posted on 2020-03-23, 19:13authored byJianhua 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
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.