Eye Color Predicts Alcohol Dependence Risk

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Blue Eyes

Eye color may seem like a trivial feature, but a new novel study by genetic researchers at the University of Vermont shows eye color may be an indicator of whether you are likely to be an alcoholic.

The study, published in the American Journal of Medical Genetics: Neuropsychiatric Genetics, suggests individuals with blue eyes face an increased risk for alcohol abuse. It is also the first study to find a direct link between eye color and alcohol dependency.

“This suggests an intriguing possibility: that eye color can be useful in the clinic for alcohol dependence diagnosis,” says Arvis Sulovari, a doctoral student in cellular, molecular and biological sciences.

Sulovari, with fellow research and assistant professor of microbiology and molecular genetics, Dawei Li, Ph.D., found that primarily European-Americans with light-colored eyes – including individuals with green, grey, and brown in the center – had a higher incidence of alcohol dependence compared to those with dark brown eyes. Individuals with blue eyes showed the strongest tendency of all eye colors.

The report details the genetic components that determine eye color and explains they line up along the same chromosome as the genes associated to excessive alcohol abuse. However, Li states, “we still don’t know the reason” and calls for further research.

Over the past decade, Li has worked with several other researchers to construct a clinical and genetic database including over 10,000 individuals. Most of the individuals have been African-Americans and European-Americans, diagnosed with at least one psychiatric disorder such as depression, schizophrenia, and bipolar disorder, as well as addiction and alcohol dependence.

“These are complex disorders,” he said. “There are many genes, and there are many environmental triggers.”

After filtering out 1,263 alcohol-dependent patients with European ancestry, Sulovari noted the eye-color connection, leading him and his team to retest their analysis multiple times to account for and compare age, gender, and various ethnic or geographic backgrounds.

Li indicates the findings are just the start, as he wishes to explore deeper into the link between cultural background and genetic makeup. According to Li, all the genes identified in the past 20 years “can only explain a small percentage of the genetics part that has been suggested. A large number is still missing, is still unknown.”

“What has fascinated me the most about this work has been investigating the interface between statistics, informatics, and biology,” said Sulovari. “It’s an incredible opportunity to study genomics in the context of complex human diseases.”

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