• Yifen Lin, Jianqiu Kong, Ting Tian, Xiangbin Zhong, Shaozhao Zhang, Haojin Zhou, Zhenyu Xiong, Jiashu Zhao, Yiquan Huang, Menghui Liu, Yuehua Dong, Junjiong Zheng, Xiayao Diao, Jieyin Wu, Haide Qin, Yue Hu, Xueqin Wang, Xiaodong Zhuang, and Xinxue Liao.
• Cardiology department, First affiliated hospital of Sun Yat-Sen University.
• Int J Med Sci. 2022 Jan 1; 19 (13): 192019281920-1928.

AbstractBackground: A comprehensive understanding of phenotypes related to CKD will facilitate the identification and management of CKD. We aimed to panoramically test and validate associations between multiple phenotypes and CKD using a phenotype-wide association study (PheWAS). Methods: 15,815 subjects from cross-sectional cohorts of the National Health and Nutrition Examination Survey (1999-2006) were randomly 50:50 split into training and testing sets. CKD was defined as eGFR < 60 mL/min/1.73m2. We performed logistic regression analyses between each of 985 phenotypes with CKD in the training set (false discovery rate < 1%) and validated in the testing set (false discovery rate < 1% ). Random forest (RF) model, Nagelkerke's Pseudo-R2, and the area under the receiver operating characteristic (AUROC) were used to validate the identified phenotypes. Results: We identified 18 phenotypes significantly related to CKD, among which retinol, red cell distribution width (RDW), and C-peptide were less researched. The top 5 identified phenotypes were blood urea nitrogen (BUN), homocysteine (HCY), retinol, parathyroid hormone (PTH), and osmolality in RF importance ranking. Besides, BUN, HCY, PTH, retinol, and uric acid were the most important phenotypes based on Pseudo-R2. AUROC of the RF model was 0.951 (full model) and 0.914 (top 5 phenotypes). Conclusion: Our study demonstrated associations between multiple phenotypes with CKD from a holistic view, including 3 novel phenotypes: retinol, RDW, and C-peptide. Our findings provided valid evidence for the identification of novel biomarkers for CKD.© The author(s).

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