Shared molecular signatures between systemic lupus erythematosus and osteoporosis.

This study explores the molecular interplay between systemic lupus erythematosus (SLE) and osteoporosis (OP), aiming to uncover shared gene signatures and pathways for better treatment approaches. Leveraging microarray data from the Gene Expression Omnibus (GEO) database, we employed weighted gene coexpression network analysis to identify coexpression modules in SLE and OP, with subsequent protein-protein interaction analysis clarifying the connections among shared genes. Key genes were pinpointed using CytoHubba and random forest algorithms, validated across independent GEO datasets, and further analyzed through gene set enrichment analysis (GSEA) and immune infiltration studies. We discovered two highly correlated modules in SLE and OP, isolating 30 shared genes and identifying GBP1, SOCS1, IFI16, and XAF1 as central to both conditions. Notably, XAF1 and GBP1 mRNA levels were significantly elevated in the peripheral blood of SLE patients compared with healthy and RA counterparts, underscoring their potential as biomarkers. GSEA and immune infiltration analyses indicated pronounced immune and inflammatory responses, especially in interferon signaling pathways, implicating these core-shared gene networks in the diseases' pathogenesis. The findings highlight the involvement of GBP1, SOCS1, IFI16, and XAF1 in SLE with concurrent OP and suggest that targeting immune and inflammatory responses, particularly through interferon pathways, may offer therapeutic promise for these intertwined conditions.

A high reticulocyte count is a risk factor for the onset of metabolic dysfunction-associated steatotic liver disease: Cross-sectional and prospective studies of data of 310,091 individuals from the UK Biobank.

Background and Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) poses a considerable health risk. Nevertheless, its risk factors are not thoroughly comprehended, and the association between the reticulocyte count and MASLD remains uncertain. This study aimed to explore the relationship between reticulocyte count and MASLD. Methods: A total of 310,091 individuals from the UK Biobank were included in this cross-sectional study, and 7,316 individuals were included in this prospective study. The cross-sectional analysis categorized reticulocyte count into quartiles, considering the sample distribution. Logistic regression models examined the connection between reticulocyte count and MASLD. In the prospective analysis, Cox analysis was utilized to investigate the association. Results: Our study findings indicate a significant association between higher reticulocyte count and an elevated risk of MASLD in both the cross-sectional and prospective analyses. In the cross-sectional analysis, the adjusted odds ratios (ORs) of MASLD increased stepwise over reticulocyte count quartiles (quartile 2: OR 1.22, 95% CI 1.17-1.28, p < 0.001; quartile 3: OR 1.44; 95% CI 1.38-1.51, p < 0.001; quartile 4: OR 1.66, 95% CI 1.59-1.74, p < 0.001). The results of prospective analyses were similar. Conclusion: Increased reticulocyte count was independently associated with a higher risk of MASLD. This discovery offers new insights into the potential of reticulocytes as biomarkers for MASLD.