Neuroscience

Depression in a group of Medicare recipients ages 65 years and older appears to be associated with prevalent mild cognitive impairment and an increased risk of dementia, according to a report published Online First by Archives of Neurology, a JAMA Network publication.

Depressive symptoms occur in 3 percent to 63 percent of patients with mild cognitive impairment (MCI) and some studies have shown an increased dementia risk in individuals with a history of depression. The mechanisms behind the association between depression and cognitive decline have not been made clear and different mechanisms have been proposed, according to the study background.

Edo Richard, M.D., Ph.D., of the University of Amsterdam, the Netherlands, and colleagues evaluated the association of late-life depression with MCI and dementia in a group of 2,160 community-dwelling Medicare recipients.

“We found that depression was related to a higher risk of prevalent MCI and dementia, incident dementia, and progression from prevalent MCI to dementia, but not to incident MCI,” the authors note.

Baseline depression was associated with prevalent MCI (odds ratio [OR], 1.4) and dementia (OR, 2.2), while baseline depression was associated with an increased risk of incident dementia (hazard ratio [HR], 1.7) but not with incident MCI (HR, 0.9). Patients with MCI and coexisting depression at baseline also had a higher risk of progression to dementia (HR, 2.0), especially vascular dementia (HR, 4.3), but not Alzheimer disease (HR, 1.9), according to the study results.

“Our finding that depression was associated cross sectionally with both MCI and dementia and longitudinally only with dementia suggests that depression develops with the transition from normal cognition to dementia,” the authors conclude.

(Image: U.S. Dept. of Energy Office of Science)

The amount of time and money needed to sequence genomes continued to fall this year, perhaps to no one’s surprise. But while the field seemed to be finally approaching the heralded $1,000 human genome, the implications of reaching that milestone are not clear. Without expert analysis, the result of sequencing a human genome is just a large file of letters. You still need to manipulate and understand what those letters mean. Different companies announced services to help, from initial processing and storage of data to interpretation of the genetic data into medical meaning.

As human genomics garnered more attention from the medical community, the technology attracted new business opportunities. In April, the company behind the most widely used DNA sequencer, Illumina, fought off a hostile bid from pharmaceutical giant Roche. Just seven months later, Illumina tried to take over Complete Genomics, a company with technology well suited to medical genomics but which has never achieved financial success. That offer followed what seemed to be an all-but-assured purchased of Complete Genomics by China’s BGI. Illumina and BGI continue to fight over Complete Genomics.

Still, the medical community is only at the cusp of its understanding of how genome sequences can be used to help patients. Two branches of medicine that seem to be at the forefront of bringing on board DNA technology are reproductive medicine and cancer. Early in the summer, scientists at the University of Washington in Seattle reported a technique for determining the genome sequence of a fetus by analyzing DNA in the mother’s blood and from the father. Illumina’s CEO Jay Flatley said that prenatal diagnostics will be a major focus for the company, which has been expanding its business from sequencer manufacturing to broad DNA analysis service. In September, Illumina purchased BlueGnome, a chromosome-focused diagnostic company whose technology can detect abnormal numbers of chromosomes in IVF embryos. DNA analysis could also help prior to conception, according to a start-up called GenePeeks. That company announced it would offer predictive genome analysis for sperm bank clients to help guide them away from risky donor matches.  

Cancer patients and their doctors were also early adopters of medical genome science this year. Cancer is a disease of the genome: genetic mutations lead to abnormal cellular proliferation and behavior. Each person’s tumor and even different cells within a single tumor can have a unique profile of mutations, which makes finding the right drug to treat each patient difficult. Cambridge, Massachusetts-based  Foundation Medicine offered a sequencing service that searches for mutations that can be addressed with drugs in a patient’s tumor. Another Cambridge company, H3 Biomedicine, is using public databases of tumor sequences to find new drug targets specific to certain patient populations. 

Genetic medicines also got a boost with the first Western approval of gene therapy in November. Amsterdam-based Uniqure will begin selling its virus-mediated gene correction for a rare metabolic disorder sometime next year. The announcement could be good news for other companies trying to develop gene therapies as well as other groups developing molecular medicines, such as gene-silencing RNAi treatments that continue to move through clinical trials.

Although still untested in patients, another genetic manipulation is proving to be a powerful tool for neuroscientists. With optogenetics, scientists can manipulate neuron activity with flashes of light, and this year a group demonstrated for the first time that primate behavior could be controlled with the technique. Lab animal studies this year suggest optogenetics might one day help patients with blindness caused by retinal degeneration.

The melding of mind and machine was also big this year. Scientists in Winston-Salem, North Carolina, demonstrated that a brain implant could replace some cognitive function in primates, which could one day help people with brain damage. On the flip side, two research groups published the first accounts of quadriplegic people using brain implants to control robotic limbs. The implants recorded the participants’ intentions to move, which were translated by a computer into instructions for a robotic arm. The idea is that one day people with severe paralysis or amputations could use such neural prosthetics at home to help with the tasks of daily life.

Brain electronics were also implanted into Alzheimer’s patients this year in an attempt to slow a disease that has so far evaded pharmaceutical treatment.  The urgency for treatment is growing, but the community still doesn’t know what sets into motion the cascade of molecular events that robs people of their memory and thinking skills. With better diagnostic tools and the discovery that there are warnings decades before symptoms, scientists are turning to treating patients with a genetic predisposition for the disease before they start having symptoms. Perhaps this will be the key to treatments in future years.

Unless you have been deaf and blind to the world over the past decade, you know that functional magnetic resonance brain imaging (fMRI) can look inside the skull of volunteers lying still inside the claustrophobic, coffinlike confines of a loud, banging magnetic scanner. The technique relies on a fortuitous property of the blood supply to reveal regional activity. Active synapses and neurons consume power and therefore need more oxygen, which is delivered by the hemoglobin molecules inside the circulating red blood cells. When these molecules give off their oxygen to the surrounding tissue, they not only change color—from arterial red to venous blue—but also turn slightly magnetic.

(Image: Todd Davidson/Stock Illustration Source)

Activity in neural tissue causes an increase in the volume and flow of fresh blood. This change in the blood supply, called the hemodynamic signal, is tracked by sending radio waves into the skull and carefully listening to their return echoes. FMRI does not directly measure synaptic and neuronal activity, which occurs over the course of milliseconds; instead it uses a relatively sluggish proxy—changes in the blood supply—that rises and falls in seconds. The spatial resolution of fMRI is currently limited to a volume element (voxel) the size of a pea, encompassing about one million nerve cells.

Neuroscientists routinely exploit fMRI to infer what volunteers are seeing, imagining or intending to do. It is really a primitive form of mind reading. Now a team has taken that reading to a new, startling level.

A number of groups have deduced the identity of pictures viewed by volunteers while lying in the magnet scanner from the slew of map­like representations found in primary, secondary and higher-order visual cortical regions underneath the bump on the back of the head.

Jack L. Gallant of the University of California, Berkeley, is the acknowledged master of these techniques, which proceed in two stages. First, a volunteer looks at a couple of thousand images while lying in a magnet. The response of a few hundred voxels in the visual cortex to each image is carefully registered. These data are then used to train an algorithm to predict the magnitude of the fMRI response for each voxel. Second, this procedure is inverted. That is, for a given magnitude of hemodynamic response, a probabilistic technique called Bayesian decoding infers the most likely image that gave rise to the observed response in that particular volunteer (human brains differ substantially, so it is difficult to use one brain to predict the responses of another).

The best of these techniques exploit preexisting, or prior, knowledge about pictures that could have been seen before. The number of mathematically possible images is vast, but the types of actual scenes that are encountered in a world populated by people, animals, trees, buildings and other objects encompass a tiny fraction of all possible images. Appropriately enough, the images that we usually encounter are called natural images. Using a database of six million natural images, Gallant’s group showed in 2009 how brain responses of volunteers to photographs they had not previously encountered could be reconstructed.

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How can the immune system be reprogrammed once it goes on the attack against its own body? EPFL scientists retrained T-cells involved in type I diabetes, a common autoimmune disease. Using a modified protein, they precisely targeted the white blood cells (T-lymphocytes, or T-cells) that were attacking pancreatic cells and causing the disease. When tested on laboratory mice, the therapy eliminated all signs of the pathology. This same method could be a very promising avenue for treating multiple sclerosis as well. The scientists have just launched a start-up company, Anokion SA, on the Lausanne campus, and are planning to conduct clinical trials within the next two years. Their discovery has been published in the journal PNAS (Proceedings of the National Academy of Science).

To retrain the rebellious white blood cells, the researchers began with a relatively simple observation: every day, thousands of our cells die. Each time a cell bites the dust, it sends out a message to the immune system. If the death is caused by trauma, such as an inflammation, the message tends to stimulate white blood cells to become aggressive. But if the cell dies a programmed death at the end of its natural life cycle, it sends out a soothing signal.

In the human body there is a type of cell that dies off en masse, on the order of 200 billion per day – red blood cells. Each of these programmed deaths sends a soothing message to the immune system. The scientists took advantage of this situation, and attached the pancreatic protein targeted by T-cells in type I diabetes to red blood cells.

"Our idea was that by associating the protein under attack to a soothing event, like the programmed death of red blood cells, we would reduce the intensity of the immune response," explains Jeffrey Hubbell, co-author of the study. To do this, the researchers had to do some clever bioengineering and equip the protein with a tiny, molecular scale hook, that is able to attach itself to a red blood cell. Billions of these were manufactured and then simply injected into the body.

Complete eradication of diabetes symptoms

As these billions of red blood cells died their programmed death, they released two signals: the artificially attached pancreatic protein, and the soothing signal. The association of these two elements, like Pavlov’s dog, who associates the ringing of a bell with a good or bad outcome, essentially retrained the T lymphocytes to stop attacking the pancreatic cells. “It was a total success. We were able to eliminate the immune response in type I diabetes in mice,” explains Hubbell.

Minimizing risks and side effects

Co-author Stephan Kontos adds that the great advantage of this approach is its extreme precision. “Our method carries very little risk and shouldn’t introduce significant side effects, in the sense that we are not targeting the entire immune system, but just the specific kind of T-cells involved in the disease.”

The scientists are planning to conduct clinical trials in 2014, at the earliest. To demonstrate the potential of their method, they plan to first test applications that would counteract the immune response to a drug known for its effectiveness against gout. “We chose to begin with this application before we tackled diabetes or multiple sclerosis, since we knew and were in control of all the parameters,” explains Hubbell.

Currently, the researchers are also testing the potential of this method in treating multiple sclerosis. In this disease, T-cells destroy myelin cells, which form a protective sheath around nerve fibers. They are also studying the potential of their method with another kind of white blood cell, B-lymphocytes, that are involved in many other autoimmune diseases.

Autistic-like behaviors can be partially remedied by normalizing excessive levels of protein synthesis in the brain, a team of researchers has found in a study of laboratory mice. The findings, which appear in the latest issue of Nature, provide a pathway to the creation of pharmaceuticals aimed at treating autism spectrum disorders (ASD) that are associated with diminished social interaction skills, impaired communication ability, and repetitive behaviors.

"The creation of a drug to address ASD will be difficult, but these findings offer a potential route to get there," said Eric Klann, a professor at NYU’s Center for Neural Science and the study’s senior author. "We have not only confirmed a common link for several such disorders, but also have raised the exciting possibility that the behavioral afflictions of those individuals with ASD can be addressed."

The study’s other co-authors included researchers from the University of California, San Francisco (UCSF) and three French institutions: Aix-Marseille Universite’; Institut National de la Santé et de la Recherche Médicale (INSERM); and Le Centre National de la Recherche Scientifique (CNRS).

The researchers focused on the EIF4E gene, whose mutation is associated with autism. The mutation causing autism was proposed to increase levels of the eIF4E, the protein product of EIF4E, and lead to exaggerated protein synthesis. Excessive eIF4E signaling and exaggerated protein synthesis also may play a role in a range of neurological disorders, including fragile X syndrome (FXS).

In their experiments, the researchers examined mice with increased levels of eIF4E. They found that these mice had exaggerated levels of protein synthesis in the brain and exhibited behaviors similar to those found in autistic individuals—repetitive behaviors, such as repeatedly burying marbles, diminished social interaction (the study monitored interactions with other mice), and behavioral inflexibility (the afflicted mice were unable to navigate mazes that had been slightly altered from ones they had previously solved). The researchers also found altered communication between neurons in brain regions linked to the abnormal behaviors.

To remedy to these autistic-like behaviors, the researchers then tested a drug, 4EGI-1, which diminishes protein synthesis induced by the increased levels of eIF4E. Through this drug, they hypothesized that they could return the afflicted mice’s protein production to normal levels, and, with it, reverse autistic-like behaviors.

The subsequent experiments confirmed their hypotheses. The mice were less likely to engage in repetitive behaviors, more likely to interact with other mice, and were successful in navigating mazes that differed from those they previously solved, thereby showing enhanced behavioral flexibility. Additional investigation revealed that these changes were likely due to a reduction in protein production—the levels of newly synthesized proteins in the brains of these mice were similar to those of normal mice.

"These findings highlight an invaluable mouse model for autism in which many drugs that target eIF4E can be tested," added co-author Davide Ruggero, an associate professor at UCSF’s School of Medicine and Department of Urology. "These include novel compounds that we are developing to target eIF4E hyperactivation in cancer that may also be potentially therapeutic for autistic patients."