协变量
2019年冠状病毒病(COVID-19)
蛋白质组学
队列
医学
成对比较
计算生物学
生物
生物信息学
内科学
统计
疾病
数学
遗传学
基因
传染病(医学专业)
作者
Sara Taleb,Nisha Stephan,Sareena Chennakkandathil,Muhammad Umar Sohail,Sondos Yousef,Hina Sarwath,Muna N. Al-Noubi,Karsten Suhre,Ali Ait Hssain,Frank Schmidt
标识
DOI:10.1002/pmic.202400456
摘要
ABSTRACT We aim to verify and validate low‐abundant plasma proteins from severe COVID‐19 cases and controls through a comparative analysis between Olink and Alamar performances. Eighty‐three severe cases and 44 controls were measured for proteomics using three Olink panels and one Alamar panel, which share 94 targets. CV, pairwise correlation of intensity signals, and detectability range were compared across platforms. Statistical comparisons were performed using FDR‐adjusted linear models with age as a covariate to construct differential protein abundance volcano plots between cases and controls per platform and heatmaps between our cohort and five public cohorts. Overall, pairwise comparisons ( n = 94) showed strong correlations among cases ( r = 0.82) and controls ( r = 0.7). 60/94 proteins had mutual significance on both platforms; of which 54 showed concordant effect direction, and six showed opposite effect direction (IL‐6R, IL‐1R2, KITLG, TSLP, IL‐17C, and IL‐4R). Alamar verified 80 and 60 targets from cases and controls, respectively, along with 54 differential proteins from Olink. Compared to public cohorts measured by Olink, our Olink data showed consistent findings from 28 proteins, of which 27 were validated by Alamar.
科研通智能强力驱动
Strongly Powered by AbleSci AI