Creative Minds: Using Machine Learning to Understand Genome Function

Anshul Kundaje

Anshul Kundaje / Credit: Nalini Kartha

Science has always fascinated Anshul Kundaje, whether it was biology, physics, or chemistry. When he left his home country of India to pursue graduate studies in electrical engineering at Columbia University, New York, his plan was to focus on telecommunications and computer networks. But a course in computational genomics during his first semester showed him he could follow his interest in computing without giving up his love for biology.

Now an assistant professor of genetics and computer science at Stanford University, Palo Alto, CA, Kundaje has received a 2016 NIH Director’s New Innovator Award to explore not just how the human genome sequence encodes function, but also why it functions in the way that it does. Kundaje even envisions a time when it might be possible to use sophisticated computational approaches to predict the genomic basis of many human diseases.

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New Imaging Approach Reveals Lymph System in Brain

Considering all the recent advances in mapping the complex circuitry of the human brain, you’d think we’d know all there is to know about the brain’s basic anatomy. That’s what makes the finding that I’m about to share with you so remarkable. Contrary to what I learned in medical school, the body’s lymphatic system extends to the brain—a discovery that could revolutionize our understanding of many brain disorders, from Alzheimer’s disease to multiple sclerosis (MS).

Researchers from the National Institute of Neurological Disorders and Stroke (NINDS), the National Cancer Institute (NCI), and the University of Virginia, Charlottesville made this discovery by using a special MRI technique to scan the brains of healthy human volunteers [1]. As you see in this 3D video created from scans of a 47-year-old woman, the brain—just like the neck, chest, limbs, and other parts of the body—possesses a network of lymphatic vessels (green) that serves as a highway to circulate key immune cells and return metabolic waste products to the bloodstream.

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Creative Minds: Mapping the Biocircuitry of Schizophrenia and Bipolar Disorder

Bruce Yankner

Bruce Yankner

As a graduate student in the 1980s, Bruce Yankner wondered what if cancer-causing genes switched on in non-dividing neurons of the brain. Rather than form a tumor, would those genes cause neurons to degenerate? To explore such what-ifs, Yankner spent his days tinkering with neural cells, using viruses to insert various mutant genes and study their effects. In a stroke of luck, one of Yankner’s insertions encoded a precursor to a protein called amyloid. Those experiments and later ones from Yankner’s own lab showed definitively that high concentrations of amyloid, as found in the brains of people with Alzheimer’s disease, are toxic to neural cells [1].

The discovery set Yankner on a career path to study normal changes in the aging human brain and their connection to neurodegenerative diseases. At Harvard Medical School, Boston, Yankner and his colleague George Church are now recipients of an NIH Director’s 2016 Transformative Research Award to apply what they’ve learned about the aging brain to study changes in the brains of younger people with schizophrenia and bipolar disorder, two poorly understood psychiatric disorders.

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Creative Minds: A Transcriptional “Periodic Table” of Human Neurons

neuronal cell

Caption: Mouse fibroblasts converted into induced neuronal cells, showing neuronal appendages (red), nuclei (blue) and the neural protein tau (yellow).
Credit: Kristin Baldwin, Scripps Research Institute, La Jolla, CA

Writers have The Elements of Style, chemists have the periodic table, and biomedical researchers could soon have a comprehensive reference on how to make neurons in a dish. Kristin Baldwin of the Scripps Research Institute, La Jolla, CA, has received a 2016 NIH Director’s Pioneer Award to begin drafting an online resource that will provide other researchers the information they need to reprogram mature human skin cells reproducibly into a variety of neurons that closely resemble those found in the brain and nervous system.

These lab-grown neurons could be used to improve our understanding of basic human biology and to develop better models for studying Alzheimer’s disease, autism, and a wide range of other neurological conditions. Such questions have been extremely difficult to explore in mice and other animal models because they have shorter lifespans and different brain structures than humans.

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Antibody Makes Alzheimer’s Protein Detectable in Blood

Antibodies to Tau

Caption: The protein tau (green) aggregates abnormally in a brain cell (blue). Tau spills out of the cell and enters the bloodstream (red). Research shows that antibodies (blue) can capture tau in the blood that reflect its levels in the  brain.
Credit: Sara Moser

Age can bring moments of forgetfulness. It can also bring concern that the forgetfulness might be a sign of early Alzheimer’s disease. For those who decide to have it checked out, doctors are likely to administer brief memory exams to assess the situation, and medical tests to search for causes of memory loss. Brain imaging and spinal taps can also help to look for signs of the disease. But an absolutely definitive diagnosis of Alzheimer’s disease is only possible today by examining a person’s brain postmortem. A need exists for a simple, less-invasive test to diagnose Alzheimer’s disease and similar neurodegenerative conditions in living people, perhaps even before memory loss becomes obvious.

One answer may lie in a protein called tau, which accumulates in abnormal tangles in the brains of people with Alzheimer’s disease and other “tauopathy” disorders. In recent years, researchers have been busy designing an antibody to target tau in hopes that this immunotherapy approach might slow or even reverse Alzheimer’s devastating symptoms, with promising early results in mice [1, 2]. Now, an NIH-funded research team that developed one such antibody have found it might also open the door to a simple blood test [3].

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