Creative Minds
Preventing Glaucoma Vision Loss with ‘Big Data’
Posted on by Dr. Francis Collins

Each morning, more than 2 million Americans start their rise-and-shine routine by remembering to take their eye drops. The drops treat their open-angle glaucoma, the most-common form of the disease, caused by obstructed drainage of fluid where the eye’s cornea and iris meet. The slow drainage increases fluid pressure at the front of the eye. Meanwhile, at the back of the eye, fluid pushes on the optic nerve, causing its bundled fibers to fray and leading to gradual loss of side vision.
For many, the eye drops help to lower intraocular pressure and prevent vision loss. But for others, the drops aren’t sufficient and their intraocular pressure remains high. Such people will need next-level care, possibly including eye surgery, to reopen the clogged drainage ducts and slow this disease that disproportionately affects older adults and African Americans over age 40.

Credit: University of California San Diego
Sally Baxter, a physician-scientist with expertise in ophthalmology at the University of California, San Diego (UCSD), wants to learn how to predict who is at greatest risk for serious vision loss from open-angle and other forms of glaucoma. That way, they can receive more aggressive early care to protect their vision from this second-leading cause of blindness in the U.S..
To pursue this challenging research goal, Baxter has received a 2020 NIH Director’s Early Independence Award. Her research will build on the clinical observation that people with glaucoma frequently battle other chronic health problems, such as high blood pressure, diabetes, and heart disease. To learn more about how these and other chronic health conditions might influence glaucoma outcomes, Baxter has begun mining a rich source of data: electronic health records (EHRs).
In an earlier study of patients at UCSD, Baxter showed that EHR data helped to predict which people would need glaucoma surgery within the next six months [1]. The finding suggested that the EHR, especially information on a patient’s blood pressure and medications, could predict the risk for worsening glaucoma.
In her NIH-supported work, she’s already extended this earlier “Big Data” finding by analyzing data from more than 1,200 people with glaucoma who participate in NIH’s All of Us Research Program [2]. With consent from the participants, Baxter used their EHRs to train a computer to find telltale patterns within the data and then predict with 80 to 99 percent accuracy who would later require eye surgery.
The findings confirm that machine learning approaches and EHR data can indeed help in managing people with glaucoma. That’s true even when the EHR data don’t contain any information specific to a person’s eye health.
In fact, the work of Baxter and other groups have pointed to an especially important role for blood pressure in shaping glaucoma outcomes. Hoping to explore this lead further with the support of her Early Independence Award, Baxter also will enroll patients in a study to test whether blood-pressure monitoring smart watches can add important predictive information on glaucoma progression. By combining round-the-clock blood pressure data with EHR data, she hopes to predict glaucoma progression with even greater precision. She’s also exploring innovative ways to track whether people with glaucoma use their eye drops as prescribed, which is another important predictor of the risk of irreversible vision loss [3].
Glaucoma research continues to undergo great progress. This progress ranges from basic research to the development of new treatments and high-resolution imaging technologies to improve diagnostics. But Baxter’s quest to develop practical clinical tools hold great promise, too, and hopefully will help one day to protect the vision of millions of people with glaucoma around the world.
References:
[1] Machine learning-based predictive modeling of surgical intervention in glaucoma using systemic data from electronic health records. Baxter SL, Marks C, Kuo TT, Ohno-Machado L, Weinreb RN. Am J Ophthalmol. 2019 Dec; 208:30-40.
[2] Predictive analytics for glaucoma using data from the All of Us Research Program. Baxter SL, Saseendrakumar BR, Paul P, Kim J, Bonomi L, Kuo TT, Loperena R, Ratsimbazafy F, Boerwinkle E, Cicek M, Clark CR, Cohn E, Gebo K, Mayo K, Mockrin S, Schully SD, Ramirez A, Ohno-Machado L; All of Us Research Program Investigators. Am J Ophthalmol. 2021 Jul;227:74-86.
[3] Smart electronic eyedrop bottle for unobtrusive monitoring of glaucoma medication adherence. Aguilar-Rivera M, Erudaitius DT, Wu VM, Tantiongloc JC, Kang DY, Coleman TP, Baxter SL, Weinreb RN. Sensors (Basel). 2020 Apr 30;20(9):2570.
Links:
Glaucoma (National Eye Institute/NIH)
All of Us Research Program (NIH)
Video: Sally Baxter (All of Us Research Program)
Sally Baxter (University of California San Diego)
Baxter Project Information (NIH RePORTER)
NIH Director’s Early Independence Award (Common Fund)
NIH Support: Common Fund
Decoding Heart-Brain Talk to Prevent Sudden Cardiac Deaths
Posted on by Dr. Francis Collins

As a cardiac electrophysiologist, Deeptankar DeMazumder has worked for years with people at risk for sudden cardiac arrest (SCA). Despite the latest medical advances, less than 10 percent of individuals stricken with an SCA will survive this highly dangerous condition in which irregular heart rhythms, or arrhythmias, cause the heart suddenly to stop beating.
In his role as a physician, DeMazumder keeps a tight focus on the electrical activity in their hearts, doing his best to prevent this potentially fatal event. In his other role, as a scientist at the University of Cincinnati College of Medicine, DeMazumder is also driven by a life-saving aspiration: finding ways to identify at-risk individuals with much greater accuracy than currently possible—and to develop better ways of protecting them from SCAs. He recently received a 2020 NIH Director’s New Innovator Award to pursue one of his promising ideas.
SCAs happen without warning and can cause death within minutes. Poor heart function and abnormal heart rhythms are important risk factors, but it’s not possible today to predict reliably who will have an SCA. However, doctors already routinely capture a wealth of information in electrical signals from the heart using electrocardiograms (ECGs). They also frequently use electroencephalograms (EEGs) to capture electrical activity in the brain.
DeMazumder’s innovative leap is to look at these heart and brain signals jointly, as well as in new ways, during sleep. According to the physician-scientist, sleep is a good time to search for SCA signatures in the electrical crosstalk between the heart and the brain because many other aspects of brain activity quiet down. He also thinks it’s important to pay special attention to what happens to the body’s electrical signals during sleep because most sudden cardiac deaths happen early in the waking hours, for reasons that aren’t well understood.
He has promising preliminary evidence from both animal models and humans suggesting that signatures within heart and brain signals are unique predictors of sudden death, even in people who appear healthy [1]. DeMazumder has already begun developing a set of artificial intelligence algorithms for jointly deciphering waveform signals from the heart, brain, and other body signals [2,3]. These new algorithms associate the waveform signals with a wealth of information available in electronic health records to improve upon the algorithm’s ability to predict catastrophic illness.
DeMazumder credits his curiosity about what he calls the “art and science of healing” to his early childhood experiences and his family’s dedication to community service in India. It taught him to appreciate the human condition, and he has integrated this life-long awareness into his Western medical training and his growing interest in computer science.
For centuries, humans have talked about how true flourishing needs both head and heart. In DeMazumder’s view, science is just beginning to understand the central role of heart-brain conversations in our health. As he continues to capture and interpret these conversations through his NIH-supported work, he hopes to find ways to identify individuals who don’t appear to have serious heart disease but may nevertheless be at high risk for SCA. In the meantime, he will continue to do all he can for the patients in his care.
References:
[1] Mitochondrial ROS drive sudden cardiac death and chronic proteome remodeling in heart failure. Dey S, DeMazumder D, Sidor A, Foster DB, O’Rourke B. Circ Res. 2018;123(3):356-371.
[2] Entropy of cardiac repolarization predicts ventricular arrhythmias and mortality in patients receiving an implantable cardioverter-defibrillator for primary prevention of sudden death. DeMazumder D, Limpitikul WB, Dorante M, et al. Europace. 2016;18(12):1818-1828.
[3] Dynamic analysis of cardiac rhythms for discriminating atrial fibrillation from lethal ventricular arrhythmias. DeMazumder D, Lake DE, Cheng A, et al. Circ Arrhythm Electrophysiol. 2013;6(3):555-561.
Links:
Sudden Cardiac Arrest (National Heart, Lung, and Blood Institute/NIH)
Deeptankar DeMazumder (University of Cincinnati College of Medicine)
DeMazumder Project Information (NIH RePORTER)
NIH Director’s New Innovator Award (Common Fund)
NIH Support: National Heart, Lung, and Blood Institute; Common Fund
From Electrical Brain Maps to Learning More About Migraines
Posted on by Dr. Francis Collins

One of life’s greatest mysteries is the brain’s ability to encode something as complex as human behavior. In an effort to begin to unravel this mystery, neuroscientists often zoom in to record the activities of individual neurons. Sometimes they expand their view to look at a specific region of the brain. But if they zoom out farther, neuroscientists can observe many thousands of neurons across the entire brain firing at once to produce electrical oscillations that somehow translate into behaviors as distinct as a smile and a frown. The complexity is truly daunting.
Rainbo Hultman, University of Iowa Carver College of Medicine, Iowa City, realized years ago that by zooming out and finding a way to map all those emergent signals, she could help to change the study of brain function fundamentally. She also realized doing so offered her an opportunity to chip away at cracking the complicated code of the electrical oscillations that translate into such complex behaviors. To pursue her work in this emerging area of “electrical connectomics,” Hultman recently received a 2020 NIH Director’s New Innovator Award to study the most common human neurological disorder: migraine headaches.
A few years ago, Hultman made some impressive progress in electrical connectomics as a post-doctoral researcher in the lab of Kafui Dzirasa at Duke University, Durham, NC. Hultman and her colleagues refined a way to use electrodes to collect electrical field potentials across an unprecedented seven separate mouse brain regions at once. Using machine learning to help make sense of all the data, they uncovered a dynamic, yet reproducible, electrical brain network encoding depression [1].
What’s more, they found that the specific features of this brain-wide network could predict which mice subjected to chronic stress would develop signs of major depressive disorder. As Hultman noted, when measured and mapped in this way, the broad patterns of electrical brain activity, or “Electome factors,” could indicate which mice were vulnerable to stress and which were more resilient.
Moving on to her latest area of research, Hultman is especially intrigued by the fact that people who endure regular migraine attacks often pass through a characteristic sequence of symptoms. These symptoms can include a painful headache on one side of the head; visual disturbances; sensitivity to light, odors, or sound; mood changes; nausea; trouble speaking; and sometimes even paralysis. By studying the broad electrical patterns and networks associated with migraine in mice—simultaneously capturing electrical recordings from 14 brain regions on a millisecond timescale—she wants to understand how brain circuits are linked and work together in ways that produce the complex sequences of migraine symptoms.
More broadly, Hultman wants to understand how migraine and many other disorders affecting the brain lead to a state of heightened sensory sensitivity and how that emerges from integrated neural circuits in the brain. In her studies of migraine, the researcher suspects she might observe some of the same patterns seen earlier in depression. In fact, her team is setting up its experiments to ensure it can identify any brain network features that are shared across important disease states.
By the way, I happen to be one of many people who suffer from migraines, although fortunately not very often in my case. The visual aura of flashing jagged images that starts in the center of my visual field and then gradually moves to the periphery over about 20 minutes is pretty dramatic—a free light show! I’ve wondered what the electrical component of that must be like. But, even with treatment, the headache that follows can be pretty intense.
Hultman also has seen in her own life and family how debilitating migraines can be. Her goal isn’t just to map these neural networks, but to use them to identify where to target future therapeutics. Ultimately, she hopes her work will pave the way for more precise approaches for treating migraine and other brain disorders that are based on the emergent electrical characteristics of each individual’s brain activity. It’s a fascinating proposition, and I certainly look forward to where this research leads and what it may reveal about the fundamentals of how our brains encode complex behaviors and emotions.
Reference:
[1] Brain-wide electrical spatiotemporal dynamics encode depression vulnerability. Hultman R, Ulrich K, Sachs BD, Blount C, Carlson DE, Ndubuizu N, Bagot RC, Parise EM, Vu MT, Gallagher NM, Wang J, Silva AJ, Deisseroth K, Mague SD, Caron MG, Nestler EJ, Carin L, Dzirasa K. Cell. 2018 Mar 22;173(1):166-180.e14.
Links:
Migraine Information Page (National Institute of Neurological Disorders and Stroke/NIH)
Laboratory for Brain-Network Based Molecular Medicine (University of Iowa, Iowa City)
Hultman Project Information (NIH RePORTER)
NIH Director’s New Innovator Award (Common Fund)
NIH Support: Common Fund; National Institute of Mental Health
An Evolutionary Guide to New Immunotherapies
Posted on by Dr. Francis Collins

One of the best ways to learn how something works is to understand how it’s built. How it came to be. That’s true not only if you play a guitar or repair motorcycle engines, but also if you study the biological systems that make life possible. Evolutionary studies, comparing the development of these systems across animals and organisms, are now leading to many unexpected biological discoveries and promising possibilities for preventing and treating human disease.
While there are many evolutionary questions to ask, Brenda Bass, a distinguished biochemist at University of Utah, Salt Lake City, has set her sights on a particularly profound one: How has innate immunity evolved through the millennia in all living things, including humans? Innate immunity is the immune system’s frontline defense, the first responders that take control of an emerging infectious situation and, if needed, signal for backup.
Exploring the millennia for clues about innate immunity takes a special team, and Bass has assembled a talented one. It includes her Utah colleague Nels Elde, a geneticist; immunologist Dan Stetson, University of Washington, Seattle; and biochemist Jane Jackman, Ohio State University, Columbus.
With a 2020 NIH Director’s Transformative Research Award, this hard-working team will embark on studies looking back at 450 million years of evolution: the point in time when animals diverged to develop very distinct methods of innate immune defense [1]. The team members hope to uncover new possibilities encoded in the innate immune system, especially those that might be latent but still workable. The researchers will then explore whether their finds can be repurposed not only to boost our body’s natural response to external threats but also to internal threats like cancer.
Bass brings a unique perspective to the project. As a postdoc in the 1980s, she stumbled upon a whole new class of enzymes, called ADARs, that edit RNA [2]. Their function was mysterious at the time. It turns out that ADARs specifically edit a molecule called double-stranded RNA (dsRNA). When viruses infect cells in animals, including humans, they make dsRNA, which the innate immune system detects as a sign that a cell has been invaded.
It also turns out that animal cells make their own dsRNA. Over the years, Bass and her lab have identified thousands of dsRNAs made in animal cells—in fact, a significant number of human genes produce dsRNA [3]. Also interesting, ADARs are crucial to marking our own dsRNA as “self” to avoid triggering an immune response when we don’t need it [4].
Bass and others have found that evolution has produced dramatic differences in the biochemical pathways powering the innate immune system. In vertebrate animals, dsRNA leads to release of the immune chemical interferon, a signaling pathway that invertebrate species don’t have. Instead, in response to detecting dsRNA from an invader, and repelling it, worms and other invertebrates trigger a gene-silencing pathway known as RNA interference, or RNAi.
With the new funding, Bass and team plan to mix and match immune strategies from simple and advanced species, across evolutionary time, to craft an entirely new set of immune tools to fight disease. The team will also build new types of targeted immunotherapies based on the principles of innate immunity. Current immunotherapies, which harness a person’s own immune system to fight disease, target infections, autoimmune disorders, and cancer. But they work through our second-line adaptive immune response, which is a biological system unique to vertebrates.
Bass and her team will first hunt for more molecules like ADARs: innate immune checkpoints, as they refer to them. The name comes from a functional resemblance to the better-known adaptive immune checkpoints PD-1 and CTLA-4, which sparked a revolution in cancer immunotherapy. The team will run several screens that sort molecules successful at activating innate immune responses—both in invertebrates and in mammals—hoping to identify a range of durable new immune switches that evolution skipped over but that might be repurposed today.
Another intriguing direction for this research stems from the observation that decreasing normal levels of ADARs in tumors kickstarts innate immune responses that kill cancer cells [5]. Along these lines, the scientists plan to test newly identified immune switches to look for novel ways to fight cancer where existing approaches have not worked.
Evolution is the founding principle for all of biology—organisms learn from what works to improve their ability to survive. In this case, research to re-examine such lessons and apply them for new uses may help transform bygone evolution into a therapeutic revolution!
References:
[1] Evolution of adaptive immunity from transposable elements combined with innate immune systems. Koonin EV, Krupovic M. Nat Rev Genet. 2015 Mar;16(3):184-192.
[2] A developmentally regulated activity that unwinds RNA duplexes. Bass BL, Weintraub H. Cell. 1987 Feb 27;48(4):607-613.
[3] Mapping the dsRNA World. Reich DP, Bass BL. Cold Spring Harb Perspect Biol. 2019 Mar 1;11(3):a035352.
[4] To protect and modify double-stranded RNA – the critical roles of ADARs in development, immunity and oncogenesis. Erdmann EA, Mahapatra A, Mukherjee P, Yang B, Hundley HA. Crit Rev Biochem Mol Biol. 2021 Feb;56(1):54-87.
[5] Loss of ADAR1 in tumours overcomes resistance to immune checkpoint blockade. Ishizuka JJ, Manguso RT, Cheruiyot CK, Bi K, Panda A, et al. Nature. 2019 Jan;565(7737):43-48.
Links:
Bass Lab (University of Utah, Salt Lake City)
Elde Lab (University of Utah)
Jackman Lab (Ohio State University, Columbus)
Stetson Lab (University of Washington, Seattle)
Bass/Elde/Jackman/Stetson Project Information (NIH RePORTER)
NIH Director’s Transformative Research Award Program (Common Fund)
NIH Support: Common Fund; National Cancer Institute
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