The Role of Excitotoxicity, Oxidative Stress and Bioenergetics Disruption in the Neuropathology of Nonketotic Hyperglycinemia.

Nonketotic hyperglycinemia (NKH) is an inherited disorder of amino acid metabolism biochemically characterized by the accumulation of glycine (Gly) predominantly in the brain. Affected patients usually manifest with neurological symptoms including hypotonia, seizures, epilepsy, lethargy, and coma, the pathophysiology of which is still not completely understood. Treatment is limited and based on lowering Gly levels aiming to reduce overstimulation of N-methyl-D-aspartate (NMDA) receptors. Mounting in vitro and in vivo animal and human evidence have recently suggested that excitotoxicity, oxidative stress, and bioenergetics disruption induced by Gly are relevant mechanisms involved in the neuropathology of NKH. This brief review gives emphasis to the deleterious effects of Gly in the brain of patients and animal models of NKH that may offer perspectives for the development of novel adjuvant treatments for this disorder.

The clinical and predictive value of 18F-FDG PET/CT metabolic patterns in a clinical Chinese cohort with autoimmune encephalitis.

AIMS: To investigate the diagnostic and predictive role of 18F-FDG PET/CT in patients with autoimmune encephalitis (AE) as a whole group. METHODS: Thrty-five patients (20 females and 15 males) with AE were recruited. A voxel-to-voxel semi-quantitative analysis based on SPM12 was used to analyze 18F-FDG PET/CT imaging data compared to healthy controls. Further comparison was made in different prognostic groups categorized by modified Rankin Scale (mRS). RESULTS: In total, 24 patients (68.6%) were tested positive neuronal antibodies in serum and/or CSF. Psychiatric symptoms and seizure attacks were major clinical symptoms. In the acute stage, 13 patients (37.1%) demonstrated abnormal brain MRI results, while 33 (94.3%) presented abnormal metabolism patterns. 18F-FDG PET/CT was more sensitive than MRI (p < 0.05). Patients with AE mainly presented mixed metabolism patterns compared to the matched controls, demonstrating hypermetabolism mainly in the cerebellum, BG, MTL, brainstem, insula, middle frontal gyrus, and relatively hypometabolism in the frontal cortex, occipital cortex, temporal gyrus, right parietal gyrus, left cingulate gyrus (p < 0.05, FWE corrected). After a median follow-up of 26 months, the multivariable analysis identified a decreased level of consciousness as an independent risk factor associated with poor outcome of AE (HR = 3.591, p = 0.016). Meanwhile, decreased metabolism of right superior frontal gyrus along with increased metabolism of the middle and upper brainstem was more evident in patients with poor outcome (p < 0.001, uncorrected). CONCLUSION: 18F-FDG PET/CT was more sensitive than MRI to detect neuroimaging abnormalities of AE. A mixed metabolic pattern, characterized by large areas of cortical hypometabolism with focal hypermetabolism was a general metabolic pattern. Decreased metabolism of right superior frontal gyrus with increased metabolism of the middle and upper brainstem may predict poor long-term prognosis of AE.

Altered executive control network and default model network topology are linked to acute electronic cigarette use: A resting-state fNIRS study.

In recent years, electronic cigarettes (e-cigs) have gained popularity as stylish, safe, and effective smoking cessation aids, leading to widespread consumer acceptance. Although previous research has explored the acute effects of combustible cigarettes or nicotine replacement therapy on brain functional activities, studies on e-cigs have been limited. Using fNIRS, we conducted graph theory analysis on the resting-state functional connectivity of 61 male abstinent smokers both before and after vaping e-cigs. And we performed Pearson correlation analysis to investigate the relationship between alterations in network metrics and changes in craving. E-cig use resulted in increased degree centrality, nodal efficiency, and local efficiency within the executive control network (ECN), while causing a decrease in these properties within the default model network (DMN). These alterations were found to be correlated with reductions in craving, indicating a relationship between differing network topologies in the ECN and DMN and decreased craving. These findings suggest that the impact of e-cig usage on network topologies observed in male smokers resembles the effects observed with traditional cigarettes and other forms of nicotine delivery, providing valuable insights into their addictive potential and effectiveness as aids for smoking cessation.

Measuring functional connectivity in frequency-domain helps to better characterize brain function.

Resting-state functional connectivity (FC) is widely used in multivariate pattern analysis of functional magnetic resonance imaging (fMRI), including identifying the locations of putative brain functional borders, predicting individual phenotypes, and diagnosing clinical mental diseases. However, limited attention has been paid to the analysis of functional interactions from a frequency perspective. In this study, by contrasting coherence-based and correlation-based FC with two machine learning tasks, we observed that measuring FC in the frequency domain helped to identify finer functional subregions and achieve better pattern discrimination capability relative to the temporal correlation. This study has proven the feasibility of coherence in the analysis of fMRI, and the results indicate that modeling functional interactions in the frequency domain may provide richer information than that in the time domain, which may provide a new perspective on the analysis of functional neuroimaging.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Effects of endogenous testosterone on oscillatory activity during verbal working memory in youth.

Testosterone levels sharply rise during the transition from childhood to adolescence and these changes are known to be associated with changes in human brain structure. During this same developmental window, there are also robust changes in the neural oscillatory dynamics serving verbal working memory processing. Surprisingly, whereas many studies have investigated the effects of chronological age on the neural oscillations supporting verbal working memory, none have probed the impact of endogenous testosterone levels during this developmental period. Using a sample of 89 youth aged 6-14 years-old, we collected salivary testosterone samples and recorded magnetoencephalography during a modified Sternberg verbal working memory task. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting maps were subjected to whole-brain ANCOVAs examining the effects of testosterone and sex, controlling for age, during verbal working memory encoding and maintenance. Our primary results indicated robust testosterone-related effects in theta (4-7 Hz) and alpha (8-14 Hz) oscillatory activity, controlling for age. During encoding, females exhibited weaker theta oscillations than males in right cerebellar cortices and stronger alpha oscillations in left temporal cortices. During maintenance, youth with greater testosterone exhibited weaker alpha oscillations in right parahippocampal and cerebellar cortices, as well as regions across the left-lateralized language network. These results extend the existing literature on the development of verbal working memory processing by showing region and sex-specific effects of testosterone, and are the first results to link endogenous testosterone levels to the neural oscillatory activity serving verbal working memory, above and beyond the effects of chronological age.

Effect of glucocorticoid blockade on inflammatory responses to acute sleep fragmentation in male mice.

The association between sleep and the immune-endocrine system is well recognized, but the nature of that relationship is not well understood. Sleep fragmentation induces a pro-inflammatory response in peripheral tissues and brain, but it also activates the hypothalamic-pituitary-adrenal (HPA) axis, releasing glucocorticoids (GCs) (cortisol in humans and corticosterone in mice). It is unclear whether this rapid release of glucocorticoids acts to potentiate or dampen the inflammatory response in the short term. The purpose of this study was to determine whether blocking or suppressing glucocorticoid activity will affect the inflammatory response from acute sleep fragmentation (ASF). Male C57BL/6J mice were injected i.p. with either 0.9% NaCl (vehicle 1), metyrapone (a glucocorticoid synthesis inhibitor, dissolved in vehicle 1), 2% ethanol in polyethylene glycol (vehicle 2), or mifepristone (a glucocorticoid receptor antagonist, dissolved in vehicle 2) 10 min before the start of ASF or no sleep fragmentation (NSF). After 24 h, samples were collected from brain (prefrontal cortex, hypothalamus, hippocampus) and periphery (liver, spleen, heart, and epididymal white adipose tissue (EWAT)). Proinflammatory gene expression (TNF-α and IL-1ß) was measured, followed by gene expression analysis. Metyrapone treatment affected pro-inflammatory cytokine gene expression during ASF in some peripheral tissues, but not in the brain. More specifically, metyrapone treatment suppressed IL-1ß expression in EWAT during ASF, which implies a pro-inflammatory effect of GCs. However, in cardiac tissue, metyrapone treatment increased TNF-α expression in ASF mice, suggesting an anti-inflammatory effect of GCs. Mifepristone treatment yielded more significant results than metyrapone, reducing TNF-α expression in liver (only NSF mice) and cardiac tissue during ASF, indicating a pro-inflammatory role. Conversely, in the spleen of ASF-mice, mifepristone increased pro-inflammatory cytokines (TNF-α and IL-1ß), demonstrating an anti-inflammatory role. Furthermore, irrespective of sleep fragmentation, mifepristone increased pro-inflammatory cytokine gene expression in heart (IL-1ß), pre-frontal cortex (IL-1ß), and hypothalamus (IL-1ß). The results provide mixed evidence for pro- and anti-inflammatory functions of corticosterone to regulate inflammatory responses to acute sleep loss.

Dragon boat exercise reshapes the temporal-spatial dynamics of the brain.

Although exercise training has been shown to enhance neurological function, there is a shortage of research on how exercise training affects the temporal-spatial synchronization properties of functional networks, which are crucial to the neurological system. This study recruited 23 professional and 24 amateur dragon boat racers to perform simulated paddling on ergometers while recording EEG. The spatiotemporal dynamics of the brain were analyzed using microstates and omega complexity. Temporal dynamics results showed that microstate D, which is associated with attentional networks, appeared significantly altered, with significantly higher duration, occurrence, and coverage in the professional group than in the amateur group. The transition probabilities of microstate D exhibited a similar pattern. The spatial dynamics results showed the professional group had lower brain complexity than the amateur group, with a significant decrease in omega complexity in the α (8-12 Hz) and ß (13-30 Hz) bands. Dragon boat training may strengthen the attentive network and reduce the complexity of the brain. This study provides evidence that dragon boat exercise improves the efficiency of the cerebral functional networks on a spatiotemporal scale.

Investigation of the effects of curcumin and piperine on cyclophosphamide-induced brain injury in rats.

Cyclophosphamide (CP) is an antineoplastic drug widely used in chemotherapy. Curcumin (CUR) and piperine (PP) show a protective effect on neurodegenerative and neurological diseases. This research was designed to measure several biochemical parameters in the brain tissue of CP-applied rats to investigate the impact of combined CUR-PP administration. The study evaluated six groups of eight rats: Group 1 was the control; Groups 2 and 3 were administered 200 or 300 mg/kg CUR-PP via oral gavage; Group 4 received only 200 mg/kg CP on day 1; Groups 5 and 6 received CP + CUR-PP for 7 days. Data from all parameters indicated that CP caused brain damage. Phosphorylated TAU (pTAU), amyloid-beta peptide 1-42 (Aß1-42), glutamate (GLU), and gamma amino butyric acid (GABA) parameters were the same in Groups 4, 5, and 6. On the other hand, 8-hydroxy-2-deoxyguanosine (8-OHdG), nitric oxide (NO), interleukin-6 (IL-6), nuclear factor kappa beta (NF-kß), malondialdehyde (MDA), and tumor necrosis factor-alpha (TNF-α) levels in the CP + CUR-PP groups were lower than those in the CP group (p < 0.05). However, superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and reduced glutathione (GSH) parameters were higher in the CP + CUR-PP groups compared to the CP group (p < 0.05). It is thought that the similarity of Groups 5 and 6 with Group 4 in Aß1-42, pTAU, GLU, and GABA parameters hinder the determination of treatment protection however, they might have a therapeutic effect if the applied dose or study duration were changed. This study attempted to evaluate the effects of a CUR-PP combination on CP-induced brain damage in rats by measuring biochemical parameters and performing histopathological examinations. Based on the findings, this CUR-PP combination could be considered an alternative medicine option in cases with conditions similar to those evaluated in this study.

CHORDC1, the novel interacting partner of tau protein.

Alzheimer's disease is currently not curable. Almost all attempts to identify disease-modifying drugs failed and the causes of disease etiology are not well understood. Neurofibrillary tangles composed of pathological tau protein belong to the main hallmarks of this disease. Identification of novel physiological and pathological tau interacting proteins may lead to a better understanding of Alzheimer's disease pathology and tau physiology and therefore we performed a screening of the brain library by a yeast two-hybrid system intending to identify new tau interaction partners. We identified CHORDC1 (cysteine and histidine-rich domain-containing protein 1) as a novel tau interaction partner by this approach. The CHORDC1-tau interaction was validated by co-immunoprecipitation from rat brain tissues and by in vitro co-localization in the cellular model expressing full-length human tau protein. We believe that our results can be useful for researchers studying tau protein in health and disease.

A strike to the head: Parallels between the pediatric and adult human and the rodent in traumatic brain injury.

Traumatic brain injury (TBI) is a condition that occurs commonly in children from infancy through adolescence and is a global health concern. Pediatric TBI presents with a bimodal age distribution, with very young children (0-4 years) and adolescents (15-19 years) more commonly injured. Because children's brains are still developing, there is increased vulnerability to the effects of head trauma, which results in entirely different patterns of injury than in adults. Pediatric TBI has a profound and lasting impact on a child's development and quality of life, resulting in long-lasting consequences to physical, cognitive, and emotional development. Chronic issues like learning disabilities, behavioral problems, and emotional disturbances can develop. Early intervention and ongoing support are critical for minimizing these long-term deficits. Many animal models of TBI exist, and each varies significantly, displaying different characteristics of clinical TBI. The neurodevelopment differs in the rodent from the human in timing and effect, so TBI outcomes in the juvenile rodent can thus vary from the human child. The current review compares findings from preclinical TBI work in juvenile and adult rodents to clinical TBI research in pediatric and adult humans. We focus on the four brain regions most affected by TBI: the prefrontal cortex, corpus callosum, hippocampus, and hypothalamus. Each has its unique developmental projections and thus is impacted by TBI differently. This review aims to compare the healthy neurodevelopment of these four brain regions in humans to the developmental processes in rodents.

Formulation and Characterization of Silibinin Entrapped Nano-Liquid Crystals for Activity against Aß1-42 Neurotoxicity in In-Vivo Model.

Silibinin (SIL) Encapsulated Nanoliquid Crystalline (SIL-NLCs) particles were prepared to study neuroprotective effect against amyloid beta (Aß1-42) neurotoxicity in Balb/c mice model. Theses NLCs were prepared through hot emulsification and probe sonication technique. The pharmacodynamics was investigatigated on Aß1-42 intracerebroventricular (ICV) injected Balb/c mice. The particle size, zeta potential and drug loading were optimized to be 153 ± 2.5 nm, -21 mV, and 8.2%, respectively. Small angle X-ray (SAXS) and electron microscopy revealed to crystalline shape of SIL-NLCs. Thioflavin T (ThT) fluroscence and circular dichroism (CD) technique were employed to understand monomer inhibition effect of SIL-NLCs on Aß1-4. In neurobehavioral studies, SIL-NLCs exhibited enhanced mitigation of memory impairment induced on by Aß1-42 in T-maze and new object recognition test (NORT). Whereas biochemical and histopathological estimation of brain samples showed reduction in level of Aß1-42 aggregate, acetylcholine esterase (ACHE) and reactive oxygen species (ROS). SIL-NLCs treated animal group showed higher protection against Aß1-42 toxicity compared to free SIL and Donopezil (DPZ). Therefore SIL-NLCs promises great prospect in neurodegenerative diseases such as Alzheimer's disease.

Pia-FLOW: Deciphering hemodynamic maps of the pial vascular connectome and its response to arterial occlusion.

The pial vasculature is the sole source of blood supply to the neocortex. The brain is contained within the skull, a vascularized bone marrow with a unique anatomical connection to the brain meninges. Recent developments in tissue clearing have enabled detailed mapping of the entire pial and calvarial vasculature. However, what are the absolute flow rate values of those vascular networks? This information cannot accurately be retrieved with the commonly used bioimaging methods. Here, we introduce Pia-FLOW, a unique approach based on large-scale transcranial fluorescence localization microscopy, to attain hemodynamic imaging of the whole murine pial and calvarial vasculature at frame rates up to 1,000 Hz and spatial resolution reaching 5.4 µm. Using Pia-FLOW, we provide detailed maps of flow velocity, direction, and vascular diameters which can serve as ground-truth data for further studies, advancing our understanding of brain fluid dynamics. Furthermore, Pia-FLOW revealed that the pial vascular network functions as one unit for robust allocation of blood after stroke.

Predicting creative behavior using resting-state electroencephalography.

Neuroscience research has shown that specific brain patterns can relate to creativity during multiple tasks but also at rest. Nevertheless, the electrophysiological correlates of a highly creative brain remain largely unexplored. This study aims to uncover resting-state networks related to creative behavior using high-density electroencephalography (HD-EEG) and to test whether the strength of functional connectivity within these networks could predict individual creativity in novel subjects. We acquired resting state HD-EEG data from 90 healthy participants who completed a creative behavior inventory. We then employed connectome-based predictive modeling; a machine-learning technique that predicts behavioral measures from brain connectivity features. Using a support vector regression, our results reveal functional connectivity patterns related to high and low creativity, in the gamma frequency band (30-45 Hz). In leave-one-out cross-validation, the combined model of high and low networks predicts individual creativity with very good accuracy (r = 0.36, p = 0.00045). Furthermore, the model's predictive power is established through external validation on an independent dataset (N = 41), showing a statistically significant correlation between observed and predicted creativity scores (r = 0.35, p = 0.02). These findings reveal large-scale networks that could predict creative behavior at rest, providing a crucial foundation for developing HD-EEG-network-based markers of creativity.

APP dyshomeostasis in the pathogenesis of Alzheimer's disease: implications for current drug targets.

The Amyloid precursor protein (APP) is a transmembrane glycoprotein from which amyloid-ß (Aß) peptides are generated after proteolytic cleavage. Aß peptides are the main constituent of amyloid plaques in Alzheimer's Disease (AD). The physiological functions of APP in the human adult brain are very diverse including intracellular signaling, synaptic and neuronal plasticity, and cell adhesion, among others. There is growing evidence that APP becomes dysfunctional in AD and that this dyshomeostasis may impact several APP functions beyond Aß generation. The vast majority of current anti-amyloid approaches in AD have focused on reducing the synthesis of Aß or increasing the clearance of brain Aß aggregates following a paradigm in which Aß plays a solo in APP dyshomeostasis. A wider view places APP at the center stage in which Aß is an important, but not the only, factor involved in APP dyshomeostasis. Under this paradigm, APP dysfunction is universal in AD, but with some differences across different subtypes. Little is known about how to approach APP dysfunction therapeutically beyond anti-Aß strategies. In this review, we will describe the role of APP dyshomeostasis in AD beyond Aß and the potential therapeutic strategies targeting APP.

Benzodiazepine use in relation to long-term dementia risk and imaging markers of neurodegeneration: a population-based study.

BACKGROUND: Benzodiazepine use is common, particularly in older adults. Benzodiazepines have well-established acute adverse effects on cognition, but long-term effects on neurodegeneration and dementia risk remain uncertain. METHODS: We included 5443 cognitively healthy (MMSE ≥ 26) participants from the population-based Rotterdam Study (57.4% women, mean age 70.6 years). Benzodiazepine use from 1991 until baseline (2005-2008) was derived from pharmacy dispensing records, from which we determined drug type and cumulative dose. Benzodiazepine use was defined as prescription of anxiolytics (ATC-code: N05BA) or sedative-hypnotics (ATC-code: N05CD) between inception of pharmacy records and study baseline. Cumulative dose was calculated as the sum of the defined daily doses for all prescriptions. We determined the association with dementia risk until 2020 using Cox regression. Among 4836 participants with repeated brain MRI, we further determined the association of benzodiazepine use with changes in neuroimaging markers using linear mixed models. RESULTS: Of all 5443 participants, 2697 (49.5%) had used benzodiazepines at any time in the 15 years preceding baseline, of whom 1263 (46.8%) used anxiolytics, 530 (19.7%) sedative-hypnotics, and 904 (33.5%) used both; 345 (12.8%) participants were still using at baseline assessment. During a mean follow-up of 11.2 years, 726 participants (13.3%) developed dementia. Overall, use of benzodiazepines was not associated with dementia risk compared to never use (HR [95% CI]: 1.06 [0.90-1.25]), irrespective of cumulative dose. Risk estimates were somewhat higher for any use of anxiolytics than for sedative-hypnotics (HR 1.17 [0.96-1.41] vs 0.92 [0.70-1.21]), with strongest associations for high cumulative dose of anxiolytics (HR [95% CI] 1.33 [1.04-1.71]). In imaging analyses, current use of benzodiazepine was associated cross-sectionally with lower brain volumes of the hippocampus, amygdala, and thalamus and longitudinally with accelerated volume loss of the hippocampus and to a lesser extent amygdala. However, imaging findings did not differ by type of benzodiazepines or cumulative dose. CONCLUSIONS: In this population-based sample of cognitively healthy adults, overall use of benzodiazepines was not associated with increased dementia risk, but potential class-dependent adverse effects and associations with subclinical markers of neurodegeneration may warrant further investigation.

Utilizing human cerebral organoids to model breast cancer brain metastasis in culture.

BACKGROUND: Metastasis, the spread, and growth of malignant cells at secondary sites within a patient's body, accounts for over 90% of cancer-related mortality. Breast cancer is the most common tumor type diagnosed and the leading cause of cancer lethality in women in the United States. It is estimated that 10-16% breast cancer patients will have brain metastasis. Current therapies to treat patients with breast cancer brain metastasis (BCBM) remain palliative. This is largely due to our limited understanding of the fundamental molecular and cellular mechanisms through which BCBM progresses, which represents a critical barrier for the development of efficient therapies for affected breast cancer patients. METHODS: Previous research in BCBM relied on co-culture assays of tumor cells with rodent neural cells or rodent brain slice ex vivo. Given the need to overcome the obstacle for human-relevant host to study cell-cell communication in BCBM, we generated human embryonic stem cell-derived cerebral organoids to co-culture with human breast cancer cell lines. We used MDA-MB-231 and its brain metastatic derivate MDA-MB-231 Br-EGFP, other cell lines of MCF-7, HCC-1806, and SUM159PT. We leveraged this novel 3D co-culture platform to investigate the crosstalk of human breast cancer cells with neural cells in cerebral organoid. RESULTS: We found that MDA-MB-231 and SUM159PT breast cancer cells formed tumor colonies in human cerebral organoids. Moreover, MDA-MB-231 Br-EGFP cells showed increased capacity to invade and expand in human cerebral organoids. CONCLUSIONS: Our co-culture model has demonstrated a remarkable capacity to discern the brain metastatic ability of human breast cancer cells in cerebral organoids. The generation of BCBM-like structures in organoid will facilitate the study of human tumor microenvironment in culture.

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.