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Aims/hypothesis <p>The aim of this study was to facilitate the fine classification of diabetic complications and the prioritisation of drug targets via immune-cell-related gene expression data, distinguishing cell-type-related pleiotropy.</p> Methods <p>We analysed the combined clinical, genetic and immune-related features of diabetic complications, generating distinct clusters. Using 18,611 immune expression quantitative trait loci (eQTL) of 4487 genes, we investigated the causal effects of immune-cell-related gene expression on the risks of type 2 diabetes and its complications through Mendelian randomisation (MR) and colocalisation approaches. We then explored cell-type-related enrichment and specificity, and attenuated the cell-type-related pleiotropy for the top MR findings via multivariable MR methods.</p> Results <p>Clustering analyses identified diabetic neuropathy as a distinct cluster of diabetes complications, with distinct immune-related features. MR and colocalisation analyses revealed the expression of 425 and 123 unique genes associated with type 2 diabetes and its complications, respectively, with external validation performed using single-cell RNA-seq data. We further quantified the impacts of cell-type-related pleiotropy, demonstrating that the percentage of pleiotropic genes increased from 40.0% (classic pleiotropy) to 71.1% (classic and/or cell-type-related pleiotropy). Applying six multivariable MR (MVMR) methods substantially attenuated the cell-type-related pleiotropy for the top findings. Finally, we integrated clinical trial evidence with genetic evidence and prioritised ten immune-related drug targets for diabetic complications.</p> Conclusions/interpretation <p>Our study supports a key role for immune mechanisms in diabetic complications and highlights promising therapeutic targets by distinguishing and minimising the influence of cell-type-related pleiotropy.</p> Graphical Abstract <p></p>

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Integrating immune-cell transcriptomic data with Mendelian randomisation reveals novel causal genes for type 2 diabetes and its complications

  • 期刊论文

  • 发表日期：

    2026年5月12日

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  • Yilan Ding,
  • Haoyu Liu,
  • Lei Jiang,
  • Qian Yang,
  • Shuangyuan Wang,
  • Hong Lin,
  • Mian Li,
  • Zhiyun Zhao,
  • Tiange Wang,
  • Min Xu,
  • Yu Xu,
  • Guang Ning,
  • Weiqing Wang,
  • Yufang Bi,
  • Jie Zheng,
  • Jieli Lu

摘要

Aims/hypothesis

The aim of this study was to facilitate the fine classification of diabetic complications and the prioritisation of drug targets via immune-cell-related gene expression data, distinguishing cell-type-related pleiotropy.

Methods

We analysed the combined clinical, genetic and immune-related features of diabetic complications, generating distinct clusters. Using 18,611 immune expression quantitative trait loci (eQTL) of 4487 genes, we investigated the causal effects of immune-cell-related gene expression on the risks of type 2 diabetes and its complications through Mendelian randomisation (MR) and colocalisation approaches. We then explored cell-type-related enrichment and specificity, and attenuated the cell-type-related pleiotropy for the top MR findings via multivariable MR methods.

Results

Clustering analyses identified diabetic neuropathy as a distinct cluster of diabetes complications, with distinct immune-related features. MR and colocalisation analyses revealed the expression of 425 and 123 unique genes associated with type 2 diabetes and its complications, respectively, with external validation performed using single-cell RNA-seq data. We further quantified the impacts of cell-type-related pleiotropy, demonstrating that the percentage of pleiotropic genes increased from 40.0% (classic pleiotropy) to 71.1% (classic and/or cell-type-related pleiotropy). Applying six multivariable MR (MVMR) methods substantially attenuated the cell-type-related pleiotropy for the top findings. Finally, we integrated clinical trial evidence with genetic evidence and prioritised ten immune-related drug targets for diabetic complications.

Conclusions/interpretation

Our study supports a key role for immune mechanisms in diabetic complications and highlights promising therapeutic targets by distinguishing and minimising the influence of cell-type-related pleiotropy.

Graphical Abstract