High altitude exposes the brain to heterogeneous hypoxic, hemodynamic, rheological, inflammatory, and healthcare-access conditions. This heterogeneity makes altitude biologically informative for stroke research, but it does not justify treating natural altitude exposure as a single protective or harmful state. In this structured narrative review, we searched and organized the literature to ask which altitude-associated hypoxic cues resemble or reveal mechanisms compatible with cerebral ischemic tolerance, and what level of evidence supports that claim. We separate long-term adaptation, short-term acclimatization, chronic or excessive environmental hypoxia, and experimental hypoxic conditioning; define direct, supportive, and indirect evidence tiers; and integrate neurovascular-unit biology with multi-omics and stroke pathophysiology. Experimental hypoxic preconditioning remains the clearest direct evidence that a defined sublethal hypoxic stimulus can induce a time-limited tolerant state. In contrast, human high-altitude epidemiology, physiology, and genetics mainly constrain the clinical context and nominate candidate pathways rather than prove stroke-specific protection. We also emphasize that chronic hypoxia can be maladaptive through endothelial dysfunction, oxidative stress, erythrocytosis, thrombogenicity, blood–brain barrier impairment, and microvascular injury. Across neurovascular-unit cell types, a transparent evidence-weighting framework prioritizes endothelial biology because of its direct connection to BBB stability, effective reperfusion, hemorrhagic transformation risk, and no-reflow, while neurons, astrocytes, microglia, oligodendrocyte-lineage cells, and pericytes require different degrees of causal and human validation. We argue that the most productive path forward is not to label altitude as protective, but to use altitude-related biology to prioritize testable, stroke-facing hypotheses regarding BBB stability, microvascular patency, metabolic support, inflammatory thresholds, white-matter resilience, and biomarker-defined conditioning windows.
Immune aging biomarkers for clinical trials
Nature Medicine, Published online: 03 July 2026; doi:10.1038/s41591-026-04493-5
The authors present a framework for the selection of immune aging biomarkers suitable for clinical trials in geroscience, alongside a translational roadmap for biomarker development to support the next generation of clinical studies on immune aging.
Blood circRNAs Can Predict Alzheimer’s Years Prior to Symptoms Onset
A set of blood-based circular RNAs (circRNAs) could change how we diagnose and monitor Alzheimer’s disease, providing a simple, noninvasive test that can detect the disease with remarkable accuracy and predict its progression years before symptoms appear.
Washington University School of Medicine researchers analyzed blood samples from 1,221 individuals, including people with Alzheimer’s disease and cognitively healthy participants, making it one of the largest investigations of blood circRNAs in Alzheimer’s to date. The findings, published in a Nature Medicine study, identified 34 circRNAs whose combined expression patterns accurately distinguished Alzheimer’s disease from healthy aging.
Unlike conventional RNA molecules, circRNAs form single-stranded closed loops that resist degradation and are abundant in the brain. Their stability and ability to cross the blood-brain barrier make them attractive candidates for blood-based biomarkers that reflect changes occurring in the brain.
The research indicated that a predictive model built from the 34 circRNAs achieved an area under the curve (AUC) of 0.945 for identifying biomarker-confirmed Alzheimer’s disease, outperforming the widely used plasma biomarker pTau217 (AUC 0.877). When circRNA measurements were combined with pTau217, diagnostic performance increased further to an AUC of 0.977.
Beyond diagnosis, the circRNA signature demonstrated exceptional ability to predict disease progression. Individuals with elevated circRNA scores were nearly three times more likely to progress to symptomatic Alzheimer’s disease than those with lower scores. The model also outperformed pTau217 in forecasting progression and remained highly specific for Alzheimer’s, showing limited predictive ability for other neurodegenerative disorders such as Parkinson’s disease, frontotemporal dementia, and dementia with Lewy bodies.
Importantly, the findings were independently replicated in two additional cohorts, including 551 participants from the Knight Alzheimer’s Disease Research Center and 1,767 participants enrolled in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) study. This independent validation demonstrates that the circRNA signature is robust across multiple populations and study designs.
The researchers also found evidence that circRNA changes begin approximately two to four years before the onset of clinical symptoms, suggesting that these molecules may capture biological processes closely linked to the transition from silent pathology to cognitive decline. Such biomarkers could become increasingly valuable as disease-modifying therapies enter clinical practice, where monitoring ongoing neurodegeneration is just as important as detecting amyloid pathology.
The work builds on intellectual property protected by patent PCT/US2026/017857, “Blood Circular RNA as a Noninvasive Biomarker of Alzheimer’s Disease,” which Circular Genomics has licensed. The company, based in San Diego, California, is developing next-generation molecular blood biomarker diagnostics for precision neurology. The patent covers the use of blood circRNA signatures for the diagnosis and monitoring of Alzheimer’s disease and supports continued development of clinically deployable blood tests.
While the authors emphasize that larger prospective studies are still needed before widespread clinical implementation, the findings position blood circRNAs as a promising new class of biomarkers for Alzheimer’s disease. By combining high diagnostic accuracy with strong prediction of disease progression using a simple blood sample, circRNA-based testing could help identify patients earlier, improve clinical trial enrollment, and provide physicians with new tools to monitor disease over time.
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Personalized Therapy Could Overcome Resistance in Metastatic Melanoma
Researchers at the University of Texas MD Anderson Cancer Center have identified a strategy to reverse resistance to standard treatment in BRAF-mutant advanced melanoma. Their findings, published today in Nature Communications, support using a biomarker-guided approach to improve outcomes for patients with treatment-resistant melanoma.
“Patients whose melanoma has stopped responding to standard therapies currently have very few effective treatment options,” said Vashisht Gopal Yennu Nanda, PhD, associate professor of melanoma medical oncology and translational molecular pathology at UT MD Anderson. “Our findings could help address this critical need for these patients by guiding clinicians toward combinations tailored to each individual’s tumors.”
About 50% of melanoma tumors carry BRAF mutations that drive uncontrolled tumor growth. Although the standard of care, consisting of a combination of BRAF and MEK inhibitors, is initially effective in most patients, about 80% will develop resistance within two years. In many cancers, but especially in melanoma, acquired resistance is often driven by the tumor increasing production of proteins from the BCL2 family, which block apoptosis and support the survival of cancer cells.
Yennu Nanda and colleagues tested the effects of adding a BCL2 inhibitor drug to the standard two-drug regimen in patient-derived xenograft models, which were established using melanoma tumors that had acquired resistance to standard therapy. Results showed that tumors that expressed high levels of BCL2 responded well to the triple combination, reversing resistance and inducing a complete tumor regression.
However, tumors that expressed high levels of MCL1—another protein from the BCL2 family—did not respond to this combination. In these tumors, the researchers tested an alternative treatment course adding an experimental MCL1 inhibitor to standard treatment, which successfully led to complete tumor regression.
“Targeted therapy works by shutting down the main signal driving melanoma growth, but tumors often have backup systems that keep them alive,” said Yennu Nanda. “By identifying which protein a tumor relies on for survival, we may be able to match patients to drug combinations tailored to their specific tumor biology.”
MCL1 inhibitors have previously shown promising antitumor activity, but early clinical trials flagged concerning heart-related side effects that have prevented them from moving through clinical development and receiving approval. In this study, however, the combination of an MCL1 inhibitor with standard BRAF-MEK inhibitors seemed to protect cardiac cells from the harmful effects associated with these experimental drugs.
“We did not anticipate that pairing these drugs would reduce MCL1 inhibitor toxicity,” said Michael A. Davies, MD, PhD, chair of melanoma medical oncology at UT MD Anderson. “If this finding is confirmed in clinical trials, it could give a second life to a class of drugs that has struggled to advance through development. It also reinforces that the most effective combinations are those that eliminate cancer while sparing healthy tissue.”
Building on these findings, the researchers are now working on analyzing tumor samples from a recent Phase II clinical trial in melanoma patients who received standard treatment and a BCL2 inhibitor, with the goal of studying whether MCL1 expression can predict clinical response. Down the line, their goal is to design clinical trials where melanoma patients are matched with drug combinations based on the expression of BCL2 or MCL1 biomarkers.
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Age-stratified multimodal MRI and machine learning to explore autism-related brain characteristics in youth
PurposeAutism is a common neurodevelopmental condition (NDC) that is characterized by restricted, repetitive behaviors and social communication differences that can impact the daily functioning of individuals. The clinical diagnosis of autism can be challenging, mainly due to its behavioral variability and frequent co-occurrence with other NDCs. This study investigates the ability of machine learning-based classification models trained using multimodal neuroimaging data combined with feature-importance analyses to identify development-specific brain characteristics associated with autism.ApproachA total of 144 participants aged 5 to 18 years with structural MRI (sMRI), diffusion MRI (dMRI), and resting-state functional MRI (rs-fMRI) data available were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. Radiomic features were extracted from each MRI data modality and used to train support vector machine (SVM) classifiers to identify neuroimaging patterns associated with autism. Single MRI modality classifiers, as well as one combining all three modalities, were trained for comparison purposes. To investigate age-specific effects, the same approach was followed for three age sub-groups: younger children (5–11 years), adolescents (12–18 years), and the entire 5–18 years age cohort. Model performance was evaluated using leave-one-out cross-validation across 30 diagnosis-balanced data splits. Feature-importance analyses were conducted to identify the most important neuroimaging features for classification.ResultsThe classification accuracies of the unimodal models ranged from 68.3% to 75.3% for sMRI, from 69.3% to 77.6% for dMRI, and from 66.3% to 69.9% for rs-fMRI data across age groups. Among all single imaging modalities and age groups, dMRI showed the highest performance with a 77.6% accuracy in younger children (5–11 years). The multimodal approach improved classification performance when compared to the unimodal models in all age groups, achieving accuracies of 78.9%, 76.7%, and 70.5% in the younger, adolescent, and entire age cohorts, respectively. Our findings indicate that multimodal classifiers integrating complementary structural, microstructural, and functional imaging features result in a more comprehensive representation of brain features that strengthens model performance. The most informative brain regions for classification differed between children and adolescents while several diffusion-derived features significantly correlated with social responsiveness scores, emphasizing the clinical importance of studying white and gray matter microstructure in autism.ConclusionsThis study demonstrates the potential of multimodal neuroimaging-based machine learning models to identify development-specific biomarkers associated with autism. The results highlight the value of integrating age-stratified analyses of multimodal neuroimaging to better capture autism-associated developmental brain characteristics. The framework adopted in this study could be extended to explore other NDCs in the future.
New Antibody Biomarkers May Improve Early Detection of Lyme Disease, Predict Persistent Symptoms
Researchers have identified a distinct set of anti-lipid antibodies that could improve the early diagnosis of Lyme disease while also helping distinguish patients who develop persistent symptoms after treatment from those who recover fully.
The study, published in Infection and Immunity, found that antibodies against specific phospholipids appear before conventional Lyme disease antibodies in some patients and persist in a subset of individuals with post-treatment Lyme disease (PTLD). The findings suggest these immune markers could eventually complement existing diagnostic tests and provide new clues about the biology underlying chronic symptoms.
Lyme disease, caused by the spirochete Borrelia burgdorferi, is the most common vector-borne infection in North America and Europe. Although most patients respond well to a two- to three-week course of antibiotics, an estimated 10% to 20% continue to experience fatigue, pain, cognitive impairment, and other nonspecific symptoms long after treatment. The biological basis for these persistent symptoms remains poorly understood, and clinicians currently lack objective biomarkers to identify affected patients.
Current diagnostic testing also has significant limitations. Standard two-tier serologic testing relies on antibodies directed against Borrelia proteins, but these antibodies often do not appear until several weeks after infection and can remain detectable long after the bacteria have been eliminated. As a result, existing tests have limited sensitivity during early infection and cannot reliably distinguish active infection from previous exposure or persistent post-treatment illness.
The new study builds on earlier work showing that B. burgdorferi scavenges lipids from its human host and incorporates them into its outer membrane. The researchers hypothesized that this unusual biology could trigger immune responses against host lipids that might serve as biomarkers of disease activity.
To test that idea, investigators analyzed serum samples from patients with acute Lyme disease and PTLD collected from two independent biobanks. Together, the cross-sectional and longitudinal cohorts allowed researchers to follow antibody responses from the day of diagnosis through one year after treatment.
Among numerous lipid targets examined, only three antiphospholipid antibodies were consistently elevated following infection. Two antibodies—anti-phosphatidic acid (αPA) and anti-phosphatidylserine (αPS)—were significantly elevated at diagnosis, including in patients with erythema migrans before they had seroconverted on conventional Lyme disease testing.
Longitudinal analyses showed that antibody levels followed distinct patterns over time. Both αPA and αPS peaked approximately three to six months after diagnosis before declining in most patients. However, αPS remained persistently elevated in a subset of individuals with PTLD, distinguishing them from healthy controls and from patients with autoimmune and chronic illnesses that often resemble post-treatment Lyme disease, including systemic lupus erythematosus, multiple sclerosis, fibromyalgia, long COVID, and chronic fatigue syndrome.
The researchers propose that persistent αPS elevations may reflect an abnormal immune response rather than ongoing infection. While the precise mechanism remains unknown, they suggest that dysregulated activation of innate-like B cells or continued exposure to phosphatidylserine antigens could sustain antibody production in susceptible individuals.
Importantly, the authors note that whether these antibodies actively contribute to disease or simply mark immune dysfunction remains uncertain. “The presence of autoantibodies does not always drive autoimmune disease,” the authors write, emphasizing that further mechanistic studies are needed.
The investigators also draw parallels with syphilis, another spirochete infection. In syphilis, lipid-directed antibody tests are routinely used alongside pathogen-specific assays to monitor disease activity and treatment response. The authors suggest a similar strategy could eventually enhance Lyme disease diagnostics.
“The addition of antilipid antibodies to these panels may improve sensitivity while retaining the more specific diagnostic antibodies,” the authors write. They note that anti-lipid antibodies could potentially function both as adjuncts for early diagnosis and as biomarkers for monitoring recovery following treatment.
The study has several limitations, including relatively modest sample sizes and the use of specimens collected from multiple biobanks with differing collection protocols. Nevertheless, the consistency of findings across independent cohorts strengthens confidence in the observations.
Ultimately, the authors conclude that “the antibodies described here may be valuable biomarkers of early or persistent disease and suggest another mechanism linking B. burgdorferi infection and pathologic autoimmunity.” Larger prospective studies will be needed to determine whether these antibodies can be incorporated into clinical practice for diagnosing Lyme disease or identifying patients at risk for persistent symptoms.
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Associations of TNF-α, MIF, and cortisol with cognitive function in patients with bipolar disorder during acute manic episodes: a short-term follow-up study
BackgroundBipolar disorder (BD) is frequently accompanied by cognitive impairment, and growing evidence suggests that immune-inflammatory activation and hypothalamic-pituitary-adrenal axis dysregulation may contribute to its pathophysiology. This study aimed to examine the associations of tumor necrosis factor-α (TNF-α), macrophage migration inhibitory factor (MIF), and cortisol (COR) with cognitive function in patients with BD during manic episodes and to characterize their short-term changes.MethodsIn this short-term follow-up study, 53 patients with BD during manic episodes and 53 healthy controls (HCs) were enrolled. Plasma TNF-α, MIF, and COR levels were measured using enzyme-linked immunosorbent assay. Cognitive function was assessed using the Chinese Brief Cognitive Test, including information processing speed (IPS), executive function (EF), sustained attention (SAT), and working memory (WM). Patients were evaluated at baseline and after 8 weeks of treatment, whereas HCs were assessed once at baseline. Group comparisons and biomarker–cognition correlation analyses were performed. Multiple testing in the correlation analyses was controlled using the Benjamini–Hochberg false discovery rate (FDR) procedure.ResultsAt both baseline and follow-up, patients with BD had significantly lower IPS, EF, SAT, and WM scores, but significantly higher plasma TNF-α, MIF, and COR levels, than HCs. After 8 weeks of treatment, cognitive scores in the BD group improved significantly, whereas reductions in TNF-α, MIF, and COR did not reach statistical significance. In exploratory unadjusted Pearson analyses, several biomarker–cognition associations survived FDR correction. However, in the primary adjusted partial correlation analyses, only the negative association between TNF-α and WM remained significant after adjustment for covariates and FDR correction at both baseline and follow-up.ConclusionPatients with BD during manic episodes exhibited widespread cognitive impairment accompanied by elevated inflammatory and neuroendocrine markers. TNF-α showed the most robust association with working memory after adjustment for covariates and correction for multiple comparisons. Associations involving MIF or cortisol and executive function should be interpreted as exploratory and require validation in larger longitudinal studies.
Relationship of Peripheral Inflammatory and Neuroprotective Biomarkers With Response to Intermittent Theta Burst Stimulation in Treatment-Resistant Depression
Conditions: Treatment-resistant Depression (TRD); Major Depression
Interventions: Device: Intermittent Theta Burst Stimulation (iTBS)
Sponsors: Gulhane Training and Research Hospital
Not yet recruiting
Interventions: Device: Intermittent Theta Burst Stimulation (iTBS)
Sponsors: Gulhane Training and Research Hospital
Not yet recruiting
Blood Protein May Signal Dementia Risk Decades Before Symptoms Appear
A blood protein long associated with dementia in older adults may also identify people at increased risk decades before symptoms develop, according to a large international study published in Science Advances.
Analyzing data from six large longitudinal cohorts, researchers from the National Institute on Aging found that elevated levels of growth differentiation factor-15 (GDF15)—a circulating cytokine involved in inflammation and cellular stress responses—in adults younger than 55 years were associated with a significantly greater risk of developing dementia later in life, particularly vascular dementia. The findings suggest that molecular changes associated with neurodegeneration may be detectable years before cognitive symptoms emerge.
“Our findings extend existing evidence by demonstrating that elevated GDF15 levels are detectable in midlife—before age 55—in individuals who later develop dementia,’” the authors write.
The study included approximately 500,000 participants from the UK Biobank, more than 15,000 from the Atherosclerosis Risk in Communities (ARIC) study, nearly 5,700 from the AGES-Reykjavik Study, and three additional cohorts. Participants were followed for 15 to 25 years, enabling investigators to determine whether plasma GDF15 levels measured in midlife predicted future dementia.
Across nearly all cohorts, elevated plasma GDF15 was associated with increased risk for all-cause dementia. However, the relationship was strongest for vascular dementia, with effect sizes approximately two to five times greater than those observed for Alzheimer’s disease.
The distinction suggests GDF15 may be particularly useful for identifying individuals at risk for vascular cognitive impairment rather than the amyloid-driven pathology typically associated with Alzheimer’s disease. As the authors note, “the association was particularly pronounced for vascular dementia,” supporting the protein’s potential as an early marker of vascular brain injury.
To investigate whether GDF15 might play a biological role in disease rather than simply reflect ongoing pathology, the researchers performed Mendelian randomization analyses using genetic data. The analyses supported a potential causal relationship between elevated circulating GDF15 and Alzheimer’s disease and related dementias.
Additional analyses linked higher plasma GDF15 concentrations with several established indicators of neurodegeneration, including cerebral small vessel disease, elevated phosphorylated tau (pTau-181) in both plasma and cerebrospinal fluid, and increased neurofilament light, a marker of neuronal injury. In contrast, GDF15 was not associated with amyloid pathology, suggesting that it may reflect alternative disease mechanisms.
Instead, multiple lines of evidence pointed toward inflammation and immune dysregulation. Individuals with elevated GDF15 exhibited cerebrospinal fluid protein signatures consistent with neuroimmune activation, including complement activation, inflammatory signaling pathways, and disease-associated microglial responses.
To better understand these mechanisms, the investigators exposed cultured human macrophages to recombinant GDF15. The protein altered cellular pathways involved in interferon signaling, energy metabolism, and heme scavenging—processes that have all been implicated in dementia risk. Together, the experimental and clinical findings suggest that GDF15 may actively influence neurodegeneration through immune and vascular pathways rather than acting solely as a marker of biological aging.
The authors conclude that “these findings support circulating GDF15’s role as an early biomarker—particularly for vascular dementia and neuroinflammation—and identify the mechanisms by which it may drive dementia risk.”
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Pump You Up: Epigenetic Editor Drives Muscle Growth in FSHD Patients
A first-in-human clinical trial of an experimental epigenetic therapy has produced an outcome long considered elusive in the progressive genetic muscle degeneration disease facioscapulohumeral muscular dystrophy (FSHD): measurable gains in lean muscle volume.
Epicrispr Biotechnologies announced updated interim results from its ongoing Phase I/II study of EPI-321, reporting that all three FSHD patients who reached the six-month evaluation point experienced increases in lean muscle mass following a single intravenous (IV) infusion of the therapy. The findings represent what the company says is the first clinical evidence that a treatment may be capable of increasing muscle volume in FSHD, which affects an estimated 870,000 people worldwide and is one of the most common forms of muscular dystrophy.
Although the study remains in its early stages with only nine total patients across two dosing cohorts, the promising findings were supported by imaging data, functional measurements, and biomarker changes that together suggest the therapy may be altering the biological drivers of the disease.
FSHD lacks disease-modifying treatments to intervene in the characteristic loss of skeletal muscle function, starting in the face, shoulders, and upper arms and spreading throughout the body. “We were pretty blown away,” Epicrispr CEO Amber Salzman told Inside Precision Medicine. “Every single patient gained lean muscle volume. No one has seen that.”
A silencing GEM
FSHD is caused by hypomethylation of the D4Z4 region, which is a polymorphic variable number tandem repeat (VNTR) array made up of 3.3 kilobase units, with each unit encoding the DUX4 gene. This hypomethylation leads to abnormal activation of the DUX4 gene, triggering muscle cell death and tissue degeneration, resulting in progressive muscle weakness, asymmetry, and fat infiltration.
Unlike conventional gene-editing therapies that permanently alter DNA sequences, Epicrispr’s therapy uses their Gene Expression Modulation System (GEMS). Epicrispr’s EPI-321 is an adeno-associated virus (AAV)-delivered epigenetic gene therapy that restores D4Z4 methylation and suppresses DUX4 expression, and preclinical studies show improved muscle function and reduced muscle cell death. “We don’t cut DNA,” Salzman said. “We’re not using Cas9 in the traditional editing sense. We use a dead Cas protein and an epigenetic mechanism to silence the gene.”
According to Epicrispr, preclinical studies demonstrated that the epigenetic modifications persist through many rounds of cell division, suggesting long-term suppression may be possible after a single treatment.
In addition to the therapeutic innovation, Epicrispr has also made headway into the long-standing challenge of identifying reliable molecular biomarkers for FSHD to evaluate activity downstream of DUX4. Traditional muscle biopsies provide information from only a small tissue sample and can be difficult to interpret when substantial fat replacement has already occurred.
Instead, Epicrispr collaborated with researchers at the University of Colorado investigating circulating cell-free DNA signatures associated with DUX4-driven disease activity. The biomarker, known as CBT17, emerged from studies comparing blood samples from approximately 50 healthy individuals and 50 FSHD patients. The biomarker may provide a whole-body readout of disease activity, offering evidence that DUX4 suppression is occurring beyond individual muscles examined through biopsy.
As of the May 12, 2026 data cutoff, EPI-321 has demonstrated a manageable safety profile, with nine patients treated across two dose cohorts. One IV infusion was administered to six patients in the first cohort at a target dose of 2×10¹³ vg/kg and to three patients in the second cohort at a target dose of 4×10¹³ vg/kg.
The company reported a “manageable” safety profile, with no severe dose-limiting toxicities disclosed to date. Salzman was careful not to overstate the findings. “I never want to be hubristic when it comes to AAV,” she said. “You’re giving people a lot of virus.”
She described the treatment experience as somewhat analogous to vaccine-related immune responses, noting that prophylactic immunosuppression is used as part of the protocol. “It’s manageable,” she said. “I’m not going to say it’s favorable. It’s manageable.” No serious grade 3 or grade 4 treatment-related safety concerns have been reported so far.
Baseline levels of CBT17 in treated patients fell substantially after therapy. “When we looked at baseline and three months, our patients’ levels came down so that it was just about in the healthy range,” she said.
Functional measures match MRI
The headline result comes from whole-body MRI analyses conducted six months after treatment. Among the first three evaluable patients, lean muscle volume increased in every individual compared with baseline measurements. On average, patients gained approximately 370 milliliters of lean muscle tissue, equivalent to roughly 0.8 pounds of muscle mass. Individual gains ranged from about 0.5 to 1.3 pounds. For a disease characterized by chronic muscle loss, even stabilizing muscle mass would be considered a meaningful achievement. Actual gains are potentially more significant.
The MRI analyses were performed in collaboration with Springbok Analytics, a company specializing in AI-powered muscle imaging. In addition to being widely used in professional sports to monitor injury recovery and rehabilitation, as well as a growing number of clinical settings, FSHD is one of Springbok’s primary clinical focus areas, along with disorders such as Charcot-Marie-Tooth disease and Duchenne muscular dystrophy. Using a specialized MRI protocol that runs on standard scanners, the company can quantify changes across as many as 140 individual muscles throughout the body, measuring muscle volume, muscle composition, and fat infiltration, producing objective data on muscle health.
According to Salzman, Springbok compared patients’ baseline scans against machine-learning models trained on longitudinal imaging datasets from more than 100 FSHD patients. “They can predict what it’s going to look like in six months—how much muscle patients will lose and where,” she said. “Then we sent them the six-month scans, and every patient gained lean muscle volume.”
The gains were not evenly distributed throughout the body. Patients appeared to benefit most in muscles that still retained substantial healthy tissue before treatment. “If you have too much fat in that muscle, there’s not that much we can do,” Salzman explained. “But if you have some residual muscle, it can not only stop getting worse because we’re cutting off the poison, but you can also regenerate muscle.”
One participant, a post-menopausal woman, gained approximately 1.3 pounds of lean muscle mass according to the MRI analysis. The increase was particularly notable because age-related muscle loss would normally be expected in that population. Earlier data released by Epicrispr showed favorable trends across several functional and strength assessments at the three-month mark. These measures included tests commonly used in neuromuscular disease studies, such as the Timed Up and Go test, 10-meter walk/run assessments, and quantitative muscle testing.
Because many functional endpoints depend on patient effort, interpreting changes in small open-label studies can be challenging. Investigators and investors alike often question whether participants simply perform better because they know they received treatment. Salzman acknowledged those concerns. “You could say maybe they had a good day, and that’s why the functional measures were better,” she said.
MRI measurements, however, are not subject to effort-dependent variability. “You can’t fake MRI,” she added. Importantly, the regions showing muscle growth on imaging appeared to correspond with areas where patients demonstrated improved performance.
One participant who gained substantial upper-body muscle volume showed corresponding gains on upper-body strength assessments, while lower-body improvements were more limited in areas where muscle loss had already become severe. “The whole story is holding together,” Salzman said. “Their functional measures are getting better; their lean muscle is increasing.”
Taken together, the MRI, biomarker, and functional data provide multiple independent signals supporting biological activity. “You can’t fake blood; you can’t fake MRIs,” Salzman said. “Those are totally supportive.”
Epitome of epigenetic editing?
Beyond FSHD, researchers are closely watching EPI-321 because it represents one of the first clinical tests of an epigenetic CRISPR-based therapeutic strategy. “This is an important milestone not just for FSHD but for epigenetic medicine,” Salzman said. The approach could potentially be adapted to other diseases caused by harmful gene activation or insufficient gene silencing.
Still, significant hurdles remain before EPI-321 can be considered a proven therapy. The current dataset includes only three patients with six months of follow-up. Epicrispr plans to present additional data from six patients at the World Muscle Society Annual Congress in September 2026.
The company expects the initial Phase I/II study to complete enrollment and generate a full readout in mid-2027. Yet, larger studies will be needed to determine whether muscle gains persist, whether they translate into meaningful long-term functional benefits, and whether safety remains acceptable over time.
Regulators will also require evidence linking increases in lean muscle volume to tangible improvements in patient function and quality of life. To that end, Epicrispr is preparing discussions with the U.S. Food and Drug Administration regarding potential future endpoints and whether MRI-based muscle measurements could eventually serve as surrogate markers of clinical benefit.
Whether those early signals hold up in larger populations remains to be seen. But for a disease in which muscle loss has long been viewed as inevitable, the possibility of reversing that trend, even modestly, marks a notable moment for the FSHD field.
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