ABSTRACT
BACKGROUND: Evidence regarding cortical atrophy patterns in Parkinson's disease (PD) with probable rapid eye movement sleep behavior disorder (RBD) (PD-pRBD) remains scarce. Cortical mean diffusivity (cMD), as a novel imaging biomarker highly sensitive to detecting cortical microstructural changes in different neurodegenerative diseases, has not been investigated in PD-pRBD yet. OBJECTIVES: The aim was to investigate cMD as a sensitive measure to identify subtle cortical microstructural changes in PD-pRBD and its relationship with cortical thickness (CTh). METHODS: Twenty-two PD-pRBD, 31 PD without probable RBD (PD-nonpRBD), and 28 healthy controls (HC) were assessed using 3D T1-weighted and diffusion-weighted magnetic resonance imaging on a 3-T scanner and neuropsychological testing. Measures of cortical brain changes were obtained through cMD and CTh. Two-class group comparisons of a general linear model were performed (P < 0.05). Cohen's d effect size for both approaches was computed. RESULTS: PD-pRBD patients showed higher cMD than PD-nonpRBD patients in the left superior temporal, superior frontal, and precentral gyri, precuneus cortex, as well as in the right middle frontal and postcentral gyri and paracentral lobule (d > 0.8), whereas CTh did not detect significant differences. PD-pRBD patients also showed increased bilateral posterior cMD in comparison with HCs (d > 0.8). These results partially overlapped with CTh results (0.5 < d < 0.8). PD-nonpRBD patients showed no differences in cMD when compared with HCs but showed cortical thinning in the left fusiform gyrus and lateral occipital cortex bilaterally (d > 0.5). CONCLUSIONS: cMD may be more sensitive than CTh displaying significant cortico-structural differences between PD subgroups, indicating this imaging biomarker's utility in studying early cortical changes in PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Subject(s)
Cerebral Cortex , Parkinson Disease , REM Sleep Behavior Disorder , Humans , Parkinson Disease/diagnostic imaging , Parkinson Disease/pathology , Parkinson Disease/complications , Parkinson Disease/physiopathology , REM Sleep Behavior Disorder/diagnostic imaging , REM Sleep Behavior Disorder/pathology , Male , Female , Aged , Middle Aged , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/pathology , Magnetic Resonance Imaging , Diffusion Magnetic Resonance Imaging/methods , Atrophy/pathology , Neuropsychological TestsABSTRACT
The risk factors for post-COVID-19 cognitive impairment have been poorly described. This study aimed to identify the sociodemographic, clinical, and lifestyle characteristics that characterize a group of post-COVID-19 condition (PCC) participants with neuropsychological impairment. The study sample included 426 participants with PCC who underwent a neurobehavioral evaluation. We selected seven mental speed processing and executive function variables to obtain a data-driven partition. Clustering algorithms were applied, including K-means, bisecting K-means, and Gaussian mixture models. Different machine learning algorithms were then used to obtain a classifier able to separate the two clusters according to the demographic, clinical, emotional, and lifestyle variables, including logistic regression with least absolute shrinkage and selection operator (LASSO) (L1) and Ridge (L2) regularization, support vector machines (linear/quadratic/radial basis function kernels), and decision tree ensembles (random forest/gradient boosting trees). All clustering quality measures were in agreement in detecting only two clusters in the data based solely on cognitive performance. A model with four variables (cognitive reserve, depressive symptoms, obesity, and change in work situation) obtained with logistic regression with LASSO regularization was able to classify between good and poor cognitive performers with an accuracy and a weighted averaged precision of 72%, a recall of 73%, and an area under the curve of 0.72. PCC individuals with a lower cognitive reserve, more depressive symptoms, obesity, and a change in employment status were at greater risk for poor performance on tasks requiring mental processing speed and executive function. Study registration: www.ClinicalTrials.gov , identifier NCT05307575.
ABSTRACT
Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging.
Subject(s)
Aging/physiology , Cerebral Cortex/physiology , Education , Hippocampus/physiology , Aged , Brain/diagnostic imaging , Brain/physiology , Cerebral Cortex/diagnostic imaging , Female , Hippocampus/diagnostic imaging , Humans , Magnetic Resonance Imaging , Male , Middle AgedABSTRACT
INTRODUCTION: Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS: We included 436 patients from the European-DLB consortium and the Mayo Clinic. Sex differences and sex-by-age interactions were assessed through visual atrophy rating scales (n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness (n = 165; 69 ± 9 years, 72% males). RESULTS: We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex-by-age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION: We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. HIGHLIGHTS: Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales. Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods. Sex differences in gray matter measures in DLB tended to disappear with increasing age.
Subject(s)
Alzheimer Disease , Lewy Body Disease , Humans , Male , Female , Lewy Body Disease/diagnostic imaging , Lewy Body Disease/pathology , Alzheimer Disease/pathology , Sex Characteristics , Cerebral Cortex/pathology , Atrophy/pathology , Magnetic Resonance ImagingABSTRACT
Disease-modifying treatments are currently being trialled in multiple system atrophy. Approaches based solely on clinical measures are challenged by heterogeneity of phenotype and pathogenic complexity. Neurofilament light chain protein has been explored as a reliable biomarker in several neurodegenerative disorders but data on multiple system atrophy have been limited. Therefore, neurofilament light chain is not yet routinely used as an outcome measure in multiple system atrophy. We aimed to comprehensively investigate the role and dynamics of neurofilament light chain in multiple system atrophy combined with cross-sectional and longitudinal clinical and imaging scales and for subject trial selection. In this cohort study, we recruited cross-sectional and longitudinal cases in a multicentre European set-up. Plasma and CSF neurofilament light chain concentrations were measured at baseline from 212 multiple system atrophy cases, annually for a mean period of 2 years in 44 multiple system atrophy patients in conjunction with clinical, neuropsychological and MRI brain assessments. Baseline neurofilament light chain characteristics were compared between groups. Cox regression was used to assess survival; receiver operating characteristic analysis to assess the ability of neurofilament light chain to distinguish between multiple system atrophy patients and healthy controls. Multivariate linear mixed-effects models were used to analyse longitudinal neurofilament light chain changes and correlated with clinical and imaging parameters. Polynomial models were used to determine the differential trajectories of neurofilament light chain in multiple system atrophy. We estimated sample sizes for trials aiming to decrease neurofilament light chain levels. We show that in multiple system atrophy, baseline plasma neurofilament light chain levels were better predictors of clinical progression, survival and degree of brain atrophy than the neurofilament light chain rate of change. Comparative analysis of multiple system atrophy progression over the course of disease, using plasma neurofilament light chain and clinical rating scales, indicated that neurofilament light chain levels rise as the motor symptoms progress, followed by deceleration in advanced stages. Sample size prediction suggested that significantly lower trial participant numbers would be needed to demonstrate treatment effects when incorporating plasma neurofilament light chain values into multiple system atrophy clinical trials in comparison to clinical measures alone. In conclusion, neurofilament light chain correlates with clinical disease severity, progression and prognosis in multiple system atrophy. Combined with clinical and imaging analysis, neurofilament light chain can inform patient stratification and serve as a reliable biomarker of treatment response in future multiple system atrophy trials of putative disease-modifying agents.
Subject(s)
Multiple System Atrophy , Humans , Cohort Studies , Cross-Sectional Studies , Intermediate Filaments , Neurofilament Proteins , Biomarkers , Disease ProgressionABSTRACT
How the brain represents gender identity is largely unknown, but some neural differences have recently been discovered. We used an intrinsic ignition framework to investigate whether there are gender differences in the propagation of neural activity across the whole-brain and within resting-state networks. Studying 29 trans men and 17 trans women with gender incongruence, 22 cis women, and 19 cis men, we computed the capability of a given brain area in space to propagate activity to other areas (mean-ignition), and the variability across time for each brain area (node-metastability). We found that both measurements differentiated all groups across the whole brain. At the network level, we found that compared to the other groups, cis men showed higher mean-ignition of the dorsal attention network and node-metastability of the dorsal and ventral attention, executive control, and temporal parietal networks. We also found higher mean-ignition values in cis men than in cis women within the executive control network, but higher mean-ignition in cis women than cis men and trans men for the default mode. Node-metastability was higher in cis men than cis women in the somatomotor network, while both mean-ignition and node-metastability were higher for cis men than trans men in the limbic network. Finally, we computed correlations between these measurements and a body image satisfaction score. Trans men's dissatisfaction as well as cis men's and cis women's satisfaction toward their own body image were distinctively associated with specific networks in each group. Overall, the study of the whole-brain network dynamical complexity discriminates gender identity groups, functional dynamic approaches could help disentangle the complex nature of the gender dimension in the brain.
Subject(s)
Transgender Persons , Brain/diagnostic imaging , Female , Gender Identity , Humans , MaleABSTRACT
Multi-site MRI datasets are crucial for big data research. However, neuroimaging studies must face the batch effect. Here, we propose an approach that uses the predictive probabilities provided by Gaussian processes (GPs) to harmonize clinical-based studies. A multi-site dataset of 216 Parkinson's disease (PD) patients and 87 healthy subjects (HS) was used. We performed a site GP classification using MRI data. The outcomes estimated from this classification, redefined like Weighted HARMonization PArameters (WHARMPA), were used as regressors in two different clinical studies: A PD versus HS machine learning classification using GP, and a VBM comparison (FWE-p < .05, k = 100). Same studies were also conducted using conventional Boolean site covariates, and without information about site belonging. The results from site GP classification provided high scores, balanced accuracy (BAC) was 98.39% for grey matter images. PD versus HS classification performed better when the WHARMPA were used to harmonize (BAC = 78.60%; AUC = 0.90) than when using the Boolean site information (BAC = 56.31%; AUC = 0.71) and without it (BAC = 57.22%; AUC = 0.73). The VBM analysis harmonized using WHARMPA provided larger and more statistically robust clusters in regions previously reported in PD than when the Boolean site covariates or no corrections were added to the model. In conclusion, WHARMPA might encode global site-effects quantitatively and allow the harmonization of data. This method is user-friendly and provides a powerful solution, without complex implementations, to clean the analyses by removing variability associated with the differences between sites.
Subject(s)
Parkinson Disease , Gray Matter , Humans , Machine Learning , Magnetic Resonance Imaging/methods , Neuroimaging/methods , Parkinson Disease/diagnostic imagingABSTRACT
BACKGROUND: In contrast to cisgender persons, transgender persons identify with a different gender than the one assigned at birth. Although research on the underlying neurobiology of transgender persons has been accumulating over the years, neuroimaging studies in this relatively rare population are often based on very small samples resulting in discrepant findings. AIM: To examine the neurobiology of transgender persons in a large sample. METHODS: Using a mega-analytic approach, structural MRI data of 803 non-hormonally treated transgender men (TM, nâ¯=â¯214, female assigned at birth with male gender identity), transgender women (TW, nâ¯=â¯172, male assigned at birth with female gender identity), cisgender men (CM, nâ¯=â¯221, male assigned at birth with male gender identity) and cisgender women (CW, nâ¯=â¯196, female assigned at birth with female gender identity) were analyzed. OUTCOMES: Structural brain measures, including grey matter volume, cortical surface area, and cortical thickness. RESULTS: Transgender persons differed significantly from cisgender persons with respect to (sub)cortical brain volumes and surface area, but not cortical thickness. Contrasting the 4 groups (TM, TW, CM, and CW), we observed a variety of patterns that not only depended on the direction of gender identity (towards male or towards female) but also on the brain measure as well as the brain region examined. CLINICAL TRANSLATION: The outcomes of this large-scale study may provide a normative framework that may become useful in clinical studies. STRENGTHS AND LIMITATIONS: While this is the largest study of MRI data in transgender persons to date, the analyses conducted were governed (and restricted) by the type of data collected across all participating sites. CONCLUSION: Rather than being merely shifted towards either end of the male-female spectrum, transgender persons seem to present with their own unique brain phenotype. Mueller SC, Guillamon A, Zubiaurre-Elorza L, et al. The Neuroanatomy of Transgender Identity: Mega-Analytic Findings From the ENIGMA Transgender Persons Working Group. J Sex Med 2021;18:1122-1129.
Subject(s)
Transgender Persons , Transsexualism , Brain/diagnostic imaging , Female , Gender Identity , Humans , Infant, Newborn , Male , Neuroanatomy , Transsexualism/diagnostic imagingABSTRACT
Functional brain organization in transgender persons remains unclear. Our aims were to investigate global and regional connectivity differences within functional networks in transwomen and transmen with early-in-life onset gender incongruence; and to test the consistency of two available hypotheses that attempted to explain gender variants: (i) a neurodevelopmental cortical hypothesis that suggests the existence of different brain phenotypes based on structural MRI data and genes polymorphisms of sex hormone receptors; (ii) a functional-based hypothesis in relation to regions involved in the own body perception. T2*-weighted images in a 3-T MRI were obtained from 29 transmen and 17 transwomen as well as 22 cisgender women and 19 cisgender men. Resting-state independent component analysis, seed-to-seed functional network and graph theory analyses were performed. Transmen, transwomen, and cisgender women had decreased connectivity compared with cisgender men in superior parietal regions, as part of the salience (SN) and the executive control (ECN) networks. Transmen also had weaker connectivity compared with cisgender men between intra-SN regions and weaker inter-network connectivity between regions of the SN, the default mode network (DMN), the ECN and the sensorimotor network. Transwomen had lower small-worldness, modularity and clustering coefficient than cisgender men. There were no differences among transmen, transwomen, and ciswomen. Together these results underline the importance of the SN interacting with DMN, ECN, and sensorimotor networks in transmen, involving regions of the entire brain with a frontal predominance. Reduced global connectivity graph-theoretical measures were a characteristic of transwomen. It is proposed that the interaction between networks is a keystone in building a gendered self. Finally, our findings suggest that both proposed hypotheses are complementary in explaining brain differences between gender variants.
Subject(s)
Brain/physiology , Connectome , Default Mode Network/physiology , Gender Dysphoria/physiopathology , Magnetic Resonance Imaging , Nerve Net/physiology , Prefrontal Cortex/physiology , Sex Characteristics , Transgender Persons , Adolescent , Adult , Brain/diagnostic imaging , Default Mode Network/diagnostic imaging , Female , Gender Dysphoria/diagnostic imaging , Humans , Male , Nerve Net/diagnostic imaging , Prefrontal Cortex/diagnostic imaging , Young AdultABSTRACT
Androgenization in adult natal women, as in transsexual men (TM), affects brain cortical thickness and the volume of subcortical structures. In order to understand the mechanism underlying these changes we have developed an adult female rat model of androgenization. Magnetic resonance imaging and spectroscopy were used to monitor brain volume changes, white matter microstructure and ex vivo metabolic profiles over 32 days in androgenized and control subjects. Supraphysiological doses of testosterone prevents aging decrease of fractional anisotropy values, decreased general cortical volume and the relative concentrations of glutamine (Gln) and myo-Inositol (mI). An increase in the N-acetylaspartate (NAA)/mI ratio was detected d. Since mI and Gln are astrocyte markers and osmolytes, we suspect that the anabolic effects of testosterone change astrocyte osmolarity so as to extrude Mi and Gln from these cells in order to maintain osmotic homeostasis. This mechanism could explain the brain changes observed in TM and other individuals receiving androgenic anabolic steroids.
Subject(s)
Brain/metabolism , Brain/pathology , Metabolome/physiology , Virilism/pathology , Animals , Anisotropy , Brain/diagnostic imaging , Brain/drug effects , Female , Functional Laterality , Glutamic Acid/metabolism , Glycine/metabolism , Inositol/metabolism , Magnetic Resonance Imaging , Rats , Rats, Wistar , Testosterone/blood , Testosterone Propionate/pharmacology , Tritium/metabolism , Virilism/blood , Virilism/diagnostic imaging , White Matter/pathologyABSTRACT
The description of brain networks as graphs where nodes represent different brain regions and edges represent a measure of connectivity between a pair of nodes is an increasingly used approach in neuroimaging research. The development of powerful methods for edge-wise group-level statistical inference in brain graphs while controlling for multiple-testing associated false-positive rates, however, remains a difficult task. In this study, we use simulated data to assess the properties of threshold-free network-based statistics (TFNBS). The TFNBS combines threshold-free cluster enhancement, a method commonly used in voxel-wise statistical inference, and network-based statistic (NBS), which is frequently used for statistical analysis of brain graphs. Unlike the NBS, TFNBS generates edge-wise significance values and does not require the a priori definition of a hard cluster-defining threshold. Other test parameters, nonetheless, need to be set. We show that it is possible to find parameters that make TFNBS sensitive to strong and topologically clustered effects, while appropriately controlling false-positive rates. Our results show that the TFNBS is an adequate technique for the statistical assessment of brain graphs.
Subject(s)
Algorithms , Brain Mapping , Brain/anatomy & histology , Brain/physiology , Neural Pathways/anatomy & histology , Neural Pathways/physiology , Data Interpretation, Statistical , Humans , Nerve NetABSTRACT
BACKGROUND: Numerous neuropsychological tests and test versions are used in Parkinson's disease research, but their relative capacity to detect mild cognitive deficits and their comparability across studies are unknown. The objective of this study was to identify neuropsychological tests that consistently detect cognitive decline in PD across studies. METHODS: Data from 30 normed neuropsychological tests across 20 international studies in up to 2908 nondemented PD patients were analyzed. A subset of 17 tests was administered to up to 1247 healthy controls. A 2-step meta-analytic approach using standardized scores compared performance in PD with normative data. RESULTS: Pooled estimates of the differences between PD and site-specific healthy controls identified significant cognitive deficits in PD patients on 14 test scores across 5 commonly assessed cognitive domains (attention or working memory, executive, language, memory, and visuospatial abilities), but healthy control performance was statistically above average on 7 of these tests. Analyses based on published norms only, as opposed to direct assessment of healthy controls, showed high between-study variability that could not be accounted for and led to inconclusive results. CONCLUSIONS: Normed neuropsychological tests across multiple cognitive domains consistently detect cognitive deficits in PD when compared with site-specific healthy control performance, but relative PD performance was significantly affected by the inclusion and type of healthy controls versus the use of published norms only. Additional research is needed to identify a cognitive battery that can be administered in multisite international studies and that is sensitive to cognitive decline, responsive to therapeutic interventions, and superior to individual cognitive tests. © 2018 International Parkinson and Movement Disorder Society.
Subject(s)
Cognitive Dysfunction/diagnosis , Cognitive Dysfunction/etiology , Neuropsychological Tests , Parkinson Disease/complications , Aged , Databases, Bibliographic , Female , Humans , Male , Middle AgedABSTRACT
BACKGROUND: Diagnosis of mild cognitive impairment in Parkinson's disease (PD) is relevant because it is a marker for evolution to dementia. However, the selection of suitable tests to evaluate separate cognitive domains in mild cognitive impairment related to PD remains an open question. The current work aims to investigate the neuroanatomical correlates of several visuospatial/visuoperceptual tests using the same sample and a multimodal MRI approach. METHODS: The study included 36 PD patients and 20 healthy subjects matched for age, sex, and education. The visuospatial/visuoperceptual tests selected were: Pentagon Copying Test (PCT), Judgment of Line Orientation Test (JLOT), Visual Form Discrimination Test (VFDT), Facial Recognition Test (FRT), Symbol Digit Modalities Test (SMDT), and clock copying task (CLOX2). FreeSurfer was used to assess cortical thickness, and tract-based spatial statistics was used for fractional anisotropy analysis. RESULTS: Lower performance in the PCT, JLOT, and SDMT was associated with extensive cortical thickness reductions in lateral parietal and temporal regions. VFDT and CLOX2 did not show this common pattern and correlated with more limited medial occipito-temporal and occipito-parietal regions. Performance in all visuospatial/visuoperceptual tests correlated with fractional anisotropy in the corpus callosum. CONCLUSIONS: Our findings show that JLOT, SDMT, and PCT, in addition to differentiating patients from controls, are suitable visuospatial/visuoperceptual tests to reflect cortical thinning in lateral temporo-parietal regions in PD patients. We did not observe the dissociation between dorsal and ventral streams that was expected according to the neuropsychological classification of visuospatial and visuoperceptual tests. (JINS, 2018, 24, 33-44).
Subject(s)
Cerebral Cortex/pathology , Cognitive Dysfunction/diagnosis , Parkinson Disease/diagnosis , Space Perception/physiology , Visual Perception/physiology , Aged , Cerebral Cortex/diagnostic imaging , Cognitive Dysfunction/etiology , Cognitive Dysfunction/pathology , Cognitive Dysfunction/physiopathology , Cohort Studies , Diffusion Tensor Imaging , Female , Humans , Male , Middle Aged , Neuropsychological Tests , Parkinson Disease/complications , Parkinson Disease/pathology , Parkinson Disease/physiopathologyABSTRACT
Fetal growth restriction (FGR) affects brain development in preterm infants, but little is known about its effects on resting-state functional connectivity. We compared 20 preterm infants, born at <34 weeks of gestation with abnormal antenatal Doppler measurements and birth weights <10th percentile, with 20 appropriate for gestational age preterm infants of similar gestational age and 20 term infants. They were scanned without sedation at 12 months of age and screened for autistic traits at 26 months. Resting functional connectivity was assessed using group independent component analysis and seed-based correlation analysis. The groups showed 10 common resting-state networks involving cortical, subcortical regions, and the cerebellum. Only infants with FGR showed patterns of increased connectivity in the visual network and decreased connectivity in the auditory/language and dorsal attention networks. No significant differences between groups were found using seed-based correlation analysis. FGR infants displayed a higher frequency of early autism features, related to decreased connectivity involving the salience network, than term infants. These data suggest that FGR is an independent risk factor for disrupted intrinsic functional connectivity in preterm infants when they are 1-year old and provide more clues about the neurodevelopmental abnormalities reported in this population.
Subject(s)
Brain/growth & development , Infant, Premature/growth & development , Birth Weight/physiology , Brain Mapping , Female , Fetal Growth Retardation , Gestational Age , Humans , Infant, Newborn , Male , Rest/physiologyABSTRACT
Dyskinetic cerebral palsy (CP) has long been associated with basal ganglia and thalamus lesions. Recent evidence further points at white matter (WM) damage. This study aims to identify altered WM pathways in dyskinetic CP from a standardized, connectome-based approach, and to assess structure-function relationship in WM pathways for clinical outcomes. Individual connectome maps of 25 subjects with dyskinetic CP and 24 healthy controls were obtained combining a structural parcellation scheme with whole-brain deterministic tractography. Graph theoretical metrics and the network-based statistic were applied to compare groups and to correlate WM state with motor and cognitive performance. Results showed a widespread reduction of WM volume in CP subjects compared to controls and a more localized decrease in degree (number of links per node) and fractional anisotropy (FA), comprising parieto-occipital regions and the hippocampus. However, supramarginal gyrus showed a significantly higher degree. At the network level, CP subjects showed a bilateral pathway with reduced FA, comprising sensorimotor, intraparietal and fronto-parietal connections. Gross and fine motor functions correlated with FA in a pathway comprising the sensorimotor system, but gross motor also correlated with prefrontal, temporal and occipital connections. Intelligence correlated with FA in a network with fronto-striatal and parieto-frontal connections, and visuoperception was related to right occipital connections. These findings demonstrate a disruption in structural brain connectivity in dyskinetic CP, revealing general involvement of posterior brain regions with relative preservation of prefrontal areas. We identified pathways in which WM integrity is related to clinical features, including but not limited to the sensorimotor system. Hum Brain Mapp 38:4594-4612, 2017. © 2017 Wiley Periodicals, Inc.
Subject(s)
Brain/diagnostic imaging , Brain/physiopathology , Cerebral Palsy/diagnostic imaging , Cerebral Palsy/physiopathology , Cognition , Motor Activity , Adolescent , Adult , Cerebral Palsy/psychology , Child , Cognition/physiology , Connectome/methods , Disability Evaluation , Female , Humans , Magnetic Resonance Imaging , Male , Motor Activity/physiology , Neural Pathways/diagnostic imaging , Neural Pathways/physiopathology , Neuropsychological Tests , Organ Size , White Matter/diagnostic imaging , White Matter/physiopathology , Young AdultABSTRACT
BACKGROUND: Clinical variability in the Parkinson's disease phenotype suggests the existence of disease subtypes. We investigated whether distinct anatomical patterns of atrophy can be identified in Parkinson's disease using a hypothesis-free, data-driven approach based on cortical thickness data. METHODS: T1-weighted 3-tesla MRI and a comprehensive neuropsychological assessment were performed in a sample of 88 nondemented Parkinson's disease patients and 31 healthy controls. We performed a hierarchical cluster analysis of imaging data using Ward's linkage method. A general linear model with cortical thickness data was used to compare clustering groups. RESULTS: We observed 3 patterns of cortical thinning in patients when compared with healthy controls. Pattern 1 (n = 30, 34.09%) consisted of cortical atrophy in bilateral precentral gyrus, inferior and superior parietal lobules, cuneus, posterior cingulate, and parahippocampal gyrus. These patients showed worse cognitive performance when compared with controls and the other 2 patterns. Pattern 2 (n = 29, 32.95%) consisted of cortical atrophy involving occipital and frontal as well as superior parietal areas and included patients with younger age at onset. Finally, in pattern 3 (n = 29, 32.95%), there was no detectable cortical thinning. Patients in the 3 patterns did not differ in disease duration, motor severity, dopaminergic medication doses, or presence of mild cognitive impairment. CONCLUSIONS: Three cortical atrophy subtypes were identified in nondemented Parkinson's disease patients: (1) parieto-temporal pattern of atrophy with worse cognitive performance, (2) occipital and frontal cortical atrophy and younger disease onset, and (3) patients without detectable cortical atrophy. These findings may help identify prognosis markers in Parkinson's disease. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
Subject(s)
Cerebral Cortex/pathology , Parkinson Disease/pathology , Aged , Aged, 80 and over , Atrophy/pathology , Cerebral Cortex/diagnostic imaging , Female , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Parkinson Disease/diagnostic imagingABSTRACT
BACKGROUND: The study of functional connectivity by means of magnetic resonance imaging (MRI) in asymptomatic LRRK2 mutation carriers could contribute to the characterization of the prediagnostic phase of LRRK2-associated Parkinson's disease (PD). The objective of this study was to characterize MRI functional patterns during the resting state in asymptomatic LRRK2 mutation carriers. METHODS: We acquired structural and functional MRI data of 18 asymptomatic LRRK2 mutation carriers and 18 asymptomatic LRRK2 mutation noncarriers, all first-degree relatives of LRRK2-PD patients. Starting from resting-state data, we analyzed the functional connectivity of the striatocortical and the nigrocortical circuitry. Structural brain data were analyzed by voxel-based morphometry, cortical thickness, and volumetric measures. RESULTS: Asymptomatic LRRK2 mutation carriers had functional connectivity reductions between the caudal motor part of the left striatum and the ipsilateral precuneus and superior parietal lobe. Connectivity in these regions correlated with subcortical gray-matter volumes in mutation carriers. Asymptomatic carriers also showed increased connectivity between the right substantia nigra and bilateral occipital cortical regions (occipital pole and cuneus bilaterally and right lateral occipital cortex). No intergroup differences in structural MRI measures were found. In LRRK2 mutation carriers, age and functional connectivity correlated negatively with striatal volumes. Additional analyses including only subjects with the G2019S mutation revealed similar findings. CONCLUSIONS: Asymptomatic LRRK2 mutation carriers showed functional connectivity changes in striatocortical and nigrocortical circuits compared with noncarriers. These findings support the concept that altered brain connectivity precedes the onset of classical motor features in a genetic form of PD. © 2016 International Parkinson and Movement Disorder Society.
Subject(s)
Cerebral Cortex/physiopathology , Connectome/methods , Leucine-Rich Repeat Serine-Threonine Protein Kinase-2/genetics , Neostriatum/physiopathology , Parkinson Disease/genetics , Parkinson Disease/physiopathology , Prodromal Symptoms , Substantia Nigra/physiopathology , Adult , Cerebral Cortex/diagnostic imaging , Female , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Mutation , Neostriatum/diagnostic imaging , Nuclear Family , Parkinson Disease/diagnostic imaging , Substantia Nigra/diagnostic imagingABSTRACT
The present review focuses on the brain structure of male-to-female (MtF) and female-to-male (FtM) homosexual transsexuals before and after cross-sex hormone treatment as shown by in vivo neuroimaging techniques. Cortical thickness and diffusion tensor imaging studies suggest that the brain of MtFs presents complex mixtures of masculine, feminine, and demasculinized regions, while FtMs show feminine, masculine, and defeminized regions. Consequently, the specific brain phenotypes proposed for MtFs and FtMs differ from those of both heterosexual males and females. These phenotypes have theoretical implications for brain intersexuality, asymmetry, and body perception in transsexuals as well as for Blanchard's hypothesis on sexual orientation in homosexual MtFs. Falling within the aegis of the neurohormonal theory of sex differences, we hypothesize that cortical differences between homosexual MtFs and FtMs and male and female controls are due to differently timed cortical thinning in different regions for each group. Cross-sex hormone studies have reported marked effects of the treatment on MtF and FtM brains. Their results are used to discuss the early postmortem histological studies of the MtF brain.
Subject(s)
Brain/diagnostic imaging , Transsexualism/diagnostic imaging , Adolescent , Adult , Aged , Biomedical Research , Child , Diffusion Tensor Imaging , Female , Humans , Male , Middle Aged , Young AdultABSTRACT
The human brain is a complex network that has been noted to contain a group of densely interconnected hub regions. With a putative "rich club" of hubs hypothesized to play a central role in global integrative brain functioning, we assessed whether hub and rich club organizations are associated with cognitive performance in healthy participants and whether the rich club might be differentially involved in cognitive functions with a heavier dependence on global integration. A group of 30 relatively older participants (range = 39-79 years of age) underwent extensive neuropsychological testing, combined with diffusion-weighted magnetic resonance imaging to reconstruct individual structural brain networks. Rich club connectivity was found to be associated with general cognitive performance. More specifically, assessing the relationship between the rich club and performance in two specific cognitive domains, we found rich club connectivity to be differentially associated with attention/executive functions-known to rely on the integration of distributed brain areas-rather than with visuospatial/visuoperceptual functions, which have a more constrained neuroanatomical substrate. Our findings thus provide first empirical evidence of a relevant role played by the rich club in cognitive processes.
Subject(s)
Aging/pathology , Aging/psychology , Brain/anatomy & histology , Cognition , Adult , Aged , Brain/growth & development , Diffusion Magnetic Resonance Imaging , Female , Humans , Male , Middle Aged , Models, Neurological , Neural Pathways/anatomy & histology , Neural Pathways/growth & developmentABSTRACT
The purpose of this work was to evaluate changes in the connectivity patterns of a set of cognitively relevant, dynamically interrelated brain networks in association with cognitive deficits in Parkinson's disease (PD) using resting-state functional MRI. Sixty-five nondemented PD patients and 36 matched healthy controls were included. Thirty-four percent of PD patients were classified as having mild cognitive impairment (MCI) based on performance in attention/executive, visuospatial/visuoperceptual (VS/VP) and memory functions. A data-driven approach using independent component analysis (ICA) was used to identify the default-mode network (DMN), the dorsal attention network (DAN) and the bilateral frontoparietal networks (FPN), which were compared between groups using a dual-regression approach controlling for gray matter atrophy. Additional seed-based analyses using a priori defined regions of interest were used to characterize local changes in intranetwork and internetwork connectivity. Structural group comparisons through voxel-based morphometry and cortical thickness were additionally performed to assess associated gray matter atrophy. ICA results revealed reduced connectivity between the DAN and right frontoinsular regions in MCI patients, associated with worse performance in attention/executive functions. The DMN displayed increased connectivity with medial and lateral occipito-parietal regions in MCI patients, associated with worse VS/VP performance, and with occipital reductions in cortical thickness. In line with data-driven results, seed-based analyses mainly revealed reduced within-DAN, within-DMN and DAN-FPN connectivity, as well as loss of normal DAN-DMN anticorrelation in MCI patients. Our findings demonstrate differential connectivity changes affecting the networks evaluated, which we hypothesize to be related to the pathophysiological bases of different types of cognitive impairment in PD.