Many human diseases, such as tobacco and alcohol addictions, are inheritable. Until now, little has been known about what genetic factors contribute to these addictions, and if they put people at risk of other medical conditions. A new study, published in Nature Genetics, reveals that these addictions result from a complex blend of genes and environmental influences, and are genetically correlated to other health issues and diseases.
More than 100 international scientists, including researchers from the Penn State College of Medicine, conducted a genome-wide association study (GWAS) to examine genetic factors linked to tobacco and alcohol addiction.
For this study, the GWAS and the Sequencing Consortium of Alcohol and Nicotine Use (GSCAN) examined data from nearly 1.2 million individuals, including data from biobanks and direct-to-consumer genetic testing companies, such as 23andMe.
Researchers analyzed an array of phenotypes, or characteristics, related to individuals’ smoking and drinking behaviors, including at what age they started, how many cigarettes they smoke and how often they consume alcohol. Next, the findings were compared to data on participants’ overall wellness, history of disease and life events. According to the results, phenotypes associated with smoking are positively genetically correlated with several diseases. Meanwhile, an increased genetic risk for drinking is associated with a lower risk for many diseases.
According to the study, there are more than 400 locations in the genome and more than 500 variants within these locations that influence smoking or alcohol use. These variants impact several chemical functions related to glutamate transmission, dopamine, and acetylcholine.
“This research shows the power that big data can have in modern-day, large-scale genetic studies. Now, through innovative computational methods, we can provide a list of potential causal genetic variants that influence people’s likelihood of developing smoking and drinking addictions. Such discoveries will pave the way for more in-depth biological analyses of substance use behaviors in humans,” says Dr. Dajiang Liu, associate professor in public health sciences from Penn State College of Medicine, a co-leader of the project.
Joining Dr. Liu from Penn State were Ms. Yu Jiang, a biostatistics graduate student and lead analyst for the project, along with research scholar Dr. Fang Chen and Daniel McGuire, a research assistant and PhD candidate in biostatistics.