THE GENETICS OF ALZHEIMER'S

FROM:  THE NATIONAL SCIENCE FOUNDATION 
Uncovering Alzheimer's complex genetic networks
Researchers from the Mayo Clinic use NSF-supported Blue Waters supercomputer to understand gene expression in the brain
February 3, 2015

The release of the film, "Still Alice," in September 2014 shone a much-needed light on Alzheimer's disease, a debilitating neurological disease that affects a growing number of Americans each year.

More than 5.2 million people in the U.S. are currently living with Alzheimer's. One out of nine Americans over 65 has Alzheimer's, and one out of three over 85 has the disease. For those over 65, it is the fifth leading cause of death.

There are several drugs on the market that can provide relief from Alzheimer's symptoms, but none stop the development of disease, in part because the root causes of Alzheimer's are still unclear.

"We re interested in studying the genetics of Alzheimer's disease," said Mariet Allen, a post-doctoral fellow at the Mayo Clinic in Florida. "Can we identify genetic risk factors and improve our understanding of the biological pathways and cellular mechanisms that can play a role in the disease process?"

Allen is part of a team of researchers from the Mayo Clinic who are using Blue Waters, one of the most powerful supercomputers in the world, to decode the complicated language of genetic pathways in the brain. In doing so, they hope to provide insights into what genes and proteins are malfunctioning in the brain, causing amyloid beta plaques, tau protein tangles and brain atrophy due to neuronal cell loss--the telltale signs of the disease--and how these genes can be detected and addressed.

In the case of late onset Alzheimer's disease (LOAD), it is estimated that as much as 80 percent of risk is due to genetic factors. In recent years, researchers discovered 20 common genetic loci, in addition to the well-known APOE gene, that are found to increase or decrease risk for the disease. (Loci are specific locations of a gene, DNA sequence, or position on a chromosome.) These loci do not necessarily have a causal connection to the disease, but they provide useful information about high-risk patients.

Despite all that doctors have learned in recent years about the genetic basis of Alzheimer's, according to Allen, a substantial knowledge gap still exists. It has been estimated that likely less than 40 percent of genetic risk for LOAD can be explained by known loci. Furthermore, it is not always clear which are the affected genes at these known loci.

In other words, scientists have a long way to go to get a full picture of which genes are involved in processes related to the disease and how they interact.

The Mayo team and their colleagues had been very successful in the past in finding genetic risk factors using a method that matched individual differences in the DNA code--single-nucleotide polymorphisms or SNPs, to phenotypes--the outward appearances of the disease. In particular, the Mayo team focused on identifying SNPs that influence expression of genes in the brain. However, they now hypothesize that the single SNP method may be too simplistic to find all genetic factors, and is likely not an accurate reflection of the complex biological interactions that take place in an organism.

For that reason, the Mayo researchers have recently turned their attention to investigating the brain using genetic interaction (epistasis) studies. Such studies allow researchers to understand the effects of pairs of gene changes on a given phenotype and can uncover additional genetic variants that influence gene expression and disease.

The process involves the analysis of billions of DNA base pairs (the familiar C, G, A and T) to find statistically significant correlations. Importantly, the search is not to discover simple one-to-one connections, since these have largely been found, but to study the interaction effects of pairs of DNA sequence variations.

Solving a problem of this size and complexity requires a huge amount of computational processing time, so the researchers turned to the Blue Waters supercomputer at the National Center for Supercomputing Applications (NCSA).

Supported by the National Science Foundation and the University of Illinois at Urbana-Champaign, Blue Waters allows scientists and engineers across the country to tackle a wide range of challenging problems using massive computing and data processing power. From predicting the behavior of complex biological systems to simulating the evolution of the cosmos, Blue Waters assists researchers whose computing problems are at a scale or complexity that cannot be reasonably approached using any other method.

Allen and her colleagues used Blue Waters to rapidly advance their Alzheimer's epistasis study through NCSA's Private Sector Program, which lets teams outside of academia access the system.

Instead of requiring as much as a year or more of processing on a single workstation or university cluster, the research team was able to do each analysis on Blue Waters in less than two days.

The researchers conducted three sets of analysis to investigate brain gene expression levels in a group of individuals without Alzheimer's, a group of individuals with Alzheimer's and then a combined analysis of both groups together. To date, these analyses have been completed for the almost 14,000 genes expressed in the majority of the brain samples studied.

Through their work with collaborators at NCSA and the University of Illinois at Urbana-Champaign (including Victor Jongeneel and Liudmila Mainzer), the Mayo team overcame many of the challenges that a project of this scope presented.

"The analysis of epistatic effects in large studies, such as ours, requires powerful computational resources and would not be possible without the unique computing capabilities of Blue Waters," wrote project lead Nilufer Ertekin-Taner from the Mayo Clinic.

"The Mayo Clinic project is emblematic of the type of problem that is beginning to emerge in computational medicine," said Irene Qualters, division director of Advanced Computing Infrastructure at NSF. "Through engagement with the Blue Waters project, researchers at Mayo have demonstrated the potential of new analytic approaches in addressing the challenges of a daunting medical frontier."

The team reported on their progress at the Blue Waters Symposium in May 2014. Allen and her colleagues are currently processing and filtering the results so they can be analyzed.

"Recent studies by our collaborators and others have shown that both the risk for late onset Alzheimer's disease and gene expression are likely influenced by epistasis. However little is known about the effect of genetic interactions on brain gene expression specifically and how this might influence risk for neurological diseases such as LOAD," said Allen. "The goal of our study is to address this knowledge gap; something we have been uniquely positioned to do using our existing data and the resources available on Blue Waters."

-- Aaron Dubrow, NSF

NSF: BRAIN SYSTEM INTERACTION

FROM:  NATIONAL SCIENCE FOUNDATION 

Complexity of eye-hand coordination

Research helps understand how brain systems interact to carry out cognitive processes

People not only use their eyes to see, but also to move. It takes less than a fraction of a second to execute the loop that travels from the brain to the eyes, and then to the hands and/or arms. Bijan Pesaran is trying to figure out what occurs in the brain during this process.

"Eye-hand coordination is the result of a complex interplay between two systems of the brain, but there are many regions where this interaction takes place," says Pesaran, an associate professor of neural science at New York University. "One of the things about the current state of knowledge is that it is focused on the different pieces of the brain and how each works individually. Relatively little work has been done to link how they work together at the cellular level."

The thrust of his research involves studying how neurons in these parts of the brain communicate with one another.

"The cerebral cortex contains a mosaic of brain areas that are connected to form distributed networks," says the National Science Foundation (NSF)-funded scientist. "In the frontal and parietal cortex, these networks are specialized for movements such as saccadic (voluntary) eye movements and reaches, that is, hand and arm movements. Before each movement we decide to make, these areas contain specific patterns of neural activity which can be used to predict what we will do."

A more sophisticated understanding of the brain's role in eye-hand coordination can be an important model for discovering how brain systems interact to carry out cognitive processes in general, he says. Such insights could lead to new neural technologies that translate thoughts into actions, for example, to control a robotic arm or prompt speech.

"There is a whole new set of technologies called neural prostheses," Pesaran says. "In the future, there could be devices in the brain that will help people remember, to think more clearly, and to help them move."

Using eye movements to prompt hand and arm movements involves building a spatial representation, "which is improved by moving our eyes," he says. "The command that is sent to the eyes moves the eyes, which effectively measure space when they move, and that is used to improve the accuracy of the reach. We move our eyes to improve our movement, not just to see better."

He often describes the behavior of high level ping pong players to explain how it works.

"You keep your eye on the ball so you know where it is, so you can hit it," he says. "But right up until the minute you hit the ball, something important is happening, which is that your brain is sending a command to your arm to hit the ball. But the visual signals are delayed. At the time you hit the ball, the vision of the ball won't enter your brain for another fraction of a second, so there is no point in looking at the ball. You can look all you want, but your arm already has moved.

"When ping pong players are playing at a high level, they look at the ball up to the point where they hit it. As soon as the paddle makes contact with the ball, you can see their eyes and head turn to now look at their opponent. They think they are looking at their opponent when they are hitting the ball, but they are looking at ball. Their eyes are tracking the ball, even though they are aware of their opponent.

"This helps the brain keep a very high resolution of space to make the stroke more accurate," he continues. "It's not about seeing the ball, because by then it's too late. It's about moving the eyes with the ball so that the stroke is more accurate. And the brain orchestrates this complicated pattern of behavior."

Visual signals always are delayed. They enter the brain, converted into a movement, and then leave the brain for the arm muscles. "It's a loop that takes about 200 millisecond--about one-fifth of second--and in that time the ball is moved," he says.

Pesaran is conducting his research under an NSF Faculty Early Career Development (CAREER) award, which he received in 2010. The award supports junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of the mission of their organization.

To prove his hypothesis that two regions in the brain (the parietal reach region and the parietal eye field, both in the parietal cortex) must talk to each other to prompt movement, Pesaran and his team are recording the activity of neurons, brain cells that send electrical signals to each other called "spikes." They do so by placing micro-electrodes into the brains of animals that look and reach, much like humans, and study the correlation and patterns in those signals.

"We think we can measure these signals when they are leaving one area, and coming into another," he says. "How does this show that this reflects communication between those two areas? Because something happens, something changes. We set up these movements in a particular way that requires communication between the eye and the arm centers, and we then made measurements in the brain from those centers. Then we linked the changes in the activity between the two areas to the changes in how the eyes and arm move."

As part of the grant's educational component, Pesaran is trying to show youngsters how far neuroscience has come, and encourage them to learn about it. He and his colleagues are working with middle school children in Brooklyn, and have presented demonstrations at the American Museum of Natural History about the field of brain science.

"We go into schools and teach children about what we know about the brain," he says. "We had a brain computer interface, where they had the chance to control the cursor on the screen with their minds. We placed an EEG sensor on their heads, which measures brain activity. When they concentrate, it changes the position of the ball, and moves it up or down."

School children typically are unaware of neuroscience as an emerging field "that involves medicine, biology, engineering, a whole range of disciplines that come together," he says. "Increasing their sophistication and tools in this discipline early will be a hallmark of the next generation of brain scientists."

-- Marlene Cimons, National Science Foundation
Investigators
Bijan Pesaran
Related Institutions/Organizations
New York University