Chang Alexander R, Wongboonsin Janewit, Mallett Andrew J, Morales Ana, Retterer Kyle, Mirshahi Tooraj, Sayer John A
Department of Population of Health Sciences, Geisinger, Danville, PA, USA; Center for Kidney Health Research, Geisinger, Danville, PA, USA.
Renal Division, Department of Internal Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand; Division of Renal Medicine, Brigham and Women's Hospital, Boston, MA, United States; Division of Nephrology, Boston Children's Hospital, Boston, MA, United States; Bumrungrad Genomic Medicine Institute and Department of Medicine, Bumrungrad International Hospital, Bangkok, Thailand.
Semin Nephrol. 2025 Jul 11:151651. doi: 10.1016/j.semnephrol.2025.151651.
Chronic kidney disease (CKD) affects approximately 9% of the global population, leading to increased risks of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and mortality. Patients with CKD are a huge burden on health care resources globally. CKD is a complex condition influenced by a combination of genetic, environmental, and traditional risk factors. Family studies have suggested heritability rates for CKD ranging from 30% to 75%, and large genomic biobank studies have proven essential in identifying genes with substantial effects on CKD risk and in capturing cumulative genetic risk through polygenic risk scores. These biobanks are crucial for discovering new genes associated with kidney health and disease, and their growing size enhances the power to detect novel genetic associations. Integrating multi-omics technologies such as transcriptomics, metabolomics, and proteomics further enriches our understanding of CKD, while advanced computational tools continue to expand our insights into genetic data. Polygenic risk scores, derived from hundreds of genetic variants with small effect sizes, can help identify individuals at high risk of CKD. Genomic biobanks offer valuable opportunities for early identification and personalized treatment of monogenic kidney disorders, such as autosomal dominant polycystic kidney disease and Alport syndrome. These biobanks help fill knowledge gaps, particularly in individuals with milder or asymptomatic presentations who are often underrepresented in traditional studies. Expanding genomic biobank efforts globally, especially in diverse populations, is vital to enhancing our understanding of the genetic underpinnings of kidney disease. This review highlights the significant contributions of genomic biobanks to advancing our comprehension of the genetics of CKD. Semin Nephrol 36:x-xx © 20XX Elsevier Inc. All rights reserved.
慢性肾脏病（CKD）影响着全球约9%的人口，导致终末期肾病（ESKD）、心血管疾病（CVD）风险增加以及死亡率上升。CKD患者给全球医疗资源带来了巨大负担。CKD是一种受遗传、环境和传统风险因素综合影响的复杂病症。家族研究表明CKD的遗传率在30%至75%之间，大型基因组生物样本库研究对于识别对CKD风险有重大影响的基因以及通过多基因风险评分捕捉累积遗传风险至关重要。这些生物样本库对于发现与肾脏健康和疾病相关的新基因至关重要，其规模的不断扩大增强了检测新遗传关联的能力。整合转录组学、代谢组学和蛋白质组学等多组学技术进一步丰富了我们对CKD的理解，而先进的计算工具不断拓展我们对遗传数据的认识。源自数百个效应大小较小的遗传变异的多基因风险评分有助于识别CKD高风险个体。基因组生物样本库为单基因肾病（如常染色体显性多囊肾病和阿尔波特综合征）的早期识别和个性化治疗提供了宝贵机会。这些生物样本库有助于填补知识空白，特别是在传统研究中代表性不足的症状较轻或无症状的个体方面。在全球范围内扩大基因组生物样本库的工作，尤其是在不同人群中，对于增强我们对肾脏疾病遗传基础的理解至关重要。本综述强调了基因组生物样本库对推进我们对CKD遗传学理解的重大贡献。《肾脏病学研讨会》36:x - xx © 20XX爱思唯尔公司。保留所有权利。
