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A GWAS study of almost 3.4 million people with multiple ancestry has uncovered more than 3,800 genetic variants potentially associated with smoking and alcohol use. The subjects had African, American, East Asian, and European ancestry.

The study appeared in Nature this week and was led by Scott Vrieze, Department of Psychology, University of Minnesota, Minneapolis, and Dajiang Liu, a statistical geneticist at Penn State College of Medicine in Hershey, Pennsylvania.

The team identified 3,823 genetic variants that were associated with smoking or drinking behaviors. Thirty-nine of these were linked with the age at which individuals started smoking, 243 with the number of cigarettes smoked per day and 849 with the number of alcoholic drinks consumed per week.

Tobacco and alcohol use are associated with many worldwide deaths—annually in the U.S., smoking causes one-in-five deaths while alcohol is related to five percent of deaths. These traits are known to be heritable and are common across the globe. But, so far the genetics of these traits has been hard to unravel, since they appear to be complex and have strong environmental influences.

Genome-wide association studies have looked at this topic, but until now, most have focused largely on individuals of European ancestries. A 2017 GWAS study of alcohol consumption using the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort, included four race/ethnicity groups: non-Hispanic whites, Hispanic/Latinos, East Asians and African Americans. That team found that different variants were more likely to be found among certain groups. 

This team aimed to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to clarify function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations.

They write,” We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions.”

Adding that, “However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.”

Of the variants they found, 721 were identified only by the multi-ancestry GWAS, and not by an ancestry-naive model the authors developed for comparison. The researchers also found similar heritability estimates of these traits across the populations, and that the majority of genetic associations for drinking and smoking.

Such studies may also help researchers better understand addiction, which is a growing problem in society.  The use of GWAS is becoming increasingly common in this field.  Researchers at Yale recently used the technique to find 18 new variants linked to opioid use disorder.

In 2019, Hancock et al. reported that, “With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward.” They reported replicable GWAS findings spanning 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined. Adding that, “GWAS have discovered several novel, replicable variants contributing to addiction.”

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