With further research, clinical laboratories may soon be performing macrobiotic testing to measure certain bacterial levels in patients’ gut bacteria
New insights from the University of Chicago (UChicago) into how human microbiota (aka, gut bacteria) play a role in food allergies has the potential to change the way a number of gastrointestinal health conditions are diagnosed and treated. This would give microbiologists and clinical laboratories a greater role in helping physicians diagnose, treat, and monitor patients with these health issues.
Past research has shown that certain gut bacteria can prevent antigens that trigger allergic reactions from entering the bloodstream. For example, Clostridium bacteria in the stomach produce a short-chain fatty acid known as butyrate, a metabolite that promotes the growth of healthy bacteria in the gut. This helps keep the microbiome in balance.
One way butyrate is created in the gut is through the fermentation of fiber. However, a lack of fiber in the diet can deplete the production of butyrate and cause the microbiome to be out of balance. When this happens, a state known as dysbiosis occurs that disrupts the microbiome and can lead to food allergies.
Without butyrate, the gut lining can become permeable and allow food to leak out of the gastrointestinal tract and into the body’s circulatory system. This reaction can trigger a potentially fatal anaphylactic response in the form of a food allergy. Thus, eating enough fiber is critical to the production of butyrate and to maintaining a balanced microbiome.
But today’s western diet can be dangerously low in soluble fiber. Therefore, the scientists at the University of Chicago have developed “a special type of polymeric molecule to deliver a crucial metabolite produced by these bacteria directly to the gut, where it helps restore the intestinal lining and allows the beneficial bacteria to flourish. … these polymers, called micelles, can be designed to release a payload of butyrate, a molecule that is known to help prevent food allergies, directly in the small and large intestines,” according to a UChicago news release.
This will be of interest to microbiologists, in particular. It’s another example of researchers connecting a specific species of bacteria in the human microbiome to a specific benefit.
“It’s very unlikely that butyrate is the only relevant metabolite, but the beauty of this platform is that we can make polymers with other microbial metabolites that could be administered in conjunction with butyrate or other therapies,” said Cathryn Nagler, PhD (above), Bunning Family Professor in the Biological Sciences Division and Pritzker School of Molecular Engineering at UChicago and a senior author of the study. “So, the potential for the polymer platform is pretty much wide open.” As further research validates these findings, clinical labs are likely to be doing microbiomic testing to monitor these therapies. (Photo copyright: University of Chicago.)
Restoring Butyrate in the Gut
One way to treat this anomaly has been through a microbiota transplant—also called a fecal biota transplant—where the administration of a solution of fecal matter is transplanted from a donor into the intestinal tract of the recipient. This transplant alters the recipient’s gut microbial composition to a healthier state, but it has had mixed results.
So, the UChicago researchers went in another direction (literally). They created an oral solution of butyrate and administered it to mice in the lab. The purpose of the solution was to thwart an allergic reaction when the mice were exposed to peanuts.
But there was a problem with their oral solution. It was repulsive.
“Butyrate has a very bad smell, like dog poop and rancid butter, and it also tastes bad, so people wouldn’t want to swallow it,” Shijie Cao, PhD, Postdoctoral Scientist at the Pritzker School of Molecular Engineering at UChicago and one of the researchers who worked on the project, told Medical News Today.
The researchers developed a new configuration of polymers that masked the butyrate. They then delivered these polymer micelles directly into the digestive systems of mice that lacked healthy gut bacteria or a proper gut linings.
The treatment restored the microbiome by increasing the production of peptides that obliterate harmful bacteria. This allowed more of the beneficial butyrate-producing bacteria to emerge, which protected the mice from an anaphylactic reaction to peanuts and even reduced the symptom severity in an ulcerative colitis model.
“We were delighted to see that our drug both replenished the levels of butyrate present in the gut and helped the population of butyrate-producing bacteria to expand,” said Cathryn Nagler, PhD, Bunning Family Professor in the Biological Sciences Division and Pritzker School of Molecular Engineering at the University of Chicago and a senior author of the study, in the press release. “That will likely have implications not only for food allergy and inflammatory bowel disease (IBD), but also for the whole set of non-communicable chronic diseases that have been rising over the last 30 years, in response to lifestyle changes and overuse of antibiotics in our society.”
Future Benefits of UChicago Treatment
According to data from the Asthma and Allergy Foundation of America, about 20 million Americans suffered from food allergies in 2021. This includes approximately 16 million (6.2%) of adults and four million (5.8%) of children. The most common allergens for adults are shellfish, peanuts, and tree nuts, while the most common allergens for children are milk, eggs, and peanuts.
The best way to prevent an allergic reaction to a trigger food is strict avoidance. But this can be difficult to ensure outside of the home. Therefore, scientists are searching for ways to prevent food allergies from happening in the first place. The micelle technology could be adapted to deliver other metabolites and molecules which may make it a potential platform for treating allergies as well as other inflammatory gastrointestinal diseases.
“It’s a very flexible chemistry that allows us to target different parts of the gut,” said Jeffrey Hubbell, PhD, Eugene Bell Professor in Tissue Engineering and Vice Dean and Executive Officer at UChicago’s Pritzker School of Molecular Engineering and one of the project’s principal investigators, in the UChicago news release. “And because we’re delivering a metabolite like butyrate, it’s antigen-agnostic. It’s one agent for many different allergic indications, such as peanut or milk allergies. Once we begin working on clinical trials, that will be a huge benefit.”
Nagler and Hubbell have co-founded a company called ClostraBio to further the development of butyrate micelles into a commercially available treatment for peanut and other food allergies. They hope to begin clinical trials within the next 18 months and expand the technology to other applications as well.
Further research and clinical trials are needed to prove the validity of using polymer micelles in the treatment of diseases. But it is possible that clinical laboratories will be performing microbiomic testing in the future to help alleviate allergic reactions to food and other substances.
WASE-COVID Study also found that use of artificial intelligence technology minimized variability among echocardiogram scan results
Many physicians—including anatomic pathologists—are watching the development of artificial intelligence (AI)-powered diagnostic tools that are intended to analyze images and analyze the data with accuracy comparable to trained doctors. Now comes news of a recent study that demonstrated the ability of an AI tool to analyze echocardiograph images and deliver analyses equal to or better than trained physicians.
Conducted by researchers from the World Alliance Societies of Echocardiography and presented at the latest annual sessions of the American College of Cardiology (ACC), the WASE-COVID Study involved assessing the ability of the AI platform to analyze digital echocardiograph images with the goal of predicting mortality in patients with severe cases of COVID-19.
To complete their research, the WASE-COVID Study scientists examined 870 patients with acute COVID-19 infection from 13 medical centers in nine countries throughout Asia, Europe, United States, and Latin America.
Human versus Artificial Intelligence Analysis
Echocardiograms were analyzed with automated, machine learning-derived algorithms to calculate various data points and identify echocardiographic parameters that would be prognostic of clinical outcomes in hospitalized patients. The results were then compared to human analysis.
All patients in the study had previously tested positive for COVID-19 infection using a polymerase chain reaction (PCR) or rapid antigen test (RAT) and received a clinically-indicated echocardiogram upon admission. For those patients ultimately discharged from the hospital, a follow-up echocardiogram was performed after three months.
“What we learned was that the manual tracings were not able to predict mortality,” Federico Asch, MD, FACC, FASE, Director of the Echocardiography Core Lab at MedStar Health Research Institute in Washington, DC, told US Cardiology Review in a video interview describing the WASE-COVID Study findings.
Asch is also Associate Professor of Medicine (Cardiology) at Georgetown University. He added, “But on the same echoes, if the analysis was done by machine—Ultromics EchoGo Core, a software that is commercially available—when we used the measurements obtained through this platform, we were able to predict in-hospital and out-of-hospital mortality both with ejection fraction and left ventricular longitudinal strain.”
Nearly half of the 870 hospitalized patients were admitted to intensive care units, 27% were placed on ventilators, 188 patients died in the hospital, and 50 additional patients died within three to six months after being released from the hospital.
10 of 13 medical centers performed limited cardiac exams as their primary COVID in-patient practice and three out of the 13 centers performed comprehensive exams.
In-hospital mortality rates ranged from 11% in Asia, 19% in Europe, 26% in the US, to 27% in Latin America.
Left ventricular longitudinal strain (LVLS), right ventricle free wall strain (RVFWS), as well as a patient’s age, lactic dehydrogenase levels and history of lung disease, were independently associated with mortality. Left ventricle ejection fraction (LVEF) was not.
Fully automated quantification of LVEF and LVLS using AI minimized variability.
AI-based left ventricular analyses, but not manual, were significant predictors of in-hospital and follow-up mortality.
The WASE-COVID Study also revealed the varying international use of cardiac ultrasound (echocardiography) on COVID-19 patients.
“By using machines, we reduce variability. By reducing variability, we have a better capacity to compare our results with other outcomes, whether that outcome in this case is mortality or it could be changes over time,” Asch stated in the US Cardiology Review video. “What this really means is that we may be able to show associations and comparisons by using AI that we cannot do with manual [readings] because manual has more variation and is less reliable.”
He said the next steps will be to see if the findings hold true when AI is used in other populations of cardiac patients.
COVID-19 Pandemic Increased Need for Swift Analyses
An earlier WASE Study in 2016 set out to answer whether normal left ventricular heart chamber quantifications vary across countries, geographical regions, and cultures. However, the data produced by that study took years to review. Asch said the COVID-19 pandemic created a need for such analysis to be done more quickly.
“When the pandemic began, we knew that the clinical urgency to learn as much as possible about the cardiovascular connection to COVID-19 was incredibly high, and that we had to find a better way of securely and consistently reviewing all of this information in a timely manner,” he said in the Ultromics new release.
Coronary artery disease (CAD) is the most common form of heart disease and affects more than 16.5 million people over the age of 20. By 2035, the economic burden of CAD will reach an estimated $749 billion in the US alone, according to the Ultromics website.
“COVID-19 has placed an even greater pressure on cardiac care and looks likely to have lasting implications in terms of its impact on the heart,” said Ross Upton, PhD, Founder and CEO of Oxford, UK-based Ultromics, in a news release announcing the US Food and Drug Administration’s 510(k) clearance for the EchoGo Pro, which supports clinicians’ diagnosing of CAD. “The healthcare industry needs to quickly pivot towards AI-powered automation to reduce the time to diagnosis and improve patient care.”
Use of AI to analyze digital pathology images is expected to be a fast-growing element in the anatomic pathology profession, particularly in the diagnosis of cancer. As Dark Daily outlined in this free white Paper, “Anatomic Pathology at the Tipping Point? The Economic Case for Adopting Digital Technology and AI Applications Now,” anatomic pathology laboratories can expect adoption of AI and digital technology to gain in popularity among pathologists in coming years.
Latest research provides new opportunities for clinical laboratories to demonstrate how testing can help curb hospital-acquired infections
Pathologists, microbiologists, and other healthcare providers have long been aware that hospital patients taking antibiotics are at higher risk of contracting the potentially deadly Clostridium difficile infection (C. diff). But new research adds an interesting twist to this issue.
Recent research indicates that being a “second user” of a bed may be another risk factor for acquiring the disease. This will give clinical laboratory professionals, microbiologists, and others on the front lines of hospital infection control programs another factor to consider when working to halt the spread of hospital-acquired infections (HAIs).
The recent study was published online in JAMA Internal Medicine. It shows that patients put in a hospital bed previously occupied by someone given antibiotics are 22% more likely to develop the C. difficile infection, even if they do not themselves receive antibiotics. (more…)
The National Institute of Health’s ClinVar public database of genetic variation is demonstrating good accuracy, and a handful of clinical labs are learning to share and review this relatively small genetic database
Accessible databases like ClinVar, which was launched by the National Institute of Health (NIH) in 2013, have emerged to aggregate genetic sequencing with acceptable results. ClinVar exists to meet the needs of the medical genetics community. It collaborates with organizations to make pertinent genetic information available.
ClinVar is an archive of compiled data relating to genotype and phenotype variations among humans. Through this database, individuals can present and peruse submissions regarding variants found in patient samples.
ClinVar is averaging about 6,000 submissions per month by both commercial laboratory companies and reference labs. Major contributors to the database include: (more…)
Similar to Oscar Healthcare in New York, this California-based enterprise technology company offers services to make it easy for individuals to see providers’ prices, including medical laboratory test prices
Another company has entered the marketplace with their unorthodox business model to support health insurance programs. One cornerstone feature is a tool that enables both employers and beneficiaries to see the prices of different providers.
This young player in the health benefits marketplace is Castlight Health (NYSE: CSLT). Based in San Francisco, it was founded in 2008. One aspect of Castlight that pathologists and clinical laboratory managers may find particularly interesting is its price transparency tool. (more…)