Epigenetic drivers and biomarkers of diabetic kidney disease

 描述：糖尿病（DM）使预期寿命缩短约10年。肾脏疾病显示出与死亡率最强的相关性，但我们对糖尿病肾病（DKD）的理解仍然有限。表观遗传学是指基因表达模式的可遗传变化，这些变化不是由核苷酸序列本身的改变引起的。表观遗传系统在细胞水平上是可遗传和可逆的。胞嘧啶修饰完全符合这些标准。其他因素包括：组蛋白尾部修饰、更高级的染色质组织和长和短的非编码RNA分子通常被描述为表观遗传机制，但它们并不满足表观遗传机制的所有标准。一些证据表明，表观基因组是我们理解DKD发病机制中重要的缺失环节。该提案的假设是胞嘧啶甲基化变化反映了长期的先前代谢改变。表观遗传学差异可以对DKD患者进行亚群分析，并通过影响转录水平的变化预测肾功能下降。根据这项建议，我们计划：1。在800个显微切割的人肾TEC中表征全基因组胞嘧啶甲基化模式;包括对照组（无糖尿病、高血压和正常肾功能）、糖尿病或高血压患者和无肾病患者以及高血压背景下的CKD患者，并将其与DKD样本进行比较。2.明确胞嘧啶甲基化改变对表型形成的影响。使用新的统计方法定义胞嘧啶甲基化和基因表达变化之间的关联。3.通过比较入组时快速与缓慢进展DKD患者的胞嘧啶甲基化变化，了解胞嘧啶甲基化变化是否可用于预测CRIC队列中的GFR病程。

 DESCRIPTION: Diabetes (DM) shortens life expectancy by about 10 years. Renal disease shows the strongest correlation with excess mortality, yet our comprehension of diabetic kidney disease (DKD) remains limited. Epigenetics refers to heritable changes in gene expression patterns that are not caused by alterations in the nucleotide sequence itself. The epigenetic system is heritable and reversible at the cellular level. Cytosine modifications fully meet these criteria. Other factors including: histone tail modifications, higher order chromatin organization and long and short non-coding RNA molecules are often described as epigenetic mechanisms, but they not fulfill all criteria as epigenetic mechanism. Several lines of evidence point to the epigenome as an important missing link in our understanding of DKD pathogenesis. The hypothesis of the proposal is that cytosine methylation changes reflect long-term prior metabolic alterations. Epigenetic differences can subgroup DKD patients and can predict kidney function decline by influencing transcript level changes. Under this proposal we plan to: 1. Characterize genome-wide cytosine methylation patterns in 800 microdissected human kidney TEC; including controls (in absence of diabetes, hypertension and normal kidney function), patients with diabetes or hypertension and absence of renal disease and patients with CKD in the setting of hypertension and compare them to DKD samples. 2. Define the contribution of cytosine methylation changes to phenotype development. Define the association between cytosine methylation and gene expression changes using novel statistical methods. 3. Understand whether cytosine methylation changes can be used to predict GFR course in the CRIC cohort, by comparing cytosine methylation changes of patients with rapidly vs. slowly progressive DKD upon enrollment.