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机器学习与孟德尔随机化整合分析发现 PALMD 是特发性眼眶炎性假瘤的预后生物标志物

Integrated machine learning and Mendelian randomization reveal PALMD as a prognostic biomarker for nonspecific orbital inflammation.

机构信息

Hunan University of Chinese Medicine, Changsha, 410208, Hunan, China.

Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying, 257091, Shandong, People's Republic of China.

出版信息

Sci Rep. 2024 Oct 14;14(1):24020. doi: 10.1038/s41598-024-74409-1.

Abstract

BACKGROUND

Nonspecific Orbital Inflammation (NSOI) remains a perplexing enigma among proliferative inflammatory disorders. Its etiology is idiopathic, characterized by distinctive and polymorphous lymphoid infiltration within the orbital region. Preliminary investigations suggest that PALMD localizes within the cytosol, potentially playing a crucial role in cellular processes, including plasma membrane dynamics and myogenic differentiation. The potential of PALMD as a biomarker for NSOI warrants meticulous exploration.

METHODS

PALMD was identified through the intersection analysis of common DEGs from datasets GSE58331 and GSE105149 from the GEO database, alongside immune-related gene lists from the ImmPort database, using Lasso regression and SVM-RFE analysis. GSEA and GSVA were conducted with gene sets co-expressed with PALMD. To further investigate the correlation between PALMD and immune-related biological processes, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate immune microenvironment characteristics of each sample. The expression levels of PALMD were subsequently validated using GSE105149.

RESULTS

Among the 314 DEGs identified, several showed significant differences. Lasso and SVM-RFE algorithms pinpointed 15 hub genes. Functional analysis of PALMD emphasized its involvement in cell-cell adhesion, leukocyte migration, and leukocyte-mediated immunity. Enrichment analysis revealed that gene sets positively correlated with PALMD were enriched in immune-related pathways. Immune infiltration analysis indicated that resting dendritic cells, resting mast cells, activated NK cells, and plasma cells positively associate with PALMD expression. Conversely, naive B cells, activated dendritic cells, M0 and M1 macrophages, activated mast cells, activated CD4 memory T cells, and naive CD4 T cells showed a negative correlation with PALMD expression. PALMD demonstrated significant diagnostic potential in differentiating NSOI.

CONCLUSIONS

This study identifies PALMD as a potential biomarker linked to NSOI, providing insights into its pathogenesis and offering new avenues for tracking disease progression.

摘要

背景

非特异性眼眶炎症(NSOI)仍然是增殖性炎症性疾病中的一个令人困惑的谜。其病因是特发性的,其特征是眼眶区域内独特的多形性淋巴样浸润。初步研究表明,PALMD 定位于细胞质内,可能在细胞过程中发挥关键作用,包括质膜动力学和肌生成分化。PALMD 作为 NSOI 生物标志物的潜力值得细致探索。

方法

通过在 GEO 数据库的 GSE58331 和 GSE105149 数据集以及 ImmPort 数据库的免疫相关基因列表中使用 Lasso 回归和 SVM-RFE 分析,对共同的 DEGs 进行交集分析,识别出 PALMD。进行 GSEA 和 GSVA 分析,以研究与 PALMD 共表达的基因集。为了进一步研究 PALMD 与免疫相关生物过程的相关性,使用 CIBERSORT 算法和 ESTIMATE 方法评估每个样本的免疫微环境特征。随后使用 GSE105149 验证 PALMD 的表达水平。

结果

在鉴定的 314 个 DEGs 中,有几个显示出显著差异。Lasso 和 SVM-RFE 算法确定了 15 个枢纽基因。PALMD 的功能分析强调了它参与细胞-细胞粘附、白细胞迁移和白细胞介导的免疫。富集分析表明,与 PALMD 呈正相关的基因集在免疫相关途径中富集。免疫浸润分析表明,静息树突状细胞、静息肥大细胞、活化 NK 细胞和浆细胞与 PALMD 表达呈正相关。相反,幼稚 B 细胞、活化树突状细胞、M0 和 M1 巨噬细胞、活化肥大细胞、活化 CD4 记忆 T 细胞和幼稚 CD4 T 细胞与 PALMD 表达呈负相关。PALMD 在区分 NSOI 方面具有显著的诊断潜力。

结论

本研究确定 PALMD 为与 NSOI 相关的潜在生物标志物,为其发病机制提供了新的见解,并为跟踪疾病进展提供了新的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c97/11473641/2d18f969e3f5/41598_2024_74409_Fig1_HTML.jpg

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