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Hip pain is a common musculoskeletal complaint that leads many people to seek medical attention. We conducted a primary genome-wide association study (GWAS) on the hip pain phenotype within the UK Biobank cohort. Sex-stratified GWAS analysis approach was also performed to explore sex specific variants associated with hip pain. We found seven different loci associated with hip pain at GWAS significance level, with the most significant single nucleotide polymorphism (SNP) being rs77641763 within the EXD3 ( p value = 2.20 × 10 –13 ). We utilized summary statistics from the FinnGen cohort and a previous GWAS meta-analysis on hip osteoarthritis as replication cohorts. Four loci (rs509345, rs73581564, rs9597759, rs2018384) were replicated with a p value less than 0.05. Sex-stratified GWAS analyses revealed a unique locus within the CUL1 gene (rs4726995, p  = 2.56 × 10 –9 ) in males, and three unique loci in females: rs1651359966 on chromosome 7 ( p  = 1.15 × 10 –8 ), rs552965738 on chromosome 9 ( p  = 2.72 × 10 –8 ), and rs1978969 on chromosome 13 ( p  = 2.87 × 10 –9 ). This study has identified seven genetic loci associated with hip pain. Sex-stratified analysis also revealed sex specific variants associated with hip pain in males and females. This study has provided a foundation for advancing research of hip pain and hip osteoarthritis.

Background Current human retina studies predominantly utilize post-mortem tissue, and the sample accessibility constraints make the characterization of the living human retina at single-cell resolution a challenge. Although single-nucleus RNA-seq expands the utility of frozen samples, it provides a nuclear-centric view, potentially missing key cytoplasmic information and transient biological processes. Thus, it is important to generate resources directly from living human retinal tissue to complement existing datasets. Methods We profiled 106,829 single cells from nine unfrozen human retina samples. Living samples were collected within 10 min of therapeutic enucleation and four postmortem samples were collected within 6 h. After standardized dissociation, single-cell transcriptomes were generated using 10x Genomics 3’ RNA-seq and applied scVI to generate batch-corrected integrated atlas. Major cell types and subtypes were annotated through iterative Leiden clustering, canonical markers. Subsequent analyses included differential expression comparisons between cell states and regulon activity profiling to further characterize cellular identities and regulatory networks. Transcriptional dynamics were assessed using RNA velocity, and cell-cell signaling pathways were inferred with CellChat. Key findings were validated in independent samples from two additional donors (four samples) using the identical workflow. Results We contribute to establishing a reference for retinal cell type proportions and cellular states. Our analysis revealed ELF1-mlCone, a distinct cluster of mlCone photoreceptors identified by distinct transcriptional features. The presence and transcriptional features of this cluster were validated in independent samples. Additionally, by comparing living and post-mortem samples, our study highlights differences in transcriptional dynamics: living tissue preserved coherent RNA velocity streams, enabling clear dynamic state transitions, while post-mortem tissue exhibited disorganized patterns. These findings suggest that using living tissue can improve the capture of active cellular states and transitions. Conclusions Our atlas provides a single-cell reference contrasting living versus early postmortem human retina, integrating cell type composition, transcriptional diversity, and functional insights. It may serve as a useful resource for retinal research and for understanding aspects of human retinal biology, particularly given its inclusion of living tissue and diverse pathological states.

Widespread pain is a hallmark characteristic of fibromyalgia, commonly affecting older individuals. This study aimed to identify novel genetic variants associated with widespread pain by utilizing the extensive UK Biobank dataset. We conducted a primary genome-wide association study (GWAS) using a novel definition of widespread pain, defined as pain experienced all over the body during the past month. Sex-stratified GWAS analysis approach was also performed to analyze the impact of sex on widespread pain. The primary GWAS identified one novel significant genetic locus (rs34691025, = 1.76 × 10 ) on chromosome 5q13.2 within the gene and several loci that approached genome-wide significance. The sex-stratified GWAS outputs revealed biological difference widespread pain between males and females, with a novel locus identified in the female-specific analysis within the gene on chromosome 10. Genetic Correlation analysis demonstrated significant genetic correlations between widespread pain and other phenotypes, including joint disorders and spondylosis. The PheWAS revealed associations between the significant genetic variants with hearing disorders and cardiovascular diseases. A two-sample Mendelian randomization analysis found no significant causal association between hearing loss and widespread pain. Our study advances the understanding of the genetic factors contributing to widespread pain, highlighting notable differences between males and females and identifying a novel genetic locus associated with this condition.

Diabetic retinopathy (DR) remains a principal cause of vision impairment worldwide, involved complex retinal cellular pathophysiology that remains incompletely understood. To elucidate cell-type-specific molecular signatures underlying DR, we generated a high-resolution single-cell transcriptomic atlas of 297,121 retinal cells from 20 Chinese donors, including non-diabetic controls (26.4%), diabetic without retinopathy (23.4%) and DR (50.2%). Following rigorous quality control, batch-effect correction, and clustering and annotation, 10 major retinal cell populations were delineated. Differential expression analyses across disease states within each cell type yielded candidate gene sets, which were further refined via a multi-stage machine-learning pipeline combining L1-regularized logistic regression and recursive feature elimination with cross-validation, alongside bootstrap stability selection. Resulting cell-type-specific classifiers achieved high accuracy (79–95%) and AUCs (0.85–0.99) in distinguishing DR disease states. Enrichment analyses implicated immune activation, oxidative stress, neurodegeneration and synaptic dysfunction pathways across multiple cell types in retina. Integrating 567 unique marker genes from all cell types, a general multilayer perceptron classifier achieved 95.31% overall accuracy on held-out test data, demonstrating the translational potential of these signatures for non-diabetic controls, diabetic without retinopathy and DR classification. This high-resolution atlas and the accompanying analytic framework provide a robust computational framework for biomarker discovery, mechanistic insight and targeted intervention strategies in diabetic retinal diseases.

Single-cell RNA sequencing (scRNA-seq) has significantly advanced our understanding of retinal aging, yet the specific molecular characteristics within cell populations remain incompletely defined. We profiled 223,612 single cells from 18 unfrozen human retinas obtained from 13 Chinese donors aged 34–92 years, providing an ethnically specific atlas across the adult lifespan. A sparsity-driven machine-learning (ML) pipeline (L1-regularized logistic regression, recursive feature elimination with cross-validation) identified age-discriminatory genes within each major retinal cell type, complemented by gene set scoring for cellular senescence and metabolic pathways. Using integrated differential expression and ML feature selection, we identified eleven major retinal cell populations and observed aging-associated shifts. ML classifiers achieved high accuracy (80–96%), particularly for microglia (96%), revealing mitochondria-centric aging signatures in rods and bipolar cells, proteostasis and retinoid metabolism in cones, and structural-RNA maintenance signatures in horizontal cells. This study delivers the first ML-derived, cell-type-specific aging gene signatures for the human retina in a Chinese cohort, offering a reference for population-tailored biomarker discovery.

The human retina exhibits complex cellular heterogeneity which is critical for visual function, yet comprehensive ethnic-specific references are scarce in ophthalmic transcriptomics. The lack of single-cell RNA sequencing (scRNA-seq) data from Asian populations particularly Chinese donors imposes significant limitations in understanding population-specific retinal biology. We constructed the first comprehensive single-cell transcriptomic atlas of the human retina from Chinese donors, generated through high-throughput scRNA-seq of ∼290,000 viable cells obtained from 18 fresh retinal specimens (living donor and post-mortem specimens). Our multi-level analysis identified 10 distinct retinal cell types, encompassing all major neuronal lineages, Müller glia, astrocytes, microglia. Detailed subcluster analyses further revealed extensive heterogeneity, identifying distinct subtypes within several cell populations such as 7 amacrine cell subtypes and 14 bipolar cell subtypes. Concurrently, through systematic analysis of delineated subtype-specific molecular programs, we mapped their associated biological signaling pathways, functions, and mechanistic processes. This analysis explained the critical involvement of these subpopulations in core biological processes including synaptic organization, neurotransmission, and phototransduction cascades, potentially governing retinal homeostatic regulation and disease mechanisms. Single-cell transcriptomic atlas of the human retina from Chinese donors describes a comprehensive cellular landscape, encompassing major cell types and subtypes including neuronal, glial, and immune populations. This ethnic-specific atlas provided an important reference for understanding retinal development, cellular interaction and disease pathogenesis in Chinese populations, addressing a longstanding gap in ophthalmic transcriptomic resources.

AbstractDiabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we perform single-cell RNA sequencing of thirteen human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We uncover three distinct microglial states—homeostatic, stress-response, and inflammatory—along a functional continuum, rather than discrete activation states, with dynamic transitions occurring throughout disease progression. Trajectory analysis indicates bifurcating paths starting from the homeostatic state branching toward stress-response and inflammatory states. Three major functional modules: ribosomal/translation, coordinated immune cell function, and inflammatory/transcriptional regulation, showing disease-specific activation patterns were identified. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.Competing Interest StatementThe authors have declared no competing interest.

The human retina has a remarkable diversity of cell types, which is crucial for understanding the mechanisms underpinning visual development and function. While single-cell RNA sequencing (scRNA-seq) has advanced our understanding of retinal biology, most studies have relied on postmortem or frozen samples, potentially missing important transcriptional information. The aim of this study was to create the first comprehensive scRNA-seq atlas of fresh human retinal samples from living donors and recently deceased individuals using scRNA-seq technology. A total of 106,829 cells were analyzed, which were collected from nine retinal samples using standardized scRNA-seq workflow. Our findings identified several novel subtypes of known retinal cells, including new subgroups of cones and amacrine cells (ACs), each characterized by distinct gene expression profiles. Notably, we discovered a novel cone subtype, the ELF1-Cone, which shows a clear developmental trajectory from mlCone precursors. This subtype exhibits unique functional properties and metabolic profiles, regulated by key transcription factors ELF1 and PRKAA1. We also identified five distinct AC subtypes, including three GABAergic ACs, each with unique gene expression profiles and functional characteristics. Our study highlights the critical importance of using fresh human retinal tissue for accurate cellular mapping and trajectory inference. Significant differences were observed between fresh and postmortem retinal samples in terms of pseudo time analysis such as RNA velocity. We also performed a comparative analysis of diabetic without retinopathy, diabetic retinopathy, and non-diabetic samples, suggesting diabetes-related transcriptional variation. In conclusion, we present a comprehensive human retina atlas using fresh samples that contribute to existing knowledge of retinal cell diversity, function, and transcriptional profiles. Our study is a milestone for future studies that will improve understanding of retinal biology and disease mechanisms.

Bacterial infection in skin and soft tissue has emerged as a critical concern. Overreliance on antibiotic therapy has led to numerous challenges, including the emergence of multidrug-resistant bacteria and adverse drug reactions. It is imperative to develop non-antibiotic treatment strategies that not only exhibit potent antibacterial properties but also promote rapid wound healing and demonstrate biocompatibility. Herein, a novel multimodal synergistic antibacterial system (SNO-CS@MoS 2 ) was developed. This system employs easily surface-modified thin-layer MoS 2 as photothermal agents and loaded with S-nitrosothiol-modified chitosan (SNO-CS) via electrostatic interactions, thus realizing the combination of NO gas therapy and photothermal therapy (PTT). Furthermore, this surface modification renders SNO-CS@MoS 2 highly stable and capable of binding with bacteria. Through PTT’s thermal energy, SNO-CS@MoS 2 rapidly generates massive NO, collaborating with PTT to achieve antibacterial effects. This synergistic therapy can swiftly disrupt the bacterial membrane, causing protein leakage and ATP synthesis function damage, ultimately eliminating bacteria. Notably, after effectively eliminating all bacteria, the residual SNO-CS@MoS 2 can create trace NO to promote fibroblast migration, proliferation, and vascular regeneration, thereby accelerating wound healing. This study concluded that SNO-CS@MoS 2 , a novel multifunctional nanomaterial with outstanding antibacterial characteristics and potential to promote wound healing, has promising applications in infected soft tissue wound treatment.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer and is associated with poor prognosis. The histone H3 lysine 36 methyltransferase SET-domain-containing 2 (SETD2) has been reported to be expressed at low levels and frequently mutated in ccRCC. Ferroptosis, a form of death distinct from apoptosis and necrosis, has been reported in recent years in renal cancer. However, the relationship between SETD2 and ferroptosis in renal cancer is not clear. Here, we demonstrated that SETD2 was expressed at low levels in ccRCC and was associated with poor prognosis. Moreover, we found that knockdown of SETD2 increased lipid peroxidation and Fe 2+ levels in tumor cells, thereby increasing the sensitivity of erastin, a ferroptosis inducer. Mechanistically, histone H3 lysine 36 trimethylation (H3K36me3) which was catalyzed by SETD2, interacted with the promoter of ferrochelatase (FECH) to regulate its transcription and ferroptosis-related signaling pathways. In conclusion, the presesnt study revealed that knockdown of the epigenetic molecule, SETD2, significantly increases the sensitivity of ferroptosis inducers which promotes tumor cell death, thereby indicating that SETD2 may be a potential therapeutic target for ccRCC.