Garavan and Addiction Working Group Part of Worldwide Brain Study
“Big Data” combines with crowd-sourcing to accelerate medical research
- By Jennifer Nachbur
The National Institutes of Health (NIH) has announced the increased funding of a global initiative to pool data about the human brain, which will include grant funding for the University of Vermont College of Medicine. The ENIGMA project -- a large, multi-site, data-pooling initiative focused on genetics and the brain that has analyzed tens of thousands of study participants at more than 100 labs in over 30 countries -- will receive an $11 million increase in federal funding. A piece of this funding will allow Hugh Garavan, UVM associate professor of psychiatry and a co-developer of the ENIGMA Addiction Working Group, to direct the meta-analyses of more than 9,000 genetic-neuroimaging datasets in an effort to understand better the biological underpinnings of addiction.
This news comes just a little more than a week following the White House’s Sept. 30 announcement of funding boosts for brain research as part of a presidential initiative, and also follows a similar recent European initiative, the Human Brain Project, which is slated to receive one billion euros over the next decade.
The economic and personal cost of diseases such as schizophrenia, Alzheimers and depression are substantial, but their underlying causes remain unknown. The ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) project aims to identify new sources of disease risk and develop better diagnostic tools by screening brain scans and genetic tests collected across 33 countries of the world. Currently, computing facilities worldwide analyze ENIGMA’s data around the clock, in order to detect effects of treatments or risk factors that may vary and even trend worldwide.
Named after an allied code-breaking initiative in World War II, ENIGMA unites brain researchers to discover factors that affect the brain, either by helping or harming it. Started in 2009 by medical researchers in the U.S., Europe and Australia, the research alliance studies medical scans of the brain and DNA collected from 30,000 people at over 185 sites globally.
Garavan’s team will focus on addiction by coordinating the standardized analyses of cortical and subcortical brain structures and GWAS (genome-wide association studies) at the participating sites and will take the lead in the combined meta-analyses.
“These new grants address two substantial obstacles to understanding the genetic aspects of addiction: one, the need for large sample sizes to detect what may be subtle genetic contributions to addiction and two, the need to apply sophisticated analytic methods to capture the complex and unknown patterns of gene-to-gene and gene-to-environment interactions,” says Garavan. “The data pooling of the ENIGMA project enables this process; we currently have pooled brain-gene data from almost 10,000 participants for our addiction analyses. We can import Big Data methods to help us interrogate the very large datasets (a million sources of genetic variation plus tens of thousands of separate brain measures for each participant) that this pooling creates.”
The Addiction Working Group will analyze data relevant to addiction-related genetic characteristics, including case-control comparisons across a variety of abused substances. In addition, Garavan and his team and colleagues at the University of Montreal and Yale University will examine the influence of co-occurring chronic conditions, gender and stages of dependence. Using aggregate data from case-control and developmental cohorts, the researchers will examine the relative contribution of various genetic and brain correlates on risk for early onset substance misuse, transition to regular use, susceptibility to dependence, and individual differences in relapse vulnerability.
“Our hope is that once established, the Addiction Working Group will be able to provide increasingly substantial and insightful analyses and the pooled data will become a unique resource for addiction researchers,” says Garavan.
The announcement of funding for ENIGMA comes as part of a $100 million federal program to support 11 national Centers of Excellence, part of the Big Data to Knowledge Initiative announced in 2013, to discover patterns in large scale collections of medical data. The efforts targeting large scale biomedical data promise to discover better diagnostic tools for dementia, schizophrenia and developmental disorders such as autism, which have been challenging to treat as their root causes are unknown.
For more information, visit the ENIGMA Consortium website.