The Nose Knows: Dogs Are Being Trained to Detect the Coronavirus
Asher is eccentric and inquisitive. He loves an audience, likes keeping busy, and howls to be let through doors. He is a six-year-old working Cocker Spaniel, who, with five other furry colleagues, has now been trained to sniff body odor samples from humans to detect COVID-19 infections.
As the Delta variant and other new versions of the SARS-CoV-2 virus emerge, public health agencies are once again recommending masking while employers contemplate mandatory vaccination. While PCR tests remain the "gold standard" of COVID-19 tests, they can take hours to flag infections. To accelerate the process, scientists are turning to a new testing tool: sniffer dogs.
At the London School of Hygiene and Tropical Medicine (LSHTM), researchers deployed Asher and five other trained dogs to test sock samples from 200 asymptomatic, infected individuals and 200 healthy individuals. In May, they published the findings of the yearlong study in a preprint, concluding that dogs could identify COVID-19 infections with a high degree of accuracy – they could correctly identify a COVID-positive sample up to 94% of the time and a negative sample up to 92% of the time. The paper has yet to be peer-reviewed.
"Dogs can screen lots of people very quickly – 300 people per dog per hour. This means they could be used in places like airports or public venues like stadiums and maybe even workplaces," says James Logan, who heads the Department of Disease Control at LSHTM, adding that canines can also detect variants of SARS-CoV-2. "We included samples from two variants and the dogs could still detect them."
Detection dogs have been one of the most reliable biosensors for identifying the odor of human disease. According to Gemma Butlin, a spokesperson of Medical Detection Dogs, the UK-based charity that trained canines for the LSHTM study, the olfactory capabilities of dogs have been deployed to detect malaria, Parkinson's disease, different types of cancers, as well as pseudomonas, a type of bacteria known to cause infections in blood, lungs, eyes, and other parts of the human body.
COVID-19 has a distinctive smell — a result of chemicals known as volatile organic compounds released by infected body cells, which give off an odor "fingerprint."
"It's estimated that the percentage of a dog's brain devoted to analyzing odors is 40 times larger than that of a human," says Butlin. "Humans have around 5 million scent receptors dedicated to smell. Dogs have 350 million and can detect odors at parts per trillion. To put this into context, a dog can detect a teaspoon of sugar in a million gallons of water: two Olympic-sized pools full."
According to LSHTM scientists, COVID-19 has a distinctive smell — a result of chemicals known as volatile organic compounds released by infected body cells, which give off an odor "fingerprint." Other studies, too, have revealed that the SARS-CoV-2 virus has a distinct olfactory signature, detectable in the urine, saliva, and sweat of infected individuals. Humans can't smell the disease in these fluids, but dogs can.
"Our research shows that the smell associated with COVID-19 is at least partly due to small and volatile chemicals that are produced by the virus growing in the body or the immune response to the virus or both," said Steve Lindsay, a public health entomologist at Durham University, whose team collaborated with LSHTM for the study. He added, "There is also a further possibility that dogs can actually smell the virus, which is incredible given how small viruses are."
In April this year, researchers from the University of Pennsylvania and collaborators published a similar study in the scientific journal PLOS One, revealing that detection dogs could successfully discriminate between urine samples of infected and uninfected individuals. The accuracy rate of canines in this study was 96%. Similarly, last December, French scientists found that dogs were 76-100% effective at identifying individuals with COVID-19 when presented with sweat samples.
Grandjean Dominique, a professor at France's National Veterinary School of Alfort, who led the French study, said that the researchers used two types of dogs — search and rescue dogs, as they can sniff sweat, and explosive detection dogs, because they're often used at airports to find bomb ingredients. Dogs may very well be as good as PCR tests, said Dominique, but the goal, he added, is not to replace these tests with canines.
In France, the government gave the green light to train hundreds of disease detection dogs and deploy them in airports. "They will act as mass pre-test, and only people who are positive will undergo a PCR test to check their level of infection and the kind of variant," says Dominique. He thinks the dogs will be able to decrease the amount of PCR testing and potentially save money.
Since the accuracy rate for bio-detection dogs is fairly high, scientists think they could prove to be a quick diagnosis and mass screening tool, especially at ports, airports, train stations, stadiums, and public gatherings. Countries like Finland, Thailand, UAE, Italy, Chile, India, Australia, Pakistan, Saudi Arabia, Switzerland, and Mexico are already training and deploying canines for COVID-19 detection. The dogs are trained to sniff the area around a person, and if they find the odor of COVID-19 they will sit or stand back from an individual as a signal that they've identified an infection.
While bio-detection dogs seem promising for cheap, large-volume screening, many of the studies that have been performed to date have been small and in controlled environments. The big question is whether this approach work on people in crowded airports, not just samples of shirts and socks in a lab.
"The next step is 'real world' testing where they [canines] are placed in airports to screen people and see how they perform," says Anna Durbin, professor of international health at the John Hopkins Bloomberg School of Public Health. "Testing in real airports with lots of passengers and competing scents will need to be done."
According to Butlin of Medical Detection Dogs, scalability could be a challenge. However, scientists don't intend to have a dog in every waiting room, detecting COVID-19 or other diseases, she said.
"Dogs are the most reliable bio sensors on the planet and they have proven time and time again that they can detect diseases as accurately, if not more so, than current technological diagnostics," said Butlin. "We are learning from them all the time and what their noses know will one day enable the creation an 'E-nose' that does the same job – imagine a day when your mobile phone can tell you that you are unwell."
Small changes in how a person talks could reveal Alzheimer’s earlier
Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.
“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”
Gene therapy helps restore teen’s vision for first time
Story by Freethink
For the first time, a topical gene therapy — designed to heal the wounds of people with “butterfly skin disease” — has been used to restore a person’s vision, suggesting a new way to treat genetic disorders of the eye.
The challenge: Up to 125,000 people worldwide are living with dystrophic epidermolysis bullosa (DEB), an incurable genetic disorder that prevents the body from making collagen 7, a protein that helps strengthen the skin and other connective tissues.Without collagen 7, the skin is incredibly fragile — the slightest friction can lead to the formation of blisters and scarring, most often in the hands and feet, but in severe cases, also the eyes, mouth, and throat.
This has earned DEB the nickname of “butterfly skin disease,” as people with it are said to have skin as delicate as a butterfly’s wings.
The gene therapy: In May 2023, the FDA approved Vyjuvek, the first gene therapy to treat DEB.
Vyjuvek uses an inactivated herpes simplex virus to deliver working copies of the gene for collagen 7 to the body’s cells. In small trials, 65 percent of DEB-caused wounds sprinkled with it healed completely, compared to just 26 percent of wounds treated with a placebo.
“It was like looking through thick fog.” -- Antonio Vento Carvajal.
The patient: Antonio Vento Carvajal, a 14 year old living in Florida, was one of the trial participants to benefit from Vyjuvek, which was developed by Pittsburgh-based pharmaceutical company Krystal Biotech.
While the topical gene therapy could help his skin, though, it couldn’t do anything to address the severe vision loss Antonio experienced due to his DEB. He’d undergone multiple surgeries to have scar tissue removed from his eyes, but due to his condition, the blisters keep coming back.
“It was like looking through thick fog,” said Antonio, noting how his impaired vision made it hard for him to play his favorite video games. “I had to stand up from my chair, walk over, and get closer to the screen to be able to see.”
The idea: Encouraged by how Antonio’s skin wounds were responding to the gene therapy, Alfonso Sabater, his doctor at the Bascom Palmer Eye Institute, reached out to Krystal Biotech to see if they thought an alternative formula could potentially help treat his patient’s eyes.
The company was eager to help, according to Sabater, and after about two years of safety and efficacy testing, he had permission, under the FDA’s compassionate use protocol, to treat Antonio’s eyes with a version of the topical gene therapy delivered as eye drops.
The results: In August 2022, Sabater once again removed scar tissue from Antonio’s right eye, but this time, he followed up the surgery by immediately applying eye drops containing the gene therapy.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy. Don’t be afraid.” -- Yunielkys “Yuni” Carvajal.
The vision in Antonio’s eye steadily improved. By about eight months after the treatment, it was just slightly below average (20/25) and stayed that way. In March 2023, Sabater performed the same procedure on his young patient’s other eye, and the vision in it has also steadily improved.
“I’ve seen the transformation in Antonio’s life,” said Sabater. “He’s always been a happy kid. Now he’s very happy. He can function pretty much normally. He can read, he can study, he can play video games.”
Looking ahead: The topical gene therapy isn’t a permanent fix — it doesn’t alter Antonio’s own genes, so he has to have the eye drops reapplied every month. Still, that’s far less invasive than having to undergo repeated surgeries.
Sabater is now working with Krystal Biotech to launch trials of the eye drops in other patients, and not just those with DEB. By changing the gene delivered by the therapy, he believes it could be used to treat other eye disorders that are far more common — Fuchs’ dystrophy, for example, affects the vision of an estimated 300 million people over the age of 30.
Antonio’s mother, Yunielkys “Yuni” Carvajal, meanwhile, has said that having her son be the first to receive the eye drops was “very scary,” but she’s hopeful others will take a chance on new gene therapies if given the opportunity.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy,” she said. “Don’t be afraid.”