BMI-discrepant phenotypes and transitions reveal sex-specific heterogeneity and reshape cardiometabolic risk in Chinese adults

Q: What is the clinical evidence from this study?

Study design: Cohort. Population: Cardiometabolic diseases (Type 2 diabetes, chronic kidney disease, cardiovascular disease) (n=175642). Intervention: BMI-discrepant metabolic phenotypes (specifically High Fasting Glucose [HFG] profile and phenotype transitions) vs. Non-significant feature (NSF) reference profile. Primary outcome: Incident type 2 diabetes (T2D) in women associated with a 20% probability shift toward the high fasting glucose (HFG) profile (HR 2.38, 95% CI 2.03-2.78).

Q: What does this research mean for the field?

A high fasting glucose BMI-discrepant profile elevates type 2 diabetes risk in women and cardiovascular disease risk in men, while reversion of this profile is associated with a 68% reduction in cardiovascular disease risk among women. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

Hong Lin; Jinfeng Wang; Yonghua Yu; Xiaojing Jia; Qiuyu Cao; Hong Qiao; Guijun Qin; Shengli Wu; Shuangyuan Wang; Mian Li; Yuchen Xu; Feiyue Huang; Xingkun Xu; Yu Xu; Min Xu; Tiange Wang; Xulei Tang; Zhen Ye; Ruying Hu; Lixin Shi; Qing Su; Xuefeng Yu; Yan Li; Qin Wan; Gang Chen; Zhengnan Gao; Guixia Wang; Feixia Shen; Xuejiang Gu; 罗佐杰; Yingfen Qin; Li Chen; Xinguo Hou; Qiang Li; Yanan Huo; Yinfei Zhang; Tianshu Zeng; Lulu Chen; Chao Liu; Youmin Wang; Tao Yang; Huacong Deng; Jiajun Zhao; Mu Yiming; Yifang Zhang; Guang Ning; Weiqing Wang; Yufang Bi; Jieli Lu; for the 4C Study Group

doi:10.1186/s12933-026-03425-4

Key result

High fasting glucose BMI-discrepant profile linked to ~2.4-fold higher T2D risk in women.

HR 2.38
95% CI 2.03-2.78
n=175,642

Why the study?

Body mass index alone inadequately captures the heterogeneous cardiometabolic risk associated with obesity.

Do BMI-discrepant biomarker phenotypes and their longitudinal transitions predict sex-specific risks of type 2 diabetes, chronic kidney disease, and cardiovascular disease in Chinese adults?

Key Points

To determine whether biomarker profiles that deviate from expected body mass index (BMI) relationships identify sex-specific cardiometabolic risks and whether longitudinal profile transitions alter future disease outcomes.
Analyzed four Chinese cohorts (N = 175,642; discovery cohort 4C_2011, N = 155,097; replication cohorts CHARLS, XJ_2011, and SN_2009) using linear regression residuals of seven routine biomarkers to identify BMI-independent metabolic phenotypes.
Tracked incident type 2 diabetes (T2D), chronic kidney disease (CKD), cardiovascular disease (CVD), stroke, and myocardial infarction over a median follow-up of 3.8 years.
Evaluated dynamic phenotypic transitions and their associations with subsequent cardiometabolic risk across sexes.
The high fasting glucose (HFG) profile elevated T2D risk in women (HR 2.38, 95% CI 2.03–2.78) while increasing CVD risk in men (HR 1.12, 95% CI 1.05–1.20).
The high triglycerides (HTG) profile increased T2D risk and the high blood pressure (HBP) profile increased CVD risk consistently across both sexes.
In women, phenotype reversions over 3.8 years were associated with reduced risk: HFG reversion was linked to a 68% lower risk of CVD (HR 0.32, 95% CI 0.11–0.90) and HBP reversion to a 50% lower risk of stroke (HR 0.50, 95% CI 0.30–0.86).

Study Design

Type

Cohort (n=175,642)

Multicenter

Yes

Structured PICO

Do BMI-discrepant biomarker phenotypes and their longitudinal transitions predict sex-specific risks of type 2 diabetes, chronic kidney disease, and cardiovascular disease in Chinese adults?

P

Population

175,642 Chinese adults aged 40 years or older across four prospective cohorts (4C_2011, CHARLS, XJ_2011, and SN_2009) evaluated for BMI-biomarker discrepant phenotypes and followed for a median of 9.5 to 13.5 years (3.8 years for longitudinal transition analysis).

E

Exposure

Identification of BMI-discrepant biomarker phenotypic profiles (high blood pressure [HBP], high triglycerides [HTG], high fasting glucose [HFG], high serum creatinine [HSCR], and male-specific high HDL-C [HHDL]) using residual-based clustering of seven routine biomarkers (fasting glucose, HDL-C, LDL-C, triglycerides, SBP, DBP, serum creatinine), and evaluation of longitudinal phenotype transitions over a median of 3.8 years.

C

Comparator

Non-significant feature (NSF) reference profile (characterized by biomarkers within expected age-, sex-, and BMI-predicted ranges), or persistence in a discrepant profile for longitudinal transition analyses.

O

Outcome

Incident type 2 diabetes (T2D), chronic kidney disease (CKD), and composite cardiovascular disease (CVD, comprising non-fatal myocardial infarction, non-fatal stroke, and cardiovascular death, verified by adjudication committee or self-reported physician diagnosis across cohorts) over follow-up (median 3.8 years for transition analysis; cohort medians 9.5 to 13.5 years, truncated at 10 years for nested Cox models).composite

Main Result

Hazard Ratio: 2.38 (95% CI 2.03–2.78)

Routine biomarker deviations from BMI-predicted levels identify distinct, sex-specific metabolic phenotypes and longitudinal transitions that stratify and modify the risk of diabetes, chronic kidney disease, and cardiovascular events beyond BMI alone.

Limitations

Loss to follow-up and exclusions due to incomplete death surveillance coverage or missing event information in the discovery cohort
Self-reported physician diagnosis used for incident T2D, CKD, and non-fatal CVD in the CHARLS validation cohort
Lifestyle factors and circulating metabolites were assessed at the same baseline examination, precluding determination of temporal or causal relationships in mediation analyses
None of the lifestyle-metabolite mediation effects remained statistically significant after false discovery rate (FDR) correction for multiple testing
Inverse associations between phenotype reversion and CVD risk in women lost statistical significance in medication-stratified subgroup analyses

Implication

Sex-specific BMI-discrepant phenotypes may refine risk stratification; hypothesis-generating and requires prospective validation before clinical adoption.

Abstract

Body mass index (BMI) alone inadequately captures the heterogeneous cardiometabolic risk associated with obesity. In four Chinese cohorts( N = 175,642), BMI–biomarker phenotypic profiles were identified using residual-based clustering of seven routine biomarkers, revealing sex-specific metabolic patterns associated with type 2 diabetes(T2D), chronic kidney disease (CKD) and cardiovascular disease (CVD). The high triglycerides (HTG) profile increased T2D risk and the high blood pressure (HBP) profile increased CVD risk across sexes. Showing distinct sex differences, the high fasting glucose (HFG) profile elevated T2D risk in women (hazard ratio [HR] 2.38[2.03–2.78]) while increasing CVD risk in men (HR 1.12, 95% CI 1.05–1.20). During a median follow-up of 3.8 years, certain phenotype transitions were associated with lower subsequent cardiovascular risk in women, with HFG reversion linked to a 68% lower risk of CVD (HR 0.32, 95% CI 0.11–0.90) and HBP reversion to a 50% lower risk of stroke (HR 0.50, 95% CI 0.30–0.86). These findings provide a phenotype-driven framework for characterizing metabolic heterogeneity and exploring temporal changes in cardiometabolic risk.

Discussion

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Cite This Study

Lin et al. (2026) conducted a cohort in Cardiometabolic diseases (Type 2 diabetes, chronic kidney disease, cardiovascular disease) (n=175,642). BMI-discrepant metabolic phenotypes (specifically High Fasting Glucose [HFG] profile and phenotype transitions) vs. Non-significant feature (NSF) reference profile was evaluated on Incident type 2 diabetes (T2D) in women associated with a 20% probability shift toward the high fasting glucose (HFG) profile (HR 2.38, 95% CI 2.03-2.78). The high fasting glucose BMI-discrepant profile elevated T2D risk in women (HR 2.38, 95% CI 2.03-2.78) and CVD risk in men (HR 1.12, 95% CI 1.05-1.20), while reverting to normal reduced female CVD risk by 68%.

synapsesocial.com/papers/6ae584d14c46c197bbab29e0 https://doi.org/10.1186/s12933-026-03425-4

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BMI-discrepant phenotypes and transitions reveal sex-specific heterogeneity and reshape cardiometabolic risk in Chinese adults

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

BMI-discrepant phenotypes and transitions reveal sex-specific heterogeneity and reshape cardiometabolic risk in Chinese adults

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

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