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Abstract：
BACKGROUND: Osteoporosis (OP), often referred to as the \"silent disease of the twenty-first century,\" poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking.
METHODS: This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).
RESULTS: Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.
CONCLUSIONS: This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.
METHODS: This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).
RESULTS: Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.
CONCLUSIONS: This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.
摘要：
背景：骨质疏松症（OP），通常被称为“二十一世纪的无声疾病”，“由于其严重性，构成了重大的公共卫生问题，慢性性质，和进步课程，主要影响绝经后妇女和老年人。该疾病的发病机制和进展与肿瘤代谢途径的失调有关。值得注意的是,谷氨酰胺的代谢利用已成为癌症生物学中的关键角色。虽然代谢重编程已在各种恶性肿瘤中得到广泛研究，并与临床结果相关，它在OP背景下的全面调查仍然缺乏。
方法：本研究旨在通过全面的生物信息学分析来鉴定和验证与OP相关的潜在谷氨酰胺代谢基因（GlnMgs）。GlnMgs的鉴定是通过整合加权基因共表达网络分析和一组28个候选GlnMgs来实现的。随后，使用基因集变异分析阐明了与GlnMgs相关的推定生物学功能和途径。LASSO方法用于识别关键枢纽基因，并评估了5种选定的GlnMGs在OP检测中的诊断功效。此外,研究了hubGlnMgs与临床特征之间的关系。最后,使用独立的数据集(GSE2208,GSE7158,GSE56815和GSE35956)验证了5种GlnMGs的表达水平.
结果：五个GlnMgs，即IGKC,TMEM187,RPS11,IGLL3P,GOLGA8N,在这项研究中确定。为了深入了解它们的生物学功能，特别强调突触传递GABA能，内向整流钾通道活性，和溶酶体膜的细胞质侧。此外，这五个GlnMGs在区分患有OP的个体方面的诊断潜力产生了有希望的结果，表明它们作为OP的区别标志物的功效。
结论：本研究发现了5种与OP相关的GlnMGs。他们揭示了OP的潜在新生物标志物并跟踪其进展。
方法：本研究旨在通过全面的生物信息学分析来鉴定和验证与OP相关的潜在谷氨酰胺代谢基因（GlnMgs）。GlnMgs的鉴定是通过整合加权基因共表达网络分析和一组28个候选GlnMgs来实现的。随后，使用基因集变异分析阐明了与GlnMgs相关的推定生物学功能和途径。LASSO方法用于识别关键枢纽基因，并评估了5种选定的GlnMGs在OP检测中的诊断功效。此外,研究了hubGlnMgs与临床特征之间的关系。最后,使用独立的数据集(GSE2208,GSE7158,GSE56815和GSE35956)验证了5种GlnMGs的表达水平.
结果：五个GlnMgs，即IGKC,TMEM187,RPS11,IGLL3P,GOLGA8N,在这项研究中确定。为了深入了解它们的生物学功能，特别强调突触传递GABA能，内向整流钾通道活性，和溶酶体膜的细胞质侧。此外，这五个GlnMGs在区分患有OP的个体方面的诊断潜力产生了有希望的结果，表明它们作为OP的区别标志物的功效。
结论：本研究发现了5种与OP相关的GlnMGs。他们揭示了OP的潜在新生物标志物并跟踪其进展。
