This App Helps Diagnose Rare Genetic Disorders from a Picture
Medical geneticist Omar Abdul-Rahman had a hunch. He thought that the three-year-old boy with deep-set eyes, a rounded nose, and uplifted earlobes might have Mowat-Wilson syndrome, but he'd never seen a patient with the rare disorder before.
"If it weren't for the app I'm not sure I would have had the confidence to say 'yes you should spend $1000 on this test."
Rahman had already ordered genetic tests for three different conditions without any luck, and he didn't want to cost the family any more money—or hope—if he wasn't sure of the diagnosis. So he took a picture of the boy and uploaded the photo to Face2Gene, a diagnostic aid for rare genetic disorders. Sure enough, Mowat-Wilson came up as a potential match. The family agreed to one final genetic test, which was positive for the syndrome.
"If it weren't for the app I'm not sure I would have had the confidence to say 'yes you should spend $1000 on this test,'" says Rahman, who is now the director of Genetic Medicine at the University of Nebraska Medical Center, but saw the boy when he was in the Department of Pediatrics at the University of Mississippi Medical Center in 2012.
"Families who are dealing with undiagnosed diseases never know what's going to come around the corner, what other organ system might be a problem next week," Rahman says. With a diagnosis, "You don't have to wait for the other shoe to drop because now you know the extent of the condition."
A diagnosis is the first and most important step for patients to attain medical care. Disease prognosis, treatment plans, and emotional coping all stem from this critical phase. But diagnosis can also be the trickiest part of the process, particularly for rare disorders. According to one European survey, 40 percent of rare diseases are initially misdiagnosed.
Healthcare professionals and medical technology companies hope that facial recognition software will help prevent families from facing difficult disruptions due to misdiagnoses.
"Patients with rare diseases or genetic disorders go through a long period of diagnostic odyssey, and just putting a name to a syndrome or finding a diagnosis can be very helpful and relieve a lot of tension for the family," says Dekel Gelbman, CEO of FDNA.
Consequently, a misdiagnosis can be devastating for families. Money and time may have been wasted on fruitless treatments, while opportunities for potentially helpful therapies or clinical trials were missed. Parents led down the wrong path must change their expectations of their child's long-term prognosis and care. In addition, they may be misinformed regarding future decisions about family planning.
Healthcare professionals and medical technology companies hope that facial recognition software will help prevent families from facing these difficult disruptions by improving the accuracy and ease of diagnosing genetic disorders. Traditionally, doctors diagnose these types of conditions by identifying unique patterns of facial features, a practice called dysmorphology. Trained physicians can read a child's face like a map and detect any abnormal ridges or plateaus—wide-set eyes, broad forehead, flat nose, rotated ears—that, combined with other symptoms such as intellectual disability or abnormal height and weight, signify a specific genetic disorder.
These morphological changes can be subtle, though, and often only specialized medical geneticists are able to detect and interpret these facial clues. What's more, some genetic disorders are so rare that even a specialist may not have encountered it before, much less a general practitioner. Diagnosing rare conditions has improved thanks to genomic testing that can confirm (or refute) a doctor's suspicion. Yet with thousands of variants in each person's genome, identifying the culprit mutation or deletion can be extremely difficult if you don't know what you're looking for.
Facial recognition technology is trying to take some of the guesswork out of this process. Software such as the Face2Gene app use machine learning to compare a picture of a patient against images of thousands of disorders and come back with suggestions of possible diagnoses.
"This is a classic field for artificial intelligence because no human being can really have enough knowledge and enough experience to be able to do this for thousands of different disorders."
"When we met a geneticist for the first time we were pretty blown away with the fact that they actually use their own human pattern recognition" to diagnose patients, says Gelbman. "This is a classic field for AI [artificial intelligence], for machine learning because no human being can really have enough knowledge and enough experience to be able to do this for thousands of different disorders."
When a physician uploads a photo to the app, they are given a list of different diagnostic suggestions, each with a heat map to indicate how similar the facial features are to a classic representation of the syndrome. The physician can hone the suggestions by adding in other symptoms or family history. Gelbman emphasized that the app is a "search and reference tool" and should not "be used to diagnose or treat medical conditions." It is not approved by the FDA as a diagnostic.
"As a tool, we've all been waiting for this, something that can help everyone," says Julian Martinez-Agosto, an associate professor in human genetics and pediatrics at UCLA. He sees the greatest benefit of facial recognition technology in its ability to empower non-specialists to make a diagnosis. Many areas, including rural communities or resource-poor countries, do not have access to either medical geneticists trained in these types of diagnostics or genomic screens. Apps like Face2Gene can help guide a general practitioner or flag diseases they might not be familiar with.
One concern is that most textbook images of genetic disorders come from the West, so the "classic" face of a condition is often a child of European descent.
Maximilian Muenke, a senior investigator at the National Human Genome Research Institute (NHGRI), agrees that in many countries, facial recognition programs could be the only way for a doctor to make a diagnosis.
"There are only geneticists in countries like the U.S., Canada, Europe, Japan. In most countries, geneticists don't exist at all," Muenke says. "In Nigeria, the most populous country in all of Africa with 160 million people, there's not a single clinical geneticist. So in a country like that, facial recognition programs will be sought after and will be extremely useful to help make a diagnosis to the non-geneticists."
One concern about providing this type of technology to a global population is that most textbook images of genetic disorders come from the West, so the "classic" face of a condition is often a child of European descent. However, the defining facial features of some of these disorders manifest differently across ethnicities, leaving clinicians from other geographic regions at a disadvantage.
"Every syndrome is either more easy or more difficult to detect in people from different geographic backgrounds," explains Muenke. For example, "in some countries of Southeast Asia, the eyes are slanted upward, and that happens to be one of the findings that occurs mostly with children with Down Syndrome. So then it might be more difficult for some individuals to recognize Down Syndrome in children from Southeast Asia."
There is a risk that providing this type of diagnostic information online will lead to parents trying to classify their own children.
To combat this issue, Muenke helped develop the Atlas of Human Malformation Syndromes, a database that incorporates descriptions and pictures of patients from every continent. By providing examples of rare genetic disorders in children from outside of the United States and Europe, Muenke hopes to provide clinicians with a better understanding of what to look for in each condition, regardless of where they practice.
There is a risk that providing this type of diagnostic information online will lead to parents trying to classify their own children. Face2Gene is free to download in the app store, although users must be authenticated by the company as a healthcare professional before they can access the database. The NHGRI Atlas can be accessed by anyone through their website. However, Martinez and Muenke say parents already use Google and WebMD to look up their child's symptoms; facial recognition programs and databases are just an extension of that trend. In fact, Martinez says, "Empowering families is another way to facilitate access to care. Some families live in rural areas and have no access to geneticists. If they can use software to get a diagnosis and then contact someone at a large hospital, it can help facilitate the process."
Martinez also says the app could go further by providing greater transparency about how the program makes its assessments. Giving clinicians feedback about why a diagnosis fits certain facial features would offer a valuable teaching opportunity in addition to a diagnostic aid.
Both Martinez and Muenke think the technology is an innovation that could vastly benefit patients. "In the beginning, I was quite skeptical and I could not believe that a machine could replace a human," says Muenke. "However, I am a convert that it actually can help tremendously in making a diagnosis. I think there is a place for facial recognition programs, and I am a firm believer that this will spread over the next five years."
Scientists are making machines, wearable and implantable, to act as kidneys
Like all those whose kidneys have failed, Scott Burton’s life revolves around dialysis. For nearly two decades, Burton has been hooked up (or, since 2020, has hooked himself up at home) to a dialysis machine that performs the job his kidneys normally would. The process is arduous, time-consuming, and expensive. Except for a brief window before his body rejected a kidney transplant, Burton has depended on machines to take the place of his kidneys since he was 12-years-old. His whole life, the 39-year-old says, revolves around dialysis.
“Whenever I try to plan anything, I also have to plan my dialysis,” says Burton says, who works as a freelance videographer and editor. “It’s a full-time job in itself.”
Many of those on dialysis are in line for a kidney transplant that would allow them to trade thrice-weekly dialysis and strict dietary limits for a lifetime of immunosuppressants. Burton’s previous transplant means that his body will likely reject another donated kidney unless it matches perfectly—something he’s not counting on. It’s why he’s enthusiastic about the development of artificial kidneys, small wearable or implantable devices that would do the job of a healthy kidney while giving users like Burton more flexibility for traveling, working, and more.
Still, the devices aren’t ready for testing in humans—yet. But recent advancements in engineering mean that the first preclinical trials for an artificial kidney could happen soon, according to Jonathan Himmelfarb, a nephrologist at the University of Washington.
“It would liberate people with kidney failure,” Himmelfarb says.
An engineering marvel
Compared to the heart or the brain, the kidney doesn’t get as much respect from the medical profession, but its job is far more complex. “It does hundreds of different things,” says UCLA’s Ira Kurtz.
Kurtz would know. He’s worked as a nephrologist for 37 years, devoting his career to helping those with kidney disease. While his colleagues in cardiology and endocrinology have seen major advances in the development of artificial hearts and insulin pumps, little has changed for patients on hemodialysis. The machines remain bulky and require large volumes of a liquid called dialysate to remove toxins from a patient’s blood, along with gallons of purified water. A kidney transplant is the next best thing to someone’s own, functioning organ, but with over 600,000 Americans on dialysis and only about 100,000 kidney transplants each year, most of those in kidney failure are stuck on dialysis.
Part of the lack of progress in artificial kidney design is the sheer complexity of the kidney’s job. Each of the 45 different cell types in the kidney do something different.
Part of the lack of progress in artificial kidney design is the sheer complexity of the kidney’s job. To build an artificial heart, Kurtz says, you basically need to engineer a pump. An artificial pancreas needs to balance blood sugar levels with insulin secretion. While neither of these tasks is simple, they are fairly straightforward. The kidney, on the other hand, does more than get rid of waste products like urea and other toxins. Each of the 45 different cell types in the kidney do something different, helping to regulate electrolytes like sodium, potassium, and phosphorous; maintaining blood pressure and water balance; guiding the body’s hormonal and inflammatory responses; and aiding in the formation of red blood cells.
There's been little progress for patients during Ira Kurtz's 37 years as a nephrologist. Artificial kidneys would change that.
UCLA
Dialysis primarily filters waste, and does so well enough to keep someone alive, but it isn’t a true artificial kidney because it doesn’t perform the kidney’s other jobs, according to Kurtz, such as sensing levels of toxins, wastes, and electrolytes in the blood. Due to the size and water requirements of existing dialysis machines, the equipment isn’t portable. Physicians write a prescription for a certain duration of dialysis and assess how well it’s working with semi-regular blood tests. The process of dialysis itself, however, is conducted blind. Doctors can’t tell how much dialysis a patient needs based on kidney values at the time of treatment, says Meera Harhay, a nephrologist at Drexel University in Philadelphia.
But it’s the impact of dialysis on their day-to-day lives that creates the most problems for patients. Only one-quarter of those on dialysis are able to remain employed (compared to 85% of similar-aged adults), and many report a low quality of life. Having more flexibility in life would make a major different to her patients, Harhay says.
“Almost half their week is taken up by the burden of their treatment. It really eats away at their freedom and their ability to do things that add value to their life,” she says.
Art imitates life
The challenge for artificial kidney designers was how to compress the kidney’s natural functions into a portable, wearable, or implantable device that wouldn’t need constant access to gallons of purified and sterilized water. The other universal challenge they faced was ensuring that any part of the artificial kidney that would come in contact with blood was kept germ-free to prevent infection.
As part of the 2021 KidneyX Prize, a partnership between the U.S. Department of Health and Human Services and the American Society of Nephrology, inventors were challenged to create prototypes for artificial kidneys. Himmelfarb’s team at the University of Washington’s Center for Dialysis Innovation won the prize by focusing on miniaturizing existing technologies to create a portable dialysis machine. The backpack sized AKTIV device (Ambulatory Kidney to Increase Vitality) will recycle dialysate in a closed loop system that removes urea from blood and uses light-based chemical reactions to convert the urea to nitrogen and carbon dioxide, which allows the dialysate to be recirculated.
Himmelfarb says that the AKTIV can be used when at home, work, or traveling, which will give users more flexibility and freedom. “If you had a 30-pound device that you could put in the overhead bins when traveling, you could go visit your grandkids,” he says.
Kurtz’s team at UCLA partnered with the U.S. Kidney Research Corporation and Arkansas University to develop a dialysate-free desktop device (about the size of a small printer) as the first phase of a progression that will he hopes will lead to something small and implantable. Part of the reason for the artificial kidney’s size, Kurtz says, is the number of functions his team are cramming into it. Not only will it filter urea from blood, but it will also use electricity to help regulate electrolyte levels in a process called electrodeionization. Kurtz emphasizes that these additional functions are what makes his design a true artificial kidney instead of just a small dialysis machine.
One version of an artificial kidney.
UCLA
“It doesn't have just a static function. It has a bank of sensors that measure chemicals in the blood and feeds that information back to the device,” Kurtz says.
Other startups are getting in on the game. Nephria Bio, a spinout from the South Korean-based EOFlow, is working to develop a wearable dialysis device, akin to an insulin pump, that uses miniature cartridges with nanomaterial filters to clean blood (Harhay is a scientific advisor to Nephria). Ian Welsford, Nephria’s co-founder and CTO, says that the device’s design means that it can also be used to treat acute kidney injuries in resource-limited settings. These potentials have garnered interest and investment in artificial kidneys from the U.S. Department of Defense.
For his part, Burton is most interested in an implantable device, as that would give him the most freedom. Even having a regular outpatient procedure to change batteries or filters would be a minor inconvenience to him.
“Being plugged into a machine, that’s not mimicking life,” he says.
This article was first published by Leaps.org on May 5, 2022.
With this new technology, hospitals and pharmacies could make vaccines and medicines onsite
Most modern biopharmaceutical medicines are produced by workhorse cells—typically bacterial but sometimes mammalian. The cells receive the synthesizing instructions on a snippet of a genetic code, which they incorporate into their DNA. The cellular machinery—ribosomes, RNAs, polymerases, and other compounds—read and use these instructions to build the medicinal molecules, which are harvested and administered to patients.
Although a staple of modern pharma, this process is complex and expensive. One must first insert the DNA instructions into the cells, which they may or may not uptake. One then must grow the cells, keeping them alive and well, so that they produce the required therapeutics, which then must be isolated and purified. To make this at scale requires massive bioreactors and big factories from where the drugs are distributed—and may take a while to arrive where they’re needed. “The pandemic showed us that this method is slow and cumbersome,” says Govind Rao, professor of biochemical engineering who directs the Center for Advanced Sensor Technology at the University of Maryland, Baltimore County (UMBC). “We need better methods that can work faster and can work locally where an outbreak is happening.”
Rao and his team of collaborators, which spans multiple research institutions, believe they have a better approach that may change medicine-making worldwide. They suggest forgoing the concept of using living cells as medicine-producers. Instead, they propose breaking the cells and using the remaining cellular gears for assembling the therapeutic compounds. Instead of inserting the DNA into living cells, the team burst them open, and removed their DNA altogether. Yet, the residual molecular machinery of ribosomes, polymerases and other cogwheels still functioned the way it would in a cell. “Now if you drop your DNA drug-making instructions into that soup, this machinery starts making what you need,” Rao explains. “And because you're no longer worrying about living cells, it becomes much simpler and more efficient.” The collaborators detail their cell-free protein synthesis or CFPS method in their recent paper published in preprint BioAxiv.
While CFPS does not use living cells, it still needs the basic building blocks to assemble proteins from—such as amino acids, nucleotides and certain types of enzymes. These are regularly added into this “soup” to keep the molecular factory chugging. “We just mix everything in as a batch and we let it integrate,” says James Robert Swartz, professor of chemical engineering and bioengineering at Stanford University and co-author of the paper. “And we make sure that we provide enough oxygen.” Rao likens the process to making milk from milk powder.
For a variety of reasons—from the field’s general inertia to regulatory approval hurdles—the method hasn’t become mainstream. The pandemic rekindled interest in medicines that can be made quickly and easily, so it drew more attention to the technology.
The idea of a cell-free protein synthesis is older than one might think. Swartz first experimented with it around 1997, when he was a chemical engineer at Genentech. While working on engineering bacteria to make pharmaceuticals, he discovered that there was a limit to what E. coli cells, the workhorse darling of pharma, could do. For example, it couldn’t grow and properly fold some complex proteins. “We tried many genetic engineering approaches, many fermentation, development, and environmental control approaches,” Swartz recalls—to no avail.
“The organism had its own agenda,” he quips. “And because everything was happening within the organism, we just couldn't really change those conditions very easily. Some of them we couldn’t change at all—we didn’t have control.”
It was out of frustration with the defiant bacteria that a new idea took hold. Could the cells be opened instead, so that the protein-forming reactions could be influenced more easily? “Obviously, we’d lose the ability for them to reproduce,” Swartz says. But that also meant that they no longer needed to keep the cells alive and could focus on making the specific reactions happen. “We could take the catalysts, the enzymes, and the more complex catalysts and activate them, make them work together, much as they would in a living cell, but the way we wanted.”
In 1998, Swartz joined Stanford, and began perfecting the biochemistry of the cell-free method, identifying the reactions he wanted to foster and stopping those he didn’t want. He managed to make the idea work, but for a variety of reasons—from the field’s general inertia to regulatory approval hurdles—the method hasn’t become mainstream. The pandemic rekindled interest in medicines that can be made quickly and easily, so it drew more attention to the technology. For their BioArxiv paper, the team tested the method by growing a specific antiviral protein called griffithsin.
First identified by Barry O’Keefe at National Cancer Institute over a decade ago, griffithsin is an antiviral known to interfere with many viruses’ ability to enter cells—including HIV, SARS, SARS-CoV-2, MERS and others. Originally isolated from the red algae Griffithsia, it works differently from antibodies and antibody cocktails.
Most antiviral medicines tend to target the specific receptors that viruses use to gain entry to the cells they infect. For example, SARS-CoV-2 uses the infamous spike protein to latch onto the ACE2 receptor of mammalian cells. The antibodies or other antiviral molecules stick to the spike protein, shutting off its ability to cling onto the ACE2 receptors. Unfortunately, the spike proteins mutate very often, so the medicines lose their potency. On the contrary, griffithsin has the ability to cling to the different parts of viral shells called capsids—namely to the molecules of mannose, a type of sugar. That extra stuff, glued all around the capsid like dead weight, makes it impossible for the virus to squeeze into the cell.
“Every time we have a vaccine or an antibody against a specific SARS-CoV-2 strain, that strain then mutates and so you lose efficacy,” Rao explains. “But griffithsin molecules glom onto the viral capsid, so the capsid essentially becomes a sticky mess and can’t enter the cell.” Mannose molecules also don’t mutate as easily as viruses’ receptors, so griffithsin-based antivirals do not have to be constantly updated. And because mannose molecules are found on many viruses’ capsids, it makes griffithsin “a universal neutralizer,” Rao explains.
“When griffithsin was discovered, we recognized that it held a lot of promise as a potential antiviral agent,” O’Keefe says. In 2010, he published a paper about griffithsin efficacy in neutralizing viruses of the corona family—after the first SARS outbreak in the early 2000s, the scientific community was interested in such antivirals. Yet, griffithsin is still not available as an off-the-shelf product. So during the Covid pandemic, the team experimented with synthesizing griffithsin using the cell-free production method. They were able to generate potent griffithsin in less than 24 hours without having to grow living cells.
The antiviral protein isn't the only type of medicine that can be made cell-free. The proteins needed for vaccine production could also be made the same way. “Such portable, on-demand drug manufacturing platforms can produce antiviral proteins within hours, making them ideal for combating future pandemics,” Rao says. “We would be able to stop the pandemic before it spreads.”
Top: Describes the process used in the study. Bottom: Describes how the new medicines and vaccines could be made at the site of a future viral outbreak.
Image courtesy of Rao and team, sourced from An approach to rapid distributed manufacturing of broad spectrumanti-viral griffithsin using cell-free systems to mitigate pandemics.
Rao’s idea is to perfect the technology to the point that any hospital or pharmacy can load up the media containing molecular factories, mix up the required amino acids, nucleotides and enzymes, and harvest the meds within hours. That will allow making medicines onsite and on demand. “That would be a self-contained production unit, so that you could just ship the production wherever the pandemic is breaking out,” says Swartz.
These units and the meds they produce, will, of course, have to undergo rigorous testing. “The biggest hurdles will be validating these against conventional technology,” Rao says. The biotech industry is risk-averse and prefers the familiar methods. But if this approach works, it may go beyond emergency situations and revolutionize the medicine-making paradigm even outside hospitals and pharmacies. Rao hopes that someday the method might become so mainstream that people may be able to buy and operate such reactors at home. “You can imagine a diabetic patient making insulin that way, or some other drugs,” Rao says. It would work not unlike making baby formula from the mere white powder. Just add water—and some oxygen, too.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.