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news & views © 2001 Nature Publishing Group http://genetics.nature.com © 2001 Nature Publishing Group http://genetics.nature.com In embryos lacking Gcnf, Oct4 has an expanded range of expression in the posterior end of the embryo and is also expressed in the hindbrain region (see figure). Despite this expanded Oct4 expression pattern, some development proceeds normally, suggesting that Oct4 may be necessary, but not sufficient, for maintenance of the pluripotent state. Nevertheless, it will be interesting to see if expanded Oct4 expression in Gcnf-deficient embryos, particularly in the posterior region, results in increased numbers of germ cells being formed. Gcnf may be involved in starting the process of Oct4 repression, but it may not be the only factor that can maintain repression. In fact, in Gcnf-deficient embryos, Oct4 still remains repressed in much of the embryo even though Gcnf is absent. That repression could be maintained by other orphan receptors such as Coup-TfI and Coup-TfII, but could also be brought about by epigenetic mechanisms such as promoter methylation or histone deacetylation. In fact, downregulation of Oct4 expression is associated with promoter methylation11. Recent studies suggest that DNA methylation can synergize with histone deacetylation in repressing gene expression12. It is intriguing then that nuclear receptors such as Gcnf, together with co-repressors, can associate with histone deacetylases that play a critical role in the chromatin remodeling associated with gene silencing13–15. So perhaps Gcnf flicks the switch that triggers Oct4 promoter methylation and histone deacetylation. The resultant chromatin remodeling would close and lock the Oct4 promoter and shut down Oct4 expression. The identification of Gcnf as a repressor of Oct4 undoubtedly raises more questions than it answers, but the great thing is that now there are hypotheses about Oct4 regulation that can be tested experimentally. Watch this space Over the last couple of years, two distinct but related fields have figured greatly in the scientific news headlines—stem cells and cloning. In both fields, Oct4 looms large. For stem-cell biologists, some of the critical issues concern our ignorance of the fundamental nature of stem cells. What are the critical factors required for self-renewal of stem cells or maintenance of stem cells in an undifferentiated state? What are the real differences between pluripotent stem cells from embryos and stem cells derived from adults? One of the answers is clearly Oct4. For the cloning field, a major issue is the need to understand what is required to transform a nucleus that is restricted in potency into a nucleus that is totipotent and can recapitulate development. Put another way, what are the differences between a somatic (restricted) nucleus and a germline (totipotent) nucleus? One of the answers, again, is Oct4. Understanding what this factor does to regulate developmental potency is central to both fields of study. The identification of a nexus between Oct4 and Gcnf provides some critical clues as to how the differences between pluripotent cells and differentiated cells are established and maintained. Stay tuned! 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. Pesce, M., Gross, M. K. & Schöler, H. R. Bioessays 20, 722–732 (1998). Fuhrmann, G. et al. Dev. Cell 1, 377–387 (2001). Nichols, J. et al. Cell 95, 379–391 (1998). Niwa, H., Miyazaki, J. & Smith, A.G. Nature Genet. 24, 372–376 (2000). Pikarsky, E., Sharir, H., Ben-Shushan, E. & Bergman, Y. Mol. Cell. Biol. 14, 1026–1038 (1994). Schoorlemmer, J. et al. Mol. Cell. Biol. 14, 1122–1136 (1994). Sylvester, I. & Schöler, H. R. Nucleic Acids Res. 22, 901–911 (1994). Ben-Shushan, E., Sharir, H., Pikarsky, E. & Bergman, Y. Mol. Cell. Biol. 15, 1034–1048 (1995). Fuhrmann, G., Sylvester, I. & Schöler, H. R. Cell. Mol. Biol. (Noisy-le-grand) 45, 717–724. (1999). Chen, F., Cooney, A. J., Wang, Y., Law, S. W. & O’Malley, B. W. Mol. Endocrinol. 8, 1434–1444 (1994). Ben-Shushan, E., Pikarsky, E., Klar, A. & Bergman, Y. Mol. Cell. Biol. 13, 891–901 (1993). El-Osta, A. & Wolffe, A.P. Gene Exp. 9, 63–75 (2000). Nagy, L. et al. Cell 89, 373–380 (1997). Alland, L. et al. Nature 387, 49–55 (1997). Heinzel, T. et al. Nature 387, 43–48 (1997). Pharmacogenetics: more than skin deep Howard L. McLeod Department of Medicine, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, Missouri 63110, USA. e-mail: [email protected] It is well known that the efficacy of certain drugs varies from individual to individual, depending in part on variation in the genes that encode drug metabolizing enzymes. Whereas ethnic and geographic differences are commonly used to classify drug response, new results show that more accurate and robust genetic clusters—identified by genotyping a modest number of neutral markers—can be inferred with no prior knowledge of ethnicity. Such an approach may eventually become a part of drug evaluation and clinical practice. The ongoing identification of singlenucleotide polymorphisms (SNPs) has produced a greater understanding of the sources of genetic variability1. One area that will probably benefit from this effort is pharmacogenetics—the inherited component of variability in drug disposition, efficacy and toxicity. Geographic, ethnic and racial differences in the frequency of variant alleles provide a mechanistic basis for at least some of the observed clinical differences in pharmacokinetics or drug effect between popunature genetics • volume 29 • november 2001 lations2–4. On page 265 of this issue, James Wilson and colleagues5 compare the relative effectiveness of two methods of identifying clusters of people who have distinct patterns of drug-metabolizing enzyme SNPs. They show that clusters identified by genotyping (using microsatellite DNA) are far more robust than those identified using geographic and ethnic labels. These findings suggest both the power, and possible limitations, of a population genetic approach to drug response. DNA-based protocols are already in place for the prospective prevention of severe toxicity from some medications. For example, homozygous mutation in the gene encoding thiopurine methyltransferase brings a high risk (near 100%) of severe toxicity in patients receiving standard doses of 6-mercaptopurine or azathioprine6. Genetic screening of those patients who might receive these drugs for the treatment of leukemia or rheumatic disease, or to avoid rejection of trans247 © 2001 Nature Publishing Group http://genetics.nature.com news & views planted organs, may prevent potentially life-threatening toxicity6. Similar PCRbased assays can be carried out to determine the proper dose of the anticoagulant warfarin, the odds of pain relief from codeine and other clinical phenotypes that are influenced by SNP status1,7. Wilson and colleagues5 assess the representation of drug-metabolizing enzyme variants through a population genetic approach. Genotype analysis was carried out using microsatellite repeats from chromosome 1 (16 markers) and the X chromosome (23 markers) in 354 individuals from eight populations. These included Caucasian (Norwegian, Ashkenazi Jew, Armenian), Black (Bantu, Ethiopian, Afro-Caribbean) and Asian (Chinese, New Guinean) groups. The genetic data were then subjected to hierarchical clustering analysis (using the program STRUCTURE) to objectively determine distinct groups of individuals. Chromosome 1 markers gave clearer resolution than did the X chromosome, although no population was found to segregate completely with one of the four derived clusters. In addition, they show that inferred groupings based on the panel of chromosome 1 markers are much more successful at identifying people with distinct drugmetabolizing enzyme SNP patterns than an approach based solely on an ethnic or geographic label. This stands in contrast both to the common use of ethnicity as a variable in the evaluation of clinical studies and the literature that segregates populations into distinct ethnic or racial 248 © 2001 Nature Publishing Group http://genetics.nature.com BOB CRIMI groupings. The results highlight the genetic diversity of individuals, which is far beyond that which can be attributed to skin color or geography. This work also provides impetus for defining the underlying molecular basis of apparent racial or ethnic influences on clinical phenotypes. For example, a recent study of an angiotensin-converting enzyme inhibitor for heart failure described a lack of benefit for black patients, but a significant benefit for white patients8. This was not an ‘all-or-none’ phenomenon; 14% of black patients benefited compared with 49% of white patients. The genetic basis of the racial differential in drug efficacy may also explain why 51% of white patients were not helped by this therapy. It is no surprise that skin pigment is a lousy surrogate for drugmetabolism status or most any aspect of human physiology9. There is a reason for this clinical observation, but it is not as simple as geography, ethnicity or such. Wilson et al.5 show that genetic clustering is preferable to less objective measures, but there is no clustering algorithm that can provide a predictive surrogate for all of the drug-metabolizing enzyme SNPs. With the growing importance of SNPs and other genomic variants for guiding the selection of therapy, identification of disease risk, prevention of drug toxicity and other aspects of medical decision-making, there is no escaping the need to carry out individual genotype analysis for each SNP in individual patients. There will be no shortcuts or derived genomic map in the context of pharmacogenetics. As such, we must await improvements in the throughput, speed and cost of genotyping in order to bring this exciting academic exercise into medical application. 1. 2. 3. 4. 5. 6. 7. 8. 9. McLeod, H.L & Evans, W.E. Annu. Rev. Pharmacol. Toxicol. 41,101–121 (2001). Ameyaw, M.M. et al. Pharmacogenetics 11, 217–221 (2001). Xie, H.G., Kim, R.B., Wood, A.J. & Stein, C.M. Annu. Rev. Pharmacol. Toxicol. 41, 815–850 (2001). McLeod, H.L. et al. Pharmacogenetics 9, 773–776 (1999). Wilson, J.F. et al. Nature Genet. 29, 265–269 (2001). McLeod, H.L., Krynetski, E.Y., Relling, M.V. & Evans, W.E. Leukemia 14, 567–572 (2000). Evans, W.E. & Relling, M.V. Science 286, 487–491 (1999). Exner, D.V., Dries, D.L., Domanski, M.J. & Cohn, J.N. N. Engl. J. Med. 344, 1351–1357 (2001). McLeod, H.L. N. Engl. J. Med. 345, 766–767 (2001). nature genetics • volume 29 • november 2001