The influence of shift work: A bibliometric analysis of research progress and frontiers on health effects.

Shift work has been found to disrupt the circadian system, leading to negative health effects. The objective of this study was to assess the progress and frontiers in research on the health-related influence of shift work. The study analyzed 3,696 data points from Web of Science, using the bibliometric software CiteSpace to visualize and analyze the field. The results showed a steady increase in annual publications, particularly in the last 5 years, with a rapid increase in publications from China. The United States contributed the most to the number of publications and worldwide collaborations. The most prolific institution and author were the Brigham and Women's Hospital and Professor Bjorn Bjorvatn, respectively. The Journal of Chronobiology International ranked at the top and focused primarily on shift worker research. In the first decade of study, the primary focus was on the associations between shift work and cardiovascular disease and metabolic disorders. Over time, research on the health effects of shift work has expanded to include cancer and mental health, with subsequent studies investigating molecular mechanisms. This study provides a comprehensive and intuitive analysis of the negative health impacts of shift work. It highlights existing research hotspots and provides a roadmap for future studies. Further research is needed to explore the adverse health consequences and related mechanisms of shift work exposure, as well as interventions to mitigate its health effects.

Comprehensive analysis on subchondral bone marrow lesions of human osteoarthritis by integrating bulk and single-cell transcriptomes.

OBJECTIVE: This study aims to demonstrate the cellular composition and underlying mechanisms in subchondral bone marrow lesions (BMLs) of knee osteoarthritis (OA). METHODS: BMLs were assessed by MRI Osteoarthritis Knee Score (MOAKS)≥2. Bulk RNA-sequencing (bulk-seq) and BML-specific differentially expressed genes (DEGs) analysis were performed among subchondral bone samples (including OA-BML=3, paired OA-NBML=3; non-OA=3). The hub genes of BMLs were identified by verifying in independent datasets and multiple bioinformatic analyses. To further estimate cell-type composition of subchondral bone, we utilized two newly developed deconvolution algorithms (MuSiC, MCP-counter) in transcriptomic datasets, based on signatures from open-accessed single-cell RNA sequencing (scRNA-seq). Finally, competing endogenous RNA (ceRNA) and transcription factor (TF) networks were constructed through multiple predictive databases, and validated by public non-coding RNA profiles. RESULTS: A total of 86 BML-specific DEGs (up 79, down 7) were identified. IL11 and VCAN were identified as core hub genes. The "has-miR-424-5p/lncRNA PVT1" was determined as crucial network, targeting IL11 and VCAN, respectively. More importantly, two deconvolution algorithms produced approximate estimations of cell-type composition, and the cluster of heterotopic-chondrocyte was discovered abundant in BMLs, and positively correlated with the expression of hub genes. CONCLUSION: IL11 and VCAN were identified as the core hub genes of BMLs, and their molecular networks were determined as well. We profiled the characteristics of subchondral bone at single-cell level and determined that the heterotopic-chondrocyte was abundant in BMLs and was closely linked to IL11 and VCAN. Our study may provide new insights into the microenvironment and pathological molecular mechanism of BMLs, and could lead to novel therapeutic strategies.

The effect of systemic iron status on osteoarthritis: A mendelian randomization study.

Objective: To assess the causal effect of systemic iron status by using four biomarkers (serum iron; transferrin saturation; ferritin; total iron-binding capacity) on knee osteoarthritis (OA), hip OA, total knee replacement, and total hip replacement using 2-sample Mendelian randomization (MR) design. Methods: Three instrument sets were used to construct the genetic instruments for the iron status: Liberal instruments (variants associated with one of the iron biomarkers), sensitivity instruments (liberal instruments exclude variants associated with potential confounders), and conservative instruments (variants associated with all four iron biomarkers). Summary-level data for four OA phenotypes, including knee OA, hip OA, total knee replacement, and total hip replacement were obtained from the largest genome-wide meta-analysis with 826,690 individuals. Inverse-variance weighted based on the random-effect model as the main approach was conducted. Weighted median, MR-Egger, and Mendelian randomization pleiotropy residual sum and outlier methods were used as sensitivity MR approaches. Results: Based on liberal instruments, genetically predicted serum iron and transferrin saturation were significantly associated with hip OA and total hip replacement, but not with knee OA and total knee replacement. Statistical evidence of heterogeneity across the MR estimates indicated that mutation rs1800562 was the SNP significantly associated with hip OA in serum iron (odds ratio, OR = 1.48), transferrin saturation (OR = 1.57), ferritin (OR = 2.24), and total-iron binding capacity (OR = 0.79), and hip replacement in serum iron (OR = 1.45), transferrin saturation (OR = 1.25), ferritin (OR = 1.37), and total-iron binding capacity (OR = 0.80). Conclusion: Our study suggests that high iron status might be a causal factor of hip OA and total hip replacement where rs1800562 is the main contributor.

Osteophytes mediate the associations between cartilage morphology and changes in knee symptoms in patients with knee osteoarthritis.

AIMS: To investigate whether the associations between cartilage defects and cartilage volumes with changes in knee symptoms were mediated by osteophytes. METHODS: Data from the Vitamin D Effects on Osteoarthritis (VIDEO) study were analyzed as a cohort. The Western Ontario and McMaster Universities Osteoarthritis Index was used to assess knee symptoms at baseline and follow-up. Osteophytes, cartilage defects, and cartilage volumes were measured using magnetic resonance imaging at baseline. Associations between cartilage morphology and changes in knee symptoms were assessed using linear regression models, and mediation analysis was used to test whether these associations were mediated by osteophytes. RESULTS: A total of 334 participants (aged 50 to 79 years) with symptomatic knee osteoarthritis were included in the analysis. Cartilage defects were significantly associated with change in total knee pain, change in weight-bearing pain, and change in non-weight-bearing pain after adjustment for age, sex, body mass index, and intervention. Cartilage volume was significantly associated with change in weight-bearing pain and change in physical dysfunction after adjustment. Lateral tibiofemoral and patellar osteophyte mediated the associations of cartilage defects with change in total knee pain (49-55%) and change in weight-bearing pain (61-62%) and the association of cartilage volume with change in weight-bearing pain (27-30%) and dysfunction (24-25%). Both cartilage defects and cartilage volume had no direct effects on change in knee symptoms. CONCLUSIONS: The significant associations between cartilage morphology and changes in knee symptoms were indirect and were partly mediated by osteophytes.