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sist over long periods of time, and they there are inborn cohesive forces 1 Pinker S. How the Mind Works. WW Nor- cannot grow except by recruitment. which cause the different individ- ton & Company: New York, London, 1997, pp 1–528. In short, populations differ from uals within a population to coop- 2 Wynne Edwards WC. Evolution through each other because many of their erate sufficiently for the popu- group selection. Blackwell: Oxford, 1986. members tend to carry different lation to function as one 3 Wilson DS. Proc Nat Acad Sci USA 1975; 72: mutants; furthermore, it is the non- evolutionary unit. 143–146. 4 Wilson DS. Science 1997; 276: 1816–1817. uniformity of the individual members (2) As a second requirement, there 5 Wilson DS, Sober E. J Theor Biol 1989; 136: of a population which helps a popu- must be effective evolutionary dif- 337–356. lation to function as an effective ferences between individuals 6 Rice SH. J Theor Biol 1995; 177: 237–245. entity, and thereby to allow evolution- which at the same time make 7 Crognier E. Ann Hum Biol 2000; 27: 221– 237. ary competition. The situation is anal- every population different from 8 Michod RE, Roze D. Heredity 2001; 86:1–7. ogous to that of a complex organism other populations. The existence 9 Hamilton WD. J Theor Biol 1964; 7:1–52. which has different cells, but they col- of mutations assures the occur- 10 Maynard Smith J. Evolutionary Genetics (2nd laborate and form a living unit. Many rence of differences between indi- edn). Oxford University Press: Oxford, New York, Tokyo, 1998, pp 163–178. of the individual diversities in a popu- viduals as well as between popu- 11 Bradley BJ. Q Rev Biol 1999; 74: 171–194. lation are genetically controlled, as are lations. 12 Chomsky N. Chomsky’s Classic Works. Lang- the different cells of a multicellular uage and Responsibility and Reflections on Important in the current context is organism. Language. New Press: New York, 1998. the fact that it is genetic factors carried 13 Pinker S. Nature 1997; 387: 547–548. To allow evolutionary forces to by individuals which make it possible 14 Lorenz K. Evolution and Modification of favor, or to eliminate, either an indi- for populations to function as differ- Behavior. University of Chicago Press: vidual or a population, there are two Chicago, IL, 1971. ent evolutionary units. requirements applying to both these 15 Charrier I et al. Nature 2001; 412: 873. 16 Weimerskirch H et al. Nature 2001; 413: units of selection: DUALITY OF INTEREST 697–698. 292 (1) The first requirement is the pres- None declared. 17 Goldenberg J et al. Science 2001; : 2433. ence and function of cohesive 18 Seashore CE. Psychology of Music. Dover: Correspondence should be sent to forces; we are not surprised when New York, 1967. W Kalow, Department of Pharmacology, the cohesive forces between the 19 Boehm C. Curr Anthropol 1993; 34: 227– Medical Sciences Building, University of different cells of a multicellular 254. Toronto, Toronto M5S 1A8, Canada. 20 Kalow W. Pharmacogenetics 2001; 10:1–3. organism allow this organism to Tel: 416 978 2734 21 Siller S. Nature 2001; 411: 689–692. act as an individual. However, we Fax: 416 978 6395 also have to accept the fact that Email: w.kalowȰutoronto.ca

of predictable outcomes from a study Pharmacogenomics—Is there a role of human genomes and their responses ex vivo to a particular phar- in antibiotic therapy? macological agent.2,3 Treatment of infectious diseases is a DB Davison1, TJ Dougherty2, JF Barrett3 and M Pucci1 bit of a therapeutic outlier. Ideally, one desires an agent that has no discern- 1Bristol-Myers Squibb Pharmaceutical Research Institute, Wallingford, CT, USA; 2Pfizer ible effects on the host of an infection, Global Research & Development, Groton, CT, USA; 3Merck Research Laboratories, while having lethal effects on the Rahway, NJ, USA invading organism. Neither of these ideals is ever achieved. When one thinks of pharmacogenomics in infec- The Pharmacogenomics Journal (2002) 2, and possibly adverse events that vary tious diseases, it is often in the context 14–16. DOI: 10.1038/sj/tpj/6500064 with the host’s repertoire of gene poly- of drug effects (P450 interactions, etc) 1 morphisms. Several of the most obvi- and seldom in terms of the microbial In its purest form, pharmacogenomics ous and well-discussed areas of pharm- population that the drug affects. Usu- is defined as the functional linkage of acogenomics potential have been ally this is couched in terms of a the science of human pharmacology, oncology, CNS disorders, and decision in prescribing of a drug to toxicology and genomics. This link is inflammation, where a pattern of gene which the patient may be allergic or somewhat artificial, and in its current expression (up- or down-regulation) prescribing a drug to which the patient usage, pharmacogenomics implies an may be monitored in response to a may have an adverse response due to association of some pharmacological given pharmacological agent. The ulti- aberrant metabolism because of, eg, agent with measurable host responses mate promise of pharmacogenomics is polymorphic variations in the

The Pharmacogenomics Journal Pharmacogenomics—a role in antibiotic therapy? DB Davison et al 15

expression of the repertoire of human organisms. It has become clear that Another important pharmacogen- cytochromes. If a pharmacogenetic, or microbial populations, despite being omic measurement is the pathogen’s pharmacogenomic evaluation was largely clonal at the onset, can during response to both the host immune somehow instantaneously possible, an infection become heterogeneous in response and the antibiotic used to the drug of choice would be matched terms of, for example, antibiotic resist- suppress or kill it. The host response against the maximum compatibility of ance. Let’s consider the possible exam- can be assessed by its ability to invoke the host and maximal effect on the ination of antibiotic resistance by a a competent host immune response, infectious agent. pharmacogenomics analysis. There is both non-specific(ieRESsystem)and However, there may not be any evidence accumulating that differing specific (antibody or T-cell response). more significant effector of human environments (eg, in a host Gene markers can quantitatively pharmacology than the microbial compartment) and stress (eg, anti- measure all of these responses, but infection itself (bacterial, fungal and biotic treatment) can increase none at present immediately help viral). The cascade of gene expression mutation rates in bacteria.6 This popu- with diagnosis of infection or choice response to infection is diverse and lation heterogeneity, in turn, can lead of therapy. immense, affecting numerous human to increased rates of resistance devel- The bacterium’s response at the gen- host response genes including the opment and treatment failures. This omic level, however, may be a very complement cascade, general heterogeneity of bacterial populations direct and quick indicator of the resist- inflammation responses, febrile in an infection can become quite ance potential. For example, the response, the numerous immune marked; for example, a very high per- science of gene expression profiling response systems, and likely additional centage of mutators are found among (microarrays, etc) has evolved to the factors yet to be uncovered. The Pseudomonas aeruginosa isolated from point that, within a day or two, a com- human population heterogeneity can cystic fibrosis patients.7 plete time-sequence-based expression have an even more profound influence The predictive nature of data from a pattern of gene products could be on the outcome of infection. Con- pharmacogenomic evaluation of any assessed in bacteria. This would allow sider, for example, the presence of sin- given drug’s effects on a pathogen for contrasting the ‘normal’ and ‘drug gle-nucleotide polymorphisms in the could have a significantly greater affected’ bacterium to see what effects human population; these minor differ- impact than single point MIC drug treatment may have on the ences in certain genes are known to measurements. That is, a MIC deter- dynamics of the pathogen population. affect the outcome of the events asso- mines the ability of a drug to inhibit The ability of chips to detect single ciated with the gene products. A visible bacterial growth in a standard mismatches and expression levels of recent, well-publicized example is that assay, but does nothing to predict key resistance genes could be used of individuals naturally resistant to resistance potential, mode of inhi- both to detect resistance mutations, HIV.4 A mutation in the CD4 receptor bition (bactericidal or bacteristatic), and measure expression levels of resist- prevents the virus from binding, thus virulence, efflux, genes turned on or ance genes. If a profile of relevant preventing infection. Another off—all ‘genomics-measurable’ para- example is the recent discovery of meters that may better predict the out- mouse polymorphisms in the kif1C come of a given treatment regimen. gene that alter susceptibility of macro- But how could this work? The most phages to anthrax toxin.5 It is antici- straightforward way to proceed would pated that this genetic basis for be a ‘profiling’ of gene expression in anthrax susceptibility will extend to devising a pharmacogenomic evalu- man. The antimicrobials used to treat ation, most likely established initially pathogens may also affect the ‘pharm- by whole genome microarrays with a acogenomic’ response in humans significant contribution possible from indirectly by affecting the presen- proteomics. Effects normalized to tation of a pathogen to the human drug-free controls and normalization host (eg modification of the pathogen to growth rates of a pathogen may pro- surface or lytic events exposing bac- vide data in which a rapid diagnostic terial intracellular content). Alterna- test of gene expression (custom chip) tively, the drug used to treat the infec- and an algorithm designed to weigh tion can in itself affect host response factors beyond mere inhibition of vis- by direct pharmacological action (eg, ible growth are employed in the macrolides) or through effects on host future. In addition, the effect of a Figure 1 The key to the successful appli- gene regulation and/or expression. pathogen on the up- or down-regu- cation of antimicrobial pharmacogenomics Since pharmacogenomics deals with lation of host defense function may will be defining and exploiting the overlap populations, one can perhaps likewise also constitute a highly relevant ‘pharmacogenomics’ of the effects of anti- apply this approach of genomic popu- measurement of the potential for suc- biotics on both the bacterium and the lation analysis to the infecting micro- cess of the drug in the clinic. host itself.

www.nature.com/tpj The HUGO Mutation Database Initiative RGH Cotton and O Horaitis 16

resistance markers or surrogate mark- teins’ expression are changed in the infection. We now have the opport- ers for resistance is available, it may pathogen upon infection provides unity to look deeper into the infective impact on the selection of the drug for additional targets for antimicrobial process and find other points at which therapy. Specific examples would be chemotherapy. Knowing that same to stop the pathogen. It is a tremen- the point mutations in key topoiso- information for the host offers dously exciting time to be working in merase loci associated with quinolone additional targets that can be assessed anti-infectives: the promise is con- resistance or the presence of the mec to help the host fight off an infection, siderable, and the goal the best poss- region or an ermB-bearing transposon. eg by regulating the innate immune ible: saving millions of lives. Another example would be type and response or blocking inappropriate expression levels of ␤-lactamases or inflammation. This knowledge will DUALITY OF INTEREST drug efflux pumps. A ‘profile’ of resist- occur first in the laboratory, and the None declared. ant or resistance-prone strains may be hunt for correlations will take time. ascertained, and this profile could Once correlations are established, emerge as predictive of the chance of though, there are two immediate Correspondence should be sent to resistance emergence in a particular paths available: screening to identify DB Davison, Bioinformatics, HW3-0.07, Bristol- Myers Squibb Pharmaceutical Research pathogen population. A pharmaco- agents to stop the infection and devel- Institute, 311 Pennington-Rocky Hill Road, genomics analysis of gene expression opment of rapid, highly specific diag- Pennington, NJ 08534, USA. of a pathogen may provide a predictive nostics to assess the pathogen popu- Tel: +1 609 818 4224 outcome on therapy. At present, the lation. Fax: +1 609 818 3100 methods are too costly and time con- Genomics, pharmacogenomics, and E-mail: Daniel.DavisonȰbms.com suming to contemplate this for routine proteomics are technologies that offer analysis. However, it is not too early tremendous promise in anti-infective 1 Peet NP, Bey P. Drug Discov Today 2001; to begin to devise methods and gather drug discovery. The key to pro- 6: 495–498. data on these questions. ductively using these technologies is 2 Wieczorek SJ, Tsongalis GJ. Clin Chim Acta Pharmacogenomics offers the to think beyond the current research 2001; 308:1–8. opportunity to exploit knowledge of paradigm ie, identify a compound that 3 Schmitz G et al. Clin Chim Acta 2001; the change in mRNA expression and kills or prevents the infective agent 308:43–53. the change in protein expression in from growing. Instead, these techno- 4 Stephenson J. JAMA 2001; 286: 1441– response to a novel antimicrobial logies give us the potential for tens, if 1442. 5 Dietrich WF. Curr Biol 2001; 11: 1503– agent. These changes in expression not hundreds, of novel anti-infective 1511. can be in the host, in the pathogen, targets—from the pathogen’s gene 6 Martinez JL, Baquero F. Antimicrob Agents or even in an intermediary commensal regulation and expression in response Chemother 2000; 44: 1771–1777. organism (Figure 1). Knowing what to therapy, to the host’s gene regu- 7 Oliver A et al. Science 2000; 289: 391– genes are turned on, or which pro- lation and expression in response to 392.

important in common disease, in vari- The HUGO Mutation Database ation in drug metabolism and as mark- ers in linkage studies. When one con- Initiative siders single base changes in the 3 ϫ 109 bases and that each of these can RGH Cotton1,2 and O Horaitis1 on behalf of the HUGO change to one of three others, there Mutation Database Initiative are potentially 9 ϫ 109 base changes possible (without insertions or 1Genomic Disorders Research Centre, St Vincent’s Hospital Melbourne, Fitzroy, deletions). Thus it is clear that there Australia; 2The University of Melbourne, Department of Medicine, Melbourne, Australia are likely to be at least tens of millions of base changes that are important to human health. In the case of single The Pharmacogenomics Journal (2002) 2, mutations causing single gene dis- gene disorders, each mutational event 16–19. DOI: 10.1038/sj/tpj/6500070 orders if mutations in all genes cause needs to be characterized by at least 10 disease. A more conservative figure is 3 extra pieces of data, ideally more like The human genome has somewhere ϫ 106. If we consider also non-disease 50,2 whereas polymorphisms perhaps around 30000 genes.1 If we consider causing polymorphisms that are need less. This means that there are at that some genes such as cystic fibrosis thought to occur every 200–1000 bases least hundreds of millions of pieces of have nearly 1000 mutations causing in the 3 ϫ 109 genome, we arrive at 3– data that are needed to fully record this rare inherited disorder, it is poss- 15 million possible polymorphisms. In variation in the human genome. This ible that there may be up to 30 ϫ 106 the case of polymorphisms these are is only one order of magnitude less

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