Why Are Autism Rates Steadily Rising?
Stefania Sterling was just 21 when she had her son, Charlie. She was young and healthy, with no genetic issues apparent in either her or her husband's family, so she expected Charlie to be typical.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period."
It wasn't until she went to a Mommy and Me music class when he was one, and she saw all the other one-year-olds walking, that she realized how different her son was. He could barely crawl, didn't speak, and made no eye contact. By the time he was three, he was diagnosed as being on the lower functioning end of the autism spectrum.
She isn't sure why it happened – and researchers, too, are still trying to understand the basis of the complex condition. Studies suggest that genes can act together with influences from the environment to affect development in ways that lead to Autism Spectrum Disorder (ASD). But rates of ASD are rising dramatically, making the need to figure out why it's happening all the more urgent.
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Indeed, the CDC's latest autism report, released last week, which uses 2016 data, found that the prevalence of ASD in four-year-old children was one in 64 children, or 15.6 affected children per 1,000. That's more than the 14.1 rate they found in 2014, for the 11 states included in the study. New Jersey, as in years past, was the highest, with 25.3 per 1,000, compared to Missouri, which had just 8.8 per 1,000.
The rate for eight-year-olds had risen as well. Researchers found the ASD prevalence nationwide was 18.5 per 1,000, or one in 54, about 10 percent higher than the 16.8 rate found in 2014. New Jersey, again, was the highest, at one in 32 kids, compared to Colorado, which had the lowest rate, at one in 76 kids. For New Jersey, that's a 175 percent rise from the baseline number taken in 2000, when the state had just one in 101 kids.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period," said Walter Zahorodny, an associate professor of pediatrics at Rutgers New Jersey Medical School, who was involved in collecting the data.
The study echoed the findings of a surprising 2011 study in South Korea that found 1 in every 38 students had ASD. That was the the first comprehensive study of autism prevalence using a total population sample: A team of investigators from the U.S., South Korea, and Canada looked at 55,000 children ages 7 to 12 living in a community in South Korea and found that 2.64 percent of them had some level of autism.
Searching for Answers
Scientists can't put their finger on why rates are rising. Some say it's better diagnosis. That is, it's not that more people have autism. It's that we're better at detecting it. Others attribute it to changes in the diagnostic criteria. Specifically, the May 2013 update of the Diagnostic and Statistical Manual of Mental Disorders-5 -- the standard classification of mental disorders -- removed the communication deficit from the autism definition, which made more children fall under that category. Cynical observers believe physicians and therapists are handing out the diagnosis more freely to allow access to services available only to children with autism, but that are also effective for other children.
Alycia Halladay, chief science officer for the Autism Science Foundation in New York, said she wishes there were just one answer, but there's not. While she believes the rising ASD numbers are due in part to factors like better diagnosis and a change in the definition, she does not believe that accounts for the entire rise in prevalence. As for the high numbers in New Jersey, she said the state has always had a higher prevalence of autism compared to other states. It is also one of the few states that does a good job at recording cases of autism in its educational records, meaning that children in New Jersey are more likely to be counted compared to kids in other states.
"Not every state is as good as New Jersey," she said. "That accounts for some of the difference compared to elsewhere, but we don't know if it's all of the difference in prevalence, or most of it, or what."
"What we do know is that vaccinations do not cause autism."
There is simply no defined proven reason for these increases, said Scott Badesch, outgoing president and CEO of the Autism Society of America.
"There are suggestions that it is based on better diagnosis, but there are also suggestions that the incidence of autism is in fact increasing due to reasons that have yet been determined," he said, adding, "What we do know is that vaccinations do not cause autism."
Zahorodny, the pediatrics professor, believes something is going on beyond better detection or evolving definitions.
"Changes in awareness and shifts in how children are identified or diagnosed are relevant, but they only take you so far in accounting for an increase of this magnitude," he said. "We don't know what is driving the surge in autism recorded by the ADDM Network and others."
He suggested that the increase in prevalence could be due to non-genetic environmental triggers or risk factors we do not yet know about, citing possibilities including parental age, prematurity, low birth rate, multiplicity, breech presentation, or C-section delivery. It may not be one, but rather several factors combined, he said.
"Increases in ASD prevalence have affected the whole population, so the triggers or risks must be very widely dispersed across all strata," he added.
There are studies that find new risk factors for ASD almost on a daily basis, said Idan Menashe, assistant professor in the Department of Health at Ben-Gurion University of the Negev, the fastest growing research university in Israel.
"There are plenty of studies that find new genetic variants (and new genes)," he said. In addition, various prenatal and perinatal risk factors are associated with a risk of ASD. He cited a study his university conducted last year on the relationship between C-section births and ASD, which found that exposure to general anesthesia may explain the association.
Whatever the cause, health practitioners are seeing the consequences in real time.
"People say rates are higher because of the changes in the diagnostic criteria," said Dr. Roseann Capanna-Hodge, a psychologist in Ridgefield, CT. "And they say it's easier for children to get identified. I say that's not the truth and that I've been doing this for 30 years, and that even 10 years ago, I did not see the level of autism that I do see today."
Sure, we're better at detecting autism, she added, but the detection improvements have largely occurred at the low- to mid- level part of the spectrum. The higher rates of autism are occurring at the more severe end, in her experience.
A Polarizing Theory
Among the more controversial risk factors scientists are exploring is the role environmental toxins may play in the development of autism. Some scientists, doctors and mental health experts suspect that toxins like heavy metals, pesticides, chemicals, or pollution may interrupt the way genes are expressed or the way endocrine systems function, manifesting in symptoms of autism. But others firmly resist such claims, at least until more evidence comes forth. To date, studies have been mixed and many have been more associative than causative.
"Today, scientists are still trying to figure out whether there are other environmental changes that can explain this rise, but studies of this question didn't provide any conclusive answer," said Menashe, who also serves as the scientific director of the National Autism Research Center at BGU.
"It's not everything that makes Charlie. He's just like any other kid."
That inconclusiveness has not dissuaded some doctors from taking the perspective that toxins do play a role. "Autism rates are rising because there is a mismatch between our genes and our environment," said Julia Getzelman, a pediatrician in San Francisco. "The majority of our evolution didn't include the kinds of toxic hits we are experiencing. The planet has changed drastically in just the last 75 years –- it has become more and more polluted with tens of thousands of unregulated chemicals being used by industry that are having effects on our most vulnerable."
She cites BPA, an industrial chemical that has been used since the 1960s to make certain plastics and resins. A large body of research, she says, has shown its impact on human health and the endocrine system. BPA binds to our own hormone receptors, so it may negatively impact the thyroid and brain. A study in 2015 was the first to identify a link between BPA and some children with autism, but the relationship was associative, not causative. Meanwhile, the Food and Drug Administration maintains that BPA is safe at the current levels occurring in food, based on its ongoing review of the available scientific evidence.
Michael Mooney, President of St. Louis-based Delta Genesis, a non-profit organization that treats children struggling with neurodevelopmental delays like autism, suspects a strong role for epigenetics, which refers to changes in how genes are expressed as a result of environmental influences, lifestyle behaviors, age, or disease states.
He believes some children are genetically predisposed to the disorder, and some unknown influence or combination of influences pushes them over the edge, triggering epigenetic changes that result in symptoms of autism.
For Stefania Sterling, it doesn't really matter how or why she had an autistic child. That's only one part of Charlie.
"It's not everything that makes Charlie," she said. "He's just like any other kid. He comes with happy moments. He comes with sad moments. Just like my other three kids."
The Death Predictor: A Helpful New Tool or an Ethical Morass?
Whenever Eric Karl Oermann has to tell a patient about a terrible prognosis, their first question is always: "how long do I have?" Oermann would like to offer a precise answer, to provide some certainty and help guide treatment. But although he's one of the country's foremost experts in medical artificial intelligence, Oermann is still dependent on a computer algorithm that's often wrong.
Doctors are notoriously terrible at guessing how long their patients will live.
Artificial intelligence, now often called deep learning or neural networks, has radically transformed language and image processing. It's allowed computers to play chess better than the world's grand masters and outwit the best Jeopardy players. But it still can't precisely tell a doctor how long a patient has left – or how to help that person live longer.
Someday, researchers predict, computers will be able to watch a video of a patient to determine their health status. Doctors will no longer have to spend hours inputting data into medical records. And computers will do a better job than specialists at identifying tiny tumors, impending crises, and, yes, figuring out how long the patient has to live. Oermann, a neurosurgeon at Mount Sinai, says all that technology will allow doctors to spend more time doing what they do best: talking with their patients. "I want to see more deep learning and computers in a clinical setting," he says, "so there can be more human interaction." But those days are still at least three to five years off, Oermann and other researchers say.
Doctors are notoriously terrible at guessing how long their patients will live, says Nigam Shah, an associate professor at Stanford University and assistant director of the school's Center for Biomedical Informatics Research. Doctors don't want to believe that their patient – whom they've come to like – will die. "Doctors over-estimate survival many-fold," Shah says. "How do you go into work, in say, oncology, and not be delusionally optimistic? You have to be."
But patients near the end of life will get better treatment – and even live longer – if they are overseen by hospice or palliative care, research shows. So, instead of relying on human bias to select those whose lives are nearing their end, Shah and his colleagues showed that they could use a deep learning algorithm based on medical records to flag incoming patients with a life expectancy of three months to a year. They use that data to indicate who might need palliative care. Then, the palliative care team can reach out to treating physicians proactively, instead of relying on their referrals or taking the time to read extensive medical charts.
But, although the system works well, Shah isn't yet sure if such indicators actually get the appropriate patients into palliative care. He's recently partnered with a palliative care doctor to run a gold-standard clinical trial to test whether patients who are flagged by this algorithm are indeed a better match for palliative care.
"What is effective from a health system perspective might not be effective from a treating physician's perspective and might not be effective from the patient's perspective," Shah notes. "I don't have a good way to guess everybody's reaction without actually studying it." Whether palliative care is appropriate, for instance, depends on more than just the patient's health status. "If the patient's not ready, the family's not ready and the doctor's not ready, then you're just banging your head against the wall," Shah says. "Given limited capacity, it's a waste of resources" to put that person in palliative care.
The algorithm isn't perfect, but "on balance, it leads to better decisions more often."
Alexander Smith and Sei Lee, both palliative care doctors, work together at the University of California, San Francisco, to develop predictions for patients who come to the hospital with a complicated prognosis or a history of decline. Their algorithm, they say, helps decide if this patient's problems – which might include diabetes, heart disease, a slow-growing cancer, and memory issues – make them eligible for hospice. The algorithm isn't perfect, they both agree, but "on balance, it leads to better decisions more often," Smith says.
Bethany Percha, an assistant professor at Mount Sinai, says that an algorithm may tell doctors that their patient is trending downward, but it doesn't do anything to change that trajectory. "Even if you can predict something, what can you do about it?" Algorithms may be able to offer treatment suggestions – but not what specific actions will alter a patient's future, says Percha, also the chief technology officer of Precise Health Enterprise, a product development group within Mount Sinai. And the algorithms remain challenging to develop. Electronic medical records may be great at her hospital, but if the patient dies at a different one, her system won't know. If she wants to be certain a patient has died, she has to merge social security records of death with her system's medical records – a time-consuming and cumbersome process.
An algorithm that learns from biased data will be biased, Shah says. Patients who are poor or African American historically have had worse health outcomes. If researchers train an algorithm on data that includes those biases, they get baked into the algorithms, which can then lead to a self-fulfilling prophesy. Smith and Lee say they've taken race out of their algorithms to avoid this bias.
Age is even trickier. There's no question that someone's risk of illness and death goes up with age. But an 85-year-old who breaks a hip running a marathon should probably be treated very differently than an 85-year-old who breaks a hip trying to get out of a chair in a dementia care unit. That's why the doctor can never be taken out of the equation, Shah says. Human judgment will always be required in medical care and an algorithm should never be followed blindly, he says.
Experts say that the flaws in artificial intelligence algorithms shouldn't prevent people from using them – carefully.
Researchers are also concerned that their algorithms will be used to ration care, or that insurance companies will use their data to justify a rate increase. If an algorithm predicts a patient is going to end up back in the hospital soon, "who's benefitting from knowing a patient is going to be readmitted? Probably the insurance company," Percha says.
Still, Percha and others say, the flaws in artificial intelligence algorithms shouldn't prevent people from using them – carefully. "These are new and exciting tools that have a lot of potential uses. We need to be conscious about how to use them going forward, but it doesn't mean we shouldn't go down this road," she says. "I think the potential benefits outweigh the risks, especially because we've barely scratched the surface of what big data can do right now."
“Young Blood” Transfusions Are Not Ready For Primetime – Yet
The world of dementia research erupted into cheers when news of the first real victory in a clinical trial against Alzheimer's Disease in over a decade was revealed last October.
By connecting the circulatory systems of a young and an old mouse, the regenerative potential of the young mouse decreased, and the old mouse became healthier.
Alzheimer's treatments have been famously difficult to develop; 99 percent of the 200-plus such clinical trials since 2000 have utterly failed. Even the few slight successes have failed to produce what is called 'disease modifying' agents that really help people with the disease. This makes the success, by the midsize Spanish pharma company Grifols, worthy of special attention.
However, the specifics of the Grifols treatment, a process called plasmapheresis, are atypical for another reason - they did not give patients a small molecule or an elaborate gene therapy, but rather simply the most common component of normal human blood plasma, a protein called albumin. A large portion of the patients' normal plasma was removed, and then a sterile solution of albumin was infused back into them to keep their overall blood volume relatively constant.
So why does replacing Alzheimer's patients' plasma with albumin seem to help their brains? One theory is that the action is direct. Alzheimer's patients have low levels of serum albumin, which is needed to clear out the plaques of amyloid that slowly build up in the brain. Supplementing those patients with extra albumin boosts their ability to clear the plaques and improves brain health. However, there is also evidence suggesting that the problem may be something present in the plasma of the sick person and pulling their plasma out and replacing it with a filler, like an albumin solution, may be what creates the purported benefit.
This scientific question is the tip of an iceberg that goes far beyond Alzheimer's Disease and albumin, to a debate that has been waged on the pages of scientific journals about the secrets of using young, healthy blood to extend youth and health.
This debate started long before the Grifols data was released, in 2014 when a group of researchers at Stanford found that by connecting the circulatory systems of a young and an old mouse, the regenerative potential of the young mouse decreased, and the old mouse became healthier. There was something either present in young blood that allowed tissues to regenerate, or something present in old blood that prevented regeneration. Whatever the biological reason, the effects in the experiment were extraordinary, providing a startling boost in health in the older mouse.
After the initial findings, multiple research groups got to work trying to identify the "active factor" of regeneration (or the inhibitor of that regeneration). They soon uncovered a variety of compounds such as insulin-like growth factor 1 (IGF1), CCL11, and GDF11, but none seemed to provide all the answers researchers were hoping for, with a number of high-profile retractions based on unsound experimental practices, or inconclusive data.
Years of research later, the simplest conclusion is that the story of plasma regeneration is not simple - there isn't a switch in our blood we can flip to turn back our biological clocks. That said, these hypotheses are far from dead, and many researchers continue to explore the possibility of using the rejuvenating ability of youthful plasma to treat a variety of diseases of aging.
But the bold claims of improved vigor thanks to young blood are so far unsupported by clinical evidence.
The data remain intriguing because of the astounding results from the conjoined circulatory system experiments. The current surge in interest in studying the biology of aging is likely to produce a new crop of interesting results in the next few years. Both CCL11 and GDF11 are being researched as potential drug targets by two startups, Alkahest and Elevian, respectively.
Without clarity on a single active factor driving rejuvenation, it's tempting to try a simpler approach: taking actual blood plasma provided by young people and infusing it into elderly subjects. This is what at least one startup company, Ambrosia, is now offering in five commercial clinics across the U.S. -- for $8,000 a liter.
By using whole plasma, the idea is to sidestep our ignorance, reaping the benefits of young plasma transfusion without knowing exactly what the active factors are that make the treatment work in mice. This space has attracted both established players in the plasmapheresis field – Alkahest and Grifols have teamed up to test fractions of whole plasma in Alzheimer's and Parkinson's – but also direct-to-consumer operations like Ambrosia that just want to offer patients access to treatments without regulatory oversight.
But the bold claims of improved vigor thanks to young blood are so far unsupported by clinical evidence. We simply haven't performed trials to test whether dosing a mostly healthy person with plasma can slow down aging, at least not yet. There is some evidence that plasma replacement works in mice, yes, but those experiments are all done in very different systems than what a human receiving young plasma might experience. To date, I have not seen any plasma transfusion clinic doing young blood plasmapheresis propose a clinical trial that is anything more than a shallow advertisement for their procedures.
The efforts I have seen to perform prophylactic plasmapheresis will fail to impact societal health. Without clearly defined endpoints and proper clinical trials, we won't know whether the procedure really lowers the risk of disease or helps with conditions of aging. So even if their hypothesis is correct, the lack of strong evidence to fall back on means that the procedure will never spread beyond the fringe groups willing to take the risk. If their hypothesis is wrong, then people are paying a huge amount of money for false hope, just as they do, sadly, at the phony stem cell clinics that started popping up all through the 2000s when stem cell hype was at its peak.
Until then, prophylactic plasma transfusions will be the domain of the optimistic and the gullible.
The real progress in the field will be made slowly, using carefully defined products either directly isolated from blood or targeting a bloodborne factor, just as the serious pharma and biotech players are doing already.
The field will progress in stages, first creating and carefully testing treatments for well-defined diseases, and only then will it progress to large-scale clinical trials in relatively healthy people to look for the prevention of disease. Most of us will choose to wait for this second stage of trials before undergoing any new treatments. Until then, prophylactic plasma transfusions will be the domain of the optimistic and the gullible.