Gray Matter Volume Alterations Research Articles

Exploring the links among brain iron accumulation, cognitive performance, and dietary intake in older adults: A longitudinal MRI study

This study evaluated longitudinal brain iron accumulation in older adults, its association with cognition, and the role of specific nutrients in mitigating iron accumulation. MRI-based, quantitative susceptibility mapping estimates of brain iron concentration were acquired from seventy-two healthy older adults (47 women, ages 60–86) at a baseline timepoint (TP1) and a follow-up timepoint (TP2) 2.5–3.0 years later. Dietary intake was evaluated at baseline using a validated questionnaire. Cognitive performance was assessed at TP2 using the uniform data set (Version 3) neuropsychological tests of episodic memory (MEM) and executive function (EF). Voxel-wise, linear mixed-effects models, adjusted for longitudinal gray matter volume alterations, age, and several non-dietary lifestyle factors revealed brain iron accumulation in multiple subcortical and cortical brain regions, which was negatively associated with both MEM and EF performance at T2. However, consumption of specific dietary nutrients at TP1 was associated with reduced brain iron accumulation. Our study provides a map of brain regions showing iron accumulation in older adults over a short 2.5-year follow-up and indicates that certain dietary nutrients may slow brain iron accumulation.

Gray matter volume differences based on sex in first-episode drug-naive patients with major depressive disorder and its molecular analysis.

This study analyzed whether gray matter volume (GMV) differences exist between the sexes in patients with major depressive disorder (MDD) and explored the relationships between these differences and neurotransmitter systems. This study enrolled 190 first-episode drug-naive patients with MDD and 293 healthy controls. All participants underwent T1-weighted high-resolution MRI. The interaction between the diagnosis (healthy controls vs. MDD) and sex (male vs. female) regarding GMV alterations was analyzed. The JuSpace toolbox, which covers a wide range of neurotransmitter systems, was used to identify the relationship between MDD-induced and sex-induced GMV alterations and specific receptor/transporter proteins in the brain. Sex-specific GMV differences were observed in the healthy controls but not in MDD patients. Male healthy controls had a larger GMV in the bilateral parahippocampal, lingual, inferior occipital, fusiform, cerebellar subregions, and left inferior temporal than female healthy controls, but several subregions of the thalamus had a larger GMV in female healthy controls than in male healthy controls. Sex-induced GMV alterations were associated with 5-hydroxytryptamine receptor subtype 1a, cannabinoid receptor, and dopamine receptor (P < 0.01, false discovery rate corrected). GMV differences were not detected in the main effect of diagnosis and the interaction of diagnosis and sex. Sex-specific GMV differences are associated with the spatial distribution of serotonin, dopamine, and cannabinoid neurotransmitter receptor systems. Sex-based physiological differences in the GMV may account for male and female susceptibility to and differences in the clinical symptoms of MDD.

Disrupted gray matter connectome in vestibular migraine: a combined machine learning and individual-level morphological brain network analysis

BackgroundAlthough gray matter (GM) volume alterations have been extensively documented in previous voxel-based morphometry studies on vestibular migraine (VM), little is known about the impact of this disease on the topological organization of GM morphological networks. This study investigated the altered network patterns of the GM connectome in patients with VM.MethodsIn this study, 55 patients with VM and 57 healthy controls (HCs) underwent structural T1-weighted MRI. GM morphological networks were constructed by estimating interregional similarity in the distributions of regional GM volume based on the Kullback–Leibler divergence measure. Graph-theoretical metrics and interregional morphological connectivity were computed and compared between the two groups. Partial correlation analyses were performed between significant GM connectome features and clinical parameters. Logistic regression (LR), support vector machine (SVM), and random forest (RF) classifiers were used to examine the performance of significant GM connectome features in distinguishing patients with VM from HCs.ResultsCompared with HCs, patients with VM exhibited increased clustering coefficient and local efficiency, as well as reduced nodal degree and nodal efficiency in the left superior temporal gyrus (STG). Furthermore, we identified one connected component with decreased morphological connectivity strength, and the involved regions were mainly located in the STG, temporal pole, prefrontal cortex, supplementary motor area, cingulum, fusiform gyrus, and cerebellum. In the VM group, several connections in the identified connected component were correlated with clinical measures (i.e., symptoms and emotional scales); however, these correlations did not survive multiple comparison corrections. A combination of significant graph- and connectivity-based features allowed single-subject classification of VM versus HC with significant accuracy of 77.68%, 77.68%, and 72.32% for the LR, SVM, and RF models, respectively.ConclusionPatients with VM had aberrant GM connectomes in terms of topological properties and network connections, reflecting potential dizziness, pain, and emotional dysfunctions. The identified features could serve as individualized neuroimaging markers of VM.

Highfield imaging of the subgenual anterior cingulate cortex in uni- and bipolar depression.

The subgenual Anterior Cingulate Cortex (sgACC), as a part of the Anterior Cingulate Cortex and the limbic system plays a crucial role in mood regulation. Previous structural and functional brain imaging studies of the sgACC have revealed alterations of Gray Matter (GM) volumes and Blood Oxygenation Level Dependent signals (BOLD) in patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD), suggesting potential biomarker traits for affective disorders. In this study we investigated the gray matter volume of the sgACC in 3 different patient groups: 40 MDD patients, of which 20 were medicated (MDDm) and 20 were unmedicated (MDDu), and 21 medicated BD patients, and compared them with 23 healthy volunteers. We examined GM volume alteration using high-resolution 7T Magnetic Resonance Imaging (MRI) which produced quantitative maps of the spin-lattice relaxation time (T1). T1 maps provide high contrast between gray and white matter, and at 7 Tesla voxels with submillimeter resolution can be acquired in a reasonable scan time. We developed a semi-automatic segmentation protocol based on refined landmarks derived from previous volumetric studies using quantitative T1 maps as raw input data for automatic tissue segmentation of GM, WM and CSF (cerebrospinal fluid) tissue. The sgACC ROI was then superimposed on these tissue probability maps and traced manually by two independent raters (F.B., M.M.) following our semi-automatic segmentation protocol. Interrater reliability was calculated on a subset of 10 brain scans for each hemisphere, showing an Intra-Class Correlation coefficient (ICC) r = 0.96 for left sgACC and r = 0.84 for right sgACC respectively. In summary, we have developed a reproducible and reliable semi-automatic segmentation protocol to measure gray matter volume in the sgACC. Based on previous findings from meta-analyses on morphometric studies of the sgACC, we hypothesized that patients with MDD would have lower gray matter sgACC volumes compared to healthy subjects. Post-hoc analysis revealed smaller subgenual volumes for the left hemisphere in both the medicated (MDDm) and non-medicated (MDDu) group versus healthy controls (p = .001, p = .008) respectively. For the right hemisphere, the (MDDu) and BD group exhibited significantly lower subgenual volumes than healthy controls (p < .001, p = .004) respectively. To our knowledge, this is the first morphometric MRI study using T1 maps obtained in high-resolution 7 Tesla MRI to compare MDD and BD patients with healthy controls.

Expanded gray matter atrophy with severity stages of adult comorbid insomnia and sleep apnea

ObjectiveTo investigate gray matter volume (GMV) changes in patients with comorbid insomnia and sleep apnea (COMISA) of differing severity and relationships between GMV alterations and clinical measures. MethodsThirty-four COMISA patients and 24 healthy controls (HC) were recruited. All patients underwent structural MRI and completed measures related to respiration, sleep, mood, and cognition. COMISA patients were further divided into a mild and moderate COMISA (MC) and a severe COMISA (SC) group. Changes in GMV of COMISA patients were investigated via VBM. The voxel-wise differences in GMV were compared between HC group and COMISA group. Analysis of covariance (ANCOVA) was performed on individual GMV maps in MC, SC, and HC groups to further investigate effects of different stages of COMISA severity on GMV. Partial correlation analysis was then performed to analyze relationships between altered GMV and clinical measures. ResultsGMV atrophy was mainly located in the temporal lobes and fusiform gyrus in COMISA group. The post-hoc analysis of the ANCOVA revealed temporal lobes and fusiform gyrus atrophy in MC and SC groups compared to HC and the temporal lobe atrophy was expanded in SC group based on cluster size. Moreover, the SC group showed GMV atrophy of the right amygdala compared to both MC and HC groups. Partial correlation analysis revealed positive relationships between the GMV and mood-and cognitive-related measures and negative correlation between GMV and respiration measure. ConclusionsOur findings showed GMV atrophy expansion from temporal lobe to limbic system (right amygdala) as severity stages increase in COMISA patients. These findings contribute to our understanding of neurobiological mechanisms underlying different stages of severity in COMISA patients.

Volume-based structural connectome of epilepsy partialis continua in Rasmussen's encephalitis.

Rasmussen's encephalitis is a rare, progressive neurological inflammatory with hemispheric brain atrophy. Epilepsy partialis continua (EPC) is a diagnostic clinical condition in patients with Rasmussen's encephalitis. However, the incidence of EPC in the natural course of Rasmussen's encephalitis is only about 50%. The majority of experts hold the belief that EPC is associated with dysfunction in the motor cortex, yet the whole pathogenesis remains unclear. We hypothesize that there is a characteristic topological discrepancy between groups with EPC and without EPC from the perspective of structural connectome. To this end, we described the structural MRI findings of 20 Rasmussen's encephalitis cases, 11 of which had EPC, and 9 of which did not have EPC (NEPC), and 20 healthy controls. We performed voxel-based morphometry to evaluate the alterations of grey matter volume. Using a volume-based structural covariant network, the hub distribution and modularity were studied at the group level. Based on the radiomic features, an individual radiomics structural similarity network was constructed for global topological properties, such as small-world index, higher path length, and clustering coefficient. And then, the Pearson correlation was used to delineate the association between duration and topology properties. In the both EPC and NEPC groups, the volume of the motor cortex on the affected side was significantly decreased, but putamen atrophy was most pronounced in the EPC group. Hubs in the EPC group consisted of the executive network, and the contralateral putamen was the hub in the NEPC group with the highest betweenness centrality. Compared to the NEPC, the EPC showed a higher path length and clustering coefficient in the structural similarity network. Moreover, the function of morphological network integration in EPC patients was diminished as the duration of Rasmussen's encephalitis increased. Our study indicates that motor cortex atrophy may not be directly related to EPC patients. Whereas atrophy of the putamen, and a more regularized configuration may contribute to the generation of EPC. The findings further suggest that the putamen could potentially serve as a viable target for controlling EPC in patients with Rasmussen's encephalitis.

The association between adverse childhood experiences and alterations in brain volume and cortical thickness in adults with alcohol use disorder.

Previous studies have established a connection between adverse childhood experiences (ACE) and alcohol use disorder (AUD), both of which are associated with alterations in grey matter volume (GMV) and cortical thickness (CT). The current study aimed to assess the neurobiological impact of ACE specifically in the context of AUD, as well as the role of maltreatment type (i.e., abuse or neglect) and timing. Structural MRI data were collected from 35 adults with AUD (mean age: 40; 31% female) and 28 healthy controls (mean age: 36; 61% female). ACE were assessed retrospectively using the Childhood Trauma Questionnaire, and the Maltreatment and Abuse Chronology interview. Global and regional GMV and CT were estimated using voxel- and surface-based morphometry. Relative to the healthy controls, the AUD group had significantly reduced CT in the left inferior frontal gyrus, left circular sulcus of the insula and subcentral gyrus and sulci (cluster C1), and in the central sulcus and precentral gyrus (cluster C2). Within the AUD group, a reduction of CT in cluster C1 was significantly associated with higher severity of ACE and AUD. Type and timing analyses revealed a significant association between higher levels of abuse at ages 13 to 15 and reduced CT in cluster C1 within the AUD group. In adults with AUD, abuse experienced during early adolescence is associated with reduced CT in regions involved in inhibitory control, indicating the potential relevance of cognitive pathways in the association between ACE and AUD. Longitudinal studies are needed to confirm and expand upon current findings.

Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study.

Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry. We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain. Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates. aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction). Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches.

Association between kidney function and Parkinson’s disease risk: a prospective study from the UK Biobank

BackgroundParkinson’s disease (PD) is a neurodegenerative influenced by various clinical factors. The potential relationship between renal function and the risk of PD remains poorly understood. This study aims to explore the association between kidney function and the risk of developing PD.MethodsA population-based cohort study was conducted using data from 400,571 UK Biobank participants. Renal function was assessed using the estimated glomerular filtration rate (eGFR), calculated from serum creatinine and cystatin C levels. The association between eGFR levels and PD risk was evaluated using univariate and multivariate Cox regression analyses, Restricted Cubic Spline (RCS) analysis, and Kaplan-Meier analysis. Additionally, a clinical prediction model was developed and its diagnostic accuracy was evaluated using ROC analysis. A heatmap was also constructed to examine the relationship between clinical factors and gray matter volume in various brain regions.ResultsOver a median observation period of 13.8 years, 2740 PD events were recorded. Cox regression and Kaplan-Meier analyses revealed a significant association between decreased eGFR and increased PD risk, particularly in participants with eGFR < 30 ml/min/1.73 m2. This association was confirmed across three adjusted models. RCS analysis demonstrated a nonlinear relationship between decreasing eGFR and increasing PD risk. Furthermore, changes in eGFR were correlated with alterations in subcortical gray matter volume in regions such as the frontal cortex, striatum, and cerebellum. The clinical prediction model showed high diagnostic accuracy with AUC values of 0.776, 0.780, and 0.824 for 4-, 8-, and 16-year predictions, respectively.ConclusionRenal insufficiency is significantly associated with an increased risk of PD, highlighting the importance of maintaining good kidney function as a potential preventive measure against PD.

Effects of growth hormone and sex steroid therapy on brain structure and pituitary function in turner syndrome

Introduction: Turner syndrome (TS) is a chromosomal disorder affecting approximately 1 in 2,500 live female births, characterized by the partial or complete absence of one X chromosome. This genetic anomaly leads to physical, cognitive, and endocrine abnormalities, including short stature, gonadal dysgenesis, and structural brain anomalies. Cognitive deficits in TS involve visuospatial processing, memory, and executive function, often linked to structural brain changes. Magnetic resonance imaging (MRI) has revealed significant alterations in gray and white matter volumes in various brain regions. Growth hormone (GH) and sex steroid therapies, such as estrogen and progesterone, are used to address growth and developmental delays in TS. However, their impact on brain structure and pituitary function remains an area of active research. Aim of the Review: To systematically review and synthesize findings on the effects of GH and sex steroid therapy on brain structure and pituitary function in patients with Turner syndrome. Methods: A comprehensive literature review was conducted to identify studies examining the effects of GH and sex steroid therapy on brain structure and pituitary function in TS. Data from various sources were compiled, focusing on MRI-based structural brain changes. Key parameters analyzed included sample size, findings from MRI and fMRI studies, and clinical associations. Studies were summarized and presented in a structured table format. Results: Estrogen-progesterone treatment was found to suppress pituitary gonadotropin release more effectively than estrogen alone, indicating a feedback interaction between pituitary gonadotropin release and sex steroids. MRI studies showed that TS patients exhibit smaller volumes in the hippocampus, caudate, lenticular, thalamic nuclei, and parieto-occipital brain matter, correlating with cognitive deficits. GH-IGF axis abnormalities are modulated by body composition and physical fitness, with sex hormone replacement normalizing the GH-IGF axis and improving body composition. Although GH therapy alone did not significantly improve cognitive functions, the combination of GH with oxandrolone improved working memory. Estrogen deficiency and TS are associated with slower growth in parieto-occipital regions and enhanced volume growth in basal ganglia and cerebellar areas during adolescence, underscoring the importance of estrogen replacement in brain development. Discussion: GH and sex steroid therapies significantly impact brain structure, pituitary function, and clinical outcomes in TS. GH therapy, often combined with sex steroids, improves growth and cognitive functions, particularly working memory. However, GH alone does not significantly impact overall cognitive function. The timing and combination of these therapies are crucial for optimizing outcomes. Regular monitoring and individualized treatment plans are essential to address the complex needs of TS patients. Further research is needed to explore the long-term impacts of these therapies and develop optimal treatment regimens. Conclusion: GH and sex steroid therapies are vital in managing TS contributing to improved growth, body composition, and cognitive enhancements. A multifaceted therapeutic approach and regular monitoring are crucial for optimizing treatment outcomes and quality of life for TS patients.

Neural correlates of inattention in adults with ADHD.

In the last two decades, numerous magnetic resonance imaging (MRI) studies have examined differences in cortical structure between individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) and healthy controls. These studies primarily emphasized alterations in gray matter volume (GMV) and cortical thickness (CT). Still, the scientific literature is notably scarce in regard to investigating associations of cortical structure with ADHD psychopathology, specifically inattention within adults with ADHD. The present study aimed to elucidate neurobiological underpinnings of inattention beyond GMV and CT by including cortical gyrification, sulcal depth, and fractal dimension. Building upon the Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study (COMPAS), cortical structure parameters were investigated using 141 T1-weighted anatomical scans of adult patients with ADHD. All brain structural analyses were performed using the threshold-free cluster enhancement (TFCE) approach and the Computational Anatomy Toolbox (CAT12) integrated into the Statistical Parametric Mapping Software (Matlab Version R2021a). Results revealed significant correlations of inattention in multiple brain regions. Cortical gyrification was negatively correlated, whereas cortical thickness and fractal dimension were positively associated with inattention. The clusters showed widespread distribution across the cerebral cortex, with both hemispheres affected. The cortical regions most prominently affected included the precuneus, para-, pre-, and postcentral gyri, superior parietal lobe, and posterior cingulate cortex. This study highlights the importance of cortical alterations in attentional processes in adults with ADHD. Further research in this area is warranted to elucidate intricacies of inattention in adults with ADHD to potentially enhance diagnostic accuracy and inform personalized treatment strategies.

Multimodal abnormalities of brain structures in adolescents and young adults with major depressive disorder: An activation likelihood estimation meta-analysis.

Major depressive disorder (MDD) in adolescents and young adults contributes significantly to global morbidity, with inconsistent findings on brain structural changes from structural magnetic resonance imaging studies. Activation likelihood estimation (ALE) offers a method to synthesize these diverse findings and identify consistent brain anomalies. To identify consistent brain structural changes in adolescents and young adults with MDD using ALE meta-analysis. We performed a comprehensive literature search in PubMed, Web of Science, Embase, and Chinese National Knowledge Infrastructure databases for neuroimaging studies on MDD among adolescents and young adults published up to November 19, 2023. Two independent researchers performed the study selection, quality assessment, and data extraction. The ALE technique was employed to synthesize findings on localized brain function anomalies in MDD patients, which was supplemented by sensitivity analyses. Twenty-two studies comprising fourteen diffusion tensor imaging (DTI) studies and eight voxel-based morphometry (VBM) studies, and involving 451 MDD patients and 465 healthy controls (HCs) for DTI and 664 MDD patients and 946 HCs for VBM, were included. DTI-based ALE demonstrated significant reductions in fractional anisotropy (FA) values in the right caudate head, right insula, and right lentiform nucleus putamen in adolescents and young adults with MDD compared to HCs, with no regions exhibiting increased FA values. VBM-based ALE did not demonstrate significant alterations in gray matter volume. Sensitivity analyses highlighted consistent findings in the right caudate head (11 of 14 analyses), right insula (10 of 14 analyses), and right lentiform nucleus putamen (11 of 14 analyses). Structural alterations in the right caudate head, right insula, and right lentiform nucleus putamen in young MDD patients may contribute to its recurrent nature, offering insights for targeted therapies.

Structure-function interrelationships and associated neurotransmitter profiles in drug-naïve benign childhood epilepsy with central-temporal spikes patients.

To explore the interrelationships between structural and functional changes as well as the potential neurotransmitter profile alterations in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients. Structural magnetic resonance imaging (sMRI) and resting-state functional MRI data from 20 drug-naïve BECTS patients and 33 healthy controls (HCs) were acquired. Parallel independent component analysis (P-ICA) was used to identify covarying components among gray matter volume (GMV) maps and fractional amplitude of low-frequency fluctuations (fALFF) maps. Furthermore, we explored the spatial correlations between GMV/fALFF changes derived from P-ICA and neurotransmitter maps in JuSpace toolbox. A significantly positive correlation (p < 0.001) was identified between one structural component (GMV_IC6) and one functional component (fALFF_IC4), which showed significant group differences between drug-naïve BECTS patients and HCs (GMV_IC6: p < 0.01; fALFF_IC4: p < 0.001). GMV_IC6 showed increased GMV in the frontal lobe, temporal lobe, thalamus, and precentral gyrus as well as fALFF_IC4 had enhanced fALFF in the cerebellum in drug-naïve BECTS patients compared to HCs. Moreover, significant correlations between GMV alterations in GMV_IC6 and the serotonin (5HT1a: p < 0.001; 5HT2a: p < 0.001), norepinephrine (NAT: p < 0.001) and glutamate systems (mGluR5: p < 0.001) as well as between fALFF alterations in fALFF_IC4 and the norepinephrine system (NAT: p < 0.001) were detected. The current findings suggest co-altered structural/functional components that reflect the correlation of language and motor networks as well as associated with the serotonergic, noradrenergic, and glutamatergic neurotransmitter systems. The relationship between anatomical brain structure and intrinsic neural activity was evaluated using a multimodal fusion analysis and neurotransmitters which might provide an important window into the multimodal neural and underlying molecular mechanisms of benign childhood epilepsy with central-temporal spikes. Structure-function relationships in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients were explored. The interrelated structure-function components were found and correlated with the serotonin, norepinephrine, and glutamate systems. Co-altered structural/functional components reflect the correlation of language and motor networks and correlate with the specific neurotransmitter systems.

Gray matter volume alterations in de novo Parkinson's disease: A mediational role in the interplay between sleep quality and anxiety.

Parkinson's disease (PD) is increasingly recognized for its non-motor symptoms, among which emotional disturbances and sleep disorders frequently co-occur. The commonality of neuroanatomical underpinnings for these symptoms is not fully understood. This study is intended to investigate the differences in gray matter volume (GMV) between PD patients with anxiety (A-PD) and those without anxiety (NA-PD). Additionally, it seeks to uncover the interplay between GMV variations and the manifestations of anxiety and sleep quality. A total of 37 A-PD patients, 43 NA-PD patients, and 36 healthy controls (HCs) were recruited, all of whom underwent voxel-based morphometry (VBM) analysis. Group differences in GMV were assessed using analysis of covariance (ANCOVA). Partial correlation between GMV, anxiety symptom, and sleep quality were analyzed. Mediation analysis explored the mediating role of the volume of GMV-distinct brain regions on the relationship between sleep quality and anxiety within the PD patient cohort. A-PD patients showed significantly lower GMV in the fusiform gyrus (FG) and right inferior temporal gyrus (ITG) compared to HCs and NA-PD patients. GMV in these regions correlated negatively with Hamilton Anxiety Rating Scale (HAMA) scores (right ITG: r = -0.690, p < 0.001; left FG: r = -0.509, p < 0.001; right FG: r = -0.576, p < 0.001) and positively with sleep quality in PD patients (right ITG: r = 0.592, p < 0.001; left FG: r = 0.356, p = 0.001; right FG: r = 0.470, p < 0.001). Mediation analysis revealed that GMV in the FG and right ITG mediated the relationship between sleep quality and anxiety symptoms, with substantial effect sizes accounted for by the right ITG (25.74%) and FG (left: 11.90%, right: 15.59%). This study has shed further light on the relationship between sleep disturbances and anxiety symptoms in PD patients. Given the pivotal roles of the FG and the ITG in facial recognition and the recognition of emotion-related facial expressions, our findings indicate that compromised sleep quality, under the pathological conditions of PD, may exacerbate the reduction in GMV within these regions, impairing the recognition of emotional facial expressions and thereby intensifying anxiety symptoms.

Gray matter alterations in Huntington's disease: A meta-analysis of VBM neuroimaging studies.

Increasing neuroimaging studies have attempted to identify biomarkers of Huntington's disease (HD) progression. Here, we conducted voxel-based meta-analyses of voxel-based morphometry (VBM) studies on HD to investigate the evolution of gray matter volume (GMV) alterations and explore the effects of genetic and clinical features on GMV changes. A systematic review was performed to identify the relevant studies. Meta-analyses of whole-brain VBM studies were performed to assess the regional GMV changes in all HD mutation carriers, in presymptomatic HD (pre-HD), and in symptomatic HD (sym-HD). A quantitative comparison was performed between pre-HD and sym-HD. Meta-regression analyses were used to explore the effects of genetic and clinical features on GMV changes. Twenty-eight studies were included, comparing a total of 1811 HD mutation carriers [including 1150 pre-HD and 560 sym-HD] and 969 healthy controls (HCs). Pre-HD showed decreased GMV in the bilateral caudate nuclei, putamen, insula, anterior cingulate/paracingulate gyri, middle temporal gyri, and left dorsolateral superior frontal gyrus compared with HCs. Compared with pre-HD, GMV decrease in sym-HD extended to the bilateral median cingulate/paracingulate gyri, Rolandic operculum and middle occipital gyri, left amygdala, and superior temporal gyrus. Meta-regression analyses found that age, mean lengths of CAG repeats, and disease burden were negatively associated with GMV atrophy of the bilateral caudate and right insula in all HD mutation carriers. This meta-analysis revealed the pattern of GMV changes from pre-HD to sym-HD, prompting the understanding of HD progression. The pattern of GMV changes may be biomarkers for disease progression in HD.

The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks.

Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN). We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores. Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD. We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

The interplay between white adipose tissue, adipokines, and structural gray matter changes

AbstractThe growing global obesity issue emphasizes the importance of understanding its health implications. Previous research has identified consistent alterations in gray matter (GM) volume in connection with obesity. Given the various implications of distinct fat compartments and the potential role of adipose tissue‐derived adipokines in brain health, a more detailed investigation of adiposity is required. This study investigates a sample of 65 males with varying body mass indices to explore the relationship between various fat compartments, adipokine levels, and volumetric GM variations, aiming to provide a deeper understanding of the interplay between adiposity, brain structure, and metabolic signals. Whole‐body magnetic resonance imaging (MRI) was used to assess total, visceral, and subcutaneous adipose tissue, while MR spectroscopy was performed to capture liver fat content. For the assessment of adipokine levels leptin and adiponectin concentrations were measured, and structural brain images underwent cortical and subcortical segmentation for GM volume and thickness. A predictive modeling approach with leave‐one‐out cross‐validation was used to predict body composition metrics and adipokine levels based on structural GM data. Our investigation revealed diminished GM volume and thickness correlated with elevated leptin levels in areas crucial for appetite regulation, decision‐making, and cognitive control, including the anterior insula, orbitofrontal cortex, and anterior cingulate cortex. These findings suggest a potential adverse impact of heightened leptin concentrations on brain health and eating habits. Contrary to expectations, our investigation found no significant relationship between GM volume and any of the measured fat compartments. This result prompts the need for further research to elucidate the relationship between obesity, adipokines, and brain structure.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

Lower motor performance is linked with poor sleep quality, depressive symptoms, and grey matter volume alterations.

Motor performance (MP) is essential for functional independence and well-being, particularly in later life. However, the relationship between behavioural aspects such as sleep quality and depressive symptoms, which contribute to MP, and the underlying structural brain substrates of their interplay remains unclear. This study used three population-based cohorts of younger and older adults (n=1,950) from the Human Connectome Project-Young Adult (HCP-YA), HCP-Aging (HCP-A), and enhanced Nathan Kline Institute-Rockland sample (eNKI-RS). Several canonical correlation analyses were computed within a machine learning framework to assess the associations between each of the three domains (sleep quality, depressive symptoms, grey matter volume (GMV)) and MP. The HCP-YA analyses showed progressively stronger associations between MP and each domain: depressive symptoms (unexpectedly positive, r=0.13, SD=0.06), sleep quality (r=0.17, SD=0.05), and GMV (r=0.19, SD=0.06). Combining sleep and depressive symptoms significantly improved the canonical correlations (r=0.25, SD=0.05), while the addition of GMV exhibited no further increase (r=0.23, SD=0.06). In young adults, better sleep quality, mild depressive symptoms, and GMV of several brain regions were associated with better MP. This was conceptually replicated in young adults from the eNKI-RS cohort. In HCP-Aging, better sleep quality, fewer depressive symptoms, and increased GMV were associated with MP. Robust multivariate associations were observed between sleep quality, depressive symptoms and GMV with MP, as well as age-related variations in these factors. Future studies should further explore these associations and consider interventions targeting sleep and mental health to test the potential effects on MP across the lifespan.

Gray Matter Atrophy in a 6-OHDA-induced Model of Parkinson’s Disease

IntroductionMagnetic resonance imaging (MRI) based brain morphometric changes in unilateral 6-hydroxydopamine (6-OHDA) induced Parkinson’s disease (PD) model can be elucidated using voxel-based morphometry (VBM), study of alterations in gray matter volume and Machine Learning (ML) based analyses. MethodsWe investigated gray matter atrophy in 6-OHDA induced PD model as compared to sham control using statistical and ML based analysis. VBM and atlas-based volumetric analysis was carried out at regional level. Support vector machine (SVM)-based algorithms wherein features (volume) extracted from (a) each of the 150 brain regions (b) statistically significant features (only) and (c) volumes of each cluster identified after application of VBM (VBM_Vol) were used for training the decision model. The lesion of the 6-OHDA model was validated by estimating the net contralateral rotational behaviour by the injection of apomorphine drug and motor impairment was assessed by rotarod and open field test. Results and discussionIn PD, gray matter volume (GMV) atrophy was noted in bilateral cortical and subcortical brain regions, especially in the internal capsule, substantia nigra, midbrain, primary motor cortex and basal ganglia-thalamocortical circuits in comparison with sham control. Behavioural results revealed an impairment in motor performance. SVM analysis showed 100% classification accuracy, sensitivity and specificity at both 3 and 7 weeks using VBM_Vol. ConclusionUnilateral 6-OHDA induced GMV changes in both hemispheres at 7th week may be associated with progression of the disease in the PD model. SVM based approaches provide an increased classification accuracy to elucidate GMV atrophy.