Rapid detection of urinary soluble intercellular adhesion molecule-1 for determination of lupus nephritis activity

快速检测尿液中可溶性细胞间黏附分子-1以测定狼疮性肾炎的活动性

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Abstract

The current methods of monitoring the activity of lupus nephritis (LN) may cause unnecessary hospital visits or delayed immunosuppressive therapy. We aimed to find a urinary biomarker that could be developed as a home-based test for monitoring the activity of LN.Urine samples were collected immediately before a renal biopsy from patients of suspected active LN, and also from patients with inactive LN, systemic lupus erythematous without LN or healthy controls. Biomarker search was conducted on a cytokine antibody array and confirmation was done by quantitative evaluation with enzyme-linked immunosorbent assay. The Mann-Whiney test or Student t test was used to compare the levels of 9 cytokines between different groups. The sensitivity and specificity of each cytokine for diagnosis of LN was evaluated by receiver operating characteristic curve. A rapid test based on colloidal gold immunochromatography was then developed for bedside or home use. Furthermore, an experimental e-healthcare system was constructed for recording and sharing the results of the rapid test a cloud-assisted internet of things (IoT) consisting of a sensing device, an IoT device and a cloud server.Adiponectin (Acrp30), soluble intercellular cell adhesion molecule-1 (sICAM-1), neural cell adhesion molecule 1 (NCAM-1), and CD26 were significantly higher in urine samples of active LN patients. sICAM-1 appeared more sensitive and specific among these candidates. When the cut-off value of sICAM-1 was set at 1.44 ng/mL, the sensitivity reached 98.33% with a specificity at 85.71%. The sICAM-1 strip test showed comparable sensitivity of 95% and a specificity of 83.3% for assessing the LN activity. Meanwhile, the e-healthcare system was able to conveniently digitize and share the sICAM-1 rapid test results.sICAM-1 appeared to be an excellent biomarker for monitoring LN activity. The e-healthcare system with cloud-assisted IoT could assist the digitalization and sharing of the bedside or home-based sICAM-1 test results.

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