Discordant muscle-adipose phenotypes and insulin resistance in prediabetes: sex-specific associations and predictive utility of TyG-WHtR combined with HDL-C.
Wang Z, Lin C, et al. • Frontiers in endocrinology • 2026
In prediabetes, insulin resistance appears to be driven primarily by visceral adiposity rather than overall obesity, and a nomogram combining TyG-WHtR and HDL-C showed good discrimination (AUC 0.815) and calibration as a potential primary-care screening tool for insulin resistance.
Key Findings
Results
Muscle-adipose composite phenotypes differed significantly in adiposity, insulin, HOMA-IR, HDL-C and TyG-derived indices among 167 people with prediabetes.
167 Pre-DM subjects were classified into four phenotypes (high-muscle/low-fat, high-muscle/high-fat, low-muscle/high-fat, low-muscle/low-fat) by appendicular skeletal muscle index and visceral fat level.
Significant intergroup differences were found for BMI, waist circumference, fasting insulin, HOMA-IR, HDL-C, and TyG-derived indices (all P < 0.05).
Results
Fasting insulin and HOMA-IR correlated positively with adiposity and muscle measures, while triglycerides correlated positively and HDL-C negatively with these metrics.
Spearman correlation: fasting insulin and HOMA-IR were positively correlated with WHtR, waist circumference, BMI, body fat mass, visceral fat level, body fat percentage, and ASMI (all P < 0.01).
Triglycerides were positively and HDL-C negatively correlated with these metrics (all P < 0.05).
Results
TyG-WHtR showed the strongest correlation with HOMA-IR among the indices examined.
The correlation between TyG-WHtR and HOMA-IR had P < 0.001.
Results
The high-muscle/high-fat (HM/HF) phenotype was the strongest independent predictor of HOMA-IR in hierarchical regression.
HM/HF remained significant after full adjustment (B = 3.264, P < 0.001).
The final model accounted for 36.0% of the variance in HOMA-IR.
Results
The protective association of the low-muscle/low-fat (LM/LF) phenotype was attenuated to marginal significance after adjusting for blood lipids.
After lipid adjustment, B = -0.705, P = 0.082.
The authors interpret this as reflecting low visceral fat rather than muscle mass per se.
Results
No statistically significant multiplicative interaction between low muscle mass and high visceral fat was detected.
Interaction P = 0.089.
The authors note the study may be underpowered and additive interaction was not formally assessed, so whether the effects are additive remains inconclusive.
Results
In exploratory stratified analyses, phenotype effects on HOMA-IR differed by sex and age.
The HM/HF effect was larger in men (B = 5.662) and in adults aged <60 years (B = 4.425).
The protective LM/LF effect was restricted to women (B = -0.914).
In the ≥60-year group, the sex coefficient changed from negative to positive without reaching significance; formal interaction testing is needed to confirm age modification.
Results
TyG-WHtR and HDL-C were independent determinants of insulin resistance in logistic regression.
TyG-WHtR OR = 8.231; HDL-C OR = 0.183.
Corresponding Cohen's d values exceeded the conventional large-effect threshold of 0.8.
Results
A nomogram combining TyG-WHtR and HDL-C showed good discrimination and calibration for identifying insulin resistance.
AUC = 0.815 (95% CI 0.748-0.881).
Hosmer-Lemeshow test showed no evidence of departure from perfect calibration; the calibration curve from 1000 bootstrap resamples closely followed the ideal diagonal.
Decision curve analysis showed net benefit greater than 'intervene-all' and 'intervene-none' strategies across threshold probabilities of 0.2-0.8.
Conclusions
The authors conclude that insulin resistance in prediabetes is driven mainly by visceral adiposity rather than overall obesity, and that the metabolic impact of muscle depends on the lipid milieu.
Maintaining moderate muscle mass with low visceral adiposity is suggested to confer greater metabolic benefit.
The nomogram may serve as a practical screening tool in primary care.
What This Means
This study looked at 167 people with prediabetes and grouped them by how much muscle and visceral (belly) fat they had. It then checked how these body types related to insulin resistance, a key step toward type 2 diabetes. People with both high muscle and high visceral fat had the highest insulin resistance. The apparent protective effect of having low muscle and low fat faded after accounting for blood lipids, suggesting that low visceral fat, rather than muscle itself, was doing most of the work.
The researchers also found that men and women, and younger and older adults, may differ in how body composition relates to insulin resistance. These sex- and age-related patterns came from exploratory analyses and were not confirmed by formal tests, and the study was small, so they should be treated cautiously.
The team built a simple prediction tool (a nomogram) using a measure combining triglycerides, glucose and waist-to-height ratio (TyG-WHtR) plus HDL cholesterol. It identified insulin resistance reasonably well (AUC 0.815). This research suggests that such readily available measures could help screen for insulin resistance in primary care, though the tool needs testing in larger and independent groups before wide use.
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Wang Z, Lin C, Xie Y, Huang L, Xiao S, Chen H, et al.. (2026). Discordant muscle-adipose phenotypes and insulin resistance in prediabetes: sex-specific associations and predictive utility of TyG-WHtR combined with HDL-C.. Frontiers in endocrinology. https://doi.org/10.3389/fendo.2026.1937778