Gluconeogenesis related gene signatures as biomarkers for nonspecific orbital inflammation

Abstract

Nonspecific orbital inflammation (NSOI) is a chronic, idiopathic inflammatory disorder marked by persistent tissue proliferation and immune activation. Gluconeogenesis, a core metabolic pathway enabling endogenous glucose production in the absence of dietary input, plays a vital role in cellular energy homeostasis and immune regulation. Metabolic rewiring of immune cells is not merely a consequence of inflammation but a critical determinant of disease trajectory in orbital disorders. Within this conceptual landscape, the exploration of gluconeogenesis represents a logical and timely extension, offering potential insights into how alternative metabolic pathways may orchestrate immune cell function and fibrotic responses in the orbital microenvironment. Differentially expressed genes (DEGs) were intersected with a curated list of 53 gluconeogenesis-related genes (GRGs) to pinpoint candidates potentially involved in NSOI. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), were employed to elucidate biological functions. Further refinement using Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) facilitated the identification of key hub genes and evaluated their diagnostic potential for NSOI. Our investigation identified seven GRGs, ADH5, BPGM, PGM1, ADH4, ADH1B, G6PC3, ALDH1B1, that are closely associated with NSOI. Functional analyses revealed their involvement in processes such as pyruvate metabolic process, hexose metabolic process, monosaccharide metabolic process. Notably, the diagnostic capabilities of these GRGs demonstrated significant efficacy in distinguishing NSOI from unaffected states. Through rigorous bioinformatics analyses, this study identifies ADH5, BPGM, PGM1, ADH4, ADH1B, G6PC3, ALDH1B1 as novel biomarker candidates for NSOI, shedding light on their potential roles in the disease's pathogenesis.

Keywords: Biomarker candidates; Cell communication; Gluconeogenesis-related gene; Immune infiltration; Nonspecific orbital inflammation.

Fig. 1

Framework.

Fig. 2

Principal component analysis. (a) Difference analysis. (b) Correlation analysis. (c) GO. (d) KEGG.

Fig. 3

The GRGs signature. (a): Regression of LASSO. (b): Cross-validation. (c and d): Accuracy and error. (e): Venn. (f): AUC of seven hub genes. (g): AUC of train group.

Fig. 4

GSEA and GSVA of Analysis in G6PC3 and PGM1. (a and c): GO. (b and d): KEGG.

Fig. 5

Immunological Environment. (a) Immune cell. (b) Correlation between GRGs and immune cells. (c) G6PC3. (d) PGM1.

Fig. 6

Gene regulatory networks of GRGs.

Fig. 7

miRNAs-LncRNAs shared Genes Network. Note: Red circles are mrnas, blue quadrangles are miRNAs, and green triangles are lncRNAs.

Fig. 8

Validation of hub genes.

Fig. 9

Model verification. (a) Residual expression patterns. (b) Model expression patterns. (c) AUC of the model. (d) AUC of the test group.