Imagine knowing your risk for disease long before symptoms appear. With early detection and targeted interventions, this knowledge could transform how complex healthcare challenges are addressed. Researchers are now leveraging genetic data to enhance disease risk prediction through an innovative tool known as a polygenic risk score. Learn more on a new episode of Tomorrow's Cure.

The podcast's latest episode features Victor Ortega, M.D., Ph.D., associate director of the Mayo Clinic Center for Individualized Medicine, and Louise Wain, Ph.D., professor of respiratory research, University of Leicester in the U.K.

Scientists have developed polygenic risk scores to analyze multiple genetic variants across a person's genome. These scores assess the likelihood of developing conditions such as heart and lung diseases, diabetes, asthma, and certain cancers.

"There's really no one singular variant in the genome that causes common diseases. It's really a lot of different variants across the genome, across our genomes that have weaker or milder effects on disease risk, but all together give us this increased risk," explains Dr. Ortega.

"With those discoveries, we've developed genetic risk scores, polygenic risk scores, where we bring together the effects or associations across variants, across entire genomes into a singular score," he continues.

Clinicians can then utilize these risk scores to potentially customize prevention and treatment strategies.

"These are quite early in development, but are potentially really, really important," says Dr. Wain. "In the future, we could use these to improve diagnosis where somebody is already presenting with the disease, but they need a specific diagnosis in order to access the medicines that are going to work for them." Dr. Ortega says the potential of polygenic risk scores is both exciting and promising. Find out more on the latest episode of Tomorrow's Cure. To view the complete list of episodes and featured experts, visit tomorrowscure.com.

Related content:

• What's your health forecast? Expert explains science behind personal guides to well-being
• Mayo pioneers population science to advance personalized medicine

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Antibody-drug conjugates are targeted cancer therapies. They deliver potent drugs directly into cancer cells while minimizing harm to healthy tissue. These therapies work by recognizing specific proteins found on the surface of cancer cells.

The proteins function like a lock and the therapy acts as a key, latching onto the cancer cells with precision to deliver the treatment.

But precision alone isn’t enough. Even when the key fits the lock, the door often stays closed. This prevents the drug from entering the cell to attack the cancer. 

Now, Mayo Clinic researchers have developed a pioneering strategy that may help overcome this barrier. The approach combines antibody-drug conjugates with proteolysis-targeting chimeras. These molecular tools break down specific proteins to improve how cancer cells internalize the cancer-fighting therapy.  

"The ability to target specific proteins and improve drug absorption into tumor cells represents a significant step forward in how we approach aggressive cancers."

Aaron Mansfield, M.D.

In a preclinical study, published in Communications Biology, the combined therapy improved the internalization of these treatments by up to 1.9 times in certain models.  

"The ability to target specific proteins and improve drug absorption into tumor cells represents a significant step forward in how we approach aggressive cancers," 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. 

Dr. Mansfield and his team tested the approach using breast cancer organoids. They created these miniaturized, lab-grown versions of breast tissue to mimic the complexity of real tumors. Unlike traditional cell cultures, organoids better replicate how tumors behave in the body.

Specifically, the research focused on three proteins often found in aggressive cancers. These include human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor (EGFR), and mesenchymal-epithelial transition factor (MET). These proteins are associated with breast, lung and pancreatic cancers.  

Overall, the study highlights the versatility of this approach by demonstrating potential benefits across multiple cancer types and protein targets. 

For a complete list of authors, disclosures and funding, review the study. 

Other recent research from Dr. Mansfield

Innovative Mayo Clinic test may improve mesothelioma detection rate in blood

Dr. Mansfield and his team have developed an innovative testing strategy for mesothelioma that could potentially increase the detection rate of cancer DNA in the blood. Read more.

Researchers predict immunotherapy response in mesothelioma cancer

Dr. Mansfield and his team have discovered a potential genomic signature to predict which patients with mesothelioma could benefit from immunotherapy.  Read more.

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Mayo Clinic researchers have developed organoid models to study uveal melanoma, one of the most common types of eye cancer in adults. Their goal is to use these models to better understand how this disease works and develop treatments for unmet patient needs.

Organoids are 3D models grown from patient tissue that accurately reflect a patient's unique genetic and biological characteristics, also known as "avatars." When derived from a patient's cancer tumor, an organoid will behave and respond to treatments outside the body in a lab (in vitro) just like the original tumor would inside the body (in vivo).

In 50% of patients, uveal melanoma metastasizes, spreading to other parts of the body, leading to a poor prognosis and average survival of less than two years.  Unfortunately, current treatments for this condition often have limited effectiveness, leaving patients and their doctors with few options.

"The hope is that these patient-derived organoid models better represent human cancer in the laboratory," says Lauren Dalvin, M.D., a Mayo Clinic Comprehensive Cancer Center ocular oncologist and surgeon-scientist who is one of the lead researchers. "Using these models as a foundation for drug testing will facilitate new treatment discoveries with higher success rates in clinical trials, ultimately translating to improved outcomes for patients with uveal melanoma."

Growing an eye cancer biobank

In the past, the lack of human disease models representing the entire spectrum of uveal melanoma has created a bottleneck, limiting the ability of scientists to identify effective targets for treatment and prevention. Most laboratory studies have drawn from the same set of commercially available cell lines, which are not representative of the disease and often differ in important ways from the original tumors.

To blast through this bottleneck, a study team led by Dr. Dalvin, in collaboration with Martin Fernandez-Zapico, M.D., a cancer biologist with Mayo Clinic Comprehensive Cancer Center, decided to develop a new, uveal melanoma patient-derived organoid biobank. Their goal is to create a research resource representing the real-world variability of this cancer.

In a paper published in Investigative Ophthalmology & Visual Science, they described the initial development of this biobank. The researchers successfully created organoids derived from Mayo Clinic ocular oncology patients who enrolled in a prospective study involving the collection of tumor tissue for research from July 1, 2019, through July 1, 2024. Their study determined that these organoid models:

• Could be generated, retained their stability through many uses and were a renewable living resource capable of being regenerated at need.
• Retained the clinically relevant features of the original tumors, clustered into appropriate molecular groups based on validated prognostic markers and resembled human disease when compared to in vivo animal models.
• Served as suitable human models for drug screening.

Recognizing the immense value of this organoid biobank, the investigators have already begun expanding it to include other research centers. Their goal is to create a resource capable of representing the global epigenomic variability of uveal melanoma. In the future, they hope this biobank will serve as a comprehensive platform for drug screening and other types of lab research on uveal melanoma. This collaborative effort will accelerate research and pave the way for improved treatments and outcomes for patients with this disease.

Read the paper to learn more about the study, including funding and disclosures.

Mayo Clinic organoid research across the spectrum of disease

Organoids are transforming the landscape of biomedical research. Scientists are using this innovative approach to model diseases, track their progression and identify and characterize potential treatments. Mayo Clinic is at the forefront of organoid research, applying this approach to study a wide range of health conditions including:

• Neurodegenerative and neurological disorders, such as Lewy body dementia, Alzheimer's disease, autism, opioid addiction and alcohol use disorder.
• Measles and other infectious diseases.
• Many types of cancer including breast cancer.
• Inflammatory bowel disease.

The goals of this research extend far beyond its current applications. Mayo Clinic researchers aim to develop organoids representing organs throughout the human body to track disease, screen drugs and regenerate tissues. This approach holds the promise of accelerating research in precision medicine and the search for cures in other areas of biomedical research.

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ROCHESTER, Minn. — Mayo Clinic today unveiled separate groundbreaking collaborations with Microsoft Research and with Cerebras Systems in the field of generative artificial intelligence (AI), designed to personalize patient care, significantly accelerate diagnostic time and improve accuracy.

Announced during the 43^rd Annual J.P. Morgan Healthcare Conference, the projects focus on developing and testing foundation models customized for various applications, leveraging the power of multimodal radiology images and data (including CT scans and MRIs) with Microsoft Research and genomic sequencing data with Cerebras. The innovations have the potential to transform how clinicians approach diagnosis and treatment, ultimately leading to better patient outcomes. 

Foundation AI models are large, pre-trained models capable of adapting to and carrying out many tasks with minimal extra training. They learn from massive datasets, acquiring general knowledge that can be used across diverse applications. This adaptability makes them efficient and versatile building blocks for numerous AI systems.

Mayo Clinic and Microsoft Research advance AI for chest X-rays

Mayo Clinic and Microsoft Research are collaboratively developing foundation models that integrate text and images. For this use case, Mayo and Microsoft Research are working together to explore the use of generative AI in radiology using Microsoft Research’s AI technology and Mayo Clinic’s X-ray data.

"Multimodal foundation models hold immense promise in tackling significant roadblocks across the radiology ecosystem. The innovations we’re creating with Microsoft Research will help unlock valuable insights for the future of medical imaging to improve how radiologists work and how patients are cared for," says Matthew Callstrom, M.D. Ph.D., chair of Mayo Clinic Radiology in the Midwest and medical director for Generative AI and Strategy. "Focusing on chest X-ray reports, Mayo's clinical teams and Microsoft researchers will collaborate to advance the state-of-the-art in multimodal AI radiology, helping bring innovation to real-world application faster and at scale, which is key to making exemplary healthcare more accessible." 

Empowering clinicians with instant access to the information they need is at the heart of this research project. Mayo Clinic aims to develop a model that can automatically generate reports, evaluate tube and line placement in chest X-rays, and detect changes from prior images. This proof-of-concept model seeks to improve clinician workflow and patient care by providing a more efficient and comprehensive analysis of radiographic images.

"This collaboration is a crucial step towards our mutual goal of developing generative AI that improves patient outcomes and the clinician experience," says Jonathan Carlson, Ph.D., managing director, Health Futures at Microsoft Research. "The fusion of Microsoft's recognized research innovations in biomedical AI and Mayo Clinic's radiology excellence will empower clinicians with the tools they need to deliver more precise and accessible care and furthers Microsoft’s commitment to bringing the power of emerging AI to clinical researchers worldwide."

Mayo Clinic and Cerebras create a world-leading genomic foundation model

Mayo Clinic and Cerebras have created a genomic foundation model that combines publicly available human reference genome data that represents an ideal version of the human genome, with Mayo's comprehensive patient exome data and the power of its Mayo Clinic Platform. Exome data focuses on the protein-coding region of the genome where several disease-causing mutations take place. Cerebras's high-powered computing and generative AI capabilities make it possible to train and develop the model at scale, positioning it to be further refined for more specific uses.

"The genomic foundation model represents a significant advancement in personalized medicine," says Dr. Callstrom. "Its ability to analyze genomic data and compare them in almost real-time with patients with similar traits allows for more precise prediction of disease and treatment response, leading to faster diagnoses and the selection of targeted therapies for patients."

For example, rheumatoid arthritis (RA) is a debilitating autoimmune disease, and the standard treatment approach often requires trials of different therapies to achieve disease remission. It can take several months to know if a therapy is working. A new genomic model developed by Mayo Clinic and Cerebras offers a potential solution to shorten the time to identify effective treatment and avoid long-term morbidity associated with the untreated disease. Early findings demonstrate high performance against benchmarks and show early promise in identifying patient response to therapy. As more patient data is added, the model's predictive power is expected to increase, leading to faster, more effective personalized treatment for RA patients.   

"Mayo’s genomic foundation model sets a new bar for genomic models, excelling not only in standard tasks like predicting functional and regulatory properties of DNA but also enabling discoveries of complex correlations between genetic variants and medical conditions," says Natalia Vassilieva, Field CTO at Cerebras Systems. "Unlike current approaches focused on single-variant associations, this model enables the discovery of connections where collections of variants contribute to a particular condition."

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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:

• Terri Malloy, Mayo Clinic Communications, newsbureau@mayo.edu

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ROCHESTER, Minn. — Against the backdrop of the 43^rd Annual J.P. Morgan Healthcare Conference, Mayo Clinic announced the formation of Mayo Clinic Digital Pathology, designed on a platform architecture to boldly unlock the power of its extensive archive of digital slides to revolutionize pathology and accelerate medical breakthroughs.

Mayo Clinic's expertise, de-identified clinical data, and its Platform architecture, combined with technical expertise and resources of NVIDIA, a world leader in accelerated computing, is powering the ability to accelerate this transformation. In addition, to improve performance and scalability of generative AI in pathology, Mayo Clinic is collaborating with Aignostics, an industry leader in building artificial intelligence (AI) models for digital solutions in precision medicine in a way that mirrors its established approach to patient care. This collaborative, multidisciplinary effort leverages both medical and technological strengths, and the early achievements are promising.

"Mayo Clinic is reimagining what is possible in disease detection and prediction, both within its own system and globally. We are doing this by using large, diverse datasets to build powerful artificial intelligence models in pathology. This will make diagnoses faster, more accurate, and more efficient, improving treatment approaches and speeding new cures to patients," says Jim Rogers, CEO, Mayo Clinic Digital Pathology.

"AI-driven insights can accelerate diagnostics, enhance precision medicine and revolutionize patient care," said Kimberly Powell, VP of Healthcare and Life Sciences, NVIDIA. "By digitizing and harnessing the power of vast datasets through its Digital Pathology platform, powered by NVIDIA's accelerated computing, Mayo Clinic is helping pave the way for a future with faster medical breakthroughs, better treatments and improved outcomes for patients across the globe."

"Merging Mayo Clinic's data and expertise with our advanced machine learning capabilities will produce breakthrough foundation models and AI products that advance the field of precision medicine and meaningfully improve patient care," says Viktor Matyas, CEO of Aignostics.

The vast majority of pathology practices remain tethered to analog processes, hindering access to critical diagnostic data that could be used to expand diagnostics and treatments and speed the development of new therapies to benefit patients. To address this challenge, Mayo Clinic has moved quickly, investing in digitizing its pathology practice and by scanning its extensive archive of pathology slides, as well as prospectively scanning pathology slides from current patients. To date, Mayo Clinic Digital Pathology has leveraged 20 million digital slide images linked to 10 million patient records that incorporate treatments, medications, imaging, clinical notes, genomic data and more.

In less than two months, Mayo Clinic and Aignostics developed a leading foundation model built on 1.2 million deidentified slides from Mayo Clinic and Charité – Universitätsmedizin Berlin, findings of which were published in a paper on Jan. 9. Current efforts include developing and deploying new solutions enabled by this model. Future plans are focused on building new models, including one being trained on 5 million slides.   

The NVIDIA collaboration will create a first-in-class infrastructure for building and deploying foundation models to accelerate generative AI advances in pathology and beyond. With NVIDIA's healthcare-specific full stack computing architecture for artificial intelligence, NVIDIA Clara, Mayo Clinic is building models that will open new frontiers in medicine and lay the foundation for more personalized patient experiences.      

The development of Mayo Clinic Digital Pathology has been a planned process over many years. The pathology platform takes advantage of the portfolios of Mayo Clinic Platform, a global network that drives digital innovation around diagnosis, treatment and operational improvements worldwide, and Mayo Clinic Laboratories, which provides advanced testing and pathology services for healthcare organizations worldwide. Continuing its efforts to transform healthcare, Mayo Clinic is working with investors and data providers to continue building a pathology platform that spurs innovation and transforms the medical practice for the benefit of healthcare systems and patients worldwide.

"These new capabilities using digital pathology data will unlock this critically important clinical information for building AI solutions for advanced diagnosis and care of patients and that will improve the lives of patients globally," says Matthew Callstrom, M.D. Ph.D., chair of Mayo Clinic Radiology in the Midwest and medical director for Generative AI and Strategy.

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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:

• Terri Malloy, Mayo Clinic Communications, newsbureau@mayo.edu

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Each year, many women undergo surgery for pelvic organ prolapse, a condition where weakened muscles and tissues allow organs like the bladder or uterus to shift and press against the vaginal wall. This typically results in feelings of tissue bulging from the vagina, pelvic pressure or urinary issues.

While the surgical procedure often alleviates symptoms, many women experience a common post-surgical complication: urinary tract infections.  

Now, researchers at Mayo Clinic, led by Marina Walther-Antonio, Ph.D., and John Occhino, M.D., have found a way to potentially predict who will develop these infections before surgery even begins.

Their study reveals that specific patterns in the vaginal microbiome — a community of microorganisms, including bacteria, fungi and viruses — could serve as early indicators of urinary tract infection risk. Their findings are published in Nature Scientific Reports.

Zeroing in on key bacteria

Their findings show that women with lower levels of the protective bacterial species Lactobacillus were more likely to develop urinary tract infections following pelvic organ prolapse surgery. In addition, they found that higher levels of Prevotella and Gardnerella — bacteria linked to inflammation and infection — are also associated with an increased risk of postoperative complications. 

The research also provides insights on how surgery itself impacts the microbiome. Samples taken after surgery showed notable disruptions to both the vaginal and urinary microbiomes. These changes included lower microbial diversity, which can leave the body more vulnerable to infection.  

The reasons for the changes are likely multifactorial and may include preoperative antibiotic administration, vaginal cleansing prior to surgery and surgery itself. 

"Our ability to detect these microbiome patterns provides a potential opportunity to personalize treatment strategies and improve outcomes."

Marina Walther-Antonio, Ph.d.

"Our ability to detect these microbiome patterns provides a potential opportunity to personalize treatment strategies and improve outcomes," says Dr. Walther-Antonio, a microbiome researcher at Microbiomics Program at Mayo Clinic's Center for Individualized Medicine. Dr. Walther-Antonio also conducts research in the Departments of Surgery and Obstetrics and Gynecology, as well as the Mayo Clinic Comprehensive Cancer Center. 

Dr. Walther-Antonio's collaboration with Dr. Occhino bridges a gap between cutting-edge research and clinical practice. 

"Understanding the microbiome's role in post-surgical infections gives us a unique opportunity to possibly prevent these complications altogether," says Dr. Occhino, a Mayo Clinic urogynecologic surgeon. Dr. Occhino specializes in treating pelvic floor disorders, including conditions like pelvic organ prolapse and urinary incontinence.  

Turning microbiome data into action 

The study analyzed microbiome samples from postmenopausal women undergoing a vaginal hysterectomy with pelvic reconstruction. Researchers collected samples using vaginal swabs or urine collection at five stages, including before surgery, immediately after and during recovery. Advanced sequencing techniques were used to map the genetic material of the microbes and identify changes in the microbial communities. 

"Understanding the microbiome's role in post-surgical infections gives us a unique opportunity to possibly prevent these complications altogether."

John Occhino, M.D.

Dr. Walther-Antonio and Dr. Occhino plan to expand their research to include larger and more diverse patient groups. This effort aims to confirm their findings and explore interventions. This could include using probiotics to restore microbial balance before surgery or adjusting surgical timing for at-risk patients. 

Dr. Walther-Antonio's other recent microbiome discoveries

Dr. Walther-Antonio's expertise in microbiome research extends beyond surgical outcomes. Her work also focuses on specific microbial communities associated with gynecologic cancers, including endometrial and ovarian cancers. She has also investigated how these microbes may contribute to disease progression and influence treatment responses. These discoveries have driven the development of noninvasive swab tests designed for earlier detection to improve outcomes. 

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

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Mayo Clinic researchers have pioneered an artificial intelligence (AI) tool, called OmicsFootPrint, that helps convert vast amounts of complex biological data into two-dimensional circular images.  

Omics is the study of genes, proteins and other molecular data to help uncover how the body functions and how diseases develop. By mapping this data, the OmicsFootPrint may provide clinicians and researchers with a new way to visualize patterns in diseases, such as cancer and neurological disorders, that can help guide personalized therapies. It may also provide an intuitive way to explore disease mechanisms and interactions. 

The details of the tool are published in a new study in Nucleic Acids Research.  

"Data becomes most powerful when you can see the story it's telling," says Krishna Rani Kalari, Ph.D., lead author of the study and associate professor of biomedical informatics at Mayo Clinic's Center for Individualized Medicine. "The OmicsFootPrint could open doors to discoveries we haven't been able to achieve before." 

Simplifying complex data 

Genes act as the body’s instruction manual, while proteins carry out those instructions to keep cells functioning. Sometimes, changes in these instructions — called mutations — can disrupt this process and lead to disease. The OmicsFootPrint helps make sense of these complexities by turning data — such as gene activity, mutations and protein levels — into colorful, circular maps that offer a clearer picture of what’s happening in the body. 

In their study, the researchers used the OmicsFootPrint to analyze drug response and cancer multi-omics data. The tool distinguished between two types of breast cancer — lobular and ductal carcinomas — with an average accuracy of 87%. When applied to lung cancer, it demonstrated over 95% accuracy in identifying two types: adenocarcinoma and squamous cell carcinoma. 

Small data sets bring big impacts 

The study showed that combining several types of molecular data produces more accurate results than using just one type of data. 

The OmicsFootPrint also shows potential in providing meaningful results even with limited datasets. It uses advanced AI methods that learn from existing data and apply that knowledge to new scenarios — a process known as transfer learning. In one example, it helped researchers achieve over 95% accuracy in identifying lung cancer subtypes using less than 20% of the typical data volume.  

"This approach could be beneficial for research even with small sample size or clinical studies," Dr. Kalari says. 

To enhance its accuracy and insights, the OmicsFootPrint framework also uses an advanced method called SHAP (SHapley Additive exPlanations). SHAP highlights the most important markers, genes or proteins that influence the results to help researchers understand the factors driving disease patterns. 

From research to clinical practice 

Beyond research, the OmicsFootPrint is designed for clinical use. It compresses large biological datasets into compact images that require just 2% of the original storage space. This could make the images easy to integrate into electronic medical records to guide patient care in the future. 

The research team plans to expand the OmicsFootPrint to study other diseases, including neurological diseases and other complex disorders. They are also working on updates to make the tool even more accurate and flexible, including the ability to find new disease markers and drug targets. 

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

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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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