Analysis of Alzheimer's disease severity across brain regions by topological analysis of gene co-expression networks

Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks

BACKGROUND

The growing use of imaging procedures in medicine has raised concerns about exposure to low-dose ionising radiation (LDIR). While the disastrous effects of high dose ionising radiation (HDIR) is well documented, the detrimental effects of LDIR is not well understood and has been a topic of much debate. Since little is known about the effects of LDIR, various kinds of wet-lab and computational analyses are required to advance knowledge in this domain. In this paper we carry out an "upside-down pyramid" form of systems biology analysis of microarray data. We characterised the global genomic response following 10 cGy (low dose) and 100 cGy (high dose) doses of X-ray ionising radiation at four time points by analysing the topology of gene coexpression networks. This study includes a rich experimental design and state-of-the-art computational systems biology methods of analysis to study the differences in the transcriptional response of skin cells exposed to low and high doses of radiation.

RESULTS

Using this method we found important genes that have been linked to immune response, cell survival and apoptosis. Furthermore, we also were able to identify genes such as BRCA1, ABCA1, TNFRSF1B, MLLT11 that have been associated with various types of cancers. We were also able to detect many genes known to be associated with various medical conditions.

CONCLUSIONS

Our method of applying network topological differences can aid in identifying the differences among similar (eg: radiation effect) yet very different biological conditions (eg: different dose and time) to generate testable hypotheses. This is the first study where a network level analysis was performed across two different radiation doses at various time points, thereby illustrating changes in the cellular response over time.

Phosphoproteome profiling of substantia nigra and cortex regions of Alzheimer's disease patients

Alzheimer's disease (AD) is the most common form of dementia and cognitive impairment usually characterized by widespread neurodegeneration throughout the association cortex, limbic system and hippocampus. Aberrant protein phosphorylation is a defining pathological hallmark of AD and implicated in the dysregulation of major cellular processes through highly dynamic and complex signaling pathways. Here in, we demonstrate 81 proteins, of 600 spots selected, unambiguously identified as phosphorylated, providing a partial phosphoproteome profile of AD substantia nigra and cortex and respective control brain regions. More importantly, abnormal phosphorylation signal intensity of nine physiologically important proteins observed can profoundly affect cell metabolism, signal transduction, cytoskeleton integration, and synaptic function and accounts for biological and morphological alterations. Our studies employed two-dimensional gel electrophoresis for protein separation, Pro-Q(®) Diamond phosphoprotein staining and electrospray ionization quadrupole time of flight tandem MS for protein identification. NetPhosk 1.0 is used for the confirmation of protein modification status as well known/putative phosphoproteins. A further insight into the links among the identified phosphoproteins and functional roles STRING 8.3, KEGG and REACTOME pathway databases were applied. The present quantitative phosphoproteomic analysis can be supportive in establishing a broad database of potential protein targets of abnormal phosphorylation in AD brain.

The age of the "ome": genome, transcriptome and proteome data set collection and analysis

The current state of human genetic studies is both a marvel and a morass. A marvel in that with the completion of the human genome sequence, projects that used to take years now take months or weeks; however, this creates a wealth of data concomitant to a black hole of meaning. In terms of the well used analogy: the human genome sequence is a library in an ancient language with no Rosetta stone. Researchers have readily exploited the human genome map and thousands of candidate gene studies for a multitude of diseases have been performed. However, many of those studies have found that the variants associated with disease risk are not obvious coding changes. The question now becomes: what do these associations mean? One approach to the downstream mapping of associations is to use additional information to map which variant might truly be causative of risk and what that risk variant is doing. This review will summarize the current state of both data set collection and analysis for the understanding of DNA variants and their downstream effects on transcripts and proteins. This article is part of a Special Issue entitled 'Transcriptome'.

Inequalities and duality in gene coexpression networks of HIV-1 infection revealed by the combination of the double-connectivity approach and the Gini's method

The symbiosis (Sym) and pathogenesis (Pat) is a duality problem of microbial infection, including HIV/AIDS. Statistical analysis of inequalities and duality in gene coexpression networks (GCNs) of HIV-1 infection may gain novel insights into AIDS. In this study, we focused on analysis of GCNs of uninfected subjects and HIV-1-infected patients at three different stages of viral infection based on data deposited in the GEO database of NCBI. The inequalities and duality in these GCNs were analyzed by the combination of the double-connectivity (DC) approach and the Gini's method. DC analysis reveals that there are significant differences between positive and negative connectivity in HIV-1 stage-specific GCNs. The inequality measures of negative connectivity and edge weight are changed more significantly than those of positive connectivity and edge weight in GCNs from the HIV-1 uninfected to the AIDS stages. With the permutation test method, we identified a set of genes with significant changes in the inequality and duality measure of edge weight. Functional analysis shows that these genes are highly enriched for the immune system, which plays an essential role in the Sym-Pat duality (SPD) of microbial infections. Understanding of the SPD problems of HIV-1 infection may provide novel intervention strategies for AIDS.

microRNA-34c is a novel target to treat dementias

MicroRNAs are key regulators of transcriptome plasticity and have been implicated with the pathogenesis of brain diseases. Here, we employed massive parallel sequencing and provide, at an unprecedented depth, the complete and quantitative miRNAome of the mouse hippocampus, the prime target of neurodegenerative diseases such as Alzheimer's disease (AD). Using integrative genetics, we identify miR-34c as a negative constraint of memory consolidation and show that miR-34c levels are elevated in the hippocampus of AD patients and corresponding mouse models. In line with this, targeting miR-34 seed rescues learning ability in these mouse models. Our data suggest that miR-34c could be a marker for the onset of cognitive disturbances linked to AD and indicate that targeting miR-34c could be a suitable therapy.