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Background <p>Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health burden linked to insulin resistance and atherogenic dyslipidemia, estimated by the glucose disposal rate (eGDR) and atherogenic index of plasma (AIP), respectively. However, the nature of their&#xa0;combined association—whether additive or interactive—with MASLD risk, and its utility for risk stratification, remains unexplored.</p> Methods <p>In this large-scale cross-sectional analysis of 30,143 adults, we calculated eGDR and AIP from routine clinical measures. Their independent and joint associations with ultrasonography-defined MASLD were assessed using multivariable logistic regression, restricted cubic splines (RCS), and interaction analysis. Based on RCS-derived thresholds, participants were categorized into four metabolic phenotypes for combined risk assessment.</p> Results <p>Both lower eGDR and higher AIP were independently and nonlinearly associated with greater MASLD risk (p for trend &lt; 0.001). A significant interaction was observed (p &lt; 0.001), revealing a&#xa0;convergent pattern: the protective association of high eGDR appeared attenuated as AIP increased, and the risk disparity attributable to AIP narrowed markedly at low eGDR levels. Participants with the combined low-eGDR/high-AIP phenotype had the highest MASLD odds (OR = 3.42, 95% CI 3.07–3.81). These findings were robust to alternative adjustment strategies and phenotype definitions in sensitivity analyses.</p> Conclusions <p>eGDR and AIP exhibit a significant&#xa0;interactive association&#xa0;with MASLD risk, characterized by a&#xa0;convergent pattern: the incremental risk associated with atherogenic dyslipidemia (high AIP) appeared less pronounced under conditions of severe insulin resistance (low eGDR). Integrating these two metrics identifies a distinct high-risk phenotype and may inform future risk stratification strategies. Longitudinal studies are needed to establish causality and clinical utility.</p>

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Converging pathways: the interaction between estimated glucose disposal rate and atherogenic index of plasma in MASLD risk stratification

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月25日

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  • Mingxing Chang,
  • Peipu Shen,
  • Guifang Shen

摘要

Background

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health burden linked to insulin resistance and atherogenic dyslipidemia, estimated by the glucose disposal rate (eGDR) and atherogenic index of plasma (AIP), respectively. However, the nature of their combined association—whether additive or interactive—with MASLD risk, and its utility for risk stratification, remains unexplored.

Methods

In this large-scale cross-sectional analysis of 30,143 adults, we calculated eGDR and AIP from routine clinical measures. Their independent and joint associations with ultrasonography-defined MASLD were assessed using multivariable logistic regression, restricted cubic splines (RCS), and interaction analysis. Based on RCS-derived thresholds, participants were categorized into four metabolic phenotypes for combined risk assessment.

Results

Both lower eGDR and higher AIP were independently and nonlinearly associated with greater MASLD risk (p for trend < 0.001). A significant interaction was observed (p < 0.001), revealing a convergent pattern: the protective association of high eGDR appeared attenuated as AIP increased, and the risk disparity attributable to AIP narrowed markedly at low eGDR levels. Participants with the combined low-eGDR/high-AIP phenotype had the highest MASLD odds (OR = 3.42, 95% CI 3.07–3.81). These findings were robust to alternative adjustment strategies and phenotype definitions in sensitivity analyses.

Conclusions

eGDR and AIP exhibit a significant interactive association with MASLD risk, characterized by a convergent pattern: the incremental risk associated with atherogenic dyslipidemia (high AIP) appeared less pronounced under conditions of severe insulin resistance (low eGDR). Integrating these two metrics identifies a distinct high-risk phenotype and may inform future risk stratification strategies. Longitudinal studies are needed to establish causality and clinical utility.