Perspectives on systems biology applications in diabetic kidney disease.
Perspectives on systems biology applications in diabetic kidney disease.
复制标题
系统生物学在糖尿病肾病中的应用前景。
DOI：
10.1007/s12265-012-9382-7
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发表时间：
2012-08
影响因子：
3.4
通讯作者：
Kretzler, Matthias
中科院分区：
文献类型：
--
作者：
Komorowsky, Claudiu V.;Brosius, Frank C., III;Pennathur, Subramaniam;Kretzler, Matthias
关键词：
糖尿病肾病(DKD)是1型和2型糖尿病的一种微血管并发症，对患者个人、家庭和整个社会都有毁灭性的影响。DKD是慢性肾脏病(CKD)发病最常见的单一原因，占终末期肾病(ESRD)人口的40%以上。导致高患病率的因素是肥胖和随后的糖尿病的增加，以及糖尿病患者长期存活率的改善。环境和遗传变异导致DKD易感性和进行性肾功能丧失。在DKD的启动和发展过程中，遗传和环境暴露的分子机制如何相互作用是当前研究的重点。标准化、无偏见的高通量人类DKD样本分析技术的发展为捕捉DKD病理生物学的多个层面开辟了新的途径。这些技术例行公事地询问全基因组范围的分析物，产生与DKD相关的全面指纹。将分子指纹与深入的临床表型联系起来，可能最终阐明疾病阶段和亚型特定方式的复杂分子相互作用。这种洞察力将形成准确预后的基础，并促进有针对性的治疗干预。在这篇综述中，我们介绍了正在进行的从大规模数据集成到DKD中改进的和个性化的医疗保健的努力。
Diabetic kidney disease (DKD) is a microvascular complication of type 1 and 2 diabetes with a devastating impact on individuals with the disease, their families and society as a whole. DKD is the single most frequent cause of incident chronic kidney disease (CKD) cases and accounts for over 40% of the population with end stage renal disease (ESRD). Contributing factors for the high prevalence are the increase in obesity and subsequent diabetes combined with an improved long–term survival with diabetes. Environment and genetic variations contribute to DKD susceptibility and progressive loss of kidney function. How the molecular mechanisms of genetic and environmental exposures interact during DKD initiation and progression are the focus of ongoing research efforts. The development of standardized, unbiased high throughput profiling technologies of human DKD samples opens new avenues in capturing the multiple layers of DKD pathobiology. These techniques routinely interrogate analytes on a genome–wide scale generating comprehensive DKD associated fingerprints. Linking the molecular fingerprints to deep clinical phenotypes may ultimately elucidate the intricate molecular interplay in a disease stage and subtype specific manner. This insight will form the basis for accurate prognosis and facilitate targeted therapeutic interventions. In this review, we present ongoing efforts from large scale data integration translating “–omics” research efforts into improved and individualized health care in DKD.
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影响因子：
7.7
作者：
Caramori, ML;Fioretto, P;Mauer, M
通讯作者：
Mauer, M
影响因子：
16.2
作者：
American Diabetes Association
通讯作者：
American Diabetes Association
DOI：
10.1038/nrg2918
发表时间：
2011-01
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
通讯作者：
--
DOI：
10.2215/cjn.03980609
发表时间：
2009-10-01
影响因子：
9.8
作者：
Barreto, Fellype C.;Barreto, Daniela V.;Massy, Ziad A.
通讯作者：
Massy, Ziad A.
影响因子：
2
作者：
Ahn, Jung-Mo;Kim, Byung-Gyu;Cho, Je-Yoel
通讯作者：
Cho, Je-Yoel