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Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage.
Proceedings of the National Academy of Sciences of the United States of America ( IF 9.4 ) Pub Date : 2020-08-25 , DOI: 10.1073/pnas.2007719117
Grant C O'Connell 1 , Megan L Alder 2 , Christine G Smothers 2 , Julia H C Chang 2
Affiliation  

The identification of precision blood biomarkers which can accurately indicate damage to brain tissue could yield molecular diagnostics with the potential to improve how we detect and treat neurological pathologies. However, a majority of candidate blood biomarkers for neurological damage that are studied today are proteins which were arbitrarily proposed several decades before the advent of high-throughput omic techniques, and it is unclear whether they represent the best possible targets relative to the remainder of the human proteome. Here, we leveraged mRNA expression data generated from nearly 12,000 human specimens to algorithmically evaluate over 17,000 protein-coding genes in terms of their potential to produce blood biomarkers for neurological damage based on their expression profiles both across the body and within the brain. The circulating levels of proteins associated with the top-ranked genes were then measured in blood sampled from a diverse cohort of patients diagnosed with a variety of acute and chronic neurological disorders, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, Alzheimer’s disease, and multiple sclerosis, and evaluated for their diagnostic performance. Our analysis identifies several previously unexplored candidate blood biomarkers of neurological damage with possible clinical utility, many of which whose presence in blood is likely linked to specific cell-level pathologic processes. Furthermore, our findings also suggest that many frequently cited previously proposed blood biomarkers exhibit expression profiles which could limit their diagnostic efficacy.



中文翻译:

大规模信息分析可通过算法识别神经损伤的血液生物标志物。

精确的血液生物标志物的鉴定可以准确地表明对脑组织的损伤,可以产生分子诊断学,并有可能改善我们检测和治疗神经病理学的方式。然而,当今研究的大多数神经损伤候选血液生物标志物是在高通量免疫组化技术出现前几十年任意提出的蛋白质,目前尚不清楚它们是否代表了相对于其余药物而言最好的靶标。人类蛋白质组。在这里,我们利用从将近12,000个人类标本中产生的mRNA表达数据,根据它们在人体和大脑内的表达谱,就其产生血液损伤神经系统损伤的生物标志物的潜力,对17,000个蛋白质编码基因进行算法评估。然后,从被诊断患有各种急性和慢性神经系统疾病(包括缺血性中风,出血性中风,脑外伤,阿尔茨海默氏病和其他疾病)的各种队列的血液中测量与排名靠前的基因相关的蛋白质的循环水平。多发性硬化症,并评估其诊断性能。我们的分析确定了神经损伤的几种先前尚未探索的候选血液生物标记物,可能具有临床用途,其中许多血液中的存在可能与特定的细胞水平病理过程有关。此外,我们的发现还表明,许多经常被引用的先前提出的血液生物标志物表现出可能限制其诊断功效的表达谱。

更新日期:2020-08-26
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