Is Residual Memory Variance a Valid Method for Quantifying Cognitive Reserve? A Longitudinal Application

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point

Hippocampal volume varies with educational attainment across the life-span

Socioeconomic disparities—and particularly differences in educational attainment—are associated with remarkable differences in cognition and behavior across the life-span. Decreased educational attainment has been linked to increased exposure to life stressors, which in turn have been associated with structural differences in the hippocampus and the amygdala. However, the degree to which educational attainment is directly associated with anatomical differences in these structures remains unclear. Recent studies in children have found socioeconomic differences in regional brain volume in the hippocampus and amygdala across childhood and adolescence. Here we expand on this work, by investigating whether disparities in hippocampal and amygdala volume persist across the life-span. In a sample of 275 individuals from the BRAINnet Foundation database ranging in age from 17 to 87, we found that socioeconomic status (SES), as operationalized by years of educational attainment, moderates the effect of age on hippocampal volume. Specifically, hippocampal volume tended to markedly decrease with age among less educated individuals, whereas age-related reductions in hippocampal volume were less pronounced among more highly educated individuals. No such effects were found for amygdala volume. Possible mechanisms by which education may buffer age-related effects on hippocampal volume are discussed

Higher BMI is associated with reduced brain volume in heart failure

Abstract Background Heart failure (HF) patients are at risk for structural brain changes due to cerebral hypoperfusion. Past work shows obesity is linked with reduced cerebral blood flow and associated with brain atrophy in healthy individuals, although its effects on the brain in HF are unclear. This study examined the association among body mass index (BMI), cerebral perfusion, and brain volume in HF patients. Results Eighty HF patients underwent transcranial Doppler sonography to quantify cerebral blood flow velocity of the middle cerebral artery (CBF-V of the MCA) and brain magnetic resonance imaging (MRI) to quantify total brain, total and subcortical gray matter, white matter volume, and white matter hyperintensities. Body mass index (BMI) operationalized weight status. Nearly 45% of HF patients exhibited a BMI consistent with obesity. Regression analyses adjusting for medical variables, demographic characteristics, and CBF-V of the MCA, showed increased BMI was associated with reduced white matter volume (p \u3c .05). BMI also interacted with cerebral perfusion to impact total gray matter volume, but this pattern did not emerge for any other MRI indices (p \u3c 0.05). Conclusions Our findings suggest increased BMI negatively affects brain volume in HF, and higher BMI interacts with cerebral perfusion to impact gray matter volume. The mechanisms for these findings remain unclear and likely involve multiple physiological processes. Prospective studies are needed to elucidate the exact pattern and rates of brain changes in obese HF persons

Post-mortem brain analyses of the Lothian Birth Cohort 1936:Extending lifetime cognitive and brain phenotyping to the level of the synapse

INTRODUCTION: Non-pathological, age-related cognitive decline varies markedly between individuals andplaces significant financial and emotional strain on people, their families and society as a whole.Understanding the differential age-related decline in brain function is critical not only for the development oftherapeutics to prolong cognitive health into old age, but also to gain insight into pathological ageing suchas Alzheimer’s disease. The Lothian Birth Cohort of 1936 (LBC1936) comprises a rare group of people forwhom there are childhood cognitive test scores and longitudinal cognitive data during older age, detailedstructural brain MRI, genome-wide genotyping, and a multitude of other biological, psycho-social, andepidemiological data. Synaptic integrity is a strong indicator of cognitive health in the human brain;however, until recently, it was prohibitively difficult to perform detailed analyses of synaptic and axonalstructure in human tissue sections. We have adapted a novel method of tissue preparation at autopsy toallow the study of human synapses from the LBC1936 cohort in unprecedented morphological andmolecular detail, using the high-resolution imaging techniques of array tomography and electronmicroscopy. This allows us to analyze the brain at sub-micron resolution to assess density, proteincomposition and health of synapses. Here we present data from the first donated LBC1936 brain andcompare our findings to Alzheimer’s diseased tissue to highlight the differences between healthy andpathological brain ageing. RESULTS: Our data indicates that compared to an Alzheimer’s disease patient, the cognitively normalLBC1936 participant had a remarkable degree of preservation of synaptic structures. However,morphological and molecular markers of degeneration in areas of the brain associated with cognition(prefrontal cortex, anterior cingulate cortex, and superior temporal gyrus) were observed. CONCLUSIONS: Our novel post-mortem protocol facilitates high-resolution neuropathological analysis of the well-characterized LBC1936 cohort, extending phenotyping beyond cognition and in vivo imaging to nowinclude neuropathological changes, at the level of single synapses. This approach offers an unprecedentedopportunity to study synaptic and axonal integrity during ageing and how it contributes to differences in agerelatedcognitive change. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40478-015-0232-0) contains supplementary material, which is available to authorized users

Soluble amyloid beta levels are elevated in the white matter of Alzheimer's patients, independent of cortical plaque severity

Alzheimer’s disease (AD) is the most common neurodegenerative disease and the leading cause of dementia. In addition to grey matter pathology, white matter changes are now recognized as an important pathological feature in the emergence of the disease. Despite growing recognition of the importance of white matter abnormalities in the pathogenesis of AD, the causes of white matter degeneration are still unknown. While multiple studies propose Wallerian-like degeneration as the source of white matter change, others suggest that primary white matter pathology may be due, at least in part, to other mechanisms, including local effects of toxic Aβ peptides. In the current study, we investigated levels of soluble amyloid-beta (Aβ) in white matter of AD patients (n=12) compared with controls (n=10). Fresh frozen white matter samples were obtained from anterior (Brodmann area 9) and posterior (Brodmann area 1, 2 and 3) areas of post-mortem AD and control brains. ELISA was used to examine levels of soluble Aβ -42 and Aβ -40. Total cortical neuritic plaque severity rating was derived from individual ratings in the following areas of cortex: mid-frontal, superior temporal, pre-central, inferior parietal, hippocampus (CA1), subiculum, entorhinal cortex, transentorhinal cortex, inferior temporal, amygdala and basal forebrain. Compared with controls, AD samples had higher white matter levels of both soluble Aβ -42 and Aβ -40. While no regional white matter differences were found in Aβ -40, Aβ -42 levels were higher in anterior regions than in posterior regions across both groups. After statistically controlling for total cortical neuritic plaque severity, differences in both soluble Aβ -42 and Aβ -40 between the groups remained, suggesting that white matter Aβ peptides accumulate independent of overall grey matter fibrillar amyloid pathology and are not simply a reflection of overall amyloid burden. These results shed light on one potential mechanism through which white matter degeneration may occur in AD. Given that white matter degeneration may be an early marker of disease, preceding grey matter atrophy, understanding the mechanisms and risk factors that may lead to white matter loss could help to identify those at high risk and to intervene earlier in the pathogenic process.Lyndsey E Collins-Praino, Yitshak I Francis, Erica Y Griffith, Anne F Wiegman, Jonathan Urbach, Arlene Lawton, Lawrence S Honig, Etty Cortes, Jean Paul G Vonsattel, Peter D Canoll, James E Goldman and Adam M Brickma

Motional Averaging in a Superconducting Qubit

Superconducting circuits with Josephson junctions are promising candidates for developing future quantum technologies. Of particular interest is to use these circuits to study effects that typically occur in complex condensed-matter systems. Here, we employ a superconducting quantum bit (qubit),a transmon, to carry out an analog simulation of motional averaging, a phenomenon initially observed in nuclear magnetic resonance (NMR) spectroscopy. To realize this effect, the flux bias of the transmon is modulated by a controllable pseudo-random telegraph noise, resulting in stochastic jumping of the energy separation between two discrete values. When the jumping is faster than a dynamical threshold set by the frequency displacement of the levels, the two separated spectral lines merge into a single narrow-width, motional-averaged line. With sinusoidal modulation a complex pattern of additional sidebands is observed. We demonstrate experimentally that the modulated system remains quantum coherent, with modified transition frequencies, Rabi couplings, and dephasing rates. These results represent the first steps towards more advanced quantum simulations using artificial atoms.Comment: Main text (5 pages and 4 figures) and Supplementary Information (11 pages and 5 figures

Diffusion tensor imaging of frontal lobe white matter tracts in schizophrenia

We acquired diffusion tensor and structural MRI images on 103 patients with schizophrenia and 41 age-matched normal controls. The vector data was used to trace tracts from a region of interest in the anterior limb of the internal capsule to the prefrontal cortex. Patients with schizophrenia had tract paths that were significantly shorter in length from the center of internal capsule to prefrontal white matter. These tracts, the anterior thalamic radiations, are important in frontal-striatal-thalamic pathways. These results are consistent with findings of smaller size of the anterior limb of the internal capsule in patients with schizophrenia, diffusion tensor anisotropy decreases in frontal white matter in schizophrenia and hypothesized disruption of the frontal-striatal-thalamic pathway system

A Cross-Species Analysis of a Mouse Model of Breast Cancer-Specific Osteolysis and Human Bone Metastases Using Gene Expression Profiling

<p>Abstract</p> <p>Background</p> <p>Breast cancer is the second leading cause of cancer-related death in women in the United States. During the advanced stages of disease, many breast cancer patients suffer from bone metastasis. These metastases are predominantly osteolytic and develop when tumor cells interact with bone. <it>In vivo </it>models that mimic the breast cancer-specific osteolytic bone microenvironment are limited. Previously, we developed a mouse model of tumor-bone interaction in which three mouse breast cancer cell lines were implanted onto the calvaria. Analysis of tumors from this model revealed that they exhibited strong bone resorption, induction of osteoclasts and intracranial penetration at the tumor bone (TB)-interface.</p> <p>Methods</p> <p>In this study, we identified and used a TB microenvironment-specific gene expression signature from this model to extend our understanding of the metastatic bone microenvironment in human disease and to predict potential therapeutic targets.</p> <p>Results</p> <p>We identified a TB signature consisting of 934 genes that were commonly (among our 3 cell lines) and specifically (as compared to tumor-alone area within the bone microenvironment) up- and down-regulated >2-fold at the TB interface in our mouse osteolytic model. By comparing the TB signature with gene expression profiles from human breast metastases and an <it>in vitro </it>osteoclast model, we demonstrate that our model mimics both the human breast cancer bone microenvironment and osteoclastogenesis. Furthermore, we observed enrichment in various signaling pathways specific to the TB interface; that is, TGF-β and myeloid self-renewal pathways were activated and the Wnt pathway was inactivated. Lastly, we used the TB-signature to predict cyclopenthiazide as a potential inhibitor of the TB interface.</p> <p>Conclusion</p> <p>Our mouse breast cancer model morphologically and genetically resembles the osteoclastic bone microenvironment observed in human disease. Characterization of the gene expression signature specific to the TB interface in our model revealed signaling mechanisms operative in human breast cancer metastases and predicted a therapeutic inhibitor of cancer-mediated osteolysis.</p

Maximum (prior) brain size, not atrophy, correlates with cognition in community-dwelling older people: a cross-sectional neuroimaging study

<p>Abstract</p> <p>Background</p> <p>Brain size is associated with cognitive ability in adulthood (correlation ~ .3), but few studies have investigated the relationship in normal ageing, particularly beyond age 75 years. With age both brain size and fluid-type intelligence decline, and regional atrophy is often suggested as causing decline in specific cognitive abilities. However, an association between brain size and intelligence may be due to the persistence of this relationship from earlier life.</p> <p>Methods</p> <p>We recruited 107 community-dwelling volunteers (29% male) aged 75–81 years for cognitive testing and neuroimaging. We used principal components analysis to derived a 'general cognitive factor' (g) from tests of fluid-type ability. Using semi-automated analysis, we measured whole brain volume, intracranial area (ICA) (an estimate of maximal brain volume), and volume of frontal and temporal lobes, amygdalo-hippocampal complex, and ventricles. Brain atrophy was estimated by correcting WBV for ICA.</p> <p>Results</p> <p>Whole brain volume (WBV) correlated with general cognitive ability (g) (r = .21, P < .05). Statistically significant associations between brain areas and specific cognitive abilities became non-significant when corrected for maximal brain volume (estimated using ICA), i.e. there were no statistically significant associations between atrophy and cognitive ability. The association between WBV and g was largely attenuated (from .21 to .03: i.e. attenuating the variance by 98%) by correcting for ICA. ICA accounted for 6.2% of the variance in g in old age, whereas atrophy accounted for < 1%.</p> <p>Conclusion</p> <p>The association between brain regions and specific cognitive abilities in community dwelling people of older age is due to the life-long association between whole brain size and general cognitive ability, rather than atrophy of specific regions. Researchers and clinicians should therefore be cautious of interpreting global or regional brain atrophy on neuroimaging as contributing to cognitive status in older age without taking into account prior mental ability and brain size.</p