With the Advent of “Personalized Addiction Medicine” We May Be Going to the Promised Land—I’ll Take You There!

We are entering an era of genomic medicine and neuroimaging as they relate to addiction, a subset of Reward Deficiency Syndrome (RDS) (Blum & Badgaiyan, 2015). Previously we have discussed the importance of providing a common rubric to identify all addictive behaviors drug and non-drug related and potential genetic antecedents (Blum et al., 1996). Globally there is a fight against iatrogenic opioid dependence (Blum et al., 2013). Keeping this in mind there is a current need for early diagnosis through genetic testing and the incorporation of inducing “dopamine homeostasis” for long-term therapy. The current approved Food and Drug Administration (FDA) list for the treatment of alcoholism, heroin dependence, and smoking cessation favors the blocking of dopamine release at the reward center in the brain (Volkow, Frieden, Hyde, & Cha, 2014). However, it can be argued that by doing so in the long term, the brain is being hijacked of its required dopamine supply, and this in turn can lead to mood changes including suicide ideation. By understanding this conundrum can we find a better solution, providing real recovery, eliminating unnatural “white knuckle sobriety” (Frank & Jaén, 1993).

 

In 2005 my laboratory received the first patent in the United States on Nutrigenomics and RDS treatment. This was awarded on the basis of earlier work showing anti-addiction activity of a nutraceutical consisting of amino-acid precursors and enkephalinase inhibition properties and our discovery of the first polymorphic gene (Dopamine D2 Receptor Gene [DRD2]) associated with severe alcoholism (Blum et al., 1990).

 

Prior to the more recent genetic finding, we had developed the concept of Brain Reward Cascade (BRC), which continues to act as blueprint for stratification of addiction risk through neurogentics (Blum & Kozlowski, 1990). As discussed earlier, in 1996 our laboratory also coined the term “Reward Deficiency Syndrome” (RDS) to define a common genetic rubric for both substance and non-substance related addictive behaviors (Blum & Badgaiyan, 2015). Following many reiterations we utilized polymorphic targets of a number of reward genes (serotonergic, Opioidergic, GABAergic and Dopaminergic) to customize KB220 [Neuroadaptogen- amino-acid therapy (NAAT)] by specific algorithms.

 

Identifying 1,000 obese subjects in the Netherlands, a subsequent small subset was administered various KB220 formulae customized according to respective DNA polymorphisms (e.g., serotonin genetic deficits signaled increases in tryptophan, etc.). Individualized dopamine agonist nutrigenomics was utilized differentially for each subject. This novel approach translated to significant decreases in both body mass index (BMI) and weight (Blum et al., 2008b). This approach was followed up in the U.S. with similar significant effects (Blum et al., 2008a; Blum et al., 2008c).

 

Following these experiments we have been successfully developing a panel of genes known as “Genetic Addiction Risk Score” (GARSDX).™ When we selected 10 genes with appropriate variants, a statistically significant association between the ASI-MV (Addiction Severity Index-Multimedia Version, an online, interactive version of the ASI) alcohol and drug severity scores and GARSDx was found. This association was found in 273 patients attending seven diverse treatment centers.

 

Independently, the effects of a variant of NAAT-KB220Z was observed in abstinent heroin addicts showing a remarkably increased resting state functional connectivity in a putative network that included the dorsal anterior cingulate, medial frontal gyrus, nucleus accumbens, posterior cingulate, occipital cortical areas, and cerebellum (Blum et al., 2014). In other as yet unpublished laboratory work we show that KB220Z significantly activates, more than a placebo, seed regions of interest including the left nucleus accumbens, cingulate gyrus, anterior thalamic nuclei, hippocampus, pre-limbic, and infra-limbic loci. This response induced by KB220Z demonstrates significant functional connectivity, increased brain volume recruitment, and enhanced dopaminergic functionality across the brain reward circuitry. This robust yet selective response implies clinical relevance.

 

Considering the frequency of prescribing highly addictive opioid pain medications to the large number of individuals presenting to pain clinics, and the subsequent induction of iatrogenic legal addiction to, for example OxyContin®, we must find better solutions. Indeed, initial genetic screening should help identify potential at-risk individuals, providing possible alternatives to treatment (Volkow, Frieden, Hyde, & Cha, 2014).

 

We are now poised to propose a Reward Deficiency System Solution™ that promotes early identification and stratification of risk alleles by utilizing GARSDx, allowing for customized nutrigenomic targeting of these risk alleles by altering NAAT ingredients as an algorithmic function of carrying these polymorphic DNA–SNPS as well as brain electrotherapy, potentially yielding the first ever nutrigenomic solution for addiction and pain (Blum, Oscar-Berman, Demetrovics, Barh, & Gold, 2014). While we are not in the promised land of personalized medicine and addiction treatment yet, I am convinced that through sophisticated research we will indeed get there.

 

References

Blum, K., & Badgaiyan, R. D. (2015). Reward Deficiency Syndrome (RDS): Entering the genomic and neuroscience era of addiction. Journal of Reward Deficiency Syndrome, 1(1), 1-2.

 

Blum, K., Chen, A. L., Chen, T. J., Rhoades, P., Prihoda, T. J., Downs, B. W., … Palomo, T. (2008a). LG839: Anti-obesity effects and polymorphic gene correlates of reward deficiency syndrome. Advances in Therapy, 25, 894–913.

 

Blum, K., Chen, T. J., Chen, A. L., Rhoades, P., Prihoda, T. J., Downs, B.W., … Reinking, J. (2008b). Dopamine D2 Receptor Taq A1 allele predicts treatment compliance of LG839 in a subset analysis of a pilot study in The Netherlands. Gene Therapy and Molecular Biology,

12, 129–140.

 

Blum, K., Chen, T. J. H., Williams, L., Chen, A. L. C., Downs, B. W., Waite, R. L., … Braverman, E. R. (2008c). A short-term pilot open label study to evaluate efficacy and safety of LG839, a customized DNA directed nutraceutical in obesity: Exploring nutrigenomics. Gene Therapy and Molecular Biology, 112, 371-382.

 

Blum, K., & Kozlowski, G. P. (1990). Ethanol and neuromodulator interactions: A cascade model of reward. In H. Ollat, S. Parvez, & H. Parvez (Eds.), Alcohol and Behavior (pp. 131-149). Utrecht, The Netherlands: VSP Press.

 

Blum, K., Liu, Y., Wang, W., Wang, Y., Zhang, Y., Oscar-Berman, M., … Gold, M. S. (2015). rsfMRI effects of KB220Z™ on neural pathways in reward circuitry of abstinent genotyped heroin addicts. Postgraduate Medicine, 127(2), 232-241.

 

Blum, K., Noble, E. P., Sheridan, P. J., Montgomery, A., Ritchie, T., Jagadeeswaran, P., … Cohn, J. B. (1990). Allelic association of human dopamine D2 receptor gene in alcoholism. JAMA, 263(15), 2055-2060.

 

Blum, K., Oscar-Berman, M., Demetrovics, Z., Barh, D., Gold, M. S. (2014). Genetic Addiction Risk Score (GARS): Molecular neurogenetic evidence for predisposition to Reward Deficiency Syndrome (RDS). Molecular Neurobiology, 50(3), 765-796.

 

Blum, K., Oscar-Berman, M., Dinubile, N., Giordano, J., Braverman, E. R., Truesdell, C. E., … Badgaiyan, R. (2013). Coupling Genetic Addiction Risk Score (GARS) with electrotherapy: Fighting iatrogenic opioid dependence. Journal of Addiction Research & Therapy, 4(163), 1000163.

 

Blum, K., Sheridan, P. J., Wood, R. C., Braverman, E. R., Chen, T. J., Cull, J. G., & Comings, D. E. (1996). The D2 dopamine receptor gene as a determinant of reward deficiency syndrome. Journal of the Royal Society of Medicine, 89(7), 396-400.

 

Frank, S. H., & Jaén C. R. (1993). Office evaluation and treatment of the dependent smoker. Primary Care, 20(1), 251-268.

 

Volkow, N. D., Frieden, T. R., Hyde, P. S., & Cha, S. S. (2014). Medication-assisted therapies—tackling the opioid-overdose epidemic. New England Journal of Medicine, 370(22), 2063-2066.