Subtle Changes In Brain Receptor Gene May Have Significant Consequences For Addiction

"These findings are potentially very important because of the high frequency of two versions, or alleles, of this gene in the general population," says co-senior author Mary Jeanne Kreek, M.D., professor and head of the Laboratory on the Biology of Addictive Diseases at Rockefeller. "We have defined alterations in the function of one allele studied for both binding and activity."

"These interesting pre-clinical findings present a very important target for additional research into what makes people vulnerable to addictive diseases," says Alan I. Leshner, Ph.D., director of the National Institute on Drug Abuse (NIDA) of the National Institutes of Health, which funded part of the study.

The scientists studied variations in the DNA sequence of the mu opioid receptor gene called single-nucleotide polymorphisms (SNPs). The double-helical structure of DNA comprises four building blocks called nucleotides, represented by the letters A, T, G and C. The nucleotides pair-A with T, G with C-to form limitless combinations along the double helix. SNPs derive from single differences in the base pairing, which may produce changes in the protein products of the gene.

The mu opioid receptor system plays a key role in the body, including pain management, the stress response, normal gastrointestinal function and the immune system.

The researchers extracted DNA from blood samples taken from 152 unrelated subjects. Of these, 113 were long-term heroin addicts enrolled in methadone maintenance programs, and 39 had no history of drug or alcohol dependence. Study subjects included 69 females and 83 males. The ethnic breakdown of the study subjects was 31 African-American, 52 Caucasian, 67 Hispanic, 1 Native North American and 1 multiethnic.

Using molecular cloning techniques and polymerase chain reaction, the scientists identified five SNPs of the mu opioid receptor gene in the coding region. Two of the SNPs were identified previously by researchers at other institutions, but the other three are described for the first time in this paper.

The two most prevalent SNPs, called A118G and C17T, were found in 10.5 and 6.6 percent of sample, respectively. For A118G, the researchers found no significant difference in frequencies between opioid-dependent and non-opioid-dependent subjects when all ethnic groups were combined. However, within the Hispanic study subject group, A118G was present in a significantly higher percentage of subjects with no history of opioid dependency.

"We think that this finding suggests that A118G may confer a relative protection against opioid dependency in that population," says Kreek.

The researchers also found that C17T was present in higher overall proportion of opioid-dependent persons in the study sample, confirming a previous result by one other researcher.

The researchers also conducted binding studies using the A118G SNP or the most common mu variant in cultured cell lines. They determined that A118G had a threefold greater binding with beta-endorphin than the usual mu opioid receptor. beta-endorphin, a naturally occurring opioid peptide, plays a role in diverse biological functions, including the nervous system, stress response and in addictive diseases.

"The approximately threefold greater binding of beta-endorphin suggests that individuals carrying A118G may show differences in some of the functions mediated by beta-endorphin action at the altered mu opioid receptors," says Kreek. "Thus, for example, response to stress, reproductive function and pain perception could be altered. Moreover, subtle changes could have significant effects on the susceptibility or vulnerability to develop mulitfactorial diseases, such as specific addictions."

Kreek's senior co-author on the paper is Lei Yu, professor at the University of Cincinnati College of Medicine. Kreek's and Yu's co-authors are molecular biologists K. Steven LaForge, James Schluger and Lisa Borg, and registered nurse Dorothy Melia in the Laboratory on the Biology of Addictive Diseases at Rockefeller; Suzanne M. Leal, assistant professor in the Laboratory of Statistical Genetics at Rockefeller; molecular biologist Cherie Bond, molecular neurobiologist Mingting Tian and Jay A. Tischfield, professor, at Indiana University School of Medicine; and graduate student Shengwang Zhang, molecular biologist Jianhua Gong, and electrophysiologist Judith A. Strong, research associate professor at University of Cincinnati College of Medicine.

This research was supported in part by NIDA and the National Human Genome Research Institute, both part of the federal government's National Institutes of Health (NIH) and by a General Clinical Research Center grant from the National Center for Research Resources at NIH.