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Six Genes May Determine How Much Coffee You Should be Drinking

Update Date: Oct 07, 2014 04:21 PM EDT

Your DNA may predict your daily coffee intake, according to a new study.

Scientists have recently found six new genetic variants that significantly increase the likelihood of habitual coffee drinking behaviors. The latest findings may explain the different effects caffeine has on different people and offer a starting point for future research.

"Coffee and caffeine have been linked to beneficial and adverse health effects. Our findings may allow us to identify subgroups of people most likely to benefit from increasing or decreasing coffee consumption for optimal health," lead researcher Marilyn Cornelis, research associate in the Department of Nutrition at Harvard School of Public Health, said in a news release.

The latest findings are considered a breakthrough in coffee and health research as scientists have never been able to link specific genetic variants to individual differences in response to coffee and caffeine.

The latest study involved genetic data from more than 120,000 regular coffee drinkers of European and African American descent. The study revealed two variants that determined caffeine metabolism (POR and ABCG2), two that influence the rewarding effects of caffeine (BDNF and SLC6A4), and two others involved in the metabolism or neurological effects of coffee.

"The new candidate genes are not the ones we have focused on in the past, so this is an important step forward in coffee research," said Cornelis.

"Like previous genetic analyses of smoking and alcohol consumption, this research serves as an example of how genetics can influence some types of habitual behavior," senior author Daniel Chasman, an associate professor at Brigham and Women's Hospital, said in a statement.

In other words, the latest findings suggest that our genes determine how much coffee we need to drink to feel the optimal effects, and that differences in genes directly influence our coffee intake and caffeine metabolism.

The findings were published online Oct. 7 in the journal Molecular Psychiatry.

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