Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Jatinangor, Indonesia.
Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Jatinangor, Indonesia.
Curr Diabetes Rev. 2021;17(6):e123120189796. doi: 10.2174/1573399817666210101105253.
There is a continuous rise in the prevalence of type 2 diabetes mellitus (T2DM) worldwide and most patients are unaware of the presence of this chronic disease at the early stages. T2DM is associated with complications related to long-term damage and failure of multiple organ systems caused by vascular changes associated with glycated end products, oxidative stress, mild inflammation, and neovascularization. Among the most frequent complications of T2DM observed in about 20-40% of T2DM patients is diabetes nephropathy (DN).
A literature search was made in view of highlighting the novel applications of genomics, proteomics and metabolomics, as the new prospective strategy for predicting DN in T2DM patients.
The complexity of DN requires a comprehensive and unbiased approach to investigate the main causes of disease and identify the most important mechanisms underlying its development. With the help of evolving throughput technology, rapidly evolving information can now be applied to clinical practice.
DN is also the leading cause of end-stage renal disease and comorbidity independent of T2DM. In terms of the comorbidity level, DN has many phenotypes; therefore, timely diagnosis is required to prevent these complications. Currently, urine albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are gold standards for assessing glomerular damage and changes in renal function. However, GFR estimation based on creatinine is limited to hyperfiltration status; therefore, this makes albuminuria and eGFR indicators less reliable for early-stage diagnosis of DN.
The combination of genomics, proteomics, and metabolomics assays as suitable biological systems can provide new and deeper insights into the pathogenesis of diabetes, as well as discover prospects for developing suitable and targeted interventions.
全球 2 型糖尿病（T2DM）的患病率不断上升，大多数患者在疾病早期都不知道自己患有这种慢性病。T2DM 与长期损害和多个器官系统衰竭有关，这些损害和衰竭是由糖化终产物、氧化应激、轻度炎症和新生血管化引起的血管变化引起的。在大约 20-40%的 T2DM 患者中观察到的 T2DM 最常见的并发症之一是糖尿病肾病（DN）。
鉴于基因组学、蛋白质组学和代谢组学的新应用可能是预测 T2DM 患者 DN 的新策略，我们进行了文献检索。
DN 的复杂性需要一种全面和无偏的方法来研究疾病的主要原因，并确定其发展的最重要机制。随着高通量技术的发展，现在可以将快速发展的信息应用于临床实践。
DN 也是终末期肾病和与 T2DM 无关的合并症的主要原因。就合并症水平而言，DN 有许多表型；因此，需要及时诊断以预防这些并发症。目前，尿白蛋白与肌酐比值和估计肾小球滤过率（eGFR）是评估肾小球损伤和肾功能变化的金标准。然而，基于肌酐的 GFR 估计仅限于高滤过状态；因此，这使得白蛋白尿和 eGFR 指标对早期 DN 的诊断不太可靠。
将基因组学、蛋白质组学和代谢组学分析组合成合适的生物系统，可以为糖尿病的发病机制提供新的、更深入的见解，并为开发合适的靶向干预措施提供前景。
