25,120 research outputs found

    Modeling the brain morphology distribution in the general aging population

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    <p>Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.</p

    A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments

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    In this study we propose a deformation-based framework to jointly model the influence of aging and Alzheimer's disease (AD) on the brain morphological evolution. Our approach combines a spatio-temporal description of both processes into a generative model. A reference morphology is deformed along specific trajectories to match subject specific morphologies. It is used to define two imaging progression markers: 1) a morphological age and 2) a disease score. These markers can be computed locally in any brain region. The approach is evaluated on brain structural magnetic resonance images (MRI) from the ADNI database. The generative model is first estimated on a control population, then, for each subject, the markers are computed for each acquisition. The longitudinal evolution of these markers is then studied in relation with the clinical diagnosis of the subjects and used to generate possible morphological evolution. In the model, the morphological changes associated with normal aging are mainly found around the ventricles, while the Alzheimer's disease specific changes are more located in the temporal lobe and the hippocampal area. The statistical analysis of these markers highlights differences between clinical conditions even though the inter-subject variability is quiet high. In this context, the model can be used to generate plausible morphological trajectories associated with the disease. Our method gives two interpretable scalar imaging biomarkers assessing the effects of aging and disease on brain morphology at the individual and population level. These markers confirm an acceleration of apparent aging for Alzheimer's subjects and can help discriminate clinical conditions even in prodromal stages. More generally, the joint modeling of normal and pathological evolutions shows promising results to describe age-related brain diseases over long time scales.Comment: NeuroImage, Elsevier, In pres

    Regenerative Medicine for the Aging Brain

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    In the central nervous system, cholinergic and dopaminergic (DA) neurons are among the cells most susceptible to the deleterious effects of age. Thus, the basal forebrain cholinergic system is known to undergo moderate neurodegenerative changes during normal aging as well as severe atrophy in Alzheimer’s disease (AD). Parkinson’s disease (PD), a degeneration of nigro-striatal DA neurons is the most conspicuous reflection of the vulnerability of DA neurons to age. In this context, cell reprogramming offers novel therapeutic possibilities for the treatment of these devastating diseases. In effect, the generation of induced pluripotent stem cells (iPSCs) from somatic cells demonstrated that adult mammalian cells can be reprogrammed to a pluripotent state by the overexpression of a few embryonic transcription factors (TF). This discovery fundamentally widened the research horizon in the fields of disease modeling and regenerative medicine. Although it is possible to re-differentiate iPSCs to specific somatic cell types, the tumorigenic potential of contaminating iPSCs that failed to differentiate, increases the risk for clinical application of somatic cells generated by this procedure. Therefore, reprogramming approaches that bypass the pluripotent stem cell state are being explored. A method called lineage reprogramming has been recently documented. It consists of the direct conversion of one adult cell type into another by transgenic expression of multiple lineage-specific TF or microRNAs. Another approach, termed direct reprogramming, features several advantages such as the use of universal TF system and the ability to generate a rejuvenated multipotent progenitor cell population, able to differentiate into specific cell types in response to a specific differentiation factors. These novel approaches offer a new promise for the treatment of pathologies associated with the loss of specific cell types as for instance, nigral DA neurons (in PD) or basal forebrain cholinergic neurons in the early stages of AD. The above topics are reviewed here.Fil: López León, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Reggiani, Paula Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Hereñú, Claudia Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Goya, Rodolfo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; Argentin

    Neuronal Correlation Parameter in the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System

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    Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition

    Aging is associated with an earlier arrival of reflected waves without a distal shift in reflection sites

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    Background-Despite pronounced increases in central pulse wave velocity (PWV) with aging, reflected wave transit time (RWTT), traditionally defined as the timing of the inflection point (T-INF) in the central pressure waveform, does not appreciably decrease, leading to the controversial proposition of a "distal-shift" of reflection sites. T-INF, however, is exceptionally prone to measurement error and is also affected by ejection pattern and not only by wave reflection. We assessed whether RWTT, assessed by advanced pressure-flow analysis, demonstrates the expected decline with aging. Methods and Results-We studied a sample of unselected adults without cardiovascular disease (n=48; median age 48 years) and a clinical population of older adults with suspected/established cardiovascular disease (n=164; 61 years). We measured central pressure and flow with carotid tonometry and phase-contrast MRI, respectively. We assessed RWTT using wave-separation analysis (RWTTWSA) and partially distributed tube-load (TL) modeling (RWTTTL). Consistent with previous reports, T-INF did not appreciably decrease with age despite pronounced increases in PWV in both populations. However, aging was associated with pronounced decreases in RWTTWSA (general population -15.0 ms/decade, P<0.001; clinical population -9.07 ms/decade, P=0.003) and RWTTTL (general -15.8 ms/decade, P<0.001; clinical -11.8 ms/decade, P<0.001). There was no evidence of an increased effective reflecting distance by either method. TINF was shown to reliably represent RWTT only under highly unrealistic assumptions about input impedance. Conclusions-RWTT declines with age in parallel with increased PWV, with earlier effects of wave reflections and without a distal shift in reflecting sites. These findings have important implications for our understanding of the role of wave reflections with aging

    Interleukin-6 gene (IL-6): a possible role in brain morphology in the healthy adult brain

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    Background: Cytokines such as interleukin 6 (IL-6) have been implicated in dual functions in neuropsychiatric disorders. Little is known about the genetic predisposition to neurodegenerative and neuroproliferative properties of cytokine genes. In this study the potential dual role of several IL-6 polymorphisms in brain morphology is investigated. Methodology: In a large sample of healthy individuals (N = 303), associations between genetic variants of IL-6 (rs1800795; rs1800796, rs2069833, rs2069840) and brain volume (gray matter volume) were analyzed using voxel-based morphometry (VBM). Selection of single nucleotide polymorphisms (SNPs) followed a tagging SNP approach (e.g., Stampa algorigthm), yielding a capture 97.08% of the variation in the IL-6 gene using four tagging SNPs. Principal findings/results: In a whole-brain analysis, the polymorphism rs1800795 (−174 C/G) showed a strong main effect of genotype (43 CC vs. 150 CG vs. 100 GG; x = 24, y = −10, z = −15; F(2,286) = 8.54, puncorrected = 0.0002; pAlphaSim-corrected = 0.002; cluster size k = 577) within the right hippocampus head. Homozygous carriers of the G-allele had significantly larger hippocampus gray matter volumes compared to heterozygous subjects. None of the other investigated SNPs showed a significant association with grey matter volume in whole-brain analyses. Conclusions/significance: These findings suggest a possible neuroprotective role of the G-allele of the SNP rs1800795 on hippocampal volumes. Studies on the role of this SNP in psychiatric populations and especially in those with an affected hippocampus (e.g., by maltreatment, stress) are warranted.Bernhard T Baune, Carsten Konrad, Dominik Grotegerd, Thomas Suslow, Eva Birosova, Patricia Ohrmann, Jochen Bauer, Volker Arolt, Walter Heindel, Katharina Domschke, Sonja Schöning, Astrid V Rauch, Christina Uhlmann, Harald Kugel and Udo Dannlowsk

    Hippocampal subfields and limbic white matter jointly predict learning rate in older adults

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    First published online: 04 December 2019Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants aged 61-82 years (Mage = 69.66, SDage = 3.92 years), we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task of recall over five repeated trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, and their latent interaction. Results showed limbic WM and the interaction of HC and WM-but not HC volume alone-predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher WM anisotropy. We conclude that the structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults
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