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<p>This chronic inflammatory condition of the skin known as psoriasis manifests through abnormal epidermal growth patterns and irregular immune system responses. Ribosome biogenesis-related genes (RiboSisRGs), as pivotal regulators of cell proliferation and immune response, potentially modulate disease progression through protein synthesis regulation. However, their comprehensive role remains insufficiently elucidated. This investigation sought to delineate the molecular network of RiboSisRGs in psoriasis through integrative analysis of transcriptomes based on bulk sequencing and single-cell sequencing, construct a high-accuracy diagnostic model, and investigate their interactions with the immune microenvironment. Multi-center transcriptomic datasets were consolidated, enabling differential expression analysis, weighted gene coexpression network analysis (WGCNA), and machine learning-driven hub gene identification. Cellular heterogeneity was assessed via single-cell sequencing, while immune infiltration analysis quantified immune cell populations. Functional enrichment and regulatory networks were systematically analyzed to elucidate molecular mechanisms. Eleven RiboSisRGs demonstrating significant associations with psoriasis were identified, culminating in the development of a 6-gene diagnostic model (<i>MXD1</i>, <i>SCO2</i>, <i>FOSL1</i>, <i>STAT1</i>, <i>LTF</i>, <i>DEPDC1B</i>) with robust predictive performance (AUC &gt; 0.9). Immune profiling indicated dysregulation of regulatory T cells (Tregs) and dendritic cells (DCs), whereas single-cell analysis revealed cell-type-specific expression patterns in keratinocytes and monocytes. Functional enrichment analysis indicated that the model genes influence disease progression primarily via NF-κB and <i>IL-17</i> signaling pathways. This study systematically integrates bulk sequencing and single-cell sequencing transcriptomic data for the first time to characterize the molecular network of RiboSisRGs in psoriasis, yielding a diagnostic model with substantial clinical translational potential. The immune microenvironment analysis elucidated the mechanistic basis of Tregs imbalance and <i>STAT1</i>-mediated inflammatory polarization, presenting novel avenues for targeted therapeutic interventions.</p>

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Single-cell multi-omics of ribosome biogenesis-related genes reveals immune microenvironment in psoriasis and constructs a diagnostic model

  • 期刊论文

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  • 发表日期：

    2025年11月11日

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  • Yunpeng Xu,
  • Shengxiu Liu

摘要

This chronic inflammatory condition of the skin known as psoriasis manifests through abnormal epidermal growth patterns and irregular immune system responses. Ribosome biogenesis-related genes (RiboSisRGs), as pivotal regulators of cell proliferation and immune response, potentially modulate disease progression through protein synthesis regulation. However, their comprehensive role remains insufficiently elucidated. This investigation sought to delineate the molecular network of RiboSisRGs in psoriasis through integrative analysis of transcriptomes based on bulk sequencing and single-cell sequencing, construct a high-accuracy diagnostic model, and investigate their interactions with the immune microenvironment. Multi-center transcriptomic datasets were consolidated, enabling differential expression analysis, weighted gene coexpression network analysis (WGCNA), and machine learning-driven hub gene identification. Cellular heterogeneity was assessed via single-cell sequencing, while immune infiltration analysis quantified immune cell populations. Functional enrichment and regulatory networks were systematically analyzed to elucidate molecular mechanisms. Eleven RiboSisRGs demonstrating significant associations with psoriasis were identified, culminating in the development of a 6-gene diagnostic model (MXD1, SCO2, FOSL1, STAT1, LTF, DEPDC1B) with robust predictive performance (AUC > 0.9). Immune profiling indicated dysregulation of regulatory T cells (Tregs) and dendritic cells (DCs), whereas single-cell analysis revealed cell-type-specific expression patterns in keratinocytes and monocytes. Functional enrichment analysis indicated that the model genes influence disease progression primarily via NF-κB and IL-17 signaling pathways. This study systematically integrates bulk sequencing and single-cell sequencing transcriptomic data for the first time to characterize the molecular network of RiboSisRGs in psoriasis, yielding a diagnostic model with substantial clinical translational potential. The immune microenvironment analysis elucidated the mechanistic basis of Tregs imbalance and STAT1-mediated inflammatory polarization, presenting novel avenues for targeted therapeutic interventions.