Integrating immune-cell transcriptomic data with Mendelian randomisation reveals novel causal genes for type 2 diabetes and its complications.
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.
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.
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.
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.
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.
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.
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.
Authors
Ding Ding, Liu Liu, Jiang Jiang, Yang Yang, Wang Wang, Lin Lin, Li Li, Zhao Zhao, Wang Wang, Xu Xu, Xu Xu, Ning Ning, Wang Wang, Bi Bi, Zheng Zheng, Lu Lu
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