Her Incredible Sense of Smell Led Scientists to Develop the First Parkinson's Test
Thirty-seven years ago, Joy Milne, a nurse from Perth, Scotland, noticed a musky odor coming from her husband, Les.
To her surprise, at a local support group meeting, she caught the familiar scent once again, hanging over the group like a cloud.
At first, Milne thought the smell was a result of bad hygiene and badgered her husband to take longer showers. But when the smell persisted, Milne learned to live with it, not wanting to hurt her husband's feelings.
Twelve years after she first noticed the "woodsy" smell, Les was diagnosed at the age of 44 with Parkinson's Disease, a neurodegenerative condition characterized by lack of dopamine production and loss of movement. Parkinson's Disease currently affects more than 10 million people worldwide.
Milne spent the next several years believing the strange smell was exclusive to her husband. But to her surprise, at a local support group meeting in 2012, she caught the familiar scent once again, hanging over the group like a cloud. Stunned, Milne started to wonder if the smell was the result of Parkinson's Disease itself.
Milne's discovery led her to Dr. Tilo Kunath, a neurobiologist at the Centre for Regenerative Medicine at the University of Edinburgh. Together, Milne, Kunath, and a host of other scientists would use Milne's unusual sense of smell to develop a new diagnostic test, now in development and poised to revolutionize the treatment of Parkinson's Disease.
"Joy was in the audience during a talk I was giving on my work, which has to do with Parkinson's and stem cell biology," Kunath says. "During the patient engagement portion of the talk, she asked me if Parkinson's had a smell to it." Confused, Kunath said he had never heard of this – but for months after his talk he continued to turn the question over in his mind.
Kunath knew from his research that the skin's microbiome changes during different disease processes, releasing metabolites that can give off odors. In the medical literature, diseases like melanoma and Type 2 diabetes have been known to carry a specific scent – but no such connection had been made with Parkinson's. If people could smell Parkinson's, he thought, then it stood to reason that those metabolites could be isolated, identified, and used to potentially diagnose Parkinson's by their presence alone.
First, Kunath and his colleagues decided to test Milne's sense of smell. "I got in touch with Joy again and we designed a protocol to test her sense of smell without her having to be around patients," says Kunath, which could have affected the validity of the test. In his spare time, Kunath collected t-shirt samples from people diagnosed with Parkinson's and from others without the diagnosis and gave them to Milne to smell. In 100 percent of the samples, Milne was able to detect whether a person had Parkinson's based on smell alone. Amazingly, Milne was even able to detect the "Parkinson's scent" in a shirt from the control group – someone who did not have a Parkinson's diagnosis, but would go on to be diagnosed nine months later.
From the initial study, the team discovered that Parkinson's did have a smell, that Milne – inexplicably – could detect it, and that she could detect it long before diagnosis like she had with her husband, Les. But the experiments revealed other things that the team hadn't been expecting.
"One surprising thing we learned from that experiment was that the odor was always located in the back of the shirt – never in the armpit, where we expected the smell to be," Kunath says. "I had a chance meeting with a dermatologist and he said the smell was due to the patient's sebum, which are greasy secretions that are really dense on your upper back. We have sweat glands, instead of sebum, in our armpits." Patients with Parkinson's are also known to have increased sebum production.
With the knowledge that a patient's sebum was the source of the unusual smell, researchers could go on to investigate exactly what metabolites were in the sebum and in what amounts. Kunath, along with his associate, Dr. Perdita Barran, collected and analyzed sebum samples from 64 participants across the United Kingdom. Once the samples were collected, Barran and others analyzed it using a method called gas chromatography mass spectrometry, or GS-MC, which separated, weighed and helped identify the individual compounds present in each sebum sample.
Barran's team can now correctly identify Parkinson's in nine out of 10 patients – a much quicker and more accurate way to diagnose than what clinicians do now.
"The compounds we've identified in the sebum are not unique to people with Parkinson's, but they are differently expressed," says Barran, a professor of mass spectrometry at the University of Manchester. "So this test we're developing now is not a black-and-white, do-you-have-something kind of test, but rather how much of these compounds do you have compared to other people and other compounds." The team identified over a dozen compounds that were present in the sebum of Parkinson's patients in much larger amounts than the control group.
Using only the GC-MS and a sebum swab test, Barran's team can now correctly identify Parkinson's in nine out of 10 patients – a much quicker and more accurate way to diagnose than what clinicians do now.
"At the moment, a clinical diagnosis is based on the patient's physical symptoms," Barran says, and determining whether a patient has Parkinson's is often a long and drawn-out process of elimination. "Doctors might say that a group of symptoms looks like Parkinson's, but there are other reasons people might have those symptoms, and it might take another year before they're certain," Barran says. "Some of those symptoms are just signs of aging, and other symptoms like tremor are present in recovering alcoholics or people with other kinds of dementia." People under the age of 40 with Parkinson's symptoms, who present with stiff arms, are often misdiagnosed with carpal tunnel syndrome, she adds.
Additionally, by the time physical symptoms are present, Parkinson's patients have already lost a substantial amount of dopamine receptors – about sixty percent -- in the brain's basal ganglia. Getting a diagnosis before physical symptoms appear would mean earlier interventions that could prevent dopamine loss and preserve regular movement, Barran says.
"Early diagnosis is good if it means there's a chance of early intervention," says Barran. "It stops the process of dopamine loss, which means that motor symptoms potentially will not happen, or the onset of symptoms will be substantially delayed." Barran's team is in the processing of streamlining the sebum test so that definitive results will be ready in just two minutes.
"What we're doing right now will be a very inexpensive test, a rapid-screen test, and that will encourage people to self-sample and test at home," says Barran. In addition to diagnosing Parkinson's, she says, this test could also be potentially useful to determine if medications were at a therapeutic dose in people who have the disease, since the odor is strongest in people whose symptoms are least controlled by medication.
"When symptoms are under control, the odor is lower," Barran says. "Potentially this would allow patients and clinicians to see whether their symptoms are being managed properly with medication, or perhaps if they're being overmedicated." Hypothetically, patients could also use the test to determine if interventions like diet and exercise are effective at keeping Parkinson's controlled.
"We hope within the next two to five years we will have a test available."
Barran is now running another clinical trial – one that determines whether they can diagnose at an earlier stage and whether they can identify a difference in sebum samples between different forms of Parkinson's or diseases that have Parkinson's-like symptoms, such as Lewy Body Dementia.
"Within the next one to two years, we hope to be running a trial in the Manchester area for those people who do not have motor symptoms but are at risk for developing dementia due to symptoms like loss of smell and sleep difficulty," Barran says. "If we can establish that, we can roll out a test that determines if you have Parkinson's or not with those first pre-motor symptoms, and then at what stage. We hope within the next two to five years we will have a test available."
But a definitive Parkinson's test, however revolutionary, would likely not be made available to the general population – at least, not for a while.
"We would likely first give this test to people who are at risk due to a genetic predisposition, or who are at risk based on prodomal symptoms, like people who suffer from a REM sleep disorder who have a 50 to 70 percent chance of developing Parkinson's within a ten year period," Barran says. "Those would be people who would benefit from early therapeutic intervention. For the normal population, it isn't beneficial at the moment to know until we have therapeutic interventions that can be useful."
Milne's husband, Les, passed away from complications of Parkinson's Disease in 2015. But thanks to him and the dedication of his wife, Joy, science may have found a way to someday prolong the lives of others with this devastating disease.
[Ed. Note: This hit article from our archives originally ran on September 3, 2019.]
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.