Determining IFI44 as a key lupus nephritis's biomarker through bioinformatics and immunohistochemistry

Lupus nephritis (LN) emerges as a severe complication of systemic lupus erythematosus (SLE), significantly affecting patient survival. Despite improvements in treatment reducing LN's morbidity and mortality, existing therapies remain suboptimal, emphasizing the necessity for early detection to improve patient outcomes.

This study employs bioinformatics and machine learning to identify and validate potential LN biomarkers using immunohistochemistry (IHC). It explores the relationship between these biomarkers and the clinical and pathological characteristics of LN, assessing their prognostic significance. The research provides deeper mechanistic insights by employing Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Additionally, the study characterizes the immune profiles of LN patients through the CIBERSORT algorithm, focusing on the role of interferon-inducible protein 44 (IFI44) as a key biomarker.

IFI44 shows elevated expression in LN-affected kidneys, compared to healthy controls. The levels of IFI44 positively correlate with serum creatinine and the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and inversely with serum complement C3 and initial estimated glomerular filtration rate (eGFR).

IFI44 is identified as a promising biomarker for LN, offering potential to refine the assessment of disease progression and predict clinical outcomes. This facilitates the development of more personalized treatment strategies for LN patients.