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New clusters of serum electrolytes aid in stratification of diabetes and metabolic risk

BACKGROUND: Serum electrolytes were found to associate with type 2 diabetes. Our study aimed to stratify nondiabetes by clusters based on multiple serum electrolytes and evaluate their associations with risk of developing diabetes and longitudinal changes in glucose and lipid metabolic traits. METHO...

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Detalles Bibliográficos
Autores principales: Hou, Yanan, Xiang, Jiali, Dai, Huajie, Wang, Tiange, Li, Mian, Lin, Hong, Wang, Shuangyuan, Xu, Yu, Lu, Jieli, Chen, Yuhong, Wang, Weiqing, Ning, Guang, Zhao, Zhiyun, Bi, Yufang, Xu, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wiley Publishing Asia Pty Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060051/
https://www.ncbi.nlm.nih.gov/pubmed/34963041
http://dx.doi.org/10.1111/1753-0407.13244
Descripción
Sumario:BACKGROUND: Serum electrolytes were found to associate with type 2 diabetes. Our study aimed to stratify nondiabetes by clusters based on multiple serum electrolytes and evaluate their associations with risk of developing diabetes and longitudinal changes in glucose and lipid metabolic traits. METHODS: We performed a data‐driven cluster analysis in 4937 nondiabetes individuals aged ≥40 years at baseline from a cohort follow‐up for an average of 4.4 years. Cluster analysis was based on seven commonly measured serum electrolytes (iron, chlorine, magnesium, sodium, potassium, calcium, and phosphorus) by using the k‐means method. RESULTS: A total of 4937 nondiabetes individuals were classified into three distinct clusters, with 1635 (33.1%) assigned to Cluster A, 1490 (30.2%) to Cluster B, and 1812 (36.7%) to Cluster C. Individuals in Cluster A had higher serum chlorine, were older, and more were women. Individuals in Cluster B had higher serum iron and body mass index (BMI). Individuals in Cluster C had higher serum phosphorus, were younger, and had lower BMI. Cluster B had 1.41‐fold higher risk of developing diabetes and Cluster C’s risk was 1.33‐fold higher compared with Cluster A. Over an average follow‐up of 4.4 years, Cluster A showed a moderate and stable BMI, Cluster B showed an accelerated deterioration in glucose metabolism, and Cluster C showed the most sharply increased serum low‐density lipoprotein cholesterol level. CONCLUSIONS: Clusters based on seven common serum electrolytes differed in diabetes risk and progression of glucose and lipid metabolic traits. Serum electrolytes clusters could provide a powerful tool to differentiate individuals into different risk stratification for developing type 2 diabetes.