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In the brains of Alzheimer's disease patients, the entorhinal cortex is known to show signs of early pathology. In this study, Khan et al . performed cerebral blood volume imaging of patients with preclinical Alzheimer's disease and mouse models of disease. Their results pinpoint the subregion in the entorhinal cortex most sensitive to the disease, and show how amyloid and tau interact in driving dysfunction and how dysfunction spreads to distal cortical regions. The entorhinal cortex has been implicated in the early stages of Alzheimer's disease, which is characterized by changes in the tau protein and in the cleaved fragments of the amyloid precursor protein (APP). We used a high-resolution functional magnetic resonance imaging (fMRI) variant that can map metabolic defects in patients and mouse models to address basic questions about entorhinal cortex pathophysiology. The entorhinal cortex is divided into functionally distinct regions, the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC), and we exploited the high-resolution capabilities of the fMRI variant to ask whether either of them was affected in patients with preclinical Alzheimer's disease. Next, we imaged three mouse models of disease to clarify how tau and APP relate to entorhinal cortex dysfunction and to determine whether the entorhinal cortex can act as a source of dysfunction observed in other cortical areas. We found that the LEC was affected in preclinical disease, that LEC dysfunction could spread to the parietal cortex during preclinical disease and that APP expression potentiated tau toxicity in driving LEC dysfunction, thereby helping to explain regional vulnerability in the disease.

Alzheimer’s disease typically evolves over a period of several years before an affected person seeks medical attention for a diagnosis. The pathologic features of the brain in patients with Alzheimer’s disease include extracellular amyloid plaques, intraneuronal neurofibrillary tangles, and the loss of neurons and synapses. For decades, researchers speculated about which of these manifestations appears first. The discovery of rare genetic variants affecting the production of amyloid-beta (Aβ) peptide in autosomal dominant Alzheimer’s disease provided the first clue. On the basis of this new information, researchers considered amyloid deposition to be the incipient process, followed by a cascade of other . . .

Many of the Alzheimer’s disease (AD) risk genes are specifically expressed in microglia and astrocytes, but how and when the genetic risk localizing to these cell types contributes to AD pathophysiology remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets and uncover the impact of cell-type-specific genetic risk on AD endophenotypes. In an autopsy dataset spanning all stages of AD ( n  = 1457), the astrocytic ADPRS affected diffuse and neuritic plaques (amyloid-β), while microglial ADPRS affected neuritic plaques, microglial activation, neurofibrillary tangles (tau), and cognitive decline. In an independent neuroimaging dataset of cognitively unimpaired elderly ( n  = 2921), astrocytic ADPRS was associated with amyloid-β, and microglial ADPRS was associated with amyloid-β and tau, connecting cell-type-specific genetic risk with AD pathology even before symptom onset. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage. Alzheimer’s disease genetic risk is enriched in glial genes. Here, the authors derive cell-type-specific polygenic risk scores and link astrocytic genes with Aβ, and microglial genes with Aβ, tau, microglial activation, and cognitive decline.

Autosomal dominant familial Alzheimer’s disease (ADAD) is a rare disorder with non-amnestic neurological symptoms in some clinical presentations. We aimed to compile and compare data from symptomatic participants in the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS) with those reported in the literature to estimate the prevalences of non-amnestic neurological symptoms in participants with ADAD. We prospectively collected data from the DIAN-OBS database, which recruited participants from study centres in the USA, Europe, and Australia, between Feb 29, 2008, and July 1, 2014. We also did a systematic review of publications to extract individual-level clinical data for symptomatic participants with ADAD. We used data for age of onset (from first report of cognitive decline), disease course from onset to death, and the presence of 13 neurological findings that have been reported in association with ADAD. Using multivariable linear regression, we investigated the prevalences of various non-amnestic neurological symptoms and the contributions of age of onset and specific mutation type on symptoms. The DIAN-OBS dataset included 107 individuals with detailed clinical data (forming the DIAN-OBS cohort). Our systematic review yielded 188 publications reporting on 1228 symptomatic individuals, with detailed neurological examination descriptions available for 753 individuals (forming the published data cohort). The most prevalent non-amnestic cognitive manifestations in participants in the DIAN-OBS cohort were those typical of mild to moderate Alzheimer’s disease, including visual agnosia (55·1%, 95% CI 45·7–64·6), aphasia (57·9%, 48·6–67·3), and behavioural changes (61·7%, 51·5–70·0). Non-amnestic cognitive manifestations were less prevalent in the published data cohort (eg, visual agnosia [5·6%, 3·9–7·2], aphasia [23·0%, 20·0–26·0], and behavioural changes [31·7%, 28·4–35·1]). Prevalence of non-cognitive neurological manifestations in the DIAN-OBS cohort was low, including myoclonus and spasticity (9·3%, 95% CI 3·8–15·0), and seizures (2·8%, 0·5–5·9) and moderate for parkinsonism (11·2%, 5·3–17·1). By constrast, prevalence was higher in the published data cohort for myoclonus and spasticity (19·4%, 16·6–22·2 and 15·0%, 12·5–17·6, respectively), parkinsonism (12·5%, 10·1–15·0), and seizures (20·3%, 17·4–23·2). In an analysis of the published data cohort, ischaemic stroke was more prevalent at older ages of onset of symptoms of ADAD (odds ratio 1·09 per 1 year increase in age of onset, 95% CI 1·04–1·14, p=0·0003); and motor symptoms were more common at younger age of onset (myoclonus 0·93, 0·90–0·97, p=0·0007; seizures 0·95, 0·92–0·98, p=0·0018; corticobulbar deficits 0·91, 0·86–0·96, p=0·0012; and cerebellar ataxia 0·82, 0·74–0·91, p=0·0002). In the DIAN-OBS cohort, non-cognitive symptoms were more common at more severe stages of disease. The non-cognitive clinical manifestations of Alzheimer’s disease seem to affect a small proportion of participants with mild to moderate ADAD, and are probably influenced by disease severity, environmental, and genetic factors. When evaluating patients with potential ADAD, clinicians should note that cognitive symptoms typical of sporadic Alzheimer’s disease are the most consistent finding, with some patients manifesting non-cognitive neurological symptoms. Future work is needed to determine the environmental and genetic factors that cause these neurological symptoms. National Institutes of Health and German Center for Neurodegenerative Diseases.

In this study of a cohort of adults with genetic mutations that cause autosomal dominant Alzheimer's disease, researchers identified abnormalities in cerebrospinal fluid biomarkers and neuroimaging tests that develop decades before the onset of dementia. Alzheimer's disease is the most common cause of dementia and is currently estimated to affect more than 5 million people in the United States, with an expected increase to 13 million by the year 2050. The typical clinical presentation is progressive loss of memory and cognitive function, ultimately leading to a loss of independence and causing a heavy personal toll on the patient and the family. The costs of care of patients with Alzheimer's disease in 2010 were estimated at more than $172 billion in the United States, an annual cost that is predicted to increase to a trillion dollars . . .

Cerebral microbleeds, observed as small, spherical hypointense regions on gradient echo (GRE) or susceptibility weighted (SWI) magnetic resonance imaging (MRI) sequences, reflect small hemorrhagic infarcts, and are associated with conditions such as vascular dementia, small vessel disease, cerebral amyloid angiopathy, and Alzheimer’s disease. The current gold standard for detecting and rating cerebral microbleeds in a research context is visual inspection by trained raters, a process that is both time consuming and subject to poor reliability. We present here a novel method to automate microbleed detection on GRE and SWI images. We demonstrate in a community-based cohort of older adults that the method is highly sensitive (greater than 92% of all microbleeds accurately detected) across both modalities, with reasonable precision (fewer than 20 and 10 false positives per scan on GRE and SWI, respectively). We also demonstrate that the algorithm can be used to identify microbleeds over longitudinal scans with a higher level of sensitivity than visual ratings (50% of longitudinal microbleeds correctly labeled by the algorithm, while manual ratings was 30% or lower). Further, the algorithm identifies the anatomical localization of microbleeds based on brain atlases, and greatly reduces time spent completing visual ratings (43% reduction in visual rating time). Our automatic microbleed detection instrument is ideal for implementation in large-scale studies that include cross-sectional and longitudinal scanning, as well as being capable of performing well across multiple commonly used MRI modalities.

The primary abnormality in Down syndrome (DS), trisomy 21, is well known; but how this chromosomal gain produces the complex DS phenotype, including immune system defects, is not well understood. We profiled DNA methylation in total peripheral blood leukocytes (PBL) and T-lymphocytes from adults with DS and normal controls and found gene-specific abnormalities of CpG methylation in DS, with many of the differentially methylated genes having known or predicted roles in lymphocyte development and function. Validation of the microarray data by bisulfite sequencing and methylation-sensitive Pyrosequencing (MS-Pyroseq) confirmed strong differences in methylation (p<0.0001) for each of 8 genes tested: TMEM131, TCF7, CD3Z/CD247, SH3BP2, EIF4E, PLD6, SUMO3, and CPT1B, in DS versus control PBL. In addition, we validated differential methylation of NOD2/CARD15 by bisulfite sequencing in DS versus control T-cells. The differentially methylated genes were found on various autosomes, with no enrichment on chromosome 21. Differences in methylation were generally stable in a given individual, remained significant after adjusting for age, and were not due to altered cell counts. Some but not all of the differentially methylated genes showed different mean mRNA expression in DS versus control PBL; and the altered expression of 5 of these genes, TMEM131, TCF7, CD3Z, NOD2, and NPDC1, was recapitulated by exposing normal lymphocytes to the demethylating drug 5-aza-2'deoxycytidine (5aza-dC) plus mitogens. We conclude that altered gene-specific DNA methylation is a recurrent and functionally relevant downstream response to trisomy 21 in human cells.

Inflammation plays a major role in cognitive aging. Most studies on peripheral inflammation and cognitive aging focused on selected major inflammatory biomarkers. However, inflammatory markers are regulated and influenced by each other, and it is therefore important to consider a more comprehensive panel of markers to better capture diverse immune pathways and characterize the overall inflammatory profile of individuals. We explored 23 circulating inflammatory biomarkers using data from 1,743 participants without dementia (≥ 65 years-old) from the community-based, multiethnic Washington Heights Inwood Columbia Aging Project. Using principal component analysis (PCA), we developed six inflammatory profiles (PC-1 to PC-6) based on these 23 biomarkers and tested the association of resulting inflammatory profile with cognitive decline, over up to 12 years of follow-up. PC-1 described a pro-inflammatory profile characterized by high positive loadings for pro-inflammatory biomarkers. A higher PC-1 score was associated with lower baseline cognitive performances. No association of this profile with cognitive decline was observed in longitudinal analysis. However, PC-5 characterized by high PDGF-AA and RANTES was associated with a faster cognitive decline. Among older adults, a circulating pro-inflammatory immune profile is associated with lower baseline cognitive performance, and some specific pro-inflammatory cytokines might be associated with faster cognitive decline.

Alzheimer disease is the most common cause of dementia. It occurs worldwide and affects all ethnic groups. The incidence of Alzheimer disease is increasing due, in part, to increased life expectancy and the aging baby boomer generation. The average lifetime risk of developing Alzheimer disease is 10–12%. This risk at least doubles with the presence of a first-degree relative with the disorder. Despite its limited utility, patients express concern over their risk and, in some instances, request testing. Furthermore, research has demonstrated that testing individuals for apolipoprotein E can be valuable and safe in certain contexts. However, because of the complicated genetic nature of the disorder, few clinicians are prepared to address the genetic risks of Alzheimer disease with their patients. Given the increased awareness in family history thanks to family history campaigns, the increasing incidence of Alzheimer disease, and the availability of direct to consumer testing, patient requests for information is increasing. This practice guideline provides clinicians with a framework for assessing their patients' genetic risk for Alzheimer disease, identifying which individuals may benefit from genetic testing, and providing the key elements of genetic counseling for AD.

Recent studies showed that polymorphisms in the Fat and Obesity-Associated (FTO) gene have robust effects on obesity, obesity-related traits and endophenotypes associated with Alzheimer's disease (AD). We used 1,877 Caucasian cases and controls from the NIA-LOAD study and 1,093 Caribbean Hispanics to further explore the association of FTO with AD. Using logistic regression, we assessed 42 SNPs in introns 1 and 2, the region previously reported to be associated with AD endophenotypes, which had been derived by genome-wide screenings. In addition, we performed gene expression analyses of neuropathologically confirmed AD cases and controls of two independent datasets (19 AD cases, 10 controls; 176 AD cases, 188 controls) using within- and between-group factors ANOVA of log(10) transformed rank invariant normalized expression data. In the NIALOAD study, one SNP was significantly associated with AD and three additional markers were close to significance (rs6499640, rs10852521, rs16945088, rs8044769, FDR p-value: 0.050.9) with the previously reported SNPs. In the Caribbean Hispanic dataset, we identified three SNPs (rs17219084, rs11075996, rs11075997, FDR p-value: 0.009

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