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Identification of autoantibody clusters that best predict lupus disease activity using glomerular proteome arrays
Quan Li Zhen, … , Chaim Putterman, Chandra Mohan
Quan Li Zhen, … , Chaim Putterman, Chandra Mohan
Published December 1, 2005
Citation Information: J Clin Invest. 2005;115(12):3428-3439. https://doi.org/10.1172/JCI23587.
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Research Article Immunology

Identification of autoantibody clusters that best predict lupus disease activity using glomerular proteome arrays

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Abstract

Nephrophilic autoantibodies dominate the seroprofile in lupus, but their fine specificities remain ill defined. We constructed a multiplexed proteome microarray bearing about 30 antigens known to be expressed in the glomerular milieu and used it to study serum autoantibodies in lupus. Compared with normal serum, serum from B6.Sle1.lpr lupus mice (C57BL/6 mice homozygous for the NZM2410/NZW allele of Sle1 as well as the FASlpr defect) exhibited high levels of IgG and IgM antiglomerular as well as anti–double-stranded DNA/chromatin Abs and variable levels of Abs to α-actinin, aggrecan, collagen, entactin, fibrinogen, hemocyanin, heparan sulphate, laminin, myosin, proteoglycans, and histones. The use of these glomerular proteome arrays also revealed 5 distinct clusters of IgG autoreactivity in the sera of lupus patients. Whereas 2 of these IgG reactivity clusters (DNA/chromatin/glomeruli and laminin/myosin/Matrigel/vimentin/heparan sulphate) showed association with disease activity, the other 3 reactivity clusters (histones, vitronectin/collagen/chondroitin sulphate, and entactin/fibrinogen/hyaluronic acid) did not. Human lupus sera also displayed 2 distinct IgM autoantibody clusters, one reactive to DNA and the other apparently polyreactive. Interestingly, the presence of IgM polyreactivity in patient sera was associated with reduced disease severity. Hence, the glomerular proteome array promises to be a powerful analytical tool for uncovering novel autoantibody disease associations and for distinguishing patients at high risk for end-organ disease.

Authors

Quan Li Zhen, Chun Xie, Tianfu Wu, Meggan Mackay, Cynthia Aranow, Chaim Putterman, Chandra Mohan

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