2,300 genes that predict alcohol and tobacco use

A large genetic study analyzed data from over 3.4 million people and identified over 2,300 genes that predict alcohol and tobacco use.

Most of these genes were similar among people of European, African, American and Asian ancestry.

alcohol and tobacco use are associated with approximately 15% and 5% of deaths worldwide, respectively, and are associated with chronic diseases such as cancer and heart disease. Environment and culture can influence an individual’s use and susceptibility to becoming addicted to these substances, but genetics is also a factor, according to researchers at the Pennsylvania State University of Medicine. A research study helped identify about 400 genes associated with specific alcohol and tobacco use behaviors in people.

“We have now identified more than 1,900 additional genes associated with alcohol and tobacco use behavior,” said Dajiang Liu, research professor and vice chair of the Department of Public Health Sciences. “His one-fifth of the samples used in our analysis were from non-European ancestry, adding to the relevance of these findings to diverse populations.”

Working with colleagues at the University of Minnesota and over 100 other institutions, Liu and team evaluated genetic datasets of more than 3.4 million people, at least 20% of whom were of non-European ancestry. According to Liu, their study is the largest genetic study of smoking and drinking behavior to date and has the highest ancestral diversity. He says his previous study in 2019 only included data from populations of European ancestry.

Liu et al. included genetic datasets from African, East Asian, and American ancestry to characterize a range of smoking and alcohol characteristics, ranging from initiation of drinking or smoking to initiation and consumption of regular use. Using machine learning techniques, researchers identified genes associated with these behaviors.

Comparing data between samples from different ancestry, Liu and colleagues found striking similarities in genes associated with alcohol and tobacco use behavior among different ancestry, with 80% of the variants studied. showed consistent effects across populations. Although some genetic variants had differential or ancestral-specific effects among ancestry, genes associated with alcohol and tobacco use were largely concordant across samples of different ancestry. rice field.

Researchers have used machine learning to develop a genetic risk score that can identify people at risk for specific alcohol and tobacco use behaviors. Despite similarities in genetic influences, models developed using data from individuals of European ancestry were only able to accurately predict alcohol and tobacco use behavior in people of European ancestry. The model was not very accurate in predicting risk for people of other ancestry, so sample sizes from non-European ancestry should be increased to develop more sophisticated prediction methods, Liu said. said.The results will be published in the journal today Nature.

Liu, a researcher at the Pennsylvania State Cancer Institute, said: “Having more robust and diverse data will help us develop predictive risk factor tools applicable to all populations.”

According to Liu, within two to three years, these genetic risk scores will improve and the routine care of individuals already identified as being at high risk for alcohol and tobacco use through basic screening. may become part.

Future research will focus on digging deeper into their findings, Liu said. Because most of the genes the team identified have unknown functions, researchers need to understand their functions and how their alterations, functions, and interactions with the environment might contribute to the risk of addiction behavior. He also says that increasing the diversity of the genetic samples in the dataset will help the team develop predictive risk models for individuals from diverse ancestry. .

The Biomedical Informatics and Artificial Intelligence Program at the National Institutes of Health and Pennsylvania State Medical College supported this research. Opinions expressed are solely those of the researchers and do not necessarily reflect the views of the sponsor. Additional acknowledgments are in the manuscript.

sauce: Pennsylvania