慢性肾病的全景预测与人群风险评估

Chronic kidney disease (CKD) is a condition characterized by a gradual loss ofkidney function over time，CKD became one of the major reasons of end stage renal disease (ESRD) and death in China and globally. Recently, the incidence of CKD increased dramatically, meanwhile, due to the slience onset and treatment difficulties, the early prediction of CKD became more important. Although biomarkers and loci were found that associated with CKD by many epidemiology,genetics, genomics, and multi-omics studies, however, it is still unclear if those markers were independent risk factors of CKD, how they contribute to the population risk of CKD is still enigmatic. Therefore, integrating genetic and non-genetic risk factors and evaluate those risk factors in cohort studies, establishing effective CKD prediction models are essential for CKD treatment and prevention. In this study, we would like to perform cohort and nested case control (NCC) analyses in a chronic disease cohort, to investigte indenpendent risk factors of CKD; Genetic, non-genetic factors and mutli-omics data will be integrated to establish a panoramic prediction model of CKD, the model will further be validated in multiple cohorts. The effective prediction model will provide important information for developing better helth policies of CKD prevention and treatment.

慢性肾病(chronic kidney disease, CKD) 是一类以慢性进展性肾功能丧失为特征的疾病，是终末期肾病和致死的主要原因之一。近年来，慢性肾病的发病呈快速上升趋势，因其发病隐匿、知晓率低、治疗困难、医疗费用负担重，其早期预警尤为重要。包括我们的研究在内的流行病学、遗传学和组学研究发现了多个与CKD发病相关的生物标志物和关联的基因位点，但这些标志物是否为CKD发病的独立风险因素尚不明确，其在群体水平上对CKD发病的贡献缺乏有效评估。本研究在前期队列和遗传学研究的基础上，将利用已建立14年的慢性病队列及其临床、生物标志物及基因型数据，通过队列和巢式病例对照研究筛选CKD的独立风险因素；将多组学数据进行整合，纳入人群的遗传和非遗传因素多组学数据作为预测因子，并在多个队列人群中进行验证，建立有效的CKD全景风险预测模型，为CKD的预防、治疗提供政策依据。

慢性肾病(chronic kidney disease, CKD) 是一类由多种病因引起、以慢性进展性肾功能丧失为特征的疾病。近年来，CKD的患病率在全球范围呈上升趋势，全世界约有6亿CKD患者，其中每年约有100万患者死于CKD引起的终末期肾病。2014年我国CKD的患病率为10.8%，约有1.3亿患者，其中3千万会发展成为终末期肾病。CKD的发病隐匿、知晓率低，一经发现往往已经存在肾小球滤过率的显著下降，治疗非常困难。中国终末期肾病的平均肾透析时间为48.2±19.4月，而我国肾透析患者每年的直接医疗费用即已达10万元以上。无论从患病率、致死率和经济负担来说，CKD都是严重的健康问题，一旦发展到终末期肾病，会给医保资金的分配和使用带来很大困难。基于人群大数据进行有效筛选、早期发现CKD患者，对实现防治的关口前移，实施有效的健康管理具有重要的意义。本项目研究建立了包括非遗传因素、遗传因素和生物标志物的CKD的预测模型，AUC达到85%以上；完成了生物标志物及多组学指标的筛选，确定CKD的独立风险因素及其对人群CKD风险的贡献；完成了CKD的全基因组关联分析、通路关联分析和基因交互作用分析，找到与CKD及肾功能数量性状相关的关联。在国际较高水平专业期刊上发表文章2篇，通过本项目研究，培养硕士生5名、博士生2名。