Moving beyond the subjective patient history model that the addiction field currently uses in assessment and trying to add more diagnostic tools that offer a clearer snapshot of the individual, including what risk factors he or she has– that is the goal of drug testing company Dominion Diagnostics and genomics company LifeGen,Inc. as they move forward in their latest research.
The research results, which are on track to be released around April, could show that LifeGen's newly developed test is valuable in determining a patient's Genetic Addiction Risk Score (GARS), or relative predisposition to addictive behaviors.
The study will seek to validate the new test against the Addiction Severity Index (ASI) designed and marketed by Inflexxion, Inc. When both tools are used, the team will evaluate the results to determine if the data are similar or different, and what exactly that means.
Although much research is being conducted on the genes associated with addiction, Mary P. Hauser, MA, Vice President of Addiction Services at Dominion, believes this project is unique because of the comparison “to a bio-psycho-social tool that’s validated and used by a lot of the treatment centers.”
There will be useful information to put on paper; however, the target of this project is more complex. The goal is to “actually evolve into a tool that can be used effectively in the treatment of addiction and also assess the risk factor of addiction in other healthcare settings,” says Hauser.
Stratifying risk with genes
The GARS analysis is set to investigate a panel of genes primarily involved in brain reward circuitry. These “candidate genes” have been associated with aspects of addictive behavior such as cravings and relapse, according to Kenneth Blum, PhD, primary investigator for this study.
For 30% of the human population (approximately 100 million people), genetics are a large factor in dopamine-driven addiction. This subset of the population carries the dopamine D2 receptor (DRD2), which induces low dopamine brain function that results in the propensity for addictive cravings. The GARS test takes a deeper look at nine reward genes and related polymorphisms that have significant impact on substance use disorders.
Blum, who is credited with the first known association of the DRD2 with alcoholism and other addictive behaviors, hopes the GARS test will achieve two important outcomes. One— stratifying risk—will help to classify clients as low-, moderate- or high-risk.
Coupled with patient history, this classification would help guide a facility or program to the appropriate treatment for that individual. Currently in the field, Hauser says patients are evaluated and must “fail at the least restrictive level of care to obtain enhanced services.” She says the hopes are that with a high GARS score and clinical assessment, a higher level of care will be easier to defend. With a low GARS, a less restrictive setting with more psychoeducational and supportive work may be appropriate, she says.
Blum says the risk has been stratified for the first batch of samples, and the results for this group were 14% low-risk, 81% moderate-risk, and 5% high-risk.
The other side of this research involves pharmacogenomics. Blum explains that due to the variations in an individual’s genes, the effectiveness of certain medications can change. He says that some people have variations that would “eat up the drug very quickly.” He talks about this test being useful for medication monitoring because the prescriber would be able to determine specifically what the genes say about the individual’s metabolism.
Stepping outside of the addiction field, Hauser says the GARS test can provide an indication of risk factors for the prescription of analgesic medicine in chronic pain programs, and other types of pain related treatments, for example. In this situation, if the physician knows that the individual is a high-genetic risk, he or she might not be a candidate to receive analgesics, she explains.
“It certainly will help the pain field to reduce the risk that you’re going to be making addicts because they have a predisposition to drug dependence,” Blum adds.
The results gathered will help Dominion to develop a mathematical weighted algorithm that will, according to Blum, be engineered into an automatic way of printing out the possible risk factors when an individual gets his or her results.
Input from addiction professionals
Ideally, 300 to 400 patient subjects selected from addiction treatment facilities across the country will be involved in the GARS analysis. In mid-January, the team had 81 samples in-house and another 60 en route to the lab, putting the researchers over their midpoint as far as collection of samples, according to Hauser.
As for the samples being collected, Dominion has enlisted a number of medical schools and universities (external professionals with expertise in genetics) that are performing double-checks as to avoid any bias.
Both Hauser and Blum speak of a clinical decision tree that is also part of the research project. The team has developed an advisory board that is made up of academics, physicians, addiction medicine specialists and clinicians in practice. Hauser says the purpose of this board is to vet all potential concerns that any of the treatment centers might have about the security of the information, how it could be used, etc. Blum says the group addresses questions such as: What are the limitations of this test? What are the pitfalls? What are the benefits?