We discuss the theoretical structure and constructive methodology for large-scale graphical models, motivated by their potential in evaluating and aiding the exploration of patterns of association in gene expression data. The theoretical discussion covers basic ideas and connections between Gaussian graphical models, dependency networks and specific classes of directed acyclic graphs we refer to as compositional networks. We describe a constructive approach to generating interesting graphical models for very high-dimensional distributions that builds on the relationships between these various stylized graphical representations. Issues of consistency of models and priors across dimension are key. The resulting methods are of value in evaluating patterns of association in large-scale gene expression data with a view to generating biological insights about genes related to a known molecular pathway or set of specified genes. Some initial examples relate to the estrogen receptor pathway in breast cancer, and the Rb-E2F cell proliferation control pathway. r 2004 Elsevier Inc. All rights reserved.

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Despite the strikingly grave prognosis for older patients with glioblastomas, significant variability in patient outcome is experienced. To explore the potential for developing improved prognostic capabilities based on the elucidation of potential biological relationships, we did analyses of genes commonly mutated, amplified, or deleted in glioblastomas and DNA microarray gene expression data from tumors of glioblastoma patients of age >50 for whom survival is known. No prognostic significance was associated with genetic changes in epidermal growth factor receptor (amplified in 17 of 41 patients), TP53 (mutated in 11 of 41 patients), p16INK4A (deleted in 15 of 33 patients), or phosphatase and tensin homologue (mutated in 15 of 41 patients). Statistical analysis of the gene expression data in connection with survival involved exploration of regression models on small subsets of genes, based on computational search over multiple regression models with cross-validation to assess predictive validity. The analysis generated a set of regression models that, when weighted and combined according to posterior probabilities implied by the statistical analysis, identify patterns in expression of a small subset of genes that are associated with survival and have value in assessing survival risks. The dominant genes across such multiple regression models involve three key genes-SPARC (Osteonectin), Doublecortex, and Semaphorin3B-which play key roles in cellular migration processes. Additional analysis, based on statistical graphical association models constructed using similar computational analysis methods, reveals other genes which support the view that multiple mediators of tumor invasion may be important prognostic factor in glioblastomas in older patients. (Cancer Res 2005; 65(10): 4051-8)

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The covariance between two variables in a multivariate Gaussian distribution is decomposed into a sum of path weights for all paths connecting the two variables in an undirected independence graph. These weights are useful in determining which variables are important in mediating correlation between the two path endpoints. The decomposition arises in undirected Gaussian graphical models and does not require or involve any assumptions of causality. This covariance decomposition is derived using basic linear algebra. The decomposition is feasible for very large numbers of variables if the corresponding precision matrix is sparse, a circumstance that arises in examples such as gene expression studies in functional genomics. Additional computational efficiencies are possible when the undirected graph is derived from an acyclic directed graph.

The spatial organization of the chromosomes is crucial for gene expression and development. Inter-and intrachromosomal interactions form a crucial part of this epigenomic regulatory system. Here we use circular chromosome conformation capture-on-chip (4C) to identify interactions between repetitive and non-repetitive loci within the yeast genome. The interacting regions occur in non-randomly distributed clusters. Furthermore, the SIR2 histone deacetylase has opposing roles in the organization of the inter-or intrachromosomal interactions. These data establish a dynamic domain model for yeast genome organization. Moreover, they point to the repeated elements playing a central role in the dynamic organization of genome architecture.

Fruit and vegetables are key elements of a cardioprotective diet, but benefits on plasma lipids, especially HDL-cholesterol (HDL-C), are inconsistent both within and between studies. In the present study, we investigated whether four selected HDL-C-related polymorphisms (cholesteryl ester transfer protein (CETP) Taq1B, APOA1 2 75G/A, hepatic lipase (LIPC) 2 514C ! T, and endothelial lipase (LIPG) I24582) modulate the plasma lipid response to a kiwifruit intervention. This is a retrospective analysis of data collected during a 12-week randomised controlled cross-over trial. A total of eighty-five hypercholesterolaemic men completed a 4-week healthy diet run-in period before being randomised to one of two 4-week intervention sequences of two green kiwifruit/d plus healthy diet (kiwifruit intervention) or healthy diet alone (control intervention). The measurement of anthropometric parameters and collection of fasting blood samples were carried out at baseline 1 and after the run-in (baseline 2) and intervention periods. At baseline 2, B1/B1 homozygotes of the CETP Taq1B gene had significantly higher total cholesterol:HDL-C, TAG:HDL-C, and apoB:apoA1 ratios and small-dense LDL concentrations than B2 carriers. A significant CETP Taq1B genotype £ intervention interaction was observed for the TAG:HDL-C ratio (P¼ 0·03). B1/B1 homozygotes had a significantly lower TAG:HDL-C (20·23 (SD 0·58) mmol/l; P¼ 0·03) ratio after the kiwifruit intervention than after the control intervention, whereas the ratio of B2 carriers was not affected. The lipid response was not affected by other gene polymorphisms. In conclusion, the significant decrease in the TAG:HDL-C ratio in B1/B1 homozygotes suggests that regular inclusion of green kiwifruit as part of a healthy diet may improve the lipid profiles of hypercholesterolaemic men with this genotype.

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