Abstract

Lupus nephritis (LN) is an autoimmune nephropathy associated with systemic lupus erythematosus. Circadian rhythms are involved in the development of several diseases, especially inflammation-related diseases, but their relationship with LN is unclear. This was an integrative bioinformatics study. The expression profile from glomeruli, tubular interstitium and renal whole tissue samples was used to assess the expression levels and relevance of circadian rhythm-related genes. To screen for circadian rhythm-related signatures, we employed the LASSO and SVM-RFE algorithms. A consensus clustering algorithm was used to classify LN patients into two circadian rhythm patterns (cluster A and cluster B). We made immune cell infiltration analysis. We used the weighted gene co-expression network analysis (WGCNA) algorithm to identify cluster-specific differentially expressed genes. Nephroseq data were used to observe the relationship between genes and renal function. We found more significant differences in circadian rhythm-related gene expression in LN glomeruli compared with tubulointerstitial and whole-kidney tissues. We established a circadian rhythm-related signature consisting of eight genes that can easily distinguish LN from healthy individuals. Patients in cluster A were associated with B-cell-dominated immunity, whereas patients in cluster B were associated with T-cell-dominated immunity. As most of the patients with proliferative LN combined with membranous LN belonged to cluster B, patients in cluster B may have more severe renal pathology compared with patients in cluster A. Fifteen circadian rhythm-related genes associated with LN and LN typing were screened using the WGCNA algorithm, with COL1A2 and DOCK2 associated with renal prognosis. This study found that circadian rhythms are associated with the occurrence of LN, providing new ideas for the development of new LN treatment options from the perspective of circadian rhythms.

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