Green tea extract may harm liver in people with certain genetic variations

Long-term use of high-dose green tea extract may provide some protection against cancer, cardiovascular disease, obesity and type 2 diabetes, but it also may create liver damage in a small minority of the population.

Who is at risk? Research from Rutgers, published in The Journal of Dietary Supplements, provides the first solid clue: two genetic variants that predict some of the risk.

"Learning to predict who will suffer liver damage is potentially important because there's growing evidence that high-dose green tea extract may have significant health benefits for those who can safely take it," said Hamed Samavat, senior author of the study and an assistant professor of nutrition sciences at the Rutgers School of Health Professions.

Using data from the Minnesota Green Tea Trial, a large study of green tea's effect on breast cancer, the research team investigated whether people with certain genetic variations were more likely than others to show signs of liver stress after a year of ingesting 843 milligrams per day of the predominant antioxidant in green tea, a catechin called epigallocatechin gallate (EGCG).

Researchers led by Laura Acosta, then a doctoral student, now a graduate, selected two genetic variations in question because each controls the synthesis of an enzyme that breaks EGCG down. They selected the Minnesota Green Tea Trial because it was a large, well-designed study of a unique population. The year-long, placebo-controlled trial included more than 1,000 postmenopausal women and collected data at 3, 6, 9 and 12 months.

An analysis by researchers showed that early signs of liver damage were somewhat more common than normal in women with one variation in the catechol-O-methyltransferase (COMT) genotype and strongly predicted by a variation in the uridine 5'-diphospho-glucuronosyltransferase 1A4 (UGT1A4) genotype.

On average, participants with the high-risk UGT1A4 genotype saw the enzyme that indicates liver stress go up nearly 80 percent after nine months of consuming the green tea supplement, while those with low-risk genotypes saw the same enzyme go up 30 percent.

"We're still a long way from being able to predict who can safely take high-dose green tea extract," said Samavat, who noted the risk of liver toxicity is only associated with high levels of green tea supplements and not with drinking green tea or even taking lower doses of green tea extract. "Variations in this one genotype don't completely explain the variations in liver enzyme changes among study participants. The full explanation probably includes a number of different genetic variations and probably a number of non-genetic factors."

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People with similar faces likely have similar DNA

A collection of photos of genetically unrelated lookalikes, along with DNA analysis, revealed that strong facial similarity is associated with shared genetic variants. The work appears August 23rd in the journal Cell Reports.

"Our study provides a rare insight into human likeness by showing that people with extreme lookalike faces share common genotypes, whereas they are discordant at the epigenome and microbiome levels," says senior author Manel Esteller of the Josep Carreras Leukaemia Research Institute in Barcelona, Spain. "Genomics clusters them together, and the rest sets them apart."

The number of people identified online as virtual twins or doubles who are genetically unrelated has increased due to the expansion of the World Wide Web and the possibility of exchanging pictures of humans across the planet. In the new study, Esteller and his team set out to characterize, on a molecular level, random human beings that objectively share facial features.

To do so, they recruited human doubles from the photographic work of François Brunelle, a Canadian artist who has been obtaining worldwide pictures of lookalikes since 1999. They obtained headshot pictures of 32 lookalike couples. The researchers determined an objective measure of likeness for the pairs using three different facial recognition algorithms.

In addition, the participants completed a comprehensive biometric and lifestyle questionnaire and provided saliva DNA for multiomics analysis. "This unique set of samples has allowed us to study how genomics, epigenomics, and microbiomics can contribute to human resemblance," Esteller says.

Overall, the results revealed that these individuals share similar genotypes, but differ in their DNA methylation and microbiome landscapes. Half of the lookalike pairs were clustered together by all three algorithms. Genetic analysis revealed that 9 of these 16 pairs clustered together, based on 19,277 common single-nucleotide polymorphisms.

Moreover, physical traits such as weight and height, as well as behavioral traits such as smoking and education, were correlated in lookalike pairs. Taken together, the results suggest that shared genetic variation not only relates to similar physical appearance, but may also influence common habits and behavior.

"We provided a unique insight into the molecular characteristics that potentially influence the construction of the human face," Esteller says. "We suggest that these same determinants correlate with both physical and behavioral attributes that constitute human beings."

A few study limitations include the small sample size, the use of 2D black-and-white images, and the predominance of European participants. Despite these caveats, the findings may provide a molecular basis for future applications in various fields such as biomedicine, evolution, and forensics.

"These results will have future implications in forensic medicine -- reconstructing the criminal's face from DNA -- and in genetic diagnosis -- the photo of the patient's face will already give you clues as to which genome he or she has," Esteller says. "Through collaborative efforts, the ultimate challenge would be to predict the human face structure based on the individual's multiomics landscape."

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