Network-based analysis of affected biological processes in type 2 diabetes models.
Network-based analysis of affected biological processes in type 2 diabetes models.
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DOI：
10.1371/journal.pgen.0030096
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发表时间：
2007-06
期刊：
影响因子：
4.5
通讯作者：
Kasif S
中科院分区：
文献类型：
--
作者：
Liu M;Liberzon A;Kong SW;Lai WR;Park PJ;Kohane IS;Kasif S
2型糖尿病是一种与多种遗传、表观遗传、发育和环境因素相关的复杂疾病。2型糖尿病的动物模型基于饮食、药物治疗和基因敲除而不同，但所有动物模型都显示出外周组织中高血糖和胰岛素抵抗的临床特征。基因表达微阵列技术的最新进展为在全基因组范围内和不同模型中研究2型糖尿病提供了前所未有的机会。迄今为止，一个关键的挑战是确定在疾病中起重要作用的生物过程或信号通路。在这里，使用基于网络的分析方法，我们确定了与胰岛素信号传导和核受体网络相关的两组基因，它们在统计上显着数量的糖尿病和胰岛素抵抗模型中重复出现，并在不同组织类型中发生转录改变。我们还确定了两个基因组成员之间的蛋白质-蛋白质相互作用网络，这可能有助于它们之间的信号传导。两者合计，结果说明了整合高通量微阵列研究的好处，连同蛋白质-蛋白质相互作用网络，阐明与复杂疾病相关的潜在生物学过程。2型糖尿病目前影响数百万人。其临床特征在于除了葡萄糖反应受损之外的胰岛素抵抗，并且与许多并发症相关，包括心脏病、中风、神经病和肾衰竭等。准确识别疾病或其并发症的潜在分子机制是一个重要的研究问题，可能导致新的诊断和治疗。主要的挑战源于胰岛素抵抗是一种复杂的疾病，影响许多生物过程、代谢网络和信号通路。在这份报告中，作者开发了一种基于网络的方法，该方法在检测疾病状态下失调的分子过程方面似乎比以前的方法更敏感。该方法揭示了胰岛素信号传导和核受体网络在许多胰岛素抵抗模型中一致且差异表达。积极的结果表明，这种基于网络的诊断技术有望成为未来潜在有用的临床和研究工具。
Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin resistance in peripheral tissue. The recent advances in gene-expression microarray technologies present an unprecedented opportunity to study type 2 diabetes mellitus at a genome-wide scale and across different models. To date, a key challenge has been to identify the biological processes or signaling pathways that play significant roles in the disorder. Here, using a network-based analysis methodology, we identified two sets of genes, associated with insulin signaling and a network of nuclear receptors, which are recurrent in a statistically significant number of diabetes and insulin resistance models and transcriptionally altered across diverse tissue types. We additionally identified a network of protein–protein interactions between members from the two gene sets that may facilitate signaling between them. Taken together, the results illustrate the benefits of integrating high-throughput microarray studies, together with protein–protein interaction networks, in elucidating the underlying biological processes associated with a complex disorder. Type 2 diabetes mellitus currently affects millions of people. It is clinically characterized by insulin resistance in addition to an impaired glucose response and associated with numerous complications including heart disease, stroke, neuropathy, and kidney failure, among others. Accurate identification of the underlying molecular mechanisms of the disease or its complications is an important research problem that could lead to novel diagnostics and therapy. The main challenge stems from the fact that insulin resistance is a complex disorder and affects a multitude of biological processes, metabolic networks, and signaling pathways. In this report, the authors develop a network-based methodology that appears to be more sensitive than previous approaches in detecting deregulated molecular processes in a disease state. The methodology revealed that both insulin signaling and nuclear receptor networks are consistently and differentially expressed in many models of insulin resistance. The positive results suggest such network-based diagnostic technologies hold promise as potentially useful clinical and research tools in the future.
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影响因子：
7.7
作者：
Biddinger, SB;Almind, K;Kahn, CR
通讯作者：
Kahn, CR
影响因子：
8.2
作者：
Hara, K;Tobe, K;Kadowaki, T
通讯作者：
Kadowaki, T
影响因子：
158.5
作者：
Graham, Timothy E.;Yang, Qin;Kahn, Barbara B.
通讯作者：
Kahn, Barbara B.
DOI：
10.1002/dmr.5610040803
发表时间：
1988-12-01
期刊：
DIABETES-METABOLISM REVIEWS
影响因子：
--
作者：
GOLAY, A;FELBER, JP;FERRANNINI, E
通讯作者：
FERRANNINI, E
DOI：
10.1073/pnas.0307326101
发表时间：
2004-03-02
影响因子：
11.1
作者：
Karaoz, U;Murali, TM;Kasif, S
通讯作者：
Kasif, S