Comprehensive Analyses of the Immunoglobulin Proteome for the Classification of Glomerular Diseases.

Abstract

Glomerular diseases, which are currently diagnosed using an invasive renal biopsy, encompass numerous disease subtypes that often display similar clinical manifestations even though they have different therapeutic regimes. Therefore, a noninvasive assay is needed to classify and guide the treatment of glomerular diseases. Here, we develop and apply a high-throughput and quantitative microarray platform to characterize the immunoglobulin proteome in the serum from 419 healthy and diseased patients. The immunoglobulin proteome-clinical variable correlation network revealed novel pathological mechanisms of glomerular diseases. Furthermore, an immunoglobulin proteome-multivariate normal distribution (IP-MiND) mathematical model based on the correlation network classified healthy volunteers and patients with idiopathic membranous nephropathy with an average recall of 48% (23-80%) in the discovery cohort and 64% (63-65%) in an independent validation cohort. Our results demonstrate the translational utility of our microarray platform to glomerular diseases as well as its clinical potential in characterizing other human diseases.

• Authors: Jianhua Liu, Yang Li, Jiayu Dai, Baoxu Lin, Chunying Xiao, Xinpeng Zhang, Lin Luo, Tingting Wang, Xiaoying Li, Yao Yu, Shixiao Chen, Lina Wu, Yong Liu, Xiaobo Yu, Xiaosong Qin
• Journal: Journal of proteome research (J Proteome Res) Vol. 19 Issue 4 Pg. 1502-1512 (04 03 2020) ISSN: 1535-3907 [Electronic] United States
• PMID: 32168457 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• Immunoglobulins
• Proteome

Topics

• Cohort Studies
• Humans
• Immunoglobulins
• Proteome
• Proteomics