Development and validation of potential molecular subtypes and signatures of ocular sarcoidosis based on autophagy-related gene analysis.

IF 1.6 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Open Medicine Pub Date : 2025-08-05 eCollection Date: 2025-01-01 DOI:10.1515/med-2025-1243
Zixuan Wu, Xi Long, Kang Tan, Xiaolei Yao, Qinghua Peng
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引用次数: 0

Abstract

Background: Sarcoidosis is characterized by the proliferation of noncaseating granulomas and presents as a complex chronic inflammatory disease. Autophagy plays a crucial role in the initiation, progression, and treatment resistance of various cancers. Despite the recognized importance of autophagy, the involvement of autophagy-related genes (ARGs) in the pathophysiology of ocular sarcoidosis (OS) remains largely unexplored.

Methods: We intersected differentially expressed genes with a curated list of 177 ARGs to identify candidates potentially involved in OS. Advanced methodologies, including GSEA and GSVA, were employed to explore the biological functions. Further refinement using Lasso regression and SVM-RFE allowed for the identification of key hub genes and the assessment of their diagnostic potential for OS.

Results: Our investigation identified 11 ARGs (DRAM1, SOGA1, ATG16L2, FYCO1, ATG7, ATG12, ATG14, KIAA0226, KIAA1324, KIAA1324L, and KIAA0226L) closely associated with OS. Functional analyses revealed their involvement in processes such as extracellular stimulus, response to nutrient levels, and positive regulation of catabolic process. Importantly, the diagnostic capabilities of these ARGs demonstrated significant efficacy in distinguishing OS from unaffected states.

Conclusions: Through rigorous bioinformatics analyses, this study identifies 11 ARGs as novel biomarker candidates for OS, elucidating their potential roles in the disease's pathogenesis.

基于自噬相关基因分析的眼结节病潜在分子亚型和特征的开发和验证。
背景:结节病以非干酪化肉芽肿增生为特征,是一种复杂的慢性炎症性疾病。自噬在各种癌症的发生、发展和治疗抵抗中起着至关重要的作用。尽管自噬的重要性已得到公认,但自噬相关基因(ARGs)在眼结节病(OS)病理生理中的作用仍未得到充分研究。方法:我们将差异表达基因与177个ARGs进行交叉分析,以确定可能参与OS的候选基因。采用先进的方法,包括GSEA和GSVA来探索生物功能。使用Lasso回归和SVM-RFE进一步细化,可以识别关键枢纽基因并评估其诊断OS的潜力。结果:共鉴定出与OS密切相关的11种ARGs (DRAM1、SOGA1、ATG16L2、FYCO1、ATG7、ATG12、ATG14、KIAA0226、KIAA1324、KIAA1324L和KIAA0226L)。功能分析显示它们参与细胞外刺激、对营养水平的反应和分解代谢过程的积极调节等过程。重要的是,这些ARGs的诊断能力在区分OS和未受影响状态方面显示出显著的功效。结论:通过严格的生物信息学分析,本研究确定了11种ARGs作为OS的新的生物标志物候选物,阐明了它们在疾病发病机制中的潜在作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Open Medicine
Open Medicine Medicine-General Medicine
CiteScore
3.00
自引率
0.00%
发文量
153
审稿时长
20 weeks
期刊介绍: Open Medicine is an open access journal that provides users with free, instant, and continued access to all content worldwide. The primary goal of the journal has always been a focus on maintaining the high quality of its published content. Its mission is to facilitate the exchange of ideas between medical science researchers from different countries. Papers connected to all fields of medicine and public health are welcomed. Open Medicine accepts submissions of research articles, reviews, case reports, letters to editor and book reviews.
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