Scientists Find Genes That Influence Brain Wave Patterns

Brain wave patterns may be a surrogate marker for genetic susceptibility to alcoholism.

NIAAA scientists have identified new genes and pathways that influence an individual’s typical pattern of brain electrical activity, a trait that may serve as a useful surrogate marker for more genetically complex traits and diseases. One of the genes, for example, was found to be associated with alcoholism. The report appears in the May 2010 issue of the Proceedings of the National Academy of Sciences.

The researchers used genome-wide association studies (GWAS)—techniques that involve scanning the complete set of DNA of many individuals—to search for genetic variants related to electroencephalogram (EEG), or brain wave, patterns in a sample of more than 300 Native American individuals. EEG patterns are highly heritable and have been associated with alcoholism and other psychiatric disorders. The researchers identified multiple genes that were associated with the amplitude, or height, of two of the four characteristic electrical frequencies that make up the wave patterns found in EEG recordings.

One of the genes identified in the study was found to account for nearly 9 percent of the EEG theta wave variability seen in the Native American sample. Theta waves are relatively low-frequency brain waves; previous studies have shown that their amplitude is altered among alcoholics. The researchers then showed that the same gene accounted for about 4 percent of theta wave variability in a sample of North American whites. In the same study, researchers showed that genetic variation in one of the genes identified for theta wave variability was also associated with an altered risk for alcoholism.

“While our main findings are for genes that influence EEG wave patterns, this study represents an important step towards the use of EEG as a surrogate marker for alcoholism,” notes David Goldman, M.D., chief of the NIAAA Laboratory of Neurogenetics and an author on the paper. “It also reveals new molecular pathways involved in addiction processes.”

The article abstract can be found here:
Genome-wide Association Identifies Candidate Genes That Influence the Human Electroencephalogram.