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已发表论文
探讨妊娠期糖尿病中的内质网应激：基于孟德尔随机化的多组学见解
Authors Wang Y, Li J, Wang Y, Guo Y
Received 9 June 2025
Accepted for publication 3 February 2026
Published 10 February 2026 Volume 2026:18 545706
DOI https://doi.org/10.2147/IJWH.S545706
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Matteo Frigerio
Ying Wang, Junfeng Li, Yan Wang, Yingxue Guo
Department of Clinical Laboratory, The Second Hospital of Jilin University, Changchun, 130041, People’s Republic of China
Correspondence: Yingxue Guo, Department of Clinical Laboratory, The Second Hospital of Jilin University, Changchun, 130041, People’s Republic of China, Tel +8613504489434, Email guoyingxue@jlu.edu.cn
Objective: Recent studies suggest a correlation between endoplasmic reticulum (ER) stress and gestational diabetes mellitus (GDM). Nevertheless, the potential causal role of ER stress-related genes remains largely unexplored. This study aims to generate hypotheses regarding these connections through an integrative analysis of multiomics data.
Methods: We utilized an exploratory list of genes related to ER stress and integrated quantitative trait loci (QTL) for gene expression (eQTLs), DNA methylation (mQTLs), and protein levels (pQTLs). Genome-wide association studies (GWAS) summary statistics for GDM were obtained from the publicly accessible FinnGen database, with replication attempted using data from the GWAS Catalog. The summary-data-based Mendelian Randomization (SMR) method was applied to explore the genetic ties between these genes and GDM, followed by colocalization analysis to pinpoint overlapping causal genetic variants. Placental endothelial transcriptome data (GSE103552) were used for validation.
Results: The SMR and colocalization identified potential causal links for 27 mQTLs, 8 eQTLs, and 4 pQTLs with GDM risk. Integration of evidence across mQTL and eQTL levels suggested potential causal roles for the NUP133, VHL, TAPBP, and GPX1 genes in GDM. Notably, NUP133 shows suggestive colocalization evidence at the eQTL level. Analysis relating methylation to expression suggested hypermethylation at the CpG site cg17439967 may upregulate NUP133, potentially associating with reduced GDM risk. Transcriptomic validation in placental endothelial cells further showed differential expression of these four genes between GDM and controls.
Conclusion: Our findings provide suggestive genetic evidence linking specific ER stress-related genes, particularly NUP133, with GDM risk, highlighting potential pathways that warrant further investigation.
Keywords: diabetes mellitus, gestational, endoplasmic reticulum stress, multiomics, Mendelian randomization analysis, quantitative trait loci, genetic linkage
Department of Clinical Laboratory, The Second Hospital of Jilin University, Changchun, 130041, People’s Republic of China
Correspondence: Yingxue Guo, Department of Clinical Laboratory, The Second Hospital of Jilin University, Changchun, 130041, People’s Republic of China, Tel +8613504489434, Email guoyingxue@jlu.edu.cn
Objective: Recent studies suggest a correlation between endoplasmic reticulum (ER) stress and gestational diabetes mellitus (GDM). Nevertheless, the potential causal role of ER stress-related genes remains largely unexplored. This study aims to generate hypotheses regarding these connections through an integrative analysis of multiomics data.
Methods: We utilized an exploratory list of genes related to ER stress and integrated quantitative trait loci (QTL) for gene expression (eQTLs), DNA methylation (mQTLs), and protein levels (pQTLs). Genome-wide association studies (GWAS) summary statistics for GDM were obtained from the publicly accessible FinnGen database, with replication attempted using data from the GWAS Catalog. The summary-data-based Mendelian Randomization (SMR) method was applied to explore the genetic ties between these genes and GDM, followed by colocalization analysis to pinpoint overlapping causal genetic variants. Placental endothelial transcriptome data (GSE103552) were used for validation.
Results: The SMR and colocalization identified potential causal links for 27 mQTLs, 8 eQTLs, and 4 pQTLs with GDM risk. Integration of evidence across mQTL and eQTL levels suggested potential causal roles for the NUP133, VHL, TAPBP, and GPX1 genes in GDM. Notably, NUP133 shows suggestive colocalization evidence at the eQTL level. Analysis relating methylation to expression suggested hypermethylation at the CpG site cg17439967 may upregulate NUP133, potentially associating with reduced GDM risk. Transcriptomic validation in placental endothelial cells further showed differential expression of these four genes between GDM and controls.
Conclusion: Our findings provide suggestive genetic evidence linking specific ER stress-related genes, particularly NUP133, with GDM risk, highlighting potential pathways that warrant further investigation.
Keywords: diabetes mellitus, gestational, endoplasmic reticulum stress, multiomics, Mendelian randomization analysis, quantitative trait loci, genetic linkage