<![CDATA[DSM-6 forces psychiatry to choose: sharper science or softer labels. Explore why validity, biomarkers, and hierarchy matter for credibility.]]>
Clinical application of 1H MRS in the human brain at 7T
Proton magnetic resonance spectroscopy (1H MRS) enables non-invasive biochemical sampling of tissues, potentially aiding diagnosis, prognosis and monitoring of various pathologies, while providing novel imaging biomarkers. Ultra-high-field (UHF) imaging at 7 tesla (7T) benefits from improved spectral dispersion due to an increase in chemical shift differences between metabolites, and a higher signal-to-noise ratio (SNR), making 1H MRS at 7T a particularly promising diagnostic tool for identifying and separating metabolites not clearly resolved at lower field strengths. However, 1H MRS at UHF presents technical challenges related to the short RF wavelength at 7T, resulting in B1 transmit field inhomogeneity, and the increased magnetic susceptibility gradients leading to B0 field inhomogeneity. Appropriate MRS methods are required to address these issues. In this article, we describe the technical aspects and challenges of 1H MRS at 7T, based on the experience in our centre, where single voxel 1H MRS has featured prominently in clinical 7T research applications for several years. We present data from six patients with glial tumours, including three who were post-operative, in whom post-surgical metalware affects the specific absorption rate (SAR), along with two patients with neuroinflammatory conditions and two with neurodegenerative diseases. The potential clinical use of 1H MRS for these pathologies and its possible integration as a promising biomarker into advanced imaging pathways are discussed.
First Atlas of Female Reproductive System Maps Uncharted Menopause Biology
The first large-scale study across all major female reproductive organs has uncovered how aging processes impact each organ and tissue in unique ways. Published today in Nature Aging, the study has identified novel blood biomarkers that could help physicians anticipate health risks associated with menopause, such as pelvic floor prolapse.
“Until now, we tended to consider menopause mainly as the end of the ovary’s reproductive function,” says Marta Melé, PhD, leader of the transcriptomics and functional genomics group at the Barcelona Supercomputing Center (BSC) and director of the study. “However, our results show that it acts as a turning point that profoundly reorganizes other organs and tissues of the reproductive system, and allow us to identify the genes and molecular processes that could be behind these changes.”
Menopause is a complex biological process with significant implications for overall health, which is estimated to be actively affecting 6% of the world’s population at any given time. However, the cellular and molecular processes driving it across reproductive organs and tissues have historically remained understudied.
To map the complex biology of menopause, Melé’s team analyzed 1,112 tissue images and 659 RNA sequencing samples from 304 women between the ages of 20 and 70. This allowed the researchers to reconstruct aging trajectories of the uterus, ovary, vagina, cervix, breast, and Fallopian tubes. Using deep learning algorithms, they were able to identify key changes associated with aging in each organ, both at the molecular and tissue levels.
Results showed that not all organs age uniformly across the female reproductive system. For instance, the ovary and vagina were shown to age gradually in a process starting years before menopause. Meanwhile, the uterus undergoes a very abrupt transition during menopause.
Even within the same organ, different tissues were shown to age in distinct ways. In particular, the muscle tissue of the uterine wall and the vaginal epithelium were observed to be the most affected during menopause, undergoing sharp changes.
The study also analyzed blood plasma samples from 21,441 women, which led to the identification of molecular signals of aging that can be detected in the blood. These biomarkers could offer non-invasive monitoring of female reproductive organs during menopause and enable more accessible, less invasive follow-up tests for women at risk of complications associated with menopause, such as pelvic floor prolapse.
“We not only identified the molecular changes underlying the aging of these organs, but we also saw that they can be detected in blood, which opens the door to new clinical tools,” says Oleksandra Soldatkina, PhD, lead author of the study and researcher at BSC.
This study marks a step toward better understanding a key biological process that has historically been left behind, leading to better prevention, diagnosis and treatment of multiple diseases linked to menopause. The researchers highlighted that their findings “position menopause as a key inflection point in female aging and provide insights with tissue-specific focus to support healthier menopausal transitions and reduce age-related disease risk.”
The post First Atlas of Female Reproductive System Maps Uncharted Menopause Biology appeared first on Inside Precision Medicine.
Plasma Biomarker Patterns Distinguish Early-Onset Dementia
Plasma biomarker levels change in differing ways for different types of early-onset dementia, with unique clinical associations that could help stratify risk in patients, research suggests.
The findings may help improve detection and prognosis of these neurodegenerative diseases, which manifest before the age of 65 years and are often challenging to treat due to atypical symptoms and clinical heterogeneity.
The report, in JAMA Network Open, revealed differences in both the concentrations of biomarkers over time and their association with clinical outcomes in early-onset Alzheimer disease (EOAD) and frontotemporal dementia (FTD).
“Our results highlight disease-specific plasma biomarker dynamics and their potential utility in monitoring disease progression in early-onset dementia,” reported Eun-Joo Kim, PhD, from Pusan National University Hospital in Korea, and colleagues.
Recent developments with plasma biomarkers have changed the landscape of dementia diagnosis.
Phosphorylated tau 217 (p-tau217), a marker specific of Alzheimer’s disease, has been found to be highly accurate in detecting its pathology.
Meanwhile, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are emerging as astrocytic activation and neurodegeneration markers, respectively, with NfL particularly relevant for FTD.
Combining p-tau217 and NfL could therefore enable Alzheimer’s disease and FTD, two leading causes of dementia at an early age, to be distinguished.
To investigate further, Kim and team compared biomarker trajectories and clinical outcomes in 322 patients with EOAD and FTD, of whom 245 had EOAD and 77 FTD.
Around two thirds of each group was female, and the mean age was in the early to mid 60s.
High baseline levels of p-tau217, GFAP, and NfL were significantly associated with all clinical outcomes in the EOAD group, assessed using scores on the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating–Sum of Boxes (CDR-SB).
However, among patients with FTD, only baseline GFAP and NfL were associated with decreases in MMSE scores.
The association of p-tau217 and GFAP levels with clinical outcomes was greater at earlier stages of EOAD, with the former biomarker showing no association at later stages of disease.
The plasma biomarkers followed distinct longitudinal trajectories in the two forms of early-onset dementia. In the EOAD group, the levels of all three biomarkers increased significantly over time, but with FTD only NfL increased.
Annualized changes in levels of all three biomarkers showed outcome-specific associations with clinical decline in EOAD. GFAP and NfL changes were associated with declines in MMSE score and p-tau217 levels with worsening CDR-SB score in this group. No such associations were observed for patients with FTD.
“In this multicenter, prospective cohort study of patients with EOAD and FTD, the clinical relevance of plasma biomarker levels and longitudinal changes may vary between EOAD and FTD,” the authors summarized.
“These findings may inform future clinical practice and trial design regarding stratifying patient populations and monitoring clinical progression, particularly in EOAD.”
The post Plasma Biomarker Patterns Distinguish Early-Onset Dementia appeared first on Inside Precision Medicine.
<![CDATA[New US patent backs Denovo’s ANK3 biomarker guiding DB104 for treatment‑resistant depression, highlighting promising efficacy in selected patients.]]>
Autonomic-vascular dysregulation in CKD-associated hypertension: a narrative review with evidence hierarchy
Hypertension and chronic kidney disease frequently coexist and mutually accelerate cardiovascular and renal injury. This narrative review prioritizes direct human autonomic phenotyping (Level 1: microneurography, HRV/BRS), human vascular correlates (Level 2: PWV, FMD), and complementary preclinical evidence (Level 3) to elucidate autonomic-vascular mechanisms. Autonomic imbalance, characterized by sympathetic overactivity and reduced parasympathetic restraint, represents a key interface between neural control and vascular pathology in this setting. This narrative review synthesizes experimental and clinical evidence on how the autonomic nervous system shapes vascular function in hypertension and CKD. We outline physiological autonomic control of vascular tone (baroreflex pathways, central networks, brain–kidney communication), characteristic autonomic alterations in hypertension (elevated MSNA, impaired HRV/BRS), and their vascular consequences (endothelial dysfunction, arterial stiffness). We emphasize CKD-specific autonomic drivers (renal afferents, uremic toxins, inflammation) and their translation to exaggerated vascular injury and adverse BP phenotypes. Finally, we discuss pharmacological/device-based strategies targeting autonomic–vascular pathways, highlighting opportunities for neuromodulation, biomarker-guided risk stratification, and individualized treatment. By integrating multidisciplinary evidence, this review frames CKD hypertension as amplified autonomic–vascular injury and positions the autonomic nervous system as a promising therapeutic target.
Serum cystatin C levels are independently correlated with cognitive impairment in individuals with cerebral small vessel disease
Background and purposePrevious studies have shown that serum cystatin C (CysC) is associated with cerebral small vessel disease (CSVD) and that elevated CysC levels are linked to an increased risk of cognitive impairment in the elderly. However, whether CysC is specifically associated with cognitive impairment in patients with CSVD remains unclear.MethodA total of 334 CSVD patients with available demographic, blood biomarker, and brain imaging data were included. Patients were divided into vascular cognitive impairment and normal cognition groups. Univariate analysis was used to compare baseline data, blood biomarkers, imaging features, and behavioral scores between the two groups. Binary logistic regression was used to evaluate the diagnostic value of cystatin C for CSVD-related cognitive impairment.ResultsCompared with the normal cognition group, the VCI group exhibited significantly elevated serum levels of CysC, homocysteine, urea nitrogen, creatinine, uric acid, fibrinogen, and D-dimer, along with a lower red blood cell count. The VCI group also showed a higher prevalence of severe periventricular white matter hyperintensity, severe deep white matter hyperintensity, severe total white matter hyperintensity, and brain atrophy. The combination of these eight blood biomarkers markedly improved the diagnostic performance for VCI (AUC = 0.672, 95% CI: 0.615–0.730, p < 0.001). Multivariate analysis revealed that elevated CysC levels (OR = 2.677, p = 0.041), age (OR = 1.067, p < 0.001), and severe total WMH (OR = 2.713, p < 0.001) were associated with CSVD-related cognitive impairment. After adjusting for confounding variables, serum CysC levels remained independently correlated with cognitive impairment (OR = 3.257, 95% CI: 1.192–8.899, p = 0.021).ConclusionSerum CysC levels are independently associated with cognitive impairment in CSVD patients.
Acupoint temperature as a biomarker: infrared thermography in the diagnosis of adolescents with major depressive disorder
BackgroundThe prevalence of adolescent major depressive disorder (MDD) is rising; however, diagnosis relies on subjective measures due to a lack of objective biomarkers. This study explored infrared thermography (IRT) as a non-invasive tool to quantify thermal radiation characteristics of acupoints in adolescents with MDD. The objective was to establish diagnostic models based on acupoint temperature-derived biomarkers.MethodsA prospective, multi-center observational study enrolled 108 participants (65 adolescents with MDD and 43 healthy controls [HCs]). We first examined correlations between acupoint temperatures and depression severity using Pearson analysis. Multiple linear and binary logistic regression models were developed to diagnose MDD and assess severity. The diagnostic model for MDD was visualized as a nomogram and validated using Receiver Operating Characteristic (ROC) curves, Hosmer-Lemeshow tests, calibration plots, and decision curve analysis (DCA). Internal validation was performed using the bootstrap method.ResultsAmong 27 acupoints analyzed, adolescents with MDD exhibited altered acupoint temperatures at Taiyang (EX-HN5), Quchi (LI11), Yanggu (SI5), and Waiqiu (GB36). Subsequent Pearson correlation analysis revealed negative correlations between the infrared relative temperatures of Taiyang (EX-HN5), Quchi (LI11), and Waiqiu (GB36) and depression severity (P = 0.001, r = -0.319; P = 0.022, r = -0.229; P = 0.001, r = -0.325) and a weak positive correlation between the infrared relative temperature of Yanggu (SI5) and depression severity (P = 0.043, r = 0.202). Building on these findings, two diagnostic models were developed: a linear regression model for depression severity of adolescents (Y = 52.25-9.52*TEX-HN5-13.07*TGB36) and a logistic regression model for adolescents with MDD diagnosis (P = ex/(1+ex), x = 0.22-1.14*TEX-HN5+0.45*TSI5-2.19*TGB36). The nomogram-based model demonstrated good calibration (Hosmer-Lemeshow P = 0.855), discrimination (AUC = 0.785, 95%CI: 0.693 – 0.876), and clinical utility. Internal validation using the bootstrap method produced a C-index of 0.752 (95% CI: 0.617 – 0.877), further confirming the model’s robustness.ConclusionsIn conclusion, acupoint temperature-based models show promising efficacy for the objective and non-invasive diagnosis and severity quantification of adolescents with MDD, offering valuable tools for early clinical intervention. Future studies should validate these findings across diverse populations and integrate multi-modal biomarkers to enhance diagnostic precision.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT06750640.
Predicting referral need for febrile children in low-resource community settings in South and Southeast Asia
Nature Medicine, Published online: 29 April 2026; doi:10.1038/s41591-026-04338-1
A multicountry cohort study found that prediction models combining clinical parameters with either pulse oximetry or the host biomarker sTREM1 more accurately identified febrile children needing referral than standard WHO criteria.
Multi-Cancer Early Detection Goes Global and Gets Personal
The video starts simply: a couple at home, music playing, dogs in the background. Allison Barry smiles as she talks about the rhythms of her life with her husband Chris, how they’ve built a life together that’s carefully planned, structured, and anchored around work and the future. Vacations could be put off. Retirement would be the time to explore.
Barry loved her job. As senior director of portfolio communications at Exact Sciences, she was deeply involved with the launch of Cancerguard, a new multi-cancer early detection (MCED) test. The day that Cancerguard became available, September 10, 2025, would be a day to remember. “We were in New York at the New York Stock Exchange, and [the announcement of Cancerguard] was on the big billboard,” said Barry in the video released by Exact Sciences a month ago. “It was one of the proudest moments of my entire life.”
But that wasn’t the only notable event of the day. Barry did one other thing—she ordered the Cancerguard test, expecting a negative result. Then the tone in the video shifts. Barry’s test was positive. “She was the very first positive result,” Tom Beer, MD, then chief medical officer (CMO) at Exact Sciences, told me as we watched the video about Barry’s experience with Cancerguard. “She literally ordered it the first day.”
What follows is a blur of scans, fear, and uncertainty until doctors find a tumor the size of a football (22 cm). The diagnosis: stage-one mucinous ovarian cancer, a disease that is almost always caught too late. Surgery follows. The outcome is positive. That all happened in the span of six months. Today, Barry is cancer-free.
A test for unscreened cancers
Beer and the team at Exact Sciences have spent years designing Cancerguard, named in the same vein as the company’s flagship product Cologuard, to identify cancers that currently lack effective screening options and to catch them earlier, when treatment is more likely to succeed.
Cancerguard is a multi-biomarker MCED classifier that combines two types of biological signals: cell-free DNA (cfDNA) methylation and protein biomarkers. Each is analyzed separately, then integrated into a single result. If either signal is positive, the test flags a potential cancer. “They’re complementary sources of information,” Beer explained.
Beer’s colleague Frank Dielh, PhD, presented new data during the AACR 2026 conference showing that the multi-biomarker MCED approach used in the Cancerguard test improves cancer detection across stages by combining these two signals, with each set of biomarkers contributing independently to overall performance.
The prospective case-control study of 3,163 participants showed detection was driven by cfDNA methylation alone in 47.1% of cases, protein alone in 7.4%, and both in 45.5%, with no false positives showing both markers, underscoring the value of a multi-signal approach for earlier and broader detection.
But what’s most valuable, according to Beer, is the stages that the combined scores provide. Across a broad range of cancers, sensitivity increases from about 24% in stage one to 90% in stage four. While those early-stage numbers may seem modest at first glance, Beer emphasized the context. “We’ve been really focused on early-stage sensitivity as our North Star,” said Beer. “We’re screening for cancers that currently have zero effective screening. So, even incremental sensitivity is meaningful.”
By layering different biological signals, the test builds a more complete picture: one that is particularly valuable when tumors are small and harder to detect.
Going global and human impact
In November 2025, a couple months after Cancerguard launched, Exact Sciences made a deal to be acquired by Abbott, a major bet for the medical device and healthcare company on cancer diagnostics. While the technology for Cologuard and Cancerguard was already in development at Exact, the scale of deployment changes dramatically with access to a global healthcare network. “Abbott has a truly global presence,” Beer said. “Relationships with health systems and governments around the world. That changes how we think about opportunity.” An ongoing study in Japan reflects that shift.
On December 11, 2025, Exact Sciences launched the CRANE (Cancer Recognition and Assessment through Non-invasive Evaluation) Study in Japan—a large, multi-center trial enrolling about 2,000 participants—to evaluate the sensitivity and specificity of Cancerguard test across different cancer types and stages. “If you’re going to build something for global use, you need to understand how it behaves globally,” he said. “Geography and ethnicity could influence performance.”
Designing a cancer screening test isn’t just about detecting as many cases as possible. It’s about balance, particularly between sensitivity and specificity. Internally, Beer explains, the team models outcomes in terms of life-years gained versus the risks and costs of false positives. These trade-offs determine where thresholds are set within the algorithm. “We’re not just picking a random cutoff,” he said. “We’re thinking deeply about how to deliver the greatest public health impact.”
These internal models, though not publicly shared, guide every stage of development. The goal is not just accuracy but meaningful outcomes, catching cancers early without overwhelming patients and healthcare systems with unnecessary follow-ups.
For all the technical detail, our conversation keeps returning to people. Beer recalls another friend who retired at 65, only to be diagnosed with advanced pancreatic cancer six months later. He didn’t survive.
Placed alongside Barry’s story, the contrast is stark. One life was altered by early detection; the other never got the chance to do anything about it. What makes Barry’s story powerful is not just its outcome but also its implication, which is that cases of cancer can be caught early enough to change everything. The ultimate goal for Beer is to make such stories routine.
The post Multi-Cancer Early Detection Goes Global and Gets Personal appeared first on Inside Precision Medicine.