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代谢组学和基因组分析在糖尿病临床医学中的新兴应用。

Emerging applications of metabolomic and genomic profiling in diabetic clinical medicine.

机构信息

AAD Centre for Pharmacy and Diabetes, School of Biomedical Sciences, University of Ulster, Coleraine, Northern Ireland, UK.

出版信息

Diabetes Care. 2011 Dec;34(12):2624-30. doi: 10.2337/dc11-0837.

Abstract

Clinical and epidemiological metabolomics provides a unique opportunity to look at genotype-phenotype relationships as well as the body\x{2019}s responses to environmental and lifestyle factors. Fundamentally, it provides information on the universal outcome of influencing factors on disease states and has great potential in the early diagnosis, therapy monitoring, and understanding of the pathogenesis of disease. Diseases, such as diabetes, with a complex set of interactions between genetic and environmental factors, produce changes in the body\x{2019}s biochemical profile, thereby providing potential markers for diagnosis and initiation of therapies. There is clearly a need to discover new ways to aid diagnosis and assessment of glycemic status to help reduce diabetes complications and improve the quality of life. Many factors, including peptides, proteins, metabolites, nucleic acids, and polymorphisms, have been proposed as putative biomarkers for diabetes. Metabolomics is an approach used to identify and assess metabolic characteristics, changes, and phenotypes in response to influencing factors, such as environment, diet, lifestyle, and pathophysiological states. The specificity and sensitivity using metabolomics to identify biomarkers of disease have become increasingly feasible because of advances in analytical and information technologies. Likewise, the emergence of high-throughput genotyping technologies and genome-wide association studies has prompted the search for genetic markers of diabetes predisposition or susceptibility. In this review, we consider the application of key metabolomic and genomic methodologies in diabetes and summarize the established, new, and emerging metabolomic and genomic biomarkers for the disease. We conclude by summarizing future insights into the search for improved biomarkers for diabetes research and human diagnostics.

摘要

临床和流行病学代谢组学为研究基因型-表型关系以及机体对环境和生活方式因素的反应提供了独特的机会。从根本上讲,它提供了影响因素对疾病状态的普遍影响的信息,在疾病的早期诊断、治疗监测和发病机制的理解方面具有巨大的潜力。糖尿病等疾病具有一系列复杂的遗传和环境因素相互作用,会导致机体生化特征发生变化,从而为诊断和治疗的启动提供潜在的标志物。显然,需要发现新的方法来辅助诊断和评估血糖状态,以帮助减少糖尿病并发症并提高生活质量。许多因素,包括肽、蛋白质、代谢物、核酸和多态性,都被提议作为糖尿病的潜在生物标志物。代谢组学是一种用于识别和评估代谢特征、变化和表型的方法,以响应环境、饮食、生活方式和病理生理状态等影响因素。由于分析和信息技术的进步,代谢组学在识别疾病生物标志物方面的特异性和敏感性变得越来越可行。同样,高通量基因分型技术和全基因组关联研究的出现也促使人们寻找糖尿病易感性或易感性的遗传标记。在这篇综述中,我们考虑了代谢组学和基因组学关键方法在糖尿病中的应用,并总结了该疾病已建立、新出现和新兴的代谢组学和基因组学生物标志物。最后,我们总结了未来对寻找改善糖尿病研究和人类诊断的生物标志物的研究进展。

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