Simple 3-Marker Index May Flag CKM Syndrome Risk Before Costly Disease Progression

The cholesterol, high-density lipoprotein (HDL), and glucose (CHG) index—a composite biomarker reflecting the joint burden of lipid and glucose dysregulation—is significantly associated with the onset, stage-wise progression, and adverse prognosis of cardiovascular-kidney-metabolic (CKM) syndrome, according to a new study published in Diabetology & Metabolic Syndrome.¹ Drawing on data from 2 large prospective cohorts, the findings suggest the CHG index may serve as a practical tool for risk stratification across the CKM continuum.

CKM syndrome, a framework introduced by the American Heart Association, captures the interplay between metabolic dysfunction, chronic kidney disease (CKD), and cardiovascular disease (CVD).² Despite growing recognition of its clinical significance, identifying simple, scalable biomarkers to predict disease onset and guide early intervention remains an unmet need. The CHG index, calculated from total cholesterol, HDL cholesterol (HDL-C), and fasting glucose, was hypothesized to reflect this composite metabolic burden. Prior work had linked the index to specific disease states, but its role across the full CKM spectrum had not been established.¹

Analysis Draws on 2 Large Prospective Cohorts

Researchers analyzed data from 370,916 participants in the UK Biobank (UKB) who were free of CKM-related conditions at baseline, with a median follow-up of 16.5 years. Fine-Gray subdistribution hazard models estimated associations between CHG levels and incident type 2 diabetes (T2D), CVD, and CKD, as well as CKM stage progression. A second cohort of 8494 patients with established coronary artery disease (CAD), representing CKM stage IV, was drawn from Beijing Anzhen Hospital with a median follow-up of 645 days. Cox regression assessed risk of major adverse cardiovascular and cerebrovascular events (MACCEs), and a causal forest algorithm identified subgroups with the strongest prognostic signal.

Higher CHG Index Linked to Incident Diabetes, Cardiovascular Disease, and CKD

Among the general population, each 1–standard deviation (SD) increase in the CHG index was associated with significantly elevated risk of incident T2D (HR, 1.47; 95% CI, 1.40-1.53), CVD (HR, 1.07; 95% CI, 1.06-1.09), and CKD (HR, 1.07; 95% CI, 1.04-1.10). The index also predicted stage-wise CKM progression: from stages 0-1 to stages 2-3 (HR, 1.16; 95% CI, 1.11-1.23) and from stages 1-3 to stage 4 (HR, 1.06; 95% CI, 1.05-1.08).

In patients with established CAD, elevated CHG remained independently associated with higher MACCE risk (HR, 1.12; 95% CI, 1.05-1.19). Machine learning analysis identified a high-risk subgroup characterized by low systemic inflammation and elevated hemoglobin A_1C, in whom the prognostic impact was particularly pronounced. Restricted cubic spline analysis confirmed dose-response relationships across all outcomes.

Implications for Risk Stratification and Population Health Management

The findings carry practical implications for managed care. The CHG index integrates 3 routinely collected laboratory values—total cholesterol, HDL-C, and fasting glucose—into a single metric that tracks metabolic risk across disease stages. For payers and health systems managing populations at risk for CKM syndrome, the index could offer an accessible approach to identifying high-risk individuals before they advance to more costly, complex stages of disease.

The study also underscores the value of addressing metabolic risk factors in tandem rather than in silos. By capturing cholesterol and glucose burden simultaneously, the CHG index reflects the biological interplay driving CKM pathogenesis, insulin resistance, oxidative stress, and endothelial dysfunction, rather than treating each as an independent variable.

Study Limitations and Future Applications of the CHG Index

As an observational study, the research cannot establish causality, and the predominantly European ancestry of the UK Biobank may limit generalizability. The Beijing Anzhen cohort, while geographically distinct, also represents a specific high-risk population. Still, the consistency of findings across 2 large, independent cohorts strengthens confidence in the results, according to the authors. As CKM syndrome gains traction as a unified clinical framework, the CHG index offers a practical, low-cost tool for stratifying risk and prioritizing intervention across the full disease spectrum.

References

1. Zhao Z, Bai Y, Ma C, et al. Association of the CHG Index with the onset, progression, and prognosis of cardiovascular-kidney-metabolic syndrome: findings from two large prospective cohorts. Diabetol Metab Syndr. Published online June 6, 2026. doi:10.1186/s13098-026-02192-2
2. Ndumele CE, Neeland IJ, Tuttle KR, et al. A synopsis of the evidence for the science and clinical management of cardiovascular-kidney-metabolic (CKM) syndrome: a scientific statement from the American Heart Association. Circulation. 2023;148(20):1636-1664. doi:10.1161/CIR.0000000000001186