Embrace diversity! Systems genetics-enabled discovery of disease networks

Abstract

identify robust and strain-, sex-, and strain*sex-dependent responses to the diet. Global analysis of the expression data by ANOVA revealed extensive impact of both strain and sex on dietary responses in liver. The main effect of diet was apparent in the differential expression of almost 57% of genes on the arrays. Among the top co-regulated of these, the authors showed using Gene Ontology (GO) enrichment analyses that the expected effects of diet-mediated suppression of cholesterol biosynthesis occurred in all strains and that other specific biological systems functional involvements were also strongly implicated. Valuable data emerge from the ability to identify sets of genes that are reflective of strain-, sex-, and strain*sexdependent effects of diet, attributable in part from the statistical power of the study design in which the underlying genetic variations imparted systematic effects at the level of biological pathways and processes. When strain is taken into account, the majority of significantly enriched GO categories reflected a powerful correlation between effects of diet on immune function, such as antigen processing and presentation. The authors suggest that these changes may be related to diet-induced liver damage, which was indicated by changes expression of damage-related genes and by an increase in circulating levels of glutamate dehydrogenase. However, these changes may also broadly reflect genetic correlation between pathways that mediate immune responses and the development of diet-induced atherogenic plaques, the formation and propagation of which are driven by immune responses. Integrating the expression data with information about the incidence, severity, and phenotypic details of atherosclerotic lesions in this same set of strains should shed additional light on this possibility. Other important follow-on studies may also determine if strainspecific patterns of immune gene expression in liver are paralleled by qualitatively similar effects on lymphocyte populations, atherogenic lesions, and insulin pathway-associated tissues. Importantly, the authors have also provided a publicly accessible database that can be mined in a number of ways. For example, this resource could be used to select strains with divergent responses to diet (e.g., sensitive and resistant to liver damage) or to identify coexpression networks centered around a gene(s) of specific interest. It could also be used to extract supportive evidence for genes implicated in processes related