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Huge brain study uncovers ‘buried’ genetic networks linked to mental illness

December 13, 2018 This article courtesy of Nature News.

Enormous genomic analysis yields tantalizing insights into mechanisms behind conditions such as schizophrenia and bipolar disorder.

Brain conditions such as schizophrenia and autism spectrum disorder have long been known to have an inherited component, but pinpointing how gene variants contribute to disease has been a major challenge. Now, some of the first findings from the most comprehensive genomic analysis of the human brain ever undertaken are shedding light on the roots of these disorders.

Among the discoveries are elements buried in the genome’s ‘dark matter’ that seem to regulate gene expression. Researchers have also uncovered previously unidentified networks of genes and the buried elements, which might contribute to the chances of developing such disorders.

“We’re not claiming in the remotest way to have figured out the underlying mechanism of these diseases, or how you would go about designing drugs, but we are highlighting genes, pathways and also cell types that are associated with these diseases,” says Mark Gerstein, a molecular biophysicist at Yale University in New Haven, Connecticut, who was involved in a number of the project’s studies, selection of which were published this week in Science.

Unlike disorders caused by mutations in a single gene — such as cystic fibrosis or some types of muscular dystrophy — neuropsychiatric disorders including schizophrenia involve hundreds of genes that interact with environmental factors. Each gene contributes only a small amount to the overall disease risk.

Over the past decade, scientists have identified numerous genetic variants that are associated with such disorders. But in many cases, it is not clear how the sequence changes alter gene function — if at all. “Typically, when we do a genetic study, we might find 50 associated genetic variants all clustered in the same region of the genome, and maybe only one of them is directly influencing the risk of disease,” says Michael O’Donovan, a psychiatric geneticist at Cardiff University, UK.

Further complicating matters, some of these variants fall in regions of DNA that do not code for proteins. Until the past few years, scientists presumed these areas to be wastelands. But buried within them are the codes for elements that regulate gene expression, such as transcription factors and microRNAs, which can also have a powerful influence on a person’s disease risk.

Beyond the genes

The PsychENCODE Consortium, which was founded by the US National Institutes of Health in 2015, aims to join the dots between these genetic associations and actual changes in gene function, by taking samples of brain tissue from thousands of cadavers and studying them using multiple genomic-sequencing techniques. “We know that [common neuropsychiatric] diseases are extremely heritable, but people still don’t have a good idea of mechanism; the goal is to use functional genomics to try to figure out what’s going on,” says Gerstein.

One of these studies combined multiple types of sequencing data from brain tissue taken from 1,866 dead people, as well as from single brain-cell types. Previous studies have revealed widespread variation in gene expression between brains, but by comparing sequencing data from specific cell types with that from whole brains, the team established that around 90% of this variance is related to the relative proportion of different cell types in individuals’ brains — something that seems to vary with age, and in conditions such as autism. “We could even figure out key genetic variants that were linked to increases in these cell types,” says Gerstein.

The researchers also used these data to draw connections between specific genes and noncoding DNA variants that had previously been linked to neuropsychiatric disease. This narrows the search for those that actually influence how genes function and seem to be contributing directly to conditions such as schizophrenia. “Some of these genes and cell types are well known, but there are also some new ones that we find, that people could potentially follow up on,” Gerstein adds.

The growing brain

Gerstein and his colleagues also explored how gene expression; chemical, or ‘epigenetic’, modifications to genes that can alter their expression; and regulatory elements in various regions of the brain vary during brain development, using samples of tissue and single cells taken from 60 brains. They found that the greatest variation in gene expression occurs during fetal development and adolescence, which are known to be crucial periods for brain development.

During these periods, genes previously associated with neuropsychiatric disease risk seem to form networks in certain brain regions. This could provide new insights into when and where to study these disease mechanisms and model them, says Nenad Sestan, a neuroscientist also at Yale, whose lab led this study.

In a separate paper, other members of the PsychENCODE Consortium focused on the potential role that gains or losses of large chunks of DNA sequences called copy number variations (CNVs) might have in neuropsychiatric disease. Previous studies have suggested that rare CNVs can strongly affect schizophrenia risk, although the mechanism by which they do so is unclear.

“In the past, we have always concentrated on CNVs affecting protein-coding genes, but there has been a blind spot which is CNVs in regions containing long-noncoding RNAs,” says Chunyu Liu, a specialist in psychiatry and behavioural sciences at SUNY Upstate Medical University in Syracuse, New York, who led this study. Although such molecules show no protein-coding potential, some of them are still capable of regulating gene expression and might contribute to schizophrenia risk in their own right.

Liu and his colleagues analysed brain tissue from 259 cadavers, focusing on long-noncoding RNAs (lncRNAs) in ten CNV-deletion regions that have previously been associated with an elevated risk of schizophrenia, looking to see if the expression of any of them correlated with that of protein-coding genes, which might imply a relationship. This led them to several lncRNAs that they suspect might help to regulate gene expression. One was called DGCR5; further experiments in neural progenitor cells revealed that it serves as a hub for several schizophrenia-related genes, potentially explaining why its absence is associated with an increased risk of the disease.

In a related study, Liu and his colleagues analysed brain tissue from people with schizophrenia or bipolar disorder, and from healthy controls. They looked for microRNAs whose expression correlated with that of protein-coding genes. This led them to a network of microRNAs, transcription factors and genes that seem to work together to influence schizophrenia risk. By focusing on such networks, rather than simply on the influence of single genes, Liu hopes to improve understanding of the root causes of complex diseases such as schizophrenia. Even so, he emphasizes that this is just the beginning of a long journey to understand how variation in such regions affects gene expression, and how this, in turn, contributes to disease risk.

O’Donovan agrees. “These publications are important, but they do not provide the definitive answer to how genetic changes contribute to brain diseases,” he says. “These are reasonably substantial steps, but they are just steps — although we do hope that a lot more work of this sort will help us link the genetics to the biology of these disorders.”

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