Data scientists discover seven genetic variants linked to intracranial volume, Parkinson’s disease risk, and cognitive ability
Scientists collaborating across 250 institutions in 35 countries have identified variations of the genetic code that are associated with intracranial volume, which is a reflection of the maximum brain volume an individual achieves over a lifetime. These variations were also found to be associated with a person’s individual risk for Parkinson’s disease and to cognitive ability. The findings provide new avenues of research that may lead to an enhanced understanding of how differences in our genetic code can predispose individuals to brain disorders.
The findings were the result of the collective analysis of MRI brain scans and DNA from over 32,000 people worldwide. The researchers published their work in the October 3rd issue of the journal Nature Neuroscience.
“The magnitude of this study is truly remarkable,” said Vinay Pai, Ph.D., director of the Division of Health Informatics Technologies at the National Institute of Biomedical Imaging and Bioengineering (NIBIB), part of the U.S. National Institutes of Health (NIH). “If you want to discover genes that affect the brain, the only way we know how to do that is by analyzing tens of thousands of brain scans and their corresponding genetic data. But that requires bringing together hundreds of researchers and their biomedical datasets, all of whom may have a different way of looking at the data. In this study, we are seeing the fruits of NIH investments in data science, which have helped to ensure that all the researchers were analyzing the data in the same way and with the same degree of scientific rigor. This is a study that simply could not have been conducted five years ago because no system existed to enable collaboration on this scale.”
The study was carried out by a team of researchers from two global scientific consortia, ENIGMA and CHARGE, which began to pool their brain imaging and genetic datasets back in 2009 to look for genetic markers that affect one’s risk of developing brain diseases. The team collectively combed through the DNA and brain images of individuals to determine whether there were differences in our DNA that could account for differences in images of the brain. Such information could then be used to help tease out factors that put a person at risk for developing a disease, whether genetic or environmental, or give insight into whether an intervention is working.
“This field of imaging genomics, which is the merger of imaging with genetic technology, requires a lot of hard work in the field of data science,” said Paul Thompson, Ph.D., professor of neurology at the University of Southern California and principal investigator of ENIGMA. “It’s a monumentally complicated challenge to try to discover things in your DNA that affect the brain because the two types of data are very different and there are so many things that can affect your brain such as diet, education and physical activity. But with enough data you can actually begin to disentangle single letter changes in the genome that affect the brain. This is really a big data problem. You march through the genome letter by letter and you ask whether that letter affects anything in the brain.”
In 2014, The NIH Big Data to Knowledge (BD2K) Program funded the ENIGMA Center for Worldwide Medicine, Imaging, and Genomics as one of its 13 National Centers of Excellence in Big Data Computing in the Biomedical Sciences. At that time, ENIGMA was poised to lead the way in developing international approaches for working with big data in biomedical science acquired around the globe. The Center supported the development of a set of shared protocols for imaging analysis as well as training for researchers across the globe so they would have the knowledge to implement them. It also provided administrative support to facilitate communication among the 250 laboratories.
“Without the investment of the NIH, the data would still be sitting in 35 different countries,” said Thompson. “BD2K really helped us to bring all the data together.”
In a previous study published in 2015 in the journal Nature, the researchers reported correlations between variations in an individual’s genetic code and the size of a number of structures in the brain. Building on this work, the team has now determined that there are seven areas in our DNA where differences in the genetic code are associated with intracranial volume, which is the size of the skull cavity in which the brain resides. Since the brain shrinks as we age, intracranial volume is thought to represent the size of the brain at its largest point.
These genetic variations were found in regions of the DNA that were near genes involved in Parkinson’s disease and other brain disorders. “When the scientists zeroed in on the DNA of people whose images showed smaller brains, they found a consistent relationship between subtle shifts in the genetic code and their intracranial volume, risk for Parkinson’s disease, and even cognitive ability,” said Thompson.
The researchers hypothesized that one of these genetic variations may affect the function of specialized proteins that stabilize the internal scaffolding of brain cells. “These proteins, known as “tau”, may malfunction later in life to cause dementias such as Alzheimer’s and Parkinson’s disease,” said Thompson.
Patrick Bellgowan, Ph.D., a program director at the National Institute of Neurological Disorders and Stroke at NIH, says the study is a clear demonstration of how the open science approach to data can help generate new hypotheses about brain disorders: “Through data sharing and collaboration, ENIGMA is working to uncover important common and distinguishing neurobiological and genetic features of psychiatric and neurological disorders.”
The researchers also suggested that genes related to intracranial volume may affect DNA replication, the growth of neural stem cells, and signaling in the brain.
Stacia Friedman-Hill, Ph.D., a program director at NIH’s National Institute of Mental Health, says these findings are particularly relevant to the field of mental health research because many mental health disorders are marked by changes in cognitive function, sometimes years before clinical symptoms become significant, and because mental health disorders often involve changes in the developing brain.
“The ability to identify genetic variants that affect intracranial volume, cognitive function, and cell proliferation and growth may offer important clues to the cellular processes through which genetic risk for a disease is translated into abnormalities in the brain," said Friedman-Hill.
Thompson says that the next step in this work is to look not just at intracranial volume but the brain’s connections or its function using other brain imaging modalities such as diffusion tensor imaging or functional MRI.
This research was funded in part by NIH grant EB020403 (funding provided by the NIH BD2K program and managed by NIBIB).
About the National Institute of Biomedical Imaging and Bioengineering (NIBIB): NIBIB’s mission is to improve health by leading the development and accelerating the application of biomedical technologies. The Institute is committed to integrating the physical and engineering sciences with the life sciences to advance basic research and medical care. NIBIB supports emerging technology research and development within its internal laboratories and through grants, collaborations, and training. More information is available at the NIBIB website: http://www.nibib.nih.gov.
About the National Institute of Neurological Disorders and Stroke (NINDS): NINDS is the nation’s leading funder of research on the brain and nervous system. The mission of NINDS is to seek fundamental knowledge about the brain and nervous system and to use that knowledge to reduce the burden of neurological disease.
About the National Institute of Mental Health (NIMH): The mission of the NIMH is to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery and cure. For more information, visit the NIMH website.
About the NIH Big Data to Knowledge (BD2K) Program: The NIH is dedicated to harnessing the potential of the computational and quantitative sciences to elevate the impact and efficiency of biomedical research. BD2K is a trans-NIH initiative established to enable biomedical research as a digital research enterprise, to facilitate discovery and support new knowledge, and to maximize community engagement.