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."
New tech for prison reform spreads to 11 states
A new non-profit called Recidiviz is using data technology to reduce the size of the U.S. criminal justice system. The bi-coastal company (SF and NYC) is currently working with 11 states to improve their systems and, so far, has helped remove nearly 69,000 people — ones left floundering in jail or on parole when they should have been released.
“The root cause is fragmentation,” says Clementine Jacoby, 31, a software engineer who worked at Google before co-founding Recidiviz in 2019. In the 1970s and 80s, the U.S. built a series of disconnected data systems, and this patchwork is still being used by criminal justice authorities today. It requires parole officers to manually calculate release dates, leading to errors in many cases. “[They] have done everything they need to do to earn their release, but they're still stuck in the system,” Jacoby says.
Recidiviz has built a platform that connects the different databases, with the goal of identifying people who are already qualified for release but remain behind bars or on supervision. “Think of Recidiviz like Google Maps,” says Jacoby, who worked on Maps when she was at the tech giant. Google Maps takes in data from different sources – satellite images, street maps, local business data — and organizes it into one easy view. “Recidiviz does something similar with criminal justice data,” Jacoby explains, “making it easy to identify people eligible to come home or to move to less intensive levels of supervision.”
People like Jacoby’s uncle. His experience with incarceration is what inspired her passion for criminal justice reform in the first place.
The problems are vast
The U.S. has the highest incarceration rate in the world — 2 million people according to the watchdog group, Prison Policy Initiative — at a cost of $182 billion a year. The numbers could be a lot lower if not for an array of problems including inaccurate sentencing calculations, flawed algorithms and parole violations laws.
Sentencing miscalculations
To determine eligibility for release, the current system requires corrections officers to check 21 different requirements spread across five different databases for each of the 90 to 100 people under their supervision. These manual calculations are time prohibitive, says Jacoby, and fall victim to human error.
In addition, Recidiviz found that policies aimed at helping to reduce the prison population don’t always work correctly. A key example is time off for good behavior laws that allow inmates to earn one day off for every 30 days of good behavior. Some states' data systems are built to calculate time off as one day per month of good behavior, rather than per day. Over the course of a decade-long sentence, Jacoby says these miscalculations can lead to a huge discrepancy in the calculated release data and the actual release date.
Algorithms
Commercial algorithm-based software systems for risk assessment continue to be widely used in the criminal justice system, even though a 2018 study published in Science Advances exposed their limitations. After the study went viral, it took three years for the Justice Department to issue a report on their own flawed algorithms used to reduce the federal prison population as part of the 2018 First Step Act. The program, it was determined, overestimated the risk of putting inmates of color into early-release programs.
Despite its name, Recidiviz does not build these types of algorithms for predicting recidivism, or whether someone will commit another crime after being released from prison. Rather, Jacoby says the company’s "descriptive analytics” approach is specifically intended to weed out incarceration inequalities and avoid algorithmic pitfalls.
Parole violation laws
Research shows that 350,000 people a year — about a quarter of the total prison population — are sent back not because they’ve committed another crime, but because they’ve broken a specific rule of their probation. “Things that wouldn't send you or I to prison, but would send someone on parole,” such as crossing county lines or being in the presence of alcohol when they shouldn’t be, are inflating the prison population, says Jacoby.
It’s personal for the co-founder and CEO
“I grew up with an uncle who went into the prison system,” Jacoby says. At 19, he was sentenced to ten years in prison for a non-violent crime. A few months after being released from jail, he was sent back for a non-violent parole violation.
“For my family, the fact that one in four prison admissions are driven not by a crime but by someone who's broken a rule on probation and parole was really profound because that happened to my uncle,” Jacoby says. The experience led her to begin studying criminal justice in high school, then college. She continued her dive into how the criminal justice system works as part of her Passion Project while at Google, a program that allows employees to spend 20 percent of their time on pro-bono work. Two colleagues whose family members had also been stuck in the system joined her.
As part of the project, Jacoby interviewed hundreds of people involved in the criminal justice system. “Those on the right, those on the left, agreed that bad data was slowing down reform,” she says. Their research brought them to North Dakota where they began to understand the root of the problem. The corrections department is making “huge, consequential decisions every day [without] … the data,” Jacoby says. In a new video by Recidiviz not yet released, Jacoby recounts her exchange with the state’s director of corrections who told her, “‘It’s not that we have the data and we just don’t know how to make it public; we don’t have the information you think we have.'"
A mock-up (with fake data) of the types of dashboards and insights that Recidiviz provides to state governments.
Recidiviz
As a software engineer, Jacoby says the comment made no sense to her — until she witnessed it first-hand. “We spent a lot of time driving around in cars with corrections directors and parole officers watching them use these incredibly taxing, frankly terrible, old data systems,” Jacoby says.
As they weeded through thousands of files — some computerized, some on paper — they unearthed the consequences of bad data: Hundreds of people in prison well past their release date and thousands more whose release from parole was delayed because of minor paperwork issues. They found individuals stuck in parole because they hadn’t checked one last item off their eligibility list — like simply failing to provide their parole officer with a paystub. And, even when parolees advocated for themselves, the archaic system made it difficult for their parole officers to confirm their eligibility, so they remained in the system. Jacoby and her team also unpacked specific policies that drive racial disparities — such as fines and fees.
The Solution
It’s more than a trivial technical challenge to bring the incomplete, fragmented data onto a 21st century data platform. It takes months for Recidiviz to sift through a state’s information systems to connect databases “with the goal of tracking a person all the way through their journey and find out what’s working for 18- to 25-year-old men, what’s working for new mothers,” explains Jacoby in the video.
TED Talk: How bad data traps people in the U.S. justice system
TED Fellow Clementine Jacoby's TED Talk went live on Jan. 13. It describes how we can fix bad data in the criminal justice system, "bringing thousands of people home, reducing costs and improving public safety along the way."
Clementine Jacoby • TED2022
Ojmarrh Mitchell, an associate professor in the School of Criminology and Criminal Justice at Arizona State University, who is not involved with the company, says what Recidiviz is doing is “remarkable.” His perspective goes beyond academic analysis. In his pre-academic years, Mitchell was a probation officer, working within the framework of the “well known, but invisible” information sharing issues that plague criminal justice departments. The flexibility of Recidiviz’s approach is what makes it especially innovative, he says. “They identify the specific gaps in each jurisdiction and tailor a solution for that jurisdiction.”
On the downside, the process used by Recidiviz is “a bit opaque,” Mitchell says, with few details available on how Recidiviz designs its tools and tracks outcomes. By sharing more information about how its actions lead to progress in a given jurisdiction, Recidiviz could help reformers in other places figure out which programs have the best potential to work well.
The eleven states in which Recidiviz is working include California, Colorado, Maine, Michigan, Missouri, Pennsylvania and Tennessee. And a pilot program launched last year in Idaho, if scaled nationally, with could reduce the number of people in the criminal justice system by a quarter of a million people, Jacoby says. As part of the pilot, rather than relying on manual calculations, Recidiviz is equipping leaders and the probation officers with actionable information with a few clicks of an app that Recidiviz built.
Mitchell is disappointed that there’s even the need for Recidiviz. “This is a problem that government agencies have a responsibility to address,” he says. “But they haven’t.” For one company to come along and fill such a large gap is “remarkable.”
How Leqembi became the biggest news in Alzheimer’s disease in 40 years, and what comes next
A few months ago, Betsy Groves traveled less than a mile from her home in Cambridge, Mass. to give a talk to a bunch of scientists. The scientists, who worked for the pharmaceutical companies Biogen and Eisai, wanted to know how she lived her life, how she thought about her future, and what it was like when a doctor’s appointment in 2021 gave her the worst possible news. Groves, 73, has Alzheimer’s disease. She caught it early, through a lumbar puncture that showed evidence of amyloid, an Alzheimer’s hallmark, in her cerebrospinal fluid. As a way of dealing with her diagnosis, she joined the Alzheimer’s Association’s National Early-Stage Advisory Board, which helped her shift into seeing her diagnosis as something she could use to help others.
After her talk, Groves stayed for lunch with the scientists, who were eager to put a face to their work. Biogen and Eisai were about to release the first drug to successfully combat Alzheimer’s in 40 years of experimental disaster. Their drug, which is known by the scientific name lecanemab and the marketing name Leqembi, was granted accelerated approval by the U.S. Food and Drug Administration last Friday, Jan. 6, after a study in 1,800 people showed that it reduced cognitive decline by 27 percent over 18 months.
It is no exaggeration to say that this result is a huge deal. The field of Alzheimer’s drug development has been absolutely littered with failures. Almost everything researchers have tried has tanked in clinical trials. “Most of the things that we've done have proven not to be effective, and it's not because we haven’t been taking a ton of shots at goal,” says Anton Porsteinsson, director of the University of Rochester Alzheimer's Disease Care, Research, and Education Program, who worked on the lecanemab trial. “I think it's fair to say you don't survive in this field unless you're an eternal optimist.”
As far back as 1984, a cure looked like it was within reach: Scientists discovered that the sticky plaques that develop in the brains of those who have Alzheimer’s are made up of a protein fragment called beta-amyloid. Buildup of beta-amyloid seemed to be sufficient to disrupt communication between, and eventually kill, memory cells. If that was true, then the cure should be straightforward: Stop the buildup of beta-amyloid; stop the Alzheimer’s disease.
It wasn’t so simple. Over the next 38 years, hundreds of drugs designed either to interfere with the production of abnormal amyloid or to clear it from the brain flamed out in trials. It got so bad that neuroscience drug divisions at major pharmaceutical companies (AstraZeneca, Pfizer, Bristol-Myers, GSK, Amgen) closed one by one, leaving the field to smaller, scrappier companies, like Cambridge-based Biogen and Tokyo-based Eisai. Some scientists began to dismiss the amyloid hypothesis altogether: If this protein fragment was so important to the disease, why didn’t ridding the brain of it do anything for patients? There was another abnormal protein that showed up in the brains of Alzheimer’s patients, called tau. Some researchers defected to the tau camp, or came to believe the proteins caused damage in combination.
The situation came to a head in 2021, when the FDA granted provisional approval to a drug called aducanumab, marketed as Aduhelm, against the advice of its own advisory council. The approval was based on proof that Aduhelm reduced beta-amyloid in the brain, even though one research trial showed it had no effect on people’s symptoms or daily life. Aduhelm could also cause serious side effects, like brain swelling and amyloid related imaging abnormalities (known as ARIA, these are basically micro-bleeds that appear on MRI scans). Without a clear benefit to memory loss that would make these risks worth it, Medicare refused to pay for Aduhelm among the general population. Two congressional committees launched an investigation into the drug’s approval, citing corporate greed, lapses in protocol, and an unjustifiably high price. (Aduhelm was also produced by the pharmaceutical company Biogen.)
To be clear, Leqembi is not the cure Alzheimer’s researchers hope for. While the drug is the first to show clear signs of a clinical benefit, the scientific establishment is split on how much of a difference Leqembi will make in the real world.
So far, Leqembi is like Aduhelm in that it has been given accelerated approval only for its ability to remove amyloid from the brain. Both are monoclonal antibodies that direct the immune system to attack and clear dysfunctional beta-amyloid. The difference is that, while that’s all Aduhelm was ever shown to do, Leqembi’s makers have already asked the FDA to give it full approval – a decision that would increase the likelihood that Medicare will cover it – based on data that show it also improves Alzheimer’s sufferer’s lives. Leqembi targets a different type of amyloid, a soluble version called “protofibrils,” and that appears to change the effect. “It can give individuals and their families three, six months longer to be participating in daily life and living independently,” says Claire Sexton, PhD, senior director of scientific programs & outreach for the Alzheimer's Association. “These types of changes matter for individuals and for their families.”
To be clear, Leqembi is not the cure Alzheimer’s researchers hope for. It does not halt or reverse the disease, and people do not get better. While the drug is the first to show clear signs of a clinical benefit, the scientific establishment is split on how much of a difference Leqembi will make in the real world. It has “a rather small effect,” wrote NIH Alzheimer’s researcher Madhav Thambisetty, MD, PhD, in an email to Leaps.org. “It is unclear how meaningful this difference will be to patients, and it is unlikely that this level of difference will be obvious to a patient (or their caregivers).” Another issue is cost: Leqembi will become available to patients later this month, but Eisai is setting the price at $26,500 per year, meaning that very few patients will be able to afford it unless Medicare chooses to reimburse them for it.
The same side effects that plagued Aduhelm are common in Leqembi treatment as well. In many patients, amyloid doesn’t just accumulate around neurons, it also forms deposits in the walls of blood vessels. Blood vessels that are shot through with amyloid are more brittle. If you infuse a drug that targets amyloid, brittle blood vessels in the brain can develop leakage that results in swelling or bleeds. Most of these come with no symptoms, and are only seen during testing, which is why they are called “imaging abnormalities.” But in situations where patients have multiple diseases or are prescribed incompatible drugs, they can be serious enough to cause death. The three deaths reported from Leqembi treatment (so far) are enough to make Thambisetty wonder “how well the drug may be tolerated in real world clinical practice where patients are likely to be sicker and have multiple other medical conditions in contrast to carefully selected patients in clinical trials.”
Porsteinsson believes that earlier detection of Alzheimer’s disease will be the next great advance in treatment, a more important step forward than Leqembi’s approval.
Still, there are reasons to be excited. A successful Alzheimer’s drug can pave the way for combination studies, in which patients try a known effective drug alongside newer, more experimental ones; or preventative studies, which take place years before symptoms occur. It also represents enormous strides in researchers’ understanding of the disease. For example, drug dosages have increased massively—in some cases quadrupling—from the early days of Alzheimer’s research. And patient selection for studies has changed drastically as well. Doctors now know that you’ve got to catch the disease early, through PET-scans or CSF tests for amyloid, if you want any chance of changing its course.
Porsteinsson believes that earlier detection of Alzheimer’s disease will be the next great advance in treatment, a more important step forward than Leqembi’s approval. His lab already uses blood tests for different types of amyloid, for different types of tau, and for measures of neuroinflammation, neural damage, and synaptic health, but commercially available versions from companies like C2N, Quest, and Fuji Rebio are likely to hit the market in the next couple of years. “[They are] going to transform the diagnosis of Alzheimer's disease,” Porsteinsson says. “If someone is experiencing memory problems, their physicians will be able to order a blood test that will tell us if this is the result of changes in your brain due to Alzheimer's disease. It will ultimately make it much easier to identify people at a very early stage of the disease, where they are most likely to benefit from treatment.”
Learn more about new blood tests to detect Alzheimer's
Early detection can help patients for more philosophical reasons as well. Betsy Groves credits finding her Alzheimer’s early with giving her the space to understand and process the changes that were happening to her before they got so bad that she couldn’t. She has been able to update her legal documents and, through her role on the Advisory Group, help the Alzheimer’s Association with developing its programs and support services for people in the early stages of the disease. She still drives, and because she and her husband love to travel, they are hoping to get out of grey, rainy Cambridge and off to Texas or Arizona this spring.
Because her Alzheimer’s disease involves amyloid deposits (a “substantial portion” do not, says Claire Sexton, which is an additional complication for research), and has not yet reached an advanced stage, Groves may be a good candidate to try Leqembi. She says she’d welcome the opportunity to take it. If she can get access, Groves hopes the drug will give her more days to be fully functioning with her husband, daughters, and three grandchildren. Mostly, she avoids thinking about what the latter stages of Alzheimer’s might be like, but she knows the time will come when it will be her reality. “So whatever lecanemab can do to extend my more productive ways of engaging with relationships in the world,” she says. “I'll take that in a minute.”