Autism cases are still on the rise, and scientists don't know why. In April, the Centers for Disease Control (CDC) reported that rates of autism had increased once again, now at an estimated 1 in 59 children up from 1 in 68 just two years ago. Rates have been climbing steadily since 2007 when the CDC initially estimated that 1 in 150 children were on the autism spectrum.
Some clinicians are concerned that the creeping expansion of autism is causing the diagnosis to lose its meaning.
The standard explanation for this increase has been the expansion of the definition of autism to include milder forms like Asperger's, as well as a heightened awareness of the condition that has improved screening efforts. For example, the most recent jump is attributed to children in minority communities being diagnosed who might have previously gone under the radar. In addition, more federally funded resources are available to children with autism than other types of developmental disorders, which may prompt families or physicians to push harder for a diagnosis.
Some clinicians are concerned that the creeping expansion of autism is causing the diagnosis to lose its meaning. William Graf, a pediatric neurologist at Connecticut Children's Medical Center, says that when a nurse tells him that a new patient has a history of autism, the term is no longer a useful description. "Even though I know this topic extremely well, I cannot picture the child anymore," he says. "Use the words mild, moderate, or severe. Just give me a couple more clues, because when you say autism today, I have no idea what people are talking about anymore."
Genetic testing has emerged as one potential way to remedy the overly broad label by narrowing down a heterogeneous diagnosis to a specific genetic disorder. According to Suma Shankar, a medical geneticist at the University of California, Davis, up to 60 percent of autism cases could be attributed to underlying genetic causes. Common examples include Fragile X Syndrome or Rett Syndrome—neurodevelopmental disorders that are caused by mutations in individual genes and are behaviorally classified as autism.
With more than 500 different mutations associated with autism, very few additional diagnoses provide meaningful information.
Having a genetic diagnosis in addition to an autism diagnosis can help families in several ways, says Shankar. Knowing the genetic origin can alert families to other potential health problems that are linked to the mutation, such as heart defects or problems with the immune system. It may also help clinicians provide more targeted behavioral therapies and could one day lead to the development of drug treatments for underlying neurochemical abnormalities. "It will pave the way to begin to tease out treatments," Shankar says.
When a doctor diagnoses a child as having a specific genetic condition, the label of autism is still kept because it is more well-known and gives the child access to more state-funded resources. Children can thus be diagnosed with multiple conditions: autism spectrum disorder and their specific gene mutation. However, with more than 500 different mutations associated with autism, very few additional diagnoses provide meaningful information. What's more, the presence or absence of a mutation doesn't necessarily indicate whether the child is on the mild or severe end of the autism spectrum.
Because of this, Graf doubts that genetic classifications are really that useful. He tells the story of a boy with epilepsy and severe intellectual disabilities who was diagnosed with autism as a young child. Years later, Graf ordered genetic testing for the boy and discovered that he had a mutation in the gene SYNGAP1. However, this knowledge didn't change the boy's autism status. "That diagnosis [SYNGAP1] turns out to be very specific for him, but it will never be a household name. Biologically it's good to know, and now it's all over his chart. But on a societal level he still needs this catch-all label [of autism]," Graf says.
"It gives some information, but to what degree does that change treatment or prognosis?"
Jennifer Singh, a sociologist at Georgia Tech who wrote the book Multiple Autisms: Spectrums of Advocacy and Genomic Science, agrees. "I don't know that the knowledge gained from just having a gene that's linked to autism," is that beneficial, she says. "It gives some information, but to what degree does that change treatment or prognosis? Because at the end of the day you have to address the issues that are at hand, whatever they might be."
As more children are diagnosed with autism, knowledge of the underlying genetic mutation causing the condition could help families better understand the diagnosis and anticipate their child's developmental trajectory. However, for the vast majority, an additional label provides little clarity or consolation.
Instead of spending money on genetic screens, Singh thinks the resources would be better used on additional services for people who don't have access to behavioral, speech, or occupational therapy. "Things that are really going to matter for this child in their future," she says.
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."