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Using Crowd-Sourced Data To Find Genetic Links to Depression
It’s long been understood that depression can run in families, but for years scientists have been unable to uncover genetic risk factors associated with the disease.1
For one, depression is a complex condition caused by a variety of factors–both genetic and environmental–and there are various subtypes of the disease.1 The other great challenge has been in finding a large enough pool of genetic data to study.1
But a recent collaboration between Pfizer and the genetic testing company 23andMe has lead to the discovery of 15 regions of the human genome that appear to be linked to major depressive disorder. In the largest study of its kind, researchers analyzed genetic data from more than 70,000 23andMe customers, who said they’d been diagnosed with depression and agreed to submit their anonymous data for research. By using crowd-sourced data, researchers had access to an unprecedented amount of genetic information, nearly 10 times the amount of the next-largest depression study.3
“In previous genetic studies, depression had been left out of the game,” said Craig Hyde, Director of Clinical Research Statistics at Pfizer. “We didn’t have enough subjects to be able to pinpoint and verify which genes were associated with the disease. Collecting DNA can be a slow process. In this collaboration customers sent in saliva; providing a much faster way to identify study subjects, “ added Hyde, who was lead author of the study’s findings published in Nature Genetics.
Understanding the brain and depression
More than 350 million people worldwide suffer from depression. 4With these recent genetic discoveries, scientists are establishing evidence that depression is a brain disease, helping reduce the stigma associated with the condition. In the future, scientists can also use this new genetic information to potentially uncover novel treatment targets for depression.5
Through the 23andMe model, customers purchase a kit and send in their saliva samples to learn about their genetic history. They have the option of filling out online health and lifestyle questionnaires and to allow their anonymous information to be used for scientific research.
Searching for common variations
In the first phase of the study, investigators analyzed the genetic data of more than 300,000 individuals of European ancestry from the 23andMe database. More than 70,000 subjects reported having been diagnosed with or treated for depression, and another 230,000 reported no depression. Using statistical analyses, researchers scanned for specific locations of genetic variation on their DNA known as single nucleotide polymorphisms (SNPs), comparing those with depression to those without.
Initially, they found two SNPs highly associated with depression risk; one was on a gene linked to regulation of brain synapses and another was on a gene associated with epilepsy and intellectual disability.6 “We’re looking for distinct peaks of statistical evidence on one spot of the chromosome,” said Hyde.
In a second phase of the study, researchers combined data with a prior smaller genome study, and found 13 SNPS associated with depression. These variations were found in regions associated associated with brain development and psychiatric disorders. 7,8
Future treatments and discoveries
While this new understanding won’t immediately lead to new treatments, it’s a starting point, said Hyde. “I think once people do follow-ups with various supporting data and consider nearby genes in order to determine which genes are responsible for the signals we are seeing, you have a potential starting point to make molecules to inhibit a gene contributing to disease, or possibly enhance a gene that protects from disease,” he added.
Combined with traditional methods of data collection, crowd-sourced consumer data is showing promise to speed up the genetic research discovery process. Since forming its collaboration with 23andMe in January 2015, Pfizer already has had several important discoveries. In the coming months, Hyde and his team will submit studies on the genetic links to pain and body mass index (BMI) for publication. “The advent of crowd-sourced collection of genetic data has revolutionized our ability to collect large enough sample sizes to detect subtle genetic effects on complex diseases, and these may well provide the first steps to a new generation of therapies in the future”, said Hyde.