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Comprehensive Analyses of the Immunoglobulin Proteome for the Classification of Glomerular Diseases.
Journal of Proteome Research ( IF 4.4 ) Pub Date : 2020-03-13 , DOI: 10.1021/acs.jproteome.9b00748
Jianhua Liu 1 , Yang Li 2 , Jiayu Dai 2 , Baoxu Lin 1 , Chunying Xiao 1 , Xinpeng Zhang 1 , Lin Luo 1 , Tingting Wang 1 , Xiaoying Li 1 , Yao Yu 1 , Shixiao Chen 1 , Lina Wu 1 , Yong Liu 1 , Xiaobo Yu 2 , Xiaosong Qin 1
Affiliation  

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.

中文翻译:

免疫球蛋白蛋白质组对肾小球疾病分类的综合分析。

目前使用侵入性肾活检诊断为肾小球疾病,涵盖了许多疾病亚型,即使它们具有不同的治疗方案,它们也经常表现出相似的临床表现。因此,需要非侵入性测定来分类和指导肾小球疾病的治疗。在这里,我们开发并应用了高通量和定量微阵列平台,以表征419名健康和患病患者血清中的免疫球蛋白蛋白质组。免疫球蛋白蛋白质组-临床变量相关网络揭示了肾小球疾病的新病理机制。此外,基于相关网络的免疫球蛋白蛋白质组多态正态分布(IP-MiND)数学模型对健康志愿者和特发性膜性肾病患者进行分类,发现队列中的平均召回率为48%(23–80%),而64%(63 –65%)在独立的验证队列中。我们的结果证明了我们的微阵列平台对肾小球疾病的翻译实用性及其在表征其他人类疾病中的临床潜力。
更新日期:2020-04-24
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