Though the new technology could speed diagnoses of cancers and other skin diseases, it would also greatly reduce dermatopathology biopsy referrals and revenue
What effect would elimination of tissue biopsies have on dermatopathology and clinical laboratory revenue? Quite a lot. Dermatologists alone account for a significant portion of skin biopsies sent to dermatopathologists. Thus, any new technology that can “eliminate the need for invasive skin biopsies” would greatly reduce the number of histopathological referrals and reduce revenue to those practices.
“What if we could entirely bypass the biopsy process and perform histology-quality staining without taking tissue and processing tissue in a noninvasive way? Can we create images that diagnosticians can benefit from?” asked Aydogan Ozcan, PhD (above), Chancellor’s Professor of Electrical and Computer Engineering at UCLA’s Samueli School of Engineering, one of the scientists who developed UCLA’s new virtual histology method, during an interview with Medical Device + Diagnostic Industry (MD+DI). (Photo copyright: Nature.)
Could Skin Biopsies be Eliminated?
The UCLA researchers believe their innovative deep learning-enabled imaging framework could possibly circumvent the need for skin biopsies to diagnose skin conditions.
“Here, we present a deep learning-based framework that uses a convolutional neural network to rapidly transform in vivo RCM images of unstained skin into virtually-stained hematoxylin and eosin-like images with microscopic resolution, enabling visualization of the epidermis, dermal-epidermal junction, and superficial dermis layers.
“This application of deep learning-based virtual staining to noninvasive imaging technologies may permit more rapid diagnoses of malignant skin neoplasms and reduce invasive skin biopsies,” the researchers added in their published study.
According to the published study, the UCLA team trained their neural network under an adversarial machine learning scheme to transform grayscale RCM images into virtually stained 3D microscopic images of normal skin, basal cell carcinoma, and pigmented melanocytic nevi. The new images displayed similar morphological features to those shown with the widely used hematoxylin and eosin (H&E) staining method.
“In our studies, the virtually stained images showed similar color contrast and spatial features found in traditionally stained microscopic images of biopsied tissue,” Ozcan told Photonics Media. “This approach may allow diagnosticians to see the overall histological features of intact skin without invasive skin biopsies or the time-consuming work of chemical processing and labeling of tissue.”
The framework covers different skin layers, including the epidermis, dermal-epidermis, and superficial dermis layers. It images deeper into tissue without being invasive and can be quickly performed.
“The virtual stain technology can be streamlined to be almost semi real time,” Ozcan told Medical Device + Diagnostic Industry (MD+DI). “You can have the virtual staining ready when the patient is wrapping up. Basically, it can be within a couple of minutes after you’re done with the entire imaging.”
Currently, medical professionals rely on invasive skin biopsies and histopathological evaluations to diagnose skin diseases and cancers. These diagnostic techniques can result in unnecessary biopsies, scarring, multiple patient visits and increased medical costs for patients, insurers, and the healthcare system.
Improving Time to Diagnosis through Digital Pathology
Another advantage of this virtual technology, the UCLA researchers claim, is that it can provide better images than traditional staining methods, which could improve the ability to diagnose pathological skin conditions and help alleviate human error.
“The majority of the time, small laboratories have a lot of problems with consistency because they don’t use the best equipment to cut, process, and stain tissue,” dermatopathologist Philip Scumpia, MD, PhD, Assistant Professor of Dermatology and Dermatopathology at UCLA Health and one of the authors of the research paper, told MD+DI.
“What ends up happening is we get tissue on a histology slide that’s basically unevenly stained, unevenly put on the microscope, and it gets distorted,” he added, noting that this makes it very hard to make a diagnosis.
Scumpia also added that this new technology would allow digital images to be sent directly to the pathologist, which could reduce processing and laboratory times.
“With electronic medical records now and the ability to do digital photography and digital mole mapping, where you can obtain a whole-body imaging of patients, you could imagine you can also use one of these reflectance confocal devices. And you can take that image from there, add it to the EMR with the virtual histology stain, which will make the images more useful,” Scumpia said. “So now, you can track lesions as they develop.
“What’s really exciting too, is that there’s the potential to combine it with other artificial intelligence, other machine learning techniques that can give more information,” Scumpia added. “Using the reflectance confocal microscope, a clinician who might not be as familiar in dermatopathology could take images and send [them] to a practitioner who could give a more expert diagnosis.”
Faster Diagnoses but Reduced Revenue for Dermatopathologists, Clinical Labs
Ozcan noted that there’s still a lot of work to be done in the clinical assessment, validation, and blind testing of their AI-based staining method. But he hopes the technology can be propelled into a useful tool for clinicians.
“I think this is a proof-of-concept work, and we’re very excited to make it move forward with further advances in technology, in the ways that we acquire 3D information [and] train our neural networks for better and faster virtual staining output,” he told MD+DI.
Though this new technology may reduce the need for invasive biopsies and expedite the diagnosis of skin conditions and cancers—thus improving patient outcomes—what affect might it have on dermatopathology practices?
More research and clinical studies are needed before this new technology becomes part of the diagnosis and treatment processes for skin conditions. Nevertheless, should virtual histology become popular and viable, it could greatly impact the amount of skin biopsy referrals to pathologists, dermatopathologists, and clinical laboratories, thus diminishing a great portion of their revenue.
MIT’s deep learning artificial intelligence algorithm demonstrates how similar new technologies and smartphones can be combined to give dermatologists and dermatopathologists valuable new ways to diagnose skin cancer from digital images
According to an MIT press release, “The paper describes the development of an SPL [Suspicious Pigmented Lesion] analysis system using DCNNs [Deep Convolutional Neural Networks] to more quickly and efficiently identify skin lesions that require more investigation, screenings that can be done during routine primary care visits, or even by the patients themselves. The system utilized DCNNs to optimize the identification and classification of SPLs in wide-field images.”
The MIT scientists believe their AI analysis system could aid dermatologists, dermatopathologists, and clinical laboratories detect melanoma, a deadly form of skin cancer, in its early stages using smartphones at the point-of-care.
“Our research suggests that systems leveraging computer vision and deep neural networks, quantifying such common signs, can achieve comparable accuracy to expert dermatologists,” said Luis Soenksen, PhD (above), Venture Builder in Artificial Intelligence and Healthcare at MIT and first author of the study in an MIT press release. “We hope our research revitalizes the desire to deliver more efficient dermatological screenings in primary care settings to drive adequate referrals.” The MIT study demonstrates that dermatologists, dermatopathologists, and clinical laboratories can benefit from using common technologies like smartphones in the diagnosis of disease. (Photo copyright: Wyss Institute Harvard University.)
Improving Melanoma Treatment and Patient Outcomes
Melanoma develops when pigment-producing cells called melanocytes start to grow out of control. The cancer has traditionally been diagnosed through visual inspection of SPLs by physicians in medical settings. Early-stage identification of SPLs can drastically improve the prognosis for patients and significantly reduce treatment costs. It is common to biopsy many lesions to ensure that every case of melanoma can be diagnosed as early as possible, thus contributing to better patient outcomes.
“Early detection of SPLs can save lives. However, the current capacity of medical systems to provide comprehensive skin screenings at scale are still lacking,” said Luis Soenksen, PhD, Venture Builder in Artificial Intelligence and Healthcare at MIT and first author of the study in the MIT press release.
The researchers trained their AI system by using 20,388 wide-field images from 133 patients at the Gregorio Marañón General University Hospital in Madrid, as well as publicly available images. The collected photographs were taken with a variety of ordinary smartphone cameras that are easily obtainable by consumers.
They taught the deep learning algorithm to examine various features of skin lesions such as size, circularity, and intensity. Dermatologists working with the researchers also visually classified the lesions for comparison.
When the algorithm is “shown” a wide-field image like that above taken with a smartphone, it uses deep convolutional neural networks to analyze individual pigmented lesions and screen for early-stage melanoma. The algorithm then marks suspicious images as either yellow (meaning further inspection should be considered) or red (indicating that further inspection and/or referral to a dermatologist is required). Using this tool, dermatopathologists may be able to diagnose skin cancer and excise it in-office long before it becomes deadly. (Photo copyright: MIT.)
“Our system achieved more than 90.3% sensitivity (95% confidence interval, 90 to 90.6) and 89.9% specificity (89.6 to 90.2%) in distinguishing SPLs from nonsuspicious lesions, skin, and complex backgrounds, avoiding the need for cumbersome individual lesion imaging,” the MIT researchers noted in their Science Translational Medicine paper.
In addition, the algorithm agreed with the consensus of experienced dermatologists 88% of the time and concurred with the opinions of individual dermatologists 86% of the time, Medgadget reported.
Modern Imaging Technologies Will Advance Diagnosis of Disease
According to the American Cancer Society, about 106,110 new cases of melanoma will be diagnosed in the United States in 2021. Approximately 7,180 people are expected to die of the disease this year. Melanoma is less common than other types of skin cancer but more dangerous as it’s more likely to spread to other parts of the body if not detected and treated early.
More research is needed to substantiate the effectiveness and accuracy of this new tool before it could be used in clinical settings. However, the early research looks promising and smartphone camera technology is constantly improving. Higher resolutions would further advance development of this type of diagnostic tool.
In addition, MIT’s algorithm enables in situ examination and possible diagnosis of cancer. Therefore, a smartphone so equipped could enable a dermatologist to diagnose and excise cancerous tissue in a single visit, without the need for biopsies to be sent to a dermatopathologist.
Currently, dermatologists refer a lot of skin biopsies to dermapathologists and anatomic pathology laboratories. An accurate diagnostic tool that uses modern smartphones to characterize suspicious skin lesions could become quite popular with dermatologists and affect the flow of referrals to medical laboratories.
DeepMind hopes its unrivaled collection of data, enabled by artificial intelligence, may advance development of precision medicines, new medical laboratory tests, and therapeutic treatments
‘Tis the season for giving, and one United Kingdom-based artificial intelligence (AI) research laboratory is making a sizeable gift. After using AI and machine learning to create “the most comprehensive map of human proteins,” in existence, DeepMind, a subsidiary of Alphabet Inc. (NASDAQ:GOOGL), parent company of Google, plans to give away for free its database of millions of protein structure predictions to the global scientific community and to all of humanity, The Verge reported.
Pathologists and clinical laboratory scientists developing proteomic assays understand the significance of this gesture. They know how difficult and expensive it is to determine protein structures using sequencing of amino acids. That’s because the various types of amino acids in use cause the [DNA] string to “fold.” Thus, the availability of this data may accelerate the development of more diagnostic tests based on proteomics.
“For decades, scientists have been trying to find a method to reliably determine a protein’s structure just from its sequence of amino acids. Attraction and repulsion between the 20 different types of amino acids cause the string to fold in a feat of ‘spontaneous origami,’ forming the intricate curls, loops, and pleats of a protein’s 3D structure. This grand scientific challenge is known as the protein-folding problem,” a DeepMind statement noted.
Enter DeepMind’s AlphaFold AI platform to help iron things out. “Experimental techniques for determining structures are painstakingly laborious and time consuming (sometimes taking years and millions of dollars). Our latest version [of AlphaFold] can now predict the shape of a protein, at scale and in minutes, down to atomic accuracy. This is a significant breakthrough and highlights the impact AI can have on science,” DeepMind stated.
Release of Data Will Be ‘Transformative’
In July, DeepMind announced it would begin releasing data from its AlphaFold Protein Structure Database which contains “predictions for the structure of some 350,000 proteins across 20 different organisms,” The Verge reported, adding, “Most significantly, the release includes predictions for 98% of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. By the end of the year, DeepMind hopes to release predictions for 100 million protein structures.”
According to Edith Heard, PhD, Director General of the European Molecular Biology Laboratory (EMBL), the open release of such a dataset will be “transformative for our understanding of how life works,” The Verge reported.
“I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis (above), told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.” The release of DeepMind’s entire protein prediction database will certainly do that. Clinical laboratory scientists worldwide will have free access to use it in developing new precision medicine treatments based on proteomics. (Photo copyright: BBC.)
Free Data about Proteins Will Accelerate Research on Diseases, Treatments
Research into how protein folds and, thereby, functions could have implications to fighting diseases and developing new medicines, according to DeepMind.
“This will be one of the most important datasets since the mapping of the human genome,” said Ewan Birney, PhD, Deputy Director General of the EMBL, in the DeepMind statement. EMBL worked with DeepMind on the dataset.
DeepMind protein prediction data are already being used by scientists in medical research. “Anyone can use it for anything. They just need to credit the people involved in the citation,” said Demis Hassabis, DeepMind CEO and Co-founder, in The Verge.
In a blog article, Hassabis listed several projects and organizations already using AlphaFold. They include:
“As researchers seek cures for diseases and pursue solutions to other big problems facing humankind—including antibiotic resistance, microplastic pollution, and climate change—they will benefit from fresh insights in the structure of proteins,” Hassabis wrote.
Because of the deep financial backing that Alphabet/Google can offer, it is reasonable to predict that DeepMind will make progress with its AI technology that regularly adds capabilities and accuracy, allowing AlphaFold to be effective for many uses.
This will be particularly true for the development of new diagnostic assays that will give clinical laboratories better tools for diagnosing disease earlier and more accurately.
Research could lead to clinical laboratory tests in service of precision medicine therapies to reduce a person’s susceptibility to being targeted by blood-sucking insects
Ever wonder why some people attract mosquitoes while others do not? Could biting insects pick their victims by smell? Scientists in California believe the answers to these questions could lead to new precision medicine therapies and clinical laboratory tests.
The research revealed evidence that some blood-sucking insects may identify their prey by homing in on the “scent” of chemicals produced by bacteria located in the skin microbiome of animals and humans.
This is yet another example of research into one area of the human microbiome that might someday lead to a new clinical laboratory test, in this case to determine if a person is more likely to attracts biting insects. If there were such a test, precision medicine therapies could be developed that change an individual’s microbiome to discourage insects from biting that individual.
Then, the clinical laboratory test would have value because it helped diagnose a health condition that is treatable.
Curiosity regarding why mosquitoes seem to gravitate towards some humans over others was the original catalyst for the UCSD Medical School research. “You know when you go to a barbeque and your friend is getting bombarded by mosquitos, but you’re fine? There is some research to support the idea that the difference in mosquito attraction is linked to your skin microbiome—the unique community of bacteria living on your skin,” said Holly Lutz, PhD (above), first author of the UCSD study. “Keeping in mind that some people are more attractive to mosquitoes than others, I wondered what makes insects attracted to some bats but not others.” Lutz’s research could lead to clinical laboratory tests that drive precision medicine therapies to alter human skin microbiomes and make people less attractive to biting insects. (Photo copyright: The Field Museum of Natural History.)
Biting Flies Prefer Specific Bats
“In these caves, I’d see all these different bat species or even taxonomic families roosting side by side. Some of them were loaded with bat flies, while others had none or only a few,” Lutz said in Phys.org. “And these flies are typically very specific to different kinds of bats—you won’t find a fly that normally feeds on horseshoe bats crawling around on a fruit bat. I started wondering why the flies are so particular. Clearly, they can crawl over from one kind of bat to another, but they don’t really seem to be doing that.”
The researchers suspected that the bacteria contained in the skin microbiomes of individual bats could be influencing which bats the flies selected to bite. The bacteria produce a distinctive odor which may make certain bats more attractive to the flies.
The type of fly assessed for the study are related to mosquitoes and most of them are incapable of flight.
“They have incredibly reduced wings in many cases and can’t actually fly,” Lutz explained. “And they have reduced eyesight, so they probably aren’t really operating by vision. So, some other sensory mechanisms must be at play, maybe a sense of smell or an ability to detect chemical cues.”
To test their hypothesis, the research team collected skin and fur samples from the bodies and wings of a variety of bat species located in various caves around Kenya and Uganda. They collected their samples at 14 field sites from August to October in 2016. They then examined the DNA of the bats as well as the microbes residing on the animals’ skin and searched for the presence of flies.
“The flies are exquisitely evolved to stay on their bat,” said Carl Dick, PhD, a professor of biology at Western Kentucky University and one of the study’s authors. “They have special combs, spines, and claws that hold them in place in the fur, and they can run quickly in any direction to evade the biting and scratching of the bats, or the efforts by researchers to capture them,” he told Phys.org.
“You brush the bats’ fur with your forceps, and it’s like you’re chasing the fastest little spider,” Lutz said. “The flies can disappear in a split second. They are fascinatingly creepy.”
Genetic Sequencing DNA of Bat Skin Bacteria
After collecting their specimens, the researchers extracted DNA from the collected bacteria and performed genetic sequencing on the samples. They created libraries of the bacteria contained in each skin sample and used bioinformatics methods to identify the bacteria and compare the samples from bats that had flies versus those that did not.
“How the flies actually locate and find their bats has previously been something of a mystery,” Dick noted. “But because most bat flies live and feed on only one bat species, it’s clear that they somehow find the right host.”
The scientists discovered that different bat families did have their own distinctive skin microbiome, even among samples collected from different locations. They found that differences in the skin microbiomes of certain bats does contribute to whether those bats have parasites. But not all their questions were answered.
“We weren’t able to collect the actual chemicals producing cue—secondary metabolites or volatile organic compounds—during this initial work. Without that information, we can’t definitively say that the bacteria are leading the flies to their hosts,” Lutz said.
Next Steps
“So, next steps will be to sample bats in a way that we can actually tie these compounds to the bacteria. In science, there is always a next step,” she added.
This research illustrates that there may be a reason why certain animals and humans tend to be more attractive to insects than others. It is also possible that an individual’s skin microbiome may explain why some people are more prone to mosquito and other types of insect bites.
More research and clinical studies on this topic are needed, but it could possibly lead to a clinical laboratory test to determine if an individual’s skin microbiome could contribute to his or her potential to being bitten by insects. Such a test would be quite beneficial, as insects can carry a variety of diseases that are harmful to humans.
Perhaps a precision medicine therapy could be developed to alter a person’s microbiome to make them invisible to blood-sucking insects. That would be a boon to regions of the world were diseases like malaria are spread by insect bites.
Determining how dogs do this may lead to biomarkers for new clinical laboratory diagnostics tests
Development of new diagnostic olfactory tools for prostate and other cancers is expected to result from research now being conducted by a consortium of researchers at different universities and institutes. To identify new biomarkers, these scientists are studying how dogs can detect the presence of prostate cancer by sniffing urine specimens.
Funded by a grant from the Prostate Cancer Foundation, the pilot study demonstrated that dogs could identify prostate samples containing cancer and discern between cancer positive and cancer negative samples.
Canine Olfactory Combined with Artificial Intelligence Analysis Approach
The part of a canine brain that controls smell is 40 million times greater than that of humans. Some dog breeds have 300 to 350 million sensory receptors, compared to about five million in humans. With their keen sense of smell, dogs are proving to be vital resources in the detection of some diseases.
The pilot study examined how dogs could be trained to detect prostate cancer in human urine samples.
Claire Guest, CEO and Chief Scientific Officer of UK-based Medical Detection Dogs and one of the study authors, is shown above with one of her cancer detecting dogs. In a Prostate Cancer Foundation article, she said, “Prostate cancer is not going to turn out to be a single note. What dogs are really good at discovering is a tune. Think of Beethoven’s Fifth Symphony, those first few notes. We suspect the cancer signature is something like that. It’s a pattern; the dogs are really good at recognizing the pattern. Machines that recognize the notes but can’t read the pattern are not reliable biomarkers,” she noted. The researchers believe the best solution for developing a clinical laboratory diagnostic that detects prostate cancer may be a combined approach using canine olfaction and AI neural networks. (Photo copyright: Janine Warwick/NPR.)
To perform the study, the researchers trained two dogs to sniff urine samples from men with high-grade prostate cancer and from men without the cancer. The two dogs used in the study were a four-year-old female Labrador Retriever named Florin, and a seven-year-old female wirehaired Hungarian Vizsla named Midas. The dogs were trained to respond to cancer-related chemicals, known as volatile organic compounds, or VOCs, the researchers added to the urine samples, and to not respond to the samples without the VOCs.
Both dogs performed well in their cancer detection roles, and both successfully identified five of seven urine samples from men with prostate cancer, correlating to a 71.4% accuracy rate. In addition, Florin correctly identified 16 of 21 non-aggressive or no cancer samples for an accuracy rate of 76.2% and Midas did the same with a 66.7% accuracy rate.
“We wondered if having the dogs detect the chemicals, combined with analysis by GC-MS, bacterial profiling, and an artificial intelligence (AI) neural network trained to emulate the canine cancer detection ability, could significantly improve the diagnosis of high-grade prostate cancer,” said Alan Partin, MD, PhD, Professor of Urology, Pathology and Oncology, Johns Hopkins University School of Medicine and one of the authors of the study, told Futurity.
The researchers determined that canine olfaction was able to distinguish between positive and negative prostate cancer in the samples, and the VOC and microbiota profiling analyses showed a qualitative difference between the two groups. The multisystem approach demonstrated a more sensitive and specific way of detecting the presence of prostate cancer than any of the methods used by themselves.
In their paper, the researchers concluded that “this study demonstrated feasibility and identified the challenges of a multiparametric approach as a first step towards creating a more effective, non-invasive early urine diagnostic method for the highly aggressive histology of prostate cancer.”
Can Man’s Best Friend be Trained to Detect Cancer and Save Lives?
Prostate cancer is the second leading cause of cancer deaths among men in the developed world. And, according to data from the National Cancer Institute, standard clinical laboratory blood tests, such as the prostate-specific antigen (PSA) test for early detection, sometimes miss the presence of cancer.
Establishing an accurate, non-invasive method of sensing the disease could help detect the disease sooner when it is more treatable and save lives.
The American Cancer Society estimates that there will be about 248,530 new cases of prostate cancer diagnosed in 2021 and that there will be approximately 34,130 deaths resulting from the disease during the same year.
Of course, more testing will be needed before Man’s best friend can be put to work detecting cancer in medical environments. But if canines can be trained to detect the disease early, and in a non-invasive way, more timely diagnosis and treatment could result in higher survival rates.
Meanwhile, as researchers identify the elements dogs use to detect cancer and other diseases, this knowledge can result in the creation of new biomarkers than can be used in clinical laboratory tests.
Although there are healthcare providers who see the potential in microbiome testing, many clinical laboratories are not yet ready to embrace microbiome-based testing
In an unlikely string of events, no less than Nordstrom, the national department store chain, announced in September that it would offer microbiome-based test claimed to “check gut health.” Apparently, its customers were interested in this clinical laboratory test, as the Nordstrom website currently indicates that the “Health Intelligence Test Kit by Viome” is already sold out!
What does it say about consumer interest in clinical laboratory self-testing that Nordstrom has decided to offer at-home microbiome tests to its store customers? Can it be assumed that Nordstrom conducted enough marketing surveys of its customers to determine: a) that they were interested in microbiome testing; and b) they would buy enough microbiome tests that Nordstrom would benefit financially from either the mark-up on the tests or from the derived goodwill for meeting customer expectations?
Whatever the motivation, the retail giant recently announced it had partnered with Viome Life Sciences to sell Viome’s microbiome testing kits to its customers online, and in 2022, at some Nordstrom retail locations. These tests are centered around helping consumers understand the relationship between their microbiome and nutrition.
Pathologists and clinical laboratories will want to track Nordstrom’s success or failure in selling microbiome-based assays to its consumers. Microbiomics is in its infancy and remains a very unsettled area of diagnostics. Similarly, Viome, a self-described precision health and wellness company that conducts mRNA analysis at scale, will need to demonstrate that its strategy of developing precision medicine diagnostics and therapeutics based on the human microbiome has clinical relevance.
Helping Consumers with ‘Precision Nutrition’
In a September news release, Viome founder and CEO Naveen Jain, a serial entrepreneur, said, “Both Viome and Nordstrom believe that true health and beauty start from within. There is no such thing as a universal healthy food or healthy supplement. What is right for one person can be wrong for someone else, especially when it comes to nutrition which is key to human longevity and vitality. Precision nutrition is the future!”
“Precision medicine seeks to improve the personalized treatment of diseases, and precision nutrition is specific to dietary intake. Both develop interventions to prevent or treat chronic diseases based on a person’s unique characteristics like DNA, race, gender, health history, and lifestyle habits. Both aim to provide safer and more effective ways to prevent and treat disease by providing more accurate and targeted strategies.
“Precision nutrition assumes that each person may have a different response to specific foods and nutrients, so that the best diet for one individual may look very different than the best diet for another.
“Precision nutrition also considers the microbiome, trillions of bacteria in our bodies that play a key role in various daily internal operations. What types and how much bacteria we have are unique to each individual. Our diets can determine which types of bacteria live in our digestive tracts, and according to precision nutrition the reverse is also true: the types of bacteria we house might determine how we break down certain foods and what types of foods are most beneficial for our bodies.”
Medical Laboratory Testing, not Guessing
Viome Life Sciences is a microbiome and RNA analysis company based in Bellevue, Wash. The test kit that Nordstrom is selling is called the Health Intelligence Test. It is an at-home mRNA test that can provide users with some insights regarding their health. Consumers use the kit to collect blood and fecal samples, then return those samples to Viome for testing.
In a press release announcing its collaboration with Nordstrom, Viome said, “In a world overwhelmed by information relating to diet and supplement advice, Viome believes in testing, not guessing and empowering its users with actionable insights. To date, Viome has helped over 250,000 individuals improve their health through precision nutrition powered by microbial and human gene expression insights.”
Nordstrom began offering Viome’s Health Intelligence Test kit for $199 on its website starting in September. As of this writing and noted above, the kits are sold out. Nordstrom plans to stock the kit in select stores starting in 2022.
Viome’s Health Intelligence Test kit (above) looks at the microbiome to determine gut health, cellular health, healthy aging, immune health, and stress responses. Test results offer consumers personalized nutritional suggestions and recommendations for supplements, probiotics, and prebiotics based on an individual’s biology. Test are performed by Viome’s own clinical laboratories and results sent directly to Nordstrom’s customers. (Photo copyright: Viome Life Sciences.)
Individuals who purchase the test submit blood and stool samples to Viome’s lab which performs an analysis of gene activity patterns in the user’s cells and microbiome. Viome provides the results to consumers within two to three weeks.
“This partnership is a giant step towards making our technology more accessible, so people can understand what’s right for their unique body,” Jain said in the news release. “We are inspired each day by the incredible changes our customers are seeing in their health including improvements in digestion, weight, stress, ability to focus, and more.”
According to the news release, Viome conducted blind studies earlier this year that revealed significant successes based on their precision nutritional approach to wellness. Study participants, Viome claims, improved their outcomes to four diseases through nutrition:
Is Microbiome Diagnostics Testing Ready for Clinical Use?
Microbiomics is a relatively new field of diagnostics research. Much more research and testing will be needed to prove its clinical value and efficacy in healthcare diagnostics. Nevertheless, companies are offering microbiomics testing to consumers and that has some healthcare providers concerned.
In the GeekWire article, David Suskind, MD, a gastroenterologist at Seattle Children’s Hospital and Professor of Pediatrics at the University of Washington, described Viome’s study methodology as “questionable,” adding, “I think this is a very interesting and exciting space and I do think there are definite potential implications, down the road. [However] we are not there in terms of looking at microbiome and making broad recommendation for individuals, as of yet.”
Will at-home clinical laboratory testing kits that analyze an individual’s microbiome someday provide data that help people lead healthier lives and ward off diseases? That’s Jain’s prediction.
In an article published in Well+Good, Jain said, “COVID-19 has, of course, been such a dark time, but one positive that did come from it is that more people are taking control of their own health. I really believe that the future of healthcare will be delivered not at the hospital, but at home.”
If this collaboration between Nordstrom and Viome proves successful, similar partnerships between at-home diagnostics developers and established retail chains may become even more common. And that should be on the radars of pathologists and clinical laboratories.
