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PubMed2026

Effects of Exergame Balance Training with Variable Cognitive Motor Challenges on Serum BDNF, p-tau181, and Cognitive Functions in Adults with Mild Cognitive Impairment: A Randomized Trial.

INTRODUCTION: Cognitive-motor exergame balance training may increase attentional demands and neuronal processing, potentially affecting serum levels of brain-derived neurotrophic factor (BDNF), Aβ1-42, and p-tau181, as well as train cognitive abilities in adults with mild cognitive impairment (MCI). This study aimed to compare the effects of exergame balance training of mild, moderate, high-difficulty, and Wii Fit™ groups on blood serum levels of BDNF, Aβ1-42, p-tau181, and cognition function in adults with MCI. METHODS: In this four-arm, parallel group randomized clinical trial, 97 adults with MCI were randomly assigned to exergame balance training groups of mild, moderate, high-difficulty, and Wii Fit exergame as a control group. All participants received 40 min/session, 3 times/week for 8 weeks. Assessment of serum levels of p-tau181, Aβ1-42, BDNF, and cognitive functions was conducted at baseline, after weeks 4 and 8. A mixed-model analysis of covariance was used, with post-baseline measurements (weeks 4 and 8) specified as the within-subject factor and the corresponding baseline value entered as a covariate to adjust for initial between-group variability. RESULTS: A significant group × time interaction was found for BDNF, F(3,92) = 6.413, P = 0.017, ηp2 = 0.181; p-tau181, F(3,92) = 4.640, P = 0.040, ηp2 = 0.138; attention, F(3,92) = 4.171, P = 0.045, ηp2 = 0.057; abstraction, F(3,92) = 4.263, P = 0.043, ηp2 = 0.058; and visuospatial skills, F(3,92) = 6.931, P < 0.001, ηp2 = 0.234. CONCLUSION: Cognitive-motor challenge-based exergame balance training was associated with an increase in serum BDNF, a reduction in p-tau181. In contrast, the Aβ1-42 levels remained stable. These changes were accompanied by improvement in selective cognitive functions (attention, abstraction, and visuospatial skills) in individuals with MCI. Greater effects were observed in moderate and high-difficulty groups, suggesting the importance of intervention intensity in promoting cognitive and neurobiological outcomes in MCI.

Humans↗

PubMed2026

Quantification of appetite-regulating hormones in children with hypothalamic and common obesity.

CONTEXT: The pathophysiology of hypothalamic obesity (HyOb) remains incompletely understood with no effective treatments. OBJECTIVE: We examined differences in appetite-regulating hormone concentrations between patients with HyOb, common obesity, and lean controls. DESIGN: Multiway cross-sectional case-control study of patients aged 2 through 19 years. SETTING: Two tertiary pediatric endocrinology centers. PATIENTS: Cases were obese (body mass index [BMI] > +2 SD score [SDS], "HyOb") and lean ("HyLean") patients with congenital (septo-optic dysplasia) or acquired (suprasellar brain tumor) hypothalamic disorders. Controls had common obesity ("Ob") or nonhypothalamic disorders and normal BMI ("Lean"). MAIN OUTCOME MEASURES: Relationships between the Dykens' Hyperphagia Questionnaire Score (DHQS), plasma or serum concentrations of leptin, insulin, α-melanocyte stimulating hormone (αMSH), brain-derived neurotrophic factor, oxytocin, acylated ghrelin, agouti-related peptide and copeptin, and BMI SDS. RESULTS: Dykens' Hyperphagia Questionnaire Score did not differ between HyOb and Ob patients (24 [17-34] vs 24 [18-31]) but correlated with BMI SDS in patients with hypothalamic disorders (P = 0.02). HyOb and Ob patients exhibited similarly increased anorexigens (insulin, leptin) and decreased orexigens (ghrelin, agouti-related peptide) compared to HyLean and Lean patients. The rate of BMI increase was independently associated with lower αMSH (β = -0.23 [-0.36 to -0.11], P = .0007) and ghrelin (β=-0.004 [-0.01 to 0.00], P = .001) concentrations, suggesting that αMSH replacement may be a therapeutic target for HyOb. HyLean patients demonstrated intermediate insulin responses to glucose compared to other subcohorts. CONCLUSION: In our cohort, patients with HyOb appeared indistinguishable from Ob in terms of their appetite and appetite-regulating neuroendocrine circuitry. Higher αMSH concentrations are associated with reduced weight gain and may be a target for therapeutic intervention.

alpha-MSH↗

PubMed2026

Adjunctive intermittent theta-burst stimulation for first-episode schizophrenia: A randomized clinical trial.

BACKGROUND: The efficacy of intermittent theta-burst stimulation (iTBS) combined with pharmacotherapy and psychotherapy in first-episode schizophrenia remains unclear. This study evaluated adjunctive iTBS with risperidone and cognitive behavioral therapy (CBT) and explored serum biomarkers indicating treatment response. METHODS: In this randomized, assessor-blind trial, 100 first-episode schizophrenia patients received either iTBS plus risperidone and CBT (iTBS group, n = 50) or risperidone and CBT alone (control, n = 50) for 3 months. The primary outcome was change in PANSS total score at 4 weeks and 3 months. Response was defined as a ≥ 50 % PANSS reduction. Secondary outcomes included cognitive function (MCCB subtests) and serum GDNF, cortisol, and dehydroepiandrosterone sulfate (DHEA-S) levels. RESULTS: The iTBS group showed significantly greater reduction in PANSS total scores than controls at both 4 weeks and 3 months (mean difference at 3 months: -13.3, 95 % CI: -16.8 to -9.8; P < 0.001), with a higher responder rate (76 % vs. 48 %). Significant improvements across all cognitive domains were observed in the iTBS group (all P < 0.001). Post-treatment, the iTBS group exhibited higher GDNF and lower cortisol and DHEA-S levels (all P < 0.001). A combined biomarker panel demonstrated superior discriminative performance for treatment efficacy (AUC=0.865 after cross-validation). Adverse events were comparable between groups. CONCLUSIONS: Adding iTBS to risperidone and CBT significantly improves clinical symptoms and cognitive function in first-episode schizophrenia. The combination of GDNF, cortisol, and DHEA-S shows promise as a composite biomarker for treatment response, though sham-controlled validation is warranted.

Humans↗

PubMed2026

Sex-dependent protective effects of microglial tumor necrosis factor on post-stroke inflammation and myelin injury.

Tumor necrosis factor (TNF) is rapidly induced after ischemic stroke, but its proposed cell-specific and sex-dependent functions during post-stroke inflammation remain insufficiently understood. Here, we investigated the role of microglia-derived TNF in the acute and subacute response to permanent middle cerebral artery occlusion (pMCAO). Tnf expression was transiently upregulated after stroke, becoming significant at 4 h, peaking at 12-24 h, and returning to baseline by 5 days. In situ hybridization confirmed strong Tnf expression in the infarct and peri-infarct regions. Whole-brain transcriptomic profiling showed that global TNF deficiency reshaped the early post-ischemic response, shifting it from microglia-associated phagocytic and wound-healing pathways toward an interferon-related inflammatory signature. To define the specific contribution of microglial TNF, we used inducible Cx3cr1CreER:Tnffl/fl mice. Microglial TNF deletion had no effect on infarct volume in males at 24 h or 5 days after pMCAO, but significantly increased infarct size in females at both time points. In both sexes, brain TNF levels peaked at 24 h and were significantly reduced in Cx3cr1CreER:Tnffl/fl mice, confirming microglia as a major source of early post-ischemic TNF. However, downstream consequences diverged by sex. At 5 days, male Cx3cr1CreER:Tnffl/fl mice showed reduced microglial reactivity and 18 kDa translocator protein (TSPO) signal, with no change in T-cell infiltration, and exhibited increased density of mature oligodendrocytes. In contrast, female Cx3cr1CreER:Tnffl/fl mice displayed enhanced microglial reactivity, increased TSPO binding, higher peri-infarct T-cell infiltration, and reduced oligodendrocyte density and myelin integrity. Together, these findings identify microglial TNF as a sex-dependent regulator of post-stroke inflammation and myelin injury.

Animals↗

PubMed2026

Insights from changes in NDEV biomarkers of metabolism: effects of PPARγ and GLP1 receptor agonists on brain metabolism.

BACKGROUND: Insulin resistance (IR) is implicated in central nervous system disorders, including depression and Alzheimer's disease (AD). METHODS: We analyzed biological samples from two cohorts of clinical trial participants: (1) participants with unremitted depression after six months of treatment as usual who received pioglitazone (PPARγ agonist, N = 12) or placebo and (2) middle-aged participants at genetic risk for AD who received liraglutide (glucagon-like peptide 1 [GLP1] receptor agonist, N = 15) or placebo. These cohorts, which previously showed treatment-related improvements in peripheral IR, were used to assess the effects of pioglitazone and liraglutide on CNS insulin signaling using neuron-derived extracellular vesicles (NDEVs) as biomarkers. We utilized biological samples to measure biomarkers of IR in NDEVs. Eleven Akt-mTOR pathway proteins were measured before and after 12 weeks of treatment in both groups. RESULTS: Participants who received pioglitazone experienced broader changes, with significant increases in GSK3β (Ser9), mTOR (Ser2448), and RPS6 (Ser235/Ser236; all P ≤ .02) compared with placebo, and 77% of participants showed mTOR (Ser2448) response. Participants who received liraglutide demonstrated significantly increased NDEV-associated phosphorylated Akt (Ser473) and mTOR (Ser2448; P = .04 and P = .025, respectively) compared with placebo, with 40% and 30% of participants in the liraglutide group showing biomarker response in both Akt (Ser473) and mTOR (Ser2448), respectively. These effects appeared relatively independent from changes in fasting plasma insulin and glucose concentration at 120-minutes during the oral glucose tolerance test. DISCUSSION: Our findings demonstrate CNS-specific biomarker responses to both PPARγ agonists and GLP1 receptor agonists.

Humans↗

PubMed2026

Epigenetic drift and LINE-1 activation in aging brain: Implications for neurodegenerative disease.

Brain aging and age-associated neurological diseases, such as Alzheimer's Disease (AD), Parkinson's Disease (PD), and Amyotrophic Lateral Sclerosis (ALS), are largely attributed to epigenetic drift which is characterized by the gradual accumulation of alterations in neural cell methylation patterns over time. These methylation changes are particularly evident in transposable element (TE)-derived sequences such as Long interspersed element-1 (LINE-1) which comprises approximately 17% of the human genome. During aging, LINE-1 elements gradually lose their methylation, as well as the regulatory safeguard mechanisms that usually keep them inactive. This repression loss can lead to LINE-1 reactivation, contributing to harmful effects including genomic instability, neuroinflammation, and more. Together these findings indicate that impaired epigenetic maintenance, especially in repetitive genome regions, plays a key role in biological aging of neurons and glial cells. In this narrative review, we discuss the methylation dynamics and regulatory mechanisms of LINE-1 retrotransposons, their activation processes during aging, and contribution to age-associated neurological diseases. We also highlight the potential of targeting LINE-1 methylation to restore methylation homeostasis, epigenetic stability and delay brain aging.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

Analysis of the Relationship between Early Clinical Factors and Glasgow Outcome Scale in Patients With Traumatic Brain Injury.

OBJECTIVE: This study aimed to evaluate the association between early clinical factors and the Glasgow outcome scale (GOS) in patients with traumatic brain injury (TBI). METHODS: We conducted a retrospective analysis of 98 TBI patients who underwent emergency surgery between January 2021 and January 2024. Based on GOS scores at 6 months post-surgery, patients were classified into a favorable outcome group (GOS ≥ 4, defined as moderate disability or good recovery, n = 58) and an unfavorable outcome group (GOS < 4, i.e., death, persistent vegetative state, or severe disability, n = 40). Baseline and early clinical parameters were compared between groups. Statistically significant variables from univariate analysis were entered into a multivariate logistic regression model to identify independent prognostic factors. RESULTS: Significant intergroup differences were observed in age, time from injury to surgery, bleeding site, midline shift, Glasgow coma scale (GCS) score at admission, blood glucose level, and D-dimer level (all p < 0.05). Multivariate analysis confirmed that age, time from injury to surgery, GCS score, blood glucose, and D-dimer level were independent predictors of GOS (all p < 0.05). CONCLUSION: Early clinical factors, including age, time to surgery, GCS score, blood glucose, and D-dimer level, independently influence GOS in TBI patients. Time from injury to surgery emerged as a potentially modifiable factor in this cohort, suggesting that minimizing delays may improve outcomes.

Humans↗

PubMed2026

Understanding specificity in immune-brain pathways: A systematic review of differential associations between individual cytokines and brain structure and function measured through magnetic resonance imaging in humans.

Research shows that cytokines are associated with psychiatric disorders, including major depression, and multiple aspects of brain structure and function. Accumulating data suggest that different cytokines may have unique profiles of biological activity, particularly in their neuromodulatory roles, but it is currently unclear whether they have unique associations with specific neural circuits in humans. In this paper, we systematically review magnetic resonance imaging studies conducted with depressed or healthy control human participants under age 65 that examine associations between peripheral cytokines and brain structure and function, with the goal of evaluating evidence for the specificity of these cytokine-brain associations. We find that across multiple measures of brain structure and function, the majority of studies reviewed reported unique associations between individual cytokines and brain outcomes. A synthesis of findings across studies also suggests a preliminary hypothesis of specific associations of interleukin-6 levels in circulation with the default mode network and tumor necrosis factor-alpha with the salience network, which could be tested in future research. We conclude the review with future directions for research that can strengthen understanding of these associations.

Humans↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2026

Risk Factors for Long-Term Health-Related Quality-of-Life and Mental Health Outcomes in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Traumatic brain injury (TBI) often leads to long-term disability, including persistent mental health issues and lower health-related quality of life (HRQoL). Early interventions can improve recovery, but because resources limit routine monitoring of all patients, trauma care remains largely symptom-driven. The combination of long-term disability and limited capacity for routine follow-up highlights the need for risk-stratified follow-up care and reliable evidence on early prognostic factors. However, the existing literature is sparse and methodologically heterogeneous, limiting the clinical applicability of findings. We therefore conducted a systematic review and meta-analysis to identify early risk factors for poorer long-term mental health and HRQoL outcomes. A systematic search of seven electronic databases identified studies of adult patients with TBI, with outcomes assessed at least 6 months postdischarge. Two authors independently screened the studies, assessed the risk of bias, and extracted the data. We pooled effect estimates using a random-effects meta-analysis and calculated 95% prediction intervals. A narrative synthesis was applied when meta-analysis was not feasible. The review was registered with PROSPERO (CRD42024576912) and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Of the 8,104 articles screened, 64 studies met the inclusion criteria (n = 334,672). Most studies (58%) had a low risk of bias. Female sex, socioeconomic disadvantage, psychiatric history, assaultive-related injuries, and previous TBI were consistently associated with worse long-term outcomes. Across meta-analyses, assault-related injuries more than doubled the odds of post-traumatic stress disorder (odds ratio [OR] = 2.72; 95% confidence interval [CI]: 2.01-3.66, I2 = 0%). Higher odds were also observed among females (OR = 1.33; 95% CI: 1.11-1.59, I2 = 0%), individuals with prior TBI (OR = 1.56; 95% CI: 1.07-2.27, I2 = 0%), and those with psychiatric history (OR = 2.38; 95% CI: 1.83-3.10, I2 = 48%). We found that female sex (OR = 1.72; 95% CI: 1.38-2.16, I2 = 58%), prior TBI (OR = 1.52; 95% CI: 1.25-1.85, I2 = 0%), and psychiatric history (OR = 3.25; 95%CI: 1.86-5.69, I2 = 98%) were associated with higher odds of depression. Furthermore, higher pooled anxiety scores were observed in females and in individuals with a psychiatric history. The study identified several readily available factors present before or at discharge that are associated with poor long-term HRQoL and mental health outcomes. Leveraging these factors in follow-up protocols, prediction modeling, and clinical decision support systems may facilitate risk-stratified postdischarge care for TBI patients.

Humans↗

PubMed2026

Pregnancy diet based on ancestral patterns increases growth in subcortical fetal brain regions.

Evidence on the biological basis for maternal nutrition effects on fetal and newborn neurodevelopment remains limited. This randomized controlled trial in Ecuador tested a maternal dietary pattern-derived from empirical studies of nutrition in human evolution and adapted locally-on offspring growth and brain development. Pregnant women (n = 215) in their first trimester were randomized to: 1) control (n = 104); or 2) Mikhuna ("nourish" in Kichwa) intervention (n = 111). The intervention, from 12 wk gestation to birth, consisted of a weekly food delivery (8 eggs, 500 g fish, and a variety of sustainably sourced fruits and vegetables) and a behavior change communication strategy encouraging diet diversity and limiting highly processed foods. Longitudinal data collection occurred at 12 wk, 21 wk, 35 wk gestation, and 2 wk postpartum, and included ultrasound imaging of fetal bone and brain parameters, maternal dietary intakes, anthropometry, socioeconomic and demographic variables, and other biomarkers. At close of intervention, a significantly higher percentage of women met the minimum dietary diversity threshold in Mikhuna (74.5%) vs. control groups (55.8%) (P = 0.004). Generalized linear regression models showed significant differences in Mikhuna compared to control for: corpus callosum length 0.19 cm (95% CI [0.02, 0.35]), gangliothalamic ovoid height 0.15 cm (95% CI [0.03 to 0.26]), and femur length -0.10 cm (95% CI [-0.19, -0.02]) from 21 wk to 35 wk; and corpus callosum Z 0.56 (95% CI [0.03, 1.09]) and femur length Z -0.21 (95% CI [-0.42, 0.00]) at 35 wk. The Mikhuna intervention increased the growth of subcortical fetal brain structures, which have established roles in motor control, cognition, and signal transmission.

Female↗

PubMed2026

Factors Associated With Accelerated Fracture Healing in Patients With Traumatic Brain Injury and Extremity Comminuted Fractures: A Retrospective Case-Control Study.

OBJECTIVE: Although traumatic brain injury (TBI) has been clinically associated with accelerated bone healing, the factors that determine which patients experience this phenomenon remain poorly defined, and previous findings are conflicting. This study aimed to investigate the clinical factors associated with accelerated fracture healing in patients with TBI combined with comminuted fractures of the limbs, so as to provide an evidence-based foundation for elucidating the clinical phenomenon of TBI-promoted fracture healing. METHODS: A retrospective case-control study design was employed. Patients between January 2020 and April 2024 with concurrent diagnoses of TBI and comminuted fractures were included. Based on radiographic findings and RUST/mRUST scores, patients were divided into an accelerated healing group (AHG) and a normal/delayed healing group (NDHG). Clinical data including demographics (age, sex, BMI), TBI characteristics (injury site, GCS score), admission laboratory indices (blood count, coagulation function, inflammatory markers), and fracture site/local soft tissue conditions, as well as functional outcomes assessed by the Short Musculoskeletal Function Assessment (SMFA) questionnaire at final follow-up were collected. Univariate analysis and multivariate logistic regression analysis were used to identify independent factors influencing accelerated fracture healing. Receiver operating characteristic (ROC) curves were plotted to evaluate their predictive value. RESULTS: A total of 119 patients were included, with 69 in the AHG and 50 in the NDHG. Significant differences were observed between the two groups in terms of age, BMI, GCS score, and platelet count (p < 0.05). Univariate analysis showed that age, BMI, GCS score, red blood cell count, and platelet count were associated with accelerated fracture healing (p < 0.20). Multivariate logistic regression analysis indicated that younger age (OR = 0.875, 95% CI: 0.821-0.934) and lower GCS score (indicating more severe TBI; OR = 0.490, 95% CI: 0.339-0.707) were independent predictors of accelerated fracture healing. ROC curve analysis showed that the area under the curve (AUC) for age and GCS score in predicting accelerated healing were 0.893 and 0.851, respectively. CONCLUSIONS: In patients with TBI combined with comminuted fractures, younger age and greater TBI severity (lower GCS score) are independent predictors of accelerated fracture healing. These findings assist clinicians in the early identification of patients with high healing potential to optimize treatment strategies, facilitate the early identification of high-risk patients, and provide clinical clues for further exploration of the molecular mechanisms underlying neurohumoral regulation of bone regeneration.

Humans↗

PubMed2026

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans↗

PubMed2026

Role of Polygenic Risk Scores in Predicting Cognitive Functioning after Mild Traumatic Brain Injury: A TRACK-TBI Study.

Patients with traumatic brain injury (TBI) and Glasgow Coma Scale scores of 13-15 (historically called mild TBI [mTBI]) commonly experience changes in cognitive functioning, including processing speed, memory, and executive functioning. In a prospective sample (N = 523) of individuals of European descent who had been treated in a U.S. level 1 trauma center for mTBI, we examined the prognostic value of four polygenic risk scores (PRS) for cognitive outcomes at 6-months postinjury. To estimate the impact of mTBI on cognition, primary cognitive outcomes were scaled as z-scores reflecting changes in performance relative to predicted preinjury performance. The PRS examined were previously developed and validated to predict cognition-related outcomes of educational attainment (Education-PRS), intelligence (Intelligence-PRS), and Alzheimer's disease (AD-mild traumatic brain injury (APOE)-PRS and AD + APOE-PRS). Both the Education-PRS and Intelligence-PRS displayed bivariate associations with all four cognitive outcomes (β = 0.19-0.32), whereas neither Alzheimer's disease PRS was significantly associated with any outcome. After controlling for other factors known to predict cognitive outcomes of TBI (e.g., sex, education, mTBI severity defined by a combination of Glasgow Coma Scale scores and the presence/absence of acute intracranial findings on clinical neuroimaging), the Education-PRS and Intelligence-PRS remained independently predictive of verbal episodic memory (β = 0.10-0.16), whereas their associations with processing speed and executive functioning were mostly nonsignificant and were mediated through educational attainment. Looking across primary z-score and secondary raw score outcomes, cognitive outcomes 6 months post-mTBI were good on average, and PRS made small independent contributions to outcome prediction. The mediation model findings may support theories of cognitive reserve, which propose that individuals with stronger preinjury cognitive processing abilities (often estimated by educational history) can better compensate for TBI. Moreover, findings indicate that PRS may contribute modestly to multivariable models predicting cognitive function after TBI.

Humans↗

PubMed2026

Genetic evidence for a causal relationship between melatonin metabolism and depression.

To investigate the causal relevance of melatonin metabolism, which provides the biological basis for circulating melatonin levels, to specific depression symptom subtypes, we performed a targeted systematic review of melatonin metabolism pathways in the human brain and liver. Using two-sample Mendelian randomization (MR), we assessed the causal effects of metabolism pathways and/or individual genes on major depressive disorder (MDD) and nine symptom subtypes derived from Patient Health Questionnaire-9 (PHQ-9). Instrumental variables (IVs) were expression quantitative trait loci (eQTL) for eight individual genes, one synthesis route, and three degradation routes. Results were assessed using Bayesian colocalization and phenome-wide association analyses. At the pathway-level, the genetically proxied synthesis-route signal was associated with PHQ-9 Assessment 5 (PHQ9A5, OR: 0.89, 95% CI: 0.85-0.93), but sensitivity analyses suggested this association was primarily driven by TPH1 and may reflect serotonin-related biology. In contrast, higher brain melatonin degradation raised the risk of both PHQ9A1 (OR: 1.03, 95% CI: 1.02-1.04) and PHQ9A7 (OR: 1.03, 95% CI: 1.02-1.03). Within degradation, up-regulation of the kynurenine sub-pathway increased the odds of PHQ9A3 (OR: 1.05, 95% CI: 1.02-1.07), PHQ9A4 (OR = 1.04, 95% CI: 1.02-1.06) and PHQ9A7 (OR: 1.05, 95% CI: 1.02-1.07). Gene-level analyses were largely concordant, except for SULT1A1, whose higher expression was genetically protective for PHQ9A3 but risk-increased for PHQ9A1 and PHQ9A4. Overall, these results demonstrate that melatonin metabolism exerts symptom-specific and pathway-specific causal effects on depression. A stratified view of melatonin's role may help optimize the application of exogenous melatonin supplementation.

Melatonin↗

PubMed2026

Thrombus Metabolism-Based Molecular Subtyping for Prognostic Risk Stratification in Acute Ischemic Stroke: A Preliminary Study.

AIMS: To preliminarily characterize metabolic molecular subtypes of cerebral thromboemboli and evaluate their clinical significance in anterior circulation acute ischemic stroke due to large vessel occlusion (AIS-LVO). METHODS: Untargeted metabolomics was performed on thromboemboli retrieved from 36 patients with anterior circulation AIS-LVO using ultra-performance coupled liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Unsupervised hierarchical clustering was employed to identify distinct metabolic molecular subtypes, and their associations with stroke etiology, radiographic severity, and functional outcomes were analyzed. RESULTS: Two distinct thrombus metabolic molecular subtypes (C1 and C2) were identified based on 12 metabolites significantly associated with both short-term (7-day ∆NIHSS) and long-term (90-day mRS) functional outcomes. The C1 subtype, predominantly cardioembolic, exhibited enhanced lipid metabolism, whereas the C2 subtype, primarily atherothrombotic, demonstrated increased folate metabolism. Patients with C1 thromboemboli presented more severe admission ischemic lesions (as indicated by ASPECTS) and experienced poorer short-term and long-term outcomes. A six-metabolite signature derived from LASSO regression was identified for exploratory discrimination of thrombus metabolic subtypes, etiological subtypes, and 90-day outcomes. CONCLUSION: This preliminary exploratory study identifies two metabolically distinct thrombus molecular subtypes with clinical implications in anterior circulation AIS-LVO, providing a novel basis for risk stratification and personalized secondary prevention and warrants further investigation.

Humans↗

PubMed2026

Migration intentions among nigerian neurosurgeons: a national survey of workforce retention.

Physician emigration from low- and middle-income countries creates critical workforce shortages. This study explored factors influencing migration intentions among Nigerian neurosurgeons and trainees. We conducted an anonymized survey of consultant neurosurgeons, fellows, and residents practicing in Nigeria. Invitations were sent by email and professional messaging platforms, and snowball sampling was used to increase participation. The survey included quantitative and open-ended questions on demographics, income, migration plans, and retention factors. Seventy-nine respondents participated (61.5 % consultants; 93.7 % male; median age: 44 years). Nearly all practiced general neurosurgery (97.3 %), and many also performed trauma (65.3 %) and spine (61.3 %) neurosurgery. Most (85.7 %) reported that their earnings were insufficient to support their families. Nearly 40 % were considering emigration, most often citing financial pressures (88.5 %) and poor working conditions (63.5 %) as push factors. By contrast, personal or family ties (63.0 %) and relocation costs (45.2 %) were cited as reasons to stay. Respondents identified higher salaries (58.1 %) and greater investment in the health sector (51.4 %) as key measures to improve retention. In univariable analyses, younger age, income insufficiency, income dissatisfaction, and feeling undervalued at work were associated with migration intention. Financial insecurity emerged as the dominant driver of migration intentions among Nigerian neurosurgeons. In addition to salary increases, sustained investment in healthcare infrastructure and workforce support is essential to improve retention. International partnerships may complement these efforts by building neurosurgical capacity and mitigating brain drain.

Humans↗