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Ankylosing spondylitis (AS) is linked to an increased prevalence of myocardial infarction (MI). However, research dedicated to elucidating the pathogenesis of AS-MI is lacking. In this study, we explored the biomarkers for enhancing the diagnostic and therapeutic efficiency of AS-MI. Datasets were obtained from the Gene Expression Omnibus database. We employed weighted gene co-expression network analysis and machine learning models to screen hub genes. A receiver operating characteristic curve and a nomogram were designed to assess diagnostic accuracy. Gene set enrichment analysis was conducted to reveal the potential function of hub genes. Immune infiltration analysis indicated the correlation between hub genes and the immune landscape. Subsequently, we performed single-cell analysis to identify the expression and subcellular localization of hub genes. We further constructed a transcription factor (TF)-microRNA (miRNA) regulatory network. Finally, drug prediction and molecular docking were performed. S100A12 and MCEMP1 were identified as hub genes, which were correlated with immune-related biological processes. They exhibited high diagnostic value and were predominantly expressed in myeloid cells. Furthermore, 24 TFs and 9 miRNA were associated with these hub genes. Enzastaurin, meglitinide, and nifedipine were predicted as potential therapeutic agents. Our study indicates that S100A12 and MCEMP1 exhibit significant potential as biomarkers and therapeutic targets for AS-MI, offering novel insights into the underlying etiology of this condition.
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http://dx.doi.org/10.1007/s11684-025-1132-8 | DOI Listing |
Kidney Blood Press Res
September 2025
Objective: Cisplatin-induced acute kidney injury (Cis-AKI) is a significant cause of renal damage, characterized by tubular injury, ferroptosis, and oxidative stress. While therapeutic options for Cis-AKI remain limited, identifying novel targets to prevent kidney injury is critical. This study focuses on GALNT14, a gene associated with ferroptosis, and its potential role in mitigating Cis-AKI.
View Article and Find Full Text PDFGenome Biol
September 2025
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
Background: Soil salinization represents a critical global challenge to agricultural productivity, profoundly impacting crop yields and threatening food security. Plant salt-responsive is complex and dynamic, making it challenging to fully elucidate salt tolerance mechanism and leading to gaps in our understanding of how plants adapt to and mitigate salt stress.
Results: Here, we conduct high-resolution time-series transcriptomic and metabolomic profiling of the extremely salt-tolerant maize inbred line, HLZY, and the salt-sensitive elite line, JI853.
Eur J Gastroenterol Hepatol
September 2025
Department of Gastroenterology, First Affiliated Hospital of Shantou University Medical College, Shantou.
Background: Crohn's disease (CD) and rheumatoid arthritis (RA) are autoimmune diseases. CD is known to be closely associated with RA. However, the mechanisms underlying these relationships remain unclear.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Department of Biology, Duke University, Durham, NC 27708.
Organisms use circadian clocks to synchronize physiological processes to anticipate the Earth's day-night cycles and regulate responses to environmental signals to gain competitive advantage. While divergent genetic clocks have been studied extensively in bacteria, fungi, plants, and animals, an ancient conserved circadian redox rhythm has been recently reported. However, its biological function and physiological outputs remain elusive.
View Article and Find Full Text PDFPsychopharmacology (Berl)
September 2025
Institute of Cardiovascular Research, Sleep Medical Center, Department of Psychiatry, Fundamental and Clinical Research on Mental Disorders Key Laboratory of Luzhou, Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province, 646000, China.
Rationale: Genome-wide association studies (GWASs) are used to identify genetic variants for association with schizophrenia (SCZ) risk; however, each GWAS can only reveal a small fraction of this association.
Objectives: This study systematically analyzed multiple GWAS data sets to identify gene subnetwork and pathways associated with SCZ.
Methods: We identified gene subnetwork using dmGWAS program by combining SCZ GWASs and a human interaction network, performed gene-set analysis to test the association of gene subnetwork with clinical symptom scores and disease state, meanwhile, conducted spatiotemporal and tissue-specific expression patterns and cell-type-specific analysis of genes in the subnetwork.