Nature Knows and Psionic Success

Researchers at Kyushu University have discovered that turning brain immune cells into neurons successfully restores brain function after stroke-like injury in mice. These findings, published on October 10 in PNAS, suggest that replenishing neurons from immune cells could be a promising avenue for treating stroke in humans.

Stroke, and other cerebrovascular diseases, occur when blood flow to the brain is affected, causing damage to neurons. Recovery is often poor, with patients suffering from severe physical disabilities and cognitive problems. Worldwide, it’s one of the most common causes for needing long-term care. When we get a cut or break a bone, our skin and bone cells can replicate to heal our body. But the neurons in our brain cannot easily regenerate, so the damage is often permanent. We therefore need to find new ways to replace lost neurons.” Professor Kinichi Nakashima, from Kyushu University’s Graduate School of Medical Sciences One possible strategy is to convert other cells in the brain into neurons. Here, the researchers focused on microglia, the main immune cells in the central nervous system. Microglia are tasked with removing damaged or dead cells in the brain, so after a stroke, they move towards the site of injury and replicate quickly.

“Microglia are abundant and exactly in the place we need them, so they are an ideal target for conversion,” says first author, Dr. Takashi Irie from Kyushu University Hospital.

In prior research, the team demonstrated that they could induce microglia to develop into neurons in the brains of healthy mice. Now, Dr. Irie and Professor Nakashima, along with Lecturer Taito Matsuda and Professor Noriko Isobe from Kyushu University Graduate School of Medical Sciences, showed that this strategy of replacing neurons also works in injured brains and contributes to brain recovery.

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To conduct the study, the researchers caused a stroke-like injury in mice by temporarily blocking the right middle cerebral artery – a major blood vessel in the brain that is commonly associated with stroke in humans. A week later, the researchers examined the mice and found that they had difficulties in motor function and had a marked loss of neurons in a brain region known as the striatum. This part of the brain is involved in decision making, action planning and motor coordination.

The researchers then used a lentivirus to insert DNA into microglial cells at the site of the injury. The DNA held instructions for producing NeuroD1, a protein that induces neuronal conversion. Over the subsequent weeks, the infected cells began developing into neurons and the areas of the brain with neuron loss decreased. By eight weeks, the new induced neurons had successfully integrated into the brain’s circuits.

At only three weeks post-infection, the mice showed improved motor function in behavioral tests. These improvements were lost when the researchers removed the new induced neurons, providing strong evidence that the newly converted neurons directly contributed to recovery.

“These results are very promising. The next step is to test whether NeuroD1 is also effective at converting human microglia into neurons and confirm that our method of inserting genes into the microglial cells is safe,” says Professor Nakashima.

Furthermore, the treatment was conducted in mice in the acute phase after stroke, when microglia were migrating to and replicating at the site of injury. Therefore, the researchers also plan to see if recovery is also possible in mice at a later, chronic phase.

Source:

Kyushu University

Journal reference:

Irie, T., et al. (2023). Direct neuronal conversion of microglia/macrophages reinstates neurological function after stroke. PNAS . doi.org/10.1073/pnas.2307972120 .

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Insights into thousands of types of brain cell could improve understanding of diseases and cognition. Credit: Researchers have created the largest atlas of human brain cells so far, revealing more than 3,000 cell types — many of which are new to science. The work, published in a package of 21 papers today in Science , Science Advances and Science Translational Medicine , will aid the study of diseases, cognition and what makes us human, among other things, say the authors.

The enormous cell atlas offers a detailed snapshot of the most complex known organ. “It’s highly significant,” says Anthony Hannan, a neuroscientist at the Florey Institute of Neuroscience and Mental Health in Melbourne, Australia. Researchers have previously mapped the human brain using techniques such as magnetic resonance imaging, but this is the first atlas of the whole human brain at the single-cell level, showing its intricate molecular interactions, adds Hannan. “These types of atlases really are laying the groundwork for a much better understanding of the human brain.”

The research is part of the US National Institutes of Health’s Brain Research through Advancing Innovative Neurotechnologies Initiative — Cell Census Network (BICCN), a collaboration between hundreds of scientists. The programme’s goals include cataloguing brain cell types across humans, non-human primates and mice to improve understanding of the cellular mechanisms behind poorly understood brain disorders. The data from the 21 studies have been made publicly available on the Neuroscience Multi-omic Archive online repository. Cellular menagerie

Kimberly Siletti, a neuroscientist now at the University Medical Center Utrecht in the Netherlands, and her team laid the cornerstone for the atlas by sequencing the RNA of more than 3 million individual cells from 106 locations covering the entire human brain, using tissue samples from three deceased male donors. They also included one motor cortex dissection from a female donor that had been used in previous studies. Their analysis documented 461 broad categories of brain cell that included more than 3,000 subtypes. “I was surprised at how many different cell types there were,” says Siletti.

Neurons — cells in the brain and nervous system that send and receive signals — varied widely in different parts of the brain, suggesting different functions and developmental histories. The mix of neurons and other cell types also differed across each region; some cells were only found in specific locations. The brainstem — a relatively under-studied structure connecting the brain to the spinal cord — harboured a particularly high number of neuron types, says study co-author Sten Linnarsson, a molecular systems biologist at the Karolinska Institute in Stockholm, Sweden. “One of the big surprises here is how incredibly complex the brainstem is.”

Other studies drilled into the mechanisms of gene regulation and expression in different cells. Joseph Ecker, a molecular biologist at the Salk Institute for Biological Studies in La Jolla, California, and his colleagues investigated the brain through an epigenetic lens using tissue samples from the same three donors. They analysed chemical markers that switch genes on or off in more than 500,000 individual cells. The various molecules that acted as switches enabled the team to identify nearly 200 brain cell types. Even the same gene in the same type of cell could have different characteristics across the brain. One gene was turned on with one switch at the front of the brain and with another at the back. “There are remarkable regional differences,” says study co-author Wei Tian, a computational biologist at the Salk Institute.

Pinpointing the switches that activate or block gene expression in brain cells could be useful for diagnosing brain disorders and developing tailored treatments, says Ecker. “That’s another tool that comes out of the toolbox we’re building,” he says. Disease risk

Improving understanding of how genetic switches might contribute to disease risk was also a focus for Bing Ren, a molecular biologist at the University of California, San Diego, and his team. They analysed how more than one million brain cells from the three donors access and use genetic information. The researchers uncovered links between certain brain cell types and neuropsychiatric disorders, including bipolar disorder, depression and schizophrenia.

Ren and his colleagues used the cell-type data to predict how the genetic switches influence gene regulation and increase the risk of neurological diseases. For instance, in cells called microglia , which clear away dead or damaged cells, the presence of some genetic switches was strongly linked to risks of Alzheimer’s disease. Such findings can be used to test whether particular genes or faulty switches contribute directly to the onset of disease. “This is made possible because we have — for the first time — delineated the genetic switches for hundreds of different cell types,” says Ren.

The next step for the BICCN team is to sequence more cells from all parts of the brain, says Ren. The researchers will also work with more tissue samples to build a picture of how the human brain can vary across populations and age groups. “This is only the beginning,” says Ren.

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This is a modal window. This modal can be closed by pressing the Escape key or activating the close button. In 21 papers published as a package Thursday, researchers have provided a new map of the human brain, refining the resolution, as one scientist described it, from a rough outline of a shoreline to a satellite view with topography.

They’re still far from a GPS guide to what’s inside our skulls. However, the new brain cell atlas offers more guidance for researchers desperate to find effective treatments for a wide range of disorders, including addiction, schizophrenia and Alzheimer’s.

The studies are part of the National Institute of Health’s BRAIN Initiative Cell Census Network, a five-year program launched in 2017 to create a catalog of brain cell types.

In the new studies, published Thursday in “Science” and related journals , the researchers identified more than 3,000 kinds of cells ‒ an order of magnitude beyond what scientists have known before.

“It’s the most complex cellular organ and we just haven’t had this basic understanding,” said Ed Lein, a senior investigator at the Allen Institute for Brain Science, who helped lead several of the studies. “If we don’t have a good understanding of the system, we’re not going to be able to treat diseases, to understand what really goes wrong.” Implications for disease research

These new maps are particularly useful for understanding the territory of brain diseases such as cancer, said Sten Linnarsson, a leader of some of the research and a professor of molecular systems biology at the Karolinska Institute in Sweden.

Cancer cells follow the same genetic programs found in normal brain cells, but in a distorted way, he said. Some cancer cells seem to repeat the pattern of early brain development, almost growing a new brain within a brain, he said. In other cancer cells, genes involved in wound healing are turned on, as if the brain senses there is something wrong and activates repair mechanisms.

We can get clues about how brain tumors behave, Linnarsson said, by comparing a brain with cancer to the “very organized architecture of the healthy, normal brain and brain development.”

Some of that was understood before, he said, but now researchers have a much higher resolution and more systematic map with a lot more cell types. Before, scientists could identify that there were cells called astrocytes involved; now, they can identify different kinds of astrocytes in different parts of the brain operating with different genetic programs.

“It will be the job for future work to figure out what that means for disease,” Linnarsson said.

Bing Ren, another research leader, said the brain atlas will allow researchers to compare healthy brains to the brains of people with neurological disorders, including schizophrenia, Alzheimer’s and addiction, and could eventually lead to advances in diagnoses and treatment.

Understanding which cells are involved and which genes are turned on and off in different brain conditions should allow more precise diagnoses for disorders that are now mainly identified by their symptoms, said Ren, also a professor at the University of California, San Diego. It can be difficult to test drugs for conditions like autism for which there is no objective diagnosis or measure of improvement; genetic analysis could provide that measure.

“The goal of the brain initiative is to really break that barrier and gain a fundamental understanding of the complex neurological disease mechanisms and to begin to develop strategies to mitigate such disorders,” Ren said. Delving deep into the brain

Just as sequencing the human genome was only the beginning of being able to understand the role of genes, so this map is just the first step toward understanding the brain, Ren said. “Interpreting the information is now the hard part.”

Every human brain has roughly 200 billion neurons ‒ the brain cells that send electrical signals.

When he was in college in the ’90s, Ren said, he was taught there were two types of neurons. In his new study, in which he and his colleagues examined 1.1 million brain cells, they found more than 90 different types of neurons ‒ but he suspects there might be thousands. “And we don’t have a very good idea of what they are and what they do.”

Plus, neurons are only one type of brain cell. Non-neuronal cells outnumber neurons by 5 or 10 to 1.

“We are looking at complicated brain maps and trying to gain a first glance of the variety of the cell types in the human brain in terms of their cell type identity, in terms of their anatomic locations and in terms of their connections among each other,” he said. “That’s a monumental job. We have to do it step by step.” Where the brains come from

Most brain research is done on tissue from people who agree to donate their brains after death.

Some of the studies in this package were also conducted on tissue donated by living patients who had brain surgery for epilepsy or cancer.

Laboratory tools now exist to enable never-before feasible genetic analysis of living tissue, said Lein from the Allen Insitute.”Part of what this package (of studies) is about is showing that the modern tools of the field that are normally only used in mouse can all now be applied to human,” he said. “It kind of opens up a whole new era of human neuroscience research where we can ask questions at a whole different level of granularity than has ever been possible.” How our brains compare to our cousins’ Several of the papers compared the human brain to the brains of our closest animal cousins, chimpanzees, gorillas, rhesus macaques, and common marmosets. Cell types are similar across primate brains, the studies found, but genetic activity differs among species.”The genes that really differentiate us from our closest relatives are related to the wiring of the brain and the function of neurocircuits,” Lein said.Evolution has sped up a bit in humans relative to primates, said Dr. Trygve Bakken, […]

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The ultimate goal of a new atlas of the brain released by researchers is to better understand the workings of the human brain — and what goes wrong in the range of neurological and psychiatric conditions that plague humans, from Alzheimer’s to depression to schizophrenia. Photo by cottonbro studio/Pexels After a massive five-year effort, researchers have unveiled an “atlas” that gives an unprecedented look at the intricacies of the human brain.

The atlas , which will be available to researchers everywhere, can be seen as similar to the atlases we all know: a book of maps.

But this one catalogues human brain cells and their striking diversity and complexity. Going forward, the atlas will help other researchers “navigate” the brain, said Bing Ren , a professor at the University of California, San Diego, who was part of the research effort.

The atlas encompasses more than 3,000 types of brain cells, and gives insight into how they vary from one person to another, how they differ from non-human primates’ brain cells, how particular brain cell types are related to specific diseases, and more.

The ultimate goal, Ren and other experts said, is to better understand the workings of the human brain — and what goes wrong in the range of neurological and psychiatric conditions that plague humans, from Alzheimer’s to depression to schizophrenia.

The publication of the brain cell atlas, Ren said, “is just the beginning.”

The work is detailed in a collection of 21 papers being published Friday in the journals Science, Science Advances and Science Translational Medicine. In all, the project involved hundreds of scientists from different countries, brought together under the U.S. National Institutes of Health’s BRAIN Initiative program.

The ambitious project was possible thanks to new technology that allows scientists to study features and functions of individual cells.

That kind of deep understanding of brain cells could eventually lead to new, highly targeted treatments for neuropsychiatric conditions — including ones no one has thought of yet, said Dr. Panos Roussos , a professor at Mount Sinai’s Icahn School of Medicine in New York City, who worked on the project.

Many current medications for those diseases target neurotransmitters, chemicals that help brain cells communicate.

They help many people, but also “leave many others behind,” said Dr. Jeffrey Borenstein , president of the nonprofit Brain and Behavior Research Foundation in New York City.

Borenstein, who was not involved in the atlas project, called it “very important work.”

“It lays the foundation for scientists to better understand how the brain works, in both health and states of disease,” he said. “I think this offers tremendous hope for people who are living with psychiatric illnesses.”

Human brain cells, it’s fair to say, are diverse and complex. Each cell in the brain has the same DNA sequence, but different cell types use different genes, and in different amounts.

To give it an analogy, Ren said brain cells can be regarded as people living in different parts of the world: Depending on where they end up residing in the brain, they speak different languages.

A broad goal, Ren and Roussos said, is to better understand how those different brain cell types interact with one another, in health and in sickness, and to identify the cell types that are relevant to any given disease.

In their study, Ren’s team analyzed three human brains, looking in detail at more than 1 million cells in 42 brain regions. They identified 107 different brain cell subtypes, then were able to correlate certain aspects of cells’ molecular biology to specific diseases — including schizophrenia, bipolar disorder and Alzheimer’s disease.

Roussos and his colleagues, meanwhile, studied brain tissue from across the life span, from fetal development to adulthood. That’s critical, Roussos said, since different neuropsychiatric conditions have different ages of onset.

They, too, were able to map certain brain cell types to specific diseases. That included associations that were previously unknown — including linking Tourette syndrome to cells called oligodendrocytes and obsessive-compulsive disorder to astrocytes.

“If you know which cell type is related to a disease, then you can make hypotheses on causes,” Ren said.

He noted that his work, like some studies before it, point to the importance of cells called microglia in Alzheimer’s. Microglia are resident immune cells in the brain, and Ren and other researchers suspect that an abnormal set of “super-activated” microglia play a central role in causing Alzheimer’s, by attacking the brain’s neurons.

“So is there some way we can tone down that over-activation?” Ren said.

Among the project’s other findings: Researchers at the Allen Institute for Brain Science, in Washington, D.C., and other centers studied which genes are “turned on” in individual cells in the human brain — allowing them to categorize more than 3,000 different kinds of brain cells.

Individuals vary widely in their proportions of different kinds of brain cells, and in which genes are active within those cells.

Humans share the same basic brain cell type “architecture” with our closest primate relatives, chimpanzees and gorillas. Where we differ is in which genes those cells “use.” Specifically, those differences are seen in genes that allow brain cells to connect and form circuits.

In a statement, Dr. John Ngai , director of the NIH BRAIN Initiative, said the program’s scientific collaborations are “propelling the field forward at an exponential pace.””The progress, and possibilities, have been simply breathtaking,” he said. More information The U.S. National Institutes of Health has a primer on brain basics. Copyright © 2023 HealthDay. All rights reserved.

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Summary: Utilizing artificial intelligence, researchers developed “HistoAge,” an algorithm predicting age at death and unraveling the enigmas of brain aging and neurodegenerative disorders.

By analyzing nearly 700 digitized hippocampal sections from elderly brain donors, the tool forecasts age with striking accuracy and identifies regions susceptible to age-related changes. Remarkably, HistoAge demonstrated a potent correlation with cognitive impairment and Alzheimer’s-type abnormalities, providing a reliable metric for exploring neurodegenerative progression.

This innovative model presents a transformative lens for understanding the aging brain, marking a substantial stride toward decoding and potentially curbing age-accelerated neurodegeneration.

Key Facts:

> Innovative Aging Prediction: The HistoAge algorithm predicts age at death with an average accuracy of within 5.45 years by analyzing the cellular composition of human brain tissue specimens.

HistoAge and Neurological Associations: HistoAge-based age acceleration shows strong associations with cognitive impairment, cerebrovascular disease, and Alzheimer’s-type protein aggregation, outpacing current age acceleration measures like DNA methylation.

AI as a Revolutionary Tool: Not only does HistoAge offer a novel paradigm in evaluating aging and neurodegeneration in human samples, but it also brings forward a robust and unbiased metric that is deployable at scale in research labs, thereby facilitating a deeper understanding of cellular changes underlying degenerative diseases.

Source: Mount Sinai

The aging brain undergoes structural and cellular changes that can impact function and increase susceptibility to neurodegenerative disorders like Alzheimer’s disease.

Age acceleration—or the differences between biological and chronological age—in the brain can reveal insights about mechanisms and normal functions of one of the body’s most important organs. They used the difference between the model-predicted age and actual age to derive the amount of age acceleration in the brain. Credit: Neuroscience News It can also explain age-related changes and functional decline, as well as identify early changes related to diseases, indicating the onset of a brain disorder.

Mount Sinai researchers say they have, for the first time ever, used AI to develop an algorithm they term “HistoAge” which predicts age at death based on the cellular composition of human brain tissue specimens with an average accuracy of within 5.45 years. This powerful tool can also identify neuroanatomical regions vulnerable to age-related changes, an indicator of potential cognitive diseases.

How :

The researchers examined a collection of almost 700 digitized images of slides with human hippocampal sections from aged brain donors to develop the histological brain age estimation algorithm.

The hippocampus is known to be involved in both brain aging and age-dependent neurodegenerative diseases, and thus is an ideal region for this analysis.

The team then trained a machine learning model to estimate a person’s age at death based solely on the digitized section, a task that is impossible for a human observer to perform with any degree of accuracy. They used the difference between the model-predicted age and actual age to derive the amount of age acceleration in the brain.

Results :

When compared with current measures of age acceleration (e.g., DNA methylation), they found that HistoAge-based age acceleration had stronger associations with cognitive impairment, cerebrovascular disease, and the levels of Alzheimer’s-type abnormal degenerative protein aggregation.

The study found that the HistoAge model is a reliable, independent metric for determining brain age and understanding factors that drive neurodegeneration over time.

Why the Research Is Interesting :

The researchers said the HistoAge model, and other subsequent similar algorithms, represent an entirely new paradigm for assessing aging and neurodegeneration in human samples and can easily be deployed at scale in clinical and translational research laboratories. Further, this approach provides more rigorous, unbiased and robust metrics of cellular changes underlying degenerative diseases.

The team will next build a multicenter collaboration to develop a large AI-ready dataset that will be used to develop even more powerful AI models that have the potential to transform and enhance our understanding of brain diseases.

Said Mount Sinai’s Dr. Crary of the research: “AI’s disruptive influence on brain research is a paradigm shift propelling us towards the next generation of cures. The HistoAge model will enable us to uncover crucial causal aspects of debilitating brain diseases such as Alzheimer’s disease.”

Said Mount Sinai’s Dr. Farrell of the research: “Using the latest computational approaches, like AI, on human tissue samples from Mount Sinai’s vast and diverse collections is a shift in the way we assess human diseases. Our novel HistoAge model is just one example of the way AI is paving the way for further discovery about the mechanisms of aging and neurodegeneration.

“Clinical scientists are increasingly using AI in research and diagnostic settings. It’s a tool that is revolutionizing medicine and we are excited to be leaders in this space, optimizing machine learning—not to replace our Health System’s commitment to compassionate care, but to improve diagnosis and treatment for all patients.”

Said Mount Sinai’s Dr. Marx of the research: “This model opens the floodgates for a slew of fascinating and essential analyses that bring us closer to finally understanding the aging brain and age-related brain diseases such as Alzheimer’s. This is the first time we have been able to put a number to how much aging there is in the brain in pathology.

“With this approach, we can discover genes that protect against brain aging or genes that make aging worse in the brain, as well as discover the environmental risk factors that make individuals’ brains age faster.” Funding: The study was supported by funding from the National Institutes of Health (R01AG054008, R01NS095252, R01AG060961, R01NS086736, P30AG066514, P50AG005138, R01AG062348, U24MH100931, and K01AG070326), Alzheimer’s Disease Research Center (P30 AG066514), the Winspear Family Center for Research on the Neuropathology of Alzheimer Disease, Rainwater Charitable Foundation / Tau Consortium, and a generous gift from Stuart Katz and Jane Martin. Researchers from the University of Pennsylvania and Boston University contributed to this study. About this AI and brain aging research Author: Stacy Anderson Source: Mount Sinai Hospital Contact: Stacy Anderson – Mount Sinai Hospital Image: The image is credited to Neuroscience News Original Research: Open access. “ Histopathologic Brain Age Estimation via Multiple Instance Learning ” by John F. Crary et al. Acta Neuropathologica Abstract Histopathologic Brain Age Estimation via Multiple […]

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