Integration of triglyceride-glucose index and biological aging to predict cardiovascular disease risk in cardiovascular–kidney–metabolic syndrome stages 0–3: a multiple prospective cohort study

Q: What are the key findings of this study?

Participants in the highest quartile of the TyG-KDM-BA index had a nearly 4-fold higher risk of incident cardiovascular disease compared to those in the lowest quartile (HR 3.97) among adults with CKM syndrome stages 0-3.

Q: What is the clinical evidence from this study?

Study design: Cohort. Population: Cardiovascular-kidney-metabolic (CKM) syndrome stages 0-3 (n=294618). Intervention: Elevated triglyceride-glucose index combined with biological age (TyG-KDM-BA) vs. Lowest quartile of TyG-KDM-BA. Primary outcome: New-onset overall cardiovascular disease (composite of coronary heart disease, heart failure, stroke, atrial fibrillation/flutter, and peripheral vascular disease) (HR 3.97, 95% CI 3.86-4.09, p=<0.001).

Q: What does this research mean for the field?

Integrating the triglyceride-glucose index and biological aging into a composite metric (TyG-KDM-BA) predicts cardiovascular disease risk in individuals with cardiovascular-kidney-metabolic syndrome stages 0-3, with the highest quartile conferring substantially higher risk than the lowest. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

Q: What question did this study set out to answer?

To evaluate whether integrating the triglyceride-glucose index and biological aging improves cardiovascular disease risk prediction among individuals with cardiovascular-kidney-metabolic syndrome stages 0–3.

Runnan Shen; Pinrong Dong; 方曙祥; Zirui Jia; Ayiguli Abudukeremu; J W Li; Kai Huang; Xiaoqin Zuo; Ma Yx; Yilin Liu; Kai Huang; Yangxin Chen

doi:10.1186/s12933-026-03192-2

June 16, 2026Cardiovascular DiabetologyOpen Access

Integration of triglyceride-glucose index and biological aging to predict cardiovascular disease risk in cardiovascular–kidney–metabolic syndrome stages 0–3: a multiple prospective cohort study

View Full Paper

Ask AI

Bookmark

Share

Key result

Highest TyG-KDM-BA index is linked to ~4-fold higher incident CVD risk in CKM syndrome.

HR 3.97
95% CI 3.86-4.09
P<0.001
n=294,618

Figures

Why the study?

No study had attempted to integrate metabolic dysfunction and biological aging to improve cardiovascular disease risk prediction in individuals with cardiovascular-kidney-metabolic syndrome stages 0-3.

Key Points

To evaluate whether integrating the triglyceride-glucose index and biological aging improves cardiovascular disease risk prediction among individuals with cardiovascular-kidney-metabolic syndrome stages 0–3.
Prospective cohort design analyzing 286,864 participants from the UK Biobank (median follow-up 15.27 years), 7,237 from the China Health and Retirement Longitudinal Study (CHARLS; median follow-up 7.84 years), and 517 hospital-based participants for external validation.
The TyG-KDM-BA metric was calculated by multiplying the triglyceride-glucose index by the Klemera-Doubal method biological age.
Associations with incident cardiovascular disease (CVD), coronary heart disease (CHD), and stroke were evaluated using Cox proportional hazards models and time-dependent receiver operating characteristic curves.
During follow-up, incident CVD occurred in 57,896 UK Biobank participants (cumulative incidence: 20.18%) and 1,610 CHARLS participants (cumulative incidence: 22.25%).
In fully adjusted models, each 1-SD increase in TyG-KDM-BA was associated with higher CVD risk in UK Biobank (HR = 1.65, 95% CI 1.64–1.67) and CHARLS (HR = 1.25, 95% CI 1.18–1.32).
Participants in the highest quartile had significantly higher CVD risk than those in the lowest quartile in UK Biobank (HR = 3.97, 95% CI 3.86–4.09; AUC 0.657–0.659 over 5–15 years) and CHARLS (HR = 1.92, 95% CI 1.63–2.25).

Study Design

Type

Cohort (n=294,618)

Multicenter

Yes

Structured PICO

P

Population

294,618 adults with cardiovascular-kidney-metabolic syndrome stages 0-3 across three prospective cohorts from the United Kingdom and China, followed for a median of 15.27 years (UKB) to evaluate incident cardiovascular disease.

E

Exposure

Higher TyG-KDM-BA index (product of triglyceride-glucose index and biological aging derived from the Klemera-Doubal method), evaluated continuously per 1-SD increase and by quartiles.

C

Comparator

Lower TyG-KDM-BA index (lowest quartile Q1) or conventional TyG-derived indices.

O

Outcome

New-onset overall cardiovascular disease (CVD), defined as a composite endpoint including coronary heart disease (CHD), heart failure, stroke, atrial fibrillation or atrial flutter, and peripheral vascular disease.composite

Main Result

Hazard Ratio: 3.97 (95% CI 3.86–4.09)

Absolute Event Rate: 31.44% vs 8.59%

p-value: p=<0.001

Integrating the triglyceride-glucose index with biological aging provides superior incremental predictive value for long-term incident cardiovascular disease risk in patients with CKM stages 0-3 compared to conventional TyG-derived indices.

Limitations

Violation of the proportional hazards assumption for the TyG-KDM-BA index in the UKB cohort.
Differences in biomarker availability and covariate structures between the UK Biobank and CHARLS cohorts.
Outcomes in the CHARLS cohort were identified based on self-reported physician diagnoses.
Missing covariate data in the CHARLS cohort necessitated multiple imputation techniques.
Differences in data structure and variable collection across cohorts
Small sample size and differences in population structure of the hospital cohort
Violation of proportional hazards assumption for TyG-KDM-BA in UKB
Missing data for certain indicators in CHARLS requiring different biomarker selection for KDM-BA

Implication

TyG-KDM-BA may refine long-term CVD risk stratification in CKM stages 0-3; extends TyG and aging markers but leaves open prospective validation before practice change.

Abstract

The triglyceride–glucose (TyG) index serves as a surrogate marker of insulin resistance and reflects underlying metabolic dysfunction, while biological aging (KDM-BA) independently contributes to cardiovascular vulnerability. However, no study has attempted to integrate metabolic dysfunction and biological aging to improve cardiovascular disease (CVD) risk prediction in individuals with cardiovascular–kidney–metabolic (CKM) syndrome stages 0–3. Multiple prospective cohorts were used, including 286,864 participants from the UK Biobank (UKB), 7237 from the China Health and Retirement Longitudinal Study (CHARLS), and 517 from Sun Yat-sen Memorial Hospital, Sun Yat-sen University, which were further included for external validation of the primary outcome. TyG-KDM-BA was calculated by multiplying the TyG index by KDM-BA. Cox proportional hazards models were used to evaluate the association. Time-dependent receiver operating characteristic (ROC) curves, as well as analyses of incremental predictive value, sensitivity analyses, and external validation were conducted to evaluate predictive performance. During a median follow-up of 15.27 years in UKB, 57,896 incident CVD events occurred (cumulative incidence: 20.18%). During a median follow-up of 7.84 years in CHARLS cohort, 1,610 incident CVD events were observed (cumulative incidence: 22.25%). CVD risk increased progressively across TyG-KDM-BA quartiles in both cohorts. In the fully adjusted model, each 1-SD increase in TyG-KDM-BA was associated with higher CVD risk in both cohorts (UKB: HR = 1.65, 95% CI 1.64–1.67; CHARLS: HR = 1.25, 95% CI 1.18–1.32). Participants in the highest quartile had significantly higher CVD risk than those in the lowest (UKB: HR = 3.97, 95% CI 3.86–4.09; CHARLS: HR = 1.92, 95% CI 1.63–2.25). TyG-KDM-BA was positively associated with CHD and stroke risk in both cohorts. Compared with conventional TyG-derived indices, TyG-KDM-BA achieved higher discrimination for CVD risk prediction, with an area under the curve of 0.657–0.659 over 5–15 years in UKB and moderate, consistent performance in CHARLS. Incremental analyses demonstrated that TyG-KDM-BA provided additional predictive value beyond conventional models and its individual components. External validation analyses supported the robustness of results. TyG-KDM-BA integrates metabolic and aging dimensions, demonstrating superior predictive ability for CVD risk among individuals with CKM stages 0–3 compared to traditional TyG-derived indicators, and may serve as a more effective tool for the early screening and intervention.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Shen et al. (2026) conducted a cohort in Cardiovascular-kidney-metabolic (CKM) syndrome stages 0-3 (n=294,618). Elevated triglyceride-glucose index combined with biological age (TyG-KDM-BA) vs. Lowest quartile of TyG-KDM-BA was evaluated on New-onset overall cardiovascular disease (composite of coronary heart disease, heart failure, stroke, atrial fibrillation/flutter, and peripheral vascular disease) (HR 3.97, 95% CI 3.86-4.09, p=<0.001). Participants in the highest quartile of the TyG-KDM-BA index had a nearly 4-fold higher risk of incident cardiovascular disease compared to those in the lowest quartile (HR 3.97) among adults with CKM syndrome stages 0-3.

synapsesocial.com/papers/6a32623f8b0a6d04ea8e69fb https://doi.org/10.1186/s12933-026-03192-2

View Full Paper

Ask AI

Bookmark

Share

Integration of triglyceride-glucose index and biological aging to predict cardiovascular disease risk in cardiovascular–kidney–metabolic syndrome stages 0–3: a multiple prospective cohort study

Figures

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

Integration of triglyceride-glucose index and biological aging to predict cardiovascular disease risk in cardiovascular–kidney–metabolic syndrome stages 0–3: a multiple prospective cohort study

Figures

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

Keep reading

More related papers

More from Cardiovascular Diabetology

Keep reading

More related papers

More from Cardiovascular Diabetology