Toward genetic rationalization of antiretroviral therapy for HIV

Daar et al. ^[1] have extended the observations of Barbour et al. ^[2] on the correlation between disease progression and standardized HIV polymerase activity in vitro. Polymerase thus joins accessory genes (nef ^[3,4], rev, tat, vif, vpr, vpu, reviewed in ^[5]), as well as tropism-determining envelope ^[6,7], as a potentially useful prognostic marker for disease progression and treatment initiation, albeit one that must be functionally assayed (like envelope tropism) rather than genetically screened. For treatment-experienced patients, reverse transcriptase and protease are already widely monitored for mutations predictive of drug resistance (reviewed ^[8,9]). Thus, Daar et al. ^[1] provide one more step toward the individualization of antiretroviral therapy (ART) by fine tuning decisions made in the context of CD4 cell counts, viremia, and drug resistance.

Current Department of Health and Human Services (DHHS) guidelines for initiation of ART ^[9] state The optimal time to initiate antiretroviral therapy among asymptomatic patients with CD4+ T cell counts >200 cells/mm³ is unknown. For these patients, the strength of the recommendation for therapy must balance other considerations, such as patient readiness for treatment and potential drug toxicities. For patients with >350 × 10⁶ CD4 T cells/l, treatment is not recommended for viral loads <100 000 copies/ml (recently revised upward from 55 000 copies/ml). We suggest that polymerase replicative capacity (RC) described by Daar et al. ^[1] should figure among the other considerations alluded to.

Rational ART could be further advanced by integrating viral determinants of progression with haplotyping of host AIDS resistance genes (ARG). To date, these include heterozygosity for HLA Class I alleles and presence of HLA B57.01 or B27.01 (reviewed in ^[10-12]), heterozygosity for ΔC32 in the CCR5 open reading frame ^[13-15], the 64I mutation in the CCR2 promoter region ^[16], the 3′A SDF1 variant ^[17], and others (reviewed in ^[18,19]), including, most recently, increased CCL3L1 (MIP-1β) gene copy number ^[20], all conferring protection in some racial or ethnic groups, based on cohort studies showing inverse correlation with disease progression, when analyzed as independent variables. Additionally, several deleterious alleles have been documented, including 5′A for the interleukin-10 gene ^[21], 179T for interferon-γ ^[22], and 186R in the structural region of APOBEC3G among African-Americans ^[23] but not French Europeans ^[24]. Other potentially interesting polymorphic loci (e.g., Cul5, TRIM5a) await clinical validation in cohort studies in various ethnic populations. More are likely to be discovered.

Known ARG alleles vary dramatically in their frequencies among various ethnic populations, and their protective or deleterious impact can be strongly influenced by background host genetics. Moreover, some alleles may exert their effects disproportionately in the early stages of disease. While the Daar study ^[1] was not designed to address questions of the impact of host genetics or disease stage, it is likely that these will both be found to influence the relative risk attributable to pol gene RC, and allow for predictive stratification when these factors are defined for a given cohort.

Individually tailored ART is a desirable goal for developed countries, but can viral and host profiling be made relevant to treatment decisions in the setting of severely limited resources, where cost-effective public health policy, rather than individualized therapy, must be the dominant concern? Considering the question only for pol RC from a narrowly limited scientific perspective, it may be necessary to demonstrate the same clinical correlation for non-B clade viruses in specific ethnic populations. Multiple factors may impact on this relationship, including the circulating HIV strains, strength of immune response to HIV proteins (including polymerase), host ARG, and coexisting pathogens. Lower CD4 cell counts and percentages among African and Asian uninfected controls, as well as presenting patients may also perturb correlations.

But larger practical problems dwarf scientific considerations, and severely restrict the ways in which predictive profiling can be used. Clinical and laboratory data on the natural history of HIV disease among the poorest populations are limited; most infected individuals are not diagnosed until symptomatic-too late for decisions about when to initiate treatment. Then, CD4 cell counts and viral loads may be unavailable, or available with insufficient frequency to serve as monitoring parameters. Thus, the relevance of even the rough DHHS guidelines for various African and Asian populations remains unclear. Indeed, World Health Organization treatment guidelines state only that infected adolescents and adults should start ART when they have clinical AIDS, and that all HIV infected people with less than 200 CD4 cells/mm³ should be offered treatment.

Assuming an optimistic scenario of increasing availability of diagnostic testing, counseling, and ART in the developing world, but a continuing absence of technology, trained personnel, and funding for laboratory monitoring of patients, it may be possible to improve treatment guidelines. For example, the pol RC assay, performed with multiple natural isolates from geographically and cladistically defined regions, would give an initial indication of where circulating strains fall along the >1 log spectrum noted by Daar et al. for North American Clade B isolates ^[1]. While this would not guarantee comparably significant correlations with disease progression, it would be a start in assessing one aspect of relative virulence among circulating strains.

Next, allelic distribution among target populations could be determined for multiple host ARG. The relative frequencies of deleterious alleles and selected haplotypes among a representative sample of donors could generate useful population profiles. After weighting the various deleterious and protective alleles by relative risk, an average risk score for the overall target population and representative HIV strains (e.g., women in a large squatters' town or refugee camp, injecting drug users seen in regional clinics) could be generated, based on frequency of alleles or, preferably, frequencies of various risk-weighted, stratified haplotypes (which would better capture any linkage disequilibrium). These average population-virus scores (updated yearly) could, in turn, inform guidelines for treatment initiation among these populations. Early screening, counseling, and identification of high risk individuals are keys to this approach, as is the monitoring of treated and treatment naive HIV-positive cohorts from representative ethnic groups.