Glutathione Peroxidase 1 Pro198Leu Polymorphism in Brazilian Alzheimer's Disease Patients: Relations to the Enzyme Activity and to Selenium Status

Background/Aims: Oxidative stress plays a central role in Alzheimer's disease (AD). Pro198Leu cytosolic glutathione peroxidase (GPx1) polymorphism seems to be associated with a lower activity of this enzyme, but there are no studies with AD patients. Thus, the aim was to determine the frequency of the GPx1 Pro198Leu polymorphism in AD patients and to verify its relation to glutathione peroxidase (GPx) activity and selenium (Se) status. Methods:The study was carried out in a group of AD elderly (n = 28) compared to a control group (n = 29). Blood Se concentrations were measured through hydride generation atomic absorption spectroscopy. GPx activity was determined using a commercial kit, and the polymorphism using amplified DNA sequencing. Results:The distribution of genotypes was not different between groups. The variant allele frequency was 0.179 (AD group) and 0.207 (control group). Although no differences regarding GPx activity were found between individuals with different genotypes, lower blood Se levels were found in Pro/Pro AD patients compared to Pro/Pro control subjects, which was not found in the Pro/Leu groups. Moreover, the association between the erythrocyte Se concentration and GPx activity was affected by the Pro198Leu genotype. Conclusions: Results indicate that this polymorphism had apparently affected Se status in AD patients and that more studies in this field are necessary. Copyright (c) 2012 S. Karger AG, Basel

Reduced serum levels of adiponectin in elderly patients with major depression

Recent studies have implicated adiponectin and other adipocytokines in brain function, particularly in processes related to memory and cognition. Blood levels of adiponectin are reduced in patients with primary cognitive disorders, such as Alzheimer's disease and mild cognitive impairment, and in adult patients with major depression. The aim of the present study is to determine serum levels of adiponectin in a sample of elderly patients with major depressive disorder (MOD) as compared to healthy older adults, and to examine the correlations between adiponectin levels and parameters indicative of mood and cognitive state. We recruited fifty-one unmedicated outpatients with late-life depression (LLD) and 47 age-matched controls in this study. The diagnosis of MDD was made according to the DSM-IV criteria, and the severity of depressive episode was determined with the 21-item Hamilton Depression Scale (HORS). Cognitive state was ascertained with the Cambridge Cognitive Test (CAMCOG) and the Mini-Mental State Examination (MMSE). Serum concentrations of adiponectin were determined using a sandwich ELISA method. Serum levels of adiponectin were significantly reduced in individuals with LLD (F = p < 0.001). Adiponectin level remained significantly reduced in after controlling for BMI index, scores on the CAMCOG, MMSE and HDRS and educational level (p < 0.001). Adiponectin levels showed a negative correlation with HORS scores (r = -0.59, p < 0.001) and BMI index (r = -0.42, p < 0.001); and showed a positive correlation with CAMCOG (r = 0.34, p < 0.01) and MMSE scores (r = 0.20, p = 0.05). The availability of circulating adiponectin is reduced in older adults with major depression, with likely implications on cognitive and mood state. Additional studies are required to determine whether this abnormality pertains to the pathophysiology of geriatric depression per se, or is a consequence of the morbid state. (C) 2012 Elsevier Ltd. All rights reserved.

Does Lithium Prevent Alzheimer's Disease?

Lithium salts have a well-established role in the treatment of major affective disorders. More recently, experimental and clinical studies have provided evidence that lithium may also exert neuroprotective effects. In animal and cell culture models, lithium has been shown to increase neuronal viability through a combination of mechanisms that includes the inhibition of apoptosis, regulation of autophagy, increased mitochondrial function, and synthesis of neurotrophic factors. In humans, lithium treatment has been associated with humoral and structural evidence of neuroprotection, such as increased expression of anti-apoptotic genes, inhibition of cellular oxidative stress, synthesis of brain-derived neurotrophic factor (BDNF), cortical thickening, increased grey matter density, and hippocampal enlargement. Recent studies addressing the inhibition of glycogen synthase kinase-3 beta (GSK3B) by lithium have further suggested the modification of biological cascades that pertain to the pathophysiology of Alzheimer's disease (AD). A recent placebo-controlled clinical trial in patients with amnestic mild cognitive impairment (MCI) showed that long-term lithium treatment may actually slow the progression of cognitive and functional deficits, and also attenuate Tau hyperphosphorylation in the MCI-AD continuum. Therefore, lithium treatment may yield disease-modifying effects in AD, both by the specific modification of its pathophysiology via inhibition of overactive GSK3B, and by the unspecific provision of neurotrophic and neuroprotective support. Although the clinical evidence available so far is promising, further experimentation and replication of the evidence in large scale clinical trials is still required to assess the benefit of lithium in the treatment or prevention of cognitive decline in the elderly.

Reduced platelet amyloid precursor protein ratio (APP ratio) predicts conversion from mild cognitive impairment to Alzheimer's disease

Studies have shown that platelet APP ratio (representing the percentage of 120-130 kDa to 110 kDa isoforms of the amyloid precursor protein) is reduced in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). In the present study, we sought to determine if baseline APP ratio predicts the conversion from MCI to AD dementia after 4 years of longitudinal assessment. Fifty-five older adults with varying degrees of cognitive impairment (34 with MCI and 21 with AD) were assessed at baseline and after 4 years. MCI patients were re-classified according to the conversion status upon follow-up: 25 individuals retained the diagnostic status of MCI and were considered as stable cases (MCI-MCI); conversely, in nine cases the diagnosis of dementia due to AD was ascertained. The APP ratio (APPr) was determined by the Western blot method in samples of platelets collected at baseline. We found a significant reduction of APPr in MCI patients who converted to dementia upon follow-up. These individuals had baseline APPr values similar to those of demented AD patients. The overall accuracy of APPr to identify subjects with MCI who will progress to AD was 0.74 +/- A 0.10, p = 0.05. The cut-off of 1.12 yielded a sensitivity of 75 % and a specificity of 75 %. Platelet APPr may be a surrogate marker of the disease process in AD, with potential implications for the assessment of abnormalities in the APP metabolism in patients with and at risk for dementia. However, diagnostic accuracy was relatively low. Therefore, studies in larger samples are needed to determine whether APPr may warrant its use as a biomarker to support the early diagnosis of AD.

Transcriptional Alterations Related to Neuropathology and Clinical Manifestation of Alzheimer's Disease

Alzheimer's disease (AD) is the most common cause of dementia in the human population, characterized by a spectrum of neuropathological abnormalities that results in memory impairment and loss of other cognitive processes as well as the presence of non-cognitive symptoms. Transcriptomic analyses provide an important approach to elucidating the pathogenesis of complex diseases like AD, helping to figure out both pre-clinical markers to identify susceptible patients and the early pathogenic mechanisms to serve as therapeutic targets. This study provides the gene expression profile of postmortem brain tissue from subjects with clinic-pathological AD (Braak IV, V, or V and CERAD B or C; and CDR >= 1), preclinical AD (Braak IV, V, or VI and CERAD B or C; and CDR = 0), and healthy older individuals (Braak <= II and CERAD 0 or A; and CDR = 0) in order to establish genes related to both AD neuropathology and clinical emergence of dementia. Based on differential gene expression, hierarchical clustering and network analysis, genes involved in energy metabolism, oxidative stress, DNA damage/repair, senescence, and transcriptional regulation were implicated with the neuropathology of AD; a transcriptional profile related to clinical manifestation of AD could not be detected with reliability using differential gene expression analysis, although genes involved in synaptic plasticity, and cell cycle seems to have a role revealed by gene classifier. In conclusion, the present data suggest gene expression profile changes secondary to the development of AD-related pathology and some genes that appear to be related to the clinical manifestation of dementia in subjects with significant AD pathology, making necessary further investigations to better understand these transcriptional findings on the pathogenesis and clinical emergence of AD.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.