Results from a study published in the online publication Nature Genetics finds 15 genomic regions that are significantly associated with a diagnosis of depression.

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Identifying genes that increase the risk for depression may help researchers develop new treatments.

Depression is one of the most common mental disorders in the United States. In 2014, there were around 15.7 million adults aged 18 or older in the U.S. who had experienced at least one major depressive episode in the last year, which represented 6.7 percent of all American adults.

According to the Anxiety and Depression Association of America, depression is a condition in which a person feels discouraged, sad, hopeless, unmotivated, or disinterested in life in general.

At any one time, 3-5 percent of adults suffer from major depression, and the lifetime risk is around 17 percent. The disability is more common in women than men, with a median age onset of 32 ½ years.

“Identifying genes that affect risk for a disease is a first step towards understanding the disease biology itself, which gives us targets to aim for in developing new treatments,” says study co-author Dr. Roy Perlis, of the Department of Psychiatry and the Center for Human Genetic Research at Massachusetts General Hospital, and associate professor of psychiatry at Harvard Medical School.

“More generally, finding genes associated with depression should help make clear that this is a brain disease, which we hope will decrease the stigma still associated with these kinds of illnesses,” he adds.

Depression tends to run in families across multiple generations; a person whose parent or sibling has major depression has 2-3 times greater risk of developing depression, compared with the average person.

Genetic familial studies have been unable to pinpoint variants influencing the risk for depression. Although one study identified two genomic regions contributing to disease risk in Chinese women, those particular variants are rare in other ethnic groups.

Dr. Perlis and team note that many types of depression manifest and affect people in different ways, and, as with other psychiatric disorders, depression is more than likely influenced by many genes, with effects that have previously been too subtle to detect.

The study used data gathered by genomics company 23andMe – a direct-to-consumer genetic testing company – customers of which consented to be involved in research.

Participants responded to surveys and completed questionnaires about medical history and physical and demographic information.

From the 23andMe database, more than 300,000 individuals of European ancestry were analyzed for common genetic variation. There were more than 75,000 who reported diagnosis or treatment for depression and more than 230,000 with no reported history of depression.

The analysis found two genomic regions – one containing a gene expressed in the brain that is currently poorly understood, and another gene associated with epilepsy and intellectual disability – as notably associated with the risk of depression.

Outcomes from the analysis were combined with findings from other studies: a genome-wide association study with around 9,200 individuals with a history of depression and 9,500 controls, and another from 23andMe clients, with 45,800 participants with depression and 106,000 controls.

Findings identified 15 genomic regions, including 17 particular sites – several of which were located in or close to genes involved in brain development – linked with a diagnosis of depression.

The neurotransmitter-based models we are currently using to treat depression are more than 40 years old, and we really need new treatment targets. We hope that finding these genes will point us toward novel treatment strategies.”

Dr. Roy Perlis

“Another key takeaway from our study is that the traditional way of doing genetic studies is not the only way that works,” Dr. Perlis adds.

“Using existing large datasets or biobanks may be far more efficient and may be helpful for other psychiatric disorders, such as anxiety disorders, where traditional approaches also have not been successful,” he concludes.

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