KidDO project update - quantitative proteomic and metabolomic analysis of five mouse models with chronic kidney disease

Chronic kidney disease (CKD) is one of the most deadly diseases faced by patients and is a major global health and socioeconomic burden.CKD increases cardiovascular morbidity and premature mortality and decreases quality of life. Hypertension (HTN) and type 2 diabetes mellitus (T2DM), which are reaching epidemic levels, are major risk factors for CKD. CKD diagnosis and progression is based on estimated GFR (eGFR) and urinary albumin excretion. However, eGFR only has a predictive value in advanced disease and there is risk of progressive CKD in non-albuminuric individuals. Thus, there is an urgent need for new approaches for early detection of the most “at risk” individuals and identification of CKD signatures to aid in designing novel drugs and preventive measures that could ameliorate progression of CKD. Our overarching goal is to identify metabolites that predict kidney cell phenotypes during CKD and how crosstalk of these metabolites with the proteome drive CKD progression. We will integrate metabolomics and proteomic information from animal models of CKD with human CKD patient biopsies to identify common signatures in the tubulointerstitium that correlate with human pathophysiology. Here we provide quantitative proteomic and metabolomic datasets, as well as plasma and urine electrolyte measurements on five CKD mouse models.慢性肾脏病（Chronic kidney disease, CKD）是患者面临的致死性疾病之一，亦是全球范围内重大的公共卫生与社会经济负担。CKD可升高心血管疾病发病风险与过早死亡概率，同时降低患者生活质量。高血压（Hypertension, HTN）与2型糖尿病（Type 2 diabetes mellitus, T2DM）正呈流行态势，二者均为CKD的主要危险因素。 CKD的诊断与病情进展评估基于估算肾小球滤过率（estimated GFR, eGFR）与尿白蛋白排泄水平。然而，eGFR仅对晚期疾病具备预测价值，且非白蛋白尿个体仍存在CKD进展风险。因此，亟需开发新型手段以早期识别高危人群，并鉴定CKD特征标志物，助力研发新型治疗药物与干预措施，延缓CKD的疾病进展。 本研究的总体目标为鉴定可预测CKD进程中肾细胞表型的代谢物，以及这些代谢物与蛋白质组的串扰如何驱动CKD进展。我们将整合慢性肾脏病动物模型与人类CKD患者活检组织的代谢组与蛋白质组数据，以筛选出与人类肾脏病理生理特征相关的肾小管间质共同特征。 本数据集包含5种CKD小鼠模型的定量蛋白质组、代谢组数据集，以及血浆与尿液电解质检测数据。