Ankylosing spondylitis (AS), a chronic inflammatory disease primarily affecting the axial skeleton, has long been implicated in increased cardiovascular risk, particularly premature myocardial infarction (MI). Despite heightened clinical awareness, the molecular mechanisms bridging chronic systemic inflammation in AS with acute cardiac events have remained elusive. A groundbreaking systems biology investigation now elucidates this connection by identifying key biomarkers and dissecting the pathogenic landscape that conjoins these two seemingly disparate diseases.
Researchers employed integrative bioinformatics to analyze transcriptomic data derived from peripheral blood mononuclear cells obtained from AS patients, MI patients, and healthy controls, across four publicly available microarray cohorts. This meta-analysis utilized weighted gene co-expression network analysis (WGCNA) to pinpoint co-regulated gene modules associated with each condition. Intriguingly, one AS-related gene module demonstrated significant overlap with a module associated with MI, hinting at shared molecular underpinnings. Further refinement through machine learning algorithms—specifically LASSO regression combined with Support Vector Machine Recursive Feature Elimination (SVM-RFE)—narrowed the focus to two pivotal hub genes: S100A12 and MCEMP1. The synchronized elevation of these genes’ transcripts in both AS and MI patients underlines their potential as pivotal mediators at the crossroads of chronic inflammation and acute coronary events.
Performance assessment using receiver operating characteristic (ROC) curves yielded area under the curve (AUC) values ranging from 0.92 to 0.96 for distinguishing patients with combined AS-MI pathology from those with either condition alone. When integrated into a nomogram alongside clinical parameters such as age and C-reactive protein (CRP) levels, the predictive model demonstrated a net reclassification improvement of 34%, a substantial advancement that reinforces the diagnostic utility of these biomarkers. These findings pave the way for refined risk stratification strategies aimed at early identification and intervention in vulnerable populations.
At the functional level, S100A12 and MCEMP1 emerge as critical nodes in immune signaling cascades. Both genes interface with damage-associated molecular pattern (DAMP) signaling, which is pivotal for activating innate immune responses. Their roles extend to facilitating neutrophil extracellular trap (NET) formation, a process implicated in thrombo-inflammation, as well as modulating cholesterol-laden macrophage phenotypes that exacerbate atherosclerotic lesion development. Gene set enrichment analysis (GSEA) further illuminated the enrichment of pathways such as “NOD-like receptor signaling,” “IL-17 cytokine pathway,” and “platelet degranulation,” underscoring the complex immuno-inflammatory milieu that orchestrates AS-related myocardial injury. Computational inference of upstream regulators predicted nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and Signal Transducer and Activator of Transcription 3 (STAT3) as master transcription factors governing these hubs.
Single-cell RNA sequencing of coronary plaques sourced from explanted hearts of AS patients with documented myocardial infarction offered high-resolution insight into the cellular distribution of these markers. Both S100A12 and MCEMP1 exhibited pronounced expression selectively within CD14⁺ classical monocytes and CD16⁺ non-classical monocytes, while showing minimal to no expression in T lymphocytes or fibroblasts. Pseudotime trajectory reconstruction suggested a dynamic process wherein resting monocytes transition into inflammatory macrophages and subsequently differentiate into lipid-associated macrophages, perpetuating local inflammation and plaque instability under concurrent AS and MI conditions.
Evaluating peripheral immune landscape alterations revealed significant shifts in immune cell populations in AS-MI patients’ blood. Computational deconvolution algorithms such as CIBERSORT and xCell detected increased neutrophil levels (~35% compared to ~20% in controls), diminished populations of resting CD4⁺ T cells, and an expansion of myeloid-derived suppressor cells. The expression of S100A12 tightly correlated with neutrophil abundance (correlation coefficient r = 0.78), while MCEMP1 closely tracked the non-classical monocyte fraction (r = 0.81). Further exploration using bulk ATAC-seq footprinting of open chromatin regions revealed epigenetic priming of S100A12 by accessible NF-κB binding motifs, while repression of MCEMP1 was found relieved due to the diminished presence of the microRNA-223-3p binding site in AS-MI patients, highlighting complex regulatory layers influencing their expression.
Integrative transcription factor and microRNA network analysis, leveraging ChIP-seq and miRWalk databases, identified a multifaceted regulatory architecture coupling 24 transcription factors, including RUNX1, CEBPB, and FOS, with nine microRNAs such as miR-155-5p, miR-146a-5p, and miR-223-3p. This intricate network offers 48 putative molecular intervention points, which hold promise for targeted modulation of pathogenic signaling circuits linking AS-induced systemic inflammation and myocardial infarction.
The translational potential of these discoveries was probed through in silico drug repositioning screens targeting the hub gene signature. Three FDA-approved compounds—enzastaurin, meglitinide, and nifedipine—were highlighted as candidates capable of reversing the detrimental transcriptional changes. Enzastaurin, a protein kinase C beta (PKCβ) inhibitor, was predicted to suppress S100A12 expression by interfering with NF-κB activation, supported by molecular docking simulations showing strong binding affinity (ΔG < -8.5 kcal/mol) to the S100A12 promoter region. Meglitinide, a known antidiabetic agent, appeared to inhibit MCEMP1 transcription by disrupting STAT3 recruitment to the gene’s regulatory regions, confirmed by docking to the MCEMP1 3′-UTR microRNA target site. Nifedipine, a calcium-channel blocker with antioxidant properties, demonstrated indirect attenuation of both gene expressions through modulation of oxidative stress-responsive pathways. Validation using LINCS L1000 gene expression signatures revealed that exposure to these drugs reversed the AS-MI transcriptional profile within 24 hours, underscoring their therapeutic promise.
Collectively, this study delineates S100A12 and MCEMP1 as sentinel biomarkers that integrally link chronic systemic inflammation characteristic of ankylosing spondylitis with the acute thrombo-inflammatory events leading to myocardial infarction. Their expression confined primarily to myeloid lineage cells, combined with robust diagnostic accuracy and amenability to pharmacological targeting, positions them at the forefront of efforts to improve cardiovascular risk prediction and develop novel, repurposed therapeutic strategies. Future clinical translation of these findings could fundamentally alter the management paradigm for AS patients, enabling preemptive interventions that abrogate myocardial injury and enhance survival.
The convergence of multi-omic technologies, including transcriptomics, epigenomics, and single-cell profiling, exemplifies the power of systems biology approaches to unravel complex disease interrelationships. This integrative framework not only advances fundamental understanding of AS and MI pathogenesis but also serves as a roadmap for identifying actionable molecular targets in other inflammatory comorbidities. As the global burden of inflammatory and cardiovascular diseases rises, such comprehensive analytic pipelines hold tremendous promise for ushering in precision medicine solutions tailored to molecular disease signatures.
In summary, by unveiling a shared molecular axis governed by S100A12 and MCEMP1, this investigation reframes the pathophysiology of ankylosing spondylitis-associated myocardial infarction. It highlights the intricate crosstalk between innate immune activation, epigenetic regulation, and inflammatory cell plasticity in driving coronary artery disease within this vulnerable patient population. The promising drug repositioning opportunities identified set the stage for accelerated bench-to-bedside translation, potentially revolutionizing prevention and treatment strategies for patients grappling with this dual disease burden.
Article Title: Determining the biomarkers and pathogenesis of myocardial infarction combined with ankylosing spondylitis via a systems biology approach
News Publication Date: 9-Jun-2025
Web References: http://dx.doi.org/10.1007/s11684-025-1132-8
Image Credits: Chunying Liu, Chengfei Peng, Xiaodong Jia, Chenghui Yan, Dan Liu, Xiaolin Zhang, Haixu Song, Yaling Han
