Gray Matter Alterations Research Articles

Brain microstructural changes in essential tremor patients and correlations with clinical characteristics: a diffusion kurtosis imaging study.

Essential tremor (ET) is the second most common movement disorder; however, the pathophysiological mechanism of ET is unclear. We aimed to investigate the microstructural degeneration of gray matter (GM) and white matter (WM) and their correlations with cognition and tremor in patients with ET. The participants were 63 patients with ET and 63 matched healthy controls (HCs) who underwent 3D-T1 weighted and diffusion kurtosis images (DKI). Microstructural degeneration was measured using high-level diffusion parameters derived from DKI. A voxel-wise analysis of the means of the GM-based spatial statistics and tract-based spatial statistics were conducted to assess differences in diffusion parameters between the ET and HC groups. The volume differences between the two groups were also assessed, and tremor severity and multi-domain cognitive performance were evaluated. Finally, the relationship between microstructural degeneration and clinical characteristics were assessed. The ET group had significantly lower mean kurtosis of the temporal, parietal, and occipital lobes and the cerebellum and lower radial kurtosis in several tracts. These microstructural changes in GM and WM were correlated with tremor and cognitive scores. However, no significant difference in volume was found between the groups. Our findings suggest that ET entails extensive GM and WM microstructural alterations, which support the neurodegenerative hypothesis of ET. Our study contributes to a better understanding of the mechanisms underlying tremor and cognitive impairment in ET.

Spatial patterns of gray and white matter compromise relate to age of seizure onset in temporal lobe epilepsy

ObjectiveTemporal Lobe Epilepsy (TLE) is frequently a neurodevelopmental disorder, involving subcortical volume loss, cortical atrophy, and white matter (WM) disruption. However, few studies have addressed how these pathological changes in TLE relate to one another. In this study, we investigate spatial patterns of gray and white matter degeneration in TLE and evaluate the hypothesis that the relationship among these patterns varies as a function of the age at which seizures begin. MethodsEighty-two patients with TLE and 59 healthy controls were enrolled. T1-weighted images were used to obtain hippocampal volumes and cortical thickness estimates. Diffusion-weighted imaging was used to obtain fractional anisotropy (FA) and mean diffusivity (MD) of the superficial WM (SWM) and deep WM tracts. Analysis of covariance was used to examine patterns of WM and gray matter alterations in TLE relative to controls, controlling for age and sex. Sliding window correlations were then performed to examine the relationships between SWM degeneration, cortical thinning, and hippocampal atrophy across ages of seizure onset. ResultsCortical thinning in TLE followed a widespread, bilateral pattern that was pronounced in posterior centroparietal regions, whereas SWM and deep WM loss occurred mostly in ipsilateral, temporolimbic regions compared to controls. Window correlations revealed a relationship between hippocampal volume loss and whole brain SWM disruption in patients who developed epilepsy during childhood. On the other hand, in patients with adult-onset TLE, co-occurring cortical and SWM alterations were observed in the medial temporal lobe ipsilateral to the seizure focus. SignificanceOur results suggest that although cortical, hippocampal and WM alterations appear spatially discordant at the group level, the relationship among these features depends on the age at which seizures begin. Whereas neurodevelopmental aspects of TLE may result in co-occurring WM and hippocampal degeneration near the epileptogenic zone, the onset of seizures in adulthood may set off a cascade of SWM microstructural loss and cortical atrophy of a neurodegenerative nature.

Impact of cognition-related single nucleotide polymorphisms on brain imaging phenotype in Parkinson's disease.

Multiple single nucleotide polymorphisms may contribute to cognitive decline in Parkinson's disease. However, the mechanism by which these single nucleotide polymorphisms modify brain imaging phenotype remains unclear. The aim of this study was to investigate the potential effects of multiple single nucleotide polymorphisms on brain imaging phenotype in Parkinson's disease. Forty-eight Parkinson's disease patients and 39 matched healthy controls underwent genotyping and 7T magnetic resonance imaging. A cognitive-weighted polygenic risk score model was designed, in which the effect sizes were determined individually for 36 single nucleotide polymorphisms. The correlations between polygenic risk score, neuroimaging features, and clinical data were analyzed. Furthermore, individual single nucleotide polymorphism analysis was performed to explore the main effects of genotypes and their interactive effects with Parkinson's disease diagnosis. We found that, in Parkinson's disease, the polygenic risk score was correlated with the neural activity of the hippocampus, parahippocampus, and fusiform gyrus, and with hippocampal-prefrontal and fusiform-temporal connectivity, as well as with gray matter alterations in the orbitofrontal cortex. In addition, we found that single nucleotide polymorphisms in α-synuclein (SNCA) were associated with white matter microstructural changes in the superior corona radiata, corpus callosum, and external capsule. A single nucleotide polymorphism in catechol-O-methyltransferase was associated with the neural activities of the lingual, fusiform, and occipital gyri, which are involved in visual cognitive dysfunction. Furthermore, DRD3 was associated with frontal and temporal lobe function and structure. In conclusion, imaging genetics is useful for providing a better understanding of the genetic pathways involved in the pathophysiologic processes underlying Parkinson's disease. This study provides evidence of an association between genetic factors, cognitive functions, and multi-modality neuroimaging biomarkers in Parkinson's disease.

Cerebellar gray matter alterations predict deep brain stimulation outcomes in Meige syndrome

BackgroundThe physiopathologic mechanism of Meige syndrome (MS) has not been clarified, and neuroimaging studies centering on cerebellar changes in MS are scarce. Moreover, even though deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been recognized as an effective surgical treatment for MS, there has been no reliable biomarker to predict its efficacy. ObjectiveTo characterize the volumetric alterations of gray matter (GM) in the cerebellum in MS and to identify GM measurements related to a good STN-DBS outcome. MethodsWe used voxel-based morphometry and lobule-based morphometry to compare the regional and lobular GM differences in the cerebellum between 47 MS patients and 52 normal human controls (HCs), as well as between 31 DBS responders and 10 DBS non-responders. Both volumetric analyses were achieved using the Spatially Unbiased Infratentorial Toolbox (SUIT). Further, we performed partial correlation analyses to probe the relationship between the cerebellar GM changes and clinical scores. Finally, we plotted the receiver operating characteristic (ROC) curve to select biomarkers for MS diagnosis and DBS outcomes prediction. ResultsCompared to HCs, MS patients had GM atrophy in lobule Crus I, lobule VI, lobule VIIb, lobule VIIIa, and lobule VIIIb. Compared to DBS responders, DBS non-responders had lower GM volume in the left lobule VIIIb. Moreover, partial correlation analyses revealed a positive relationship between the GM volume of the significant regions/lobules and the symptom improvement rate after DBS surgery. ROC analyses demonstrated that the GM volume of the significant cluster in the left lobule VIIIb could not only distinguish MS patients from HCs but also predict the outcomes of STN-DBS surgery with high accuracy. ConclusionMS patients display bilateral GM shrinkage in the cerebellum relative to HCs. Regional GM volume of the left lobule VIIIb can be a reliable biomarker for MS diagnosis and DBS outcomes prediction.

Structural gray matter alterations in glioblastoma and high-grade glioma-A potential biomarker of survival.

Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere). Specifically, we examined the prognostic value of widespread alterations of cortical thickness (CT) in GBM/HGG patients. We used FreeSurfer, applied with high-resolution T1-weighted MRI, to examine CT, evaluated prior to standard treatment with surgery and chemoradiation in patients (GBM/HGG, N = 162, mean age 61.3 years) and 127 healthy controls (HC; 61.9 years mean age). We then compared CT in patients to HC and studied patients' associated changes in CT as a potential biomarker of overall survival. Compared to HC cases, patients had thinner gray matter in the contralesional hemisphere at the time of tumor diagnosis. patients had significant cortical thinning in parietal, temporal, and occipital lobes. Fourteen cortical parcels showed reduced CT, whereas in 5, it was thicker in patients' cases. Notably, CT in the contralesional hemisphere, various lobes, and parcels was predictive of overall survival. A machine learning classification algorithm showed that CT could differentiate short- and long-term survival patients with an accuracy of 83.3%. These findings identify previously unnoticed structural changes in the cortex located in the hemisphere contralateral to the primary tumor mass. Observed changes in CT may have prognostic value, which could influence care and treatment planning for individual patients.

Changes in diffusion tensor imaging indices in basal ganglia and thalamus of patients with Relapsing-Remitting Multiple Sclerosis and relation with clinical conditions: A case-control study

BackgroundMultiple sclerosis (MS) is recognized as the most prevalent autoimmune abnormality of the CNS. T1WI, T2WI, and FLAIR are limited in the quantification of tissue damage and detection of tissue alterations in white and grey matter in MS. This study aimed to the evaluation of changes in DTI indices in these patients at the thalamus and basal ganglia. Methods30 relapsing-remitting MS (RRMS) cases and 30 normal individuals were included. Conventional MRI (T2, FLAIR) was acquired to confirm NAGM in MS patients. A T1 MPRAGE protocol was used to normalize DTI images. FSL, SPM, and Explore DTI software were employed to reach Mean Diffusivities (MD), Axial Diffusivities (AD), Fractional anisotropy (FA), and Radial Diffusivity (RD) at the thalamus and the basal ganglia. ResultsThe FA and RD of the thalamus were decreased in healthy controls compared to MS cases (0.319 vs. 0.296 and 0.0009 vs. 0.0006, respectively) (P < 0.05). The AD value in the thalamus and the FA value in the caudate nucleus were significantly lower in MS cases than in controls (0.0009 vs. 0.0011 and 0.16 vs. 0.18, respectively) (P < 0.05). MD values in the thalamus or basal ganglia were not significantly different between groups. ConclusionsDTI measures including FA, RD, and AD have a good diagnostic performance in detecting microstructural changes in the normal-appearing thalamus in cases with RRMS while they had no significant relationship with clinical signs in terms of EDSS. Availability of data and materialNot applicable

Radiomic features of gray matter in never-treated first-episode schizophrenia.

Alterations of radiomic features (RFs) in gray matter are observed in schizophrenia, of which the results may be limited by small study samples and confounding effects of drug therapies. We tested for RFs alterations of gray matter in never-treated first-episode schizophrenia (NT-FES) patients and examined their associations with known gene expression profiles. RFs were examined in the first sample with 197 NT-FES and 178 healthy controls (HCs) and validated in the second independent sample (90 NT-FES and 74 HCs). One-year follow-up data were available from 87 patients to determine whether RFs were associated with treatment outcomes. Associations between identified RFs in NT-FES and gene expression profiles were evaluated. NT-FES exhibited alterations of 30 RFs, with the greatest involvement of microstructural heterogeneity followed by measures of brain region shape. The identified RFs were mainly located in the central executive network, frontal-temporal network, and limbic system. Two baseline RFs with the involvement of microstructural heterogeneity predicted treatment response with moderate accuracy (78% for the first sample, 70% for the second sample). Exploratory analyses indicated that RF alterations were spatially related to the expression of schizophrenia risk genes. In summary, the present findings link brain abnormalities in schizophrenia with molecular features and treatment response.

Sex differences in white matter microstructure in aging and Alzheimer’s disease: A multi‐site free‐water imaging study

AbstractBackgroundSex differences in gray matter alterations in aging and AD have been reported, but there have been few large‐scale studies evaluating white matter microstructure. The goal of this study is to leverage multi‐site harmonized diffusion MRI data in tandem with free‐water (FW) imaging to determine the association between sex and white matter microstructure in aging and AD.MethodThe dataset used in this study leveraged cross‐sectional data from several cohorts of aging [Alzheimer’s Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory &amp; Aging Project (VMAP)]. This dataset included 1,898 participants (72±9 years, 59% female). Data was processed using standard preprocessing techniques and followed up with FW postprocessing. FW and FW‐corrected intracellular metrics of fractional anisotropy (FAT), radial diffusivity (RDT), and axial diffusivity (ADT) were then quantified within seven white matter tractography templates (see Figure 1A) and harmonized using the ComBat technique. The sex differences for each microstructural metric were then determined using a linear regression model covarying for age, diagnosis, education, and APOE‐ε4 carrier status. Secondary analyses were conducted to determine sex x diagnosis interactions on white matter microstructure.ResultWhile we found no sex differences in FW, there were significant associations in all intracellular metrics. Females had significantly lower FAT in the association (pFDR=6.62x10‐10), limbic (pFDR=5.28x10‐9), motor transcallosal (TC) (pFDR=0.008), prefrontal TC (pFDR=6.34x10‐6), and projection (pFDR=4.74x10‐20) tracts and significantly lower ADT in the association (pFDR=5.23x10‐10), limbic (pFDR=1.84x10‐6), prefrontal TC (pFDR=4.41x10‐11), and projection (pFDR=5.29x10‐17) tracts. For RDT, females exhibited higher RDT in all tracts (pFDR range: 4.94x10‐16 – 0.022). Illustrations of these results can be found in Figure 1. Sex differences were compared across cohorts and were similar (Figure 2). The only significant sex x diagnosis interaction was for the projection tract RDT measure (pFDR=0.043, Figure 3).ConclusionThis study suggests intracellular microstructural values (i.e., FAT, ADT, RDT) exhibit strong sex differences, whereby females have lower FAT/ADT and higher RDT compared to males. We also found a sex x diagnosis interaction for projection tract RDT, whereby females with AD exhibited lower RDT, but larger studies with more AD cases would be needed to further explore this finding.

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

BackgroundSince both essential tremor (ET) and Parkinson’s disease (PD) are movement disorders and share similar clinical symptoms, it is very difficult to recognize the differences in the presentation, course, and treatment of ET and PD, which leads to misdiagnosed commonly.PurposeAlthough neuroimaging biomarker of ET and PD has been investigated based on statistical analysis, it is unable to assist the clinical diagnosis of ET and PD and ensure the efficiency of these biomarkers. The aim of the study was to identify the neuroimaging biomarkers of ET and PD based on structural magnetic resonance imaging (MRI). Moreover, the study also distinguished ET from PD via these biomarkers to validate their classification performance.MethodsThis study has developed and implemented a three-level machine learning framework to identify and distinguish ET and PD. First of all, at the model-level assessment, the searchlight-based machine learning method has been used to identify the group differences of patients (ET/PD) with normal controls (NCs). And then, at the feature-level assessment, the stability of group differences has been tested based on structural brain atlas separately using the permutation test to identify the robust neuroimaging biomarkers. Furthermore, the identified biomarkers of ET and PD have been applied to classify ET from PD based on machine learning techniques. Finally, the identified biomarkers have been compared with the previous findings of the biology-level assessment.ResultsAccording to the biomarkers identified by machine learning, this study has found widespread alterations of gray matter (GM) for ET and large overlap between ET and PD and achieved superior classification performance (PCA + SVM, accuracy = 100%).ConclusionsThis study has demonstrated the significance of a machine learning framework to identify and distinguish ET and PD. Future studies using a large data set are needed to confirm the potential clinical application of machine learning techniques to discern between PD and ET.

Brain grey and white matter structural associations with future suicidal ideation and behaviors in adolescent and young adult females with mood disorders.

To reduce suicide in females with mood disorders, it is critical to understand brain substrates underlying their vulnerability to future suicidal ideation and behaviors (SIBs) in adolescence and young adulthood. In an international collaboration, grey and white matter structure was investigated in adolescent and young adult females with future suicidal behaviors (fSB) and ideation (fSI), and without SIBs (fnonSIB). Structural (n = 91) and diffusion-weighted (n = 88) magnetic resonance imaging scans at baseline and SIB measures at follow-up on average two years later (standard deviation, SD = 1 year) were assessed in 92 females [age(SD) = 16.1(2.6) years] with bipolar disorder (BD, 28.3%) or major depressive disorder (MDD, 71.7%). One-way analyses of covariance comparing baseline regional grey matter cortical surface area, thickness, subcortical grey volumes, or white matter tensor-based fractional anisotropy across fSB (n = 40, 43.5%), fSI (n = 33, 35.9%) and fnonSIB (n = 19, 20.6%) groups were followed by pairwise comparisons in significant regions (p < 0.05). Compared to fnonSIBs, fSIs and fSBs showed significant decreases in cortical thickness of right inferior frontal gyrus pars orbitalis and middle temporal gyrus, fSIs of left inferior frontal gyrus, pars orbitalis. FSIs and fSBs showed lower fractional anisotropy in left uncinate fasciculus and corona radiata, and fSBs in right uncinate and superior fronto-occipital fasciculi. The study provides preliminary evidence of grey and white matter alterations in brain regions subserving emotional and behavioral regulation and perceptual processing in adolescent and young adult females with mood disorders with, versus without, future SIBs. Findings suggest potential targets to prevent SIBs in female adolescents and young adults.

Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach.

Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles. We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP. Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences. These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.

Hyperconnectivity and altered interactions of a nucleus accumbens network in post-stroke depression.

Post-stroke depression is a common complication of stroke. To date, no consistent locus of injury is associated with this complication. Here, we probed network dynamics and structural alterations in post-stroke depression in four functional circuits linked to major depressive disorder and a visual network, which served as a control network. Forty-four participants with recent stroke (mean age = 69.03, standard deviation age = 8.59, age range = 51-86 and gender: female = 10) and 16 healthy volunteers (mean age = 71.53, standard deviation age = 10.62, age range = 51-84 and gender: female = 11) were imaged with 3-Tesla structural, diffusion and resting-state functional MRI. The Geriatric Depression Scale was administered to measure depression severity. Associations between depression severity and functional connectivity were investigated within networks seeded from nucleus accumbens, amygdala, dorsolateral prefrontal cortex and primary visual cortex. In addition, the default mode network was identified by connectivity with medial prefrontal cortex and posterior cingulate cortex. Circuits that exhibited altered activity associated with depression severity were further investigated by extracting within-network volumetric and microstructural measures from structural images. In the stroke group, functional connectivity within the nucleus accumbens-seeded network (left hemisphere: P = 0.001; and right hemisphere: P = 0.004) and default mode network (cluster one: P < 0.001; and cluster two: P < 0.001) correlated positively with depressive symptoms. Normal anticorrelations between these two networks were absent in patients with post-stroke depression. Grey matter volume of the right posterior cingulate cortex (Pearson correlation coefficient = -0.286, P = 0.03), as well as microstructural measures in the posterior cingulate cortex (right: Pearson correlation coefficient = 0.4, P = 0.024; and left: Pearson correlation coefficient = 0.3, P = 0.048), right medial prefrontal cortex (Pearson correlation coefficient = 0.312, P = 0.039) and the medial forebrain bundle (Pearson correlation coefficient = 0.450, P = 0.003), a major projection pathway interconnecting the nucleus accumbens-seeded network and linking to medial prefrontal cortex, were associated with depression severity. Depression after stroke is marked by reduced mutual inhibition between functional circuits involving nucleus accumbens and default mode network as well as volumetric and microstructural changes within these networks. Aberrant network dynamics present in patients with post-stroke depression are therefore likely to be influenced by secondary, pervasive alterations in grey and white matter, remote from the site of injury.

Brain structural plasticity in rats subjected to early binocular enucleation characterized by high resolution anatomical magnetic resonance imaging and diffusion tensor imaging

Visual deprivation leads to structural neuroplasticity in the blind subjects, including gray matter (GM) and white matter (WM) atrophy and alterations in structural connectivity. The rat model of binocular enucleation (BE) is a frequently used animal model for studying brain plasticity induced by early blindness. Yet few neuroimaging studies have been performed on this model to investigate whether or not the BE rats have image phenotypes similar to or comparable to, those observed in the early blind subjects. The current study aimed to assess brain structural plasticity in BE rats using anatomical magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). The results demonstrated that early BE at postnatal day 4 (P4) caused almost complete degeneration of optic nerve (ON) and optic chiasma (OCH), atrophy in a number of visual and non-visual structures, including optic tract (OT), dorsal lateral geniculate nucleus (DLG) and corpus callosum (CC). The BE rats also exhibited impairments of WM microstructural integrity in the OT, and reduction of structural connectivity between the normal-appearing visual cortex (VC) and somatosensory/motor cortices at 4 months of age, likely as manifestations of deafferentation-induced maldevelopment. The structural neuroplasticity in BE rats observable to structural MRI parallels largely with what has been reported in blind subjects, suggesting that longitudinal neuroimaging studies on animal models of sensory deprivation can provide insights into how the brain changes its wiring and function during development/adaption in response to the lack of sensory stimuli.

Alterations of gray and white matter volumes and cortical thickness in treated HIV-positive patients

Brain structural changes in HIV identified by voxel-based morphometry (VBM) alone could arise from a variety of causes that are difficult to distinguish without further information, such as cortical thickness (CT), gyrification index (GI) or sulcal depth (SD). Hence, our goal was to assess these additional metrics in HIV using high-resolution 3D T1-weighted images and investigate if surface-based morphometric (SBM) analysis would reveal significant changes in the gray matter (GM) and white matter (WM) volumes combined with alterations in cortical thickness (CT), gyrification index (GI), sulcal depth (SD). T1-w magnetization-prepared-rapid-acquisition gradient-echo (MP-RAGE) scans were acquired in 27 HIV-infected individuals on antiretroviral therapy (ART) and 15 HIV-uninfected healthy controls using a 3T MRI scanner equipped with a 16-channel head “receive” and a quadrature body “transmit” coil. Voxel-based and surface-based morphometric analyses were performed using the MATLAB based SPM Computational Anatomy Toolbox (CAT12.7(1700)). HIV-infected patients showed significantly altered GM and WM volumes, CT, GI, and SD, in multiple brain regions. This study showed the association of altered GM and WM volumes in local brain regions with the changes in region-wise CT, GI and SD measures of HIV-infected patients, especially in the parahippocampal and middle frontal regions as compared to uninfected healthy controls. The outcome of this study suggests that the findings of VBM may not necessarily indicate the volumetric shrinkage or increase alone, but might also be due to altered CT, GI, or SD. Correlation analysis showed a significantly accelerated gray matter loss with age in HIV-infected individuals compared to uninfected healthy controls.

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.

Seeking Overlapping Neuroanatomical Alterations between Dyslexia and Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Replication Study.

The present work is a replication article based on the paper “Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies” by McGrath and Stoodley (2019). In the original research, the authors used activation likelihood estimation (ALE), a technique to perform coordinate-based meta-analysis (CBMA), to investigate the existence of brain regions undergoing gray matter alteration in association with both attention-deficit/hyper-activity disorder (ADHD) and dyslexia. Here, the same voxel-based morphometry dataset was analyzed, while using the permutation-subject images version of signed differential mapping (PSI-SDM) in place of ALE. Overall, the replication converged with the original paper in showing a limited overlap between the two conditions. In particular, no significant effect was found for dyslexia, therefore precluding any form of comparison between the two disorders. The possible influences of biological sex, age, and medication status were also ruled out. Our findings are in line with literature about gray matter alteration associated with ADHD and dyslexia, often showing conflicting results. Therefore, although neuropsychological and clinical evidence suggest some convergence between ADHD and dyslexia, more future research is sorely needed to reach a consensus on the neuroimaging domain in terms of patterns of gray matter alteration.

Investigating the Link between Later-Life Brain Volume and Cardiorespiratory Fitness after Mild Traumatic Brain Injury Exposure

Introduction: Evidence suggests that maintaining a higher level of cardiorespiratory fitness (CRF) later in life can offer some protection against brain volume loss as we age. By contrast, mild traumatic brain injury (mTBI) could accelerate age-related cortical atrophy. The current study sought to examine whether variations in the CRF level modified the association between mTBI history and brain volumetric measures in a sample of older adults. Methods: Seventy-nine community-dwelling older adults (mean age 68.7 ± 4.3 years, 54.4% female) were assessed for their mTBI history: 25 participants (32%) reported sustaining at least one lifetime mTBI. Participants also underwent a CRF assessment and magnetic resonance imaging (MRI) to obtain global and region-of-interest volumes. Results: Analysis of covariance, controlling for age, sex, education, and apolipoprotein (APOE) ε4 allele carriage, revealed that participants with a history of mTBI had a significantly larger total mean grey matter volume (582.21 ± 12.46 cm³) in comparison to participants with no mTBI history (571.08 ± 17.21 cm³, p = 0.01 after correction for multiple comparisons). However, no differences between groups based on mTBI history were found for total white matter volume or in any other cortical or subcortical structures examined. A subsequent moderation analysis found that CRF was predominantly non-influential on the association between mTBI history and the MRI-quantified measures of brain volume. Conclusion: While unexpected, the findings suggest that a history of mTBI can lead to grey matter alterations in the ageing brain. However, concurrent variations in the CRF level did not influence the differences in brain volume found based on mTBI exposure status.

Prefrontal cortex and putamen grey matter alterations in cannabis and tobacco users.

Previous magnetic resonance imaging studies in regular cannabis users report altered grey matter volume (GMV) in brain regions, including the prefrontal cortex (PFC), putamen and hippocampus. However, most studies have tended to recruit recreational users with high levels of cannabis use, and have not controlled for the possible confounding effects of tobacco use. We attempt to address these limitations in the present study. We acquired volumetric images in sex, age and IQ-matched groups of (1) regular Cannabis users who also smoke Tobacco cigarettes ('CT'; n = 33), (2) non-cannabis-using Tobacco cigarette smokers ('T'; n = 19) and (3) non-cannabis/tobacco-using Controls ('C'; n = 35). GMV in bilateral PFC, putamen and hippocampal regions was compared across groups. We also examined the associations between GMV differences and levels of cannabis and tobacco use, measures of intellectual function, and of depression, anxiety and stress. Relative to controls, both CT and T groups showed lower GMV in the left inferior frontal gyrus, and greater GMV in the putamen. In addition, lower GMV in the right frontal pole in the CT group (but not the T group) was associated with lifetime cannabis use, but not with cigarette use. Regular cannabis users who also smoked tobacco cigarettes showed altered GMV patterns relative to controls. However, a similar pattern of GMV differences was also seen between regular tobacco users that did not use cannabis. Further research is needed to disentangle the effects of cannabis and tobacco use on brain structure.

Aberrant gray matter volume and functional connectivity in Parkinson's disease with minor hallucination.

BackgroundMinor hallucination (MH) is the most common psychotic symptom in Parkinson’s disease (PD); it can develop into well-structured visual hallucination (VH), suggesting that MH may be a staccato form of well-structured VH. However, it remains unclear whether the pathogenesis is the same. Therefore, the aim of this study was to investigate the altered gray matter volume (GMV) and functional connectivity (FC) of MH in PD to further understand the complex mechanisms.Materials and methodsWe included 67 PD patients who attended the outpatient clinic of Nanjing Medical University Affiliated Brain Hospital and recruited 31 healthy controls (HC). Demographic data and clinical characteristics of all subjects were recorded, and cranial structural magnetic resonance imaging (MRI) and resting-state functional MRI data were acquired. Patients were classified into the PD with MH (PD-MH) group and PD without hallucinations or delusions (PD-NH) group. Voxel-based morphometry was used to analyze the differences in GMV in the structural pattern. Seed-based FC was used to analyze the functional pattern. Gaussian random field correction was used, with voxel level P < 0.001 and cluster level P < 0.05 representing statistically significant differences. Finally, the correlation between FC values and scores on the clinical characteristics assessment scale was analyzed.ResultsIn the GMV analysis, compared to the PD-NH group, the PD-MH group had reduced GMV in the medial superior frontal gyrus (SFGmed). In the FC analysis, the FC between the SFGmed and the left middle occipital gyrus and right calcarine sulcus decreased in the PD-MH group compared with the PD-NH group, while the FC between SFGmed and the left middle temporal gyrus increased. Correlation analysis revealed that the FC values of the SFGmed and right calcarine sulcus were correlated with the assessment scores for anxiety and sleep symptoms. The FC values of the SFGmed and left middle occipital gyrus were correlated with assessment scores for rapid eye movement disorder.ConclusionThe aberrant structure and function of the default mode network and visual processing areas seems to facilitate the generation of MH in PD, as the alteration was previously found in well-structured VH, suggesting that the two hallucinations have similar pathophysiological mechanisms.

A systematic review and meta-analysis of voxel-based morphometric studies of migraine.

To comprehensively summarize and meta-analyze the concurrence across voxel-based morphometric (VBM) neuroimaging studies of migraine. Neuroimaging studies published from origin to August 1, 2021 were searched in six databases including PubMed, Web of Science, Excerpta Medica Database (EMBASE), China National Knowledge Infrastructure (CNKI), Wanfang Database, and Chongqing VIP. Study selection, quality assessment, and data extraction were conducted by two independent researchers. Anisotropic effect size-signed differential mapping (AES-SDM) and activation likelihood estimation (ALE) were used to perform the meta-analysis of available studies reporting whole-brain gray matter (GM) structural data in migraine patients. Clinical variables correlation analysis and migraine subgroup analysis were also conducted. 40 articles were included after the strict screening, containing 1616 migraine patients and 1681 matched healthy subjects (HS) in total. Using the method of AES-SDM, migraine patients showed GM increase in the bilateral amygdala, the bilateral parahippocampus, the bilateral temporal poles, the bilateral superior temporal gyri, the left hippocampus, the right superior frontal gyrus, and the left middle temporal gyrus, as well as GM decrease in the left insula, the bilateral cerebellum (hemispheric lobule IX), the right dorsal medulla, the bilateral rolandic operculum, the right middle frontal gyrus, and the right inferior parietal gyrus. Using the method of ALE, migraine patients showed GM increase in the left parahippocampus and GM decrease in the left insula. The results of correlation analysis showed that many of these brain regions were associated with migraine headache frequency and migraine disease duration. Migraine patients in different subtypes (such as migraine without aura (MwoA), migraine with aura (MwA), episodic migraine (EM), chronic migraine (CM), vestibular migraine (VM), etc.), and in different periods (in the ictal and interictal periods) presented not entirely consistent GM alterations. Migraine patients have GM alterations in multiple brain regions associated with sensation, affection, cognition, and descending modulation aspects of pain. These changes might be a consequence of repeated migraine attacks. Further studies are required to determine how these GM changes can be used to diagnose, monitor disease progression, or exploit potential therapeutic interventions for migraine patients.