Almost all common diseases, from diabetes to schizophrenia to arthritis to cancer, are complex. That is, these disorders are due to interactions of multiple genetic and environmental factors. Although the medical research community has been very successful in identifying the underlying causes of "simple" or Mendelian disorders, success in understanding complex disorders has been very limited. We are studying a highly complex disorder, atherosclerosis, that is the cause of heart disease and stroke (Lusis, 2000)

We have attempted to simplify the problem by studying mouse animal models of traits relevant to atherosclerosis and its risk factors. As in human populations, these tend to exhibit complex patterns of inheritance, reflecting the interactions of multiple, low penetrance mutations. In mice, however, we can construct large, planned crosses, and we can manipulate the genome.

To tackle the very difficult problem of relating particular sequence variations to these complex phenotypes, we have developed approaches that integrate genetic segregation, complex trait phenotypes, and whole genome expression array analyses. Using these combined data, we have modeled biologic networks and made predictions about the involvement of novel genes in certain traits relevant to atherosclerosis. We then tested these predictions using a series of transgenic experiments (Schadt et al., 2005). The results have been highly encouraging, as a high fraction of the genes predicted to be involved in these traits have been confirmed. In these studies, gene expression serves as a kind of intermediary between genotype and the complex phenotypes.

At the same time that we are carrying out these studies in mice, we will also carry out certain parallel studies using human cells. Recently, for example, we constructed biologic networks for human endothelial cells obtained from heart transplant donors (Gargalovic et al., 2006). Through collaborations, we are also pursuing genetic analyses of atherosclerosis in families and in populations.

References

1. Lusis A.J. (2000) Atherosclerosis. Nature 407:233-241.
2. Schadt E.E., Lamb J., Yang X., Zhu J., Edwards S., Guhathakurta D., Sieberts S.K., Monks S,. Reitman M., Zhang C., Lum P.Y., Leonardson A., Thieringer R., Metzger J.M., Yang L., Castle J., Zhu H., Kash S.F., Drake T.A., Sachs A., Lusis A.J. (2005) An integrative genomics approach to infer causal associations between gene expression and disease. Nat. Genet. 37:710-717.
3. Gargalovic PS, Imura M, Zhang B, Gharavi NM, Clark MJ, Pagnon J, Yang W-P, Truong A, Patel S, Nelson SF, Horvath S, Berliner JA, Kirchgessner TG, Lusis AJ. (2006) Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids.. Proc. Nat. Acad. Sci. USA, 103:12741-6.