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剖析膜性狼疮性肾炎和特发性膜性肾病中IgG亚类与补体的关系。

Dissecting the relationships of IgG subclasses and complements in membranous lupus nephritis and idiopathic membranous nephropathy.

作者信息

Na Woong, Yi Kijong, Song Young Soo, Park Moon Hyang

机构信息

Department of Pathology, College of Medicine, Hanyang University, Seoul, Korea.

Department of Pathology, Konyang Univsersity Hospital, Daejeon, Korea.

出版信息

PLoS One. 2017 Mar 23;12(3):e0174501. doi: 10.1371/journal.pone.0174501. eCollection 2017.

Abstract

Membranous lupus nephritis (MLN) and idiopathic membranous nephropathy (IMN) are kidney diseases with similar morphology, but distinct etiologies, both producing glomeruli with immune deposits. Immunoglobulins and complements, the main components of the deposits, can be detected by immunofluorescence (IF) microscopy. Previous researches characterized the immune deposits only individually, but not the interactions between them. To study these relationships we analyzed an IF profile of IgG subclasses and complements (IgG1, IgG2, IgG3, IgG4, C3, C1q, and C4) in 53 and 95 cases of biopsy-confirmed MLNs and IMNs, respectively, mainly using information theory and Bayesian networks. We identified significant entropy differences between MLN and IMN for all markers except C3 and IgG1, but mutual information (a measure of mutual dependence) were not significantly different for all the pairs of markers. The entropy differences between MLN and IMN, therefore, were not attributable to the mutual information. These findings suggest that disease type directly and/or indirectly influences the glomerular deposits of most of IgG subclasses and complements, and that the interactions between any pair of the markers were similar between the two diseases. A Markov chain of IgG subclasses was derived from the mutual information about each pair of IgG subclass. Finally we developed an integrated disease model, consistent with the previous findings, describing the glomerular immune deposits of the IgG subclasses and complements based on a Bayesian network using the Markov chain of IgG subclasses as seed. The relationships between the markers were effectively explored by information theory and Bayesian network. Although deposits of IgG subclasses and complements depended on both disease type and the other markers, the interaction between the markers appears conserved, independent from the disease type. The disease model provided an integrated and intuitive representation of the relationships of the IgG subclasses and complements in MLN and IMN.

摘要

膜性狼疮性肾炎(MLN)和特发性膜性肾病(IMN)是形态相似但病因不同的肾脏疾病,两者均会产生伴有免疫沉积物的肾小球。沉积物的主要成分免疫球蛋白和补体可通过免疫荧光(IF)显微镜检测到。以往的研究仅对免疫沉积物进行了单独表征,而未研究它们之间的相互作用。为了研究这些关系,我们分别分析了53例活检确诊的MLN和95例活检确诊的IMN中IgG亚类和补体(IgG1、IgG2、IgG3、IgG4、C3、C1q和C4)的IF图谱,主要采用信息论和贝叶斯网络。我们发现,除C3和IgG1外,MLN和IMN在所有标志物上均存在显著的熵差异,但所有标志物对之间的互信息(一种相互依赖性的度量)并无显著差异。因此,MLN和IMN之间的熵差异并非归因于互信息。这些发现表明,疾病类型直接和/或间接影响大多数IgG亚类和补体的肾小球沉积物,并且两种疾病中任何一对标志物之间的相互作用相似。从每对IgG亚类的互信息中得出了IgG亚类的马尔可夫链。最后,我们基于先前的研究结果,开发了一个综合疾病模型,该模型使用IgG亚类的马尔可夫链作为种子,基于贝叶斯网络描述了IgG亚类和补体的肾小球免疫沉积物。信息论和贝叶斯网络有效地探索了标志物之间的关系。尽管IgG亚类和补体的沉积物既取决于疾病类型,也取决于其他标志物,但标志物之间的相互作用似乎是保守的,与疾病类型无关。该疾病模型提供了MLN和IMN中IgG亚类与补体关系的综合且直观的表示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d463/5363951/631909cde4e1/pone.0174501.g001.jpg

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