Posted on by Dr. Francis Collins
August is here, and many folks have plans to enjoy a well-deserved vacation this month. I thought you might enjoy taking a closer look during August at the wonder and beauty of the brain here on my blog, even while giving your own brains a rest from some of the usual work and deadlines.
Some of the best imagery—and best science—comes from the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative, a pioneering project aimed at revolutionizing our understanding of the human brain. Recently, the BRAIN Initiative held a “Show Us Your Brain Contest!”, which invited researchers involved in the effort to submit their coolest images. So, throughout this month, I’ve decided to showcase a few of these award-winning visuals.
Let’s start with the first-place winner in the still-image category. What you see above is an artistic rendering of deep brain stimulation (DBS), an approach now under clinical investigation to treat cognitive impairment that can arise after a traumatic brain injury and other conditions.
The vertical lines represent wire leads with a single electrode that has been inserted deep within the brain to reach a region involved in cognition, the central thalamus. The leads are connected to a pacemaker-like device that has been implanted in a patient’s chest (not shown). When prompted by the pacemaker, the leads’ electrode emits electrical impulses that stimulate a network of neuronal fibers (blue-white streaks) involved in arousal, which is an essential component of human consciousness. The hope is that DBS will improve attention and reduce fatigue in people with serious brain injuries that are not treatable by other means.
Andrew Janson, who is a graduate student in Christopher Butson’s NIH-supported lab at the Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, composed this image using a software program called Blender. It’s an open-source, 3D computer graphics program often used to create animated films or video games, but not typically used in biomedical research. That didn’t stop Janson.
With the consent of a woman preparing to undergo experimental DBS treatment for a serious brain injury suffered years before in a car accident, Janson used Blender to transform her clinical brain scans into a 3D representation of her brain and the neurostimulation process. Then, he used a virtual “camera” within Blender to capture the 2D rendering you see here. Janson plans to use such imagery, along with other patient-specific modeling and bioelectric fields simulations, to develop a virtual brain stimulation surgery to predict the activation of specific fiber pathways, depending upon lead location and stimulation settings.
DBS has been used for many years to relieve motor symptoms of certain movement disorders, including Parkinson’s disease and essential tremor. More recent experimental applications include this one for traumatic brain injury, and others for depression, addiction, Alzheimer’s disease, and chronic pain. As the BRAIN Initiative continues to map out the brain’s complex workings in unprecedented detail, it will be exciting to see how such information can lead to even more effective applications of to DBS to help people living with a wide range of neurological conditions.
Deep Brain Stimulation for Movement Disorders (National Institute of Neurological Disorders and Stroke/NIH)
Video: Deep Brain Stimulation (University of Utah, Salt Lake City)
Butson Lab (University of Utah)
Show Us Your Brain! (BRAIN Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke
Posted on by Dr. Francis Collins
Courtesy of the Chen and Macosko labs
A few years ago, I highlighted a really cool technology called Drop-seq for simultaneously analyzing the gene expression activity inside thousands of individual cells. Today, one of its creators, Evan Macosko, reports significant progress in developing even better tools for single-cell analysis—with support from an NIH Director’s New Innovator Award.
In a paper in the journal Science, Macosko, Fei Chen, and colleagues at the Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, recently unveiled another exciting creation called Slide-seq . This technology acts as a GPS-like system for mapping the exact location of each of the thousands of individual cells undergoing genomic analysis in a tissue sample.
This 3D video shows the exquisite precision of this new cellular form of GPS, which was used to generate a high-resolution map of the different cell types found in a tiny cube of mouse brain tissue. Specifically, it provides locations of the cell types and gene expression in the hippocampal regions called CA1 (green), CA2/3 (blue), and dentate gyrus (red).
Because using Slide-seq in the lab requires no specialized imaging equipment or skills, it should prove valuable to researchers across many different biomedical disciplines who want to look at cellular relationships or study gene activity in tissues, organs, or even whole organisms.
How does Slide-seq work? Macosko says one of the main innovations is an inexpensive rubber-coated glass slide nicknamed a puck. About 3 millimeters in diameter, pucks are studded with tens of thousands of 10 micron-sized beads, each one decorated with a random snippet of genetic material—an RNA barcode—that serves as its unique identifier of the bead.
The barcodes are sequenced en masse, and the exact location of each barcoded bead is indexed using innovative software developed by a team led by Chen, who is an NIH Director’s Early Independence awardee.
Then, the researchers place a sample of fresh-frozen tissue (typically, 10 micrometers, or 0.00039 inches, thick) on the puck and dissolve the tissue, lysing the cells and releasing their messenger RNA (mRNA). That leaves only the barcoded beads binding the mRNA transcripts expressed by the cells in the tissue—a biological record of the genes that were turned on at the time the sample was frozen.
The barcoded mRNA is then sequenced. The spatial position of each mRNA molecule can be inferred, using the reference index on the puck. This gives researchers a great deal of biological information about the cells in the tissue, often including their cell type and their gene expression pattern. All the data can then be mapped out in ways similar to those seen in this video, which was created using data from 66 pucks.
Slide-seq has been tested on a range of tissues from both mouse and human, replicating results from similar maps created using existing approaches, but also uncovering new biology. For example, in the mouse cerebellum, Slide-seq allowed the researchers to detect bands of variable gene activity across the tissues. This intriguing finding suggests that there may be subpopulations of cells in this part of the brain that have gene activity influenced by their physical locations.
Such results demonstrate the value of combining cell location with genomic information. In fact, Macosko now hopes to use Slide-seq to study the response of brain cells that are located near the buildup of damaged amyloid protein associated with the early-stage Alzheimer’s disease. Meanwhile, Chen is interested in pursuing cell lineage studies in a variety of tissues to see how and where changes in the molecular dynamics of tissues can lead to disease.
These are just a few examples of how Slide-seq will add to the investigative power of single-cell analysis in the years ahead. In meantime, the Macosko and Chen labs are working hard to develop even more innovative approaches to this rapidly emerging areas of biomedical research, so who knows what “seq” we will be talking about next?
 Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, Welch J, Chen LM, Chen F, Macosko EZ. Science. 2019 Mar 29;363(6434):1463-1467.
Single Cell Analysis (NIH)
Macosko Lab (Broad Institute of Harvard and MIT, Cambridge)
Chen Lab (Broad Institute)
NIH Support: National Institute on Aging; Common Fund
Posted on by Dr. Francis Collins
Millions of people take medications each day for epilepsy, a diverse group of disorders characterized by seizures. But, for about a third of people with epilepsy, current drug treatments don’t work very well. What’s more, the medications are designed to treat symptoms of these disorders, basically by suppressing seizure activity. The medications don’t really change the underlying causes, which are wired deep within the brain.
Gemma Carvill, a researcher at Northwestern University Feinberg School of Medicine, Chicago, wants to help change that in the years ahead. She’s dedicated her research career to discovering the genetic causes of epilepsy in hopes of one day designing treatments that can control or even cure some forms of the disorder .
It certainly won’t be easy. A recent paper put the number of known genes associated with epilepsy at close to 1,000 . However, because some disease-causing genetic variants may arise during development, and therefore occur only within the brain, it’s possible that additional genetic causes of epilepsy are still waiting to be discovered within the billions of cells and their trillions of interconnections.
To find these new leads, Carvill won’t have to rely only on biopsies of brain tissue. She’s received a 2018 NIH Director’s New Innovator Award in search of answers hidden within “liquid biopsies”—tiny fragments of DNA that research in other forms of brain injury and neurological disease  suggests may spill into the bloodstream and cerebrospinal fluid (CSF) from dying neurons or other brain cells following a seizure.
Carvill and team will start with mouse models of epilepsy to test whether it’s possible to detect DNA fragments from the brain in bodily fluids after a seizure. They’ll also attempt to show DNA fragments carry telltale signatures indicating from which cells and tissues in the brain those molecules originate. The hope is these initial studies will also tell them the best time after a seizure to collect blood samples.
In people, Carvill’s team will collect the DNA fragments and begin searching for genetic alterations to explain the seizures, capitalizing on Carvill’s considerable expertise in the use of next generation DNA sequencing technology for ferreting out disease-causing variants. Importantly, if this innovative work in epilepsy pans out, it also can be applied to any other neurological condition in which DNA spills from dying brain cells, including Alzheimer’s disease and Parkinson’s disease.
 Unravelling the genetic architecture of autosomal recessive epilepsy in the genomic era. Calhoun JD, Carvill GL. J Neurogenet. 2018 Sep 24:1-18.
 Epilepsy-associated genes. Wang J, Lin ZJ, Liu L, Xu HQ, Shi YW, Yi YH, He N, Liao WP. Seizure. 2017 Jan;44:11-20.
 Identification of tissue-specific cell death using methylation patterns of circulating DNA. Lehmann-Werman R, Neiman D, Zemmour H, Moss J, Magenheim J, Vaknin-Dembinsky A, Rubertsson S, Nellgård B, Blennow K, Zetterberg H, Spalding K, Haller MJ, Wasserfall CH, Schatz DA, Greenbaum CJ, Dorrell C, Grompe M, Zick A, Hubert A, Maoz M, Fendrich V, Bartsch DK, Golan T, Ben Sasson SA, Zamir G, Razin A, Cedar H, Shapiro AM, Glaser B, Shemer R, Dor Y. Proc Natl Acad Sci U S A. 2016 Mar 29;113(13):E1826-34.
Epilepsy Information Page (National Institute of Neurological Disorders and Stroke/NIH)
Gemma Carvill Lab (Northwestern University Feinberg School of Medicine, Chicago)
Carvill Project Information (NIH RePORTER)
NIH Director’s New Innovator Award (Common Fund)
NIH Support: Common Fund; National Institute of Neurological Disorders and Stroke
Posted on by Dr. Francis Collins
Predicting whether someone will get Alzheimer’s disease (AD) late in life, and how to use that information for prevention, has been an intense focus of biomedical research. The goal of this work is to learn not only about the genes involved in AD, but how they work together and with other complex biological, environmental, and lifestyle factors to drive this devastating neurological disease.
It’s good news to be able to report that an international team of researchers, partly funded by NIH, has made more progress in explaining the genetic component of AD. Their analysis, involving data from more than 35,000 individuals with late-onset AD, has identified variants in five new genes that put people at greater risk of AD . It also points to molecular pathways involved in AD as possible avenues for prevention, and offers further confirmation of 20 other genes that had been implicated previously in AD.
The results of this largest-ever genomic study of AD suggests key roles for genes involved in the processing of beta-amyloid peptides, which form plaques in the brain recognized as an important early indicator of AD. They also offer the first evidence for a genetic link to proteins that bind tau, the protein responsible for telltale tangles in the AD brain that track closely with a person’s cognitive decline.
The new findings are the latest from the International Genomics of Alzheimer’s Project (IGAP) consortium, led by a large, collaborative team including Brian Kunkle and Margaret Pericak-Vance, University of Miami Miller School of Medicine, Miami, FL. The effort, spanning four consortia focused on AD in the United States and Europe, was launched in 2011 with the aim of discovering and mapping all the genes that contribute to AD.
An earlier IGAP study including about 25,500 people with late-onset AD identified 20 common gene variants that influence a person’s risk for developing AD late in life . While that was terrific progress to be sure, the analysis also showed that those gene variants could explain only a third of the genetic component of AD. It was clear more genes with ties to AD were yet to be found.
So, in the study reported in Nature Genetics, the researchers expanded the search. While so-called genome-wide association studies (GWAS) are generally useful in identifying gene variants that turn up often in association with particular diseases or other traits, the ones that arise more rarely require much larger sample sizes to find.
To increase their odds of finding additional variants, the researchers analyzed genomic data for more than 94,000 individuals, including more than 35,000 with a diagnosis of late-onset AD and another 60,000 older people without AD. Their search led them to variants in five additional genes, named IQCK, ACE, ADAM10, ADAMTS1, and WWOX, associated with late-onset AD that hadn’t turned up in the previous study.
Further analysis of those genes supports a view of AD in which groups of genes work together to influence risk and disease progression. In addition to some genes influencing the processing of beta-amyloid peptides and accumulation of tau proteins, others appear to contribute to AD via certain aspects of the immune system and lipid metabolism.
Each of these newly discovered variants contributes only a small amount of increased risk, and therefore probably have limited value in predicting an average person’s risk of developing AD later in life. But they are invaluable when it comes to advancing our understanding of AD’s biological underpinnings and pointing the way to potentially new treatment approaches. For instance, these new data highlight intriguing similarities between early-onset and late-onset AD, suggesting that treatments developed for people with the early-onset form also might prove beneficial for people with the more common late-onset disease.
It’s worth noting that the new findings continue to suggest that the search is not yet over—many more as-yet undiscovered rare variants likely play a role in AD. The search for answers to AD and so many other complex health conditions—assisted through collaborative data sharing efforts such as this one—continues at an accelerating pace.
 Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Kunkle BW, Grenier-Boley B, Sims R, Bis JC, et. al. Nat Genet. 2019 Mar;51(3):414-430.
 Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, DeStafano AL, Bis JC, et al. Nat Genet. 2013 Dec;45(12):1452-8.
Alzheimer’s Disease Genetics Fact Sheet (National Institute on Aging/NIH)
Margaret Pericak-Vance (University of Miami Health System, FL)
NIH Support: National Institute on Aging; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Diabetes and Digestive and Kidney Disease; National Institute of Neurological Disorders and Stroke
Posted on by Dr. Francis Collins
In addition to memory loss and confusion, many people with Alzheimer’s disease have trouble sleeping. Now an NIH-funded team of researchers has evidence that the reverse is also true: a chronic lack of sleep may worsen the disease and its associated memory loss.
The new findings center on a protein called tau, which accumulates in abnormal tangles in the brains of people with Alzheimer’s disease. In the healthy brain, active neurons naturally release some tau during waking hours, but it normally gets cleared away during sleep. Essentially, your brain has a system for taking the garbage out while you’re off in dreamland.
The latest findings in studies of mice and people further suggest that sleep deprivation upsets this balance, allowing more tau to be released, accumulate, and spread in toxic tangles within brain areas important for memory. While more study is needed, the findings suggest that regular and substantial sleep may play an unexpectedly important role in helping to delay or slow down Alzheimer’s disease.
It’s long been recognized that Alzheimer’s disease is associated with the gradual accumulation of beta-amyloid peptides and tau proteins, which form plaques and tangles that are considered hallmarks of the disease. It has only more recently become clear that, while beta-amyloid is an early sign of the disease, tau deposits track more closely with disease progression and a person’s cognitive decline.
Such findings have raised hopes among researchers including David Holtzman, Washington University School of Medicine, St. Louis, that tau-targeting treatments might slow this devastating disease. Though much of the hope has focused on developing the right drugs, some has also focused on sleep and its nightly ability to reset the brain’s metabolic harmony.
In the new study published in Science, Holtzman’s team set out to explore whether tau levels in the brain naturally are tied to the sleep-wake cycle . Earlier studies had shown that tau is released in small amounts by active neurons. But when neurons are chronically activated, more tau gets released. So, do tau levels rise when we’re awake and fall during slumber?
The Holtzman team found that they do. The researchers measured tau levels in brain fluid collected from mice during their normal waking and sleeping hours. (Since mice are nocturnal, they sleep primarily during the day.) The researchers found that tau levels in brain fluid nearly double when the animals are awake. They also found that sleep deprivation caused tau levels in brain fluid to double yet again.
These findings were especially interesting because Holtzman’s team had already made a related finding in people. The team found that healthy adults forced to pull an all-nighter had a 30 percent increase on average in levels of unhealthy beta-amyloid in their cerebrospinal fluid (CSF).
The researchers went back and reanalyzed those same human samples for tau. Sure enough, the tau levels were elevated on average by about 50 percent.
Once tau begins to accumulate in brain tissue, the protein can spread from one brain area to the next along neural connections. So, Holtzman’s team wondered whether a lack of sleep over longer periods also might encourage tau to spread.
To find out, mice engineered to produce human tau fibrils in their brains were made to stay up longer than usual and get less quality sleep over several weeks. Those studies showed that, while less sleep didn’t change the original deposition of tau in the brain, it did lead to a significant increase in tau’s spread. Intriguingly, tau tangles in the animals appeared in the same brain areas affected in people with Alzheimer’s disease.
Another report by Holtzman’s team appearing early last month in Science Translational Medicine found yet another link between tau and poor sleep. That study showed that older people who had more tau tangles in their brains by PET scanning had less slow-wave, deep sleep .
Together, these new findings suggest that Alzheimer’s disease and sleep loss are even more intimately intertwined than had been realized. The findings suggest that good sleep habits and/or treatments designed to encourage plenty of high quality Zzzz’s might play an important role in slowing Alzheimer’s disease. On the other hand, poor sleep also might worsen the condition and serve as an early warning sign of Alzheimer’s.
For now, the findings come as an important reminder that all of us should do our best to get a good night’s rest on a regular basis. Sleep deprivation really isn’t a good way to deal with overly busy lives (I’m talking to myself here). It isn’t yet clear if better sleep habits will prevent or delay Alzheimer’s disease, but it surely can’t hurt.
 The sleep-wake cycle regulates brain interstitial fluid tau in mice and CSF tau in humans. Holth JK, Fritschi SK, Wang C, Pedersen NP, Cirrito JR, Mahan TE, Finn MB, Manis M, Geerling JC, Fuller PM, Lucey BP, Holtzman DM. Science. 2019 Jan 24.
 Reduced non-rapid eye movement sleep is associated with tau pathology in early Alzheimer’s disease. Lucey BP, McCullough A, Landsness EC, Toedebusch CD, McLeland JS, Zaza AM, Fagan AM, McCue L, Xiong C, Morris JC, Benzinger TLS, Holtzman DM. Sci Transl Med. 2019 Jan 9;11(474).
Alzheimer’s Disease and Related Dementias (National Institute on Aging/NIH)
Holtzman Lab (Washington University School of Medicine, St. Louis)
NIH Support: National Institute on Aging; National Institute of Neurological Disorders and Stroke; National Center for Advancing Translational Sciences; National Cancer Institute; National Institute of Biomedical Imaging and Bioengineering