ArticleNaunyn-Schmiedeberg's archives of pharmacology2026
Genetic insights into therapeutic targets for gestational diabetes mellitus: a multi-omics analysis.
Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy associated with adverse maternal and fetal outcomes, highlighting the urgent need for novel, genetically supported drug targets due to suboptimal glycemic control and safety concerns with existing therapies. This study integrated cis-expression quantitative trait loci (cis-eQTL) of druggable genes with genome-wide association data to identify putative causal genes for GDM through two-sample Mendelian randomization (MR), with significant associations further validated using multi-tissue summary data-based Mendelian randomization (SMR), colocalization analysis, cis-protein quantitative trait loci (cis-pQTL) MR, and single-cell RNA sequencing (scRNA-seq) to confirm tissue- and cell type specific expression. MR analysis identified 15 genes significantly associated with GDM risk after Bonferroni correction, with SMR and colocalization analyses confirming robust associations for five key genes: higher expression of NRBP1, LPL, and BTN3A2 was causally linked to reduced GDM risk, while elevated GSTM1 and GRINA levels were associated with increased risk. ScRNA-seq revealed distinct expression patterns in placental cell types, with NRBP1 and GRINA highly expressed in trophoblasts and certain immune cell populations. Phenome-wide association studies revealed no significant pleiotropic effects, and pharmacological drug-target databases identified several compounds with potential regulatory interactions. This multi-omics study successfully identifies several genetically supported, druggable targets for GDM, providing a robust foundation for developing mechanism-based therapeutics and precision prevention strategies in pregnancy metabolism.
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