BMC Medicine最新文献

Background: Subcortical structures are pivotal for cortico-subcortical communication, yet are highly vulnerable to stroke. Damage to these structures can produce widespread cortical dysfunction, but how subcortical stroke reshapes the macroscale hierarchical organization of cortical networks remains poorly understood. Clarifying this relationship is critical for understanding subcortical contributions to brain-wide communication and for identifying reliable neural markers of clinical outcome.

Methods: We analyzed resting-state fMRI data from two independent cohorts of patients with subcortical stroke (discovery, 55 patients, 49 controls; replication, 23 patients, 26 controls). Cortical functional organization was mapped using diffusion map embedding to derive connectivity gradients, and group differences were quantified at both global and regional levels. Gradient metrics were further compared with conventional functional connectivity strength and tested for predictive utility using multivariate ridge regression against neurological outcome measures.

Results: Across cohorts, patients consistently exhibited compression of the principal unimodal-to-transmodal gradient, reflecting diminished hierarchical differentiation between sensory and association cortices. These alterations were stable over the first three months of recovery and spatially aligned with normative maps of dopaminergic, GABAergic, glutamatergic, serotonergic and cannabinoid systems. By contrast, conventional functional connectivity strength metrics showed poor reproducibility. Gradient features outperformed connectivity strength in predicting overall neurological severity (NIHSS scores) and generalized robustly across cohorts, although predictive power for motor-specific deficits (FMA scores) was limited.

Conclusions: Subcortical stroke disrupts cortical functional hierarchy in a reproducible and neurochemically constrained manner, and this disruption serves as a robust biomarker of global neurological impairment. These findings establish cortical gradients as a mechanistically informative and clinically relevant tool for probing subcortical-cortical interactions, with potential to inform prognosis and targeted neurorehabilitation.

Background: Acute myocardial ischemia/reperfusion (MI/R) increases risk for cognitive decline, yet the underlying mechanisms mediating heart-brain communication remain poorly understood. Small extracellular vesicles (sEVs) have emerged as novel long-range signaling mediators and may play a critical role.

Methods: MI/R was induced by transient ligation of the left anterior descending artery. Cognitive performance was assessed using multiple behavioral tests. sEVs derived from cardiomyocytes were labeled to track their distribution and cellular uptake in the brain. Heart and brain tissues were analyzed for microRNAs (miRNAs) expression using bioinformatics, qPCR, and RNAScope. The role of specific miRNAs was investigated through genetic inhibition of cardiomyocyte-derived sEVs release using Rab27a^f/fMyh6-Cre⁺ mice, pharmacological blockade of exosome, and AAV-mediated overexpression or knockdown.

Results: MI/R mice exhibited significant cognition deficits along with hypothalamic paraventricular nucleus (PVN) synaptic ultrastructural injury and dysfunction. sEVs released from injured cardiomyocytes were significantly elevated and preferentially accumulated in oxytocin neurons from the PVN. Inhibiting cardiomyocyte-derived sEVs ameliorated cognitive impairments and synaptic pathology. Conversely, injection of cardiomyocyte-derived sEVs into the PVN recapitulated MI/R-induced cognitive deficits. Among candidate miRNAs, miR-574-5p was identified as a key mediator. Its inhibition via miRNA sponge restored cognitive function. Bioinformatic analyses revealed that miR-574-5p targets genes involved in synaptic structure and GABA_B receptor signaling.

Conclusions: Cardiomyocyte-derived sEVs contribute to MI/R-induced cognitive impairment through miR-574-5p. Upon delivery to the PVN and uptake by oxytocin neurons, miR-574-5p suppresses synaptic and GABA_B receptor-related proteins, leading to synaptic disruption and cognitive decline. Targeting this pathway may represent a promising therapeutic approach for cognitive dysfunction associated with heart disease.

Background: Over 334,000 deaths in 2021 in the USA were attributed to non-optimal body mass index ([BMI] greater than 20 to 21 kg/m²), with elevated mortality among American Indian and Alaska Native (AIAN), Black, and Latino populations. Disparities in attributable mortality by race, ethnicity, and county are poorly understood. This analysis examined variation by race and/or ethnicity in obesity prevalence (BMI ≥ 30) and years of life lost (YLLs) attributable to non-optimal BMI in 3110 US counties from 2000 to 2019.

Methods: Using survey data from the Behavioral Risk Factor Surveillance System (BRFSS), Gallup Daily, and National Health and Nutrition Examination Survey (NHANES), we estimated obesity prevalence annually, stratified by county, age, sex, and five mutually exclusive racial and/or ethnic populations (AIAN, Asian or Pacific Islander [Asian], Black, Latino or Hispanic [Latino], and White). We calculated population attributable fractions (PAFs) and estimated YLLs attributable to non-optimal BMI for 27 causes of death (focusing on ischemic heart disease [IHD], colorectal cancer, and diabetes) using cause-specific YLL estimates from a previous analysis.

Results: Age-standardized obesity prevalence increased by 12.3 percentage points (95% uncertainty interval 11.9-12.8) to 40.2% (40.0-40.6) in the USA from 2000 to 2019 and was highest in the Black population, followed by the AIAN, Latino, White, and Asian populations. In 2019, the Black population had the highest rates of IHD and colorectal cancer YLLs attributable to non-optimal BMI, followed by the AIAN, White, Latino, and Asian populations. The AIAN population had the highest attributable YLL rate for diabetes in 2019, followed by the Black, Latino, White, and Asian populations. All racial and/or ethnic populations had statistically significant reductions in IHD and diabetes YLL rates attributable to non-optimal BMI from 2000 to 2019, with declines in total YLL rates for these causes more than offsetting increases in obesity prevalence and PAFs. Relative disparities among counties were two to four times as large for attributable YLL rates as for obesity prevalence.

Conclusions: Racial and/or ethnic disparities in obesity prevalence are substantial, but disparities in YLLs attributable to non-optimal BMI are larger because they are compounded by disparities in YLL rates.

Background: Influential theories propose that the complex and heterogeneous clinical and behavioral manifestations of autism spectrum disorder (ASD) arise from dysregulation of neural circuits driven by an imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) neurotransmission. Building on this framework, and considering the role of homeostatic regulation of neuronal excitability in shaping sleep stages, we hypothesized that dysregulation of neuronal network activity-including altered ratios of excitatory drive to interneuronal inhibitory control-might manifest in sleep architecture. An elevated E/I ratio in ASD is expected to render the sleep EEG noisier, less synchronized, and less precisely timed, thereby compromising NREM sleep quality and disrupting memory-related oscillatory coordination.

Methods: To test this hypothesis, we examined sleep patterns in a homogeneous cohort of adults with ASD without intellectual disability and free from pharmacological treatment, compared with neurotypical (NT) controls. We specifically investigated electrophysiological sleep markers that may reflect alterations in cortical excitability and inhibition. Macro- and microstructural features of nocturnal sleep were assessed using in-home polysomnography (PSG), including analyses of periodic EEG components, such as slow oscillations and sleep spindles, and aperiodic metrics of EEG activity.

Results: Our findings revealed sleep-stage-specific PSG differences in ASD, characterized by increased N3 sleep, decreased N2 sleep, and heightened slope and offset of aperiodic EEG activity during NREM sleep relative to NT controls. Moreover, ASD participants showed elevated alpha power during N2, which positively correlated with ADOS total scores. We also observed a steeper slow-oscillation slope, a reduced anterior-posterior gradient in spindle density, and diminished spindle-slow oscillation coupling, collectively indicating atypical thalamocortical network dynamics in ASD. Overall, these spatially distributed and sleep-stage-dependent alterations reflect dysregulated neuronal dynamics, potentially pointing to increased inhibitory activity arising from altered thalamocortical regulation and compensatory mechanisms related to E/I imbalance.

Conclusions: Our study provides novel electrophysiological evidence for a nuanced, sleep-related dysregulation in ASD that varies by sleep stage and cortical region, and subtly diverges from patterns observed in NT controls. Given the mechanistic relevance of sleep for neurodevelopment and circuit homeostasis, these findings offer valuable insights into sleep-related neurophysiological dysregulation in ASD.

Background: Infection is a significant complication of diabetes, yet comprehensive assessments of risk factors for infections in individuals with diabetes are scarce. We aimed to identify risk factor profiles and their contributions to infections in people with type 2 diabetes (T2D).

Methods: This prospective cohort study included 24,021 participants with T2D. Twenty-eight risk factors covering domains of socioeconomic status, lifestyle factors, environmental pollution, psychological factors, clinical biomarkers, and comorbidities and complications were selected. Negative binomial regression models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for infections. Population attributable fractions (PAFs) were calculated to assess the contributions of individual risk factors and domains.

Results: During a median follow‑up of 13.2 years, 9988 infection events occurred among 6517 participants, with an overall incidence rate of 33.5 per 1000 person‑years. Nineteen risk factors were significantly associated with increased infection risks, including high Townsend deprivation index, low education level, low household income, retired or unemployed status, central obesity, unhealthy diet, current smoking, non‑moderate alcohol consumption, unhealthy sleep duration, depression, loneliness, high glycated hemoglobin, low high-density lipoprotein cholesterol, low estimated glomerular filtration rate, cancer, cardiovascular disease, peripheral artery disease, diabetic microvascular complications, and chronic obstructive pulmonary disease. Central obesity was the leading individual contributor to total infections (PAF, 13.2%). Across domains, lifestyle factors contributed most to total infections (joint PAF, 32.7%), followed by socioeconomic status (joint PAF, 26.3%), comorbidities and complications (joint PAF, 25.2%), clinical biomarkers (joint PAF, 17.1%), psychological factors (joint PAF, 6.3%), and environmental pollution (joint PAF, 3.3%).

Conclusions: This study identified a broad array of risk factors for infections in adults with T2D, indicating the importance of comprehensive management strategies for preventing infections among individuals with T2D.

Background: The role of leukocyte telomere length (LTL) in predicting lung cancer risk remains controversial, particularly in individuals with pulmonary nodules.

Methods: We conducted a prospective cohort study of 1803 individuals with pulmonary nodules identified by chest CT, with no prior history of cancer. Relative LTL (rLTL) was measured using quantitative PCR. Lung cancer incidence and mortality were ascertained through linkage with the Chongqing Chronic Disease Surveillance System using ICD-10 code. Associations between rLTL and lung cancer risk were assessed using Cox proportional hazards models, with adjustment for demographic, clinical, and radiological variables. We further evaluated the incremental predictive value of rLTL when added to five established lung nodule malignancy risk models using AUC, NRI, and IDI.

Results: Patients with longer rLTL had an increased risk of lung cancer (adjusted HR = 7.26 (1.71-30.87); P = 0.007), compared with those with shorter rLTL. Subgroup analyses suggested stronger associations in younger individuals and women, although interactions were non-significant. rLTL remained an independent predictor across all five lung nodule models (HR range, 1.47-1.72). While the improvements in AUC and IDI were modest, NRI was significantly improved in all models (range, 0.380-0.847, all P < 0.05), suggesting better risk reclassification.

Conclusion: In this health check-up cohort of individuals with pulmonary nodules, longer rLTL was independently associated with increased lung cancer risk. Our findings highlight a potentially paradoxical role of telomere biology in lung carcinogenesis and suggest that rLTL may serve as a useful biomarker for malignancy risk stratification in nodule surveillance.

Background: Obesity is associated with metabolic dysfunction-associated steatotic liver disease (MASLD). Despite the rising prevalence of obesity among children and adolescents, no studies have examined risk factors or developed models to estimate MASLD burden by sex, age group, or geographic location.

Objective: To estimate and predict the distribution and shifting patterns of the burden of MASLD in children and adolescents aged 5 to 24 years, globally, regionally, and in China.

Methods: We systematically searched PubMed, EMBASE, Web of Science, Cochrane, and CNKI for studies reporting the prevalence of MASLD and its closely related diagnostic constructs, including metabolic dysfunction-associated fatty liver disease (MAFLD) and non-alcoholic fatty liver disease (NAFLD), in 5-24-year-olds, and synthesized evidence across these definitions to estimate the burden of MASLD. Random-effects meta-regression synthesized age-, sex-, and year-specific prevalence and risk factors. Additionally, using data from the Global Burden of Disease, World Population Prospects, and Chinese National Survey on Students' Constitution and Health, a risk factor-based model estimated global, regional, and provincial (China) MASLD burden. The protocol was registered in PROSPERO (CRD420251062351).

Results: Of 2747 records, 56 studies (54 English, 2 Chinese) were included; 37 informed prevalence and 38 informed risk factors. Our model indicated that the global MASLD prevalence among 5-24-year-olds was 7.0% (95% CI: 4.1, 11.7), increasing with age and year, and higher in boys. Asia had the largest number of cases in 2000 (63.8 million [51.5, 76.6]) and 2020 (160.9 million [134.5, 187.6]). Our model further indicated that Africa is projected to surpass Asia in total case numbers from 2040 onward. In China, MASLD prevalence among 6-18-year-olds was highest in Hebei, Shandong, and Beijing (2000) and in Tianjin, Shandong, and Heilongjiang (from 2020 onwards).

Conclusions: The prevalence of MASLD among children and adolescents continues to rise alongside the epidemic of obesity. Model-based estimates suggest that the burden of MASLD may shift over time towards currently less developed regions of the world, such as Africa, and less well-developed regions in China. Targeted investment in obesity prevention is urgently needed, as are health services to reduce the health impacts of MASLD during and beyond childhood and adolescence.

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global public health issue. Beyond genetic variation and behavior-related risk factors, inorganic arsenic, with a broad exposed population, serves as a critical environmental risk factor for MASLD. While hepatic steatosis has been identified as the initiating event of arsenic-induced MASLD, its effect biomarkers and underlying mechanisms remain unclear, a knowledge gap that is crucial for risk monitoring and early intervention. This study aims to identify the biomarkers and potential epigenetic mechanisms of arsenic-induced hepatic steatosis from the perspective of lipid metabolism.

Methods: This study recruited patients with arsenic-poisoned fatty liver and used lipid metabolomics to evaluate serum lipid metabolic profile alterations in these patients. Concurrently, a mouse model exposed to environmentally relevant doses of sodium arsenite (NaAsO₂) was established, with liver lipid metabolomics applied to assess arsenic's impact on lipid metabolic pathways in hepatic steatosis. Furthermore, by combining this mouse model with an in vitro model of NaAsO₂-induced lipid accumulation in hepatocytes, methods including RT-qPCR, Western blotting, and MassARRAY DNA methylation quantification were employed to explore the potential mechanism of arsenic-induced hepatic lipid metabolism disorders. Additionally, in vitro intervention models with phosphatidylcholine (PC) supplements and DNA methyltransferase inhibitors were used to validate this mechanism.

Results: Population studies showed that reduced PC levels are a significant feature of serum lipid profiles in arsenic-poisoned fatty liver patients. The accuracy of distinguishing this disease via decreased PC molecules was 83.33%. Mouse liver lipid metabolomics further revealed this PC collapse results from arsenic inhibiting hepatic choline-to-PC synthesis. Notably, mouse and in vitro studies showed arsenic upregulates DNMT1 and inhibits TET1 and TET2, inducing Chkα/Chkβ promoter hypermethylation to suppress choline-PC synthesis. This reduced triglyceride transporter levels (very-low-density lipoprotein), causing intrahepatic lipid accumulation. Supplementing PC or using DNA methyltransferase inhibitors alleviated these adverse effects in vitro.

Conclusions: This study innovatively identifies reduced serum-specific PC molecules as a potential risk marker for arsenic-induced hepatic steatosis. Chkα/Chkβ hypermethylation-mediated PC synthesis disorder is the key mechanism of arsenic-induced hepatic steatosis, and DNMT1, TET1, and TET2 dysregulation may underlie this hypermethylation. PC supplementation or epigenetic correction shows intervention potential.

Background: Accumulating evidence indicates that SARS-CoV-2 infection is associated with a broad spectrum of post-acute COVID sequelae, including diabetes. While nirmatrelvir/ritonavir and molnupiravir have demonstrated efficacy in reducing acute COVID-19 severity, their protective effects against post-COVID diabetes remain uncertain. In this study, we aimed to evaluate the effectiveness of these antiviral agents in reducing post-COVID diabetes risks, including new-onset diabetes in non-diabetic individuals and exacerbated diabetes in those with pre-existing diabetes.

Methods: We emulate target randomized controlled trials of COVID-19 antivirals in hospitalized patients who tested positive for SARS-CoV-2 between March 11, 2022, and October 10, 2023, in Hong Kong. Two analytic patient cohorts for assessing incident diabetes and exacerbation of diabetes for rehospitalization, including those with or without diabetes confirmed before the index date, were identified. Cloning, censoring, and weighting were used to emulate the target trials of nirmatrelvir/ritonavir and molnupiravir, involving treatment arm and control arm within each trial. Cause-specific Cox proportional hazard model and an extended form of Cox model for modeling recurrent hospitalizations were used to estimate the hazard ratio (HR) between arms in each trial, adjusting for baseline covariates.

Results: Among 88,643 hospitalized patients first time infected by SARS-CoV-2 identified, 35,997 and 18,865 eligible patients were included in the two analytic cohorts for the analysis on newly onset diabetes and exacerbated diabetes for rehospitalization, respectively. The median follow-up period ranged from 344 to 365 days across treatment and control arms of target trials. Compared with the no treatment arm, non-diabetic patients who received nirmatrelvir/ritonavir showed a significantly lower risk of post-COVID incident diabetes (HR: 0.75, 95% CI: 0.61 to 0.92). A reduced risk of diabetes rehospitalizations (HR: 0.70, 95% CI: 0.60 to 0.81) was observed among the diabetic patients. No significant associations were found for the use of molnupiravir and post-COVID diabetes outcomes.

Conclusions: Our study demonstrates the effectiveness of nirmatrelvir/ritonavir in reducing the risks of post-acute COVID sequelae of diabetes in the hospitalized population, regardless of their diabetic status, whereas molnupiravir showed no significant benefit. Our findings offer valuable clinical insights for managing diabetes during the post-acute phase of SARS-CoV-2 infection.

Background: Pain in knee osteoarthritis (KOA) involves maladaptive neuroplastic adaptations within the pain matrix. Tai Chi and transcranial direct current stimulation (tDCS) each alleviate KOA pain, potentially by modulating the dorsolateral prefrontal cortex (DLPFC). Whether combining them yields superior analgesic and neuromodulatory effects remains to be established.

Methods: In this four-arm, parallel-group randomized controlled trial, 152 participants with KOA were allocated to a 12-week intervention: (1) Tai Chi combined with tDCS, (2) Tai Chi, (3) tDCS, or (4) a Health Education Control group. The primary outcome was pain intensity assessed using the Pain subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Secondary outcomes included the WOMAC Stiffness and Physical Function subscales, Visual Analogue Scale (VAS), Knee Injury and Osteoarthritis Outcome Score (KOOS), Timed Up and Go Test (TUGT), and the 36-Item Short Form Health Survey (SF-36). Resting-state functional connectivity (rsFC) between the right DLPFC and key regions of the pain matrix was analyzed using functional magnetic resonance imaging (fMRI). Assessments were conducted at baseline and post-intervention.

Results: The Tai Chi combined with tDCS group demonstrated a significantly greater reduction in WOMAC Pain subscores compared to the Health Education Control group (P < 0.001), the tDCS group (P = 0.003), and the Tai Chi group (P = 0.048). However, the combined intervention did not show statistically superior improvement over Tai Chi group in secondary outcomes. Neuroimaging results indicated that all active interventions decreased rsFC between the right DLPFC and several pain-matrix regions, including the left posterior cingulate cortex, bilateral thalamus, left precuneus, and left superior frontal gyrus. Furthermore, the extent of pain reduction was positively correlated with decreased connectivity between the right DLPFC and both the left posterior cingulate cortex and the left precuneus.

Conclusions: This exploratory trial suggests that combining Tai Chi with tDCS provides superior pain relief compared to either monotherapy in individuals with KOA. Post hoc exploratory neuroimaging analyses further indicate that this analgesic effect may be associated with changes in rsFC between the right DLPFC and regions of the pain matrix.

Trial registration: This study was registered with the Chinese Clinical Trial Registry (ChiCTR2100047287).