Anatomy and Neuroscience - Research Publications
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ItemNo Preview Availableattract: A Method for Identifying Core Pathways That Define Cellular Phenotypes(PUBLIC LIBRARY SCIENCE, 2011-10-14)attract is a knowledge-driven analytical approach for identifying and annotating the gene-sets that best discriminate between cell phenotypes. attract finds distinguishing patterns within pathways, decomposes pathways into meta-genes representative of these patterns, and then generates synexpression groups of highly correlated genes from the entire transcriptome dataset. attract can be applied to a wide range of biological systems and is freely available as a Bioconductor package and has been incorporated into the MeV software system.
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ItemVariance of Gene Expression Identifies Altered Network Constraints in Neurological Disease(PUBLIC LIBRARY SCIENCE, 2011-08)Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinson's disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.
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ItemIL-12 and Related Cytokines: Function and Regulatory Implications in Candida albicans Infection(HINDAWI LTD, 2011)IL-12 is a cytokine with links to both innate and adaptive immunity systems. In mice, its deletion leads to acute susceptibility to oral infection with the yeast Candida albicans, whereas such mice are resistant to systemic disease. However, it is an essential component of the adaptive response that leads to the generation of Th1-type cytokine responses and protection against disseminated disease. This paper presents an overview of the role of IL-12 in models of systemic and mucosal infection and the possible relationships between them.
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ItemNRF2 Activation Restores Disease Related Metabolic Deficiencies in Olfactory Neurosphere-Derived Cells from Patients with Sporadic Parkinson's Disease(PUBLIC LIBRARY SCIENCE, 2011-07-01)BACKGROUND: Without appropriate cellular models the etiology of idiopathic Parkinson's disease remains unknown. We recently reported a novel patient-derived cellular model generated from biopsies of the olfactory mucosa (termed olfactory neurosphere-derived (hONS) cells) which express functional and genetic differences in a disease-specific manner. Transcriptomic analysis of Patient and Control hONS cells identified the NRF2 transcription factor signalling pathway as the most differentially expressed in Parkinson's disease. RESULTS: We tested the robustness of our initial findings by including additional cell lines and confirmed that hONS cells from Patients had 20% reductions in reduced glutathione levels and MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt] metabolism compared to cultures from healthy Control donors. We also confirmed that Patient hONS cells are in a state of oxidative stress due to higher production of H(2)O(2) than Control cultures. siRNA-mediated ablation of NRF2 in Control donor cells decreased both total glutathione content and MTS metabolism to levels detected in cells from Parkinson's Disease patients. Conversely, and more importantly, we showed that activation of the NRF2 pathway in Parkinson's disease hONS cultures restored glutathione levels and MTS metabolism to Control levels. Paradoxically, transcriptomic analysis after NRF2 pathway activation revealed an increased number of differentially expressed mRNAs within the NRF2 pathway in L-SUL treated Patient-derived hONS cells compared to L-SUL treated Controls, even though their metabolism was restored to normal. We also identified differential expression of the PI3K/AKT signalling pathway, but only post-treatment. CONCLUSIONS: Our results confirmed NRF2 as a potential therapeutic target for Parkinson's disease and provided the first demonstration that NRF2 function was inducible in Patient-derived cells from donors with uniquely varied genetic backgrounds. However, our results also demonstrated that the response of PD patient-derived cells was not co-ordinated in the same way as in Control cells. This may be an important factor when developing new therapeutics.
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ItemDefining an informativeness metric for clustering gene expression data(OXFORD UNIV PRESS, 2011-04-15)MOTIVATION: Unsupervised 'cluster' analysis is an invaluable tool for exploratory microarray data analysis, as it organizes the data into groups of genes or samples in which the elements share common patterns. Once the data are clustered, finding the optimal number of informative subgroups within a dataset is a problem that, while important for understanding the underlying phenotypes, is one for which there is no robust, widely accepted solution. RESULTS: To address this problem we developed an 'informativeness metric' based on a simple analysis of variance statistic that identifies the number of clusters which best separate phenotypic groups. The performance of the informativeness metric has been tested on both experimental and simulated datasets, and we contrast these results with those obtained using alternative methods such as the gap statistic. AVAILABILITY: The method has been implemented in the Bioconductor R package attract; it is also freely available from http://compbio.dfci.harvard.edu/pubs/attract_1.0.1.zip. CONTACT: jess@jimmy.harvard.edu; johnq@jimmy.harvard.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.