The consumption of alcohol or tobacco are behaviours that are affected by multiple biological, psychological and social factors. At the biological level, part of the predisposition to consumption is due to the existence of multiple genetic variants of very small effect distributed throughout the genome. In recent years, a large number of population biobanks have been created that include biological samples, clinical information and information on lifestyle habits, with the aim of advancing precision medicine. Given their impact on health, variables related to alcohol and tobacco consumption are routinely included in these biobanks. 

The present work makes use of this information to identify genetic variants associated with the number of alcoholic drinks consumed per week and a series of tobacco-related behaviours, such as being a regular smoker, age of onset of regular tobacco use, number of cigarettes smoked per day or having managed to quit smoking after regular consumption. As is usual in medical genetics studies, the work is the result of a collaboration of a multitude of researchers from dozens of institutions in different countries grouped in a consortium, in this case, the GSCAN. This consortium had published a similar study with a much smaller number of samples in 2019. Compared to that study, it went from analysing 1.2 million individuals to 3.4 million. As a result, the number of genetic variants identified increased considerably, from 566 to more than 3,800 in the current study. 

Perhaps the most important thing about the study is that, as is usually the case in medical genetics, the main results are freely available for any researcher to make use of. The study can therefore be seen as a starting point on which a large number of further analyses will be carried out to better understand the biological factors involved in tobacco and alcohol consumption, as well as their consequences. In this sense, this work already presents analyses that show that many of the genetic variants identified do so through cell types involved in the brain's reward system (in accordance with the mechanisms proposed for addictions). 

The joint effect of the different genetic variants identified explains an appreciable part of the existing variation at the population level. For example, individuals in the top 10% of genetic predisposition to tobacco use smoke on average twice as many cigarettes per day as those in the bottom 10% of predisposition (14 cigarettes versus 7). However, there is a problem in medical genetics related to a very high representation of people of European origin (most biobanks are European or from the United States). As a consequence, the variability explained by genetic predisposition estimates is much lower in populations of other geographical origin. 

This work, by pooling such a large number of individual samples, did manage to carry out a series of pioneering studies in relation to the different effect that the genetic variants identified may have on different populations, depending on their geographical origin. Despite the different cultural contexts, most of the identified genetic variants have similar effects regardless of the ancestry or geographical origin of the subjects analysed. The few variants that are clearly affected by ancestry (less than 5%) may provide new clues about cultural influences on alcohol and tobacco consumption (gene-environment interaction). 

The main limitation of the work is the definition of the traits under study, which are generally self-reported and not very specific. For example, two very different patterns of alcohol consumption, such as regular drinking with meals or weekly binge drinking, may result in the same number of alcoholic drinks consumed per week. It is also known that people with health problems tend to under-report their alcohol and tobacco consumption. 

In summary, the present work has generated a set of genetic information of great value for a better understanding of the mechanisms of genetic predisposition to alcohol and tobacco consumption, as well as their consequences. Given the impact of these substances on health, this information is likely to be of great relevance in the future, in line with precision medicine.