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Interactions Between Drugs of Abuse and Pharmacotherapeutics Used in the
Treatment of Infections, Drug Abuse, and Mental Disorders

3rd International Workshop on Clinical Pharmacology of HIV Therapy


Pharmacogenomics of Antiretrovirals and Drugs of Abuse Interactions

Thomas Kakuda, PharmD
Abbott Laboratories

Pharmacogenomics-the study of genetic correlates that may explain individual differences in treatment response-has attracted the attention of HIV pharmacologists seeking to explain variable responses to antiretrovirals. The ultimate goal of such research, Dr. Kakuda proposed, is "predictive medicine": using genetic testing to predict predisposition to specific diseases or variations in response to therapy. Simply put, pharmacogenomics may improve the odds of "therapy with the right drug, at the right dose, in the right patient."

Genetic polymorphisms may affect both the pharmacokinetics and pharmacodynamics of a given drug. Alone or combined, such polymorphisms produce heterogeneity in the therapeutic response. Foe example, a recent study demonstrated the frequency of mutant for six drug metabolizing enzymes from a large ethnically diverse population [1].

Genetic polymorphisms also affect drug receptor targets for numerous pharmaceutical agents, including:

  • ACE inhibitors
  • Antiretrovirals
  • Beta agonists
  • Chemotherapeutic agents
  • Estrogen
  • Tacrine

Pharmacogenomics and drugs of abuse

Opiate addiction is a genetically complex disease. Although a large number of genes are associated with opiate addiction, phenotype is not dependent on genotype. Dr. Kakuda listed the following genetic correlates from a recent study:

Genetic correlates of opiate dependence

Gene Protein Results
CYP2D6 Cytochrome Protective effect of homozygous deletion
DRD2-4 Dopamine receptor Dependence associated with DRD4 allele 7 and DRD2 alleles A1 and B1
SLC6A4 Solute carrier Dependence associated with allele 10

Source: Lichtermann D et al [2].

Dr. Kakuda cited estimates that 40% to 60% of alcoholism is attributable to genetics. At the same time, excessive drinking correlates closely with gender and age:

Percentage of alcoholics by gender and age

Age Men (%) Women (%)
18 to 24 24 8.6
25 to 44 19.3 4.8
45 to 64 12.7 2.0
65+ 2.9 0.4

In addition, the genetics of alcohol metabolism vary by ethnic group. The metabolic process can be described as:

ADH ALDH
EtOH Æ acetaldehyde Æ acetate

Among Israeli Jews, a polymorphism in alcohol dehyrogenase (ADH2 R47H) increases formation of acetaldehyde, the compound that causes toxic reactions to alcohol [3]. Another pathway that leads to alcohol toxicity is impairment of aldehyde dehydrogenase (ALDH). The prevalence of the mutant allele (ALDH2 G487K) is ~30% among Chinese and Japanese. Because this mutant allele is dominant, heterozygotes have similar expression as homozygote mutant leading to impaired ALDH in almost half of the Chinese and Japanese population. Partly because Chinese and Japanese have such a high risk of delayed acetaldehyde metabolism, the risk of alcoholism among them has been estimated as 4- to 10-fold lower than in other populations.

Amphetamine derivatives such as MDMA ("ecstasy"), MDA ("love pills"), and MDE ("Eve") have become popular recreational drugs among some people with or at risk for HIV infection. Their interactions with antiretrovirals remain poorly characterized but case reports of fatal interactions with protease inhibitors have been documented. One randomized, double-blind, crossover study of 8 people receiving 75 of 125 mg of MDMA determined that MDMA has non-linear kinetics and that the CYP2D6 genotype (see first table above) is not associated with MDMA metabolism [4].

Cannabinoids, taken as an appetite stimulant by some people with HIV infection, are metabolized by CYP2C and CYP3A4 isoforms. But a recent study found that marijuana cigarettes and dronabinol have little effect on protease inhibitor concentrations [5].

HLA haplotype and antiretrovirals

Two recent studies associated specific HLA haplotypes with hypersensitivity to the nucleoside analog abacavir. The studies are instructive in suggesting the effect of genetic diversity on antiretroviral toxicity. A study of the Western Australia HIV Cohort linked abacavir hypersensitivity to three haplotypes with a positive predictive value of 100% and a negative predictive value of 97% [6].

HLA typing in a North American population taking abacavir found that 39 (46%) of those with hypersensitivity reactions were HLA-B57 positive [7]. Although that rate was much higher than the 4% of abacavir-tolerant people who were HLA-B57 positive, the association with hypersensitivity is much weaker than in the Australian cohort. Dr. Kakuda speculated that the Australian cohort might be much less genetically heterogeneous than the North American cohort and that the utility of HLA typing for abacavir is currently unwarranted.

A separate study by the Australian researchers found that certain HLA haplotypes independently increased or decreased the risk of eight reverse transcriptase-associated resistance mutations and seven protease-associated mutations [8].

Conclusions

Dr. Kakuda outlined the following genetic determinants in HIV disease:

Disease susceptibility or progression

  • Chemokines (RANTES)
  • Chemokine receptors
  • HLA polymorphisms (B*35)
  • IL-4 589T polymorphism

Response to drugs

  • CYP2D6
  • HLA-B*5701 (abacavir hypersensitivity)
  • MDR1
  • SREPB-1 (hyperlipidemia)

(Adapted from Telenti A, Aubert V, Spertini F. Individualizing HIV treatment-pharmacogenetics and immunogenetics. Lancet 2002; 359: 722-723)

Dr. Kakuda concluded that pharmacogenomics is an emerging discipline applicable to all drugs and diseases. Ultimately, pharmacogenomic research could greatly enhance individualized approaches to drug therapy. He predicted that high-throughput microarrays might eventually provide simple and quick results. But cost and availability are likely to remain important issues.

References

  1. Wilson JF, Weale ME, Smith AC, et al. Population genetic structure of variable drug response. Nat Genetics 2001;29:265-269.

  2. Lichtermann D, Franke P, Maier W, Rao ML. Pharmacogenomics and addiction to opiates. Eur J Pharmacol 2000;410:269-279.

  3. Radel M, Goldman D. Pharmacogenetics of alcohol response and alcoholism: the interplay of genes and environmental factors in thresholds for alcoholism. Drug Metab Dispos 2001;29(4 pt 2):489-494.

  4. de la Torre R, Farre M, Ortuno J, et al. Non-linear pharmacokinetics of MDMA ('ecstasy') in humans. Br J Clin Pharmacol 2000;49:104-109.

  5. Kosel BW, Aweeka FT, Benowitz NL, et al. The effects of cannabinoids on the pharmacokinetics of indinavir and nelfinavir. AIDS 2002;16:543-550.

  6. Mallal S, Nolan D, Witt C, et al. Association between the presence of HLA-B*5701, HLA-DR7, and HLA-DQ3 and hypersensitivity to HIV-1 reverse-transcriptase inhibitor abacavir. Lancet 2002;359:727-732.

  7. Hetherington S, Hughes AR, Mosteller M, et al. Genetic variations in HLA-B region and hypersensitivity to abacavir. Lancet 2002;359:1121-1122.

  8. Moore C, John M, James I, Mallal S. The influence of host HLA on antiretroviral drug resistance mutation in HIV-1. 9th Conference on Retroviruses and Opportunistic Infections. February 24-28, 2002, Seattle. Abstract 554.

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