New Alzheimer’s research suggests possible cause: the interaction of proteins in the brain

Research shows interaction of tau and amyloid-beta in the brain may cause cognitive decline

For years, Alzheimer’s researchers have focused on two proteins that accumulate in the brains of people with Alzheimer’s and may contribute to the disease: plaques made up of the protein amyloid-beta, and tangles of another protein, called tau.

But for the first time, an Alzheimer’s researcher has looked closely at not the two proteins independently, but at the interaction of the two proteins with each other — in the brain tissue of post-mortem Alzheimer’s patients and in mouse brains with Alzheimer’s disease. The research found that the interaction between the two proteins might be the key: as these interactions increased, the progression of Alzheimer’s disease worsened.

The research, by Hemachandra Reddy, Ph.D., an associate scientist at the Oregon National Primate Research Center at Oregon Health & Science University, is detailed in the June 2013 edition of the Journal of Alzheimer’s Disease.

Reddy’s paper suggests that when the interaction between the phosphorylated tau and the amyloid-beta — particularly in its toxic form — happens at brain synapses, it can damage those synapses. And that can lead to cognitive decline in Alzheimer’s patients.

"This complex formation between amyloid-beta and tau — it is actually blocking the neural communication," Reddy said. "If we could somehow find a molecule that could inhibit the binding of these two proteins at the synapses, that very well might be the cure to Alzheimer’s disease."

To conduct the research, Reddy and his team studied three different kinds of mice, who had been bred to have some of the brain characteristics of Alzheimer’s disease, including having amyloid-beta and phosphorylated tau in their brains. Reddy also analyzed postmortem brain tissue from people who had Alzheimer’s disease.

Using multiple antibodies that recognize amyloid-beta and phosphorylated tau, Reddy and Maria Manczak, Ph.D., a research associate in Reddy’s laboratory, specifically looked for the evidence of the amyloid-beta and phosphorylated tau interactions. They found amyloid-beta/tau complexes in the human Alzheimer’s brain tissue and in the Alzheimer’s disease mouse brains. The Reddy team also found much more of those amyloid-beta/tau complexes in brains where Alzheimer’s disease had progressed the most.

Reddy found very little or no evidence of the same interaction in the “control” subjects — mice that did not have the Alzheimer’s traits and human brain tissue of people who did not have Alzheimer’s.

"So much Alzheimer’s research has been done to look at amyloid-beta and tau," Reddy said. "But ours is the first paper to strongly demonstrate that yes, there is an amyloid-beta/phosphorylated tau interaction. And that interaction might be causing the synaptic damage and cognitive decline in persons with Alzheimer’s disease."

Reddy and his lab are already working on the next crucial questions. One is to define the binding site or sites and exactly where within the neuron the interaction of amyloid-beta and tau first occurs. The second is to find a way to inhibit that interaction — and thus maybe prevent or slow the progression of Alzheimer’s.

Manczak was a co-author on the Journal of Alzheimer’s Disease article.

(Image: Shutterstock)

Long-term study reports deep brain stimulation effective for most common hereditary dystonia

In what is believed to be the largest follow-up record of patients with the most common form of hereditary dystonia – a movement disorder that can cause crippling muscle contractions – experts in deep brain stimulation report good success rates and lasting benefits.

Michele Tagliati, MD, neurologist, director of the Movement Disorders Program at Cedars-Sinai Medical Center’s Department of Neurology, and Ron L. Alterman, MD, chief of the Division of Neurosurgery at Beth Israel Deaconess Medical Center in Boston, published the study in the July issue of the journal Neurosurgery. The doctors worked together at two New York City hospitals for a decade, until Tagliati joined Cedars-Sinai in 2010.

The study is focused on early-onset generalized dystonia, which in 1997 was found to be caused by a mutation of the DYT1 gene. Less than 1 percent of the overall population carries this mutation, but the frequency is believed to be three to five times higher among people of Ashkenazi Jewish heritage. Thirty percent of people who carry the defect develop dystonia.

“Long-term follow-up of DYT1 patients who have undergone DBS treatment is scarce, with current medical literature including only about 50 patients followed for three or more years,” Tagliati said. This study reviewed medical records of 47 consecutive patients treated with DBS for at least one year over a span of 10 years, 2001 to 2011.

“We found that, on average, symptom severity dropped to less than 20 percent of baseline within two years of device implantation. Sixty-one percent of patients were able to discontinue all their dystonia-related medications, and 91 percent were able to discontinue at least one class of drugs,” Tagliati said. “Although a few earlier studies found that stimulation’s effectiveness might wane after five years, our observations confirmed what other important DBS studies in dystonia are finding. Patients had statistically and clinically significant improvement that was maintained up to eight years.”

Alterman, the article’s senior author and the neurosurgeon who performed the implant surgeries, said the study also confirmed the procedure’s safety. Complications, such as infection and device malfunction, were rare and manageable.

Patient follow-up ranged from one year to eight years after surgery; 41 patients were seen for at least two years, and four completed eight years. The youngest patient at time of surgery was 8 and the oldest was 71, with a median age of 16.

Dystonia’s muscle contractions cause the affected area of the body to twist involuntarily, with symptoms that range from mild to crippling. If drugs – which often have undesirable side effects, especially at higher doses – fail to give relief, neurosurgeons and neurologists may work together to supplement medications with deep brain stimulation, aimed at modulating abnormal nerve signals. Electrical leads are implanted in the brain – one on each side – and an electrical pulse generator is placed near the collarbone. The device is programmed with a remote, hand-held controller. Tagliati is an expert in device programming, which fine-tunes stimulation for individual patients.

How neural stem cells create new and varied neurons

A new study examining the brains of fruit flies reveals a novel stem cell mechanism that may help explain how neurons form in humans. A paper on the study by researchers at the University of Oregon appeared in the online version of the journal Nature in advance of the June 27 publication date.

"The question we confronted was ‘How does a single kind of stem cell, like a neural stem cell, make all different kinds of neurons?’" said Chris Doe, a biology professor and co-author on the paper "Combinatorial temporal patterning in progenitors expands neural diversity."

Researchers have known for some time that stem cells are capable of producing new cells, but the new study shows how a select group of stem cells can create progenitors that then generate numerous subtypes of cells.

"Instead of just making 100 copies of the same neuron to expand the pool, these progenitors make a whole bunch of different neurons in a particular way, a sequence," Doe said. "Not only are you bulking up the numbers but you’re creating more neural diversity."

The study, funded by the Howard Hughes Medical Institute and the NIH National Institute of Child Health and Human Development, builds on previous research from the Doe Lab published in 2008. That study identified a special set of stem cells that generated neural progenitors. These so-called intermediate neural progenitors (INPs) were shown to blow up into dozens of new cells. The research accounted for the number of cells generated, but did not explain the diversity of new cells.

"While it’s been known that individual neural stem cells or progenitors could change over time to make different types of neurons and other types of cells in the nervous system, the full extent of this temporal patterning had not been described for large neural stem cell lineages, which contain several different kinds of neural progenitors," said lead author Omer Bayraktar, a doctoral student in developmental neurobiology who recently defended his dissertation.

The cell types in the study, Bayraktar said, have comparable analogs in the developing human brain and the research has potential applications for human biologists seeking to understand how neurons form.

The Nature paper appears alongside another study on neural diversity by researchers from New York University. Together the two papers provide new insight into the processes involved in producing the wide range of nerve cells found in the brains of flies.

For their study, Bayraktar and Doe zeroed in on the stem cells in drosophila (fruit flies) known as type II neuroblasts. The neuroblasts, which had previously been shown to generate INPs, were shown in this study to be responsible for a more complex patterning of cells. The INPs were shown to sequentially generate distinct neural subtypes. The research accounted for additional neural diversity by revealing a second axis in the mechanism. Instead of making 100 neurons, as had been previously thought, a stem cell may be responsible for generating some 400 or 500 neurons.

The study concludes that neuroblasts and INP patterning act together to generate increased neural diversity within the central complex of the fruit fly and that progenitors in the human cerebral cortex may use similar mechanisms to increase neural diversity in the human brain. One long-term application of the research may be to eventually pinpoint stem cell treatments to target specific diseases and disorders.

"If human biologists understand how the different types of neurons are made, if we can tell them ‘This is the pathway by which x, y and z neurons are made,’ then they may be able to reprogram and redirect stem cells to make these precise neurons," Doe said.

The mechanism described in the paper has its limits. Eventually the process of generating new cells stops. One of the next questions to answer will be what makes the mechanism turn off, Doe said.

"This vital research will no doubt capture the attention of human biologists," said Kimberly Andrews Espy, vice president for research and innovation and dean of the UO graduate school. "Researchers at the University of Oregon continue to further our understanding of the processes that undergird development to improve the health and well-being of people throughout the world."

Validating maps of the brain’s resting state

Kick back and shut your eyes. Now stop thinking.

You have just put your brain into what neuroscientists call its resting state. What the brain is doing when an individual is not focused on the outside world has become the focus of considerable research in recent years. One of the potential benefits of these studies could be definitive diagnoses of mental health disorders ranging from bipolar to post-traumatic stress disorders.

A team of psychologists and imaging scientists at Vanderbilt has collaborated on a study that provides important corroboration of the validity of recent research examining the relationship of functional magnetic resonance imaging or fMRI maps of the brain’s resting state networks with it’s underlying anatomical and neurological structure. The study is published in the June 19 issue of the journal Neuron.

“Previous studies have suggested that resting state connectivity shown in brain scans is anchored by anatomical connectivity,” said co-senior author Anna Roe, professor of psychology at Vanderbilt. “But our study has confirmed this relationship at the single neuron level for the first time.”

For the last decade, neuroscientists have been using the non-invasive brain-mapping technique fMRI to examine activity patterns in human and animal brains in the resting state in order to figure out how different parts of the brain are connected and to identify the changes that occur in neurological and psychiatric diseases. For example, there are indications that Alzheimer’s may be associated with decreased connectivity; depression with increased connectivity; epilepsy with disruptions in connectivity and Parkinson’s with alterations in connectivity.

The new findings from Vanderbilt are important because fMRI doesn’t measure brain activity directly. It does so by measuring changes in blood-oxygen levels in different areas. The technique relies on the observation that when activity in an area of the brain increases, blood-oxygen levels in that region rise, which modulates the MRI signal. Neuroscientists have taken this a step further by assuming that different areas in the brain are connected if they show synchronized variations while the brain is in a resting state.

“This is an important validation,” said co-senior author John Gore, director of the Institute of Imaging Science at Vanderbilt and Hertha Ramsey Cress University Professor of Radiology and Radiological Sciences and Biomedical Engineering. “There has always been a sense of unease that we might be interpreting something incorrectly but this gives us confidence that resting state variations can be interpreted in a meaningful way and encourages us to continue the research we have been doing for a number of years. Resting state fMRI provides a uniquely powerful, non-invasive technology to look at the circuits in the human brain.”

To examine the relationship between fMRI scans, patterns of neuronal activity and anatomical structure of the brain, the researchers examined the region of the parietal lobe of squirrel monkeys devoted to monitoring touch sensations. Specifically, they looked at an area linked to the hand that consists of a series of adjacent areas each devoted to a different finger.

Using one of the strongest MRI machines available, with a field strength three to six times that of typical clinical scanners, the researchers produced brain scans that resolved millimeter-scale networks for the first time.

To compare these patterns to the actual electrical activity in the brains, the researchers inserted electrodes capable of recording the firing patterns of individual neurons. In addition, they used optical techniques to trace the anatomical connections between the neurons throughout the region.

“With all three techniques, we found the same pattern of connectivity. Connections coming from other areas in the brain tend to link to individual digits while connections that originate within the area tend to link to multiple digits,” said Roe. “Our results demonstrate that fMRI images of the resting state brain accurately reflect the brain’s anatomical and functional connectivity down to an extremely fine scale.”

Researchers Identify Emotions Based on Brain Activity

For the first time, scientists at Carnegie Mellon University have identified which emotion a person is experiencing based on brain activity.

The study, published in the June 19 issue of PLOS ONE, combines functional magnetic resonance imaging (fMRI) and machine learning to measure brain signals to accurately read emotions in individuals. Led by researchers in CMU’s Dietrich College of Humanities and Social Sciences, the findings illustrate how the brain categorizes feelings, giving researchers the first reliable process to analyze emotions. Until now, research on emotions has been long stymied by the lack of reliable methods to evaluate them, mostly because people are often reluctant to honestly report their feelings. Further complicating matters is that many emotional responses may not be consciously experienced.

Identifying emotions based on neural activity builds on previous discoveries by CMU’s Marcel Just and Tom M. Mitchell, which used similar techniques to create a computational model that identifies individuals’ thoughts of concrete objects, often dubbed “mind reading.”

“This research introduces a new method with potential to identify emotions without relying on people’s ability to self-report,” said Karim Kassam, assistant professor of social and decision sciences and lead author of the study. “It could be used to assess an individual’s emotional response to almost any kind of stimulus, for example, a flag, a brand name or a political candidate.”

One challenge for the research team was find a way to repeatedly and reliably evoke different emotional states from the participants. Traditional approaches, such as showing subjects emotion-inducing film clips, would likely have been unsuccessful because the impact of film clips diminishes with repeated display. The researchers solved the problem by recruiting actors from CMU’s School of Drama.

“Our big breakthrough was my colleague Karim Kassam’s idea of testing actors, who are experienced at cycling through emotional states. We were fortunate, in that respect, that CMU has a superb drama school,” said George Loewenstein, the Herbert A. Simon University Professor of Economics and Psychology.

For the study, 10 actors were scanned at CMU’s Scientific Imaging & Brain Research Center while viewing the words of nine emotions: anger, disgust, envy, fear, happiness, lust, pride, sadness and shame. While inside the fMRI scanner, the actors were instructed to enter each of these emotional states multiple times, in random order.

Another challenge was to ensure that the technique was measuring emotions per se, and not the act of trying to induce an emotion in oneself. To meet this challenge, a second phase of the study presented participants with pictures of neutral and disgusting photos that they had not seen before. The computer model, constructed from using statistical information to analyze the fMRI activation patterns gathered for 18 emotional words, had learned the emotion patterns from self-induced emotions. It was able to correctly identify the emotional content of photos being viewed using the brain activity of the viewers.

To identify emotions within the brain, the researchers first used the participants’ neural activation patterns in early scans to identify the emotions experienced by the same participants in later scans. The computer model achieved a rank accuracy of 0.84. Rank accuracy refers to the percentile rank of the correct emotion in an ordered list of the computer model guesses; random guessing would result in a rank accuracy of 0.50.

Next, the team took the machine learning analysis of the self-induced emotions to guess which emotion the subjects were experiencing when they were exposed to the disgusting photographs.  The computer model achieved a rank accuracy of 0.91. With nine emotions to choose from, the model listed disgust as the most likely emotion 60 percent of the time and as one of its top two guesses 80 percent of the time.

Finally, they applied machine learning analysis of neural activation patterns from all but one of the participants to predict the emotions experienced by the hold-out participant. This answers an important question: If we took a new individual, put them in the scanner and exposed them to an emotional stimulus, how accurately could we identify their emotional reaction? Here, the model achieved a rank accuracy of 0.71, once again well above the chance guessing level of 0.50.

“Despite manifest differences between people’s psychology, different people tend to neurally encode emotions in remarkably similar ways,” noted Amanda Markey, a graduate student in the Department of Social and Decision Sciences.

A surprising finding from the research was that almost equivalent accuracy levels could be achieved even when the computer model made use of activation patterns in only one of a number of different subsections of the human brain.

“This suggests that emotion signatures aren’t limited to specific brain regions, such as the amygdala, but produce characteristic patterns throughout a number of brain regions,” said Vladimir Cherkassky, senior research programmer in the Psychology Department.

The research team also found that while on average the model ranked the correct emotion highest among its guesses, it was best at identifying happiness and least accurate in identifying envy. It rarely confused positive and negative emotions, suggesting that these have distinct neural signatures. And, it was least likely to misidentify lust as any other emotion, suggesting that lust produces a pattern of neural activity that is distinct from all other emotional experiences.

Just, the D.O. Hebb University Professor of Psychology, director of the university’s Center for Cognitive Brain Imaging and leading neuroscientist, explained, “We found that three main organizing factors underpinned the emotion neural signatures, namely the positive or negative valence of the emotion, its intensity — mild or strong, and its sociality — involvement or non-involvement of another person. This is how emotions are organized in the brain.”

In the future, the researchers plan to apply this new identification method to a number of challenging problems in emotion research, including identifying emotions that individuals are actively attempting to suppress and multiple emotions experienced simultaneously, such as the combination of joy and envy one might experience upon hearing about a friend’s good fortune.

What do memories look like?

Oscar Wilde called memory “the diary that we all carry about with us.” Now a team of scientists has developed a way to see where and how that diary is written.

Led by Don Arnold and Richard Roberts of USC, the team engineered microscopic probes that light up synapses in a living neuron in real time by attaching fluorescent markers onto synaptic proteins — all without affecting the neuron’s ability to function.

The fluorescent markers allow scientists to see live excitatory and inhibitory synapses for the first time and, importantly, how they change as new memories are formed.

The synapses appear as bright spots along dendrites (the branches of a neuron that transmit electrochemical signals). As the brain processes new information, those bright spots change, visually indicating how synaptic structures in the brain have been altered by the new data.

“When you make a memory or learn something, there’s a physical change in the brain. It turns out that the thing that gets changed is the distribution of synaptic connections,” said Arnold, associate professor of molecular and computational biology at the USC Dornsife College of Letters, Arts and Sciences, and co-corresponding author of an article about the research that appears in Neuron on June 19.

The probes behave like antibodies, but they bind more tightly and are optimized to work inside the cell — something that ordinary antibodies can’t do. To make these probes, the team used a technique known as “mRNA display,” which was developed by Roberts and Nobel laureate Jack Szostak.

“Using mRNA display, we can search through more than a trillion different potential proteins simultaneously to find the one protein that binds the target the best,” said Roberts, co-corresponding author of the article and professor of chemistry and chemical engineering with joint appointments at USC Dornsife and the USC Viterbi School of Engineering.

Arnold and Roberts’ probes (called “FingRs”) are attached to green fluorescent protein (GFP), a protein isolated from jellyfish that fluoresces bright green when exposed to blue light. Because FingRs are proteins, the genes encoding them can be put into brain cells in living animals, causing the cells themselves to manufacture the probes.

The design of FingRs also includes a regulation system that cuts off the amount of FingR-GFP that is generated after 100 percent of the target protein is labeled, effectively eliminating background fluorescence — generating a sharper, clearer picture.

These probes can be put in the brains of living mice and then imaged through cranial windows using two-photon microscopy.

The new research could offer crucial insight for scientists responding to President Barack Obama’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative, which was announced in April.

Modeled after the Human Genome Project, the objective of the $100 million initiative is to fast-track research that maps out exactly how the brain works and “better understand how we think, learn and remember,” according to the BRAIN Initiative website.

IQ link to baby’s weight gain in first month

New research from the University of Adelaide shows that weight gain and increased head size in the first month of a baby’s life is linked to a higher IQ at early school age.

The study was led by University of Adelaide Public Health researchers, who analysed data from more than 13,800 children who were born full-term.

The results, published today in the international journal Pediatrics, show that babies who put on 40% of their birthweight in the first four weeks had an IQ 1.5 points higher by the time they were six years of age, compared with babies who only put on 15% of their birthweight.

Those with the biggest growth in head circumference also had the highest IQs.

"Head circumference is an indicator of brain volume, so a greater increase in head circumference in a newborn baby suggests more rapid brain growth," says the lead author of the study, Dr Lisa Smithers from the University of Adelaide’s School of Population Health.

"Overall, newborn children who grew faster in the first four weeks had higher IQ scores later in life," she says.

"Those children who gained the most weight scored especially high on verbal IQ at age 6. This may be because the neural structures for verbal IQ develop earlier in life, which means the rapid weight gain during that neonatal period could be having a direct cognitive benefit for the child."

Previous studies have shown the association between early postnatal diet and IQ, but this is the first study of its kind to focus on the IQ benefits of rapid weight gain in the first month of life for healthy newborn babies.

Dr Smithers says the study further highlights the need for successful feeding of newborn babies.

"We know that many mothers have difficulty establishing breastfeeding in the first weeks of their baby’s life," Dr Smithers says.

"The findings of our study suggest that if infants are having feeding problems, there needs to be early intervention in the management of that feeding."

(Image: thebabypicz.com)