dysfunction caused by functional deterioration of the substantia nigra. Lower putamen volume (i.e., putamen atrophy) may be an important clinical indicator of motor dysfunction and neurological symptoms, such as autonomic dysfunction, in patients with Parkinson's disease. We proposed and applied a new evaluation method for putamen volume measurement on 31 high-resolution T2-weighted magnetic resonance images from 16 patients with Parkinson's disease (age, 80.3 ± 7.30 years; seven men, nine women) and 30 such images from 19 control participants (age, 75.1 ± 7.85 years; eleven men, eight women). Putamen atrophy was expressed using a ratio based on the thalamus. The obtained values were used to assess differences between the groups using the Wilcoxon rank-sum test. The intraclass correlation coefficient showed sufficient intra-rater reliability and validity of this method. The Parkinson's disease group had a significantly lower mean change ratio in the putamen (0.633) than the control group (0.719), suggesting that putamen atrophy may be identified using two-dimensional images. The evaluation method presented in this study may indicate the appearance of motor dysfunction and cognitive decline and could serve as a clinical evaluation index for Parkinson's disease.

Effect of comorbid Parkinson's disease and Parkinson's disease dementia on the course of idiopathic normal pressure hydrocephalus.

The objective of this study was to analyze the effect of concomitant Parkinson's disease (PD) and PD dementia (PD/PDD) on the course of idiopathic normal pressure hydrocephalus (iNPH), especially as related to the outcome of lumboperitoneal shunt (LPS) surgery. The authors retrospectively analyzed patients with iNPH without accompanying disorders (iNPH alone [iNPHa]) and iNPH concomitant with PD/PDD (iNPHc+PD/PDD) who had presented to their department between 2010 and 2019. The diagnosis of iNPHc+PD/PDD was established using the diagnostic criteria of the Movement Disorder Society. The effect of LPS surgery on clinical symptoms and striatum volumes was evaluated. Thirty-three patients with iNPHa and 23 patients with iNPHc+PD/PDD were identified. Comorbid PD/PDD significantly worsened clinical outcome as measured by the iNPH grading scale, modified Rankin Scale (mRS), and Hoehn and Yahr (HY) scale. LPS surgery improved the iNPH score including gait disturbance (p < 0.01), cognitive impairment (p = 0.02), and urinary disturbance (p < 0.01) in iNPHa and improved gait disturbance (p = 0.01) and urinary disturbance (p = 0.03) in iNPHc+PD/PDD for 1 year. Comorbid synucleinopathies maintained worse mRS scores and HY stages for 3 years, and LPS surgery extended overall survival (p = 0.003), as well as the period of sustained mRS scores (p = 0.04) and HY stages (p = 0.004) in iNPHc+PD/PDD. Both caudate and putamen volumes were reduced in iNPHa (p < 0.01) compared to those in controls and in patients with iNPHc+PD/PDD compared to those in patients with PD/PDD (p < 0.01), and LPS surgery restored caudate volumes in both groups. These results revealed that comorbid PD/PDD deteriorates the clinical course of iNPH and that LPS surgery is recommended regardless of this comorbidity.

The relationship between metabolic control and basal ganglia morphometry and function in individuals with early-treated phenylketonuria.

Abnormalities of the cortical white matter are the most prominent and widely-reported neurological findings in individuals with early-treated phenylketonuria (ETPKU). Much less is known regarding the effects of ETPKU on gray matter structures in the brain such as the basal ganglia. Previous findings on basal ganglia in ETPKU have been mixed. The current study was designed to further elucidate the effects of ETPKU and elevated phe levels on the morphometry of basal ganglia structures (i.e., putamen, caudate nucleus, nucleus accumbens, and globus pallidus). High resolution magnetic resonance imaging (MRI) data was collected from a sample of 37 adults with ETPKU and a demographically-matched comparison group of 33 individuals without PKU. No overall group differences (ETPKU vs. non-PKU) in basal ganglia volumes were observed. However, within the ETPKU group, poorer metabolic control (as reflected by higher blood phenylalanine levels) was associated with larger putamen volume. Vertex-wise shape analysis revealed that the volume increase was accompanied by shape changes in the middle left putamen. Consistent with this area's role in motor control, a significant correlation between left putamen volume and motor performance was also observed. Additional research is needed to fully understand the cellular level processes underlying this effect as well as to better understand the clinical impact of these morphometric changes and their potential relation to treatment response.

Association between body mass index and subcortical volume in pre-adolescent children with autism spectrum disorder: An exploratory study.

Conflicting associations exist between autism spectrum disorder (ASD) and subcortical brain volumes. This study assessed whether obesity might have a confounding influence on associations between ASD and brain subcortical volumes. A comprehensive investigation evaluating the relationship between ASD, obesity, and subcortical structure volumes was conducted. Data obtained included body mass index (BMI) and T1-weighted structural magnetic resonance images for children with and without ASD diagnoses from the Autism Brain Imaging Data Exchange database. Brain subcortical volumes were calculated using vol2Brain software. Hierarchical linear regression analyses were performed to explore the subcortical volumes similarly or differentially associated with BMI in children with or without ASD and examine association and interaction effects regarding ASD and subcortical volume impact on the Social Responsiveness Scale and Vineland Adaptive Behavior Scale (VABS) scores. Bilateral caudate nuclei were smaller in children with ASD than in control participants. Significant interactions were observed between ASD diagnosis and BMI regarding the left caudate, right and left putamen, and right and left ventral diencephalon (DC) volumes (β=-0.384, p=0.010; β=-0.336, p=0.030; β=-0.317, p=0.040; β=0.322, p=0.010; β=0.295, p=0.021, respectively) and between ASD diagnosis and right and left ventral DC volumes regarding the VABS scores (β=0.434, p=0.014; β=0.495, p=0.007, respectively). However, each subcortical structure volume included in the ventral DC area could not be measured separately. The results identified subcortical volumes differentially associated with obesity in children with ASD compared with typically developing peers. BMI may need to be considered an important confounder in future research examining brain subcortical volumes within ASD.

Predictive models demonstrate age-dependent association of subcortical volumes and cognitive measures.

Whether brain matter volume is correlated with cognitive functioning and higher intelligence is controversial. We explored this relationship by analysis of data collected on 193 healthy young and older adults through the "Leipzig Study for Mind-Body-Emotion Interactions" (LEMON) study. Our analysis involved four cognitive measures: fluid intelligence, crystallized intelligence, cognitive flexibility, and working memory. Brain subregion volumes were determined by magnetic resonance imaging. We normalized each subregion volume to the estimated total intracranial volume and conducted training simulations to compare the predictive power of normalized volumes of large regions of the brain (i.e., gray matter, cortical white matter, and cerebrospinal fluid), normalized subcortical volumes, and combined normalized volumes of large brain regions and normalized subcortical volumes. Statistical tests showed significant differences in the performance accuracy and feature importance of the subregion volumes in predicting cognitive skills for young and older adults. Random forest feature selection analysis showed that cortical white matter was the key feature in predicting fluid intelligence in both young and older adults. In young adults, crystallized intelligence was best predicted by caudate nucleus, thalamus, pallidum, and nucleus accumbens volumes, whereas putamen, amygdala, nucleus accumbens, and hippocampus volumes were selected for older adults. Cognitive flexibility was best predicted by the caudate, nucleus accumbens, and hippocampus in young adults and caudate and amygdala in older adults. Finally, working memory was best predicted by the putamen, pallidum, and nucleus accumbens in the younger group, whereas amygdala and hippocampus volumes were predictive in the older group. Thus, machine learning predictive models demonstrated an age-dependent association between subcortical volumes and cognitive measures. These approaches may be useful in predicting the likelihood of age-related cognitive decline and in testing of approaches for targeted improvement of cognitive functioning in older adults.

Glucometabolic Changes Are Associated with Structural Gray Matter Alterations in Prodromal Dementia.

Glucometabolic changes, such as high glycemic load (GL) diet and insulin resistance (IR), are potential risk factor of Alzheimer's disease (AD). Yet, the effect of these factors on brain alterations that contribute to AD pathology has not been clearly demonstrated. We aimed to assess the relationship of GL and IR with gray matter volumes involved in prodromal dementia. GL and Triglyceride-Glucose (TyG) index, an IR surrogate marker, were calculated in 497 participants who underwent magnetic resonance imaging (MRI). The gray matter volumes most related to prodromal dementia/mild cognitive impairment (diagnosed in 18/158 participants during the 7-year follow-up) were identified using a data-driven machine learning algorithm. Higher GL diet was associated with reduced amygdala volume. The TyG index was negatively associated with the hippocampus, amygdala, and putamen volumes. These results suggest that GL and IR are associated with lower gray matter volumes in brain regions involved in AD pathology.

Contralesional macrostructural plasticity in patients with frontal low-grade glioma: a voxel-based morphometry study.

Neuroplasticity can partially compensate for the neurological deficits caused by brain tumors. However, the structural plasticity of the brain caused by brain tumors is not fully understood. This study aimed to assess the structural plasticity of the contralesional hemisphere in patients with frontal low-grade gliomas (LGGs). A total of 25 patients with left frontal LGGs (LFLGGs), 19 patients with right frontal LGGs (RFLGGs), and 25 healthy controls (HCs) were enrolled in this study. High-resolution structural T1-weighted imaging and fluid attenuation inversion recovery were performed on all participants. Voxel-based morphometry (VBM) analysis was used to detect differences in the brain structural plasticity between patients with unilateral LGGs and HCs. VBM analysis revealed that compared with HCs, the gray matter volume (GMV) of the contralesional putamen and amygdala was significantly smaller and larger in the patients with RFLGGs and LFLGGs, respectively, while the GMVs of the contralesional cuneus and superior temporal gyrus (STG) were significantly larger in the patients with LFLGGs. The surviving clusters of the right hemisphere included 1357 voxels in the amygdala, 1680 voxels in the cuneus, 384 voxels in the STG, and 410 voxels in the putamen. The surviving clusters of the left hemisphere were 522 voxels in the amygdala and 320 voxels in the putamen. The unilateral frontal LGGs are accompanied by structural plasticity in the contralesional cortex and vary with tumor laterality. Contralesional structural reorganization may be one of the physiological basis for functional reorganization or compensation in the frontal LGGs.

Toward More Accessible Fully Automated 3D Volumetric MRI Decision Trees for the Differential Diagnosis of Multiple System Atrophy, Related Disorders, and Age-Matched Healthy Subjects.

Differentiating multiple system atrophy (MSA) from related neurodegenerative movement disorders (NMD) is challenging. MRI is widely available and automated decision-tree analysis is simple, transparent, and resistant to overfitting. Using a retrospective cohort of heterogeneous clinical MRIs broadly sourced from a tertiary hospital system, we aimed to develop readily translatable and fully automated volumetric diagnostic decision-trees to facilitate early and accurate differential diagnosis of NMDs. 3DT1 MRI from 171 NMD patients (72 MSA, 49 PSP, 50 PD) and 171 matched healthy subjects were automatically segmented using Freesurfer6.0 with brainstem module. Decision trees employing substructure volumes and a novel volumetric pons-to-midbrain ratio (3D-PMR) were produced and tenfold cross-validation performed. The optimal tree separating NMD from healthy subjects selected cerebellar white matter, thalamus, putamen, striatum, and midbrain volumes as nodes. Its sensitivity was 84%, specificity 94%, accuracy 84%, and kappa 0.69 in cross-validation. The optimal tree restricted to NMD patients selected 3D-PMR, thalamus, superior cerebellar peduncle (SCP), midbrain, pons, and putamen as nodes. It yielded sensitivities/specificities of 94/84% for MSA, 72/96% for PSP, and 73/92% PD, with 79% accuracy and 0.62 kappa. There was correct classification of 16/17 MSA, 5/8 PSP, 6/8 PD autopsy-confirmed patients, and 6/8 MRIs that preceded motor symptom onset. Fully automated decision trees utilizing volumetric MRI data distinguished NMD patients from healthy subjects and MSA from other NMDs with promising accuracy, including autopsy-confirmed and pre-symptomatic subsets. Our open-source methodology is well-suited for widespread clinical translation. Assessment in even more heterogeneous retrospective and prospective cohorts is indicated.

Pathological fear, anxiety and negative affect exhibit distinct neurostructural signatures: evidence from psychiatric neuroimaging meta-analysis

Internalizing disorders encompass anxiety, fear and depressive disorders, which exhibit overlap at both conceptual and symptom levels. Given that a neurobiological evaluation is lacking, we conducted a Seed-based D-Mapping comparative meta-analysis including coordinates as well as original statistical maps to determine common and disorder-specific gray matter volume alterations in generalized anxiety disorder (GAD), fear-related anxiety disorders (FAD, i.e., social anxiety disorder, specific phobias, panic disorder) and major depressive disorder (MDD). Results showed that GAD exhibited disorder-specific altered volumes relative to FAD including decreased volumes in left insula and lateral/medial prefrontal cortex as well as increased right putamen volume. Both GAD and MDD showed decreased prefrontal volumes compared to controls and FAD. While FAD showed less robust alterations in lingual gyrus compared to controls, this group presented intact frontal integrity. No shared structural abnormalities were found. Our study is the first to provide meta-analytic evidence for distinct neuroanatomical abnormalities underlying the pathophysiology of anxiety-, fear-related and depressive disorders. These findings may have implications for determining promising target regions for disorder-specific neuromodulation interventions (e.g. transcranial magnetic stimulation or neurofeedback).

Air pollution, white matter microstructure, and brain volumes: Periods of susceptibility from pregnancy to preadolescence

Air pollution exposure during early-life is associated with altered brain development, but the precise periods of susceptibility are unknown. We aimed to investigate whether there are periods of susceptibility of air pollution between conception and preadolescence in relation to white matter microstructure and brain volumes at 9–12 years old. We used data of 3515 children from the Generation R Study, a population-based birth cohort from Rotterdam, the Netherlands (2002–2006). We estimated daily levels of nitrogen dioxide (NO2), and particulate matter (PM2.5 and PM2.5absorbance) at participants’ homes during pregnancy and childhood using land-use regression models. Diffusion tensor and structural brain images were obtained when children were 9–12 years of age, and we calculated fractional anisotropy and mean diffusivity, and several brain structure volumes. We performed distributed lag non-linear modeling adjusting for socioeconomic and lifestyle characteristics. We observed specific periods of susceptibility to all air pollutants from conception to age 5 years in association with lower fractional anisotropy and higher mean diffusivity that survived correction for multiple testing (e.g., −0.85 fractional anisotropy (95%CI -1.43; −0.27) per 5 μg/m3 increase in PM2.5 between conception and 4 years of age). We also observed certain periods of susceptibility to some air pollutants in relation to global brain and some subcortical brain volumes, but only the association between PM2.5 and putamen survived correction for multiple testing (172 mm3 (95%CI 57; 286) per 5 μg/m3 increase in PM2.5 between 4 months and 1.8 year of age). This study suggested that conception, pregnancy, infancy, toddlerhood, and early childhood seem to be susceptible periods to air pollution exposure for the development of white matter microstructure and the putamen volume. Longitudinal studies with repeated brain outcome measurements are needed for understanding the trajectories and the long-term effects of exposure to air pollution.

Smaller putamen volumes are associated with greater problems in external emotional regulation in depressed adolescents with nonsuicidal self-injury

The functions of nonsuicidal self-injury (NSSI) consist of social and emotional aspects (Social influence, Sensation seeking, Internal and External emotion regulation). Previous studies have indicated that dysfunction in reward-related brain structures especially the striatum might drive this habitual behavior. However, no studies to date have investigated the associations between striatum and different functions for adolescents engaging in NSSI behaviors. Here, we recruited 35 depressed adolescents with recent NSSI behaviors and 36 healthy controls and acquired structural brain images, depressive symptoms, social, academic and family environments assessments, in addition to NSSI functions in patients only. Subcortical volumes and cortical thickness were estimated with FreeSurfer. Mixed linear regressions were performed to examine associations between striatal structures (caudate, putamen, nucleus accumbens, pallidum) and NSSI functions, with age, sex, total intracranial volume, hemisphere and depression severity included as covariates. Effect of environmental factors and potential associations with cortical thickness and other subcortical volumes were also tested. We found that, among the four functions, external emotional regulation represented the main function for NSSI engagement. Increased external emotion regulation was significantly associated with smaller putamen volume. No environmental factors biased the association with putamen. No associations with other cortical or subcortical regions were observed. Our findings suggested that smaller putamen might be a biomarker of NSSI engagement for depressed adolescents when they regulated frustrated or angry emotions. The results have potentially clinical implications in early identification and brain intervention of NSSI in youth.

Outdoor residential air pollution exposure and the development of brain morphology across childhood: a longitudinal study

Background and aim: Emerging evidence suggests a relationship between exposure to air pollution and brain morphology in children, but little is known about how air pollution exposure influences the development of brain structures throughout childhood. We aim to study the association of air pollution exposure during pregnancy and childhood with the development of brain morphology from age 6-16 years. Methods: We used data from 4,243 children of the Generation R study, a birth cohort in Rotterdam, the Netherlands. We estimated the concentrations of fourteen air pollutants at participant´s home addresses during pregnancy and childhood, using land use regression models. We included structural brain images at three time points, namely at age 6-10 years, 9-12 years, and 13-16 years. We assessed the association between the air pollutants and brain volumes with linear mixed models, fitting an interaction term for age and each pollutant. Models were adjusted for socioeconomic status and lifestyle characteristics. Results: Higher air pollution exposure during pregnancy was associated with a slower decrease of cortical grey matter volume starting at around age 10 and a slower increase of corpus callosum volume (e.g. -12.7 mm3 increase in corpus callosum volume [95%CI -22.0; -3.3] with each year of age per 10 &amp;#x3bc;g/m3 increase in nitrogen dioxide exposure). Childhood exposure was associated with a faster decrease of putamen and caudate nucleus volume, and a slower increase of hippocampus volume. Higher exposure to air pollution during pregnancy and childhood was associated with a slower increase of thalamus volume. Air pollution exposure was not associated with cerebellum, amygdala, nucleus accumbens or globus pallidus volume. Conclusions: Air pollution exposure was associated with region-specific differences in age-related growth trajectories. Air pollution exposure during childhood might affect different brain regions than exposure during pregnancy. Keywords: air pollution, neurodevelopment, children, traffic

Relationship between CSF tau biomarkers and structural brain MRI measures in frontotemporal lobar degeneration

BackgroundRecently in the field neurodegenerative diseases increasing attention has been pointed to CSF biomarkers and their integration with neuroimaging (1). Frontotemporal lobar degeneration (FTLD) refers to a heterogeneous group of clinical syndromes with different underlying proteinopathies including tau pathology. CSF biomarkers have been proposed as diagnostic and prognostic factors. Aim of our study was to evaluate the relationship between CSF tau biomarkers and structural MRI brain measures in FTLD. MethodsWe included early FTLD patient. All included patients underwent lumbar puncture to evaluate amyloid, total-tau (t-tau), phospho-tau 181 (p-tau); p-tau/t-tau ratio was also calculated; brain MRI was performed to estimate whole brain volume, volume of principal deep grey matter structures and regional cortical thickness. ResultsDemographic characteristics of the 28 included patients were as follows: female/male: 9/19; mean ± SD age: 68.1 ± 7.8 years. The p-tau/t-tau ratio was significantly correlated with whole brain volume (r = 0.69; p: 0.001), left putamen volume (r = 0.55 p: 0.009), left pallidum volume (r = 0.41; p: 0.01), right accumbens area (r = 0.47; p: 0.02). P-tau/t tau ratio showed also a significant correlation with cortical thickness of left temporal lobe (r = 0.74; p: 0.001) and right lateral orbital frontal cortex (r = 0.45; p: 0.03). Linear regression showed a significant relationship between p-tau/t-tau ratio and left temporal pole (p = 0.01; r2: 0.60) and brain volume (p:0.002; r2: 0.56) after controlling for age and gender. ConclusionsOur data suggest that CSF biomarkers, especially p-tau/t-tau ratio, could play a role as prognostic factor in FTLD. Further longitudinal investigations are needed to confirm these findings.

Distinct brain structural abnormalities in attention-deficit/hyperactivity disorder and substance use disorders: A comparative meta-analysis

As two common mental disorders during the period of adolescence that extend to early adulthood, attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) have considerable diagnostic co-occurrence and shared neuropsychological impairments. Our study aimed to identify overlapping and distinct brain structural abnormalities associated with ADHD and SUDs among adolescents and young adults. A systematic literature search on voxel-based morphometry (VBM) studies of ADHD and SUDs was conducted in PubMed and Web of Science. Data were extracted and analyzed to identify brain abnormalities using Seed-based d-Mapping software. Data-driven functional decoding was conducted to identify the psychophysiological functioning associated with brain alterations. 13 and 14 VBM studies for ADHD (619 patients and 483 controls) and SUDs (516 patients and 413 controls), respectively, were included. Patterns of decreased gray matter volume (GMV) were found in the left precentral gyrus, bilateral superior frontal gyri, and left inferior frontal gyrus in the ADHD group compared to the control group. In contrast, individuals with SUDs, relative to controls, were characterized by increased GMV in the left putamen and insula. Comparative analysis indicated larger regional GMV in the right inferior parietal lobule and smaller volumes in the left putamen and left precentral gyrus in the ADHD group than in the SUDs group. Dissociable brain structural abnormalities in adolescents and young adults with ADHD and SUDs potentially implicate different pathogeneses and provide a reference for differential diagnosis and early detection for shared symptomology and comorbidity.

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence.

Background: Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14–15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16–17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = −0.181, r = −0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = −0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = −0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic–striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals.

Associations of medication with subcortical morphology across the lifespan in OCD: Results from the international ENIGMA Consortium

BackgroundWidely used psychotropic medications for obsessive-compulsive disorder (OCD) may change the volumes of subcortical brain structures, and differently in children vs. adults. We measured subcortical volumes cross-sectionally in patients finely stratified for age taking various common classes of OCD drugs. MethodsThe ENIGMA-OCD consortium sample (1081 medicated/1159 unmedicated OCD patients and 2057 healthy controls aged 6–65) was divided into six successive 6–10-year age-groups. Individual structural MRIs were parcellated automatically using FreeSurfer into 8 regions-of-interest (ROIs). ROI volumes were compared between unmedicated and medicated patients and controls, and between patients taking serotonin reuptake inhibitors (SRIs), tricyclics (TCs), antipsychotics (APs), or benzodiazepines (BZs) and unmedicated patients. ResultsCompared to unmedicated patients, volumes of accumbens, caudate, and/or putamen were lower in children aged 6–13 and adults aged 50–65 with OCD taking SRIs (Cohen's d = −0.24 to −0.74). Volumes of putamen, pallidum (d = 0.18–0.40), and ventricles (d = 0.31–0.66) were greater in patients aged 20–29 receiving APs. Hippocampal volumes were smaller in patients aged 20 and older taking TCs and/or BZs (d = −0.27 to −1.31). ConclusionsResults suggest that TCs and BZs could potentially aggravate hippocampal atrophy of normal aging in older adults with OCD, whereas SRIs may reduce striatal volumes in young children and older adults. Similar to patients with psychotic disorders, OCD patients aged 20–29 may experience subcortical nuclear and ventricular hypertrophy in relation to APs. Although cross-sectional, present results suggest that commonly prescribed agents exert macroscopic effects on subcortical nuclei of unknown relation to therapeutic response.