TY - JOUR
T1 - Identification of Novel Phenotypes Correlated with CKD
T2 - A Phenotype-Wide Association Study
AU - Lin, Yifen
AU - Kong, Jianqiu
AU - Tian, Ting
AU - Zhong, Xiangbin
AU - Zhang, Shaozhao
AU - Zhou, Haojin
AU - Xiong, Zhenyu
AU - Zhao, Jiashu
AU - Huang, Yiquan
AU - Liu, Menghui
AU - Dong, Yuehua
AU - Zheng, Junjiong
AU - Diao, Xiayao
AU - Wu, Jieyin
AU - Qin, Haide
AU - Hu, Yue
AU - Wang, Xueqin
AU - Zhuang, Xiaodong
AU - Liao, Xinxue
N1 - Publisher Copyright:
© The author(s).
PY - 2022
Y1 - 2022
N2 - Background: 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.
AB - Background: 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.
KW - C-peptide
KW - chronic kidney disease
KW - phenotype-wide association study
KW - red cell distribution width
KW - retinol
UR - http://www.scopus.com/inward/record.url?scp=85140909319&partnerID=8YFLogxK
U2 - 10.7150/ijms.63973
DO - 10.7150/ijms.63973
M3 - Article
C2 - 36438912
AN - SCOPUS:85140909319
SN - 1449-1907
VL - 19
SP - 1920
EP - 1928
JO - International Journal of Medical Sciences
JF - International Journal of Medical Sciences
IS - 13
ER -