(Cold Spring Harbor Laboratory) New technology developed at CSHL transforms the way detailed anatomical images can be made of whole brains and will greatly facilitate systematic comparison of neuroanatomy in mouse models of human brain disorders, e.g., autism and schizophrenia.

(Cold Spring Harbor Laboratory) New technology developed at CSHL transforms the way detailed anatomical images can be made of whole brains and will greatly facilitate systematic comparison of neuroanatomy in mouse models of human brain disorders, e.g., autism and schizophrenia.

(JAMA and Archives Journals) Adolescents diagnosed with schizophrenia and other psychoses appear to show greater decreases in gray matter volume and increases in cerebrospinal fluid in the frontal lobe compared to healthy adolescents without a diagnosis of psychosis, according to a report in the January issue of Archives of General Psychiatry, one of the JAMA/Archives journals.

(Scripps Research Institute) Scientists at the Scripps Research Institute have discovered that DNA stays too tightly wound in certain brain cells of schizophrenic subjects. The findings suggest that drugs already in development for other diseases might eventually offer hope as a treatment for schizophrenia and related conditions in the elderly.

(Scripps Research Institute) Scientists at the Scripps Research Institute have discovered that DNA stays too tightly wound in certain brain cells of schizophrenic subjects. The findings suggest that drugs already in development for other diseases might eventually offer hope as a treatment for schizophrenia and related conditions in the elderly.

(Yale University) Mice become profoundly anti-social when the creation of new brain cells is interrupted in adolescence, a surprising finding that may help researchers understand schizophrenia and other mental disorders, Yale researchers report.

(HudsonAlpha Institute for Biotechnology) Although it affects less than 1 percent of the global population, schizophrenia exacts a large toll in terms of expense and human suffering. A new study from researchers at the HudsonAlpha Institute for Biotechnology, with colleagues from Columbia University in New York and the University of Pretoria in South Africa, indicate non-familial genetic mutations may account for about half of schizophrenia cases.

(The Hastings Center) Concern about the capacity of individuals with schizophrenia to consent to clinical research studies has largely focused on impairment due to psychotic symptoms associated with the disorder. Less attention has been given to the cognitive errors that prospective participants make when undergoing a formal assessment of decisional capacity. A study reported in IRB: Ethics & Human Research found that errors due to cognitive difficulties were common.

EU-funded researchers have developed an innovative new technique that can for the first time map both the connections and functions of nerve cells in the brain, moving scientists one step closer to the development of a computer model of the brain.

The study, published in Nature, was carried out by a group of neuroscientists from University College London (UCL) and was funded in part by a European Research Council starting grant under the Seventh Framework Programme (FP7).

There are estimated to be 100 billion nerve cells (‘neurons’) in the brain, each connected to thousands of other nerve cells – resulting in an approximate total of 150 trillion connections (or ‘synapses’).

In the same vein as genomics, which maps out our genetic make-up, this new type of research is being labelled ‘connectomics’ as it aims to map out the brain’s synapses. Once scientists have an understanding of these connections, they can see how information flows through the brain’s circuits and begin to understand how our perceptions, sensations and thoughts are generated.

This knowledge would help further our understanding of Alzheimer’s disease, schizophrenia and strokes.

‘How do we figure out how the brain’s neural circuitry works?’ asks Dr Tom Mrsic-Flogel, one of the researchers from UCL. ‘We first need to understand the function of each neuron and find out to which other brain cells it connects. If we can find a way of mapping the connections between nerve cells of certain functions, we will then be in a position to begin developing a computer model to explain how the complex dynamics of neural networks generate thoughts, sensations and movements.’

The team used a technique developed in mice that enables them to combine information about the function of neurons together with details of their synaptic connections. By using high resolution imaging to look into the visual cortex of the mouse brain, which contains thousands of neurons and millions of different connections, the team managed to detect which of these neurons responded to a particular stimulus, for example a horizontal edge.

The researchers then investigated another subset of neurons to see which neurons responded to the same stimuli, which allowed them to chart whether these neurons were synaptically connected to the first group of neurons.

They found that neurons which responded very similarly to the same visual stimuli, such as edges of the same orientation (i.e. a horizontal edge or a vertical edge) or more complex visual features like faces, tended to connect more to each other than those which responded to different stimuli.

The findings from this study therefore move forward our knowledge of whether local connections between neurons occur sporadically at random and irrespective of function, or whether neurons connect to other neurons after responding to particular stimuli.

‘We are beginning to untangle the complexity of the brain,’ says Dr Mrsic-Flogel. ‘Once we understand the function and connectivity of nerve cells spanning different layers of the brain, we can begin to develop a computer simulation of how this remarkable organ works. But it will take many years of concerted efforts amongst scientists and massive computer processing power before it can be realised.’

Understanding the complex inner workings of the brain has been brought closer thanks to this study and gives neuroscientists a new tool with which they can further explore this most mysterious of human organs. These findings also have positive implications for revealing the functional circuit wiring of regions that underpin touch, hearing and movement.

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Scientists at Stanford University School of Medicine have played a major role in an international effort that has shown, for the first time, that modern genetic technologies can solve the riddle of how gene variations lead to schizophrenia.

Researchers at Stanford and 14 other institutions carried out a study of common DNA variations throughout the genome, and then combined forces with two independent studies to complete a pooled analysis of 27,000 individuals. The largest genetic differences between the study participants with and without schizophrenia were found on a stretch of chromosome 6 containing numerous genes associated with immune response (and some with other roles). This raises the possibility that immune function plays a role in schizophrenia.

Stanford’s Jianxin Shi, PhD, and Douglas Levinson, MD, are first and second authors of one of three linked papers published online together in Nature on July 1. Their paper reports on the Molecular Genetics of Schizophrenia Project. This undertaking implicated a region of the human genome not previously suspected as a risk factor for schizophrenia. That finding was bolstered by another of the simultaneously published papers, which showed an even stronger association when the number of subjects was increased to almost 48,000, and identified significant association in two additional genes. The third paper shows that there are likely to be many common gene variations, perhaps hundreds or more, that have small effects in the risk of schizophrenia.

Taken together, “the papers present the first highly significant findings of gene regions associated with schizophrenia risk,” said Levinson, professor of psychiatry and behavioral sciences, director of that department’s Program on the Genetics of Brain Function, and the Walter E. Nichols, MD, Professor in the School of Medicine.

It is already known that schizophrenia — which strikes close to one in every 100 people — has a very strong genetic component, probably accounting for at least 80 percent of risk for this disease. However, unlike sickle-cell anemia or Huntington’s disease, in which a defect at a single genetic location is responsible, most cases of schizophrenia are believed to involve interactions among a multitude of genes, with a variant of any single gene contributing only a tiny bit to a person’s risk.

“That makes it hard to tease out, in a statistically significant way, any of these schizophrenia-associated genes,” said Levinson. But it is feasible with very large numbers of subjects, he said. Finding genes involved in a multigenic trait can, at least in theory, be accomplished by means of so-called genome-wide association studies, in which DNA variations are measured in two large groups of people, one with a common pathology and the other without it.

To achieve the needed sample size, data from three independent studies were pooled and analyzed in a special way that corrected for differences in how those disparate studies were designed and run. Such a methodology is called a meta-analysis. Shi, a research scientist in Levinson’s laboratory, designed and performed the meta-analysis on the resulting pooled-subject group, some 8,000 individuals with schizophrenia and 19,000 normal controls of European ancestry. (Restricting the study population to people of similar ancestry excludes numerous non-disease-related genetic differences that would otherwise be observed, Shi said.)

In 1999, when Levinson and Shi’s study began, genomic technologies were nowhere near as advanced as they are today. But the recent hybridization of Silicon Valley-style microelectronics with biotechnology-bred DNA assay techniques has resulted in powerful new microarrays capable of scanning entire genomes for tiny variations called “single base-pair polymorphisms,” or SNPs.

A DNA base pair is effectively the genome’s smallest possible accounting unit — the penny, as it were, of genetic variation. As a simplified analogy, think of your genetic inheritance as a stack of 3 billion pennies, with each coin bearing one of four mint marks. If you set two such stacks (representing two individuals’ genomes) side by side and compare two adjacent pennies’ mint marks at any given height, they’ll usually be the same. We’re all descendants of a common ancestor, so the similarities in our genomic sequences shouldn’t surprise anyone.

But evolution happens. Every few hundred “pennies” or so, you will observe a divergence, or SNP — one chemical “mint mark” on this genome, another on that one. With the human genome being so huge, this comes to something like 10 million SNPs, of which about a million occur with frequencies of at least 5 percent.

Using commercially available “SNP chips” designed to detect those more-common variants, the investigators looked for differences between the DNA of people with schizophrenia versus the DNA of those without the disease. The scientists required that such differences achieve “genome-wide statistical significance.” Here’s why: If you flip a million coins, one at a time, you’re going to see all kinds of seemingly miraculous events — say, 15 heads in a row — that may seem significant but are typical when you toss even a perfectly balanced coin so many times.

Shi’s job was to devise analytical techniques to determine whether the “finding” of a SNP’s greater likelihood among schizophrenics was real or spurious. The genomic region on chromosome 6 survived this rigorous statistical test.

“These findings show that our genetic methods are working, and that the genetic underpinnings of schizophrenia can be understood,” said Levinson. “Similar methods have produced critical new discoveries in many other common diseases, once very large numbers of people could be studied. Now we see that the same approach works for psychiatric disorders like schizophrenia.”

Pablo Gejman, MD, of Northwestern University was the senior author of the paper. Stanford co-author Alice Whittemore, PhD, professor of health research and policy, consulted on the study’s meta-analytic methodology. The study was funded by the National Institute of Mental Health and by the National Alliance for Research on Schizophrenia and Depression.

By Bruce Goldman