Saliva May Help Diagnose PTSD in Veterans
As a bioinformatician and young veteran, Guy Shapira welcomed the opportunity to help with conducting a study to determine if saliva can reveal if war veterans have post-traumatic stress disorder, or PTSD.
The research team, which drew mostly from Tel Aviv University’s Sackler Faculty of Medicine and Sagol School of Neuroscience, collected saliva samples from approximately 200 veterans who suffered psychological trauma stemming from the years they spent fighting in the First Lebanon War in 1982. The researchers also characterized the participants’ psychological, social and medical conditions, including a detailed analysis of their microbiomes.
They found that the former soldiers with PTSD have a certain set of bacteria in their saliva, a distinct microbiotic signature that is believed to be the first biological marker for PTSD. The finding suggests that, in the future, saliva tests could be used to help identify this disorder. As of now, PTSD is often challenging to diagnose.
Shapira, a Ph.D. student at Tel Aviv University, was responsible for examining genetic and health-related data of the veterans who participated – information that had been compiled steadily over four decades. The veterans provided this data voluntarily, Shapira says, at least partly because the study carries important implications for their own psychological health.
The research was led by Illana Gozes, professor emerita of clinical biochemistry. “We looked at the bacteria in their blood and their saliva,” Gozes explains. To discover the microbial signatures, they analyzed the biometric data for each soldier individually and as a group. Comparing the results of the participants’ microbial distribution to the results of their psychological examinations and their responses to personal welfare questionnaires, the researchers learned that veterans with PTSD – and, more generally, those with significant mental health issues – have the same bacterial content in their saliva.
“Having empirical metrics to assess whether or not someone has PTSD can help veterans who make their case to the Army to get reparations,” Shapira says.
More research is required to support this finding, published in July in Nature’s prestigious Molecular Psychiatry, but it could have important implications for identifying people with PTSD. Currently, it can be diagnosed only through psychological and behavioral symptoms such as flashbacks, nightmares, sleep disorders, increased irritability and physical aggressiveness. Veterans sometimes don’t report these symptoms to health providers or realize they’re related to the trauma they experienced during combat.
The researchers also identified a correlation that indicates people with a higher level of education show a lower occurrence of the microbiotic signature linked to PTSD, while people who experienced greater exposure to air pollution show a higher occurrence of this signature. That confirms their finding that the veterans’ health is dependent on their individual biology combined with the conditions of their environment.
“Thanks to this study, it may be possible in the future to use objective molecular and biological characteristics to distinguish PTSD sufferers, taking into account environmental influences,” Gozes said in an article in Israel21c. “We hope that this new discovery and the microbial signatures described in this study might promote easier diagnosis of post-traumatic stress in soldiers so they can receive appropriate treatment.”
Gozes added that roughly a third of the subjects in their study hadn’t been diagnosed with PTSD previously. That meant they had never received any support from Israel’s Ministry of Defense or other officials for treatment and reparations, the payments to compensate for injuries sustained during war.
Shapira’s motivation to participate in this study is personal as well as professional: in addition to being veteran himself, his father served in the First Lebanon War. “Fortunately, he did not develop any PTSD, despite being shot in the foot...some of his friends died, so it wasn’t easy on him,” says Shapira.
“Having empirical metrics to assess whether or not someone has PTSD can help veterans who make their case to the Army to get reparations,” Shapira says. “It is a very difficult and demanding process, so the more empirical metrics we have to assess PTSD, the less people will have to suffer in these committees and unending examinations that are mostly pitched against the veterans because the state is trying to avoid spending too much money.”
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.