Tag: United States

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Stripe, Anthropic, and OpenAI are backing an effort to stop respiratory infections

The common cold comes for us all—often more than once a year. And there is no way to prevent it. The best you can do is take vitamin C and stay away from people with the sniffles.

Now the payment company Stripe, founded by brothers Patrick and John Collison, says it will fund a new $500 million nonprofit whose goal is preventing both the common cold and the flu. Its eventual aim is to get rid of respiratory viruses altogether.

The new organization, called Intercept, will use grants and investments to back prevention approaches, including vaccines, as well as large-scale air-cleaning systems for schools, offices, and other public spaces.

In addition to Stripe, other funders include Anthropic, Flu Lab, and the OpenAI Foundation, as well as Bill Gates and several traders at the quantitative investing fund Jane Street Capital, according to an Intercept spokesperson.

“I think we treat respiratory infections as a minor nuisance, but have really underweighted the burden that they impose on society,” says Nan Ransohoff, the Stripe executive leading the initiative along with Charlie Petty, a venture capitalist who joined Stripe this year. On average, people spend 5% of their lifetime fighting a cold or the flu, according to Ransohoff.

Despite that, drug companies put relatively little effort into preventing colds. Part of the problem is that the sniffles are caused by more than 200 different viruses, according to the American Lung Association, with rhinoviruses being the most common culprits. There are so many that it typically doesn’t pay to try to stop any one of them with a vaccine. “When pharma companies look at it, it’s not as attractive as other things they could work on,” says Ransohoff. “So it hasn’t attracted the resources.”

Stripe previously organized a $1.8 billion program called Frontier to encourage the development of carbon removal technology, as a way of countering climate change. Ransohoff says removing carbon from the atmosphere and getting rid of respiratory viruses are similar in that each is “technically possible” but they “lack commercial incentives.”

The concept for Intercept took shape after Ransohoff started talking to David Veesler, a structural biologist and vaccine designer at the University of Washington, who argued that it’s possible to come up with broad countermeasures that work against many viruses at once. 

“He effectively sort of nerd-sniped me,” Ransohoff says of Veesler. “He convinced me that this is technically possible. He also helped me understand that some of the reasons that this hasn’t been done before was sort of an incentive problem.”

Veesler says the growing tool kit available to scientists includes RNA drugs, antibodies, and computational protein design. For instance, one idea is to engineer virus-grabbing proteins that people could spray in their nasal passages, to catch viruses before they cause infection.

 “Most people just accept these viruses as a fact of life, and that got us thinking: Do we have to accept it?” says Veesler. “The more we thought about it, the more we realized that many of these problems have not been worked on with modern technologies.”

The project takes inspiration from efforts to fight the covid-19 virus, where Veesler’s group was among those involved in the speedy development of vaccines, antiviral drugs, and antibodies. 

According to Ransohoff, Intercept’s advisors will include Peter Marks, a former top FDA official, as well as Moncef Slaoui, the pharmaceutical executive who led the US coronavirus vaccine effort, Operation Warp Speed.

A key challenge for Intercept will be coming up with ways to counter many viruses at one time. That accounts for the interest in air-cleaning technology, such as using strong ultraviolet light to inactivate viruses. The idea, the group says, is to remove them from the air in the same way municipalities remove impurities from the water supply before it’s piped to people’s homes.

The US funds about $6.5 billion a year in virus research through the National Institute of Allergy and Infectious Disease, or NIAID. But that agency’s budget hasn’t grown in recent years, leaving more room for private philanthropy.

And Stripe’s Collison brothers have become some of the most reliable philanthropists in viral research. After giving away “fast grants” to help labs during the covid-19 pandemic, they later joined other donors who committed $650 million to establish the Arc Institute in Palo Alto, California, which has developed AI models for biological research.

“The diversity of viruses is just too large and seems daunting, so people don’t even try,” says Veesler. “I’m happy that someone is ready to help scientists, not accepting the status quo, and doing something different.”

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Drug Targets LDL Receptor Pathway to Control Cholesterol

Cholesterol-related heart disease remains the leading cause of death worldwide, and while doctors have more tools than ever to treat it, many patients still can’t achieve safe cholesterol levels or can’t tolerate the side effects of available medications. Researchers at the University of California (UC), San Diego, School of Medicine have now uncovered a hidden biological pathway, dependent on a protein known as Ral, which explains why high-cholesterol diets steadily chip away at our body’s ability to clear harmful low-density lipoprotein (LDL) cholesterol from the blood. The team‘s preclinical study, including tests in mice, also identified a drug candidate already proven safe in humans that could potentially target the pathway.

“We’ve known for a long time that a high-cholesterol diet reduces the liver’s ability to clear cholesterol from the blood, but we didn’t fully understand why,” said Alan Saltiel, PhD, professor of medicine at UC San Diego School of Medicine and director of the UC San Diego/UCLA Diabetes Research Center. “This new discovery explains a critical piece of that puzzle.” Saltiel is senior author of the researchers’ published paper in Nature, titled “Dietary cholesterol activates a Ral-dependent pathway driving LDLR turnover,” in which they concluded, “Together, our findings reveal a Ral-dependent signalling pathway as a key regulator of LDLR turnover and cholesterol homeostasis.”

Disruptions in cholesterol homeostasis are closely linked to an increased risk of atherosclerosis and cardiovascular disease (CVD), the authors wrote. “Elevated low-density lipoprotein cholesterol (LDL-C) significantly contributes to CVD by promoting the formation of atherosclerotic plaques in arteries.”

The liver is the main organ involved in removing cholesterol from the blood so it can be broken down and used elsewhere. This is done through LDL receptors (LDLRs), which sit on the surface of liver cells and act like docking stations, grabbing LDL cholesterol from the bloodstream and pulling it inside the cell for processing. “LDLRs have a crucial role in the uptake of LDL-C from the circulation by hepatocytes,” the investigators continued. The more LDL receptors on liver cells, the more cholesterol gets cleared from the blood, which is why most cholesterol-lowering drugs, such as statins or PCSK9 inhibitors, work by preserving or increasing the number of these receptors. However, the team noted, such treatments have their limitations. “The molecular switches that coordinate LDLR trafficking and turnover in response to nutritional cues, including high dietary cholesterol, remain poorly defined.”

The new research, carried out in mice and in human cells, reveals a previously unknown mechanism that quietly works against the cholesterol removal process, slowly reducing the number of LDL receptors and contributing to high blood cholesterol. The team found that this process begins when a protein called Ral—which Saltiel has previously studied in fat cells—is activated by high dietary cholesterol. “We describe here a previously unrecognized role for Ral signaling in orchestrating LDLR cellular trafficking and lysosomal routing in hepatocytes under chronic cholesterol stress,” the team stated.

Their studies showed that the more Ral is activated, the fewer LDL receptors remain available to clear cholesterol from the blood. This depletion process ultimately relies on a lysosomal protease enzyme called cathepsin A (CTSA). They further explained, “Ral engages the endocytic RalBP1–REPS1 complex to promote LDLR internalization and lysosomal routing, where LDLR is degraded by the lysosomal protease cathepsin A (CTSA).”

The researchers also found that blocking CTSA with a selective small molecule inhibitor (SAR164653) was enough to stabilize LDL receptors and dramatically lower circulating LDL cholesterol in mice. “Pharmacological inhibition of CTSA activity increases hepatic LDLR function and improves cholesterol clearance, offering a potential new therapeutic strategy for hypercholesterolaemia and cardiovascular disease,” they stated.

“There’s still a real need for new cholesterol-lowering options, since some people can’t get to safe levels even with the drugs we have now,” said Saltiel. “This new pathway we discovered is completely separate from anything that existing drugs target, so it gives us a new opportunity to fill that gap.”

After a fundamental biological breakthrough, it typically takes significant additional research to find drugs that target it. However, in this case, a CTSA inhibitor has already been through the early stages of drug development, with the initial goal of treating heart failure. While it was eventually shelved for strategic reasons, the drug had previously advanced to a Phase I clinical trial, where it was successfully tested for safety.

This discovery suggests that the investigational drug is already ready for testing in a Phase II trial for high cholesterol. “Luckily, there’s an experimental drug sitting on the shelf that’s already been shown to be safe in humans,” said Saltiel. “We hope to test whether this might be effective by conducting a clinical trial, which could potentially bring a new treatment option to patients much sooner than would have been expected.”

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Leveraging Self-Reporting in an Existing e-Cohort to Identify Clinically Relevant Mitral Valve Prolapse: Pilot Questionnaire Study

Background: Mitral valve prolapse (MVP) is a common valvulopathy associated, in a minority of cases, with heart failure, severe mitral regurgitation (MR), and sudden arrhythmic death. Digital tools hold promise for faster and more efficient recruitment of study participants into a large-scale MVP Registry. Objective: This study sought to evaluate the feasibility of surveying participants in an existing e-cohort to identify and clinically characterize MVP cases based on self-reporting and to recruit them in an MVP Registry at the University of California, San Francisco. Methods: We surveyed Northern Californian participants of the Health eHeart Study, a large e-cohort using the Eureka digital research infrastructure, about a prior diagnosis of MVP. MVP-positive respondents were asked to provide relevant medical records to confirm their eligibility and were invited to enroll in an MVP Registry if evidence of MVP was confirmed. A follow-up survey was sent after 1 month and after 5 years to collect data about clinical outcomes, including arrhythmias and the need for mitral valve repair. Results: The survey was delivered to 5746 participants, and 520 completed responses were collected. A prior diagnosis of MVP was self-reported by 16.3% (85/520) of respondents. Echocardiograms were obtained from 51.8% (44/85) of participants, and evidence of MVP was confirmed in 32.9% (n=28) of individuals, all of whom joined the registry. Participants with more severe MR had a higher number of correct responses regarding both MVP (odds ratio [OR] 10.58, 95% CI 3.58‐63.04; <.001) and MR diagnosis (OR 4.86, 95% CI 2.11‐16.14; =.002). Longitudinal data were available from most patients through responses to a follow-up survey sent 1 month and 5 years later (18/28, 64.3% and 17/28, 60.7% of MVP confirmed respondents, respectively). Among the patients with electronic health records available, 75% (3/4) had a correct self-reported diagnosis of arrhythmia. Conclusions: e-Cohort methods with self-reported clinical data can be used to prescreen candidates for a research study of MVP. These methods can rapidly identify and retain, among many cases of benign MVP, the minority with clinically relevant presentations such as significant MR and ventricular arrhythmias. These cases may be missed, especially when asymptomatic, by small-scale clinic-based recruitment or family screening methods.
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First-in-Human Stem Cell Therapy Trial for Huntington’s Disease Begins at UCI Health

The world’s first in-human embryonic stem cell-derived clinical trial for Huntington’s disease has launched at UCI Health, the clinical arm of the University of California, Irvine. The Phase Ib/IIa trial will evaluate the safety of hNSC-01 neural stem cells derived from embryonic stem cells delivered to the brain by a specialized neurological mapping and targeting stereotactic system.

Huntington’s disease is a fatal, progressive genetic disorder that gradually destroys brain cells. It usually begins between the ages of 35 and 50 with symptoms that include involuntary movements, difficulty thinking and planning daily tasks, and mood changes such as depression. If successful, this therapy could prolong independent living and significantly reduce long-term care costs.

“This clinical trial highlights the important role that an interdisciplinary academic and clinical team together with the HD families, plays in advancing medicine,” said Leslie M. Thompson, PhD, professor of psychiatry and human behavior at UC Irvine. “We are grateful to our patients and their incredible families for their bravery to provide hope for others with very few options.”

The first patient received the intervention at UCI Health Irvine (home to Orange County’s first adult bone marrow/stem cell transplant and cellular therapy program) in May. A second patient is scheduled to receive the intervention in July.

“The first patient intervention went very well. To date, they haven’t reported any serious adverse events,” said Ravi Rajmohan, MD, UCI Health neurologist. “This trial may help us move one step closer to a future with available treatments that could potentially slow the progression of Huntington’s disease.”

The therapy, hNSC-01, uses pluripotent neural stem cells derived from embryonic stem cells, which were manufactured through the UC Davis GMP facility. In animal studies, the cells have been shown to protect existing brain cells, replace lost cells, rebuild impaired brain circuits, release helpful proteins, such as brain-derived neurotrophic factor (BDNF), and reduce harmful protein accumulations that damage brain cells. The stem cells were also shown to be safe over long periods in mice.

The clinical trial will enroll 21 people ages 18 to 65 with early-stage Huntington’s disease. Twelve participants will be enrolled into a Phase Ib dose-escalation group and nine in a Phase IIa expansion group.

The stem cells are implanted during a roughly six-hour surgical procedure done under general anesthesia. While lying face down in an MRI scanner, the patient receives stem cells implanted directly into the striatum deep in the brain, using a purchased proprietary therapy-enabling platform for navigation and surgical delivery. Damage to the striatum, which is responsible for motor control, decision-making, motivation and more, causes Huntington’s disease symptoms. Subjects will be closely monitored for safety as well as preliminary signs of potential benefit.

The clinical trial is made possible by a $12 million grant from the California Institute of Regenerative Medicine (CIRM), and the trial is coordinated through the UC Irvine Alpha Clinic.

The post First-in-Human Stem Cell Therapy Trial for Huntington’s Disease Begins at UCI Health appeared first on GEN – Genetic Engineering and Biotechnology News.

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STAT+: U.S. health spending rose sharply in 2025, thanks to GLP-1 use and more care

Americans are seeing their doctors, getting hospital procedures, and filling prescriptions more frequently than economists and budget experts anticipated. Weight loss drugs, in particular, have morphed into their own special category of spending and are pushing budgets across the country to their limits.

Combining an increased amount of care with the country’s high baseline of prices has resulted in the health care system taking up more of the economy, new data show — findings that again reflect people’s widespread discontent with how unaffordable health care has become.

The country spent $5.7 trillion on health care in 2025, a 7.3% increase from 2024, according to the latest government figures published in the journal Health Affairs on Wednesday. That amounted to almost $16,500 per person. 

Continue to STAT+ to read the full story…

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BIO 2026: CEO Calls for U.S. Biotech Urgency and International Competitiveness

SAN DIEGO — Biotechnology is entering one of the most transformative periods in its history. But, according to Biotechnology Innovation Organization (BIO) CEO John Crowley, outdated regulations, rising development costs, and global competition threaten to slow progress unless policymakers act.

At the 2026 BIO International Convention in San Diego this week—which drew “roughly 20,000 attendees,” according to the organizers—Crowley outlined a vision for the future of biotechnology centered on accelerating clinical research, embracing artificial intelligence, and maintaining U.S. leadership in a rapidly evolving global bioeconomy.

The grassroots gauntlet

Crowley’s personal journey as a father shaped his path into biotechnology. In the late 1990s, two of his children were diagnosed with a rare form of muscular dystrophy. He left Bristol-Myers Squibb’s marketing department to co-found a biotechnology company with an Oklahoma academic researcher over scientific progress.

The struggle to get funding was immense. Crowley reflected on his first BIO convention in 2000 amidst the excitement of the Human Genome Project: “I came and there were tens of thousands of people partnering as there is today, still a quarter of a century later. Being the 31-year-old CEO of a small startup in Oklahoma City with no money, literally nobody signed up to meet with me and nobody accepted my meeting request.”

Crowley recalled going to the main stage, where a gentleman, rendered quadriplegic through a horse accident, came out on the stage and said, “Biotechnology—it’s a great big word that just means hope. It’s my hope that someday I can hold my wife’s hand on the beach or throw a ball to my kids.”

Crowley, empty-handed, returned to Oklahoma City and was able to scrounge up the funds for his startup, Novazyme Pharmaceuticals, which was ultimately funded by home equity loans and credit card advances to develop rare disease treatments. Just one year later, Novazyme was acquired by Genzyme Corporation for $225 million.

The experience engrained in Crowley two main concepts: first, developing therapeutics doesn’t always start in big pharma but, rather, often has grassroots origins; second, and relatedly, it’s an almost impossible battle for anyone outside of big pharma to fight.

“That’s the way so much of our science happens,” Crowley said. “It comes out of great universities, and it’s a scientist and entrepreneur—and increasingly, families, patients, and patient advocates—leading the way and going through the whole journey, running that gauntlet of making medicines.”

Modernizing clinical trials and accessible AI

To achieve the vision of maximizing the development and reach of biotechnology, Crowley identified a handful of problems, including the need to change the current system of clinical trials. Crowley praised the FDA’s new “Project Trailblazer” initiative to modernize experimental therapy human testing. He argued that clinical trials have become excessively burdensome and costly, limiting innovation and delaying patient access to new treatments.

Over the past year, Crowley and BIO have worked with regulators and industry stakeholders to identify development bottlenecks. “The FDA needs to continue to be the gold standard of the world,” he said, while emphasizing that modernization is necessary to make the agency a stronger “beacon of innovation.” BIO has proposed several reforms, including measures designed to streamline trial approvals and improve the efficiency of regulatory review.

Describing recent discussions among BIO’s board of directors, which includes executives from both major pharmaceutical companies and small biotechnology startups, Crowley said there were two major strategic topics that emerged that dominated the conversation: China and AI.

For AI, the question wasn’t about whether it could revolutionize biotechnology; rather, it had to do with making AI capabilities accessible to companies of all sizes. Crowley noted a major disparity. “Our biggest companies have the resources and the focus to think about AI. They’ve got hundreds or more people focused on this. Our small companies don’t have those resources,” he said.

Crowly continued, “It’s also a challenge because in our industry we would work on such long timelines, and it’s hard for an entrepreneur and biotech of a small or a mid-sized company who’s invested years to get to…starting Phase III, and all of a sudden you’ve got this massive disruptive technology. That’s exactly what AI is going to be.”

The solution, according to Crowley, is for BIO to be at the forefront to enable the rapid implementation of AI into drug development paradigms, clinical trials, and the regulatory review process.

Challenging China

Crowley’s most stressed point was that the United States must remain competitive against growing international rivals, particularly China. “Drug development has just gotten too costly and burdensome, and it takes too much time,” said Crowley. In this [global] bioeconomy where we need to compete and outcompete countries like China, these are reforms that are needed.”

He characterized biotechnology as a matter of national security and argued that the United States should treat the industry as a strategic asset. While supporting bipartisan efforts in Washington to strengthen domestic biotechnology capabilities, he cautioned against policies that could create unintended consequences or limit access to potentially life-saving technologies.

“The world is a better, safer, healthier, and more prosperous place when the United States and its allies continue to lead in biotechnology,” Crowley said.

China has identified biotechnology as a strategic priority through multiple national development plans and has invested heavily in scientific infrastructure, manufacturing capacity, and research capabilities. Crowley argued that the most effective response is not isolation but improving the competitiveness of the U.S. innovation ecosystem.

Crowley repeatedly returned to what he described as “man-made problems” holding the industry back. While scientific challenges will always exist, Crowley said barriers such as complex regulations, insufficient research funding, delays in patient access, and rising out-of-pocket healthcare costs are obstacles that policymakers can address. “We can’t come to this convention and cure every cancer,” he said. “But if we get together with policymakers and lawmakers, we can pretty quickly solve a lot of these man-made problems if we have the will.”

50 years down, 50 years ahead

As biotechnology celebrates more than 50 years of innovation, Crowley argued that the industry’s future will depend not only on scientific breakthroughs but also on its ability to modernize the systems that govern how those breakthroughs reach patients.

“I hope you see, when you’re here at this convention, that it captures that entrepreneurial spirit,” said Crowley. “It has to be grounded in great science and research, and it’s an exciting time to be in biotech, not just reflecting about all our successes and our many failures and challenges along the way in 50 years and looking out in the months, years, and next 50 years about what biotechnology can do to extend and enhance life and to alleviate an enormous amount of human suffering.”

With advances in gene editing, genomic medicine, artificial intelligence, and cell therapies accelerating simultaneously, Crowley believes the next era of biotechnology could surpass anything seen before—provided the industry can remove the barriers standing in its way.

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AI-CURA Automates Genetic Variant Classification

A new AI framework can classify hundreds of genetic variants as accurately as a human expert in a fraction of the time, research suggests.

Combining AI-assisted CURAtor (AI-CURA) with the latest large language models (LLMs) could streamline the diagnosis of rare genetic diseases.

The workflow system, described in Science Translational Medicine, performed as well as clinical experts in classifying 150 variants, while adhering to complex expert guidelines.

It was also able to categorize 150 variants with conflicting classifications.

“This study pushes the boundaries of fully automated variant interpretation,” commented senior journal editor Catherine Charneski, PhD, from the University of Bath.

Whole genome sequencing (WGM) has proven pivotal in ending the prolonged diagnostic odyssey of many patients with rare genetic disorders.

To manage the huge number of variants identified through WGS, attempts have been made by expert associations and working groups to establish guidelines and recommendations.

These now form a widely adopted classification system that categorizes variant-associated evidence into distinct rule-based categories.

But while some rules can be readily automated, most evidence still needs manual interpretation of the literature. This requires variant curators to possess broad knowledge across various aspects of molecular biology and genetics, as well as a deep understanding of expert recommendations to accurately interpret and score variants.

Wei Ma, PhD, and colleagues from the Hong Kong Genome Project (HKGP) therefore developed AI-CURA, a fully automated framework for variant classification that integrates LLMs to handle both literature-independent and literature-dependent evidence.

The tool integrates the assessment of evidence for non–literature-based criteria, which can be automated using standard bioinformatic tools, with a separate LLM-supported assessment of literature-based evidence.

Two state-of-the-art LLMs—DeepSeek-R1 and o3-mini-high—were tested for their ability to summarize literature-derived evidence relevant to variant classification.

The team found that the open-source DeepSeek-R1 outperformed o3-minihigh and had high sensitivity and 100% specificity in interpreting rules from the American College of Medical Genetics and Genomics (ACMG) that require understanding literature-based evidence.

They then tested it using 150 variants curated by ClinGen experts, with 150 expert-curated variants and 150 variants with conflicting classifications from the Clinical Genome Resource.

The open-source LLM DeepSeek-R1 showed high concordance with ClinGen experts in establishing a final diagnosis.

“In this study, DeepSeek-R1 demonstrated high accuracy (89.3 to 100%) in determining the application of seven literature-dependent ACMG rules,” the authors reported.

They added: “Our use of LLMs substantially streamlined the variant analysis and interpretation process. LLMs can finish summarizing the literature evidence in minutes.

“In comparison, curators in the HKGP typically spend around four hours per patient on WGS curation, with most of this time dedicated to reviewing literature.”

The post AI-CURA Automates Genetic Variant Classification appeared first on Inside Precision Medicine.

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Social Determinants of Health Improve Disease Risk Prediction Beyond Genetics Alone

A study by researchers at the Icahn School of Medicine at Mount Sinai has found that social determinants of health—including environmental conditions, health behaviors, access to resources, and social well-being—can contribute as much as or more than genetic risk in predicting several common diseases. The research, published in The American Journal of Human Genetics, showed that incorporating social, behavioral, and environmental information into disease-risk models improved prediction when incorporated with genetic information for conditions including asthma, chronic kidney disease, coronary heart disease, high cholesterol, breast cancer, and prostate cancer.

“Genes are an important part of the equation, but they do not determine destiny,” said senior author Samira Asgari, PhD, an assistant professor of genetics and genomic sciences at Mount Sinai. “We found that the circumstances of people’s lives—their environments, behaviors, and social experiences—can contribute as much as genetics to predicting disease risk. To truly understand health, we have to look at the whole person, not just their DNA.”

According to the researchers, complex diseases arise through the interaction of genetic predisposition with environmental, behavioral, and social influences, yet these factors are often studied in isolation. Existing genetic models often rely on polygenic risk scores, while epidemiological approaches focus on lifestyle, environmental exposures, or social factors independently. The researchers sought to bridge that gap by integrating both types of data into a single risk prediction framework.

To conduct the study, the team analyzed data from 413,457 participants in the All of Us Research Program, a nationwide research effort in the U.S. supported by the National Institutes of Health. The team combined genetic information, electronic health records, and survey responses, with more than 100 environmental, behavioral, and social variables were evaluated, to create a broad picture of the different factors that may influence health.

Rather than selecting a limited number of known social risk factors in advance for their survey, the researchers used a statistical technique called multiple correspondence analysis, or MCA. The approach converted more than 100 categorical social, environmental, and behavioral measures into low-dimensional representations that helped identify patterns of non-genetic risk.

The choice to use MCA distinguished the study from many previous approaches. Past methods often have depended on selecting a small set of established risk factors or using statistical procedures that prioritize only the strongest predictors. By contrast, MCA identifies patterns across many correlated variables simultaneously, allowing researchers to examine broader social and environmental variables without assuming beforehand which factors have the most influence on health.

The analysis found known contributors to disease risk such as economic status and smoking, but also identified factors that receive less attention in published studies, including loneliness and spirituality. First author Abhijith Biji, a PhD candidate at Icahn School of Medicine, said the data showing associations involving loneliness was particularly notable.

“Some risk factors, such as smoking, have been studied extensively for decades,” Biji said. “What is especially intriguing is that we also observed associations involving factors like loneliness. Understanding how these experiences may become biologically embedded could open new avenues for research and ultimately improve our understanding of disease.”

When the researchers incorporated the MCA-derived measures into prediction models alongside demographic information and polygenic risk scores, predictive performance improved across all six diseases studied. For four of the six diseases, the gains from the MCA-based measures exceeded those attributable to polygenic risk scores.

The findings also suggested that genetic and non-genetic influences generally act independently rather than modifying one another. The researchers found little evidence for broad gene-environment interactions. Instead, inherited genetic risk and social, behavioral, and environmental context appeared to contribute additively to disease risk.

“This additive relationship suggests that interventions targeting social and behavioral factors can reduce disease risk regardless of genetic background, offering hope for broadly applicable public-health strategies,” the researchers wrote.

The researchers noted that the study does not establish causation. Because many survey responses were collected at a single point in time and some exposures may have occurred after disease onset, the findings should be considered as contributions to disease-risk prediction rather than proof that specific factors cause disease.

Building on this work, the team next will seek to integrate social determinants of health with additional biological measures and look mechanisms that may directly connect social experiences to disease. The investigators will also bring in longitudinal data, harmonize survey instruments across cohorts, and integrating other data types to better understand how environmental, behavioral, and social factors influence disease development and interact with biological processes.

“Our goal is to build a more complete understanding of health and disease,” Asgari said. “By combining genetics with social and environmental context, we can move toward risk models that better reflect the realities of people’s lives and help advance more personalized approaches to health.”

The post Social Determinants of Health Improve Disease Risk Prediction Beyond Genetics Alone appeared first on Inside Precision Medicine.

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Judge temporarily blocks subpoenas in criminal probe of transgender care at New York hospitals

NEW YORK — A judge temporarily blocked federal prosecutors in Texas from getting access to the medical records of transgender patients treated at New York hospitals on Wednesday, saying they were part of an improper government effort to “demonize and eradicate an entire population of transgender” people.

Judge Katherine Polk Failla ruled a day after hearing oral arguments in Manhattan, calling the government’s pursuit of the most sensitive medical records of a “uniquely vulnerable group” of patients treated over a six-year period to be “most egregious” and unconstitutional.

Read the rest…

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Catheter-Based OCT Imaging Shows Promise for Noninvasive Endometrial Cancer Diagnosis

A research team at Washington University in St. Louis has developed a catheter-based optical imaging method that could be used as an “optical biopsy” for detecting endometrial cancer and its precancerous lesions. The approach, described in the journal npj Imaging, uses three-dimensional optical coherence tomography (OCT) imaging combined with a machine learning algorithm which examines and analyzes the entire endometrial cavity to identify tissue changes associated with endometrial intraepithelial neoplasia (EIN) and endometrial cancer.

“Current endometrial biopsy practice has an estimated false-negative rate of about 10% (approximately 90% sensitivity), largely due to sampling limitations and interpretive variability,” said senior investigator Quing Zhu, PhD, a professor of engineering at Washington University. “With our three-dimensional OCT imaging system combined with machine learning, we can image the entire endometrial cavity in two to three seconds and may have a potential to achieve higher sensitivity than random biopsy sampling.”

Endometrial cancer is the most common gynecologic malignancy in the United States, with estimated 69,000 cases projected to be diagnosed in 2025. As with most cancers, early detection has a significant impact on treatment outcomes with five-year survival rates between 80% and 90% when it is diagnosed at stage I.

Existing diagnostic tools have limitations that can impact early and accurate diagnosis. For instance, transvaginal ultrasound is ineffective for early EC, while endometrial biopsy has a 10% false-negative rate due to sampling and interpretive variability.” Although hysteroscopy allows direct visualization of the uterine cavity, it does not provide information about subsurface tissue architecture.

In an interview with Inside Precision Medicine, Zhu said the most widely used diagnostic approaches can miss cancers or depend heavily on operator skill. She noted that the low resolution of transvaginal ultrasound limits detection of early disease, while operative hysteroscopy requires cervical dilation and carries procedural risks. Endometrial biopsy, she added, can miss cancers that occupy less than half of the endometrial cavity surface.

The new approach developed by Zhu and team uses OCT, a light-based imaging technology that creates high-resolution cross-sectional images of tissue. This imaging method uses low-coherence interferometry to measure the echo time delay and intensity of backscattered light, producing real-time images of tissue microstructure with micrometer-scale resolution with tissues penetration depths of approximately one to two millimeters.

To create a method to comprehensively image the endometrium the WashU team developed a custom 3.1-millimeter catheter. Zhu said that the catheter rotates within the endometrial cavity at roughly 600 revolutions per minute while being pulled back automatically at a constant speed. Depending on uterine size, a 3- to 5-centimeter segment of the cavity can be imaged in approximately two to three minutes. The resulting volumetric scans provide three-dimensional views of tissue structure and optical properties throughout the cavity. The team then applied computational analysis to identify functional, structural, and radiomic features based on OCT intensity and scattering images.

To test this OCT/machine learning approach, the researchers evaluated the technology on 57 freshly excised hysterectomy specimens representing a range of conditions, including normal endometrium, benign abnormalities, EIN, and endometrial cancer. OCT identified 34 specimens that contained either high-risk precancerous lesions or early-stage cancers.

The OCT images revealed differences among normal endometrium, benign endometrium, high-risk precancerous lesions, and cancers at different stages. This new method attained an exploratory sensitivity of 94% and specificity of 87%. A cross-validated logistic regression classifier produced sensitivity of 91% and specificity of 83%.

“These findings support catheter-based 3D OCT as a promising noninvasive optical biopsy approach to improve detection of endometrial cancer,” the researchers wrote in the abstract.

The work builds on earlier investigations of OCT in endometrial disease. Previous research had shown that OCT could distinguish endometrial pathologies, but in those studies the imaging was slow or limited to two-dimensional analysis. “This study is the first to combine catheter-based 3D OCT imaging with functional, structural and radiomic feature analysis to assess the endometrial cavity,” the researchers wrote.

Researchers believe the technology could improve patient care by reducing dependence on repeated tissue biopsies. In the introduction, they wrote that “a real-time, noninvasive, high-resolution modality for subsurface imaging could improve diagnostic accuracy, reduce unnecessary biopsies, and support fertility-sparing management.” Such a tool could be particularly useful for women undergoing serial monitoring while receiving hormone-based treatment.

The investigators describe the method as an optical biopsy because it provides diagnostic information without requiring removal of tissue. “Unlike traditional tissue biopsy, it does not require painful physical tissue samples,” Zhu told Inside Precision Medicine.

The technology is still in an early stage of development. Zhu said future development will require a forward-viewing catheter to improve imaging of the uterine fundus and developing methods for faster data acquisition.

Zhu is now looking to secure funding and begin studies in patients to establish in vivo feasibility and to eventually move the technology into clinical trials.

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