Protein markers for Alzheimer disease in the frontal cortex and cerebellum

Objective: To compare proteins related to Alzheimer disease ( AD) in the frontal cortex and cerebellum of subjects with early-onset AD (EOAD) with or without presenilin 1 (PS1) mutations with sporadic late-onset AD ( LOAD) and nondemented control subjects. Methods: Immunohistochemistry, immunoblot analysis, and ELISA were used to detect and assess protein levels in brain. Results: In EOAD and to a lesser extent in LOAD, there was increased amyloid beta (Abeta) deposition (by immunohistochemistry), increased soluble Abeta (by immunoblot analysis), and specific increases in Abeta(40) and Abeta(42) ( by ELISA) in the frontal cortex and, in some cases, in the cerebellum. Surprisingly, immunoblot analysis revealed reduced levels of PS1 in many of the subjects with EOAD with or without PS1 mutations. In those PS1 mutation-bearing subjects with the highest Abeta, PS1 was barely, if at all, detectable. This decrease in PS1 was specific and not attributable solely to neuronal loss because amyloid precursor protein (APP) and the PS1-interacting protein beta-catenin levels were unchanged. Conclusions: This study shows that in the frontal cortex and cerebellum from Alzheimer disease patients harboring certain presenilin 1 mutations, high levels of amyloid beta are associated with low levels of presenilin 1. The study provides the premise for further investigation of mechanisms underlying the downregulation of presenilin 1, which may have considerable pathogenic and therapeutic relevance.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 ± 1.9 years) and 14 matched controls (age: 71.4 ± 0.9 years), each scanned twice (2.1 ± 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Corrigendum to "Mapping hippocampal and ventricular change in Alzheimer disease" [NeuroImage 22 (2004) 1754-1766] (DOI:10.1016/j.neuroimage.2004.03.040)

We recently noticed an error in the demographic data in this article. The validity of the findings and the conclusions of the paper is not affected. However, there is an error in the reported sample size and in the means and standard deviations of the subjects’ ages and MMSE scores. We would like to correct this error, which came to light when we were re-analyzing the data for a meta-analysis. The error occurred because an older version of a spreadsheet was incorrectly used when reporting the sample composition. Instead of examining 12 Alzheimer's disease patients and 14 healthy elderly controls, we in fact examined 17 Alzheimer’s disease patients and 14 healthy elderly controls. All maps and morphometric data reported in the paper are correct, except that the sample size was in fact slightly higher than that originally reported, and the maps computed in the paper were based on the larger sample (which included five more subjects in the Alzheimer’s disease group). All of the maps and figures in the paper are correct, and the conclusions of the paper are unchanged. We apologize for this error, which falls under the sole responsibility of the first author. The corrected demographic information appears below.

GFAP Isoforms in Adult Mouse Brain with a Focus on Neurogenic Astrocytes and Reactive Astrogliosis in Mouse Models of Alzheimer Disease

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Preprocess and data analysis techniques for affymetrix DNA microarrays using bioconductor: a case study in Alzheimer disease

DNA microarray, or DNA chip, is a technology that allows us to obtain the expression level of many genes in a single experiment. The fact that numerical expression values can be easily obtained gives us the possibility to use multiple statistical techniques of data analysis. In this project microarray data is obtained from Gene Expression Omnibus, the repository of National Center for Biotechnology Information (NCBI). Then, the noise is removed and data is normalized, also we use hypothesis tests to find the most relevant genes that may be involved in a disease and use machine learning methods like KNN, Random Forest or Kmeans. For performing the analysis we use Bioconductor, packages in R for the analysis of biological data, and we conduct a case study in Alzheimer disease. The complete code can be found in https://github.com/alberto-poncelas/ bioc-alzheimer

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

The COMT Val158 Met polymorphism as an associated risk factor for Alzheimer disease and mild cognitive impairment in APOE 4 carriers

Background: The aim of this study is to examine the influence of the catechol-O-methyltranferase (COMT) gene (polymorphism Val158 Met) as a risk factor for Alzheimer's disease (AD) and mild cognitive impairment of amnesic type (MCI), and its synergistic effect with the apolipoprotein E gene (APOE). A total of 223 MCI patients, 345 AD and 253 healthy controls were analyzed. Clinical criteria and neuropsychological tests were used to establish diagnostic groups. The DNA Bank of the University of the Basque Country (UPV-EHU) (Spain) determined COMT Val158 Met and APOE genotypes using real time polymerase chain reaction (rtPCR) and polymerase chain reaction (PCR), and restriction fragment length polymorphism (RFLPs), respectively. Multinomial logistic regression models were used to determine the risk of AD and MCI. Results: Neither COMT alleles nor genotypes were independent risk factors for AD or MCI. The high activity genotypes (GG and AG) showed a synergistic effect with APOE epsilon 4 allele, increasing the risk of AD (OR = 5.96, 95% CI 2.74-12.94, p < 0.001 and OR = 6.71, 95% CI 3.36-13.41, p < 0.001 respectivily). In AD patients this effect was greater in women. In MCI patients such as synergistic effect was only found between AG and APOE epsilon 4 allele (OR = 3.21 95% CI 1.56-6.63, p = 0.02) and was greater in men (OR = 5.88 95% CI 1.69-20.42, p < 0.01). Conclusion: COMT (Val158 Met) polymorphism is not an independent risk factor for AD or MCI, but shows a synergistic effect with APOE epsilon 4 allele that proves greater in women with AD.

Inflammation and Anti-inflammatory strategies for alzheimer disease a mini review

Until recently, the central nervous system (CNS) has been thought to be an immune privileged organ. However, it is now understood that neuroinflammation is linked with the development of several CNS diseases including late-onset Alzheimer's disease (LOAD). The development of inflammation is a complex process involving a wide array of molecular interactions which in the CNS remains to be further characterized. The development of neuroinflammation may represent an important link between the early stages of LOAD and its pathological outcome. It is proposed that risks for LOAD, which include genetic, biological and environmental factors can each contribute to impairment of normal CNS regulation and function. The links between risk factors and the development of neuroinflammation are numerous and involve many complex interactions which contribute to vascular compromise, oxidative stress and ultimately neuroinflammation. Once this cascade of events is initiated, the process of neuroinflammation can become overactivated resulting in further cellular damage and loss of neuronal function. Additionally, neuroinflammation has been associated with the formation of amyloid plaques and neurofibrillary tangles, the pathological hallmarks of LOAD. Increased levels of inflammatory markers have been correlated with an advanced cognitive impairment. Based on this knowledge, new therapies aimed at limiting onset of neuroinflammation could arrest or even reverse the development of the disease.

Randomized controlled trial of atorvastatin in mild to moderate Alzheimer disease:LEADe

There is some evidence that statins may have a protective and symptomatic benefit in Alzheimer disease (AD). The LEADe study is a randomized controlled trial (RCT) evaluating the efficacy and safety of atorvastatin in patients with mild to moderate AD.

Moderately elevated plasma homocysteine, methylenetetrahydrofolate reductase genotype, and risk for stroke, vascular dementia, and Alzheimer disease in Northern Ireland

Elevated plasma homocysteine level has been associated with increased risk for cardiovascular and cerebrovascular disease. Variation in the levels of this amino acid has been shown to be due to nutritional status and methylenetetrahydrofolate reductase (MTHFR) genotype.

No consistent evidence for association between mtDNA variants and Alzheimer disease

Although several studies have described an association between Alzheimer disease (AD) and genetic variation of mitochondrial DNA (mtDNA), each has implicated different mtDNA variants, so the role of mtDNA in the etiology of AD remains uncertain.

Age-Related Macular Degeneration-Associated Genes in Alzheimer Disease

Objectives: Given the clinical and pathological similarities between age-relatedmacular degeneration (AMD) and Alzheimer disease (AD), to assess whether AMDassociatedsingle nucleotide polymorphisms (SNPs), including those from complementrelatedgenes, are associated with AD. 
Design: A case-control association study-typedesign. 
Setting: A UK tertiary care dementia clinic. 
Participants: 322 cognitivelynormal participants and 258 cases with a clinical diagnosis of AD.
Measurements:Polymorphisms in the following genes were studied: CFH, ARMS2, C2/CFB, C3, CFI/PLA2G12a, SERPING1, TLR3, TLR4, CRP, APOE, and TOMM40. Haplotypes were analysedfor CFH, TOMM40, and APOE. Univariate analysis was performed for each geneticchange and case-comparator status, and then correction for multiple testing performed. 
Results: The presence of an ε4 APOE allele was significantly associated with AD. Noassociation was evident between CFH SNPs or haplotypes, or other AMD-associated SNPstested, and AD. The exceptions were TOMM40 SNPs, which were associated with AD evenafter correction for multiple comparisons. The associations disappeared, however, whenentered into a regression model including APOE genotypes. 
Conclusions: The resultsfor most SNPs tested, as well as CFH haplotypes, are novel. The functional effects ofabnormal complement activity in AD’s pathogenesis may be contradictory, butmethodological reasons may underlie the lack of association—for example, geneticchanges other than SNPs being involved.