EBioMedicine最新文献

Background: Adiponectin is a circulating adipokine involved in energy metabolism and inflammation, with reported protective effects against cardiometabolic diseases such as type 2 diabetes (T2D) and early kidney disease. However, its regulation remains poorly understood. This study aimed to identify epigenetic loci associated with adiponectin levels.

Methods: DNA methylation was profiled using Illumina 450K and EPIC (850K) arrays in 315 Ghanaians (RODAM-Pros study) and 593 Nigerians (AADM study). Differentially methylated positions (DMPs) were identified using linear regression models adjusted for age, sex, BMI, blood cell proportions, and technical covariates. Analyses were stratified by T2D status and cohort, then meta-analysed to identify DMPs associated with adiponectin across T2D status (combining participants with-and-without diabetes). RNA-seq data on 77 blood, 49 subcutaneous adipose tissue (SAT), and 55 skeletal muscle samples from the AADM study were used to identify eQTMs for identified DMPs.

Findings: We identified three epigenome-wide significant DMPs: cg03546163 (Z-score = 5.76, p ≤ 0.001, 5'UTR of FKBP5), cg02561343 (Z-score = 5.11, p ≤ 0.001, within UST), and cg23969380 (Z-score = 5.13, p ≤ 0.001, ADGRD1 body). cg03546163 was an eQTM for PLA2G12B in SAT (beta = -0.039, FDR = 0.047), cg02561343 for PSMD8 (beta = -11.85, FDR = 0.029) and TECR (beta = -9.48, FDR = 0.029) in SAT, and cg23969380 for HIGD2AP1 (beta = -0.095, FDR = 0.024) in blood. These genes have been reported to be involved in lipid metabolism (PLA2G12B and TECR), proteasomal degradation (PSMD8), and cellular stress-responses (HIGD2AP1).

Interpretation: This epigenome-wide study of adiponectin in sub-Saharan African populations identified DNA methylation loci potentially involved in adiponectin regulation through lipid-metabolism, inflammation, proteostasis, and stress-response pathways. These findings provide a foundation for replication and further investigation to improve understanding of the role of adiponectin in cardiometabolic-health.

Funding: National Institutes of Health and European Research Council.

Background: Environmental stress and iron deficiency are increasingly recognised as prevalent challenges during pregnancy, with significant implications for both maternal and foetal health. Environmental stressors such as chronic maternal anxiety can elevate cortisol levels and trigger inflammatory responses which might subsequently disrupt foetal brain development. Concurrently, iron deficiency during critical windows of gestation can hinder the formation of brain structures and neurotransmitter systems vital for emotional regulation and cognitive function after birth. Iron deficiency and exposure to stress are among the most prevalent nutritional and environmental challenges during pregnancy, and their combined influence may substantially increase the risk of neuropsychiatric disorders in the offspring. Although the individual effects of each factor are relatively well understood, their interaction during gestation remains unexplored.

Methods: In the present study, we employed human placental samples from mildly stressed and non-stressed mothers, a chronic environmental stress mouse model, and advanced in vitro techniques to examine whether gestational environmental stress alters placental iron transport.

Findings: Our findings indicate that stress enhanced placental iron uptake and accumulation, but paradoxically reduced iron transfer to the foetus-an effect observed exclusively in females and reproducible in vitro following both stress exposure and dexamethasone treatment.

Interpretation: These results provide insights into the sex-specific impact of environmental stress on placental and foetal iron availability and highlight a previously unrecognised pathway through which prenatal stress could influence long-term health trajectories in the offspring.

Funding: This study was supported by the Swiss National Science Foundation (SNF grant no. 310030_197408), the Swiss National Science Foundation via the National Center of Competence in Research (NCCR) TransCure, University of Bern, Switzerland (grant no. 51NF40_185544) and the Swiss 3R Competence Centre (3RCC; grant no OC-2019-019). TF was supported by the Hans Sigrist Foundation, Switzerland.

Background: Most gastric cancer (GC) patients receive uniform treatment due to the lack of predictive biomarkers for chemotherapy or radiotherapy. We previously identified epithelial-mesenchymal transition (EMT) and metabolism subgroups in GC cell lines based on kinomic profiles, but their clinical relevance was unknown.

Methods: We developed an ensemble model using 37 kinases that differed between cell line subgroups to classify stage II-IV GC into EMT and metabolism subgroups. Survival differences between those who received chemotherapy or radiotherapy and those who did not were compared within each subgroup to validate the model effectiveness in predicting therapeutic response. An iteration approach was further applied to optimise and validate the feature set via multiple publicly-available datasets.

Findings: An 11-kinase signature stratified 893 patients into two subgroups. The metabolism subgroup showed significantly better survival with chemotherapy (HR_{multivariable} = 0.56) and radiotherapy (HR_{multivariable} = 0.55), whereas no such improvement was observed in the EMT subgroup. Significant interaction between kinomic subgroups and treatments were noted. The chemotherapy benefits between subgroups were greater with 5-fluorouracil-based regimens than cisplatin-based ones. This kinomic taxonomy was distinct from Lauren classification and previous transcriptomic subtypes and also suggested differential therapeutic vulnerabilities between subgroups.

Interpretation: This model holds promise for optimising chemotherapy and radiotherapy decisions for GC.

Funding: Biomedicine Discovery Scholarship and Graduate Research Completion Award, Monash University; National Natural Science Foundation of China (81602165) (C.H.). Australian Research Council Centre of Excellence for the Mathematical Analysis of Cellular Systems (CE230100001) (L.K.N.).

Background: Lung cancer is mainly diagnosed in elderly adults, yet the incidence of early-onset disease in people aged ≤45 years is increasing. Current screening strategies largely target elder populations, leaving younger individuals at risk of delayed diagnosis and adverse outcomes. Phenotypic Age Acceleration (PhenoAgeAccel), which indicates the difference between biological age and chronological age, has been associated with cancer susceptibility, but its role in early-onset lung cancer is unclear.

Methods: We performed a case-control and prognostic cohort study in China, including 222 early-onset lung cancer patients and 222 age- and sex-matched healthy volunteers, and externally validated findings in the UK Biobank. PhenoAgeAccel was calculated from routinely available haematological and biochemical markers. Logistic regression models estimated associations between PhenoAgeAccel and lung cancer risk. Survival analyses assessed the relationship between PhenoAgeAccel and overall survival among early-onset patients.

Findings: Early-onset lung cancer patients had substantially higher PhenoAgeAccel than matched controls (P < 0.001). PhenoAgeAccel was associated with a dose-dependent increase in early-onset lung cancer risk (odds ratio [OR] = 1.18; 95% CI: 1.14-1.23). Subgroup analyses by chronological age demonstrated a stronger association in earlier adulthood, whereas associations among elder adults (≥65 years) were not significant. In early-onset patients, higher PhenoAgeAccel predicted worse overall survival (hazard ratio [HR] = 2.17; 95% CI: 1.20-3.93). Results were corroborated in the UK Biobank cohort.

Interpretation: PhenoAgeAccel is positively associated with both a greater risk of early-onset lung cancer and poorer prognosis, supporting its potential utility for early detection and risk stratification in younger populations.

Funding: National Natural Science Foundation of China (no. 82303969); Beijing Xisike Clinical Oncology Research Foundation (no. Y-2024AZ [EGFR]MS-0079); Beijing Natural Science Foundation (no. 7222144).

Background: Guttate psoriasis (GP) is associated with streptococcal throat infection. Neutrophils are the first immune cells to respond to Group A Streptococcal (GAS) infection, but detailed analysis of their contribution to GP pathogenesis is lacking. The study primarily focuses on phenotyping the neutrophils located at the site of inflammation in GP skin and understanding their specific contribution to the pathogenesis of the disease.

Methods: Here, we performed a comprehensive immunophenotypic and transcriptomic analysis of neutrophils from blood and inflamed GP skin using high-dimensional single-cell protein and RNA analyses. Ex vivo stimulation of neutrophils and co-culture with CD4⁺ T cells was performed to validate the function of neutrophil subsets upon GAS stimulation.

Findings: We uncovered high diversity of human neutrophils in GP, with enrichment of an immature subset in GP skin that exhibited antigen processing and presentation signature. A similar subset in healthy controls was observed only upon ex vivo stimulation of neutrophils with GAS bacteria. Additionally, the GAS-induced neutrophil subset was found to induce CD4⁺ T cell proliferation mediated by HLA-DR. Other neutrophil subsets that expanded in GP were characterised by enrichment of genes related to neutrophil migration, formation of neutrophil extracellular traps and phagocytosis.

Interpretation: Our study depicts the landscape of neutrophils in GP skin and highlights HLA-DR⁺ neutrophils with possible role in disease pathogenesis.

Funding: This work was supported by HudFonden, Psoriasisfonden, Gösta A Karlssons 60-års fond, Magnus Bergvall stiftelse, Åke Wibergs stiftelse, and Karolinska Institute. AP was supported by HudFonden. PA was partially supported by Karolinska Institute's doctoral funding (KID). LPM was supported by grants from Svenska Sällskapet för Medicinsk Forskning (SSMF) and European Society of Clinical Microbiology and Infectious Diseases (ESCMID). UN was supported by grants from the Swedish Research Council. JL was supported by Region Stockholm (clinical postdoctoral appointment). ML was supported by the Swedish Childhood Cancer research fund and the Karolinska Institute. Part of the data handling was enabled by resources at project number SNIC-2021/22-49 provided by the Swedish National Infrastructure for Computing (SNIC), partially funded by the Swedish Research Council through grant agreement no. 2018-05973.

Background: Lung cancer is the leading cause of cancer-related deaths. Diagnosis at late stages is common due to the largely non-specific nature of presenting symptoms contributing to high mortality. There is a lack of specific, minimally invasive low-cost tests to screen patients ahead of the diagnostic biopsy.

Methods: 344 patients experiencing symptoms from the lung clinic of Lister hospital suspected of lung cancer were recruited. Predictive covariates were successfully generated on 170 patients from Computed Tomography (CT) scans using CT Texture Analysis (CTTA) and Deep Learning Autoencoders (DLA) as well as from peripheral blood data for immunity using high depth flow-cytometry and for exosome protein components. Predictive signatures were formed by combining covariates using Bayesian regression on a randomly chosen 128-patient training set and validated on a 42-patient held-out set. Final signatures were generated by fusing the data sources at different levels.

Findings: Immune, CTTA and DLA single modality signatures had overall AUCs of 0.69, 0.70 and 0.73 respectively. The final combined signature had a ROC AUC of 0.81. The overall sensitivity and specificity were 0.72 and 0.77 respectively.

Interpretation: Combining immune monitoring with CT scan data is an effective approach to improving sensitivity and specificity of Lung cancer screening even in patients experiencing symptoms.

Funding: CRUK [C1519/A27375], Wellcome Trust/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z], NIHR Clinical Research Facility at Guy's and St Thomas' NHS Foundation Trust, NIHR Biomedical Research Centre.

Background: Beyond their classical roles in haemostasis and thrombosis, platelets have been recognised as active regulators of immune responses. However, whether platelets can function as immune sensors capable of monitoring immune status remains largely unexplored.

Methods: We first analysed platelet transcriptomes from patients at different stages following haematopoietic stem cell transplantation (HSCT) to assess their ability to capture immune reconstitution dynamics. We then employed immune cell-platelet co-incubation experiments to elucidate the mechanistic role of RNA transfer in reshaping platelet immune molecular profiles. Subsequently, platelet transcriptomes were examined in immune-related conditions, including HSCT-associated acute graft-versus-host disease (aGVHD), cytomegalovirus (CMV) DNAemia, and immune-inflammatory diseases such as systemic lupus erythematosus (SLE) and ulcerative colitis (UC), to evaluate their capacity to identify disease-specific immune dysregulation. Finally, machine learning models were developed based on platelet immune gene signatures to assess diagnostic performance.

Findings: Platelet transcriptomes accurately reflected the dynamics of immune reconstitution following HSCT. Mechanistically, immune cells directly reprogrammed platelet immune-related molecular features through RNA transfer. Moreover, platelets sensitively detected immune alterations associated with transplant complications, including aGVHD and CMV DNAemia, and effectively monitored immune activity and inflammatory states in SLE and UC. Machine learning models based on platelet immune gene profiles further improved diagnostic accuracy across disease settings.

Interpretation: This study establishes platelets as precise, readily accessible, and noninvasive immune sensors, extending their functional repertoire from immune regulation to immune surveillance and diagnosis in immune-related diseases.

Funding: National Natural Science Foundation of China; CAMS Innovation Fund for Medical Sciences; Science and Technology Projects of Xizang Autonomous Region, China; National Key Research and Development Program of China; Tianjin Municipal Science and Technology Commission Grant; and Natural Science Foundation of Tianjin.

Background: The association and mechanisms between biotin and dementia remain unclear.

Methods: We investigated the association through a population and animal study. UK Biobank data were used to evaluate the association of biotin with incident dementia and brain structural alteration. To validate our findings, we established a biotin-deficient mouse model, and performed behavioural tests, immunofluorescence, RT-qPCR, Western blotting, and molecular docking.

Findings: In humans, higher biotin intake was significantly associated with reduced risks of all-cause dementia (moderate: 0.83 [0.74-0.94]; high: 0.78 [0.68-0.89]), Alzheimer's disease (AD, moderate: 0.74 [0.61-0.89]; high: 0.79 [0.64-0.98]), and delayed-onset dementia (DOD, moderate: 0.810 [0.715-0.918]; high: 0.776 [0.672-0.896]), but not vascular dementia (VD) and early-onset dementia (EOD). Neuroimaging results revealed a "pseudo-atrophy" pattern-reduced cortical volume with increased tissue intensity-resembling structural remodelling rather than neurodegeneration. In mice, biotin deficiency triggered region-specific alteration of APP, PSEN1, and APOE in the hippocampus and prefrontal cortex. It was accompanied by elevated Aβ42 levels and an increased Aβ42/40 ratio. Molecular docking suggested that biotin physically interacts with the catalytic pocket of PSEN1 and the receptor-binding domain of APOE.

Interpretation: Dietary biotin is associated with a lower risk of dementia, especially AD, potentially by inhibiting amyloidogenic processing and modulating APOE-mediated clearance. The observed neuroimaging and molecular patterns suggest that maintaining adequate biotin intake is a viable strategy for dementia prevention.

Funding: This work was supported by the National Natural Science Foundation of China (No. 82273619).

Background: Periodontitis poses a significant threat to human oral health, and microorganisms serving as the initiating factor in its pathogenesis. Parvimonas micra (P. micra), a Gram-positive anaerobic bacterium prevalent within the oral cavities of patients with periodontitis, remains underexplored in terms of its full contribution to periodontitis pathogenesis.

Methods: 16S rRNA sequencing was performed on human gingival crevicular fluid samples, whilst micro-CT was used in experimental rat models to assess the impact of P. micra on periodontitis progression. Single-cell RNA sequencing was employed to examine dynamic alterations in rat periodontal cell composition and the enrichment of gene pathways during P. micra infection. Finally, His pull-down assay combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to identify key virulence factors of P. micra and host cell receptors.

Findings: In this study, we examined the abundance of P. micra in gingival crevicular fluid and validated its pathogenic potential in vivo. Single-cell RNA sequencing revealed that P. micra disrupted the periodontal immune and mineralisation microenvironment. Further investigation showed that P. micra manipulated its surface adhesins to bind receptors on periodontal ligament stem cells, activating the intracellular NF-κB and ERK1/2 signalling pathways and impairing osteogenic activity. Finally, we identified a mechanism by which P. micra employed a surface protein to evade autophagic clearance, thereby facilitating immune escape.

Interpretation: This study identifies P. micra as a pivotal periodontal pathogen, and the elucidation of its molecular mechanisms provides potential therapeutic targets for periodontitis and related systemic conditions.

Funding: This work was supported by the National Natural Science Foundation of China (No. 82270980, 82071122), Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0501400), Taishan TePin Scientist Project of Shandong Province (tstp20250546), the Natural Science Foundation of Jiangsu Province (No. BK20240268), High-Level Hospital Construction Project of Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University (No. 0024C035), Shandong Provincial Key Research and Development Program (Competitive Innovation Platform, 2025CXPT042), the Major Innovation Projects in Shandong Province (No. 2021SFGC0502), and the Shandong Province Key Research and Development Program (No. 2021ZDSYS18).