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Background <p>Statin therapy reduces cardiovascular risk, but recorded statin exposure is associated with subsequent type 2 diabetes (T2D) in some populations. Individualized risk estimation and separation of low-density lipoprotein cholesterol (LDL-C)-mediated from non-LDL components remain challenging in observational data.</p> Methods <p>We analyzed adults free of diagnosed diabetes and without substantial baseline hyperglycemia in UK Biobank, the <i>All of Us</i> Research Program, and the Abu Dhabi Public Health Center cohort. We used weighted survival and regression analyses, UK Biobank exposure-definition and propensity-score sensitivity analyses, two-stage residual inclusion Mendelian randomization mediation, and CausalT2DNet, a balanced deep counterfactual prediction model.</p> Results <p>Recorded statin exposure was associated with higher incident T2D risk over cohort-specific horizons. UK Biobank matched-method 10-year sensitivity analyses yielded adjusted risk ratios of 2.18–2.25, and a broader baseline-only IPTW sensitivity model yielded a weighted risk ratio of 1.95. In a separate CausalT2DNet 12-year absolute-risk scenario, predicted T2D risk increased from 2.24% under no statin exposure to 4.05% under statin exposure. Mediation and counterfactual analyses suggested that much of the excess risk was not explained by LDL-C lowering, under their respective assumptions.</p> Conclusions <p>Recorded statin exposure was consistently associated with higher incident T2D risk across three longitudinal cohorts. The framework supports assumption-explicit research risk estimation and hypothesis generation and requires external recalibration and prospective validation before clinical use.</p>

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Individualized statin associated type 2 diabetes risk estimation with a deep causal model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月3日

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  • Hao Zhou,
  • Jorge Passamani Zubelli,
  • Haralampos Hatzikirou,
  • Andreas Henschel,
  • Laurent Alain Najman,
  • Daniel E. Platt,
  • Antonello Maruotti,
  • Siobhan O’Sullivan,
  • Lithe Basbous,
  • Cynthia Al Hageh,
  • Mariam Al Harbi,
  • Antoine Abchee,
  • Pierre Zalloua

摘要

Background

Statin therapy reduces cardiovascular risk, but recorded statin exposure is associated with subsequent type 2 diabetes (T2D) in some populations. Individualized risk estimation and separation of low-density lipoprotein cholesterol (LDL-C)-mediated from non-LDL components remain challenging in observational data.

Methods

We analyzed adults free of diagnosed diabetes and without substantial baseline hyperglycemia in UK Biobank, the All of Us Research Program, and the Abu Dhabi Public Health Center cohort. We used weighted survival and regression analyses, UK Biobank exposure-definition and propensity-score sensitivity analyses, two-stage residual inclusion Mendelian randomization mediation, and CausalT2DNet, a balanced deep counterfactual prediction model.

Results

Recorded statin exposure was associated with higher incident T2D risk over cohort-specific horizons. UK Biobank matched-method 10-year sensitivity analyses yielded adjusted risk ratios of 2.18–2.25, and a broader baseline-only IPTW sensitivity model yielded a weighted risk ratio of 1.95. In a separate CausalT2DNet 12-year absolute-risk scenario, predicted T2D risk increased from 2.24% under no statin exposure to 4.05% under statin exposure. Mediation and counterfactual analyses suggested that much of the excess risk was not explained by LDL-C lowering, under their respective assumptions.

Conclusions

Recorded statin exposure was consistently associated with higher incident T2D risk across three longitudinal cohorts. The framework supports assumption-explicit research risk estimation and hypothesis generation and requires external recalibration and prospective validation before clinical use.