Phenotype Characterisation Using Integrated Gene Transcript, Protein and Metabolite Profiling

Phenotype Characterisation Using Integrated Gene Transcript, Protein and Metabolite Profiling
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使用集成基因转录本、蛋白质和代谢物分析进行表型表征

DOI:
10.2165/00822942-200403040-00002
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发表时间:
2004
期刊:
Applied Bioinformatics
影响因子:
--
通讯作者:
T. Plasterer
T. Plasterer
中科院分区:
--
文献类型:
--
作者:
M. Orešič;C. Clish;E. Davidov;E. Verheij;J. Vogels;L. Havekes;Eric K. Neumann;A. Adourian;S. Naylor;J. Greef;T. Plasterer

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多因子疾病对功能基因组学提出了重大挑战。由于它们的多区室效应和复杂的生物分子活性,这些疾病不能通过单一组分的变化来充分表征,也不能通过单独观察基因转录来理解病理生理变化。相反,在多个组织和器官的多因素疾病中观察到一种微妙的变化模式,相应的基因,蛋白质和代谢物水平之间存在复杂的关联。本文介绍了在生物分子水平上探索性和综合性分析病理生理变化的方法。特别是,新的方法引入了以下挑战:(i)通过电喷雾电离(ESI)液相色谱-串联质谱(LC/MS)获得的蛋白质组学和代谢组学数据的数据处理和分析方法;(ii)整合的基因,蛋白质和代谢物模式的关联分析,最能描述病理生理变化;和(iii)在已知的生物过程的背景下,从关联分析获得的结果的解释这些新的方法与载脂蛋白E3-莱顿转基因小鼠模型,动脉粥样硬化的常用模型说明。我们试图通过在疾病的致病表现之前确定和鉴定基因转录物、蛋白质和代谢物的集合,沿着它们在转基因模型和相关野生型队列中的推定关系,来深入了解疾病发作和进展的早期反应。我们的研究结果证实了以前的研究结果,并扩展了对动脉粥样硬化三个过程的预测:异常脂质代谢,炎症,组织发育和维持。
Multifactorial diseases present a significant challenge for functional genomics. Owing to their multiple compartmental effects and complex biomolecular activities, such diseases cannot be adequately characterised by changes in single components, nor can pathophysiological changes be understood by observing gene transcripts alone. Instead, a pattern of subtle changes is observed in multifactorial diseases across multiple tissues and organs with complex associations between corresponding gene, protein and metabolite levels.This article presents methods for exploratory and integrative analysis of pathophysiological changes at the biomolecular level. In particular, novel approaches are introduced for the following challenges: (i) data processing and analysis methods for proteomic and metabolomic data obtained by electrospray ionisation (ESI) liquid chromatography-tandem mass spectrometry (LC/MS); (ii) association analysis of integrated gene, protein and metabolite patterns that are most descriptive of pathophysiological changes; and (iii) interpretation of results obtained from association analyses in the context of known biological processes.These novel approaches are illustrated with the apolipoprotein E3-Leiden transgenic mouse model, a commonly used model of atherosclerosis. We seek to gain insight into the early responses of disease onset and progression by determining and identifying — well in advance of pathogenic manifestations of disease — the sets of gene transcripts, proteins and metabolites, along with their putative relationships in the transgenic model and associated wild-type cohort. Our results corroborate previous findings and extend predictions for three processes in atherosclerosis: aberrant lipid metabolism, inflammation, and tissue development and maintenance.
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发表时间: 2001-03-01
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影响因子: 32.4
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