Search

Background Though dementia rates vary by racial or ethnic groups, it is unknown if these disparities remain among those aged 90 or older. Aims To test this hypothesis, we used baseline clinical evaluation of 541 ethnically and racially diverse individuals participating in the LifeAfter90 Study to assess how associations between core demographic characteristics and measures of physical and cognitive performance differ across the racial/ethnic groups. Methods Participants in this study were long-term non-demented members of Kaiser Permanente Northern California. They were clinically evaluated and diagnosed with normal or impaired cognition (mild cognitive impairment and dementia) through an in-person comprehensive clinical assessment consisting of a detailed medical history, physical and neurological examination, functional, and cognitive tests. Results The average age at enrollment was 93.0 ± 2.6 years, 62.4% female and 34.2% non-Hispanic White. At initial evaluation 301 participants had normal cognition and 165 had mild cognitive impairment (MCI) and despite screening, 69 participants were determined to have dementia. Age, education, 3MS, FAQ and CDR scores were significantly associated with cognitive impairment (normal versus MCI and dementia), but not gender. There was a significant univariate association between race/ethnicity and cognitive impairment (p Conclusion Our results confirm the ability to reliably assess clinical diagnosis in a diverse sample of very old individuals.

Cerebral white matter lesions (WML) encompass axonal loss and demyelination and are assumed to be associated with small vessel disease (SVD)-related ischaemia. However, our previous study in the parietal lobe white matter revealed that WML in Alzheimer’s disease (AD) are linked with degenerative axonal loss secondary to the deposition of cortical AD pathology. Furthermore, neuroimaging data suggest that pathomechanisms for the development of WML differ between anterior and posterior lobes with AD-associated degenerative mechanism driving posterior white matter disruption, and both AD-associated degenerative and vascular mechanisms contributed to anterior matter disruption. In this pilot study, we used human post-mortem brain tissue to investigate the composition and aetiology of frontal WML from AD and non-demented controls to determine if frontal WML are SVD-associated and to reveal any regional differences in the pathogenesis of WML. Frontal WML tissue sections from 40 human post-mortem brains (AD, n = 19; controls, n = 21) were quantitatively assessed for demyelination, axonal loss, cortical hyperphosphorylated tau (HPτ) and amyloid-beta (Aβ) burden, and arteriolosclerosis as a measure of SVD. Biochemical assessment included Wallerian degeneration-associated protease calpain and the myelin-associated glycoprotein to proteolipid protein ratio as a measure of ante-mortem ischaemia. Arteriolosclerosis severity was found to be associated with and a significant predictor of frontal WML severity in both AD and non-demented controls. Interesting, frontal axonal loss was also associated with HPτ and calpain levels were associated with increasing Aβ burden in the AD group, suggestive of an additional degenerative influence. To conclude, this pilot data suggest that frontal WML in AD may result from both increased arteriolosclerosis and AD-associated degenerative changes. These preliminary findings in combination with previously published data tentatively indicate regional differences in the aetiology of WML in AD, which should be considered in the clinical diagnosis of dementia subtypes: posterior WML maybe associated with degenerative mechanisms secondary to AD pathology, while anterior WML could be associated with both SVD-associated and degenerative mechanisms.

To apply an AT (Aβ/tau) classification system to subcortical vascular cognitive impairment (SVCI) patients following recently developed biomarker-based criteria of Alzheimer’s disease (AD), and to investigate its clinical significance. We recruited 60 SVCI patients who underwent the neuropsychological tests, brain MRI, and 18F-florbetaben and 18F-AV1451 PET at baseline. As a control group, we further recruited 27 patients with AD cognitive impairment (ADCI; eight Aβ PET-positive AD dementia and 19 amnestic mild cognitive impairment). ADCI and SVCI patients were classified as having normal or abnormal Aβ (A−/A+) and tau (T−/T+) based on PET results. Across the three SVCI groups (A−, A+T−, and A+T+SVCI), we compared longitudinal changes in cognition, hippocampal volume (HV), and cortical thickness using linear mixed models. Among SVCI patients, 33 (55%), 20 (33.3%), and seven (11.7%) patients were A−, A+T−, and A+T+, respectively. The frequency of T+ was lower in A+SVCI (7/27, 25.9%) than in A+ADCI (14/20, 70.0%, p = 0.003) which suggested that cerebral small vessel disease affected cognitive impairments independently of A+. A+T−SVCI had steeper cognitive decline than A−SVCI. A+T+SVCI also showed steeper cognitive decline than A+T−SVCI. Also, A+T−SVCI had steeper decrease in HV than A−SVCI, while cortical thinning did not differ between the two groups. A+T+SVCI had greater global cortical thinning compared with A+T−SVCI, while declines in HV did not differ between the two groups. This study showed that the AT system successfully characterized SVCI patients, suggesting that the AT system may be usefully applied in a research framework for clinically diagnosed SVCI.

Cognitive function such as reasoning, attention, memory, and language is strongly correlated with brain aging. Compared to non-Hispanic whites, Hispanics/Latinos have a higher risk of cognitive impairment and dementia. The genetic determinants of cognitive function have not been widely explored in this diverse and admixed population. We conducted a genome-wide association analysis of cognitive function in up to 7600 middle aged and older Hispanics/Latinos (mean = 55 years) from the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). Four cognitive measures were examined: the Brief Spanish English Verbal Learning Test (B-SEVLT), the Word Fluency Test (WFT), the Digit Symbol Substitution Test (DSST), the Six-Item Screener (SIS). Four novel loci were identified: one for B-SEVLT at 4p14, two for WFT at 3p14.1 and 6p21.32, and one for DSST at 10p13. These loci implicate genes highly expressed in brain and previously connected to neurological diseases (UBE2K, FRMD4B, the HLA gene complex). By applying tissue-specific gene expression prediction models to our genotype data, additional genes highly expressed in brain showed suggestive associations with cognitive measures possibly indicating novel biological mechanisms, including IFT122 in the hippocampus for SIS, SNX31 in the basal ganglia for B-SEVLT, RPS6KB2 in the frontal cortex for WFT, and CSPG5 in the hypothalamus for DSST. These findings provide new information about the genetic determinants of cognitive function in this unique population. In addition, we derived a measure of general cognitive function based on these cognitive tests and generated genome-wide association summary results, providing a resource to the research community for comparison, replication, and meta-analysis in future genetic studies in Hispanics/Latinos.

Publisher's version (útgefin grein)., Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes., 23Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA. 24Research Unit-Genetic Epidemiology, Gottfried Schatz Research Centre for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria. 25Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15260, USA. 26Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA. 27Department of Radiology, Leiden University Medical Center, Leiden 2333ZA, the Netherlands. 28Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto M4G 1R8, Canada. 29Departments of Psychology and Psychiatry, University of Toronto, Toronto M5S 1A1, Canada.

Cognitive ageing is a complex public health, social and economic problem that demands a bold response — a paradigm shift that leads science and society to view brain health across the lifespan of every individual as critically important. Implementation of 'Life's Simple 7' is a laudable step in that direction.

Publisher's version (útgefin grein) Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations., The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρgenetic = −0.59, p-value = 3.14 × 10−6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology., See Supplementary Note 2 for information on funding sources.

During the course of normal aging, biological changes occur in the brain that are associated with changes in cognitive ability. This review presents data from neuroimaging studies of primarily "normal" or healthy brain aging. As such, we focus on research in unimpaired or nondemented older adults, but also include findings from lifespan studies that include younger and middle aged individuals as well as from populations with prodromal or clinically symptomatic disease such as cerebrovascular or Alzheimer's disease. This review predominantly addresses structural MRI biomarkers, such as volumetric or thickness measures from anatomical images, and measures of white matter injury and integrity respectively from FLAIR or DTI, and includes complementary data from PET and cognitive or clinical testing as appropriate. The findings reveal highly consistent age-related differences in brain structure, particularly frontal lobe and medial temporal regions that are also accompanied by age-related differences in frontal and medial temporal lobe mediated cognitive abilities. Newer findings also suggest that degeneration of specific white matter tracts such as those passing through the genu and splenium of the corpus callosum may also be related to age-related differences in cognitive performance. Interpretation of these findings, however, must be tempered by the fact that comorbid diseases such as cerebrovascular and Alzheimer's disease also increase in prevalence with advancing age. As such, this review discusses challenges related to interpretation of current theories of cognitive aging in light of the common occurrence of these later-life diseases. Understanding the differences between "Normal" and "Healthy" brain aging and identifying potential modifiable risk factors for brain aging is critical to inform potential treatments to stall or reverse the effects of brain aging and possibly extend cognitive health for our aging society.

Everyone knows what cognitive aging is, to borrow from William James’ famous definition of attention (James 1890). Cognitive aging is a gradual, late-life decline in cognitive performance, experienced to a degree by most individuals fortunate to reach old age (Grady 2008). Decades of scientific research have shown that there exist age-correlated deficits both in basic cognitive processes (such as speed of processing) and in higher-order cognitive functions, particularly episodic memory (ability to recall events) and cognitive control (ability to control our behaviors). Cognitive aging research also indicates that while some functions decline, others remain relatively intact and may even improve with age (such as semantic knowledge (Grady and Craik 2000; Park and Reuter-Lorenz 2009; Salthouse 2004, 2009)). Still, relatively subtle declines in cognitive performance—for example, in memory and executive functions—are frequently observed in rigorous studies of older adults without clinical conditions. This phenomenon of age-associated cognitive declines, unrelated to detectable clinical processes and distinct from Mild Cognitive Impairment (MCI), is often termed “normal” or “healthy cognitive aging,” and these elders are considered “cognitively normal” or “cognitively healthy older adults.” Even such mild cognitive declines, however, can affect functionally relevant clinical outcomes related to older age including increasing the rate of hospitalization (Wilson et al. 2014) and predicting poorer medication adherence (Hayes et al. 2009). Brain structural morphology differs with age (DeCarli et al. 2005; Fjell et al. 2013; Head et al. 2008; Raz et al. 1998; Raz et al. 1997, 2005) and accompanies age-related differences in cognition. These differences are regionally specific with the most consistent and notable age-related differences in frontal lobar and medial temporal regions (Buckner 2004; DeCarli et al. 2005; Fjell et al. 2014; Head et al. 2008; Raz et al. 1998). Newer and more technologically sophisticated imaging tools have also identified relevant age-related differences in white matter microstructure which may either underpin gray-matter atrophy differences or accompany such differences (Andrews-Hanna et al. 2007; O’Sullivan et al. 2001; Sullivan et al. 2001; Sullivan and Pfefferbaum 2006, 2007). The notion of age-related dysfunction of specific brain systems has led to the development of a host of theories aimed at integrating these two apparently related processes. The frontal theory of aging, which is consistent with the known age-related differences in frontal gray matter, is one early example (West 1996). Another theory (Salthouse 1988, 1996, 2000; Salthouse and Lichty 1985) invoked the notion of slowed or degraded signal processing, which is finding greater supportive evidence through the study of white matter microstructure. Of course these are only two of the many theories. As our knowledge of cognitive processes expands, more refined hypotheses such as that of separate and dissociable memory processes related to familiarity and recall as discussed in papers by Schoemaker and colleagues and Koen and Yonelinas in this issue (Schoemaker et al. 2014 and Koen and Yonelinas 2014) are being developed. Novel hypotheses incorporate individual differences in cognitive aging through forms of reserve capacity as discussed in this issue by Reuter-Lorenz and Park (Reuter-Lorenz and Park 2014). These relatively recent hypotheses also have recognized discrete anatomical underpinnings that may be further understood by imaging and physiological techniques on the scientific horizon. Study of the aging brain cannot be fully understood without knowledge of common age-related diseases (DeCarli 2013) and genetic influences (Atwood et al. 2004; Bis et al. 2012; Carmelli et al. 1998; DeStefano et al. 2009; Ikram et al. 2012; Pfefferbaum et al. 2000). Advanced age is associated with multiple overlapping biological processes that adversely affect brain structure and function. Such processes include Alzheimer’s disease (AD) and cerebrovascular disease (CVD), which are nearly equally prevalent with advancing age (Seshadri and Wolf 2007). Moreover, both AD and CVD processes are known to have an extended prodromal state during which an individual appears “normal” (Debette et al. 2011; DeCarli et al. 1995; Jack et al. 2013; Pike et al. 2007; Rowe et al. 2010; Sperling et al. 2011; Swan et al. 1998, 2000). Brain aging refers to imaging signs of age-related changes absent clinically significant cognitive impairment; however, it remains unclear as to what extent these differences are “normal,” and to which biological processes differences in brain structure and function can be attributed. As the brain provides the substrate for cognition, brain aging and cognitive aging are, by definition, closely linked (Grady 2008). Often age-related biological processes are difficult to disentangle from one another, with the preclinical effects of AD and CVD thought to contribute to and confound the study of normal brain aging (Lockhart et al. 2012, 2014; Mayda et al. 2011). The effects on brain aging of clinically asymptomatic CVD are particularly insidious, as CVD and cardiovascular risk factors are very common (Decarli 2004;Wolf et al. 1991), and vascular risk factor-related brain structural differences (e.g., reduced white matter integrity) are observable as early as mid-life (Maillard et al. 2012). The study of brain aging must therefore examine the contributions of normal and preclinical disease-related changes to the structure and function of the brain. This issue of Neuropsychology Review presents a series of papers that cogently synthesize and summarize structural and functional brain differences with advancing age including the potential impact of amyloid, cerebrovascular risk factors, and genetic influences on these differences, aspects of cognitive functioning with a specific focus on age-related differences in memory function, and cognitive reserve capacity. The first section of this issue focuses on biomarkers related to aging. Lockhart and DeCarli provide an overview of structural imaging measures in brain aging including cross-sectional and longitudinal brain imaging studies assessing brain differences in younger versus older adults and the effects of clinically silent CVD risk factors on cognition and behavior in advancing age. Next, Fouquet, Besson, Gonneaud, La Joie, and Chetelat review imaging studies of the effects of ApoE4 on brain structure and function in cognitively normal adults across the lifespan. These authors focus on three main neuroimaging markers associated with AD: cortical beta-amyloid deposition, hypometabolism, and atrophy in Apoe4 carriers versus noncarriers. Factors that influence the association between beta amyloid and cognition in advanced age is next reviewed by Mormino, who makes a strong case for the need of a multimodal approach in determining AD risk. The second section of this issue focuses on memory processes, specifically recollection and familiarity. Schoemaker, Gautheir, and Pruessner review these memory processes and their neural substrates in older adults with MCI and AD and include remember-know, process dissociation procedure, and receiver operating characteristic paradigms. Next, Koen and Yonelinas provide a meta-analytic review of the effect sizes reported in recollection and familiarity studies in healthy aging, amnestic MCI and AD. Conclusions from both these reviews are consistent with neuroimaging findings suggesting a double dissociation: the hippocampus plays a critical role in recollection, whereas perirhinal regions play a critical role in familiarity. The last two papers of this issue take a gestalt approach, incorporating what we know about brain and aging to inform interventions to increase level of cognitive functioning and quality of life in older adults. Reuter-Lorenz and Park provide a revision of their previously well-received STAC (Scaffolding Theory of Aging and Cognition) model of cognitive functioning in normal aging. In their conceptual model of cognitive aging, they integrate the influence of biological, environmental, and lifestyle variables and effects level of cognitive functioning and rate of cognitive decline in advancing age. Lastly, the paper by Carmichael reviews what is known and what is not yet known about vascular effects on the brain and cognition in later adulthood. This paper provides strong support for the relevance of therapeutic intervention of vascular risk factors to maintain cognitive health in later life. Taken together, these timely reviews highlight the need for a better understanding of modifiable factors related to “normal” brain aging so that we may move toward “optimal” brain aging and the retention of strong cognitive abilities even into the ninth decade of life.

Differences in brain metabolism as measured by FDG-PET in prodromal and early Alzheimer’s disease (AD) have been consistently observed, with a characteristic parietotemporal hypometabolic pattern. However, exploration of brain metabolic correlates of more nuanced measures of cognitive function has been rare, particularly in larger samples. We analyzed the relationship between resting brain metabolism and memory and executive functioning within diagnostic group on a voxel-wise basis in 86 people with AD, 185 people with mild cognitive impairment (MCI), and 86 healthy controls (HC) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We found positive associations within AD and MCI but not in HC. For MCI and AD, impaired executive functioning was associated with reduced parietotemporal metabolism, suggesting a pattern consistent with known AD-related hypometabolism. These associations suggest that decreased metabolic activity in the parietal and temporal lobes may underlie the executive function deficits in AD and MCI. For memory, hypometabolism in similar regions of the parietal and temporal lobes were significantly associated with reduced performance in the MCI group. However, for the AD group, memory performance was significantly associated with metabolism in frontal and orbitofrontal areas, suggesting the possibility of compensatory metabolic activity in these areas. Overall, the associations between brain metabolism and cognition in this study suggest the importance of parietal and temporal lobar regions in memory and executive function in the early stages of disease and an increased importance of frontal regions for memory with increasing impairment.

A recent report by Alzheimer Disease International showed that the number of persons suffering from Alzheimer’s disease will quadruple by 2050 (http://www.alz.co.uk/research/world-report-2011). This increase is predicted to occur globally and will likely pose a great societal burden, both in terms of financial costs as well as suffering for patients and care-givers [1]. Thus, there is a strong incentive to develop effective preventive and therapeutic strategies. In order to develop such strategies, full knowledge of the pathophysiology of Alzheimer’s disease is an essential first step. Similarly, identification of people at high risk of Alzheimer’s disease is equally important. Fully understanding the disease pathology and early detection methods would facilitate implementation of targeted interventions in those people, who would benefit from it most.

Mild cognitive impairment (MCI) and Alzheimer's disease (AD) are associated with a progressive loss of cognitive abilities. In the present report, we assessed the relationship of memory and executive function with brain structure in a sample of 810 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, including 188 AD, 396 MCI, and 226 healthy older adults (HC). Composite scores of memory (ADNI-Mem) and executive function (ADNI-Exec) were generated by applying modern psychometric theory to item-level data from ADNI's neuropsychological battery. We performed voxel-based morphometry (VBM) and surface-based association (SurfStat) analyses to evaluate relationships of ADNI-Mem and ADNI-Exec with grey matter (GM) density and cortical thickness across the whole brain in the combined sample and within diagnostic groups. We observed strong associations between ADNI-Mem and medial and lateral temporal lobe atrophy. Lower ADNI-Exec scores were associated with advanced GM and cortical atrophy across broadly distributed regions, most impressively in the bilateral parietal and temporal lobes. We also evaluated ADNI-Exec adjusted for ADNI-Mem, and found associations with GM density and cortical thickness primarily in the bilateral parietal, temporal, and frontal lobes. Within-group analyses suggest these associations are strongest in patients with MCI and AD. The present study provides insight into the spatially unbiased associations between brain atrophy and memory and executive function, and underscores the importance of structural brain changes in early cognitive decline.

Mild cognitive impairment (MCI) appears to be a transitional stage in the development of Alzheimer's disease (AD). Patients with MCI show impaired memory performance and hippocampal atrophy relative to normal elderly controls. Prior studies indicate that the degree of hippocampal atrophy in MCI patients predicts conversion to AD. In contrast to patients with MCI who have deficits primarily in memory, AD patients have clinically evident impairments in both memory and nonmemory cognitive domains. One explanation for the observation that a smaller hippocampal volume predicts conversion to AD might be that hippocampal atrophy is associated with early impairment in nonmemory cognitive areas as well as memory. A link between hippocampal volume and nonmemory function could occur if hippocampal atrophy was correlated with AD pathology in other brain regions. We therefore sought to determine the relationship of hippocampal volume with performance on memory and nonmemory tasks in patients with MCI. Although we found a significant correlation between hippocampal volume and memory performance, we did not find a significant correlation between hippocampal volume and nonmemory performance. We conclude that the relationship between hippocampal volume and risk of AD is likely tied to reduced memory performance and not associated with impairment in nonmemory cognitive domains.

The relationships between viral load in plasma and cerebrospinal fluid (CSF) and computed tomography (CT) brain scan abnormalities were studied in 39 children between 0.5 and 13 years of age with symptomatic HIV-1 disease. Quantitative RNA PCR was used to determine HIV-1 RNA levels and a semiquantitative analog rating technique was used to evaluate non-contrast CT brain scans. CSF HIV-1 RNA copy number correlated significantly with CT brain scan ratings for severity of cortical atrophy (r = 0.36; P < 0.05) but not with ratings of intracerebral calcifications (r = -12; NS). The difference between these two correlations was significant (P < 0.05). Plasma HIV-1 RNA copy number did not correlate significantly with any CT brain scan ratings or with CSF viral load (r = 0.05; NS). Severity of cortical atrophy appeared to reflect the level of viral load in the CSF, supporting the notion that active HIV-1 replication in the CNS is at least in part responsible for such brain abnormalities in children. The lack of correlation of intracerebral calcifications with other CT brain scan abnormalities as well as with CSF viral load suggests that this lesion is relatively independent and may reflect a different neuropathologic process.

White matter hyperintensities (WMH) have an effect on cognition and are increased in severity among individuals with amnestic mild cognitive impairment (aMCI). The influence of WMH on progression of aMCI to Alzheimer's disease (AD) is less clear.Data were drawn from a three-year prospective, double blind, placebo controlled clinical trial that examined the effect of donepezil or vitamin E on progression from aMCI to AD. WMH from multiple brain regions were scored on MR images obtained at entry into the trial from a subset of 152 study participants using a standardized visual rating scale. Cox proportional hazards models adjusting for age, education and treatment arm were used to investigate the role of WMH on time to progression.55 of the 152 (36.2 %) aMCI subjects progressed to AD. Only periventricular hyperintensities (PVH) were related to an increased risk of AD within three years (HR = 1.59, 95 % CI = 1.24 - 2.05, p-value0.001). Correcting for medial temporal lobe atrophy or the presence of lacunes did not change statistical significance.PVH are associated with an increased risk of progression from aMCI to AD. This suggests that PVH, an MRI finding thought to represent cerebrovascular damage, contributes to AD onset in vulnerable individuals independent of Alzheimer pathology.

A spectrum of common illnesses that constitute risk factors for cardiovascular diseases is associated with both cognitive impairment and high population mortality. Many clinical trials are focused on the prevention of cardiovascular mortality, but cognitive impairment should now be regarded as a similarly important outcome.