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Published Erratum
. 2025 Nov 14:16:1732027.
doi: 10.3389/fendo.2025.1732027. eCollection 2025.

Correction: Bioinformatic analysis identifies LPL as a critical gene in diabetic kidney disease via lipoprotein metabolism

Qian Dong #  1 , Huan Xu #  1 , Pengjie Xu  1 , Jiang Liu  1 , Zhouji Shen  1
Affiliations
Published Erratum

Correction: Bioinformatic analysis identifies LPL as a critical gene in diabetic kidney disease via lipoprotein metabolism

Qian Dong et al. Front Endocrinol (Lausanne). .

Abstract

[This corrects the article DOI: 10.3389/fendo.2025.1620032.].

Keywords: bioinformatic; diabetic kidney disease; immune cell infiltration; lipid metabolism; lipoprotein lipase.

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Figures

Figure 5
Figure 5
Consensus clustering analysis of five hub genes in DKD patients. (A) Cumulative Distribution Function (CDF) curve for consensus clustering with different values of k. (B) Consensus matrix for clustering, showing optimal stability at k=2, resulting in two molecular subtypes (Cluster A and Cluster B) based on the expression of hub genes. (C) Expression levels of the hub genes (LPL, BCAM, SERPINE2, GCNT3, and CTNNBIP1) in the two identified subtypes. ***P<0.001. (D) Heatmap of gene expression between Cluster A and Cluster B **P<0.01.
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