Genetic susceptibility to caffeine intake and metabolism: a systematic review.

BACKGROUND

Coffee and tea consumption account for most caffeine intake and 2-3 billion cups are taken daily around the world. Caffeine dependence is a widespread but under recognized problem.

OBJECTIVES

To conduct a systematic review on the genetic susceptibility factors affecting caffeine metabolism and caffeine reward and their association with caffeine intake.

METHODOLOGY

We conducted PubMed and Embase searches using the terms "caffeine", "reward", "gene", "polymorphism", "addiction", "dependence" and "habit" from inception till 2024. The demographics, genetic and clinical data from included studies were extracted and analyzed. Only case-control studies on habitual caffeine drinkers with at least 100 in each arm were included.

RESULTS

A total of 2552 studies were screened and 26 studies involving 1,851,428 individuals were included. Several genes that were involved with caffeine metabolism such as CYP1A2, ADORA2A, AHR, POR, ABCG2, CYP2A6, PDSS2 and HECTD4 rs2074356 (A allele specific to East Asians and monomorphic in Europeans, Africans and Americans) were associated with habitual caffeine consumption with effect size difference of 3% to 32% in number of cups of caffeinated drink per day per effect allele. In addition, ALDH2 was linked to the Japanese population. Genes associated with caffeine reward included BDNF, SLC6A4, GCKR, MLXIPL and dopaminergic genes such as DRD2 and DAT1 which had around 2-5% effect size difference in number of cups of caffeinated drink for each allele per day.

CONCLUSION

Several genes that were involved in caffeine metabolism and reward were associated with up to 30% effect size difference in number of cups of caffeinated drink per day, and some associations were specific to certain ethnicities. Identification of at-risk caffeine dependence individuals can lead to early diagnosis and stratification of at-risk vulnerable individuals such as pregnant women and children, and can potentially lead to development of drug targets for dependence to caffeine.

© 2024. The Author(s).