BackgroundGastrointestinal adverse events (GI AEs) are the main dose-limiting side effects of metformin in type 2 diabetes mellitus (T2DM), reducing adherence and compromising long-term glycaemic control. Current strategies (dose adjustment or combination therapy) seldom address both tolerability and sustained metabolic efficacy. Transcutaneous auricular vagus nerve stimulation (taVNS) is a non-invasive neuromodulation technique that may modulate gut–brain–metabolic pathways—vagal reflexes, inflammation, intestinal barrier function, and enteroendocrine signaling—and thus improve drug tolerance while preserving glycaemic control.MethodsThis single-center, randomized, sham-controlled pilot trial will enroll 60 T2DM patients with metformin-associated GI AEs, randomized 1:1 to either the taVNS group or the sham control group. The intervention lasts 2 weeks with a follow-up at week 4. Assessments at baseline and follow-up include a validated Metformin Symptom Severity Score (total score 0–50; primary outcome), Bristol Stool Form Scale, bowel urgency, glycaemic/metabolic indices [fasting blood glucose (FBG), 2-h postprandial glucose (PG2h), glycated albumin (GA), fasting C-peptide, fasting insulin, HOMA-IR, ISI], and mechanistic biomarkers (GLP-1, 5-HT, IL-6, IL-10, TNF-α, D-lactate, DAO, bile acids). Safety monitoring includes routine hematology, liver and renal function tests.DiscussionBy combining clinical outcomes with targeted biomarker analyses in a randomized design, this pilot study will assess whether taVNS alleviates metformin-associated GI intolerance without impairing glycaemic efficacy, and will provide feasibility data, effect-size estimates, and biomarker selection for future confirmatory trials.Clinical trial registrationTrial registration International Traditional Medicine Clinical Trial Registry (ITMCTR) http://itmctr.ccebtcm.org.cn/, Identifier: ITMCTR2025001086.
Diffusion tensor imaging-functional MRI fusion reveals disrupted white matter structure–function coupling in HIV-associated asymptomatic neurocognitive impairment
ObjectiveConventionally, blood oxygen level-dependent (BOLD) signals derived from resting-state functional magnetic resonance imaging (rs-fMRI) are attributed to gray matter, but recent evidence confirms stable low-frequency oscillations within white matter. While structure–function coupling is pivotal in neuropsychiatry, it remains underexplored in HIV-associated neurocognitive disorders (HAND). Focusing on Asymptomatic Neurocognitive Impairment (ANI), the earliest stage of HAND, this study establishes a white matter skeleton-based fusion framework integrating diffusion tensor imaging (DTI) and rs-fMRI to investigate underlying mechanisms.MethodsWe enrolled 47 patients with ANI and 48 matched healthy controls. Fractional anisotropy (FA) images from DTI and BOLD signals derived from rs-fMRI were projected onto a unified white matter skeleton to achieve structure–function spatial alignment. FA, skeleton-based white matter amplitude of low-frequency fluctuations (SWALFF), and its dynamic variability (dSWALFF) were calculated. Group differences in white matter structure and function were assessed, with structure–function coupling examined in regions showing overlapping FA-SWALFF and FA-dSWALFF alterations. Additionally, a novel White Matter Dys-coupling Index (WDI) was proposed to quantify the deviation between structural integrity and functional activity and evaluate its clinical relevance.ResultsCompared to controls, ANI patients exhibited widespread FA reductions and increased mean diffusivity (MD) and radial diffusivity (RD), indicating diffuse demyelination. Functionally, a spatial dissociation emerged: SWALFF was reduced in posterior occipital pathways (left vertical occipital fasciculus, forceps major), whereas SWALFF and dSWALFF were elevated in prefrontal pathways (forceps minor). Overlapping regions revealed complex coupling patterns, ranging from concordant decline to compensatory upregulation and decoupling. The interaction between FA and dSWALFF further highlighted instability in dynamic regulation. The WDI was significantly correlated with infection duration, immune status, and cognitive domain scores.ConclusionThis study identifies a characteristic “coupling imbalance” in the white matter of ANI patients, defined by the coexistence of structural degeneration and functional reorganization. We propose the WDI as a quantitative metric for this deviation. Its significant associations with clinical and cognitive metrics suggest its potential as a neuroimaging biomarker for the early identification and mechanistic understanding of HAND.
DNA Tests to Predict GLP-1 Drug Response to Launch in 2026
PrecisionLife and Ovation.io have signed a commercialization agreement to bring GLP-1 response genetic tests to the market. Today, the partners announced plans to launch both direct-to-consumer and laboratory developed tests later this year.
The companies had entered a collaboration at the end of last year, leveraging Ovation’s multi-omics and longitudinal clinical data and PrecisionLife’s advanced analytics platform to uncover genetic mechanisms of response to GLP-1 medication. Earlier this year, they reported the identification of a series of biomarker signatures that can quantitatively predict which patients are most likely to respond to GLP-1 therapies and sustain that response over time.
The partners are now actively working on translating this discovery into noninvasive genetic tests for patients to make informed decisions about the likely risks and benefits of these increasingly popular drugs, as well as for drug developers to stratify patients in clinical trials.
“Our teams have generated the world’s most detailed insights into why patients respond differently to these medicines,” said Steve Gardner, chief executive officer of PrecisionLife. “We will make these insights clinically actionable via noninvasive DNA tests supported by our results reporting platform and CLIA lab partners.”
PrecisionLife stressed that their findings go beyond the GLP-1 genetic predictors reported last week by 23andMe. “While that study highlighted a handful of variants associated with modest differences in outcomes, this work identifies combinatorial biomarker signatures that stratify patients and quantitatively predict response—and is already being translated into tests designed for use in real treatment decisions,” a company representative told Inside Precision Medicine.
Over the course of the next six months, PrecisionLife will reproduce, refine, and validate their findings using additional datasets provided by Ovation, including studies to confirm the predicted response to GLP-1 drugs including semaglutide and tirzepatide in a real-world context.
The launch of a consumer DNA test is expected to enable patients to understand their individual safety, efficacy, and tolerability profile for GLP-1 drugs before starting treatment. This could also offer providers a clearer basis for selecting therapies and help payors make more sustainable coverage decisions. The collaborators have stated they will evaluate the opportunity of using these tests to inform reimbursement decisions and expand coverage of certain health plans based on an individual’s predicted response.
For drug developers, laboratory developed tests (LDT) could open up opportunities for more precise patient stratification, improving the probability of success in clinical trials evaluating the expansion of GLP-1 drugs into new indications. The companies are currently in discussions with various stakeholders and sponsors to deploy the LDTs as stratification tools in a clinical setting.
“We’re confident that together we can translate those insights into commercial outcomes and products in GLP-1s and other diseases with huge clinical impact,” said Curt Medeiros, chief executive officer of Ovation.io.
Going forward, the partners will continue to validate their findings and expand the scope of the studies, including identifying additional markers of safety and tolerability to GLP-1 drugs as well as pinpointing further efficacy and safety signals for individual molecules.
The post DNA Tests to Predict GLP-1 Drug Response to Launch in 2026 appeared first on Inside Precision Medicine.
An acetylated Tau-174 CSF biomarker discriminates between TDP-43 and tau pathology in patients with frontotemporal lobar degeneration
Nature Medicine, Published online: 15 April 2026; doi:10.1038/s41591-026-04341-6
A new cerebrospinal fluid biomarker, AcTau174, was elevated in frontotemporal lobar degeneration with TAR DNA-binding protein (FTLD-TDP), distinguishing this pathology from FTLD-Tau, and was associated with disease severity and progression in FTLD-TDP.
Early Brainwave Biomarkers for Personalized Neuromodulation in Treatment-resistant Depression
Conditions: Major Depressive Disorder; Treatment Resistant Depression
Interventions: Device: Personalized iTBS; Device: Non-Personalized iTBS; Device: Sham iTBS
Sponsors: Stanford University; National Institute of Mental Health (NIMH)
Not yet recruiting
Interventions: Device: Personalized iTBS; Device: Non-Personalized iTBS; Device: Sham iTBS
Sponsors: Stanford University; National Institute of Mental Health (NIMH)
Not yet recruiting
Retrospective longitudinal analysis of blood microRNA-7-5p as a possible progression biomarker in people with Parkinson’s disease
BackgroundMicroRNA-7-5p (miR-7-5p) may play a neuroprotective role in people with Parkinson’s disease (PwP), as it has been found to regulate α-synuclein (α-syn) and the NLRP3 inflammasome in animal models of Parkinson’s disease (PD).ObjectiveThe study aimed to investigate the use of miR-7-5p as a potential biomarker for disease progression in PwP by correlating it with time, clinical measures, and neurofilament light chain (NfL).MethodsWe performed a longitudinal retrospective analysis of blood miR-7-5p levels in 303 de novo PwP and 159 healthy controls (HCs) from the Parkinson’s Progression Markers Initiative (PPMI) cohort. In PwP, a linear mixed-effects model was used to examine the association between miR-7-5p levels and time in the study. In addition, linear mixed-effects models were used to examine the associations between longitudinal changes in miR-7-5p and scores on the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), both for motor and total scores, as well as serum NfL levels. These models were also used to compare the associations between changes in miR-7-5p, time in the study, and NfL levels in both PwP and HCs.ResultsmiR-7-5p levels decreased more rapidly in PwP compared to HCs (p = 0.02). In PwP, miR-7-5p levels correlated with time in the study (p < 0.001) and with changes in the MDS-UPDRS motor (p = 0.007) and total scores (p = 0.01). However, when time in study was taken into account, the correlations were no longer significant. Additionally, miR-7-5p levels decreased longitudinally as NfL levels increased in PwP (p = 0.03), but this did not remain significant when time in the study was considered.ConclusionThis pattern suggests that miR-7-5p may reflect both upstream pathogenic mechanisms and downstream neuroaxonal damage. However, the loss of significance when time in the study was included in the model indicates that the changes may reflect parallel degenerative processes involving NfL and miR-7-5p. This study is novel in that it demonstrates a correlation between miR-7-5p levels, clinical severity, and NfL levels.
Prediction of Relapse Using Digital Technology in People in Recovery From Substance Use Disorders: Early Economic Evaluation With a Case Study of the Subreal App
Background: Many people relapse after achieving abstinence in substance use disorders. Health care providers may scan the horizon for new technologies to predict response that allow interventions to be targeted rather than routine. Currently, no such predictive technologies are available in the United Kingdom. The Subreal app is available for use in research contexts, but no clinical data specific to the app are yet available. Early health economic modeling can use data from the literature to explore characteristics essential for the new technology to be cost-effective. This information can guide developers in setting performance targets and pricing and estimating potential cost savings and/or cost-effectiveness for health care providers. Objective: This study was supported by a UK industry funding body to explore the potential of digital technologies such as the Subreal app to offer cost savings or cost-effectiveness for health care providers. We explored the threshold price and clinical effectiveness required to deliver cost savings and cost-effectiveness in 2 subpopulations with substance use disorders in a UK setting. Methods: Deterministic models were used to estimate costs per relapse and quality-adjusted life years over 1-, 5-, and 20-year time horizons for people who have achieved abstinence after treatment for alcohol or opioid misuse. The intervention was a digital technology predicting relapse, provided—in addition to standard care—for 1 year post achievement of abstinence. In Subreal, biomarker data are collected daily through the app, and artificial intelligence–enhanced risk assessment flags patients who require additional support. The comparator was event-driven, reactive response to relapse. Costs and quality-of-life estimates were calculated using Markov models with data from existing published sources. The base-case estimate of 15% reduction in first-year relapse rates was based on a previous study on a similar but simpler digital technology. Results: Digital technologies such as the Subreal app have the potential to be cost-saving from a UK health and social care perspective, especially when used over a longer time horizon. Assuming a reduction of 15% in first-year relapse rates, digital technologies have the potential to be cost-saving, provided that they do not cost more than £300 (US $400.09) and £460 (US $613.47) per patient per annum for alcohol and opioid use disorders, respectively. No cost was included for postalert care, as it was assumed that this could be met within existing resources. Cost savings would be achieved predominantly through a reduction in treatment requirements as fewer people relapse. Price thresholds would reduce correspondingly if a <15% reduction in relapse rates were achieved. Conclusions: Developers of digital technologies that aim to reduce relapse need to focus on the generation of evidence of clinical effectiveness and develop a commercially sustainable pricing model that allows health care providers to benefit from cost savings.
Blood Biomarker Can Predict Signs of Alzheimer’s Before PET Scans
A blood test that measures plasma phosphorylated tau 217 is capable of predicting future Alzheimer’s disease onset in cognitively normal older adults even when positron emission tomography scans do not show amyloid or tau build up in the brain.
“We used to think that positron emission tomography (PET) scan detection was the earliest sign of Alzheimer’s disease progression, revealing amyloid accumulation in the brain 10 to 20 years before symptoms appear,” said lead author Hyun-Sik Yang, MD, a neurologist with Mass General Brigham Neuroscience Institute, in a press statement.
“But now we are seeing that phosphorylated tau 217 (pTau217) can be detected years earlier, well before clear abnormalities appear on amyloid PET scans.”
In 2025, the FDA approved two blood tests for Alzheimer’s disease, one that compares the ratio of pTau217 to beta amyloid developed by Fujirebio and a pTau181 plasma test developed by Roche. However, both of these tests are only indicated for people who already have some symptoms of the condition.
The current study, published in Nature Communications, aimed to test whether pTau217 in the blood can forecast beta‑amyloid and tau build‑up in the brain before individuals become amyloid‑positive on PET scans.
Overall, 317 older adults, aged 72 years on average, from the Harvard Aging Brain Study were included in the study. About 60% were women. There were no signs of cognitive decline on enrollment, and the group had a high education level. The researchers followed up 245 people in the group with repeat amyloid scans for about six years on average.
The test was able to pick up cases where beta amyloid was visible on brain scans with a high level of accuracy. The study also showed that higher starting pTau217 levels predicted faster amyloid build‑up over time, even after accounting for age, sex, and APOE status
Centiloid units are the standard scale for amyloid on brain scans with 100 centiloids typical of full-blown disease. The team found that the test could also predict future amyloid buildup even if no signs could be seen on initial PET scans. Each one‑percentage‑point increase in pTau217 at baseline was linked to an extra 0.35 centiloid units of amyloid buildup per year. Notably, those with low pTau217 levels on enrollment were still amyloid negative on scans years later.
“What stood out in our study is that even when amyloid scans appear normal in the clinic, the pTau217 biomarker can identify individuals who later become amyloid-positive,” said Yang. “It also shows that those with low pTau217 levels are likely to stay amyloid-negative for several years.”
The post Blood Biomarker Can Predict Signs of Alzheimer’s Before PET Scans appeared first on Inside Precision Medicine.
<![CDATA[Blood-based biomarkers for Alzheimer disease continue to improve, shares expert researcher. ]]>