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Background <p>Atrial fibrillation (AF) is a prevalent arrhythmia associated with significant adverse outcomes and elevated mortality rates, though its underlying molecular mechanisms remain poorly understood. This study sought to identify key genes linked to AF through the integration of transcriptome analysis and Mendelian randomization (MR), supplemented by bioinformatics.</p> Methods <p>Differentially expressed genes (DEGs) were identified by comparing patients with AF to those without the condition. MR analysis was used to assess causal relationships between key genes and expression quantitative trait loci-associated outcomes. Single-cell sequencing, combined with Area Under the Curve for Single Cell analysis, was used to assess the activity of immune and metabolic pathways. This was further complemented by immunoinfiltration analysis.</p> Results <p>Among the 503 DEGs identified—312 upregulated and 191 downregulated—MR analysis highlighted <i>ST8SIA4</i> and <i>SLPI</i> as potential protective genes in AF pathogenesis. <i>ST8SIA4</i> was predominantly enriched in immune and inflammatory pathways and demonstrated associations with γδ T cells, M2 macrophages, and CD8<sup>+</sup>T cells. Conversely, <i>SLPI</i> was implicated in coagulation pathways, with expression observed in endothelial cells, macrophages, and T cells, and exhibited a negative correlation with eosinophil levels.</p> Conclusions <p><i>ST8SIA4</i> and <i>SLPI</i> are associated with a reduced AF risk highlighting their potential involvement in the pathogenesis of the disease and their promise as therapeutic targets<i>.</i></p>

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Integration of transcriptome and mendelian randomization analyses to explore the molecular mechanisms of atrial fibrillation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月2日

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  • Mei-juan Zheng,
  • Jiao Wang,
  • Yu-chun Yang,
  • Zhen Bao,
  • Ruo-nan Wang,
  • Muhuyati Wulasihan

摘要

Background

Atrial fibrillation (AF) is a prevalent arrhythmia associated with significant adverse outcomes and elevated mortality rates, though its underlying molecular mechanisms remain poorly understood. This study sought to identify key genes linked to AF through the integration of transcriptome analysis and Mendelian randomization (MR), supplemented by bioinformatics.

Methods

Differentially expressed genes (DEGs) were identified by comparing patients with AF to those without the condition. MR analysis was used to assess causal relationships between key genes and expression quantitative trait loci-associated outcomes. Single-cell sequencing, combined with Area Under the Curve for Single Cell analysis, was used to assess the activity of immune and metabolic pathways. This was further complemented by immunoinfiltration analysis.

Results

Among the 503 DEGs identified—312 upregulated and 191 downregulated—MR analysis highlighted ST8SIA4 and SLPI as potential protective genes in AF pathogenesis. ST8SIA4 was predominantly enriched in immune and inflammatory pathways and demonstrated associations with γδ T cells, M2 macrophages, and CD8+T cells. Conversely, SLPI was implicated in coagulation pathways, with expression observed in endothelial cells, macrophages, and T cells, and exhibited a negative correlation with eosinophil levels.

Conclusions

ST8SIA4 and SLPI are associated with a reduced AF risk highlighting their potential involvement in the pathogenesis of the disease and their promise as therapeutic targets.