已发表论文

嗜碱性粒细胞计数与妊娠期糖尿病风险的两样本孟德尔随机化研究

 

Authors Mao J, Gan Y, Tan X, He Y, Jing Q, Shi Q

Received 12 October 2024

Accepted for publication 22 January 2025

Published 26 February 2025 Volume 2025:17 Pages 517—527

DOI https://doi.org/10.2147/IJWH.S500632

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Vinay Kumar

Jing Mao,* Yanqiong Gan,* Xinlin Tan, Yuhan He, Qiao Jing, Qi Shi

Affiliated Hospital of North Sichuan Medical College, Nanchong, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Qi Shi, Affiliated Hospital of North Sichuan Medical College, No. 1, Maoyuan South Road, Shunqing District, Nanchong, Sichuan, People’s Republic of China, Tel +8615983789947, Email shiqistone@163.com

Objective: High basophil count levels are associated with an increased risk of gestational diabetes mellitus (GDM). We used two-sample Mendelian randomisation (MR) to explore a potential causal relationship. It also aims to offer genetic evidence supporting the link between basophil count and the development of gestational diabetes mellitus while addressing the potential issues of confounding and reverse causality commonly encountered in observational studies.
Methods: We utilized publically accessible summary information obtained from genome-wide association studies (GWAS) for conducting a two-sample Mendelian randomization (TSMR) study. The major analysis method employed was inverse variance weighted (IVW), whereas the other four methods, namely weighted median method, MR-Egger regression, simple model and weighted model, were used as supplemental analyses. We also investigated the relationship between GDM and basophil count in the opposite direction using directional validation of MR analysis. Furthermore, the R package “ClusterProfiler” to conduct an analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) terms was used. Additionally, with the help of the STRING database, we have constructed a network of protein–protein interactions (PPIs).
Results: The Inverse Variance Weighted (IVW) method revealed a significant causal association between basophil count and gestational diabetes mellitus (OR, 0.84; 95% CI; 0.74– 0.96; P, 0.01). A sensitivity analysis was performed to assess the reliability of the results, indicating no indication of pleiotropy or heterogeneity, hence strengthening the validity of the findings. The reverse causation of GDM predisposition on basophil counts was not supported by the results of the directional validation of the MR analysis.
Conclusion: The results of this study showed a causal relationship between high basophil counts and increased risk of GDM but did not support a causal relationship between genetic susceptibility to GDM and basophil counts.

Keywords: basophil count, gestational diabetes mellitus, GDM, Mendelian randomization