Patterns Of Gray Matter Volume Research Articles

Molecular mechanisms underlying human spatial cognitive ability revealed with neurotransmitter and transcriptomic mapping.

Mental rotation, one of the cores of spatial cognitive abilities, is closely associated with spatial processing and general intelligence. Although the brain underpinnings of mental rotation have been reported, the cellular and molecular mechanisms remain unexplored. Here, we used magnetic resonance imaging, a whole-brain spatial distribution atlas of 19 neurotransmitter receptors, transcriptomic data from Allen Human Brain Atlas, and mental rotation performances of 356 healthy individuals to identify the genetic/molecular foundation of mental rotation. We found significant associations of mental rotation performance with gray matter volume and fractional amplitude of low-frequency fluctuations in primary visual cortex, fusiform gyrus, primary sensory-motor cortex, and default mode network. Gray matter volume and fractional amplitude of low-frequency fluctuations in these brain areas also exhibited significant sex differences. Importantly, spatial correlation analyses were conducted between the spatial patterns of gray matter volume or fractional amplitude of low-frequency fluctuations with mental rotation and the spatial distribution patterns of neurotransmitter receptors and transcriptomic data, and identified the related genes and neurotransmitter receptors associated with mental rotation. These identified genes are localized on the X chromosome and are mainly involved in trans-synaptic signaling, transmembrane transport, and hormone response. Our findings provide initial evidence for the neural and molecular mechanisms underlying spatial cognitive ability.

Structural and Functional Brain Patterns Predict Formal Thought Disorder’s Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study

BackgroundFormal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level. MethodsTwo hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up. ResultsCross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%. ConclusionsWe report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

Common and distinct fronto-striatal volumetric changes in heroin and cocaine use disorders.

Different drugs of abuse impact the morphology of fronto-striatal dopaminergic targets in both common and unique ways. While dorsal striatal volume tracks with addiction severity across drug classes, opiates impact ventromedial prefrontal cortex (vmPFC) and nucleus accumbens (NAcc) neuroplasticity in preclinical models, and psychostimulants alter inhibitory control, rooted in cortical regions such as the inferior frontal gyrus (IFG). We hypothesized parallel grey matter volume changes associated with human heroin or cocaine use disorder: lower grey matter volume of vmPFC/NAcc in heroin use disorder and IFG in cocaine use disorder, and putamen grey matter volume to be associated with addiction severity measures (including craving) across both. In this cross-sectional study, we quantified grey matter volume (P < 0.05-corrected) in age/sex/IQ-matched individuals with heroin use disorder (n = 32, seven females), cocaine use disorder (n = 32, six females) and healthy controls (n = 32, six females) and compared fronto-striatal volume between groups using voxel-wise general linear models and non-parametric permutation-based tests. Overall, individuals with heroin use disorder had smaller vmPFC and NAcc/putamen volumes than healthy controls. Bilateral lower IFG grey matter volume patterns were specifically evident in cocaine versus heroin use disorders. Correlations between addiction severity measures and putamen grey matter volume did not reach nominal significance level in this sample. These results indicate alterations in dopamine-innervated regions (in the vmPFC and NAcc) in heroin addiction. For the first time we demonstrate lower IFG grey matter volume specifically in cocaine compared with heroin use disorder, suggesting a signature of reduced inhibitory control, which remains to be tested directly using select behavioural measures. Overall, results suggest substance-specific volumetric changes in human psychostimulant or opiate addiction, with implications for fine-tuning biomarker and treatment identification by primary drug of abuse.

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.

Brain Structural and Functional Dissociated Patterns in Degenerative Cervical Myelopathy: A Case-Controlled Retrospective Resting-State fMRI Study.

BackgroundPrevious studies have shown the whole-brain global functional connectivity density (gFCD) and gray matter volume (GMV) alterations in patients with degenerative cervical myelopathy (DCM). However, no study aimed to investigate the associations between the spatial patterns of GMV and gFCD alterations in patients with DCM.MethodsStructural data and resting-state functional MRI data of 35 DCM patients and 35 matched healthy controls were collected to assess their gFCD and GMV and investigate gFCD and GMV alterations in patients with DCM and their spatial pattern associations.ResultsIn our current study, significant gFCD and GMV differences were observed in some regions of the visual system, sensorimotor cortices, and cerebellum between patients with DCM and healthy controls. In our findings, decreased gFCD was found in areas primarily located at the sensorimotor cortices, while increased gFCD was observed primarily within areas located at the visual system and cerebellum. Decreased GMV was seen in the left thalamus, bilateral supplementary motor area (SMA), and left inferior occipital cortices in patients with DCM, while increased GMV was observed in the cerebellum.ConclusionOur findings suggest that structural and functional alterations independently contributed to the neuropathology of DCM. However, longitudinal studies are still needed to further illustrate the associations between structural deficits and functional alterations underlying the onset of brain abnormalities as DCM develops.

Brain patterns of pace - but not rhythm - are associated with vascular disease in older adults.

Distinct domains of gait such as pace and rhythm are linked to an increased risk for cognitive decline, falls, and dementia in aging. The brain substrates supporting these domains and underlying diseases, however, remain relatively unknown. The current study aimed to identify patterns of gray matter volume (GMV) associated with pace and rhythm, and whether these patterns vary as a function of vascular and non-vascular comorbidities. A cross-sectional sample of 297 older adults (M Age=72.5 years ± 7.2 years, 43% women) without dementia was drawn from the Tasmanian Study of Cognition and Gait (TASCOG). Factor analyses were used to reduce eight quantitative gait variables into two domains. The "pace" domain was primarily composed of gait speed, stride length, and double support time. The "rhythm" domain was composed of swing time, stance time, and cadence. Multivariate covariance-based analyses adjusted for age, sex, education, total intracranial volume, and presence of mild cognitive impairment identified gray matter volume (GMV) patterns associated with pace and rhythm, as well as participant-specific expression (or factor) scores for each pattern. Pace was positively associated with GMV in the right superior temporal sulcus, bilateral supplementary motor areas (SMA), and bilateral cerebellar regions. Rhythm was positively associated with GMV in bilateral SMA, prefrontal, cingulate, and paracingulate cortices. The GMV pattern associated with pace was less expressed in participants with any vascular disease; this association was also found independently with hypertension, diabetes, and myocardial infarction. Both pace and rhythm domains of gait were associated with the volume of brain structures that have been linked to controlled and automatic aspects of gait control, as well as with structures involved in multisensory integration. Only the brain structures associated with pace, however, were associated with vascular disease.

Spatially Covarying Patterns of Gray Matter Volume and Concentration Highlight Distinct Regions in Schizophrenia.

Introduction: Individuals with schizophrenia have consistent gray matter reduction throughout the cortex when compared to healthy individuals. However, the reduction patterns vary based on the quantity (concentration or volume) utilized by study. The objective of this study was to identify commonalities between gray matter concentration and gray matter volume effects in schizophrenia.Methods: We performed both univariate and multivariate analyses of case/control effects on 145 gray matter images from 66 participants with schizophrenia and 79 healthy controls, and processed to compare the concentration and volume estimates.Results: Diagnosis effects in the univariate analysis showed similar areas of volume and concentration reductions in the insula, occipitotemporal gyrus, temporopolar area, and fusiform gyrus. In the multivariate analysis, healthy controls had greater gray matter volume and concentration additionally in the superior temporal gyrus, prefrontal cortex, cerebellum, calcarine, and thalamus. In the univariate analyses there was moderate overlap between gray matter concentration and volume across the entire cortex (r = 0.56, p = 0.02). The multivariate analyses revealed only low overlap across most brain patterns, with the largest correlation (r = 0.37) found in the cerebellum and vermis.Conclusions: Individuals with schizophrenia showed reduced gray matter volume and concentration in previously identified areas of the prefrontal cortex, cerebellum, and thalamus. However, there were only moderate correlations across the cortex when examining the different gray matter quantities. Although these two quantities are related, concentration and volume do not show identical results, and therefore, should not be used interchangeably in the literature.

Gray matter volume covariance networks are associated with altered emotional processing in bipolar disorder: a source-based morphometry study

Widespread regional gray matter volume (GMV) alterations have been reported in bipolar disorder (BD). Structural networks, which are thought to better reflect the complex multivariate organization of the brain, and their clinical and psychological function have not been investigated yet in BD. 24 patients with BD type-I (BD-I), and 30 with BD type-II (BD-II), and 45 controls underwent MRI scan. Voxel-based morphometry and source-based morphometry (SBM) were performed to extract structural covariation patterns of GMV. SBM components associated with morphometric differences were compared among diagnoses. Executive function and emotional processing correlated with morphometric characteristics. Compared to controls, BD-I showed reduced GMV in the temporo-insular-parieto-occipital cortex and in the culmen. An SBM component spanning the prefrontal-temporal-occipital network exhibited significantly lower GMV in BD-I compared to controls, but not between the other groups. The structural network covariance in BD-I was associated with the number of previous manic episodes and with worse executive performance. Compared to BD-II, BD-I showed a loss of GMV in the temporal-occipital regions, and this was correlated with impaired emotional processing. Altered prefrontal-temporal-occipital network structure could reflect a neural signature associated with visuospatial processing and problem-solving impairments as well as emotional processing and illness severity in BD-I.

Cognitively defined subtypes of Alzheimer's disease

AbstractBackgroundWe have developed a framework for using cognitive test results at Alzheimer’s disease (AD) diagnosis to categorize people into AD subgroups. We have shown that risk factors and genetic variant associations vary across subgroups. We also showed differences in gray matter volume (GMV) using voxel‐based p‐values. Here we present new findings with beta coefficient maps and a movie showing regional atrophy associated with greater global atrophy.MethodWe use data from the first ADNI study visit with AD for 624 amyloid positive patients, and the first visit for 119 amyloid negative cognitively normal controls (CN). We generated voxel‐wise gray matter (GM) W‐scores as (actual GM‐expected GM)/SD. Expected GM is based on voxel‐wise regressions in CN in SPM12 with age, sex, ICV, and field strength. SD is the voxel‐specific SD of residuals from the regression analyses. We obtained global W‐scores as the number of voxels with W&lt;‐1.65. We generated beta‐coefficient maps from SPM, controlling for global W‐score, age, sex, ICV, and field strength. We obtained regional W‐scores using the Desikan‐Killiany cortical parcellation atlas and performed regression analyses predicting regional W‐scores as a function of total W‐score as a continuous predictor, and present the results as a movie for each region.ResultThere were 267 people with no prominent differences across domains (AD‐No Domain), 189 with AD‐Memory, 14 AD‐Executive, 46 AD‐Language, 85 AD‐Visuospatial, and 23 AD‐multiple domains. Groups did not differ with respect to sex, years of education, handedness, or proportion who were non‐Hispanic white. Mean age at diagnosis ranged from 73 (AD‐Visuospatial and controls) to 77 (AD‐Language; omnibus p = 0.015) Compared to other groups, the AD‐Memory group consistently had greater GMV loss in medial temporal lobes (Figure 1). Each of the other groups had substantial areas of cortex with greater GMV loss than the AD‐Memory group (Figure 2). Regions associated with more global atrophy varied substantially across groups (Figure 3: this is a still of coordinated movies for each subgroup).ConclusionCognitively defined AD subgroups differ in patterns of GMV in regions that make sense with the cognitive phenotype.

Eating a Weekly Serving of Walnuts Relates to Beneficial Brain Imaging Phenotypes in a Cohort at Increased Risk of Alzheimer’s Disease

Abstract Objectives There is increasing evidence on the brain benefits of nut consumption. Magnetic resonance imaging (MRI) enables the detection of brain changes associated with neurodegenerative and vascular diseases. In middle-aged cognitively unimpaired subjects at increased risk of Alzheimer's disease (AD), we searched for cross-sectional associations between nut consumption and MRI-assessed brain phenotypes, including white matter hyperintensities (WMH, a marker of cerebral small vessel disease that confers increased risk of AD and stroke) and topographic patterns of gray matter volume (GMv). Methods We performed high-resolution structural MRI in 382 participants from the ALFA study (ALzheimer and FAmilies) cohort, which is enriched by family history of sporadic AD and APOE-ε4 carriership, the most prevalent genetic risk factor for AD. We assessed nut consumption by a food-frequency questionnaire containing five items related to nuts. WMH volume was normalized by intracranial volume (TIV) and rank-transformed. For WMH, we conducted univariate models with two factors: nut consumption (&amp;lt;1 and ≥1 serving/week) and being APOE-ε4 homozygote (yes/no), and their interaction, adjusting for age, gender, hypertension, hypercholesterolemia, and adherence to Mediterranean Diet. We also explored whether nut consumption related to differences in GMv using a voxel-based morphometry analysis corrected by age, gender, number of APOE-ε4 alleles, hypertension, hypercholesterolemia, adherence to Mediterranean Diet, and TIV. Results 187 participants reported nut consumption of ≥1 serving/week, 148 of whom disclosed walnut consumption. Nut (or walnut) consumption of ≥1 serving/week related to a significantly lower WMH volume (P ≤ 0.035, both). We found no statistically significant nut × APOE-ε4 interactions. Participants reporting consumption of ≥1 walnut serving/week showed significantly greater GMv in areas including the anterior/middle cingulate cortex, which is relevant for cognition and has been associated with successful aging. Conclusions Nut (in particular walnut) consumption relates to beneficial phenotypes of both cerebral vasculature and regional GMv. Funding Sources Instituto de Salud Carlos III, Spain; “la Caixa” Foundation; California Walnut Commission.

White matter hyperintensities mediate gray matter volume and processing speed relationship in cognitively unimpaired participants.

White matter hyperintensities (WMH) have been extensively associated with cognitive impairment and reductions in gray matter volume (GMv) independently. This study explored whether WMH lesion volume mediates the relationship between cerebral patterns of GMv and cognition in 521 (mean age 57.7 years) cognitively unimpaired middle‐aged individuals. Episodic memory (EM) was measured with the Memory Binding Test and executive functions (EF) using five WAIS‐IV subtests. WMH were automatically determined from T2 and FLAIR sequences and characterized using diffusion‐weighted imaging (DWI) parameters. WMH volume was entered as a mediator in a voxel‐wise mediation analysis relating GMv and cognitive performance (with both EM and EF composites and the individual tests independently). The mediation model was corrected by age, sex, education, number of Apolipoprotein E (APOE)‐ε4 alleles and total intracranial volume. We found that even at very low levels of WMH burden in the cohort (median volume of 3.2 mL), higher WMH lesion volume was significantly associated with a widespread pattern of lower GMv in temporal, frontal, and cerebellar areas. WMH mediated the relationship between GMv and EF, mainly driven by processing speed, but not EM. DWI parameters in these lesions were compatible with incipient demyelination and axonal loss. These findings lead to the reflection on the relevance of the control of cardiovascular risk factors in middle‐aged individuals as a valuable preventive strategy to reduce or delay cognitive decline.

Patterns of co‐altered brain structure and function underlying neurological soft signs in schizophrenia spectrum disorders

Neurological soft signs (NSS) comprise a broad range of subtle neurological deficits and are considered to represent external markers of sensorimotor dysfunction frequently found in mental disorders of presumed neurodevelopmental origin. Although NSS frequently occur in schizophrenia spectrum disorders (SSD), specific patterns of co-altered brain structure and function underlying NSS in SSD have not been investigated so far. It is unclear whether gray matter volume (GMV) alterations or aberrant brain activity or a combination of both, are associated with NSS in SSD. Here, 37 right-handed SSD patients and 37 matched healthy controls underwent motor assessment and magnetic resonance imaging (MRI) at 3 T. NSS were examined on the Heidelberg NSS scale. We used a multivariate data fusion technique for multimodal MRI data-multiset canonical correlation and joint independent component analysis (mCCA + jICA)-to investigate co-altered patterns of GMV and intrinsic neural fluctuations (INF) in SSD patients exhibiting NSS. The mCCA + jICA model indicated two joint group-discriminating components (temporoparietal/cortical sensorimotor and frontocerebellar/frontoparietal networks) and one modality-specific group-discriminating component (p < .05, FDR corrected). NSS motor score was associated with joint frontocerebellar/frontoparietal networks in SSD patients. This study highlights complex neural pathomechanisms underlying NSS in SSD suggesting aberrant structure and function, predominantly in cortical and cerebellar systems that critically subserve sensorimotor dynamics and psychomotor organization.

Multivariate patterns of gray matter volume in thalamic nuclei are associated with positive schizotypy in healthy individuals.

Previous models suggest biological and behavioral continua among healthy individuals (HC), at-risk condition, and full-blown schizophrenia (SCZ). Part of these continua may be captured by schizotypy, which shares subclinical traits and biological phenotypes with SCZ, including thalamic structural abnormalities. In this regard, previous findings have suggested that multivariate volumetric patterns of individual thalamic nuclei discriminate HC from SCZ. These results were obtained using machine learning, which allows case-control classification at the single-subject level. However, machine learning accuracy is usually unsatisfactory possibly due to phenotype heterogeneity. Indeed, a source of misclassification may be related to thalamic structural characteristics of those HC with high schizotypy, which may resemble structural abnormalities of SCZ. We hypothesized that thalamic structural heterogeneity is related to schizotypy, such that high schizotypal burden would implicate misclassification of those HC whose thalamic patterns resemble SCZ abnormalities. Following a previous report, we used Random Forests to predict diagnosis in a case-control sample (SCZ = 131, HC = 255) based on thalamic nuclei gray matter volumes estimates. Then, we investigated whether the likelihood to be classified as SCZ (π-SCZ) was associated with schizotypy in 174 HC, evaluated with the Schizotypal Personality Questionnaire. Prediction accuracy was 72.5%. Misclassified HC had higher positive schizotypy scores, which were correlated with π-SCZ. Results were specific to thalamic rather than whole-brain structural features. These findings strengthen the relevance of thalamic structural abnormalities to SCZ and suggest that multivariate thalamic patterns are correlates of the continuum between schizotypy in HC and the full-blown disease.

Patterns of gray matter alterations in migraine and restless legs syndrome.

ObjectivesMigraine and restless legs syndrome (RLS) are often comorbid and share elements of pathology; however, their neuroanatomical underpinnings are poorly understood. This study aimed to identify patterns of gray matter volume (GMV) alteration specific to and common among patients with RLS, migraine, and comorbid migraine and RLS.MethodsHigh‐resolution T1‐weighted images were acquired from 116 subjects: 27 RLS patients, 22 migraine patients, 22 patients with comorbid migraine and RLS, and 45 healthy controls. Direct group comparisons and conjunction analysis were first used to localize the distinct and shared neural signatures of migraine and RLS. We also investigated whether the shared neural signature could be replicated in an additional comorbid migraine/RLS group.ResultsCompared with healthy controls, migraine patients showed GMV changes in the lateral occipital cortex, cerebellum, frontal pole, and middle frontal gyrus (MFG), and RLS patients showed GMV changes in the thalamus, middle temporal gyrus, anterior cingulate cortex, insular cortex, and MFG. In migraine, compared with RLS, GMV differences were found in the precuneus, lateral occipital and occipital fusiform cortex, superior frontal and precentral gyri, and cerebellum. Conjunction analyses for these disorders showed altered GMV in the MFG, also found in patients with comorbid migraine and RLS. The GMV of the MFG also correlated with sleep quality in patients with comorbid migraine and RLS.InterpretationMigraine and RLS are characterized by shared and distinctive neuroanatomical characteristics, with a specific role of the MFG. These findings may be related to shared pathophysiology of these two distinct disorders.

The loss of macular ganglion cells begins from the early stages of disease and correlates with brain atrophy in multiple sclerosis patients

Background: The importance of neurodegeneration in multiple sclerosis (MS) is increasingly well recognized. Objectives: To evaluate retinal pathology using optical coherence tomography (OCT) and to investigate possible associations between retinal layers’ thickness and specific patterns of gray matter volume in patients with a new diagnosis of MS. Methods: A total of 31 patients underwent OCT scans and brain magnetic resonance imaging. In total, 30 controls underwent the same OCT procedure. The association between focal cortical volume and OCT measurements was investigated with voxel-based morphometry (VBM). Results: Compared to controls, patients’ macular retinal nerve fiber layer (mRNFL), macular ganglion cell layer (mGCL), macular inner plexiform layer (mIPL), and macular ganglion cell-inner plexiform layer (mGCIPL) thickness were significantly reduced (p = 0.0009, p = 0.0003, p = 0.0049, and p = 0.0007, respectively). Peripapillary RNFL (pRNFL) and temporal sector pRNFL (T-pRNFL) did not show any significant changes, although there was a trend toward T-pRNFL thinning (p = 0.0254). VBM analysis showed that mGCIPL and pRNFL were significantly correlated with the volume reduction of occipital-parietal cortex (p < 0.005). Conclusion: mRNFL, mGCL, and mIPL are significantly reduced in MS patients without concomitant pRNFL thinning. These retinal changes show a significant association with cortical regions that are known to be important for visuospatial performance.

Regional patterns of gray matter volume, hypometabolism, and beta-amyloid in groups at risk of Alzheimer's disease

Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) deposition and neurodegeneration. To seek for signs of such pathologies, we compared regional biomarker degrees and patterns of Aβ deposition, glucose hypometabolism, and gray matter volume (GMV) reduction in 3 groups at risk of AD. In elderly carriers of the apolipoprotein E ε4 (APOE4, n = 17), patients with subjective cognitive decline (n = 16), and patients with mild cognitive impairment (n = 30), head-to-head intermodality comparisons were performed on cross-sectional structural magnetic resonance images as well as 18F-fluorodeoxyglucose and 18F-florbetapir positron emission tomography scans. In mild cognitive impairment patients, 3 distinct biomarker patterns were recovered, similarly seen in AD patients: (1) in medial temporal regions, local GMV reduction exceeded hypometabolism, (2) in temporoparietal regions, hypometabolism predominated over GMV reduction, and (3) in frontal regions, Aβ deposition exceeded GMV reduction and hypometabolism. In subjective cognitive decline patients, only pattern 1 was detected, while APOE4 carriers demonstrated only pattern 3. Our findings highlight that regional AD-like biomarker patterns may vary across different at-risk populations, potentially reflecting differential mediators of these risks.

Aberrant brain grey matter volume patterns differ among Chinese Han drug-naïve depression patients with acute and chronic stress.

Chronic or acute stress can induce structural changes and brain alterations associated with the neural mechanisms of depression. Aimed to investigate the GMV alterations in the drug-naïve depression patients with chronic and acute stress experience,we enrolled fifty depression patients with acute stress experience, fifty five depression patients with chronic stress experience and forty seven healthy controls(HC) to participant in the present study. We used voxel-based morphometry to analyze the brain grey matter volume (GMV) alterations. Compared with the HC, the patients with acute stress and those with chronic stress exhibited a distinct GMV impairment pattern. Widespread, decreased GMV was detected in most of the cerebral cortex in all the depression patients. Importantly, the greatest finding in our study is that the decreased GMV in the depression patients with chronic stress was more widespread than that in the patients with acute stress. All brain regions with decreased GMV participated in the regulation of emotions, memory, and executive function processing, which is consistent with previous findings. There was no significant difference between the major depression disorder patients with acute stressful life events and those with chronic stressful life events, and this finding largely weakens the support of our current conclusion. Thus, we cannot confirm this postulation. However, our findings probably indicate that GMV may be more sensitive to major depression disorder patients when compared to healthy controls, it did not sensitive when in the comparison of patient's group. Overall, our findings provide important information for the use of appropriate treatment methods to address acute stress and alleviate chronic stress in patients with depression, and such treatments can delay the deterioration of the affected brain regions and improve remission rates. More importantly, all the inexplicable findings in the present study encourage us to conduct a follow-up study to describe the developmental trajectory of the pathological brain features of depression patients and explore therapeutic targets for future personalized treatment.

Grey matter volume patterns in thalamic nuclei are associated with schizotypy in healthy subjects

IntroductionSchizotypy refers to a set of temporally stable traits that are observed in the general population and that resemble, in attenuated form, the symptoms of schizophrenia. In a previous work, we identified volumetric patterns in thalamic subregions which were associated with disease status, and trained a random forests classifier, accounting for such thalamic volumetric patterns, that discriminated healthy controls (HC) from patients with schizophrenia (SCZ) (81% accuracy) [1].Objectivesi) to assess performance of random forests classifier developed by Pergola and coworkers [1], in an independent sample of healthy subjects; ii) to test whether false positives (FP), i.e. HC classified as SCZ based on such classifier would be associated with greater schizotypy compared with true negatives (TN), i.e. HC classified as such.MethodsA total of 167 HC participated in the MRI study and filled the Schizotypal Personality Questionnaire (SPQ). We pre-processed MRI data with SPM8 and DARTEL. Then, we used thalamic grey matter volumes (GMV) as features in the random forests prediction of disease status at the single subject level. Finally, we tested SPQ scores differences between FP and TN with Mann-Whitney test.ResultsThe classification accuracy was 71%. FP had greater SPQ scores compared to TN (P = 0.007).ConclusionsClassification accuracy of our classifier in an independent sample suggests that thalamic GMV patterns are reproducible markers of disease status. Furthermore, the present results also suggest that variability of thalamic GMV patterns in HC may have relevance for subclinical phenotypes related to schizophrenia spectrum.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Brain structural and functional dissociated patterns in schizophrenia

BackgroundAlthough previous studies found that aberrations in gray matter volume (GMV) and global functional connectivity density (gFCD) are important characteristics of schizophrenia, to the best of our knowledge no study to date has investigated the associations between the spatial distribution patterns of GMV and gFCD alterations. We investigated pattern changes in gFCD and GMV among patients with schizophrenia and their associated spatial distributions.MethodsNinety-five patients with schizophrenia and 93 matched healthy controls underwent structural and resting-state functional MRI scanning to assess gFCD and GMV.ResultsWe found that gFCD increased in the subcortical regions (caudate, pallidum, putamen, and thalami) and limbic system (left hippocampus and parahippocampus), and decreased in the posterior parieto-occipito-temporal cortices (postcentral gyri, occipital cortex, temporo-occipital conjunction, and inferior parietal lobule), in patients with schizophrenia. By contrast, we found decreased GMV in brain regions including the frontal, parietal, temporal, occipital, cingulate cortices, and the insular, striatum, thalamus in these patients. Increased gFCD primarily occurred in subcortical regions including the basal ganglia and some regions of the limbic system. Decreased gFCD appeared primarily in the cortical regions. There were no statistically significant correlations between changes in gFCD and GMV, and their spatial distribution patterns, in different regions.ConclusionsOur findings indicate that gFCD and GMV are both perturbed in multiple brain regions in schizophrenia. gFCD and GMV consistently decreased in the cortical regions, with the exception of the Supplementary Motor Area (SMA). However, in the sub-cortical regions, the alterations of gFCD and GMV showed the opposite pattern, with increased gFCD and decreased GMV simultaneously observed in these regions. Overall, our findings suggest that structural and functional alterations appear to contribute independently to the neurobiology of schizophrenia.

Grey matter volume patterns in thalamic nuclei are associated with familial risk for schizophrenia

Previous evidence suggests reduced thalamic grey matter volume (GMV) in patients with schizophrenia (SCZ). However, it is not considered an intermediate phenotype for schizophrenia, possibly because previous studies did not assess the contribution of individual thalamic nuclei and employed univariate statistics. Here, we hypothesized that multivariate statistics would reveal an association of GMV in different thalamic nuclei with familial risk for schizophrenia. We also hypothesized that accounting for the heterogeneity of thalamic GMV in healthy controls would improve the detection of subjects at familial risk for the disorder.We acquired MRI scans for 96 clinically stable SCZ, 55 non-affected siblings of patients with schizophrenia (SIB), and 249 HC. The thalamus was parceled into seven regions of interest (ROIs). After a canonical univariate analysis, we used GMV estimates of thalamic ROIs, together with total thalamic GMV and premorbid intelligence, as features in Random Forests to classify HC, SIB, and SCZ. Then, we computed a Misclassification Index for each individual and tested the improvement in SIB detection after excluding a subsample of HC misclassified as patients.Random Forests discriminated SCZ from HC (accuracy=81%) and SIB from HC (accuracy=75%). Left anteromedial thalamic volumes were significantly associated with both multivariate classifications (p<0.05). Excluding HC misclassified as SCZ improved greatly HC vs. SIB classification (Cohen's d=1.39). These findings suggest that multivariate statistics identify a familial background associated with thalamic GMV reduction in SCZ. They also suggest the relevance of inter-individual variability of GMV patterns for the discrimination of individuals at familial risk for the disorder.