A team of researchers published their findings in Nature Genetics on the use of machine learning to identify drugs to help eliminate cigarette smoking habits.
Researchers used genetic data from over 1.3 million people. They established over 400 genes associated with smoking behaviors.
“In the present study, we conducted a multi-ancestry TWAS using GWASs and whole-genome sequence data from 1.3 million individuals,” the authors wrote in their article.
“Our TWAS results highlighted shared mechanisms with other substance use behaviors (for example, cocaine addiction) and psychiatric phenotypes (for example, pain sensitivity, depression and anxiety).”
“Given the tremendous public health burden that continues to be incurred by smoking, repurposing drugs for smoking cessation is extremely valuable, because it offers a potentially quicker and more cost-effective route to treatment than the development of new therapeutic targets.”