Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 55
Filtrar
Más filtros

Bases de datos
País/Región como asunto
Tipo del documento
Intervalo de año de publicación
1.
Alzheimers Dement ; 19(2): 646-657, 2023 02.
Artículo en Inglés | MEDLINE | ID: mdl-35633518

RESUMEN

INTRODUCTION: Volumetric and morphological changes in subcortical brain structures are present in persons with dementia, but it is unknown if these changes occur prior to diagnosis. METHODS: Between 2005 and 2016, 5522 Rotterdam Study participants (mean age: 64.4) underwent cerebral magnetic resonance imaging (MRI) and were followed for development of dementia until 2018. Volume and shape measures were obtained for seven subcortical structures. RESULTS: During 12 years of follow-up, 272 dementia cases occurred. Mean volumes of thalamus (hazard ratio [HR] per standard deviation [SD] decrease 1.94, 95% confidence interval [CI]: 1.55-2.43), amygdala (HR 1.66, 95% CI: 1.44-1.92), and hippocampus (HR 1.64, 95% CI: 1.43-1.88) were strongly associated with dementia risk. Associations for accumbens, pallidum, and caudate volumes were less pronounced. Shape analyses identified regional surface changes in the amygdala, limbic thalamus, and caudate. DISCUSSION: Structure of the amygdala, thalamus, hippocampus, and caudate is associated with risk of dementia in a large population-based cohort of older adults.


Asunto(s)
Encéfalo , Demencia , Humanos , Anciano , Persona de Mediana Edad , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Imagen por Resonancia Magnética/métodos , Hipocampo/diagnóstico por imagen , Hipocampo/patología , Demencia/diagnóstico por imagen , Demencia/epidemiología , Demencia/patología
2.
Hum Brain Mapp ; 43(1): 352-372, 2022 01.
Artículo en Inglés | MEDLINE | ID: mdl-34498337

RESUMEN

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.


Asunto(s)
Amígdala del Cerebelo/patología , Cuerpo Estriado/patología , Hipocampo/patología , Neuroimagen , Esquizofrenia/patología , Tálamo/patología , Amígdala del Cerebelo/diagnóstico por imagen , Cuerpo Estriado/diagnóstico por imagen , Hipocampo/diagnóstico por imagen , Humanos , Estudios Multicéntricos como Asunto , Esquizofrenia/diagnóstico por imagen , Tálamo/diagnóstico por imagen
3.
Hum Brain Mapp ; 43(1): 300-328, 2022 01.
Artículo en Inglés | MEDLINE | ID: mdl-33615640

RESUMEN

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.


Asunto(s)
Encéfalo , Variaciones en el Número de Copia de ADN , Imagen por Resonancia Magnética , Trastornos Mentales , Trastornos del Neurodesarrollo , Neuroimagen , Encéfalo/diagnóstico por imagen , Encéfalo/crecimiento & desarrollo , Encéfalo/patología , Humanos , Trastornos Mentales/diagnóstico por imagen , Trastornos Mentales/genética , Trastornos Mentales/patología , Estudios Multicéntricos como Asunto , Trastornos del Neurodesarrollo/diagnóstico por imagen , Trastornos del Neurodesarrollo/genética , Trastornos del Neurodesarrollo/patología
4.
Mov Disord ; 36(11): 2583-2594, 2021 11.
Artículo en Inglés | MEDLINE | ID: mdl-34288137

RESUMEN

BACKGROUND: Brain structure abnormalities throughout the course of Parkinson's disease have yet to be fully elucidated. OBJECTIVE: Using a multicenter approach and harmonized analysis methods, we aimed to shed light on Parkinson's disease stage-specific profiles of pathology, as suggested by in vivo neuroimaging. METHODS: Individual brain MRI and clinical data from 2357 Parkinson's disease patients and 1182 healthy controls were collected from 19 sources. We analyzed regional cortical thickness, cortical surface area, and subcortical volume using mixed-effects models. Patients grouped according to Hoehn and Yahr stage were compared with age- and sex-matched controls. Within the patient sample, we investigated associations with Montreal Cognitive Assessment score. RESULTS: Overall, patients showed a thinner cortex in 38 of 68 regions compared with controls (dmax  = -0.20, dmin  = -0.09). The bilateral putamen (dleft  = -0.14, dright  = -0.14) and left amygdala (d = -0.13) were smaller in patients, whereas the left thalamus was larger (d = 0.13). Analysis of staging demonstrated an initial presentation of thinner occipital, parietal, and temporal cortices, extending toward rostrally located cortical regions with increased disease severity. From stage 2 and onward, the bilateral putamen and amygdala were consistently smaller with larger differences denoting each increment. Poorer cognition was associated with widespread cortical thinning and lower volumes of core limbic structures. CONCLUSIONS: Our findings offer robust and novel imaging signatures that are generally incremental across but in certain regions specific to disease stages. Our findings highlight the importance of adequately powered multicenter collaborations. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.


Asunto(s)
Enfermedad de Parkinson , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Humanos , Imagen por Resonancia Magnética , Neuroimagen , Enfermedad de Parkinson/complicaciones , Tálamo/patología
5.
Addict Biol ; 25(6): e12830, 2020 11.
Artículo en Inglés | MEDLINE | ID: mdl-31746534

RESUMEN

While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.


Asunto(s)
Encéfalo/diagnóstico por imagen , Neuroimagen , Trastornos Relacionados con Sustancias/diagnóstico por imagen , Adolescente , Adulto , Cannabis/efectos adversos , Cocaína/efectos adversos , Etanol/efectos adversos , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino , Metanfetamina/efectos adversos , Nicotina/efectos adversos , Adulto Joven
6.
Neuroimage ; 145(Pt B): 389-408, 2017 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-26658930

RESUMEN

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.


Asunto(s)
Encefalopatías , Estudio de Asociación del Genoma Completo , Trastornos Mentales , Estudios Multicéntricos como Asunto , Encefalopatías/diagnóstico por imagen , Encefalopatías/genética , Encefalopatías/patología , Encefalopatías/fisiopatología , Humanos , Trastornos Mentales/diagnóstico por imagen , Trastornos Mentales/genética , Trastornos Mentales/patología , Trastornos Mentales/fisiopatología
7.
J Neurosci ; 34(19): 6537-45, 2014 May 07.
Artículo en Inglés | MEDLINE | ID: mdl-24806679

RESUMEN

The C allele at the rs11136000 locus in the clusterin (CLU) gene is the third strongest known genetic risk factor for late-onset Alzheimer's disease (LOAD). A recent genome-wide association study of LOAD found the strongest evidence of association with CLU at rs1532278, in high linkage disequilibrium with rs11136000. Brain structure and function are related to the CLU risk alleles, not just in LOAD patients but also in healthy young adults. We tracked the volume of the lateral ventricles across baseline, 1-year, and 2-year follow-up scans in a large sample of elderly human participants (N = 736 at baseline), from the Alzheimer's Disease Neuroimaging Initiative, to determine whether these CLU risk variants predicted longitudinal ventricular expansion. The rs11136000 major C allele-previously linked with reduced CLU expression and with increased risk for dementia-predicted faster expansion, independently of dementia status or ApoE genotype. Further analyses revealed that the CLU and ApoE risk variants had combined effects on both volumetric expansion and lateral ventricle surface morphology. The rs1532278 locus strongly resembles a regulatory element. Its association with ventricular expansion was slightly stronger than that of rs11136000 in our analyses, suggesting that it may be closer to a functional variant. Clusterin affects inflammation, immune responses, and amyloid clearance, which in turn may result in neurodegeneration. Pharmaceutical agents such as valproate, which counteract the effects of genetically determined reduced clusterin expression, may help to achieve neuroprotection and contribute to the prevention of dementia, especially in carriers of these CLU risk variants.


Asunto(s)
Enfermedad de Alzheimer/genética , Apolipoproteínas E/genética , Clusterina/genética , Ventrículos Laterales/fisiología , Anciano , Envejecimiento/fisiología , Alelos , Mapeo Encefálico , ADN/genética , Femenino , Estudio de Asociación del Genoma Completo , Genotipo , Humanos , Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética , Masculino , Reacción en Cadena en Tiempo Real de la Polimerasa , Análisis de Regresión , Riesgo
8.
Alzheimers Dement ; 11(10): 1153-62, 2015 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-25496873

RESUMEN

INTRODUCTION: Genetic variants in DAT1, the gene encoding the dopamine transporter (DAT) protein, have been implicated in many brain disorders. In a recent case-control study of Alzheimer's disease (AD), a regulatory polymorphism in DAT1 showed a significant association with the clinical stages of dementia. METHODS: We tested whether this variant was associated with increased AD risk, and with measures of cognitive decline and longitudinal ventricular expansion, in a large sample of elderly participants with genetic, neurocognitive, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative. RESULTS: The minor allele-previously linked with increased DAT expression in vitro-was more common in AD patients than in both individuals with mild cognitive impairment and healthy elderly controls. The same allele was also associated with poorer cognitive performance and faster ventricular expansion, independently of diagnosis. DISCUSSION: These results may be due to reduced dopaminergic transmission in carriers of the DAT1 mutation.


Asunto(s)
Ventrículos Cerebrales/patología , Proteínas de Transporte de Dopamina a través de la Membrana Plasmática/genética , Anciano , Anciano de 80 o más Años , Alelos , Enfermedad de Alzheimer/genética , Estudios de Casos y Controles , Cognición , Disfunción Cognitiva/genética , Femenino , Genotipo , Heterocigoto , Humanos , Imagen por Resonancia Magnética , Masculino , Polimorfismo Genético , Riesgo
9.
Alzheimers Dement ; 11(7): 740-56, 2015 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-26194310

RESUMEN

INTRODUCTION: Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. METHODS: We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. RESULTS: Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. DISCUSSION: Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.


Asunto(s)
Enfermedad de Alzheimer/diagnóstico , Encéfalo/patología , Imagen por Resonancia Magnética , Enfermedad de Alzheimer/líquido cefalorraquídeo , Enfermedad de Alzheimer/complicaciones , Biomarcadores/líquido cefalorraquídeo , Encéfalo/irrigación sanguínea , Encéfalo/diagnóstico por imagen , Trastornos del Conocimiento/etiología , Historia del Siglo XX , Historia del Siglo XXI , Humanos , Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética/historia , Imagen por Resonancia Magnética/métodos , Imagen por Resonancia Magnética/normas , Tomografía de Emisión de Positrones , Marcadores de Spin
10.
Neuroimage ; 100: 75-90, 2014 Oct 15.
Artículo en Inglés | MEDLINE | ID: mdl-24821529

RESUMEN

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion--a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.


Asunto(s)
Algoritmos , Mapeo Encefálico/métodos , Imagen de Difusión Tensora/métodos , Fibras Nerviosas Mielínicas , Sustancia Blanca/anatomía & histología , Adulto , Atlas como Asunto , Femenino , Humanos , Masculino , Adulto Joven
11.
Hum Brain Mapp ; 35(8): 3903-18, 2014 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-24453132

RESUMEN

The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database-the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T(2) test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.


Asunto(s)
Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/patología , Apolipoproteína E4/genética , Disfunción Cognitiva/genética , Disfunción Cognitiva/patología , Hipocampo/patología , Anciano , Apolipoproteína E2/genética , Apolipoproteína E3/genética , Estudios de Cohortes , Bases de Datos Factuales , Femenino , Lateralidad Funcional , Heterocigoto , Homocigoto , Humanos , Procesamiento de Imagen Asistido por Computador , Masculino , Análisis Multivariante
12.
Neuroimage ; 70: 386-401, 2013 Apr 15.
Artículo en Inglés | MEDLINE | ID: mdl-23296188

RESUMEN

We propose a new method to maximize biomarker efficiency for detecting anatomical change over time in serial MRI. Drug trials using neuroimaging become prohibitively costly if vast numbers of subjects must be assessed, so it is vital to develop efficient measures of brain change. A popular measure of efficiency is the minimal sample size (n80) needed to detect 25% change in a biomarker, with 95% confidence and 80% power. For multivariate measures of brain change, we can directly optimize n80 based on a Linear Discriminant Analysis (LDA). Here we use a supervised learning framework to optimize n80, offering two alternative solutions. With a new medial surface modeling method, we track 3D dynamic changes in the lateral ventricles in 2065 ADNI scans. We apply our LDA-based weighting to the results. Our best average n80-in two-fold nested cross-validation-is 104 MCI subjects (95% CI: [94,139]) for a 1-year drug trial, and 75AD subjects [64,102]. This compares favorably with other MRI analysis methods. The standard "statistical ROI" approach applied to the same ventricular surfaces requires 165 MCI or 94AD subjects. At 2 years, the best LDA measure needs only 67 MCI and 52AD subjects, versus 119 MCI and 80AD subjects for the stat-ROI method. Our surface-based measures are unbiased: they give no artifactual additive atrophy over three time points. Our results suggest that statistical weighting may boost efficiency of drug trials that use brain maps.


Asunto(s)
Enfermedad de Alzheimer/patología , Ventrículos Cerebrales/patología , Disfunción Cognitiva/patología , Anciano , Análisis Discriminante , Progresión de la Enfermedad , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino
13.
Neuroimage ; 66: 648-61, 2013 Feb 01.
Artículo en Inglés | MEDLINE | ID: mdl-23153970

RESUMEN

Various neuroimaging measures are being evaluated for tracking Alzheimer's disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI.


Asunto(s)
Enfermedad de Alzheimer/patología , Encéfalo/patología , Disfunción Cognitiva/patología , Imagen de Difusión Tensora/métodos , Anciano , Enfermedad de Alzheimer/genética , Apolipoproteínas E/genética , Atrofia , Ensayos Clínicos como Asunto , Interpretación Estadística de Datos , Imagen de Difusión Tensora/instrumentación , Femenino , Humanos , Masculino , Estudios Prospectivos , Proyectos de Investigación/normas
14.
Hum Brain Mapp ; 34(12): 3369-75, 2013 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-22815233

RESUMEN

Studies linking meditation and brain structure are still relatively sparse, but the hippocampus is consistently implicated as one of the structures altered in meditation practitioners. To explore hippocampal features in the framework of meditation, we analyzed high-resolution structural magnetic resonance imaging data from 30 long-term meditators and 30 controls, closely matched for sex, age, and handedness. Hippocampal formations were manually traced following established protocols. In addition to calculating left and right hippocampal volumes (global measures), regional variations in surface morphology were determined by measuring radial distances from the hippocampal core to spatially matched surface points (local measures). Left and right hippocampal volumes were larger in meditators than in controls, significantly so for the left hippocampus. The presence and direction of this global effect was confirmed locally by mapping the exact spatial locations of the group differences. Altogether, radial distances were larger in meditators compared to controls, with up to 15% difference. These local effects were observed in several hippocampal regions in the left and right hemisphere though achieved significance primarily in the left hippocampal head. Larger hippocampal dimensions in long-term meditators may constitute part of the underlying neurological substrate for cognitive skills, mental capacities, and/or personal traits associated with the practice of meditation. Alternatively, given that meditation positively affects autonomic regulation and immune activity, altered hippocampal dimensions may be one result of meditation-induced stress reduction. However, given the cross-sectional design, the lack of individual stress measures, and the limited resolution of brain data, the exact underlying neuronal mechanisms remain to be established.


Asunto(s)
Mapeo Encefálico , Hipocampo/anatomía & histología , Hipocampo/fisiología , Negociación , Adulto , Estudios de Casos y Controles , Femenino , Lateralidad Funcional , Humanos , Imagenología Tridimensional , Estudios Longitudinales , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Adulto Joven
15.
Am J Psychiatry ; 180(9): 685-698, 2023 09 01.
Artículo en Inglés | MEDLINE | ID: mdl-37434504

RESUMEN

OBJECTIVE: Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs), including autism (ASD) and schizophrenia. Little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, the authors investigated gross volume, vertex-level thickness, and surface maps of subcortical structures in 11 CNVs and six NPDs. METHODS: Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (CNVs at 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2; age range, 6-80 years; 340 males) and 782 control subjects (age range, 6-80 years; 387 males) as well as ENIGMA summary statistics for ASD, schizophrenia, attention deficit hyperactivity disorder, obsessive-compulsive disorder, bipolar disorder, and major depression. RESULTS: All CNVs showed alterations in at least one subcortical measure. Each structure was affected by at least two CNVs, and the hippocampus and amygdala were affected by five. Shape analyses detected subregional alterations that were averaged out in volume analyses. A common latent dimension was identified, characterized by opposing effects on the hippocampus/amygdala and putamen/pallidum, across CNVs and across NPDs. Effect sizes of CNVs on subcortical volume, thickness, and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and schizophrenia. CONCLUSIONS: The findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions, as well distinct effects, with some CNVs clustering with adult-onset conditions and others with ASD. These findings provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD and why a single CNV increases the risk for a diverse set of NPDs.


Asunto(s)
Trastorno por Déficit de Atención con Hiperactividad , Esquizofrenia , Masculino , Adulto , Humanos , Niño , Adolescente , Adulto Joven , Persona de Mediana Edad , Anciano , Anciano de 80 o más Años , Variaciones en el Número de Copia de ADN/genética , Esquizofrenia/genética , Encéfalo/diagnóstico por imagen , Trastorno por Déficit de Atención con Hiperactividad/genética , Genómica
16.
medRxiv ; 2023 Feb 22.
Artículo en Inglés | MEDLINE | ID: mdl-36865328

RESUMEN

Objectives: Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs) including autism (ASD) and schizophrenia (SZ). Overall, little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, we investigated gross volume, and vertex level thickness and surface maps of subcortical structures in 11 different CNVs and 6 different NPDs. Methods: Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (at the following loci: 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2) and 782 controls (Male/Female: 727/730; age-range: 6-80 years) as well as ENIGMA summary-statistics for ASD, SZ, ADHD, Obsessive-Compulsive-Disorder, Bipolar-Disorder, and Major-Depression. Results: Nine of the 11 CNVs affected volume of at least one subcortical structure. The hippocampus and amygdala were affected by five CNVs. Effect sizes of CNVs on subcortical volume, thickness and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and SZ. Shape analyses were able to identify subregional alterations that were averaged out in volume analyses. We identified a common latent dimension - characterized by opposing effects on basal ganglia and limbic structures - across CNVs and across NPDs. Conclusion: Our findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions. We also observed distinct effects with some CNVs clustering with adult conditions while others clustered with ASD. This large cross-CNV and NPDs analysis provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD, as well as why a single CNV increases the risk for a diverse set of NPDs.

17.
Med Image Anal ; 70: 102009, 2021 05.
Artículo en Inglés | MEDLINE | ID: mdl-33711742

RESUMEN

Hyperbolic geometry has been successfully applied in modeling brain cortical and subcortical surfaces with general topological structures. However, such approaches, similar to other surface-based brain morphology analysis methods, usually generate high dimensional features. It limits their statistical power in cognitive decline prediction research, especially in datasets with limited subject numbers. To address the above limitation, we propose a novel framework termed as hyperbolic stochastic coding (HSC). We first compute diffeomorphic maps between general topological surfaces by mapping them to a canonical hyperbolic parameter space with consistent boundary conditions and extracts critical shape features. Secondly, in the hyperbolic parameter space, we introduce a farthest point sampling with breadth-first search method to obtain ring-shaped patches. Thirdly, stochastic coordinate coding and max-pooling algorithms are adopted for feature dimension reduction. We further validate the proposed system by comparing its classification accuracy with some other methods on two brain imaging datasets for Alzheimer's disease (AD) progression studies. Our preliminary experimental results show that our algorithm achieves superior results on various classification tasks. Our work may enrich surface-based brain imaging research tools and potentially result in a diagnostic and prognostic indicator to be useful in individualized treatment strategies.


Asunto(s)
Enfermedad de Alzheimer , Disfunción Cognitiva , Algoritmos , Enfermedad de Alzheimer/diagnóstico por imagen , Encéfalo/diagnóstico por imagen , Disfunción Cognitiva/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética
18.
Brain Connect ; 10(4): 183-194, 2020 05.
Artículo en Inglés | MEDLINE | ID: mdl-32264696

RESUMEN

This work addresses the problem of constructing a unified, topologically optimal connectivity-based brain atlas. The proposed approach aggregates an ensemble partition from individual parcellations without label agreement, providing a balance between sufficiently flexible individual parcellations and intuitive representation of the average topological structure of the connectome. The methods exploit a previously proposed dense connectivity representation, first performing graph-based hierarchical parcellation of individual brains, and subsequently aggregating the individual parcellations into a consensus parcellation. The search for consensus-based on the hard ensemble (HE) algorithm-approximately minimizes the sum of cluster membership distances, effectively estimating a pseudo-Karcher mean of individual parcellations. Computational stability, graph structure preservation, and biological relevance of the simplified representation resulting from the proposed parcellation are assessed on the Human Connectome Project data set. These aspects are assessed using (1) edge weight distribution divergence with respect to the dense connectome representation, (2) interhemispheric symmetry, (3) network characteristics' stability and agreement with respect to individually and anatomically parcellated networks, and (4) performance of the simplified connectome in a biological sex classification task. Ensemble parcellation was found to be highly stable with respect to subject sampling, outperforming anatomical atlases and other connectome-based parcellations in classification as well as preserving global connectome properties. The HE-based parcellation also showed a degree of symmetry comparable with anatomical atlases and a high degree of spatial contiguity without using explicit priors.


Asunto(s)
Encéfalo/anatomía & histología , Imagen de Difusión por Resonancia Magnética/métodos , Red Nerviosa/anatomía & histología , Neuroimagen/métodos , Adulto , Atlas como Asunto , Encéfalo/diagnóstico por imagen , Conectoma , Imagen de Difusión por Resonancia Magnética/normas , Femenino , Humanos , Interpretación de Imagen Asistida por Computador/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Masculino , Red Nerviosa/diagnóstico por imagen , Neuroimagen/normas , Adulto Joven
19.
Neuroimage Clin ; 27: 102338, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-32683323

RESUMEN

Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer's disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansions. Here we introduce a ventricular morphometry analysis system (VMAS) that generates a whole connected 3D ventricular shape model and encodes a great deal of ventricular surface deformation information that is inaccessible by VV. VMAS contains an automated segmentation approach and surface-based multivariate morphometry statistics. We applied VMAS to two independent datasets of cognitively unimpaired (CU) groups. To our knowledge, it is the first work to detect ventricular abnormalities that distinguish normal aging subjects from those who imminently progress to clinically significant memory decline. Significant bilateral ventricular morphometric differences were first shown in 38 members of the Arizona APOE cohort, which included 18 CU participants subsequently progressing to the clinically significant memory decline within 2 years after baseline visits (progressors), and 20 matched CU participants with at least 4 years of post-baseline cognitive stability (non-progressors). VMAS also detected significant differences in bilateral ventricular morphometry in 44 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects (18 CU progressors vs. 26 CU non-progressors) with the same inclusion criterion. Experimental results demonstrated that the ventricular anterior horn regions were affected bilaterally in CU progressors, and more so on the left. VMAS may track disease progression at subregional levels and measure the effects of pharmacological intervention at a preclinical stage.


Asunto(s)
Enfermedad de Alzheimer , Enfermedad de Alzheimer/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética , Memoria , Trastornos de la Memoria/diagnóstico por imagen , Neuroimagen
20.
Transl Psychiatry ; 10(1): 172, 2020 05 29.
Artículo en Inglés | MEDLINE | ID: mdl-32472038

RESUMEN

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.


Asunto(s)
Trastorno Depresivo Mayor , Encéfalo/diagnóstico por imagen , Depresión , Trastorno Depresivo Mayor/diagnóstico por imagen , Humanos , Difusión de la Información , Neuroimagen
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA