Author: Dick Benson

  • Blood test could streamline early Alzheimer’s detection

    Blood test could streamline early Alzheimer’s detection

    In a landmark study of Hispanic and Latino adults, researchers at University of California San Diego School of Medicine have identified a link between self-reported cognitive decline and blood-based biomarkers, which could pave the way for a simple blood test to help diagnose Alzheimer’s disease and related dementias. This approach could be faster, less-invasive and more affordable than existing screening tools. The results are published in JAMA Network Open.

    “We need ways to identify underlying neurodegenerative diseases earlier in patients with cognitive symptoms,” said corresponding author Freddie Márquez, Ph.D., a postdoctoral scholar in the Department of Neurosciences at UC San Diego School of Medicine. “This study highlights the promise of blood-based biomarkers as a more accessible and scalable tool for understanding cognitive decline, particularly in populations that have been underserved by traditional methods.”

    There is currently only one blood test approved by the Food and Drug Administration to assist in diagnosing Alzheimer’s disease. While this test, the Lumipulse G pTau217/Aβ42 plasma ratio, can detect proteins associated with Alzheimer’s in the blood, it is currently very expensive and only available in specialized care settings.  Whether or not blood can be reliably used for early Alzheimer’s detection on a larger scale is still unknown.

    To help answer this question, the researchers used data from the Study of Latinos–Investigation of Neurocognitive Aging. This clinical study assessed neurocognition in a subset of participants from the Hispanic Community Health Study/Study of Latinos, the largest, most comprehensive long-term study of Hispanic and Latino health and disease in the United States.

    “Hispanic and Latino adults are thought to be more likely to get Alzheimer’s and related dementias, and this group is projected to have the largest increases in disease prevalence over the coming decades,” said senior author Hector M. González, Ph.D., professor in the Department of Neurosciences at UC San Diego School of Medicine. “Despite this, they’re still significantly underrepresented in Alzheimer’s and dementia research, which is something our study aimed to address.”

    The researchers tested the blood of 5,712 Hispanic and/or Latino adults between the ages of 50 and 86, looking for proteins that are present in the brain in people with Alzheimer’s disease, such as amyloid beta and tau proteins. They also assessed participants for subjective cognitive decline, which refers to a decline in cognitive status that the individual themself perceives.

    The researchers found:

    • Higher blood levels of NfL (nerve cell injury marker) and GFAP (brain inflammation marker) were associated with more self-reported declines in thinking, planning and overall cognitive performance. Higher blood levels of NfL and tau protein (ptau-181) were also associated with more self-reported declines in memory.
    • Blood levels of amyloid-beta protein (Aβ42/40), a protein well-known to be associated with Alzheimer’s disease in the brain, showed no associations with subjective cognitive decline.
    • Even in cognitively healthy individuals, associations between NfL and self-reported declines in cognitive performance remained, suggesting that NfL may be detecting early changes in cognition.

    In addition to providing evidence that blood-based biomarkers can be used to detect Alzheimer’s and related dementias early, the researchers also note that a strength of their study is its diverse population.

    “By including participants from underrepresented communities, we’re able to better understand how social determinants of health and comorbidities may influence cognitive trajectories and dementia risk,” added Márquez. “This makes our findings especially relevant for real-world settings.”

    However, the researchers also caution that it will take further research for this approach to make its way into widespread clinical practice, and that even when this happens, the test will still be just one tool in a clinician’s diagnostic arsenal.

    It’s important to note that there’s still a lot we don’t know about the utility of blood-based biomarkers for Alzheimer’s detection,” said Márquez. “These tests have tremendous potential, but they should complement existing approaches, not replace them.”

    Additional coauthors of the study include Kevin Gonzalez, Deisha F. Valencia and Natasha Z. Anita at UC San Diego, Wassim Tarraf at Wayne State University, Ariana M. Stickel and Linda C. Gallo at San Diego State University, Daniela Sotres-Alvarez and Haibo Zhou at University of North Carolina at Chapel Hill, Bonnie E. Levin and Zachary T. Goodman at University of Miami, Michael A. Yassa at UC Irvine, Martha Daviglus and Amber Pirzada at University of Illinois at Chicago and Bharat Thyagarajan at University of Minnesota.

    This study was funded, in part, by grants from the National Institute on Aging (R01AG075758). The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a collaborative study supported by contracts from the NHLBI to the University of North Carolina (grant Nos. HHSN268201300001I/N01-HC-65233), University of Miami (grant Nos. HHSN268201300004I/N01-HC-65234), Albert Einstein College of Medicine (grant Nos. HHSN268201300002I/N01-HC-65235), University of Illinois at Chicago (grant Nos. HHSN268201300003I/N01- HC-65236 Northwestern University), and San Diego State University (grant Nos. HHSN268201300005I/N01-HC-65237).

  • As Probiotic Use Surges, Microbiome-Supportive Food Consumption Stagnates

    As Probiotic Use Surges, Microbiome-Supportive Food Consumption Stagnates

    New research finds that probiotic supplement use has surged in the United States, while the consumption of microbiome-supportive foods has remained virtually unchanged.

    According to a study published in Clinical Gastroenterology and Hepatology, the consumption of probiotic supplements increased 287% among adults from 2009-2023 and 786% among young people (less than 20 years old).

    Over the same span, fiber intake did not meaningfully change, while the average consumption of high microbial foods rose slightly.

    “We have known that probiotic supplement use is increasing across all ages, but this is the first time we have looked closely at it in relation to other microbiome-focused health behaviors,” said Kira L. Newman M.D., Ph.D., Clinical Assistant Professor of Internal Medicine at the University of Michigan Medical School and lead author on the paper.

    “Dietary fiber and fresh produce have well-established health benefits for the gut microbiome. However, our findings suggest that people are not making changes to what they eat, even though an increasing number are concerned enough about their microbiome to take a probiotic supplement.”

    The study authors used data from the National Health and Nutrition Examination Survey.

    From 2009 to 2023, the proportion of people under 20 taking a probiotic rose from 0.63% to 5.58%.

    Among people over 20, the percentage increased from 1.8% to 6.96%.

    Probiotic supplement users were found to consume more foods high in microbial quality and fiber content than non-users.

    Researchers add, however, that these beneficial diet habits may be decreasing, as supplements are potentially used as a substitute for higher-quality diets.

    Probiotic supplement use increased dramatically after 2014 despite official guidelines suggesting limited benefits.

    The study authors note a variety of health benefits associated with high microbial foods.

    They emphasize that these benefits are not necessarily related to microbial content.

    “A diet with plenty of vegetables, fruits, legumes, and whole grains provides not just fiber, but also a wealth of other beneficial vitamins, minerals and plant-derived compounds,” Newman said.

    “This helps support a diverse range of beneficial gut microbes. Prebiotic supplements alone do not contain the same variety or richness. It’s like picking one color out of a rainbow.”

    The study authors hope these trends will highlight the need for more public health campaigns on the importance of diet in fostering microbiome health.

  • Sleep strengthens muscle and bone by boosting growth hormone levels.

    Sleep strengthens muscle and bone by boosting growth hormone levels.

    As every bodybuilder knows, a deep, restful sleep boosts levels of growth hormone to build strong muscle and bone and burn fat. And as every teenager should know, they won’t reach their full height potential without adequate growth hormone from a full night’s sleep.

    But why lack of sleep — in particular the early, deep phase called non-REM sleep — lowers levels of growth hormone has been a mystery.

    In a study published in the current issue of the journal Cell, researchers from University of California, Berkeley, dissect the brain circuits that control growth hormone release during sleep and report a novel feedback mechanism in the brain that keeps growth hormone levels finely balanced.

    The findings provide a map for understanding how sleep and hormone regulation interact. The new feedback mechanism could open avenues for treating people with sleep disorders tied to metabolic conditions like diabetes, as well as degenerative diseases like Parkinson’s and Alzheimer’s.

    “People know that growth hormone release is tightly related to sleep, but only through drawing blood and checking growth hormone levels during sleep,” said study first author Xinlu Ding, a postdoctoral fellow in UC Berkeley’s Department of Neuroscience and the Helen Wills Neuroscience Institute. “We’re actually directly recording neural activity in mice to see what’s going on. We are providing a basic circuit to work on in the future to develop different treatments.”

    Because growth hormone regulates glucose and fat metabolism, insufficient sleep can also worsen risks for obesity, diabetes and cardiovascular disease.

    The sleep-wake cycle

    The neurons that orchestrate growth hormone release during the sleep-wake cycle — growth hormone releasing hormone (GHRH) neurons and two types of somatostatin neurons — are buried deep in the hypothalamus, an ancient brain hub conserved in all mammals. Once released, growth hormone increases the activity of neurons in the locus coeruleus, an area in the brainstem involved in arousal, attention, cognition and novelty seeking. Dysregulation of locus coeruleus neurons is implicated in numerous psychiatric and neurological disorders.

    “Understanding the neural circuit for growth hormone release could eventually point toward new hormonal therapies to improve sleep quality or restore normal growth hormone balance,” said Daniel Silverman, a UC Berkeley postdoctoral fellow and study co-author. “There are some experimental gene therapies where you target a specific cell type. This circuit could be a novel handle to try to dial back the excitability of the locus coeruleus, which hasn’t been talked about before.”

    The researchers, working in the lab of Yang Dan, a professor of neuroscience and of molecular and cell biology, explored the neuroendocrine circuit by inserting electrodes in the brains of mice and measuring changes in activity after stimulating neurons in the hypothalamus with light. Mice sleep for short periods — several minutes at a time — throughout the day and night, providing many opportunities to study growth hormone changes during sleep-wake cycles.

    Using state-of-the-art circuit tracing, the team found that the two small-peptide hormones that control the release of growth hormone in the brain — GHRH, which promotes release, and somatostatin, which inhibits release — operate differently during REM and non-REM sleep. Somatostatin and GHRH surge during REM sleep to boost growth hormone, but somatostatin decreases and GHRH increases only moderately during non-REM sleep to boost growth hormone.

    Released growth hormone regulates locus coeruleus activity, as a feedback mechanism to help create a homeostatic yin-yang effect. During sleep, growth hormone slowly accumulates to stimulate the locus coeruleus and promote wakefulness, the new study found. But when the locus coeruleus becomes overexcited, it paradoxically promotes sleepiness, as Silverman showed in a study published earlier this year.

    “This suggests that sleep and growth hormone form a tightly balanced system: Too little sleep reduces growth hormone release, and too much growth hormone can in turn push the brain toward wakefulness,” Silverman said. “Sleep drives growth hormone release, and growth hormone feeds back to regulate wakefulness, and this balance is essential for growth, repair and metabolic health.”

    Because growth hormone acts in part through the locus coeruleus, which governs overall brain arousal during wakefulness, a proper balance could have a broader impact on attention and thinking.

    “Growth hormone not only helps you build your muscle and bones and reduce your fat tissue, but may also have cognitive benefits, promoting your overall arousal level when you wake up,” Ding said.

    The work was funded by the Howard Hughes Medical Institute (HHMI), which until this year supported Dan as an HHMI investigator, and the Pivotal Life Sciences Chancellor’s Chair fund. Dan is the Pivotal Life Sciences Chancellor’s Chair in Neuroscience. Other co-authors of the paper are Peng Zhong, Bing Li, Chenyan Ma, Lihui Lu, Grace Jiang, Zhe Zhang, Xiaolin Huang, Xun Tu and Zhiyu Melissa Tian of UC Berkeley; and Fuu-Jiun Hwang and Jun Ding of Stanford University.

  • A newly identified reductive uric acid pathway offers hope for gout

    A newly identified reductive uric acid pathway offers hope for gout

    Uric acid builds up in the blood when the body cannot excrete it efficiently, leading to painful gout attacks, kidney stones, and other complications. Current treatments often rely on drugs that block uric acid production, but these can have side effects and do not work for everyone.

    For many years, uric acid degradation is known as occurring mainly through an oxidative pathway, in which uricase enzymes use oxygen to break the purine ring and convert uric acid into allantoin. Humans and higher primates lack functional uricase, which is why they are particularly prone to uric acid accumulation and gout.

    A new study published in Life Metabolism reports an alternative “reductive pathway” that functions without oxygen. In this route, uric acid is first reduced to a newly identified metabolite, “yanthine”, and then further broken down by a sequence of reductive dearomatization and ring-cleaving reactions, ultimately yielding small molecules such as pyruvate and ammonia (Figure 1). This discovery revises the long-standing view of purine catabolism and highlights the metabolic versatility of gut bacteria in anaerobic environments.

    Importantly, the study also detected “yanthine” circulating in human blood, with significantly higher levels in patients with gout compared with healthy individuals. This suggests that “yanthine” could serve as a biomarker for diagnosing or monitoring uric acid-related disorders. To explore therapeutic potential, the team engineered a probiotic strain of Escherichia coli to constitutively activate the reductive pathway. In a uricase-deficient mouse model of hyperuricemia, oral administration of this engineered strain significantly lowered blood uric acid levels, alleviated kidney injury, and remained stably colonized in the gut.

    Together, these findings establish the reductive uric acid pathway as a major addition to the known repertoire of microbial metabolism. The work not only advances fundamental understanding of purine degradation but also points towards practical applications in biomarker discovery and the development of probiotic-based strategies to help control gout.

     

    Photo credit: Credit: Zhi Li, Wei Meng, Zihan Gao, Wanli Peng, Zhandong Hu, Jianhao Zhang, Yining Wang, Xiaoxia Wu, Zipeng Zhao, Chuyuan Zhang, Zhuohao Tang, Zhujun Nie, Shaohua Wu, Benjuan Wu, Hui Zheng, Duqiang Luo, Yang Tong, Yiling Hu, Zehan Hu, Yifeng Wei, Yan Zhang

    Journal Life Metabolism

  • OmegaQuant Awarded NIH Grant to Investigate Fatty Acid Biomarkers for Age-Related Macular Degeneration and Glaucoma

    OmegaQuant Awarded NIH Grant to Investigate Fatty Acid Biomarkers for Age-Related Macular Degeneration and Glaucoma

    The leader in fatty acid testing and research OmegaQuant Analytics, has been awarded a NIH Phase I Small Business Innovation Research (SBIR) grant to investigate whether patterns of fatty acids in the blood can help predict the future risk of age-related macular degeneration (AMD) and glaucoma.

    According to the CDC, AMD and glaucoma are two of the most common and debilitating eye diseases, affecting an estimated 20 million and 4 million people in the United States, respectively. The economic impact of these conditions is substantial and growing as our population continues to age, with an estimate of over $373 billion in annual lost productivity by 2050 in the United States alone.

    Although established risk factors—including smoking, high blood pressure, obesity, high cholesterol, cardiovascular disease, diabetes, poor diet, sun exposure, age, sex, and genetics—can help identify individuals at greater risk, their combined predictive ability remains limited. Earlier identification of people at increased risk could create opportunities for more targeted monitoring and preventive strategies before significant vision loss occurs.

    The newly funded project, “Developing blood fatty acid-based algorithms as early predictors of macular degeneration and glaucoma: Applying machine learning to harmonized data from prospective cohort studies,” will investigate whether red bloodcell fatty acid patterns can provide additional predictive information beyond traditional risk factors.

    Research has suggested that circulating fatty acids, particularly omega-3 fatty acids, may provide valuable information about eye health risk. However, the potential roles of other fatty acids—including trans, omega-6, saturated, and monounsaturated fatty acids—remain less clear. The new study will take a broader approach by examining patterns across multiple fatty acids rather than focusing on a single family.

    Using Machine Learning to Identify New Risk Patterns

    During Phase I, researchers will harmonize fatty acid measurements, eye health outcomes, and other health data from several well-established prospective cohort studies: the Framingham Heart Study (FHS), Women’s Health Initiative Memory Study (WHIMS), Multi-Ethnic Study of Atherosclerosis (MESA), and Boston Puerto Rican Health Study (BPRHS).

    Together, these cohorts will provide data from up to 19,922 individuals, including information on AMD or glaucoma outcomes over an average of more than 10 years of follow-up.

    Using statistical and machine-learning approaches, researchers will evaluate whether baseline red blood cell fatty acid patterns can predict the development of AMD and glaucoma. The project is designed to generate new potential fatty acid-based risk metrics.  The study will also explore relationships between fatty acid patterns and optical coherence tomography angiography (OCTA) measures, such as retinal thickness and vessel density.

    Building Toward Earlier Identification

    The ultimate goal of the research is to determine whether a blood fatty acid profile—used alone or alongside established risk factors—could improve the ability to identify individuals at increased risk for AMD or glaucoma.

    If Phase I demonstrates proof-of-concept feasibility, the findings could provide the foundation for larger prospective studies and further refinement and validation of the predictive models in Phase II.

    “Our goal is to determine whether the fatty acid patterns we can measure in a blood sample contain information that could help identify eye disease risk years before serious vision loss occurs,” said Dr. Bill Harris, Principal Investigator, Founder of OmegaQuant, and President of the Fatty Acid Research Institute (FARI).

    OmegaQuant is well positioned to translate this research into a practical testing approach. For more than 15 years, the laboratory has specialized in fatty acid measurement and interpretation. Further, it supports a large and growing customer base of researchers, clinicians, businesses, and individuals, including an increasing number of optometrists, ophthalmologists and other eye health experts.

    “If we can develop and ultimately validate these fatty acid-based risk profiles, they could provide clinicians with another tool for identifying patients who may benefit from earlier monitoring or preventive intervention,” Dr. Harris added.

    The Phase I project represents an important first step toward determining whether fatty acid biomarkers can enhance current approaches to predicting eye disease risk. Ultimately, OmegaQuant aims to develop a clinically useful blood fatty acid profile that can complement existing risk factors and support earlier, more personalized approaches to protecting eye health.

    Source: OmegaQuant Analytics

  • New Clinical Tool Helps Predict Short-term Risk of Diabetes Complications Using Routine Health Data

    New Clinical Tool Helps Predict Short-term Risk of Diabetes Complications Using Routine Health Data

    Researchers at the University of Maryland School of Medicine (UMSOM) have developed and validated a new risk calculator that can estimate an individual patient’s short-term risk of developing a range of diabetes-related complications, using information already collected during routine medical care.

    Results were published in the journal Nature Communications.

    The study, led by Rozalina G. McCoy, MD, MS, Associate Professor of Medicine in the Division of Endocrinology, Diabetes, and Nutrition, analyzed health data from more than 400,000 adults newly diagnosed with diabetes across the United States. She and her colleagues created a set of prediction models—called the Diabetes Complications Risk Calculator (DCRC)—that can estimate a patient’s likelihood of developing several common complications and update those estimates as new clinical information becomes available.

    People with diabetes are at risk for a wide range of complications, including heart disease, kidney disease, nerve damage, eye disease, and emergencies caused by very high or very low blood sugar. While prediction tools exist, most focus on just one complication at a time or predict the risk of complications over a much longer period of time. The current models also usually rely on data from specialized research groups rather than real-world care settings.

    The new risk calculator was designed to address those gaps. It can estimate risk for nine different acute and chronic complications, including cardiovascular disease, stroke, kidney disease, nerve damage, and blood sugar crises—all at once and over short time intervals that may help improve clinical decisions and patient care.

    “Our goal was to create a tool that reflects the reality clinicians face, where patients often have multiple concurrent and competing risks,” said Dr. McCoy who is also Director of the Precision Medicine and Population Health Program at the University of Maryland Institute for Health Computing. “By looking at these risks together and updating them over time, we can better understand what complication or complications our patients are most likely to experience, which can ultimately support more informed and actionable conversations between patients and their clinicians.”

    The researchers used machine learning — a type of statistical method that can identify patterns in large datasets — to analyze insurance claims and electronic health record data. The models incorporate commonly available information such as age, existing health conditions, medications, and laboratory tests.

    Unlike traditional models that provide a single long-term estimate, the DCRC produces monthly, encounter-level risk estimates that change as a patient’s health status evolves.

    In testing, the models showed good to strong accuracy in predicting whether patients would develop specific complications, both in the original nationwide dataset and in an independent group of patients treated at Mayo Clinic.

    Over time, diabetes complications were common in the study population. Within one year of diagnosis, about one-third of patients had experienced at least one complication, and that number rose to more than 40 percent after two years. The models also identified factors linked to higher risk including:

    • Older age
    • High blood pressure and related complications
    • Longer duration of diabetes
    • Kidney function measures
    • Coexisting health conditions

    Importantly, risk varied from person to person and could change over time—sometimes rising or falling as health conditions and treatments changed.

    “Machine learning and other AI-based methods agentic systems can scan routine clinical and laboratory data in our electronic health records to identify patients who are at high risk for developing irreversible complications of diabetes,” said UMSOM Dean Mark T. Gladwin, MD.  “This diabetes risk calculator demonstrates the power of this approach by continuously updating individual risk estimates as a patient’s health evolves using routine clinical data that already exists in electronic health records.”

    Dr. McCoy emphasized that the calculator is not intended to replace clinical judgment. Instead, it is designed to support care decisions, helping clinicians and patients weigh risks and prioritize prevention strategies. For example, the tool could help identify patients who may benefit from closer monitoring or earlier interventions, or guide discussions about treatment choices.

    “While our results are encouraging, these models should be used cautiously and in combination with clinical expertise,” she said. “We need to do more testing to understand how the tool performs when used in everyday clinical practice.”

    Limitations of the tool include the use of data only from insured patients, which may not fully reflect patients without consistent access to medical care. In addition, some of its predictions were less accurate for certain complications.

    The research team plans to evaluate how the calculator performs when integrated into real-world clinical workflows and whether it can improve shared decision-making and long-term health outcomes.

    Study funding was provided by the National Institute of Diabetes and Digestive and Kidney Diseases (grant number K23DK114497), the National Institute on Aging (NIA) (grant number P30AG097158), the Diane Deshong Family Fund for Artificial Intelligence in Healthcare Delivery, and the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery.

    Original release: https://www.medschool.umaryland.edu/news/2026/new-clinical-tool-helps-predict-short-term-risk-of-diabetes-complications-using-routine-health-data.html

  • AI could help detect common cardiovascular diseases from mammograms

    AI could help detect common cardiovascular diseases from mammograms

    Artificial intelligence (AI) analysis of mammograms could be used to detect different common cardiovascular diseases (CVDs), according to a study that will be presented at ESC Congress 2026.1

    Presenter, Doctor Viana Copeland from Chaim Sheba Medical Center, Tel Aviv University, Ramat Gan, Israel, explained why new detection methods are needed for CVD in women: “Despite being the leading cause of death in women worldwide, CVD is consistently underdiagnosed and undertreated. A common finding in our medical center, and around the world, is that when women do seek medical help, their CVD is already advanced. On the other hand, many women do attend routine breast cancer screening, even when they haven’t sought care for cardiovascular symptoms. We investigated whether AI could help mammography serve an additional purpose in this group – the early detection of CVD – enabling preventive strategies to be implemented.”

    This retrospective cohort study involved data from 29,921 women who underwent 97,364 mammography examinations. The cohort had a median age of 54 years. Clinical information on the presence of three common CVDs – hypertension, ischemic heart disease (also known as coronary artery disease) and stroke – was extracted from various sources including electronic medical records, medication prescriptions, and procedural and imaging findings. The prevalence was 16% for hypertension, 2.5% for ischemic heart disease and 2.5% for stroke.

    A deep learning model was trained to identify features from the mammograms of women who had hypertension, ischemic heart disease or stroke. The model’s ability to distinguish between women with and without each cardiovascular condition was evaluated using areas under the receiver operating characteristic curves (AUROC), where values range from 0.5 for random guessing to 1.0 for perfect discrimination.

    The initial model performed well, yielding AUROCs of 0.79 for hypertension, 0.78 for ischemic heart disease and 0.86 for stroke. The results were consistent when considering cancer status and age.

    Doctor Copeland noted, “Because mammography is already widely used, analyzing the same images for cardiovascular information could potentially offer a scalable approach without requiring an additional imaging examination. Mammography also reaches many women in midlife, an important period for recognizing and addressing cardiovascular risk.”

    The researchers are now working to improve the model’s accuracy and reduce both false positives and false negatives. They also plan to investigate whether mammograms could help identify other cardiovascular conditions.

    Commenting on the findings, Associate Professor Elena Arbelo, Member of the ESC Communication Committee, said: “As both a cardiologist and a woman, I find this concept compelling: a mammogram may one day do more than look for breast cancer − it may also offer a window onto cardiovascular health. That matters because CVD in women is still too often recognised late. It is great to see innovative AI studies being presented at ESC Congress 2026, aiming to address unmet needs. The challenge now is to establish accuracy and reliability − to move from experimentation to clinical implementation.”

  • Hidden hormone spikes may reveal high blood pressure condition

    Hidden hormone spikes may reveal high blood pressure condition

    A common but often overlooked cause of high blood pressure may be hiding in plain sight – and data from a pioneering wearable device could hold the key to its earlier diagnosis, according to new research.

    The study, published in the journal Science Translational Medicine, concerns a condition called primary aldosteronism – a hormone disorder which affects up to one in five people with high blood pressure and puts them at higher risk of developing heart disease, stroke, diabetes, and other major health problems.

    Researchers from the University of Bristol and the University of Manchester in the UK, the University of Bergen in Norway, and partners in Stockholm and Athens found that patients with the disorder experienced bursts of hormone production during the day as well as in the night while asleep, when routine blood testing is rarely carried out.

    Thanks to an ingenious portable device, developed at the University of Bristol, the hormone levels of patients were able to be monitored round-the-clock in their homes rather than a hospital or research unit. This means hidden irregularities could be uncovered, which may normally go undetected by current testing methods, leading to earlier detection of health conditions.

    Study co-lead author Dr Thomas Upton, Clinical Research Fellow in Automated Sampling Clinical Fellow at the University of Bristol, and Senior Clinical Fellow at Bristol Hospitals NHS Foundation Trust said: “Primary aldosteronism is an important cause of high blood pressure and the most common cause of secondary hypertension we see in our blood pressure clinic. It could be affecting millions of people in the UK. However, due to the way hormones change during the day and the current complexity of the diagnostic process, diagnosis is often delayed or never made at all.

    “In our study, patients were monitored at home during normal activity, and this allowed us to see how hormones changed over time in realistic settings. This approach could potentially revolutionise how we diagnose hypertension and ultimately reduce cardiovascular disease – particularly heart disease and strokes – that could have been prevented.”

    The proof-of-concept investigation continuously monitored hormone levels every 20 minutes in 60 patients from Bristol, Bergen, Stockholm, and Athens, over a 24-hour period. The patients all wore a lightweight device – which is the size of a mobile phone and attaches at the waist – allowing hormones to be measured from the skin, while they carried out normal daily activities, including sleeping at night.

    Called U-RHYTHM, the technology was adopted and advanced by the spinout company Dynamic Therapeutics in 2023.

    Study senior author Dr Eder Zavala, UKRI Future Leader Fellow at the University of Manchester, said: “By continuously monitoring hormones over 24 hours, we were able to reveal a previously hidden pattern of nocturnal hormone bursts. This gives us a much clearer understanding of the disease and could ultimately help doctors detect it earlier and treat patients more effectively.

    “A more detailed mathematical and computational analysis of daily hormonal profiles could eventually also help uncover earlier and more subtle forms of the disease, opening new opportunities to improve outcomes for patients living with high blood pressure.”

    Computational analysis of data from the device allowed researchers to track changes in aldosterone, the hormone responsible for regulating salt and water balance in humans, along with two closely related hormones known as 18-hydroxycortisol and 18-oxocortisol.

    Existing tests may be missing patients because the study results showed aldosterone levels do not stay high all the time. Furthermore, the researchers found that even among some of the most severe cases of the disease, there were periods when hormone levels dipped below the minimum thresholds used to diagnose the condition.

    Rather than finding persistently raised hormone levels, the researchers discovered repeated night-time bursts of hormone secretion while the day-night rhythm remained intact.

    These hormone spikes, produced by the adrenal glands, were particularly prominent in patients whose disease was caused by a problem in only one adrenal gland rather than both. The abnormal hormone patterns disappeared after surgical removal of the affected adrenal gland, providing further evidence that the bursts were directly linked to the disease.

    Study co-author Prof Stafford Lightman, Professor of Medicine at the University of Bristol and inventor of the U-RHYTHM technology, added: “The findings suggest that clinicians may need to rethink how they look for the disorder which the Endocrine Society clinical practice guidelines now recommend should be considered for all people with hypertension, also known as high blood pressure.

    “Future diagnosis could move away from single time point blood tests and towards tracking the body’s hormone rhythms over time, particularly the overnight patterns that appear to hold crucial clues to disease. Further research is needed to define the best clinical pathways, using dynamic hormone measurement, to ensure early diagnosis of this common and potentially curable cause of high blood pressure.”

    The research was funded by EU Horizon 2020, the Trond Mohn Foundation, the UKRI Biotechnology and Biological Sciences Research Council (BBSRC), Medical Research Council, University Hospitals Bristol and Weston NHS Foundation, the Swedish Medical Research Council and Knut and Alice Wallenberg Foundation.

    The findings support the University of Bristol’s research ‘Grand Challenge’ focus on Understanding and Preventing Cardiovascular Disease and builds on NIHR-funded initiatives aimed at earlier identification of people with hypertension and other cardiovascular risk factors.

    Paper

    ‘Tissue corticosteroid rhythms are dysregulated predominantly during sleep in primary aldosteronism’ by M.A. Grytaas et al. in Science Translational Medicine

  • Choose Health Launches Most Comprehensive At-Home Liver Function Test

    Choose Health Launches Most Comprehensive At-Home Liver Function Test

    A bew test developed by Choose Health, an at-home blood testing company, is Comprehensive Liver Function Test, a self-collection blood test measuring 20+ liver health markers for a disease that affects roughly one third of U.S. adults but remains undiagnosed in the majority of cases.

    “Fatty liver disease is arguably the most underdiagnosed condition in America,” said Mark Holland, Founder of Choose Health. “The tragedy is that it’s largely preventable and often reversible when identified early, but without universal screening, cases slip through until the damage is done. We built this test to change that.”

    A Silent Epidemic

    Metabolic dysfunction-associated steatotic liver disease (MASLD) affects an estimated 38% of adults globally, projected to exceed 55% by 2040. In the U.S., roughly one third of adults may be affected, with only a fraction diagnosed.

    Its trajectory can often be changed: AASLD guidance indicates 3 to 5% weight loss can improve steatosis, with above 10% needed to improve steatohepatitis and fibrosis.

    What does the Choose Health Comprehensive Liver Function Test measure?

    The test measures AST, ALT, GGT, total bilirubin and albumin; fasting glucose, HbA1c, fasting insulin and HOMA-IR; LDL, HDL, triglycerides, VLDL, ApoA1 and ApoB; and iron, UIBC, ferritin and transferrin saturation, alongside calculated scores: Fatty Liver Index, Hepatic Steatosis Index and AST:ALT ratio.

    “These calculated scores are what actually matter clinically,” said Dr. Alan Farrell, MB BCh BAO MSc, Chief Medical Officer at Choose Health and preventative medicine expert. “One elevated ALT reading doesn’t say much. But when you combine multiple biomarkers into published indices like the Fatty Liver Index, patterns of steatosis and metabolic risk become much clearer.”

    Why does a liver test include metabolic and lipid markers?

    Liver enzymes alone give an incomplete picture. Glucose, HbA1c, insulin and HOMA-IR add context on insulin resistance, commonly associated with MASLD. Lipid markers characterize cardiometabolic risk, and iron markers can surface results warranting clinical follow-up. FLI and HSI combine these with personal characteristics to estimate the likelihood of hepatic steatosis.

    “We’ve been focused on liver health since 2018 because we saw this epidemic coming,” said Holland. “With the rise of GLP-1 medications and awareness of metabolic health, now is the moment for consumers to take liver health as seriously as cholesterol or blood sugar.”

    Availability

    The Comprehensive Liver Function Test is available across 48 states (excluding New York and Rhode Island). The test uses a finger-prick sample collected at home and returns physician-reviewed results in days.

    About Choose Health

    Choose Health is an Austin, Texas-based health technology company specializing in at-home blood testing for liver and metabolic health, founded in 2018. Choose Health has conducted over 200,000 tests processed through CAP-accredited and CLIA-certified laboratories, with results reviewed by licensed physicians.

  • 10X Health Expands its Flagship Genetic Test to Now Analyze 27 Genes

    10X Health Expands its Flagship Genetic Test to Now Analyze 27 Genes

    Today, 10X Health announces the relaunch of its Methylation Genetic Test (MGT) which now features the analysis of 27 genes across 6 biochemical pathways involved in the body’s methylation cycle. Previously analyzing 5 genes across 4 body systems, the relaunch of expanded MGT now addresses a full spectrum of consumer health concerns including energy, mood, sleep, heart health, hormones, bone health, detox, and oxidative stress. The test price remains at the same original cost of $599, and includes a $100 protocol credit at 10X Health.

    Through its partnership with Novogenia, a European precision genomics lab, 10X Health has expanded the Methylation Genetic Test to analyze a total of 27 genes to provide detailed insights into how to optimize an individual’s biological pathways. The expansion adds Vitamin D metabolism, glutathione detoxification, oxidative stress defense, and serotonin/neurotransmitter pathways to the original methylation panel. 10X Health is delivering five times the genetic insight for the same price. With each Methylation Genetic Test, a one-on-one wellness concierge call is scheduled with a healthcare provider who delivers an analysis of the results as well as a personalized plan and recommendations all tailored to your body’s individual genetic makeup.

    “The methylation cycle is the body’s process of converting raw materials into usable nutrients. The 10X Methylation Genetic Test provides the map of an individual’s nutrient-processing efficiency and insights into how to optimize key biological pathways,” said Kent Bradley, MD, Chief Medical Executive at 10X Health. “The one-time test provides results that have a lifetime of impact, as DNA doesn’t change. Instead of guessing which routines or supplements the body needs, we can provide targeted and personalized action to optimize health and support longevity.”

    The expanded panel includes analysis of the following pathways:

    • Folic Acid Activation (4 genes): How your body converts and activates folate — the foundation of energy production and detox
    • Homocysteine Metabolism (5 genes): Your cardiovascular and brain protection pathway — homocysteine regulation and methylation efficiency
    • Vitamin D Metabolism – New! (6 genes): How your body makes, activates, and uses Vitamin D — bone health, immune function, mood
    • Glutathione Metabolism – New! (4 genes): Your master detox pathway — how your body neutralizes toxins and environmental chemicals
    • NOS & Free Radical – New! (3 genes): Oxidative stress defense and nitric oxide production — circulation, blood pressure, cellular protection
    • Neurotransmitter Mgmt – New! (5 genes): Mood, stress, sleep, and serotonin production — the complete neurotransmitter picture

    The at-home 10X Methylation Genetic Test does not require an individual to draw blood or visit a clinic. Users of the test simply provide a saliva sample and send it back in a prepaid envelope to begin the process of generating results and customized treatment plans. The expanded Methylation Genetic Test featuring 27 genes across 6 biochemical pathways is now available at www.10xhealthsystem.com.

    About 10X Health:
    10X Health is a personalized health and performance company focused on helping individuals unlock their full potential through data-driven insights, advanced diagnostics, and targeted wellness protocols. By integrating science, technology, and lifestyle interventions, 10X Health delivers customized solutions designed to improve energy, performance, and long-term health.