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全血转录组分析在肌萎缩侧索硬化症中的应用:一项生物标志物研究。

Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study.

机构信息

Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.

Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.

出版信息

PLoS One. 2018 Jun 25;13(6):e0198874. doi: 10.1371/journal.pone.0198874. eCollection 2018.

Abstract

The biological pathways involved in amyotrophic lateral sclerosis (ALS) remain elusive and diagnostic decision-making can be challenging. Gene expression studies are valuable in overcoming such challenges since they can shed light on differentially regulated pathways and may ultimately identify valuable biomarkers. This two-stage transcriptome-wide study, including 397 ALS patients and 645 control subjects, identified 2,943 differentially expressed transcripts predominantly involved in RNA binding and intracellular transport. When batch effects between the two stages were overcome, three different models (support vector machines, nearest shrunken centroids, and LASSO) discriminated ALS patients from control subjects in the validation stage with high accuracy. The models' accuracy reduced considerably when discriminating ALS from diseases that mimic ALS clinically (N = 75), nor could it predict survival. We here show that whole blood transcriptome profiles are able to reveal biological processes involved in ALS. Also, this study shows that using these profiles to differentiate between ALS and mimic syndromes will be challenging, even when taking batch effects in transcriptome data into account.

摘要

肌萎缩侧索硬化症(ALS)涉及的生物学途径仍难以捉摸,诊断决策可能具有挑战性。基因表达研究在克服这些挑战方面很有价值,因为它们可以揭示差异调节的途径,并最终可能确定有价值的生物标志物。这项包括 397 名 ALS 患者和 645 名对照的两阶段全转录组研究,确定了 2943 个差异表达的转录本,主要涉及 RNA 结合和细胞内运输。当克服两个阶段之间的批次效应时,三种不同的模型(支持向量机、最近收缩质心和 LASSO)在验证阶段以高精度区分 ALS 患者和对照。当将模型用于区分临床上类似 ALS 的疾病(N=75)时,其准确性会大大降低,也无法预测存活。我们在此表明,全血转录组谱能够揭示 ALS 涉及的生物学过程。此外,这项研究表明,即使考虑到转录组数据中的批次效应,使用这些谱来区分 ALS 和模拟综合征也将具有挑战性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/368c/6016933/f49cb991aa1d/pone.0198874.g001.jpg

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