Polymorphisms of the IL-6 gene increase the risk for late onset Alzheimer's disease and affected IL-6 plasma levels

PGAGP: Predicting pathogenic genes based on adaptive network embedding algorithm

The study of disease-gene associations is an important topic in the field of computational biology. The accumulation of massive amounts of biomedical data provides new possibilities for exploring potential relations between diseases and genes through computational strategy, but how to extract valuable information from the data to predict pathogenic genes accurately and rapidly is currently a challenging and meaningful task. Therefore, we present a novel computational method called PGAGP for inferring potential pathogenic genes based on an adaptive network embedding algorithm. The PGAGP algorithm is to first extract initial features of nodes from a heterogeneous network of diseases and genes efficiently and effectively by Gaussian random projection and then optimize the features of nodes by an adaptive refining process. These low-dimensional features are used to improve the disease-gene heterogenous network, and we apply network propagation to the improved heterogenous network to predict pathogenic genes more effectively. By a series of experiments, we study the effect of PGAGP's parameters and integrated strategies on predictive performance and confirm that PGAGP is better than the state-of-the-art algorithms. Case studies show that many of the predicted candidate genes for specific diseases have been implied to be related to these diseases by literature verification and enrichment analysis, which further verifies the effectiveness of PGAGP. Overall, this work provides a useful solution for mining disease-gene heterogeneous network to predict pathogenic genes more effectively.

Putative mechanisms of cognitive dysfunction in chemotherapy-naïve diffuse large B-cell lymphoma: a case report and review of the literature

Cognitive impairment is now recognized as a frequent consequence of treatments for cancers localized outside the central nervous system (CNS). In contrast, little attention has been given to the potentially deleterious cognitive effects from non-CNS cancers themselves. The present case study proposes that cognitive deficits occur in a subset of treatment-naive patients with diffuse large B-cell lymphoma in whom no gross evidence of lymphoma-related CNS involvement is apparent. Evidence is presented from a case study and elaborate putative mechanisms centering on deleterious effects of B-cell-mediated inflammatory cytokine secretion on neurons. Moreover, this case study speculates that genetic variability involving apolipoprotein E or other factors may mediate cognitive variability among these patients.

Pro-inflammatory conditions promote neuronal damage mediated by Amyloid Precursor Protein and decrease its phagocytosis and degradation by microglial cells in culture

Aberrant handling of Amyloid Precursor Protein (APP) and beta-amyloid (Abeta), glial activation and inflammation are key events in Alzheimer's disease. We set out to determine the role of inflammation on microglial reactivity against APP. We studied microglia-mediated neurotoxicity, uptake and degradation of a biotinylated APP construct (biotin-APP-C-244). APP, in contrast to Abeta, only induced mild activation of glial cells. However, under pro-inflammatory conditions, APP induced microglial-mediated cytotoxicity. Biotin-APP-C-244 or lipopolysaccharide and interferon-gamma (LPS+IFNgamma), administered separately, did not change reduction metabolism of microglia. However, biotin-APP-C-244+(LPS+IFNgamma) increased microglial reactivity and decreased reduction metabolism by 75% (P<0.001). Biotin-APP-C-244 was readily taken up by microglial cells; 80% was phagocytosed at 2 h. In the presence of LPS+IFNgamma, phagocytosis of biotin-APP-C-244 was reduced at 2 h; and cell damage was evident after 4 h. Our results support our hypothesis that, in neuroinflammation, microglial scavenger function is impaired and reactivity against APP enhanced as an initial step for neurodegeneration.

Tumour necrosis factor-alpha gene polymorphisms and Alzheimer's disease

Recent findings suggest that production of pro-inflammatory cytokines, such as tumour necrosis factor-alpha (TNF-alpha), is increased in the brains of people with Alzheimer's disease (AD). We used direct sequencing methods on a section of the enhancer/promoter region and on a smaller fragment located 10.5 kb upstream of the TNF-alpha gene to respectively examine TNF-alpha polymorphisms and TNF-a and -b microsatellite alleles in a cohort of 235 post-mortem confirmed AD and 130 control cases. None of the TNF-alpha point mutations or microsatellite alleles investigated proved to be independent risk factors for AD. However, when -308/A, -238/G and TNF-a2 were examined as a 2-1-2 haplotype, we observed that the absence of that haplotype was significantly associated with AD (P = 0.014, Fisher's exact test) suggesting that the 2-1-2 haplotype may be protective against AD.

Inflammatory processes in Alzheimer's disease

Neuroinflammation is a characteristic of pathologically affected tissue in several neurodegenerative disorders. These changes are particularly observed in affected brain areas of Alzheimer's disease (AD) cases. They include an accumulation of large numbers of activated microglia and astrocytes as well as small numbers of T-cells, mostly adhering to postcapillary venules. Accompanying biochemical alterations include the appearance or up-regulation of numerous molecules characteristic of inflammation and free radical attack. Particularly important may be the complement proteins, acute phase reactants and inflammatory cytokines. These brain phenomena combined with epidemiological evidence of a protective effect of antiinflammatory agents suggest that such agents may have a role to play in treating the disease.