Growing mini-organs to find new treatments for complex disease

Mayo Clinic investigators are growing three-dimensional human intestines in a dish to track disease and find new cures for complex conditions such as inflammatory bowel disease. These mini-organs function like human intestines, with the ability to process metabolites that convert food into energy on a cellular level and secrete mucus that protects against bacteria. These 3D mini-intestines in a dish, known as "organoids," provide a unique platform for studying the intricacies of the human gut.

"We think this has the potential to revolutionize the way we approach disease research. We hope to save time and resources and avoid the development of therapies that fail upon translation into patients," says Charles Howe, Ph.D., who leads the Translational Neuroimmunology Lab. "Understanding which treatments show potential for success in human organoids could dramatically accelerate the rate of new therapies for patients with unmet needs."

Brain stimulation shows promise in treating drug addiction

Physicians use neurostimulation to treat a variety of human disorders, including Parkinson's disease, tremor, obsessive-compulsive disorder and Tourette syndrome. A Mayo Clinic neurosurgeon and his colleagues believe one form of that treatment, called deep brain stimulation (DBS), is poised to solve one of the most significant public health challenges: drug addiction.

"Drug addiction is a huge, unmet medical need," says Kendall Lee, M.D., Ph.D., who has published nearly 100 journal articles on DBS along with his colleagues. Key to treating it, he says, is cutting off the pleasurable "high" that comes with the addiction — which DBS potentially can do.

A new class of AI aims to improve cancer research and treatments

Mayo Clinic researchers have invented a new class of artificial intelligence (AI) algorithms called hypothesis-driven AI, which is a significant departure from traditional AI models that learn solely from data. The researchers note that this emerging class of AI offers an innovative way to use massive datasets to help discover the complex causes of diseases, such as cancer, and improve treatment strategies.

"This fosters a new era in designing targeted and informed AI algorithms to solve scientific questions, better understand diseases and guide individualized medicine," says co-inventor Hu Li, Ph.D., a Mayo Clinic systems biology and AI researcher. "It has the potential to uncover insights missed by conventional AI."

What's lurking in your body? Mayo probes health risks of tiny plastic particles

Similar to natural elements like iron and copper, people can ingest, absorb, or even inhale microplastics and nanoplastics and their chemical additives. A landmark study published in the New England Journal of Medicine links microplastics and nanoplastics found in plaques of human blood vessels to a potential increased risk of heart attack, stroke or death.

"Plastics have made our lives more convenient and spurred many medical advances, but we must understand their impact on human health for the years to come," says Konstantinos Lazaridis, M.D., the Carlson and Nelson Endowed Executive Director for Mayo Clinic's Center for Individualized Medicine.

Mayo Clinic researchers' new tool links Alzheimer's disease types to rate of cognitive decline

Mayo Clinic researchers have discovered a series of brain changes characterized by unique clinical features and immune cell behaviors using a new corticolimbic index tool for Alzheimer's disease, a leading cause of dementia. The tool categorizes Alzheimer's disease cases into three subtypes according to the location of brain changes and continues the team's prior work, demonstrating how these changes affect people differently. Uncovering the microscopic pathology of the disease can help researchers pinpoint biomarkers that may affect future treatments and patient care.

"Our team found striking demographic and clinical differences among sex, age at symptomatic onset and rate of cognitive decline," says Melissa Murray, Ph.D., a translational neuropathologist at Mayo Clinic.

Mayo scientists explore swabs for early endometrial, ovarian cancer detection

Early detection improves treatment outcomes for endometrial and ovarian cancers, yet far too often, women are diagnosed when in advanced stages of these diseases. Unlike many other cancers, there are no standard screenings for early detection of endometrial and ovarian cancers. Mayo Clinic researchers have uncovered specific microbial signatures linked to endometrial and ovarian cancers, and they are working toward developing innovative home swab tests for women to assess their susceptibility.

"This research not only brings us closer to understanding the microbial dynamics in cancer, but also holds the potential to transform early detection and treatment strategies to positively impact women's health globally," says Marina Walther-Antonio, Ph.D., an assistant professor of surgery leading this research.

Reversing racism's toll on heart health

People who experience chronic exposure to racism may be affected by factors such as intergenerational trauma, reduced access to healthcare, differential treatment in healthcare settings and psychological distress. These negatively affect heart health and can have a cumulative effect throughout a person's life. Researchers from Mayo Clinic and the University of Minnesota published a paper which provides a new framework describing how racism affects heart health among people of color in Minnesota. The researchers are focused on reversing these disparities.

"This framework will help scientists explore and measure how chronic exposure to racism, not race, influences health outcomes," says Sean Phelan, Ph.D., a Mayo Clinic health services researcher. "This will help enable researchers to design interventions that address the root causes of these disparities and improve heart health for people of color everywhere."

Teamwork and research play a key role in Mayo Clinic's first larynx transplant

A team of six surgeons and 20 support staff combined expertise from the Department of Otolaryngology and the Department of Transplantation in an extraordinary 21-hour operation at Mayo Clinic. The team transplanted a donor larynx to a 59-year-old patient with cancer whose damaged larynx hampered his ability to talk, swallow and breathe. This groundbreaking surgery was only the third larynx transplant in the U.S., and the world's first known successful total larynx transplant performed in a patient with an active cancer as part of a clinical trial.

"All transplants are complex, but there are more tissue types and moving parts with laryngeal transplantation than other transplants," says David Lott, M.D., lead surgeon. "Mayo Clinic's team science approach made it possible for us to offer this type of transplant on a scale that was previously unattainable."

Space: A new frontier for exploring stem cell therapy

Two Mayo Clinic researchers say that stem cells grown in microgravity aboard the International Space Station have unique qualities that could one day help accelerate new biotherapies and heal complex disease. The research analysis by Abba Zubair, M.D., Ph.D., a laboratory medicine expert and medical director for the Center for Regenerative Biotherapeutics at Mayo Clinic in Florida, and Fay Abdul Ghani, Mayo Clinic research technologist, finds microgravity can strengthen the regenerative potential of cells. 

"Studying stem cells in space has uncovered cell mechanisms that would otherwise be undetected or unknown within the presence of normal gravity," says Dr. Zubair. "That discovery indicates a broader scientific value to this research, including potential clinical applications."

Mayo Clinic’s largest-ever exome study offers blueprint for biomedical breakthroughs

Mayo Clinic's Center for Individualized Medicine has achieved a significant milestone with its Tapestry study. It generated Mayo's largest-ever collection of exome data, which includes genes that code for proteins—key to understanding health and disease.  

Researchers analyzed DNA from over 100,000 participants of diverse backgrounds, providing important insights into certain genetic predispositions to support personalized and proactive medical guidance.  "The implications of the Tapestry study are monumental," says Konstantinos Lazaridis, M.D., the Carlson and Nelson Endowed Executive Director for the Center for Individualized Medicine. "As this study continues to inform and transform the practice of personalized medicine, it also sets a new standard for how large-scale medical research can be conducted in an increasingly digital and decentralized world."   

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news. 

Media contact:

• Colette Gallagher, Mayo Clinic Communications, newsbureau@mayo.edu

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In 2024, collaborative efforts with Mayo Clinic's Center for Individualized Medicine led to significant advances in understanding the biology that shapes health and disease. From new treatments for rare diseases to artificial intelligence-powered tools that help personalize care, these 10 studies exemplify this year’s transformative progress. 

1. Innovative tool measures health of a person’s gut microbiome 

Mayo Clinic researchers, led by Jaeyun Sung, Ph.D., developed an innovative computational tool that analyzes the gut microbiome, a complex ecosystem of trillions of bacteria, fungi, viruses and other microorganisms within the digestive system, to provide insights into overall well-being. In a study published in Nature Communications, the tool demonstrated at least 80% accuracy in differentiating healthy people from those with any disease. The tool, called Gut Microbiome Wellness Index 2, could detect even subtle changes in gut health, identifying whether a person may be progressing toward or recovering from a disease. 

"Finally, we have a standardized index to quantitatively measure how healthy a person's gut microbiome is," says Dr. Sung, the senior author and computational biologist at Mayo Clinic Center for Individualized Medicine's Microbiomics Program. Read more. 

2. Mayo Clinic’s largest-ever exome study offers blueprint for biomedical breakthroughs

Mayo Clinic's Center for Individualized Medicine reached a significant milestone with its Tapestry study, generating the clinic's largest-ever collection of exome data. This dataset, published in Mayo Clinic Proceedings, focuses on protein-coding genes that play a key role in understanding health and disease. Led by Konstantinos Lazaridis, M.D., the study analyzed DNA from over 100,000 participants from diverse backgrounds, providing important insights into certain genetic predispositions to support personalized and proactive medical guidance. Along with its impact on participants' healthcare, one of the most significant outcomes of the study is the creation of a comprehensive genetic data repository to increase the potential for breakthroughs across different fields of medicine.  

"The implications of the Tapestry study are monumental," says Dr. Lazaridis, the Carlson and Nelson Endowed Executive Director for the Center for Individualized Medicine. "As this study continues to inform and transform the practice of personalized medicine, it also sets a new standard for how large-scale medical research can be conducted in an increasingly digital and decentralized world."  Read more. 

3. Pioneering technology helps solve the unsolvable in rare disease diagnoses 

In a significant advancement for rare disease research, Mayo Clinic scientists developed a semi-automated system, known as RENEW, to rapidly reanalyze unresolved rare disease cases. Described in a study published in Human Genetics, RENEW (REanalysis of NEgative Whole-exome/genome data) provided probable diagnoses for 63 of 1,066 undiagnosed cases. This innovative technology, launched in 2022, continuously compares patient genomic data against the latest global research, uncovering previously elusive genetic variants linked to disease.  

"Considering that the majority of patients with rare diseases who undergo genomic sequencing remain without a diagnosis, this is no small accomplishment," says Alejandro Ferrer, Ph.D., a translational omics researcher at Mayo Clinic's Center for Individualized Medicine and lead author of the study. "Each successful diagnosis facilitated by RENEW signifies a profound breakthrough in providing answers and hope to people navigating the complexities of rare diseases."  Read more. 

4. Mayo researchers develop AI-enhanced strategy to personalize medication alerts 

Mayo Clinic researchers have developed an innovative artificial intelligence-enhanced system to deliver medication alerts that are more personalized and actionable. Published in Clinical and Translational Science, the study highlights how the system uses patient-specific genomic data to create concise alerts tailored to individual care needs, moving away from generic, overly detailed notifications. This advancement, led by Arjun Athreya, Ph.D., and his graduate students, represents a step forward in integrating genomic insights into routine care to improve clinical decision-making. 

"AI has the potential to greatly enhance how we deliver care by providing vital support with enhanced information to clinicians and researchers, but we need to know the barriers of technology use and factors that may improve human-technology interaction," says Dr. Athreya, a computer scientist at the Mayo Clinic Department of Molecular Pharmacology and Experimental Therapeutics. Read more. 

5. Mayo Clinic’s high-tech pursuit of precision alcohol addiction treatment 

In an innovative approach to treating alcohol addiction, Ming-Fen Ho, Ph.D., and Richard Weinshilboum, M.D., explored the role of genomics in personalizing therapies. Their study, published in Brain, Behavior and Immunity, revealed genetic variations that influence responses to medications, providing insights into why treatments work for some patients but not others. Their research paves the way for personalized therapy strategies that are precisely tailored to each patient's genomic profile. 

"We've discovered that variations in the IL17RB gene can influence treatment outcomes, affecting important factors like how quickly someone might relapse and how long they can stay in recovery," says Dr. Ho, a lead author and a stem cell biologist in the Department of Psychiatry and Psychology. Read more. 

6. Genetic cancer risks uncovered in 550 patients

A Mayo Clinic study, published in JCO Precision Oncology, revealed gaps in genetic screening protocols, particularly among underrepresented minorities, for mutations linked to hereditary cancer syndromes. As part of the Tapestry project, researchers sequenced the exomes of over 44,000 participants, identifying 550 carriers of hereditary mutations. Notably, half were unaware of their risk, and 40% didn’t meet clinical testing guidelines. 

"This study is a wake-up call, showing us that current national guidelines for genetic screenings are missing too many people at high risk of cancer," says lead author, Niloy Jewel Samadder, M.D., a Mayo Clinic gastroenterologist and cancer geneticist at the Center for Individualized Medicine and the Mayo Clinic Comprehensive Cancer Center. "Early detection of genetic markers for these conditions can lead to proactive screenings and targeted therapies, potentially saving lives of people and their family members." Read more. 

7. Innovative blood test may improve mesothelioma detection rate in blood 

A team led by Aaron Mansfield , Ph.D., developed a blood test potentially capable of detecting mesothelioma with greater accuracy than current methods. The test identifies complex DNA patterns linked to the disease, enabling earlier diagnosis and treatment for patients with this aggressive cancer. By improving detection rates, the study could significantly impact survival outcomes for mesothelioma, which is often diagnosed in its later stages. The proof-of-concept study was published in the Journal of Thoracic Oncology Clinical and Research Reports. 

“We're pushing the frontiers of what's possible in blood-based monitoring," says Dr. Mansfield, a medical oncologist and lead author of the study at the Center for Individualized Medicine and the Mayo Clinic Comprehensive Cancer Center. "Improving detection rates could offer insights into monitoring patients' responses to therapy and detecting recurrence after surgery." Read more. 

8. Scientists invent immunotherapy technique to treat autoimmune diseases 

Mayo Clinic scientists have developed an immunotherapy strategy that potentially lays the groundwork for treating a spectrum of autoimmune diseases. The new technique, detailed in a preclinical study published in Nature Biomedical Engineering, involves combining chimeric antigen receptors (CAR) with mesenchymal stromal cells (MSC), resulting in engineered stem cells known as CAR-MSCs.  

“The pioneering approach shows potential in targeting inflammatory disease sites more precisely and improving immunosuppression and healing outcomes,” says Saad Kenderian, M.B., Ch.B., a principal investigator and hematologist at Mayo Clinic. “We’re planning to study interventions that minimize the need for long-term medications for autoimmune diseases.” Read more. 

9. New class of AI may improve cancer research and treatments 

Mayo Clinic researchers, led by Hu Li, Ph.D., developed a new class of artificial intelligence to improve cancer research and treatments. By analyzing tumor data at an unprecedented level of detail, this technology enables scientists to identify specific cancer subtypes and tailor therapies to individual patients. The innovation, detailed in Cancers, holds potential for enhancing treatment precision and effectiveness, particularly for aggressive or treatment-resistant cancers.  

"This fosters a new era in designing targeted and informed AI algorithms to solve scientific questions, better understand diseases, and guide individualized medicine," says senior author and co-inventor Dr. Li, a Mayo Clinic Systems Biology and AI researcher in the Department of Molecular Pharmacology and Experimental Therapeutics. "It has the potential to uncover insights missed by conventional AI." Read more. 

10. Innovative blood analysis technique reveals insights into giant cell arteritis 

Mayo Clinic researchers, led by Jaeyun Sung, Ph.D., and Kenneth Warrington, M.D., discovered protein patterns in the blood that could improve the diagnosis and monitoring of giant cell arteritis. This chronic autoimmune disease causes inflammation in blood vessels and can lead to vision loss or stroke if untreated. The study, published in Annals of the Rheumatic Diseases, analyzed over 7,000 proteins using proteomics. Researchers developed machine learning models that identified active disease versus remission with over 95% accuracy. This work lays the foundation for more precise diagnosis and personalized treatment options. 

"This precision enables us to refine treatment decisions," says Dr. Warrington, a rheumatologist and Director of the Vasculitis Clinic in the Division of Rheumatology in the Department of Internal Medicine. "Recognizing when a patient's disease is in remission allows us to reduce reliance on certain medications, which can minimize side effects and improve overall patient care."  Read more. 

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The central dogma of molecular biology — cited in countless science textbooks — states that DNA is transcribed into RNA, and RNA is translated into proteins. This basic idea is key to understanding how genes are expressed and how to overcome genetic defects that cause disease.

For much of history, researchers have treated diseases by targeting the proteins involved, such as giving insulin for diabetes or statins for heart disease. Over the last couple of decades, however, they have pursued gene therapies that target disease at the level of the DNA, including developing drugs that correct the genetic defect in sickle-cell disease. More recently, researchers have been advancing treatments that go after the often-overlooked molecule RNA. To do so, many are harnessing a technology known as antisense oligonucleotides.

RNA molecules act as intermediaries between DNA and protein, but they also do so much more, says Margot Cousin, Ph.D., a translational genomics scientist at Mayo Clinic. There are RNAs that can perform biochemical reactions, and others that can regulate gene expression.

"We're trying to use some of the processes that exist in our body to design these drugs and make them work for us," says Cousin.

Antisense oligonucleotides, or ASOs, are short, synthetic strands of nucleotides designed to bind to complementary RNA sequences like the teeth in a zipper. These ASOs can look and behave differently depending on the type of genetic defect they are designed to target. An estimated 15 to 30 percent of genetic diseases are caused by mutations that disrupt RNA splicing, the process by which stretches of noncoding RNA are removed and the remaining coding regions are spliced back together.

"It's essentially like putting all the beads that you need to make your protein together and getting rid of all the string in between that you don't need," says Dr. Cousin.

Splicing mutations can cause these beads to be put together incorrectly,               producing defunct proteins. Dr. Cousin says that researchers can create ASOs to block these mutations and set splicing back on track. For example, the first FDA-approved treatment for spinal muscular atrophy (SMA) is an ASO that modifies the splicing of the SMN2 gene to ramp up the production of functional SMN protein, which is lacking in SMA patients.

Alternatively, mutations can cause a gene to be expressed abnormally or to acquire new properties. In those cases, scientists can design ASOs to specifically bind to the RNA sequences generated by the faulty genes and flag them to be degraded, effectively reducing the production of harmful proteins.

Dr. Cousin and her colleagues are currently assessing this technology for what is known as n=1 cases — those patients with ultra-rare diseases who have no other treatment options.

"These are patients with severe or life-threatening conditions where we know the risk of not treating is greater than the risk of treating with an experimental ASO," she says. "The chemistry of ASOs have already been approved for medicinal use, and their modular nature means that the researchers can simply change the order of the nucleotides to reach a specific target for patients who may benefit from this strategy."

"Our understanding of the human genome and genetic causes of disease continues to grow and therapeutic tools like ASOs are increasingly being pursued to overcome them," said Dr. Cousin. "The study and development of genetic therapies including ASOs will bring precision medicine to those in need with increasing frequency, making them a remarkable drug tool to explore right now."

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PHOENIX — You may be familiar with a range of tips for living a healthy life: Watch your weight, exercise, eat nutritious food and don’t smoke, for example. What if you could combine these lifestyle factors with a host of other variables to learn your risk of developing specific diseases, to help catch and treat them early or prevent them altogether? Victor Ortega, M.D., Ph.D., associate director for the Mayo Clinic Center for Individualized Medicine in Arizona, explains how science is drawing ever closer to making such personal health forecasts possible.

Previously inconceivable, such personal guides to well-being are becoming increasingly possible because of new and sophisticated genome-wide technologies that capture data spanning entire genomes, Dr. Ortega says. The complex scores are compiled from a combination of data from thousands to hundreds of thousands of a person's DNA sequence variants. This type of large genome-wide data has the potential to predict disease risks, such as heart disease, diabetes, asthma and specific cancers.

"Imagine knowing your genetic predisposition for having a heart attack in your 50s, or if you're in the top 5% of the population for the risk of cancer or diabetes based on data from your whole genome. With this knowledge, you could make informed lifestyle choices and receive enhanced screenings to mitigate that risk," Dr. Ortega says.  

As a pulmonologist and genomic scientist, Dr. Ortega is leading a charge to breathe new life into precision medicine advancements. His mission is rooted in a deep commitment to health equities and inspired by his grandmother. 

"My grandmother died of asthma, and that should not have happened. She was Puerto Rican like me, and Puerto Ricans have the highest severity and frequency of asthma of any ethnic group in the world," Dr. Ortega says. "They also represent less than 1% of people in genetic studies. So, I've made it a life mission to develop cures and diagnostics for people like my grandma, and for all people." 

Each person has millions of genetic variants, each having a small effect. But together, these variants can increase the risk of getting a condition. A polygenic risk score estimates the overall risk someone has of getting a disease by adding up the small effects of variants throughout an individual’s entire genome. 

Polygenic risk scores are not used to diagnose diseases. Some people who don't have a high-risk score for a certain disease still can be at risk of getting the disease or might already have it. Other people with high-risk scores may never get the disease.

People with the same genetic risk can have different outcomes depending on other factors such as lifestyle which determine one’s lifelong environmental exposures, also called the exposome.

Dr. Ortega says that getting to the point where all people know their polygenic risk scores will require a solid foundation of "omics" research and datasets, cutting-edge technologies and further discoveries of gene-disease links — all of which are within his team's expertise and capabilities.

Omics is an emerging multidisciplinary field of biological sciences that encompasses genomics, proteomics, epigenomics, transcriptomics, metabolomics and more.

"It's going to take considerable work and planning, but it really is the way of the future," he says.

In the shorter term, Dr. Ortega plans to transition more omics discoveries from research laboratories to the clinic. Omics data can help identify the molecular culprits driving a person's disease, as well as biomarkers that can lead to the development of targeted treatments and diagnostics.

Recent omics discoveries at Mayo Clinic's Center for Individualized Medicine have enabled scientists to predict antidepressant response in people with depression and discover a potential therapeutic strategy for bone marrow cancer. Scientists have also used omics to pinpoint genetic variations that potentially increase the risk for severe COVID-19, uncover potential clues for preventing and treating gliomas and unravel the genetic mystery of a rare neurodevelopmental disorder.

Drawing from his years of extensive clinical experience in treating patients with severe respiratory illnesses, Dr. Ortega is also working to expand genomic testing to a broader set of diseases. He highlights the center's collaborative Program for Rare and Undiagnosed Diseases as an effective model that he hopes to amplify.

The Program for Rare and Undiagnosed Diseases proactively engages healthcare teams across Mayo's clinical practice to conduct targeted genomic testing for patients with a suspected rare genetic disease. He says expanding this strategy to more diseases will help build collaborations across Mayo and educate more clinicians on genomics. It may also ensure the most effective genomic sequencing tests are given to patients, ultimately improving patient care and outcomes.

Dr. Ortega is leading the development of a polygenic risk score framework for Mayo Clinic, beginning with interstitial lung disease. This condition, marked by progressive scarring of lung tissue, is influenced by both rare gene variants and a collection of more common variants, all of which are captured together in polygenic risk scores.

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About Mayo Clinic 
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and to providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Sharon Theimer, Mayo Clinic Communications, newsbureau@mayo.edu

The post What’s your health forecast? Expert explains science behind personal guides to well-being appeared first on Mayo Clinic News Network.

ROCHESTER, Minn. — Mayo Clinic's Center for Individualized Medicine has achieved a significant milestone with its Tapestry study, generating the clinic's largest-ever collection of exome data, which include genes that code for proteins — key to understanding health and disease.  

Led by Konstantinos Lazaridis, M.D., the study analyzed DNA from over 100,000 participants from diverse backgrounds, providing important insights into certain genetic predispositions to support personalized and proactive medical guidance.    

The findings, published in Mayo Clinic Proceedings, focused on pathogenic (disease-causing) and likely pathogenic genetic variants linked to three specific conditions: hereditary breast and ovarian cancer syndrome, Lynch syndrome and familial hypercholesterolemia. Findings revealed that 1.9% of participants — nearly 2,000 people — carried at least one genetic variant that could increase their risk for these diseases. Notably, about 65% of those with a detected variant had no known prior personal or family history of the conditions.  

For many participants found to carry a genetic variant, the information has been life changing. Some have taken proactive steps, such as undergoing early screenings or preventive surgeries, which in some cases led to early cancer detection or reduced their risk of heart disease.  

"The implications of the Tapestry study are monumental," says Dr. Lazaridis, the Carlson and Nelson Endowed Executive Director for the Center for Individualized Medicine. "As this study continues to inform and transform the practice of personalized medicine, it also sets a new standard for how large-scale medical research can be conducted in an increasingly digital and decentralized world."     

A monumental, decentralized effort  

Almost as significant as the study's outcome is how it was accomplished. The Tapestry study has been Mayo Clinic's largest decentralized trial, meaning it was conducted remotely through electronic contact, education and consent, with sample collection materials delivered to the participant’s home.   

Launched in early 2020 during the COVID-19 pandemic, the project overcame unprecedented challenges, including securing consent from over 100,000 of the 1.3 million people invited to participate and mobilizing vast resources.   

"It was a tremendous effort," Dr. Lazaridis recalls. "The engagement of such a number of participants in a relatively short time and during a pandemic showcased the trust and the dedication not only of our team but also of our patients."  

"We have also learned valuable lessons about some patients' decisions not to participate in Tapestry, which will be the focus of future publications," he added.  

Participants' saliva samples from all three of Mayo Clinic's campuses — in Minnesota, Arizona and Florida — were used to extract DNA for exome sequencing. Exome sequencing analyzes nearly 20,000 genes that provide instructions for making proteins, which play many critical roles in the body. This is where most known disease-causing pathogenic or likely pathogenic genetic variants occur.   

This genetic exploration focused on hereditary conditions such as the BRCA1 and BRCA2 genes. According to the Centers for Disease Control, women with these pathogenic genetic variants have a higher likelihood of developing breast and ovarian cancer, while men with BRCA1 and BRCA2 mutations face an increased risk of breast cancer and a potentially elevated risk of prostate cancer. The study also examined Lynch syndrome, which raises the risk of colorectal and uterine cancers, and familial hypercholesterolemia, known for its impact on early-onset heart disease, heart attacks and stroke.  

In addition to targeting these well-known conditions, the center’s experts are applying advanced analytics to the Tapestry data in collaboration with investigators across the enterprise. This work aims to explore lesser-known genetic variants that may contribute to a range of other health issues and diseases. 

From data to actionable insights

These actionable insights are being integrated into participants' health records to guide future medical decisions, such as personalized interventions and regular health screenings to potentially improve patient outcomes.  

Genetic counselors have played a crucial role in educating both patients and providers about the implications of their genetic data.  

"Receiving genetic information can be difficult, but it also empowers patients to take proactive steps for their health," says Jennifer Kemppainen, CGC, supervisor of the Mayo Clinic Genetic Testing and Counseling unit and part of the Tapestry study team. "We help patients understand their results and educate them about screening and management options, so they feel prepared to meet with specialists and make informed decisions about their care." 

A repository for tomorrow's cures

Along with its impact on participants' healthcare, one of the most significant outcomes of the Tapestry study is the creation of a comprehensive genetic data repository. This extensive database has become a valuable resource for Mayo's scientific community, with 118 research requests submitted, that have resulted in the distribution of over 1.1 million exome datasets to interested investigators.  

The data repository supports ongoing individual projects and fosters a collaborative environment where researchers can exchange ideas and findings to increase the potential for breakthroughs across different fields of medicine.  

"What we've accomplished with the Tapestry study is a blueprint for future endeavors in medical science," Dr. Lazaridis says. "It demonstrates that through innovation, determination and collaboration, we can deeply advance our understanding of DNA function and eventually other bio-molecules like RNA, proteins and metabolites, turning them into novel diagnostic tools to improve health, prevent illness and even treat disease."  

Review the study for a complete list of authors, disclosures and funding.  

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About Mayo Clinic   
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and to providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.    

Media contact:    

• Susan Murphy, Mayo Clinic Communications, newsbureau@mayo.edu   

The post Mayo Clinic’s largest-ever exome study offers blueprint for biomedical breakthroughs  appeared first on Mayo Clinic News Network.

As you gather around the table this Thanksgiving to share meals, stories and traditions, consider taking a moment to talk about something that could save lives: your family's health history.  

Thanksgiving Day is recognized as Family Health History Day, a national call to raise awareness of inherited health risks. Mayo Clinic experts are encouraging families to use the holiday to identify these risks and take proactive steps toward prevention. 

"Hereditary conditions range from autoimmune disorders like celiac disease to cancers tied to genetic mutations," says Joseph Murray, M.D., a gastroenterologist at Mayo Clinic with over 30 years of expertise in treating complex digestive diseases. "Thanksgiving provides a unique opportunity to notice these patterns in your family's health and start conversations that could benefit generations to come." 

Hereditary links to digestive conditions

Two conditions Dr. Murray highlights, celiac disease and eosinophilic esophagitis, can have hereditary components but are not always linked to family history.

"Food is central to Thanksgiving, so it's a perfect time to notice who's avoiding certain dishes," Dr. Murray says. "If someone skips bread or mentions swallowing difficulties, it could point to something hereditary." 

Celiac disease, an autoimmune condition triggered by gluten, can cause symptoms like diarrhea, abdominal pain, bloating, weight loss, anemia, fatigue, skin rashes, mouth ulcers and joint pain. It can be diagnosed at any age and presents in over 300 ways, making testing crucial — especially for those with close relatives at higher risk. 

"For siblings, the risk is as high as 20%," Dr. Murray says. "Accurate diagnosis is key, because eliminating gluten without testing can mask other health issues, such as irritable bowel syndrome or lactose intolerance, and delay treatment." 

Dr. Murray says eosinophilic esophagitis is another condition to be aware of. It involves inflammation of the esophagus that leads to difficulty swallowing or food impaction. In children, symptoms can include vomiting, avoiding certain foods or difficulty gaining weight. In adults, it typically presents as difficulty swallowing or the sensation of food getting stuck, which can sometimes require emergency medical attention. Available treatment options include anti-inflammatory medications and immune-targeted therapies. 

Turning genomics into action

Family health history also plays a vital role in cancer and heart disease prevention, says John Presutti, D.O., a family medicine physician and the Cecilia and Dan Carmichael Family Associate Director for the Center for Individualized Medicine at Mayo Clinic in Florida. In his dual role, Dr. Presutti combines his expertise in primary care with advances in genomics to help patients uncover hereditary risks and take proactive steps. 

Dr. Presutti also leads Mayo Clinic's pilot program integrating genomic data into clinical care. This initiative offers genomic screening for actionable genetic markers associated with hereditary breast and ovarian cancer syndrome, Lynch syndrome and familial hypercholesterolemia. These markers can inform preemptive interventions and allow for personalized care. 

"Approximately 10% of cancers are inherited," Dr. Presutti says. "Uncovering hidden genetic mutations through family discussions allows us to screen patients earlier and potentially save lives." 

Hereditary breast and ovarian cancer syndrome is linked to mutations in the BRCA1 and BRCA2 genes. Mutations in BRCA1 can lead to a 60% lifetime risk of developing breast cancer and a 40% risk of having ovarian cancer, among other cancers. BRCA2 mutations increase the risk of developing breast cancer to 50% and ovarian cancer to 20%, with additional risks for prostate and pancreatic cancers in males.  

Lynch syndrome is associated with an 80% lifetime risk of developing colorectal cancer and 50% risk of uterine/endometrial cancer. Familial hypercholesterolemia, a genetic disorder that causes dangerously high cholesterol levels, significantly increases the risk of early heart disease and stroke if left untreated. 

 Dr. Presutti encourages families to ask questions such as: 

• Have any family members had cancer or heart disease? 

• At what age were they diagnosed? 

• Are there patterns of chronic illnesses or early deaths in the family? 

Detecting early-onset GI cancers

For younger people, family health history can be especially important as rates of gastrointestinal (GI) cancers are on the rise among people under age 55. Mayo Clinic's Early Onset and Hereditary Gastrointestinal Cancers Program aims to address this growing concern, says Niloy Jewel Samadder, M.D., a Mayo Clinic gastroenterologist and cancer geneticist. 

"The rise in young-onset gastrointestinal cancers is a pressing health issue," Dr. Samadder says. "Our goal is to put patients at the center of a collaborative framework of experts working seamlessly together." 

Launched in 2024, the program integrates gastroenterology, oncology, surgery, pathology and genetics to provide comprehensive, patient-centered care. Translational discoveries, such as immunology studies and a multi-omics approach, are also part of the program, helping to tailor treatments to a patient's unique biological profile. 

"This multidisciplinary approach doesn't just address cancer — it uncovers hereditary risks that can guide care for families," Dr. Samadder explains. "It's about creating a roadmap for prevention and better outcomes." 

A tradition that saves lives 

If you discover something significant about your family health history this Thanksgiving, take action: 

• Talk to your primary care provider about screening or preventive measures. 

• Encourage family members to discuss shared health risks with their doctors. 

• Learn about lifestyle changes or early interventions that could lower your risk. 

• Stay proactive by keeping your health records updated and sharing them with relatives. 

"Don't just talk about your family health history," Dr. Presutti says. "Act on it. It could save your life." 

For more information, visit CDC Family Health History. 

The post Why Thanksgiving is the perfect time to share family health history  appeared first on Mayo Clinic News Network.

Electronic health records are increasingly including technology-aided predictions of how patients may respond to specific medications, known as pharmacogenomic alerts. Two Mayo Clinic Ph.D. candidates are exploring how artificial intelligence (AI) can be used to make these alerts more actionable and less intrusive for clinicians, who can suffer from alert overload.

In a new study, Ph.D. candidates Caroline Grant and Jean Marrero-Polanco, under the mentorship of lead author Arjun Athreya, Ph.D., found that clinicians generally prefer concise, individualized alerts that use patient-specific genomic data to help personalize their care, rather than more generic or detailed alerts.

Their study is published in Clinical and Translational Science. Both students are doctoral candidates in the Molecular Pharmacology and Experimental Therapeutics program at the Mayo Clinic Graduate School of Biomedical Sciences.

"AI has the potential to greatly enhance how we deliver care by providing vital support with enhanced information to clinicians and researchers, but we need to know barriers of technology use and factors that may improve human-technology interaction," says Dr. Athreya, a computer scientist at the Mayo Clinic Department of Molecular Pharmacology and Experimental Therapeutics. "Our goal is to develop digital tools that are technically robust, highly usable and augment clinicians' expertise to ensure patients receive the most effective, personalized care."

Tailoring alerts to clinician experience and specialty

For the study — led by Department of Molecular Pharmacology and Experimental Therapeutics in collaboration with the Department of Psychiatry and Psychology, Internal Medicine and Family Medicine — the team surveyed 305 clinicians from a variety of backgrounds across Mayo Clinic sites in Minnesota, Arizona and Florida, and the Mayo Clinic Health System. Participants hailed from specialty practices including psychiatry, internal medicine and family medicine and included those working in both large urban hospitals and in small rural clinics. This diversity helped the researchers understand how different settings, specialties and experience levels influenced what doctors found most useful.

To analyze clinician preferences, the research team used advanced AI techniques, including natural language processing, which helps computers interpret human language, and machine learning, which allows computers to learn from data. These tools allowed the researchers to efficiently process large volumes of survey data and uncover insights that otherwise would have been difficult to detect.

The study focused on pharmacogenomic alerts in the context of treating major depressive disorder with the antidepressant citalopram. Clinicians were presented with three types of alerts:

• Generic alert: Provides standard dosage recommendations without patient-specific data.
• Concise, individualized alert: Displays AI-derived predictions of drug efficacy based on a patient’s clinical and genomic markers.
• Detailed, individualized alert: Includes in-depth information on the specific genes and markers involved in the AI-derived predictions of drug efficacy.

Overall, the clinicians favored the concise, individualized alerts. In contrast, they gave the generic alerts, which resemble current electronic health record alerts for citalopram, failing grades.

Implications for reducing burnout and enhancing care

The study emphasizes the importance of integrating patient-specific data and offering easy access to detailed information via hyperlinks. The findings also suggest that preferences for alert design varied by clinician specialty and experience. For example, experienced psychiatrists preferred detailed genetic profiles, while early-career internal medicine providers favored more concise alerts.

"Finding the right balance of detail is crucial," says Caroline Grant, first author. "Our study indicates that a one-size-fits-all approach to alerts is not effective. We need to consider who is reading the alert and what they need in that moment."

Grant's research is centered on leveraging AI and large biological data sets to identify biomarkers that predict treatment outcomes. Her long-term goal is to continue developing precision medicine tools that can be applied in both research and clinical settings.

Grant's co-first author, Jean Marrero-Polanco, notes patients will not be the only ones to benefit from the types of improvements suggested in the study.

"By designing drug alerts based on clinician preferences, we're not just supporting personalized medicine for patients — we're potentially enhancing the well-being of clinicians, too," he says, as electronic health record usability has associated with physician burnout.

Born and raised in Puerto Rico, Marrero-Polanco's passion for improving mental health outcomes is deeply personal. He is driven by the need for quality studies on mental health disparities, particularly within underserved communities. His research focuses on developing AI-driven tools that support clinicians in making better decisions, with the long-term goal of leading independent research in academia to advance AI in healthcare.

Next step: Real-world testing

The next phase of this research will involve testing these refined alerts in actual clinical settings to determine their effect on clinician burnout and patient outcomes. The team plans to develop educational resources to help clinicians understand these AI-derived predictions and use these tools in patient care.

The study was funded by the National Science Foundation. Co-principal investigators include Richard Sharp, Ph.D., director of Mayo Clinic's Biomedical Ethics Research Program; Paul Croarkin, D.O., director of Mayo Clinic’s Children’s Research; Liewei Wang, M.D., Ph.D., director of Mayo Clinic’s Pharmacogenomics Program; Liselotte Dyrbye, M.D., of the Colorado School of Public Health; and William Bobo, M.D., of the Florida State University College of Medicine.

Review the study for a complete list of authors, disclosures and funding.

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Mayo Clinic researchers have identified key protein patterns in the blood that could improve how doctors diagnose and monitor giant cell arteritis, a chronic autoimmune disease that causes inflammation in blood vessels. The condition often affects arteries in the head and can lead to vision loss or stroke if untreated.

The new research, led by Jaeyun Sung, Ph.D., and Kenneth Warrington, M.D., lays the groundwork for more accurate diagnosis and personalized treatment approaches. 

In the study, published in Annals of the Rheumatic Diseases, researchers analyzed more than 7,000 proteins from blood samples collected from patients with giant cell arteritis and healthy people. This large-scale analysis, known as proteomics, allows scientists to study the full range of proteins in a sample and identify distinct patterns associated with disease activity. The researchers used these patterns to develop machine learning models that helped them distinguish between active and remission states with over 95% accuracy. 

"In our study, we used high-throughput proteomics to help us analyze thousands of proteins simultaneously," says Dr. Sung, a computational biologist at Mayo Clinic Center for Individualized Medicine's Microbiomics Program. "We also applied machine learning to help us uncover patterns within these large datasets. This approach has provided us with deeper insights into the biology of giant cell arteritis and brings us closer to developing biomarker panels that could improve diagnosis and treatment." 

Dr. Sung specializes in developing computational models that connect biological processes to health outcomes. His expertise lies in multi-omics, which integrates data from proteins, genes and other biological markers to uncover patterns in chronic diseases. He is dedicated to turning these discoveries into practical tools that clinicians can use to improve patient care. He recently developed a computational tool to help specialists analyze the gut microbiome to provide insights into overall well-being. 

Precision through proteomics

Symptoms of giant cell arteritis, such as headaches, jaw pain and fatigue, overlap with many other conditions, making an accurate diagnosis challenging. The disease primarily affects older adults and can lead to serious complications if not treated promptly. Doctors typically rely on common inflammation tests, but they lack the specific information to confirm a diagnosis of giant cell arteritis. As a result, many patients experience delays in receiving treatment. 

Using proteomics, the researchers gained crucial insights into when the disease is active and when it’s in remission. This knowledge helps doctors not only determine when to begin treatment but also when it may be safe to pause medication. 

"This precision enables us to refine treatment decisions," says Dr. Warrington, a rheumatologist and Director of the Vasculitis Clinic in the Division of Rheumatology in the Department of Internal Medicine. "Recognizing when a patient's disease is in remission allows us to reduce reliance on certain medications, which can minimize side effects and improve overall patient care." 

Dr. Warrington's research focuses on identifying diagnostic biomarkers and understanding the molecular mechanisms behind vasculitis conditions. With extensive experience in clinical trials, he is dedicated to translating his findings into therapies that improve patient outcomes. 

Next steps in research

The researchers plan to next test these protein markers in larger, more diverse patient groups to ensure the findings are reliable. They also aim to compare the results with other inflammatory diseases to confirm the markers' specificity to giant cell arteritis. Future research will explore other biological data, such as gene expression activity, to further enhance our understanding of the disease. 

Review the study for a complete list of authors, disclosures and funding. 

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At Mayo Clinic’s Center for Individualized Medicine, scientists are investigating stool samples to uncover new insights into cancer treatment. Often seen as waste, stool may provide valuable information about the microbiome — a complex ecosystem of microorganisms, including bacteria, fungi and viruses in the gut.

Growing evidence shows the microbiome plays a significant role in health, including how the body responds to diseases like cancer and how it influences treatment outcomes. 

A new frontier in cancer research

A key part of the team's research is the Oncobiome Project, an initiative within the center’s Microbiomics Program. The project includes a large collection of stool samples from cancer patients across Mayo Clinic campuses in Minnesota, Arizona and Florida. These samples, collected before patients began treatment, are helping researchers identify microbial patterns that predict how well a patient will respond to treatments, and potentially pave the way for more personalized cancer care strategies.  

What sets the Oncobiome project apart is its strategic design, which bridges research and clinical practice. This approach makes it easier to translate scientific discoveries into personalized treatments for cancer patients. 

"Ultimately, we hope to individualize treatment plans that provide the right drug at the right time based on a person’s unique microbiome and genetics," says Purna Kashyap, M.B.B.S., the Bernard and Edith Waterman Director of the Mayo Clinic Microbiomics Program.   

Decoding microbiome's cancer link through stool analysis

At the heart of the project is the collection and analysis of more than 2,000 stool samples. This extensive biobank allows Dr. Kashyap and his team to examine whether the microbiome composition correlates with specific types of cancer. They also are investigating whether the microbiome can predict the likelihood of event-free survival for patients with cancers such as lymphoma who are undergoing various treatments.  

Additionally, the project explores whether enzymes and metabolites produced by the gut microbiome can offer insights into how patients will respond to cancer immunotherapies and help identify potential adverse reactions. 

"We included a diverse group of patients at various stages of different cancers and undergoing various treatments. This allows us to identify microbial patterns that forecast optimal cancer outcomes, independent of the underlying cancer," Dr. Kashyap says. 

Beyond personalizing cancer care, the team is integrating additional "omics" to gain deeper insights into patients' genetics, environment and immune status. This includes genomics (the study of genes), proteomics (proteins), exposomics (environmental exposures), metabolomics (metabolic processes) and transcriptomics (RNA transcripts). 

Ruben Mars, Ph.D., a research scientist at the Center for Individualized Medicine, is playing a key role in spearheading several studies within the Oncobiome project to understand the impact of microbes on cancer risk, treatment efficacy and the underlying mechanisms of any treatment side effects. 

"Although a diverse and balanced gut microbiome is widely recognized as beneficial for our health, pinpointing specific microbial changes that enhance treatment outcomes remains challenging," Dr. Mars says. "Through the Oncobiome project, we're optimistic about developing innovative methods to manipulate the microbiome and ultimately improve cancer care for patients." 

Connecting the microbiome to health outcomes

This research is part of a broader series of the team's investigations into the microbiome. Their recent published studies focus on the microbiome's role in gut-brain disorders, including how bacteria affect intestinal functions like motility. Other published work examines C. difficile infections, exploring how the bacteria persist in the intestine.

Mayo's microbiome scientists are also studying the impact of the gut microbiome on the progression of rheumatoid arthritis and patients' response to treatment. In another study, the team linked a specific microbe, Porphyromonas somerae, to endometrial cancer, finding its intracellular activity may play a pathogenic role in the disease. 

The post Mayo researchers study stool to unlock microbiome’s role in cancer treatment  appeared first on Mayo Clinic News Network.

Mayo Clinic researchers have developed an innovative testing strategy for mesothelioma that could potentially increase the detection rate of cancer DNA in the blood. This approach focuses on shuffled or swapped sections of DNA in mesothelioma cancer cells, called chromosomal rearrangements.

By detecting these complex DNA patterns, rather than just single-point mutations, the method could lead to earlier diagnoses and new avenues for targeted therapies. 

“We're pushing the frontiers of what's possible in blood-based monitoring," says Aaron Mansfield, M.D., a medical oncologist and lead author of the study at the Center for Individualized Medicine and the Mayo Clinic Comprehensive Cancer Center. "Improving detection rates could offer insights into monitoring patients' responses to therapy and detecting recurrence after surgery." 

Mesothelioma is a rare cancer that develops in the thin membranes that line the chest and abdomen, most commonly caused by inhaling asbestos fibers. These fibers are often found in insulation, vinyl tiles, roofing materials and paint. Despite decades of regulations to limit asbestos exposure, approximately 3,000 people in the U.S. are diagnosed with mesothelioma each year, according to the American Cancer Society. 

Mesothelioma typically exhibits a low number of single-point genetic mutations, making it difficult to detect with traditional blood tests. However, the presence of chromosomal rearrangements — like shuffling words in a sentence — provides a new diagnostic target. This differs from many other cancers that often rely on detecting single-point mutations — tiny changes in the DNA sequence, similar to altering a single letter in a word. 

In the proof-of-concept study, published in the Journal of Thoracic Oncology Clinical and Research Reports, Dr. Mansfield and his team used whole genome sequencing to locate key chromosomal changes in the DNA of cancer cells. Next, they created tiny pieces of DNA, called primers, that they designed in the lab to precisely match and attach to these chromosomal changes. They then searched for these changes in blood. 

This combination of cutting-edge tools allowed the researchers to create personalized tests that detect and track cancer DNA in each patient's blood. 

The findings build on the team's previous mesothelioma research, including a study that identified a genomic signature to predict which patients with mesothelioma could benefit from immunotherapy.  Additionally, Dr. Mansfield’s previous research shows how chromosomal rearrangements have neoantigenic potential, meaning they can help the body make an immune response against cancer cells. 

The team plans to expand this study to include more patients and further refine the testing method. 

Review the study for a complete list of authors, disclosures and funding. 

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