Continuous Metabolic Syndrome Severity Score Linked With CKD Risk

A patient's continuous metabolic syndrome severity score (cMetS-S) could help predict chronic kidney disease (CKD) even if other major risk factors, such as obesity, diabetes mellitus, and hypertension, are absent, according to a new report.

The study is believed to be among the first to show how the trajectory of a patient’s cMetS-S score is linked with CKD risk. It was published in the journal Kidney Diseases.¹

Previous research has shown that metabolic abnormalities have an important and intricate interplay with renal function and estimated glomerular infiltration rate (eGFR), the authors noted. A meta-analysis published in 2023 found people with metabolic syndrome are at a significantly higher risk of renal dysfunction, including a rapid decline in eGFR, new-onset kidney disease, and end-stage renal disease.² Not only do those conditions have significant individual health impacts, the authors noted, but they also lead to a significant economic burden for patients and health systems.¹ All of that means it is very important to better understand the “several interrelated risks” associated with CKD development, beyond major comorbidities like hypertension, the investigators said.

The authors noted that metabolic syndrome changes over time, and previous research has suggested that changes in metabolic syndrome status might be associated with certain health risks.

“However, there is a need to delve deeper into the relationship between MetS (metabolic syndrome) and CKD, particularly in the context of its severity and trajectory,” they said.

The investigators said the metabolic syndrome severity score is able to capture the dynamism of metabolic syndrome, and thus they said it could be a useful tool to study links between metabolic syndrome and CKD. 

The authors used data from the Tehran Lipid and Glucose Study, a longitudinal population-based study that began enrolling patients in 1999, eventually accruing 4462 participants ranging in age from 20 to 60 years old. The patients were free of CKD at baseline and then followed at 3-year intervals through 2018. For the purposes of the new report, the investigators divided up the study data into 2 periods. The first approximately 9 years of data were used to identify cMetS-S score trajectories for patients, representing the changes seen from baseline in 1999 through the third follow-up visit by 2009. The next 9 years were used to track the incidence of CKD among patients. The data were adjusted for a number of factors, including age, sex, education, family history of diabetes, and obesity, among others.

The participants were grouped into 3 cohorts based on the trajectory of their cMetS-S scores. Most (50%) were placed in the “medium trajectory” cohort. Another 28.3% were considered to have a low score trajectory. The remaining group (21.7%) had a high trajectory. After adjusting the data for confounding factors, the authors found that people with a high trajectory had an increased risk of CKD (HR, 1.32; 95% CI, 1.04-1.67).

Notably, the link between a high cMetS-S trajectory and CKD risk held true even if an individual did not have diabetes, obesity, or hypertension. However, the authors also said their association only reached statistical significance in men. It may be possible that estrogen—which has nephroprotective qualities in women—might delay CKD progression, the authors said.

The study had a strong, population-based prospective design, though the authors noted that it only included people from Iran, and it did not include reliable data on alcohol consumption, which can affect cMetS-S scores. Future studies may be able to mitigate some of these limitations.

The authors concluded that the findings suggest monitoring metabolic health changes may allow physicians to better manage patient health and encourage meaningful health behavior changes that could help reduce patient risk.

References

1. Mehran L, Amouzegar A, Masoumi S, Adib M, Azizi F, Amouzegar A. Trajectory patterns of metabolic syndrome severity score and risk of chronic kidney diseases. Kidney Dis (Basel). 2025;11(1):530-542. doi:10.1159/000545726

2. Li X, Liang Q, Zhong J, Gan L, Zuo L. The effect of metabolic syndrome and its individual components on renal function: a meta-analysis. J Clin Med. 2023;12(4):1614. doi:10.3390/jcm12041614